Miracle-dz/UniFAR-FTUs huggingface dataset:
An Efficient Independence Sampler for Updating Branches in Bayesian Markov chain Monte Carlo Sampling of Phylogenetic Trees

Sampling tree space is the most challenging aspect of Bayesian phylogenetic inference. The sheer number of alternative topologies is problematic by itself. In addition, the complex dependency between branch lengths and topology increases the difficulty of moving efficiently among topologies. Current tree proposals are fast but sample new trees using primitive transformations or re-mappings of old branch lengths. This reduces acceptance rates and presumably slows down convergence and mixing. Here, we explore branch proposals that do not rely on old branch lengths but instead are based on approximations of the conditional posterior. Using a diverse set of empirical data sets, we show that most conditional branch posteriors can be accurately approximated via a Γ distribution. We empirically determine the relationship between the logarithmic conditional posterior density, its derivatives, and the characteristics of the branch posterior. We use these relationships to derive an independence sampler for proposing branches with an acceptance ratio of ∼90% on most data sets. This proposal samples branches between 2× and 3× more efficiently than traditional proposals with respect to the effective sample size per unit of runtime. We also compare the performance of standard topology proposals with hybrid proposals that use the new independence sampler to update those branches that are most affected by the topological change. Our results show that hybrid proposals can sometimes noticeably decrease the number of generations necessary for topological convergence. Inconsistent performance gains indicate that branch updates are not the limiting factor in improving topological convergence for the currently employed set of proposals. However, our independence sampler might be essential for the construction of novel tree proposals that apply more radical topology changes.
Effects of Moderate Salt Restriction on Intralymphocytic Sodium and Pressor Response to Stress in Borderline Hypertension

The effects of a moderate dietary salt restriction on intralymphocytic sodium content and pressor response to stress (mental arithmetic, handgrip, and bicycle exercise) were tested in 25 young subjects with borderline hypertension. The study was performed by a randomized, cross-over, within-patient, experimental design. Diet did not significantly reduce blood pressure at rest but did so significantly in both systolic and diastolic blood pressure during stress and exercise. Variations in diastolic blood pressure induced by stimulation correlated significantly with intralymphocytic sodium content both before and during low-salt diet whereas no correlation was found in the case of systolic blood pressure and heart rate variations. These findings suggest that in young subjects with borderline hypertension, sodium homeostasis and blood pressure regulation are somehow interrelated, and that a moderate dietary salt restriction reduces both intralymphocytic sodium content and pressor response to adrenergic stimulation. This could be useful in preventing the development of sustained hypertension. (Hypertension 4: 789–794, 1982)
Cerebrin prohormone processing, distribution and action in Aplysia californica

The isolation, characterization, and bioactivity in the feeding circuitry of a novel neuropeptide in the Aplysia californica central nervous system are reported. The 17‐residue amidated peptide, NGGTADALYNLPDLEKIamide, has been termed cerebrin due to its primary location in the cerebral ganglion. Liquid chromatographic purification guided by matrix‐assisted laser desorption/ionization time‐of‐flight mass spectrometry allowed the isolation of the peptide with purity adequate for Edman sequencing. The cerebrin cDNA has been characterized and encodes an 86 amino acid prohormone that predicts cerebrin and one additional peptide. Mapping using in situ hybridization and immunocytochemistry showed that cerebrin containing neuronal somata are localized almost exclusively in the cerebral ganglion, mostly in the F‐ and C‐clusters. Both immunostaining and mass spectrometry demonstrated the presence of cerebrin in the neurohemal region of the upper labial nerve. In addition, immunoreactive processes were detected in the neuropil of all of the ganglia, including the buccal ganglia, and in some interganglionic connectives, including the cerebral‐buccal connective. This suggests that cerebrin may also function as a local signaling molecule. Cerebrin has a profound effect on the feeding motor pattern elicited by the command‐like neuron CBI‐2, dramatically shortening the duration of the radula protraction in a concentration‐dependent manner, mimicking the motor‐pattern alterations observed in food induced arousal states. These findings suggest that cerebrin may contribute to food‐induced arousal in the animal. Cerebrin‐like immunoreactivity is also present in Lymnaea stagnalis suggesting that cerebrin‐like peptides may be widespread throughout gastropoda.
Computational Issues for a New Class of Preconditioners

In this paper we consider solving a sequence of weighted linear least squares problems where the only changes from one problem to the next are the weights and the right hand side (or data). We alternate between iterative and direct methods to solve the normal equations for the least squares problems. The direct method is the Cholesky factorization. For the iterative method we discuss a class of preconditioners based on a low rank correction of a Cholesky factorization of a weighted normal equation coefficient matrix. Different ways to compute the preconditioner are given. Further, a sparse algorithm for modifying the Cholesky factors by a low rank matrix is derived.
C-SLANT: an asynchronous communications tool to support distributed work in the National Airspace System

In recent years there have been a number of efforts under the Collaborative Decision Making (CDM) program that have demonstrated the benefits of disseminating both knowledge and goals between organizations in the National Airspace System (NAS), and of collaboratively building decision support tools to assist in the interpretation of the large interrelated dataset produced. The paper describes the development of the Collaborative SLide ANnotation Tool (C-SLANT), an asynchronous communications tool that was developed to support discussion of data from the CDM product Post Operations Evaluation Tool. It is suggested that slide show based, multi-modal, asynchronous, messaging systems appear potentially valuable in this distributed work domain for problem solving during post operations analysis.
The importance of lifestyle entrepreneurship: A conceptual study of the tourism industry

El objetivo del trabajo es explorar y analizar el surgimiento de la iniciativa empresarial como estilo de vida. El articulo aborda la relacion entre la calidad de vida del empresario y el crecimiento empresarial. El proposito es conceptualizar esta relacion para aprender mas sobre el espiritu empresarial como estilo de vida. El turismo aporta una serie de casos para ilustrar la investigacion pertinente en el ambito de la iniciativa empresarial como estilo de vida y un marco conceptual para examinar la relacion entre las actividades empresariales y la calidad de vida percibida. El documento ofrece una revision de la literatura sobre el espiritu empresarial y ciertas formas de iniciativa y conceptualiza el crecimiento de la iniciativa empresarial como estilo de vida
Modelling the length distribution of exons by sums of geometric laws . Analysis of the structure of genes and G + C influence

Mathematical and computational methods are essential for gene identification and a more realistic modelling is necessary to better understand genome organization and gene expression. Hidden Markov models are one of the methods widely used for such identification. These models are quite efficient for gene localization but they imply that the lengths of all regions are geometrically distributed. However, in the human genome, the length distribution of the exons does not follow a geometric law. To address this problem, we propose to represent the length distribution of the exons by sums of geometric distributions with equal or different parameters. The model that we obtain has relatively few parameters, and fits very well exon lengths. Moreover, we propose a data processing method, based on a discrimination technique between Hidden Markov Models, which allows to study the structure of coding genes in detail. Our model describes known differences in gene organization between isochore classes and reveals some specific characteristics of intronless genes and a break in the homogeneity of the first coding exons. The use of hidden Markov models with complex states seems therefore to be a promising new approach for the modelling of the organization of a large genome.
Inner product computation for sparse iterative solvers on distributed supercomputer

Recent years have witnessed that iterative Krylov methods without re-designing are not suitable for distribute supercomputers because of intensive global communications. It is well accepted that re-engineering Krylov methods for prescribed computer architecture is necessary and important to achieve higher performance and scalability. The paper focuses on simple and practical ways to re-organize Krylov methods and improve their performance for current heterogeneous distributed supercomputers. In construct with most of current software development of Krylov methods which usually focuses on efficient matrix vector multiplications, the paper focuses on the way to compute inner products on supercomputers and explains why inner product computation on current heterogeneous distributed supercomputers is crucial for scalable Krylov methods. Communication complexity analysis shows that how the inner product computation can be the bottleneck of performance of (inner) product-type iterative solvers on distributed supercomputers due to global communications. Principles of reducing such global communications are discussed. The importance of minimizing communications is demonstrated by experiments using up to 900 processors. The experiments were carried on a Dawning 5000A, one of the fastest and earliest heterogeneous supercomputers in the world. Both the analysis and experiments indicates that inner product computation is very likely to be the most challenging kernel for inner product-based iterative solvers to achieve exascale.
Structured and unobtrusive observation of anonymous users and their context for requirements elicitation

Today, people find themselves surrounded by IT systems in their everyday life. Often they are not even aware that they are interacting with an IT system. More and more of these systems are context adaptive. Requirements to such systems may change for various reasons: The context may fundamentally change when other systems are introduced. New trends and fashions may evolve. Operators need to react quickly to such changes if they want to keep their systems competitive. Traditional approaches to requirements elicitation start to fail in this situation: context adaptive systems serve many users with different profiles. In addition, users may be reluctant to participate in improving it. Thus, it is hard to establish a representative model of requirements. Furthermore, it is hard to capture the context of requirements by subsequent interviews. In this paper we present a systematical approach for requirements elicitation based on observing anonymous users. The interaction of users with the system is observed in the normal working context. Observation is based on assumptions on how interaction should take place. Deviations from these assumptions point to new requirements. Observing a large number of users leads to a quantitative map of requirements in context. Preliminary evaluation shows that the approach is promising. It allows efficient observation of many stakeholders and the derivation of new requirements.
Using rule-based knowledge to improve LVCSR

We show that an elaborate linguistic model of a natural language can be a valuable knowledge source to improve large vocabulary continuous speech recognition (LVCSR). Our approach is to complement a statistical language model with rule-based linguistic knowledge. A hidden Markov model based recognizer and an N-gram language model are used to compute a word lattice which is subsequently processed by a parser. We succeeded in enhancing recognition performance by favouring word sequences which the parser identified as being grammatically correct.
Akt promotes survival of cardiomyocytes in vitro and protects against ischemia-reperfusion injury in mouse heart.

BACKGROUND IGF-1 has been shown to protect myocardium against death in animal models of infarct and ischemia-reperfusion injury. In the present study, we investigated the role of the IGF-1-regulated protein kinase Akt in cardiac myocyte survival in vitro and in vivo. METHODS AND RESULTS IGF-1 promoted survival of cultured cardiomyocytes under conditions of serum deprivation in a dose-dependent manner but had no effect on cardiac fibroblast survival. The cytoprotective effect of IGF-1 on cardiomyocytes was abrogated by the phosphatidylinositol 3-kinase (PI 3-kinase) inhibitor wortmannin. Wortmannin had no effect on cardiomyocyte viability in the absence of IGF-1. IGF-1-mediated cytoprotection correlated with the wortmannin-sensitive induction of Akt protein kinase activity. To examine the functional consequences of Akt activation in cardiomyocyte survival, replication-defective adenoviral constructs expressing wild-type, dominant-negative, and constitutively active Akt genes were constructed. Transduction of dominant-negative Akt blocked IGF-1-induced survival but had no effect on cardiomyocyte survival in the absence of IGF-1. In contrast, transduction of wild-type Akt enhanced cardiomyocyte survival at subsaturating levels of IGF-1, whereas constitutively active Akt protected cardiomyocytes from apoptosis in the absence of IGF-1. After transduction into the mouse heart in vivo, constitutively active Akt protected against myocyte apoptosis in response to ischemia-reperfusion injury. CONCLUSIONS These data are the first documentation that Akt functions to promote cellular survival in vivo, and they indicate that the activation of this pathway may be useful in promoting myocyte survival in the diseased heart.
Improvement of a Video Smoke Detection Based on Accumulative Motion Orientation Model

Early fire-alarming is very important to avoid serious human being and materials losses. The traditional sensor-based methods can detect fire when the situation already has been dangerous. The video-based smoke detection can overcome these drawbacks. This paper proposes improvements of Yuan's video-based smoke detection, which employs accumulative motion orientation to detect smoke. In the proposed improvements, optimal thresholds for motion and chrominance detection are established and isolated noisy blocks are eliminated. The motion detection threshold is experimentally determined, and the chrominance detection thresholds are deduced from observation and testing of many videos with or without smoke. The elimination of isolated noisy blocks is achieved using the connected component labeling algorithm, which allows only processing the smoke regions, reducing the computational cost. Experimental results show that the proposed scheme increase the accuracy of the smoke detection and reduce the computation time.
Forest fire localization using distributed algorithms in wireless sensor networks

The fire localization using a distributed consensus finding algorithm in a wireless sensor network is described. The fire is circumscribed by a circle. The information is available at all sensor nodes that are alive, which makes it robust against failures and losses. Minimizing energy consumption is crucial for sensor nodes that have to function autonomously as long as possible. Therefore, the speed of convergence of the consensus finding algorithm has to be optimized. We argue that optimizing, as is customary, the asymptotic speed of convergence is not the best method when a consensus value of low precision is su±cient.
Automated Analysis of Longitudinal Changes in Color Retinal Fundus Images for Monitoring Diabetic Retinopathy

Automated image analysis algorithms are presented for detection and classification of changes in longitudinal time-series of color retinal fundus images. They are applicable to clinical practice, quantitative scoring of clinical trials, computer-assisted reading centers, and training. This work focuses on diabetes-related changes, although the techniques have broader applicability. Retinal features, including the vasculature, vessel branching/crossover locations, optic disk, and fovea are extracted automatically. The images are registered to sub-pixel accuracy using a 12-dimensional mapping that accounts for the unknown retinal curvature and camera parameters. The images are corrected for non-uniform illumination using a robust homomorphic surface fitting algorithm. The changes in non-vascular regions are segmented using an algorithm that is robust to relevant artifacts such as dust particles in the optical path. They are classified into five clinically significant categories using a Bayesian algorithm constrained by Markov Random Fields. A flicker animation overlaid with change analysis results allows qualitative and quantitative assessment by the user. A multi-observer validation on 43 image pairs from 22 eyes involving non-proliferative and proliferative diabetic retinopathies, showed a 96.83 % change detection rate, a 3.17 % miss rate, and a 17.65 % false alarm rate. The performance in correctly classifying the changes was 97.39 %.
miMic: The Microphone as a Pencil

miMic, a sonic analogue of paper and pencil is proposed: An augmented microphone for vocal and gestural sonic sketching. Vocalizations are classified and interpreted as instances of sound models, which the user can play with by vocal and gestural control. The physical device is based on a modified microphone, with embedded inertial sensors and buttons. Sound models can be selected by vocal imitations that are automatically classified, and each model is mapped to vocal and gestural features for real-time control. With miMic, the sound designer can explore a vast sonic space and quickly produce expressive sonic sketches, which may be turned into sound prototypes by further adjustment of model parameters.
A privacy-preserving and language-independent speaking detecting and speaker diarization approach for spontaneous conversation using microphones

Conversation conveys important social signals of human interaction that indicates interest, service-awareness, persuasiveness, etc. In this paper, the authors employ the most common setting of using microphones to capture spontaneous conversation, and introduce a privacy-preserving and language-independent speech processing approach that can detect speaking and separate speakers in high accuracy for such setting. Experimental results have validated that the approach can deliver accurate speaking recognition results in Japanese, English and Chinese conversation, and can be processed in real time applications.
Handling Anomalies in Distributed Firewalls

Distributed Firewalls filter the incoming and outgoing network traffic based on a set of predefined filtering rules. The filtering rules have to be well defined and coherent in order to guarantee the desired responses of the Firewalls. In this paper, we propose an inference system for detecting all anomalies that could exist in a multi-Firewall network environment. Three classes of anomalies are described, namely, the Redundancy, Locking and Incoherence anomalies. Then, we give an example of common network architecture with the corresponding filtering policy. The example demonstrates how anomalies can be easily detected using the proposed inference model. Related works are discussed; and it will be demonstrated that the proposed inference model is more simple and general than related models.
A reduced complexity message passing algorithm with improved performance for LDPC decoding

In this paper, a simplified message passing algorithm for decoding Low-Density Parity-Check (LDPC) codes is proposed with a view to reduce the implementation complexity. The algorithm is based on simple hard-decision decoding techniques while utilizing the advantages of soft channel information for improvement in decoder performance. The algorithm has been validated through simulation using LDPC code compliant with Wireless Local Area Network (WLAN -IEEE 802.11n) standard. The results show that the proposed algorithm can achieve significant improvement in bit error rate (BER) performance and average decoding iterations compared to fully hard-decision based decoding algorithms.
BLUE AND GREEN EGG‐COLOR INTENSITY IS ASSOCIATED WITH PARENTAL:EFFORT AND MATING SYSTEM IN PASSERINES: SUPPORT FOR:THE SEXUAL SELECTION HYPOTHESIS.

Abstract Among several adaptive explanations proposed to account for variation in avian egg color, that related to sexual selection is of particular interest because of its possible generality. Briefly, it proposes that because biliverdin (the pigment responsible for blue‐green eggshell coloration) is an antioxidant, deposition in the eggshell by laying females may signal the capacity of females to control free radicals, despite the handicap of removing this antioxidant from their body. If males adjust parental effort in response to the intensity of the blue coloration of eggs, thereby investing more in the offspring of high‐quality mates, blue eggs may represent a postmating sexually selected signal in females. Here, by image and spectrophotometric analyses of the eggs of European passerines, we tested two different predictions of the hypothesis. First, variables related to intraspecific variation in parental effort (i.e., the duration of the nestling period controlled for body mass) should be positively related to the intensity of blue‐green color of the eggshell across species. Second, there should be a positive relationship between intensity of blue‐green color of eggs and degree of polygyny. These predictions were supported: intensity of blue‐green coloration (i.e., chroma) was significantly related to the duration of the nestling period and to degree of polygyny after controlling for possible confounding variables (i.e., body mass, incubation period, and nest type) and similarity due to common descent. Nest type (hole or nonhole) also explained a significant proportion of variation in egg chroma, perhaps reflecting different selection pressures (i.e., light conditions, risk of parasitism) affecting species with the two types of nests.
Generating Believable Mixed-Traffic Animation

We present an agent-based approach to animate microscopic mixed traffic involving cars and motorcycles in complex scenarios, including signalized and nonsignalized road intersections, and traffic jams due to blockage. Based on our new car-following and lateral movement models, our method can reproduce lane-based and nonlane-based traffic behaviors that are commonly seen in urban scenes. Our dynamic routing and intersection procedures enable a user to interactively control the movement of a car, and our system generates the microscopic behaviors of the influenced vehicles accordingly. Experimental results show that our approach can animate appealing microscopic mixed traffic with various behaviors. Our approach will benefit applications in virtual cities, computer games, and driving simulators.