Miracle-dz/UniFAR-FTUs huggingface dataset:
How to Compute Optimal Catalog Mailing Decisions

We develop, estimate, and test a response model of order timing and order volume decisions of catalog customers and derive a Bayes rule for optimal mailing strategies. The model integrates the when and how much components of the response; incorporates the mailing decision of the firm; and uses a Bayesian framework to determine the optimal mailing rule for each catalog customer. The Bayes rule we propose for optimal mailing strategy allows for a broad set of objectives to be realized across the time horizon, such as profit maximization, customer retention, and utility maximization with or without risk aversion. We find that optimizing the objective function over multiple periods as opposed to a single period leads to higher expected profits and expected utility. Our results indicate that the cataloguer is well advised to send fewer catalogs than its current practice in order to maximize expected profits and utility.
Research of mammal bionic quadruped robots: A review

This paper focuses on the mammal bionic quadruped robots. The main challenge in this field is how to design the highly dynamical and high payload quadruped robots. This paper firstly introduces the history of bionic quadruped robots, particularly the landmark quadruped robots. Then the state-of-the art of drive mode for quadruped robots is reviewed. Subsequently, the development trend of quadruped robots is described. Based on the state-of-the art of quadruped robots, the technical difficulties of bionic quadruped robots are briefly reviewed. And the hydraulic quadruped robot developed in Shandong University is introduced. Finally, the summary and future work of the quadruped robots is given.
MiR‐133b inhibits growth of human gastric cancer cells by silencing pyruvate kinase muscle‐splicer polypyrimidine tract‐binding protein 1

The metabolism in tumor cells shifts from oxidative phosphorylation to glycolysis even in an aerobic environment. This phenomenon is known as the Warburg effect. This effect is regulated mainly by polypyrimidine tract‐binding protein 1 (PTBP1), which is a splicer of the mRNA for the rate‐limiting enzymes of glycolysis, pyruvate kinase muscle 1 and 2 (PKM1 and PKM2). In the present study, we demonstrated that miR‐133b reduced PTBP1 expression at translational level and that the expression levels of miR‐133b were significantly downregulated in gastric cancer clinical samples and human cell lines, whereas the protein expression level of PTBP1 was upregulated in 80% of the 20 clinical samples of gastric cancer examined. Ectopic expression of miR‐133b and knockdown of PTBP1 in gastric cancer cells inhibited cell proliferation through the induction of autophagy by the switching of PKM isoform expression from PKM2‐dominant to PKM1‐dominant. The growth inhibition was partially canceled by an autophagy inhibitor 3‐MA or a reactive oxygen species scavenger N‐acetylcysteine. These findings indicated that miR‐133b acted as a tumor‐suppressor through negative regulation of the Warburg effect in gastric cancer cells.
On Ultra-Wideband MIMO Systems with 1-bit Quantized Outputs: Performance Analysis and Input Optimization

We study the performance of multi-input multi-output (MIMO) channels with coarsely quantized outputs in the low signal-to-noise ratio (SNR) regime, where the channel is perfectly known at the receiver. This analysis is of interest in the context of ultra-wideband (UWB) communications from two aspects. First the available power is spread over such a large frequency band, that the power spectral density is extremely low and thus the SNR is low. Second the analog-to-digital converters (ADCs) for such high bandwidth signals should be low-resolution, in order to reduce their cost and power consumption. In this paper we consider the extreme case of only 1-bit ADC for each receive signal component. We compute the mutual information up to second order in the SNR and study the impact of quantization. We show that, up to first order in SNR, the mutual information of the 1-bit quantized system degrades only by a factor of 2/pi compared to the system with infinite resolution independent of the actual MIMO channel realization. With channel state information (CSI) only at receiver, we show that QPSK is, up to the second order, the best among all distributions with independent components. We also elaborate on the ergodic capacity under this scheme in a Rayleigh flat-fading environment.
QoS awareness and adaptation in service composition

The dynamic nature of a Web service execution environment generates frequent variations in the Quality of Service offered to the consumers, therefore, obtaining the expected results while running a composite service is not guaranteed. When combining this highly changing environment with the increasing emphasis on Quality of Service, management of composite services turns into a time consuming and complicated task. Different approaches and tools have been proposed to mitigate the impacts of unexpected events during the execution of composite services. Among them, self-adaptive proposals have stood out, since they aim to maintain functional and quality levels, by dynamically adapting composite services to the environment conditions, reducing human intervention. The research presented in this Thesis is centred on self-adaptive properties in service composition, mainly focused on self-optimization. Three models have been proposed to target self-optimization, considering various QoS parameters, the benefit of performing adaptation, and looking at adaptation from two perspectives: reactive and proactive. They target situations where the QoS of the composition is decreasing. Also, they consider situations where a number of the accumulated QoS values, in certain point of the process, are better than expected, providing the possibility of improving other QoS parameters. These approaches have been implemented in service composition frameworks and evaluated through the execution of test cases. Evaluation was performed by comparing the QoS values gathered from multiple executions of composite services, using the proposed optimization models and a non-adaptive approach. The benefit of adaptation was found a useful value during the decision making process, in order to determine if adaptation was needed or not. Results show that using optimization mechanisms when executing composite services provide significant improvements in the global QoS values of the compositions. Nevertheless, in some cases there is a trade-off, where one of the measured parameters shows an increment, in order to improve the others.
Contextual Multi-Armed Bandits

D´ avid P´ al Abstract We study contextual multi-armed bandit prob- lems where the context comes from a metric space and the payoff satisfies a Lipschitz condi- tion with respect to the metric. Abstractly, a con- textual multi-armed bandit problem models a sit- uation where, in a sequence of independent trials, an online algorithm chooses, based on a given context (side information), an action from a set of possible actions so as to maximize the total pay- off of the chosen actions. The payoff depends on both the action chosen and the context. In con- trast, context-free multi-armed bandit problems, a focus of much previous research, model situa- tions where no side information is available and the payoff depends only on the action chosen. Our problem is motivated by sponsored web search, where the task is to display ads to a user of an Internet search engine based on her search query so as to maximize the click-through rate (CTR) of the ads displayed. We cast this prob- lem as a contextual multi-armed bandit problem where queries and ads form metric spaces and the payoff function is Lipschitz with respect to both the metrics. For any > 0 we present an algorithm with regret O(T a+b+1 a+b+2+ ) where a;b are the covering dimensions of the query space and the ad space respectively. We prove a lower bound ( T ~ a+~+1 ~ a+~+2 ) for the regret of any algo- rithm where ~ ~ are packing dimensions of the query spaces and the ad space respectively. For finite spaces or convex bounded subsets of Eu- clidean spaces, this gives an almost matching up- per and lower bound.
Proportional Odds Models with High‐Dimensional Data Structure

The proportional odds model is the most widely used model when the response has ordered categories. In the case of high‐dimensional predictor structure, the common maximum likelihood approach typically fails when all predictors are included. A boosting technique pomBoost is proposed to fit the model by implicitly selecting the influential predictors. The approach distinguishes between metric and categorical predictors. In the case of categorical predictors, where each predictor relates to a set of parameters, the objective is to select simultaneously all the associated parameters. In addition, the approach distinguishes between nominal and ordinal predictors. In the case of ordinal predictors, the proposed technique uses the ordering of the ordinal predictors by penalizing the difference between the parameters of adjacent categories. The technique has also a provision to consider some mandatory predictors (if any) that must be part of the final sparse model. The performance of the proposed boosting algorithm is evaluated in a simulation study and applications with respect to mean squared error and prediction error. Hit rates and false alarm rates are used to judge the performance of pomBoost for selection of the relevant predictors.
A deep look at the nuclear region of UGC 5101 through high angular resolution mid-IR data with GTC/CanariCam

We present an analysis of the nuclear infrared (IR, 1.6–18 μm) emission of the ultraluminous IR galaxy UGC 5101 to derive the properties of its active galactic nucleus (AGN) and its obscuring material. We use new mid-IR high angular resolution (0.3–0.5 arcsec) imaging using the Si-2 filter (λ_C = 8.7 μm) and 7.5–13 μm spectroscopy taken with CanariCam (CC) on the 10.4 m Gran Telescopio CANARIAS. We also use archival Hubble Space Telescope/NICMOS and Subaru/COMICS imaging and Spitzer/IRS spectroscopy. We estimate the near- and mid-IR unresolved nuclear emission by modelling the imaging data with GALFIT. We decompose the Spitzer/IRS and CC spectra using a power-law component, which represents the emission due to dust heated by the AGN, and a starburst component, both affected by foreground extinction. We model the resulting unresolved near- and mid-IR, and the starburst subtracted CC spectrum with the CLUMPY torus models of Nenkova et al. The derived geometrical properties of the torus, including the large covering factor and the high foreground extinction needed to reproduce the deep 9.7 μm silicate feature, are consistent with the lack of strong AGN signatures in the optical. We derive an AGN bolometric luminosity L_(bo)l ∼ 1.9 × 10^(45) erg s^(−1) that is in good agreement with other estimates in the literature.
Exploring the Relationship Between Longitudinal Course-Taking Patterns and In-State Transfer Into STEM Fields of Study

ABSTRACT Community colleges have increasingly played a critical role in expanding the pathway to baccalaureate degrees in science, technology, engineering, and mathematics (STEM) fields of study. At the same time, little is known about the course pathways that facilitate transfer into STEM disciplines at 4-year institutions. Adopting the STEM momentum concept, this research explored course-taking patterns that predict transfer into STEM fields of study and the timing of transfer. Employing a combination of longitudinal multidimensional k-means cluster analysis and multinomial logistic regression, the study revealed five clusters of course-taking patterns. Among them, three clusters of course-taking exhibited momentum toward transfer in STEM: one concentrating on courses in general education, one centering around major-specific coursework within and outside of STEM, and one involving the coupling of remedial courses and a broad distribution of courses within and beyond STEM. Furthermore, the first two patterns seemed to generate optimal momentum for middle transfer compared with early or late transfer, whereas the third cluster exhibited momentum for middle transfer and even greater momentum for late transfer. Discussion of the findings in the context of STEM momentum and implications for policy, practice, and research are presented.
Rapid Degradation of Host mRNAs by Stimulation of RNase E Activity by Srd of Bacteriophage T4

Escherichia coli messenger RNAs (mRNAs) are rapidly degraded immediately after bacteriophage T4 infection, and the host RNase E contributes to this process. Here, we found that a previously uncharacterized factor of T4 phage, Srd (Similarity with rpoD), was involved in T4-induced host mRNA degradation. The rapid decay of ompA and lpp mRNAs was partially alleviated and a decay intermediate of lpp mRNA rapidly accumulated in cells infected with T4 phage lacking srd. Exogenous expression of Srd in uninfected cells significantly accelerated the decay of these mRNAs. In addition, lpp(T) RNA, with a sequence identical to the decay intermediate of lpp mRNA and a triphosphate at 5′-end, was also destabilized by Srd. The destabilization of these RNAs by Srd was not observed in RNase E-defective cells. The initial cleavage of a primary transcript by RNase E can be either direct or dependent on the 5′-end of transcript. In the latter case, host RppH is required to convert the triphosphate at 5′-end to a monophosphate. lpp(T) RNA, but not lpp and ompA mRNAs, required RppH for Srd-stimulated degradation, indicating that Srd stimulates both 5′-end-dependent and -independent cleavage activities of RNase E. Furthermore, pull-down and immunoprecipitation analyses strongly suggested that Srd physically associates with the N-terminal half of RNase E containing the catalytic moiety and the membrane target sequence. Finally, the growth of T4 phage was significantly decreased by the disruption of srd. These results strongly suggest that the stimulation of RNase E activity by T4 Srd is required for efficient phage growth.
Myopic multi-hop transmission strategies in layered wireless networks

A layered wireless network is considered, where information is transmitted in a multi-hop MIMO-like fashion from the source node layer through several intermediate layers of nodes before reaching the sink node layer. Analog network coding is investigated as the network transmission strategy, exploiting the inherent superposition features of the wireless channel. A general myopic transmission protocol is proposed, allowing overhearing across several layers. Special cases are investigated in terms of diversity and bit error rate when using different types of linear detectors. Conditions for successful decoding of all source node messages at each sink node are derived.
Price‐based interference management in dense femtocell systems

Femtocell technology has been drawing considerable attention as a cost‐effective means of improving cellular coverage and capacity. However, under co‐channel deployment, femtocell system in dense environment may incur high uplink interference to existing macrocells and experiences strong inter‐cell interference at the same time. To manage the uplink interference to macrocell, as well as the inter‐cell interference, this paper proposes a price‐based uplink interference management scheme for dense femtocell systems. Specifically, on the one hand, to guarantee the macrocell users' quality of service, the macrocell base station prices the interference from femtocell users (FUEs) subject to a maximum tolerable interference power constraint. On the other hand, the inter‐cell interference is also taken into consideration. Moreover, a Stackelberg game model is adopted to jointly study the utility maximization of the macrocell base station and FUEs. Then, in order to reduce the amount of information exchange, we design a distributed power allocation algorithm for FUEs. In addition, admission control is adopted to protect the active FUEs' performance. Numerical results show that the price‐based interference management scheme is effective. Meanwhile, it is shown that the distributed power allocation combined with admission control is capable of robustly protecting the performance of all the active FUEs. Copyright © 2013 John Wiley & Sons, Ltd.
Mechanisms controlling the acquisition of a cardiac phenotype by liver stem cells

The mechanisms underlying stem cell acquisition of a cardiac phenotype are unresolved. We studied early events during the acquisition of a cardiac phenotype by a cloned adult liver stem cell line (WB F344) in a cardiac microenvironment. WB F344 cells express a priori the transcription factors GATA4 and SRF, connexin 43 in the cell membrane, and myoinositol 1,4,5-triphosphate receptor in the perinuclear region. Functional cell–cell communication developed between WB F344 cells and adjacent cocultured cardiomyocytes in 24 h. De novo cytoplasmic [Ca2+]c and nuclear [Ca2+]nu oscillations appeared in WB F344 cells, synchronous with [Ca2+]i transients in adjacent cardiomyocytes. The [Ca2+] oscillations in the WB F344 cells, but not those in the cardiomyocytes, were eliminated by a gap junction uncoupler and reappeared with its removal. By 24 h, WB F344 cells began expressing the cardiac transcription factors Nkx2.5, Tbx5, and cofactor myocardin; cardiac proteins 24 h later; and a sarcomeric pattern 4–6 days later. Myoinositol 1,4,5-triphosphate receptor inhibition suppressed WB F344 cell [Ca2+]nu oscillations but not [Ca2+]c oscillations, and L-type calcium channel inhibition eliminated [Ca2+] oscillations in cardiomyocytes and WB F344 cells. The use of these inhibitors was associated with a decrease in Nkx2.5, Tbx5, and myocardin expression in the WB F344 cells. Our findings suggest that signals from cardiomyocytes diffuse through shared channels, inducing [Ca2+] oscillations in the WB F344 cells. We hypothesize that the WB F344 cell [Ca2+]nu oscillations activate the expression of a cardiac specifying gene program, ushering in a cardiac phenotype.
The Peak of a Pandemic ? — A Phylogenetic Analysis of the H 1 N 1 Influenza Virus from 2009 to Present

The swine origin influenza A (S-OIV) virus of 2009 reached pandemic proportions due to its novel sequence identity in human populations of North America and other localities. The S-OIV virus shows subtle change from 2009-2010 in humans, affirming that the HA and NA sequences have been unable to antigenically drift or shift enough to emerge as another pandemic. This study aimed to document the succession of S-OIV from 2009 to current in addition to investigating its relationship among other locations. Based on the phylogenetic analysis, the 2010 H1N1 is similar to other isolates circulating the previous year. Furthermore, the protein sequences with the highest non-synonymous to synonymous ratio were HA and NA thus indicating strong selective pressures for the antigen receptor binding sites to adapt even within human hosts.
Representation of Finite State Automata inRecurrent Radial Basis Function NetworksPAOLO

In this paper, we propose some techniques for injecting nite state automata into Recurrent Radial Basis Function networks (R 2 BF). When providing proper hints and constraining the weight space properly, we show that these networks behave as automata. A technique is suggested for forcing the learning process to develop automata representations that is based on adding a proper penalty function to the ordinary cost. Successful experimental results are shown for inductive inference of regular grammars.
The RAxML-VI-HPC Version 2 . 0 Manual

This Section provides a brief version history of RAxML, mainly to avoid potential confusion. – RAxML-II: Initial Implementation of the hill climbing algorithm with the lazy subtree rearrangement technique. Implementation of a parallel MPIbased and distributed version of the program. – RAxML-III: Implementation of additional models of nucleotide substitution and ML-based optimization of model parameters. – RAxML-IV: Never existed, don’t ask me why. – RAxML-V: Introduction of the simulated annealing search algorithm, implementation of protein models, OpenMP-parallelization. – RAxML-VI: Introduction of the novel rapid hill climbing algorithm and automatic determination of a “good” rearrangement setting – RAxML-VI-HPC: Improvement of the OpenMP parallelization, technical tuning of the GTR-based likelihood models, re-implementation of the MP (Maximum Parsimony) starting tree computations, MPI-based parallel version for multiple bootstrapping. – RAxML-VI-HPC-2.0: Implementation of various forms of bifurcating and multifurcating constraint trees, implementation of multiple model estimates for multi-gene alignments.
Monocytes control second-phase neutrophil emigration in established lipopolysaccharide-induced murine lung injury.

RATIONALE Acute lung injury (ALI) is an important cause of morbidity and mortality, with no currently effective pharmacological therapies. Neutrophils have been specifically implicated in the pathogenesis of ALI, and there has been significant research into the mechanisms of early neutrophil recruitment, but those controlling the later phases of neutrophil emigration that characterize disease are poorly understood. OBJECTIVES To determine the influence of peripheral blood monocytes (PBMs) in established ALI. METHODS In a murine model of LPS-induced ALI, three separate models of conditional monocyte ablation were used: systemic liposomal clodronate (sLC), inducible depletion using CD11b diphtheria toxin receptor (CD11b DTR) transgenic mice, and antibody-dependent ablation of CCR2(hi) monocytes. MEASUREMENTS AND MAIN RESULTS PBMs play a critical role in regulating neutrophil emigration in established murine LPS-induced lung injury. Gr1(hi) and Gr1(lo) PBM subpopulations contribute to this process. PBM depletion is associated with a significant reduction in measures of lung injury. The specificity of PBM depletion was demonstrated by replenishment studies in which the effects were reversed by systemic PBM infusion but not by systemic or local pulmonary infusion of mature macrophages or lymphocytes. CONCLUSIONS These results suggest that PBMs, or the mechanisms by which they influence pulmonary neutrophil emigration, could represent therapeutic targets in established ALI.
Predicting Activism for a Social Cause

This study identifies factors that predict willingness to engage in activism for a social cause. In doing so, it develops a Guttman scale that ranks the various online and offline communication activities in order of likelihood of being engaged. Survey data indicate that those who perceive structural forces as the cause of homelessness are more willing to engage in activism. The societal attribution appears to drive willingness to engage in activism directly as well as indirectly by boosting confidence in persuading others to agree about the issue of homelessness (i.e., increasing communicative efficacy). This finding suggests that the causal attribution of responsibility may motivate activism by influencing the beliefs about whether one should and can help to mobilize support to address the issue.
On End-to-End Program Generation from User Intention by Deep Neural Networks

This paper envisions an end-to-end program generation scenario using recurrent neural networks (RNNs): Users can express their intention in natural language; an RNN then automatically generates corresponding code in a characterby-by-character fashion. We demonstrate its feasibility through a case study and empirical analysis. To fully make such technique useful in practice, we also point out several cross-disciplinary challenges, including modeling user intention, providing datasets, improving model architectures, etc. Although much long-term research shall be addressed in this new field, we believe end-to-end program generation would become a reality in future decades, and we are looking forward to its practice.