Miracle-dz/UniFAR-FTUs huggingface dataset:
The temporal distribution of directional gradients under selection for an optimum

Temporal variation in phenotypic selection is often attributed to environmental change causing movements of the adaptive surface relating traits to fitness, but this connection is rarely established empirically. Fluctuating phenotypic selection can be measured by the variance and autocorrelation of directional selection gradients through time. However, the dynamics of these gradients depend not only on environmental changes altering the fitness surface, but also on evolution of the phenotypic distribution. Therefore, it is unclear to what extent variability in selection gradients can inform us about the underlying drivers of their fluctuations. To investigate this question, we derive the temporal distribution of directional gradients under selection for a phenotypic optimum that is either constant or fluctuates randomly in various ways in a finite population. Our analytical results, combined with population‐ and individual‐based simulations, show that although some characteristic patterns can be distinguished, very different types of change in the optimum (including a constant optimum) can generate similar temporal distributions of selection gradients, making it difficult to infer the processes underlying apparent fluctuating selection. Analyzing changes in phenotype distributions together with changes in selection gradients should prove more useful for inferring the mechanisms underlying estimated fluctuating selection.
Research of a parallel learning adaptive dynamic programming based on genetic algorithms

In adaptive dynamic programming (ADP), the utility function is always completely designed by experience which cannot evaluate system cost very well. A novel adaptive dynamic programming based on genetic algorithms (GAADP) method is proposed with global searching and fast learning speed. First, a normal utility function of ADP was designed according to the error between current states and expected values. Second, genetic algorithms (GAs) were used to search for the optimal parameters of utility function in ADP. Finally, we employed GAADP on an inverted pendulum system control. The simulation experiments indicated that GAADP method can increase the learning speed and easily achieve the balancing state. The learning speed doubled than general ADP method, meanwhile the control performance of successful trials also improved.
Relative Brain Size and Its Relation with the Associative Pallium in Birds

Despite growing interest in the evolution of enlarged brains, the biological significance of brain size variation remains controversial. Much of the controversy is over the extent to which brain structures have evolved independently of each other (mosaic evolution) or in a coordinated way (concerted evolution). If larger brains have evolved by the increase of different brain regions in different species, it follows that comparisons of the whole brain might be biologically meaningless. Such an argument has been used to criticize comparative attempts to explain the existing variation in whole-brain size among species. Here, we show that pallium areas associated with domain-general cognition represent a large fraction of the entire brain, are disproportionally larger in large-brained birds and accurately predict variation in the whole brain when allometric effects are appropriately accounted for. While this does not question the importance of mosaic evolution, it suggests that examining specialized, small areas of the brain is not very helpful for understanding why some birds have evolved such large brains. Instead, the size of the whole brain reflects consistent variation in associative pallium areas and hence is functionally meaningful for comparative analyses.
Neuropeptidergic Signaling in the American Lobster Homarus americanus: New Insights from High-Throughput Nucleotide Sequencing

Peptides are the largest and most diverse class of molecules used for neurochemical communication, playing key roles in the control of essentially all aspects of physiology and behavior. The American lobster, Homarus americanus, is a crustacean of commercial and biomedical importance; lobster growth and reproduction are under neuropeptidergic control, and portions of the lobster nervous system serve as models for understanding the general principles underlying rhythmic motor behavior (including peptidergic neuromodulation). While a number of neuropeptides have been identified from H. americanus, and the effects of some have been investigated at the cellular/systems levels, little is currently known about the molecular components of neuropeptidergic signaling in the lobster. Here, a H. americanus neural transcriptome was generated and mined for sequences encoding putative peptide precursors and receptors; 35 precursor- and 41 receptor-encoding transcripts were identified. We predicted 194 distinct neuropeptides from the deduced precursor proteins, including members of the adipokinetic hormone-corazonin-like peptide, allatostatin A, allatostatin C, bursicon, CCHamide, corazonin, crustacean cardioactive peptide, crustacean hyperglycemic hormone (CHH), CHH precursor-related peptide, diuretic hormone 31, diuretic hormone 44, eclosion hormone, FLRFamide, GSEFLamide, insulin-like peptide, intocin, leucokinin, myosuppressin, neuroparsin, neuropeptide F, orcokinin, pigment dispersing hormone, proctolin, pyrokinin, SIFamide, sulfakinin and tachykinin-related peptide families. While some of the predicted peptides are known H. americanus isoforms, most are novel identifications, more than doubling the extant lobster neuropeptidome. The deduced receptor proteins are the first descriptions of H. americanus neuropeptide receptors, and include ones for most of the peptide groups mentioned earlier, as well as those for ecdysis-triggering hormone, red pigment concentrating hormone and short neuropeptide F. Multiple receptors were identified for most peptide families. These data represent the most complete description of the molecular underpinnings of peptidergic signaling in H. americanus, and will serve as a foundation for future gene-based studies of neuropeptidergic control in the lobster.
FET twin model

In this paper, we present a simple but elegant idea through which a body-source shorted Field Effect Transistor (FET), either enhancement-type or depletion-type, and having either an n-channel or p-channel, can be replaced by a combination of two FETs of the same kind (twins), so that the i-v characteristics in all regions of FET operation (cut-off, triode and saturation) remain the same; even though none of the two FETs in the twin model enters the triode region.
Model Predictive Control for Transparent Teleoperation Under Communication Time Delay

Prior efforts in bilateral teleoperation under communication delay have mainly yielded control algorithms that sacrifice performance in order to guarantee robust stability. In contrast, this paper proposes a multimodel predictive controller that can enhance the teleoperation transparency in the presence of a known constant delay. Separate controllers are designed for free motion/soft contact and contact with rigid environments, with switching between these mode-based control laws occurring according to the identified contact mode. Performance objectives such as position tracking and tool impedance shaping for free motion/soft contact, as well as position and force tracking for contact with rigid environments, are incorporated into a multi-input/multi-output state-space representation of the system dynamics. New Artstein-type state and measurement transformations are proposed to generate delay-free dynamics suitable for output-feedback control, based on the original dynamics with delays in various input and output channels. The application of the continuous-time linear quadratic Gaussian control synthesis to the resulting mode-based delay-free dynamics yields control laws that guarantee closed-loop stability and enhanced performance in each phase of teleoperation. The robustness of the mode-based controllers with respect to parametric uncertainty is analyzed. Experimental results with a single-axis teleoperation setup demonstrate the effectiveness of the proposed approach
Explicit Formulae for Characteristics of Finite‐Capacity M/D/1 Queues

Even though many computational methods (recursive formulae) for blocking probabilities in finite‐capacity M/D/1 queues have already been produced, these are forms of transforms or are limited to single‐node queues. Using a distinctly different approach from the usual queueing theory, this study introduces explicit (transform‐free) formulae for a blocking probability, a stationary probability, and mean sojourn time under either production or communication blocking policy. Additionally, the smallest buffer capacity subject to a given blocking probability can be determined numerically from these formulae. With proper selection of the overall offered load ρ, the approach described herein can be applicable to more general queues from a computational point of view if the explicit expressions of random vector Dn are available.
Perron-Frobenius theorem and invariant sets in linear systems dynamics

The paper explores the connections between the Perron-Frobenius (PF) theory and the flow-invariant sets with respect to the dynamics of linear systems. Our analysis includes both discrete-and continuous-time systems, and the results are separately formulated for linear dynamics generated by the following types of matrices: (i) (essentially) nonnegative and irreducible or (essentially) positive, (ii) (essentially) nonnegative and reducible. For both cases we show how the PF eigenvalue and right and left PF eigenvectors are related to invariant sets defined for any Holder p-norm (1 les p les infin ).
Approximation and Classification in Medicine with IncNet Neural Networks1

Structure of incremental neural network (IncNet) is controlled by growing and pruning to match the complexity of training data. Extended Kalman Filter algorithm and its fast version is used as learning algorithm. Bi-central transfer functions, more flexible than other functions commonly used in artificial neural networks, are used. The latest improvement added is the ability to rotate the contours of constant values of transfer functions in multidimensional spaces with only N − 1 adaptive parameters. Results on approximation benchmarks and on the real world psychometric classification problem clearly shows superior generalization performance of presented network comparing with other classification models. INTRODUCTION Artificial Neural Networks (ANN) are used to many different kinds of problems such as classification, approximation, pattern recognition, signal processing, prediction, feature extraction, etc. Most of them are solved with ANN by learning of the mapping between the input and output space for given data sets S = {〈x1, y1〉, . , 〈xn, yn〉}, where 〈xi, yi〉 is input – output pair (xi ∈ R, yi ∈ R). The underlying mapping F(·) can be written as F(xi) = yi + η, i = 1, . , n (1) where η is a zero mean white noise with variance σns. Building a network that preserves information with complexity matched to training data, using an architecture which is able to grow, shrink, and using flexible transfer functions to estimate complex probability density distributions, is the goal of this paper. The best known local learning models are the radial basis function networks (RBF) (Powell, 1987; Poggio and Girosi, 1990; Bishop, 1991), adaptive kernel methods and local risk minimization (Girosi, 1998). The RBF networks were designed as a solution to an approximation problem in multi–dimensional spaces. The typical form of the RBF network can be written as
Acquisition of high-resolution images through on-line saccade sequence planning

This paper considers the problem of scheduling an active observer to visit as many targets in an area of surveillance as possible. We show how it is possible to plan a sequence of decisions regarding what target to look at through such a foveal-sensing action. We propose a framework in which a pan/tilt/zoom camera executes saccades in order to visit, and acquire high resolution images (at least one) of, as many moving targets as possible before they leave the scene. An intelligent choice of the order of sensing the targets can significantly reduce the total dead-time wasted by the active camera and, consequently, its cycle time. We cast the whole problem into a dynamic discrete optimization framework. In particular, we will show that the problem can be solved by modeling the attentional gaze control as a kinetic traveling salesperson problem whose solution is approximated by iteratively solving time dependent orienteering problems.Congestion analysis experiments are reported demonstrating the effectiveness of the solution in acquiring high resolution images of a large number of moving targets in a wide area. The evaluation was conducted with a simulation of a dual camera system in a master-slave configuration. We also report on preliminary experiments conducted using live cameras in a real surveillance environment.
Towards an Intelligent Property Valuation Model: An Exploratory and Conceptual Study

Automated Valuation Models (AVMs) have been used by mortgage industry participants for a number of years with a limited degree of success. A lack of comprehensive data and thus restricted reliability has prevented AVMs from being fully adopted by governments, lenders, brokers, and the like. This paper presents a framework for building an intelligent property valuation model that overcomes these problems. An overview of AVM research, a survey of current AVM products and several interviews with industry participants were conducted. The findings revealed a number of important elements for optimal AVMs. This paper also provides a description of a unique dataset combining both appraisal data and public record data. This information combined with well established data mining techniques including clustering, geocoding, and ensembles provides the basis for further research towards building a new property valuation method that better meets industry needs.
Generic Pipelined Multi-Agents Architecture for Multimedia Multimodal Software Environments

Multimodal human-computer interaction needs intelligent architectures in order to enhance the flexibility and naturelness of the user interface. These architectures have the ability to manage several multithreaded input signals from different input media in order to perform their fusion into intelligent commands. In this paper, a generic comprehensive agent-based architecture for multimodal engine fusion is proposed. The architecture is sketched in term of its relevant components. Each element is modeled using timed colored Petri networks. The generic components of the engine fusion are then included in a pipelined based-agent global architecture for which the architectural quality attributes are outlined.
Asthma–Chronic Obstructive Pulmonary Diseases Overlap Syndrome Increases the Risk of Incident Tuberculosis: A National Cohort Study

Purpose The association between asthma–chronic obstructive pulmonary diseases (COPD) overlap syndrome (ACOS) and tuberculosis (TB) has yet to be studied. Methods The newly diagnosed TB patients (age > 20 y) treated from January 2000 to December 2008 were included (ACOS cohort, n = 10 751; non-ACOS cohort, n = 42 966). The non-ACOS cohort involved patients with confirmed absence of ACOS. We calculated incidence rate ratios (IRRs) for TB in the ACOS and non-ACOS cohorts by using poisson regression analysis. Cox proportional hazards regression models were used to determine the adjusted HR (aHR) for TB in the ACOS cohort compared with the non-ACOS cohort. Results The aHR for TB was 2.41 (95% confidence interval [CI], 2.19–2.66) in the ACOS cohort. The TB risk was significantly higher in the ACOS cohort than in the non-ACOS cohort when stratified by age, sex, comorbidities, and atopy. Within the ACOS cohort, the aHR was higher among patients receiving SABAs+SAMAs, LABAs+LAMAs, and ICSs (aHR [95% CI]: 3.06 [2.75–3.41], 3.68 [2.93–4.61], and 2.79 [1.25–6.22], respectively; all P < .05). Furthermore, patients with more than 15 outpatient visits and hospitalizations per year demonstrated the highest aHR (8.09; 95% CI, 6.85–9.56). Conclusions ACOS cohort potentially develop incident TB, regardless of the age,sex, comorbidities and atopy; even without receiving the inhalers.This risk is higher, especially in the ACOS cohort have a high frequency of medical services or receiving the inhalers such as SABAs+SAMAs, LABAs+LAMAs and ICSs.
CXCR4 Blockade Attenuates Hyperoxia-Induced Lung Injury in Neonatal Rats

Background: Lung inflammation is a key factor in the pathogenesis of bronchopulmonary dysplasia (BPD). Stromal-derived factor-1 (SDF-1) and its receptor chemokine receptor 4 (CXCR4) modulate the inflammatory response. It is not known if antagonism of CXCR4 alleviates lung inflammation in neonatal hyperoxia-induced lung injury. Objective: We aimed to determine whether CXCR4 antagonism would attenuate lung injury in rodents with experimental BPD by decreasing pulmonary inflammation. Methods: Newborn rats exposed to normoxia (room air, RA) or hyperoxia (FiO2 = 0.9) from postnatal day 2 (P2) to P16 were randomized to receive the CXCR4 antagonist, AMD3100 or placebo (PL) from P5 to P15. Lung alveolarization, angiogenesis and inflammation were evaluated at P16. Results: Compared to the RA pups, hyperoxic PL pups had a decrease in alveolarization, reduced lung vascular density and increased lung inflammation. In contrast, AMD3100-treated hyperoxic pups had improved alveolarization and increased angiogenesis. This improvement in lung structure was accompanied by a decrease in the macrophage and neutrophil counts in the bronchoalveolar lavage fluid and reduced lung myeloperoxidase activity. Conclusion: CXCR4 antagonism decreases lung inflammation and improves alveolar and vascular structure in neonatal rats with experimental BPD. These findings suggest a novel therapeutic strategy to alleviate lung injury in preterm infants with BPD.
Word, graph and manifold embedding from Markov processes

Continuous vector representations of words and objects appear to carry surprisingly rich semantic content. In this paper, we advance both the conceptual and theoretical understanding of word embeddings in three ways. First, we ground embeddings in semantic spaces studied in cognitive-psychometric literature and introduce new evaluation tasks. Second, in contrast to prior work, we take metric recovery as the key object of study, unify existing algorithms as consistent metric recovery methods based on co-occurrence counts from simple Markov random walks, and propose a new recovery algorithm. Third, we generalize metric recovery to graphs and manifolds, relating co-occurence counts on random walks in graphs and random processes on manifolds to the underlying metric to be recovered, thereby reconciling manifold estimation and embedding algorithms. We compare embedding algorithms across a range of tasks, from nonlinear dimensionality reduction to three semantic language tasks, including analogies, sequence completion, and classification.
The biological chemistry of folate receptors.

HE ESSENTIAL role of intracellular folates in ef-T fecting one-carbon transfers in critical enzyme systems for DNA synthesis is well This has led to extensive application of various synthetic folate analogues as therapeutic and investigative tools in a variety of infectious, immunologic, and neoplastic diseases, as well as in developmental, transplantation, and tumor b i o l ~ g y. ~ , ~ While the enzyme dihydrofolate reductase (DHFR), the major target for the antifolate, methotrexate (MTX), is a paradigm for many aspects of biologic chemistry and molecular b i o l ~ g y , ~ ~ ~ the use of MTX is also prototypical in clinical medicine. However, cells develop resistance to MTX by DHFR gene amplification/generation of a form of DHFR with an altered affinity (K,,,), failure to polygluta-mate MTX, and a transport defect in intracellular e n t ~. ~-l ~ Whereas the advanced understanding of DHFR and the first two resistance mechanisms is archetypical in oncology, understanding the mechanism of the transport defect for MTX can only be made once details on the cellular uptake of folate is known. Another compelling reason to study folate transport arises from the potentially unique properties of folates as small M,-500, hydrophilic, anionic molecules that must transverse the hydrophobic barrier of the external plasma membrane; from a teleologic point of view, it appears reasonable to speculate that specific mechanisms must exist to assure a constant availability of folates for DNA synthesis. Clinical observations wherein folate-deficient mothers deliver infants with normal folate stores and the existence of a 30-to 100-fold higher red blood cell (RBC) folate content than serum supports a physiologic role for folate transport across the placenta and into RBCs, respecti~ely. ~~~J5 In contrast, the syndromes of congenital folate malabsorption16 and familial aplastic anemiaI7 are " experiments of nature " that indicate a congenital and acquired failure in physiologic folate transport, respectively . '~~ Thus, folate transport into cells for intrinsic cellular utilization is to be distinguished from transcellular folate transport across cellular barriers, and the mechanisms involved in these two transport processes will not necessarily be identical. Significant recent advances on the components and mechanism(s) of the cellular uptake of folates in human and primate cells promise to shed new light on these and related clinical observations and form the focus of this review. Other related reviews with a different focus have been published.18-Z4 Oxidized-folic acid (pteroylmonoglutamic acid, PteGlu) …
FUTURE TRENDS IN FIBER OPTICS COMMUNICATION

–Fiber optic systems are important telecommunication infrastructure for world-wide broadband networks. Wide bandwidth signal transmission with low delay is a key requirement in present day applications. Optical fibers provide enormous and unsurpassed transmission bandwidth with negligible latency, and are now the transmission medium of choice for long distance and high data rate transmission in telecommunication networks. This paper gives an overview of fiber optic communication systems including their key technologies, and also discusses their technological trend towards the next generation.
A Switching Difference Control Method for Load Balancing Control of Web-server Clusters

With the increasing popularity of multimedia streaming applications, a Web-server usually overloads in heavy-request period. A scheme of Web-server cluster has been widely employed to provide high-efficiency Internet services. In this paper, a switching difference control method is proposed to dynamically distribute the traffic among the N Web-servers. An TV-tanks system is suitable for modeling a Web-server cluster to address the traffic-balancing problem. The proposed switching policy is based on a subsystem consisting of two tanks, called tank-pair. Based on some feedback policy, different tanks are dynamically chosen to form the tank-pair so that all the TV tanks can be controlled in a time-sharing manner. A switching rule, called first-targeted-and-then-round-round-switching (FTRRS) Rule is introduced. Some simulation results for the FTRRS rule are reported in this paper, and they show that the proposed method is effective.