Miracle-dz/UniFAR-FTUs huggingface dataset:
Dental eruption sequence and hypsodonty index of a Pleistocene macraucheniid from the Brazilian Intertropical Region

Abstract. Litopterna is represented in the Pleistocene of the Brazilian Intertropical Region by a monospecific genus of Macraucheniidae, Xenorhinotherium. Although most of the knowledge about this family is derived from the dentition, some dental features still remain unknown. This study describes the eruption sequence of permanent dentition and classifies the hypsodonty status of X. bahiense. The specimens studied are from Toca dos Ossos, a limestone cave located in Bahia State. We perform qualitative macroscopic analysis to describe the eruption dental sequence. Additionally, we perform quantitative analysis to determine the hypsodonty index. The dental eruption sequence of the juvenile specimen is M1, M2, I1, I2, M3, I3, P1, P2, P3, and P4. In addition, the analysis of tooth wear in adult specimens provides similar results. The hypsodonty index assigns a mesodont tooth crown for X. bahiense. The dental eruption sequence is most similar to a rapid-growth extant mammal. Moreover, our results do not support afrotherian-like delayed dental eruption to Litopterna. The hypsodonty index can be related to data on vegetation of the Brazilian Intertropical Region and the shape of the premaxilla of X. bahiense, both of which suggest a browsing diet for this macraucheniid.
Rotation and direction judgment from visual images head-slaved in two and three degrees-of-freedom

The contribution to spatial awareness of adding a roll degree-of-freedom (DOF) to telepresence camera platform yaw and pitch was examined in an experiment where subjects judged direction and rotation of stationary target markers in a remote scene. Subjects viewed the scene via head-slaved camera images in a head-mounted display. Elimination of the roll DOF affected rotation judgment, but only at extreme yaw and pitch combinations, and did not affect azimuth and elevation judgement. Systematic azimuth overshoot occurred regardless of roll condition. Observed rotation misjudgments are explained by kinematic models for eye-head direction of gaze.
Study of Some Haematological Parameters for Children Infected With Visceral Leishmaniasis

The present study was carried out on 50 patients infected with suspected visceral leishmaniasis showed that the infection in male's population was more than female's population. Also, the study showed high percentage of disease was in patients with visceral leishmaniasis infection at age group 1 year to 3.11 months, when compared with other age group. And this study showed the rate of prevalence in January and February months compared with other months. Also this study indicated a decrease in hemoglobin ratio and white blood cells counts in patients which infected with visceral leishmaniasis, compared with other groups. The data in this study showed decrease in packed cell volume in patients whose infected with this disease, compared with other groups, while the monocytes should increase within normal range. Finally the present study showed the significant correlation between white blood cells and hemoglobin concentration.
Simulation run lengths to estimate blocking probabilities

We derive formulas approximating the asymptotic variance of four estimators for steady-state blocking probability in a multiserver loss system, exploiting diffusion process limits. These formulas can be used to predict simulation run lengths required to obtain desired statistical precision before the simulation has been run, which can aid in the design of simulation experiments. They also indicate that one estimator can be much better than another, depending on the loading. An indirect estimator based on estimating the mean occupancy is significantly more (less) efficient than a direct estimator for heavy (light) loads. A major concern is the way computational effort scales with system size. For all the estimators, the asymptotic variance tends to be inversely proportional to the system size, so that the computational effort (regarded as proportional to the product of the asymptotic variance and the arrival rate) does not grow as system size increases. Indeed, holding the blocking probability fixed, the computational effort with a good estimator decreases to zero as the system size increases. The asymptotic variance formulas also reveal the impact of the arrival-process and service-time variability on the statistical precision. We validate these formulas by comparing them to exact numerical results for the special case of the classical Erlang M/M/s/0 model and simulation estimates for more general G/GI/s/0 models. It is natural to delete an initial portion of the simulation run to allow the system to approach steady state when it starts out empty. For small to moderately size systems, the time to approach steady state tends to be negligible compared to the time required to obtain good estimates in steady state. However, as the system size increases, the time to approach steady state remains approximately unchanged, or even increases slightly, so that the computational effort associated with letting the system approach steady state becomes a greater portion of the overall computational effort as system size increases.
Pharmacological importance, characterization and applications of gold and silver nanoparticles synthesized by Panax ginseng fresh leaves

Abstract Previously, we showed the rapid and eco-friendly synthesis of gold and silver nanoparticles within 3 and 45 min by fresh leaves extract of herbal medicinal plant Panax ginseng. In addition, we characterized the nanoparticles in terms of shape, size, morphology and stability by FE-TEM, EDX, elemental mapping, SEAD, XRD and particles size analysis. In addition of this, we showed their antimicrobial, anti-coagulant, and biofilm inhibition activity of nanoparticles. Continuing our previous study, here we highlight the further characterization and biomedical applications of P. ginseng leaf-mediated gold and silver nanoparticles. We characterized the nanoparticles further in terms of active functional group and capping layer, surface charge, and temperature stability. Based on these factors, we explored the nanoparticles for antioxidant efficacy, biocompatibility in HaCaT cells, 3T3-L1 pre-adipocytes cells, for anticancer efficacy in A549 lung cancer and B16BL6 skin melenoma cancer cell lines and for anti-inflammation efficacy in RAW 264.7 cell lines. Based on our findings, we suggest that the P. ginseng-mediated gold nanoparticles have high antioxidant activity and highly biocompatibility in HaCaT cells, 3T3-L1 pre-adipocytes cells, RAW 264.7 cells lines and could be considered for future drug delivery carriers. The silver nanoparticles also showed high potent antioxidant efficacy, additionally it showed high anticancer effect in A549 lung cancer and B16BL6 skin melenoma cancer cell lines as compared to precursor salts. Moreover, both gold and silver nanoparticles have anti-inflammatory efficacies in RAW 264.7 cells. Thus, the study may provide useful insights of P. ginseng leaves extract-mediated biocompatible gold and silver nanoparticles and improving their applicability in designing nanoparticles carrier systems for drug delivery applications.
Comparative recruitment, morphology and reproduction of a generalist trematode, Dicrocoelium dendriticum, in three species of host

SUMMARY Epidemiological rate parameters of host generalist parasites are difficult to estimate, especially in cases where variation in parasite performance can be attributed to host species. Such cases are likely common for generalist parasites of sympatric grazing mammals. In this study, we combined data from experimental exposures in cattle and sheep and natural infections in elk to compare the recruitment, morphology and reproduction of adult Dicrocoelium dendriticum, a generalist trematode that has emerged in sympatric grazing hosts in Cypress Hills Provincial Park, Alberta. Overall, there were no significant differences in the recruitment of metacercariae and in the pre-patency period of adults in experimentally exposed cattle and sheep. All flukes reached reproductive maturity and the degree of reproductive inequality between individual flukes within each infrapopulation was moderate and approximately equal among the three host species. Neither fluke size nor per capita fecundity was constrained by density dependence. Thus, fitness parameters associated with growth and reproduction were approximately equivalent among at least three species of definitive host, two of which are sympatric on pastures in this Park. The generalist life-history strategy of this trematode, which is known to extend to other stages of its life cycle, has likely contributed to its invasion history outside its native range in Europe.
Predictors of Depression after Stroke: A Systematic Review of Observational Studies

Background and Purpose— Although depression is common after stroke, there is uncertainty over its etiology and risk factors, which complicates management. Knowledge of the predictors of depression associated with stroke may allow for the better targeting of therapy, both prevention and treatment. Methods— We undertook a systematic review of all published, nonexperimental, population-, hospital-, and rehabilitation-based stroke studies (to June 2004) with prospective, consecutive patient recruitment undertaken to identify variables associated with depressive symptoms (or “illness”) after stroke. Assessments were made of the quality of studies including the validity of prognostic models. Results— Data were available from 3 population-based studies including 492 patients, 8 hospital-based studies including 15 272 patients, and 9 rehabilitation-based studies including 2170 patients. Physical disability, stroke severity and cognitive impairment were consistently associated with depression. In addition to the common problem of selection bias, major limitations of these studies included variable selection and poor statistical quality and reporting; small sample sizes meant that only a limited range of variables were analyzed in multivariate models. Conclusions— There is a paucity of well-designed studies of sufficient size to allow stable multivariate predictive models of depression after stroke to be developed. Other than showing that depression is associated with more severe strokes, current evidence does not allow for ready identification of patients most at risk of developing this important complication of stroke.
Novel Methods for Multidimensional Image Segmentation

Artificial vision is the problem of creating systems capable of processing visual information. A fundamental sub-problem of artificial vision is image segmentation, the problem of detecting a structure from a digital image. Examples of segmentation problems include the detection of a road from an aerial photograph or the determination of the boundaries of the brain's ventricles from medical imagery. The extraction of structures allows for subsequent higher-level cognitive tasks. One of them is shape comparison. For example, if the brain ventricles of a patient are segmented, can their shapes be used for diagnosis? That is to say, do the shapes of the extracted ventricles resemble more those of healthy patients or those of patients suffering from schizophrenia? This thesis deals with the problem of image segmentation and shape comparison in the mathematical framework of partial differential equations. The contribution of this thesis is threefold: (1) A technique for the segmentation of regions is proposed. A cost functional is defined for regions based on a non-parametric functional of the distribution of image intensities inside the region. This cost is constructed to favor regions that are homogeneous. Regions that are optimal with respect to that cost can be determined with limited user interaction. (2) The use of direction information is introduced for the segmentation of open curves and closed surfaces. A cost functional is defined for structures (curves or surfaces) by integrating a local, direction-dependent pattern detector along the structure. Optimal structures, corresponding to the best match with the pattern detector, can be determined using efficient algorithms. (3) A technique for shape comparison based on the Laplace equation is proposed. Given two surfaces, one-to-one correspondences are determined that allow for the characterization of local and global similarity measures. The local differences among shapes can be visualized for qualitative evaluation by a human expert. It can also be used for classifying shapes.
Inside-Outside Reestimation From Partially Bracketed Corpora

The inside-outside algorithm for inferring the parameters of a stochastic context-free grammar is extended to take advantage of constituent information in a partially parsed corpus. Experiments on formal and natural language parsed corpora show that the new algorithm can achieve faster convergence and better modelling of hierarchical structure than the original one. In particular, over 90% of the constituents in the most likely analyses of a test set are compatible with test set constituents for a grammar trained on a corpus of 700 hand-parsed part-of-speech strings for ATIS sentences.
Mammalian DET1 Regulates Cul4A Activity and Forms Stable Complexes with E2 Ubiquitin-Conjugating Enzymes

ABSTRACT DET1 (de-etiolated 1) is an essential negative regulator of plant light responses, and it is a component of the Arabidopsis thaliana CDD complex containing DDB1 and COP10 ubiquitin E2 variant. Human DET1 has recently been isolated as one of the DDB1- and Cul4A-associated factors, along with an array of WD40-containing substrate receptors of the Cul4A-DDB1 ubiquitin ligase. However, DET1 differs from conventional substrate receptors of cullin E3 ligases in both biochemical behavior and activity. Here we report that mammalian DET1 forms stable DDD-E2 complexes, consisting of DDB1, DDA1 (DET1, DDB1 associated 1), and a member of the UBE2E group of canonical ubiquitin-conjugating enzymes. DDD-E2 complexes interact with multiple ubiquitin E3 ligases. We show that the E2 component cannot maintain the ubiquitin thioester linkage once bound to the DDD core, rendering mammalian DDD-E2 equivalent to the Arabidopsis CDD complex. While free UBE2E-3 is active and able to enhance UbcH5/Cul4A activity, the DDD core specifically inhibits Cul4A-dependent polyubiquitin chain assembly in vitro. Overexpression of DET1 inhibits UV-induced CDT1 degradation in cultured cells. These findings demonstrate that the conserved DET1 complex modulates Cul4A functions by a novel mechanism.
ECOD: An Evolutionary Classification of Protein Domains

Understanding the evolution of a protein, including both close and distant relationships, often reveals insight into its structure and function. Fast and easy access to such up-to-date information facilitates research. We have developed a hierarchical evolutionary classification of all proteins with experimentally determined spatial structures, and presented it as an interactive and updatable online database. ECOD (Evolutionary Classification of protein Domains) is distinct from other structural classifications in that it groups domains primarily by evolutionary relationships (homology), rather than topology (or “fold”). This distinction highlights cases of homology between domains of differing topology to aid in understanding of protein structure evolution. ECOD uniquely emphasizes distantly related homologs that are difficult to detect, and thus catalogs the largest number of evolutionary links among structural domain classifications. Placing distant homologs together underscores the ancestral similarities of these proteins and draws attention to the most important regions of sequence and structure, as well as conserved functional sites. ECOD also recognizes closer sequence-based relationships between protein domains. Currently, approximately 100,000 protein structures are classified in ECOD into 9,000 sequence families clustered into close to 2,000 evolutionary groups. The classification is assisted by an automated pipeline that quickly and consistently classifies weekly releases of PDB structures and allows for continual updates. This synchronization with PDB uniquely distinguishes ECOD among all protein classifications. Finally, we present several case studies of homologous proteins not recorded in other classifications, illustrating the potential of how ECOD can be used to further biological and evolutionary studies.
IKP and friends

There has been increasing interest in intuitionistic methods over the years. Still, there has been relatively little work on intuitionistic set theory, and most of that has been on intuitionistic ZF. This investigation is about intuitionistic admissibility and theories of similar strength. There are several more particular goals for this paper. One is just to get some more Kripke models of various set theories out there. Those papers that have dealt with IZF usually were more proof-theoretic in nature, and did not provide models. Furthermore, the inspirations for many of the constructions here are classical forcing arguments. Although the correspondence between the forcing and the Kripke constructions is not made tight, the relationship between these two methods is of interest (see [6] for instance) and some examples, even if only suggestive, should help us better understand the relationship between forcing and Kripke constructions. Along different lines, the subject of least and greatest fixed points of inductive definitions, while of interest to computer scientists, has yet to be studied constructively, and probably holds some surprises. Admissibility is of course the proper set-theoretic context for this study. Finally, while most of the classical material referred to here has long been standard, some of it has not been well codified and may even be unknown, so along the way we'll even fill in a gap in the classical literature. The next section develops the basics of IKP, including some remarks on fixed points of inductive definitions.
A High-Throughput and Low-Latency Parallelization of Window-Based Stream Joins on Multicores

Data Stream Processing (DaSP) is a paradigm characterized by on-line (often real-time) applications working on unlimited data streams whose elements must be processed efficiently "on the fly". DaSP computations are characterized by data-flow graphs of operators connected via streams and working on the received elements according to high throughput and low latency requirements. To achieve these constraints, high-performance DaSP operators requires advanced parallelism models, as well related design and implementation techniques targeting multi-core architectures. In this paper we focus on the parallelization of the window-based stream join, an important operator that raises challenging issues in terms of parallel windows management. We review the state-of-the-art solutions about the stream join parallelization and we propose our novel parallel strategy and its implementation on multicores. As demonstrated by experimental results, our parallel solution introduces two important advantages with respect to the existing solutions: (i) it features an high-degree of configurability in order to address the symmetricity/asymmetricity of input streams (in terms of their arrival rate and window length), (ii) our parallelization provides a high throughput and it is definitely better than the compared solutions in terms of latency, providing an efficient way to perform stream joins on latency-sensible applications.
Detecting flow events in turbulent flow of vertical-slot fish passes

According to earlier research, one key features determining the influence of turbulence on fish swimming behavior is the short-term predictability of turbulence that, in this study, is interpreted as the existence of turbulent flow events in the flow field whose occurrences are predictable. Here, the fundamental assumption is that repeating sequences of flow events are the basis for predictability, because repetition facilitates their recognition by experience on the fish’ part and, therefore, flow events occurring later in time within the repeating sequences are considered predictable. This thesis presents a flow-analysis methodology for detecting repeating sequences of large-scale turbulent flow events and their occurrences in the flow. Here, the term flow event refers to changes in the flow field associated with the appearance of turbulent flow structures or with their change of position, while the term occurrence denotes instances of times at which the particular flow event happens. The presented methodology is applied in this work to a Particle Image Velocimetry measurement performed in the scale model of a vertical-slot fish pass and uses Proper Orthogonal Decomposition (POD) in a novel way. First, large-scale repeating flow events represented by POD modes are identified, then, the sequence of their occurrences is detected from the time series of the POD coefficients. This methodology has also a potential to be applied to sparse point-measurement techniques that are suited for fish-behavior experiments in full-scale facilities.
Reverse engineering socialbot infiltration strategies in Twitter

Online Social Networks (OSNs) such as Twitter and Facebook have become a significant testing ground for Artificial Intelligence developers who build programs, known as socialbots, that imitate actual users by automating their social-network activities such as forming social links and posting content. Particularly, Twitter users have shown difficulties in distinguishing these socialbots from the human users in their social graphs. Frequently, legitimate users engage in conversations with socialbots. More impressively, socialbots are effective in acquiring human users as followers and exercising influence within them. While the success of socialbots is certainly a remarkable achievement for AI practitioners, their proliferation in the Twitter-sphere opens many possibilities for cybercrime. The proliferation of socialbots in the Twitter-sphere motivates us to assess the characteristics or strategies that make socialbots most likely to succeed. In this direction, we created 120 socialbot accounts in Twitter, which have a profile, follow other users, and generate tweets either by reposting messages that others have posted or by creating their own synthetic tweets. Then, we employ a 2k factorial design experiment in order to quantify the infiltration effectiveness of different socialbot strategies. Our analysis is the first of a kind, and reveals what strategies make socialbots successful in the Twitter-sphere.
Sequence Analysis With the Kestrel SIMD Parallel Processor

Computer aided sequence analysis is a critical aspect of current biological research. Sequence information from the genome sequencing projects fills databases so quickly that humans cannot examine it all. Hence there is a heavy reliance on computer algorithms to point out the few important nuggets for human examination. Sequence search algorithms range from simple to complex, as does the representation of the biological data. Typically though, simple algorithms are used on the simplest of data representations because of the large computational demands of anything more complex. This leads to missed hits because the simple search techniques are often not sufficiently sensitive. Here we describe the implementation of several sensitive sequence analysis algorithms on the Kestrel parallel processor, a single-instruction multiple-data (SIMD) processor developed and built at UCSC. Performance of the Smith-Waterman and Hidden Markov Model algorithms, with both Viterbi and Expectation Maximization methods ranges from 6 to 20 times faster than standard computers.