Complexity of Equivalence and Learning for Multiplicity Tree Automata

We consider the complexity of equivalence and learning for multiplicity tree automata, i.e., weighted tree automata over a field. We first show that the equivalence problem is logspace equivalent to polynomial identity testing, the complexity of which is a longstanding open problem. Secondly, we derive lower bounds on the number of queries needed to learn multiplicity tree automata in Angluin's exact learning model, over both arbitrary and fixed fields. Habrard and Oncina (2006) give an exact learning algorithm for multiplicity tree automata, in which the number of queries is proportional to the size of the target automaton and the size of a largest counterexample, represented as a tree, that is returned by the Teacher. However, the smallest tree-counterexample may be exponential in the size of the target automaton. Thus the above algorithm does not run in time polynomial in the size of the target automaton, and has query complexity exponential in the lower bound. Assuming a Teacher that returns minimal DAG representations of counterexamples, we give a new exact learning algorithm whose query complexity is quadratic in the target automaton size, almost matching the lower bound, and improving the best previously-known algorithm by an exponential factor

Leydig cells express neural cell adhesion molecules in vivo and in vitro

The neural cell adhesion molecule (NCAM) polypeptides are expressed by numerous tissues during embryonic development, where they are involved in cell-cell interactions. In the adult, NCAM expression is confined to a few cell types, including neurons and peptide-hormone-producing cells. Here we demonstrate that the Leydig cells of the adult rat, mouse, and hamster testes express NCAM as well. Western blotting showed that an NCAM of approximately 120 kDa was present in the adult testes of all three species investigated. This form was also found in freshly isolated mouse Leydig cells and in Leydig cells after 2 days in culture. After 4 days in culture, mouse Leydig cells expressed additional NCAM isoforms of approximately 140 and 180 kDa, indicating changes in alternative splicing of NCAM primary transcripts. Also, NCAM mRNA of all isoforms, as detected by S1-nuclease protection assays, increased with time in culture. The expression of the cell adhesion molecule NCAM by adult Leydig cells may explain the aggregation of Leydig cells in clusters in rodent testes, which could be a prerequisite for functional coordination of groups of Leydig cells. Furthermore, the presence of this neural and endocrine marker may indicate a closer relationship between Leydig cells and neural and peptide-hormone-producing cells than is considered to exist at the present time

Inclusive cross sections for pairs of identified light charged hadrons and for single protons in e^{+}e^{-} at sqrt[s]=10.58GeV

We report the first double differential cross sections of two charged pions and kaons (e+e−→hhX) in electron-positron annihilation as a function of the fractional energies of the two hadrons for any charge and hadron combination. The dependence of these dihadron cross sections on the topology (same, opposite hemisphere or anywhere) is also studied with the help of the event shape variable thrust and its axis. The ratios of these dihadron cross sections for different charges and hadron combinations directly shed light on the contributing fragmentation functions. For example, we find that the ratio of same-sign pion pairs over opposite-sign pion pairs drops toward higher fractional energies where disfavored fragmentation is expected to be suppressed. These dihadron results are obtained from a 655  fb−1 data sample collected near the Υ(4S) resonance with the Belle detector at the KEKB asymmetric-energy e+e− collider. Extending the previously published single-pion and single-kaon cross sections, single-proton (e+e−→pX) cross sections are extracted from a 159  fb−1 data subsample

The Permafrost and Organic LayEr module for Forest Models (POLE-FM) 1.0

Climate change and increased fire are eroding the resilience of boreal forests. This is problematic because boreal vegetation and the cold soils underneath store approximately 30 % of all terrestrial carbon. Society urgently needs projections of where, when, and why boreal forests are likely to change. Permafrost (i.e., subsurface material that remains frozen for at least two consecutive years) and the thick soil-surface organic layers (SOLs) that insulate permafrost are important controls of boreal forest dynamics and carbon cycling. However, both are rarely included in process-based vegetation models used to simulate future ecosystem trajectories. To address this challenge, we developed a computationally efficient permafrost and SOL module that operates at fine spatial (1 ha) and temporal (daily) resolutions. The module mechanistically simulates daily changes in depth to permafrost, annual SOL accumulation, and their complex effects on boreal forest structure and functions. We coupled the module to an established forest landscape model, iLand, and benchmarked the model in interior Alaska at spatial scales of stands (1 ha) to landscapes (61,000 ha) and over temporal scales of days to centuries. The coupled model could generate intra- and inter-annual patterns of snow accumulation and active layer depth (portion of soil column that thaws throughout the year) consistent with independent observations in 17 instrumented forest stands. The model was also skilled at representing the distribution of near-surface permafrost presence in a topographically complex landscape. We simulated 34.6 % of forested area in the landscape as underlain by permafrost; a close match to the estimated 33.4 % from the benchmarking product. We further determined that the model could accurately simulate moss biomass, SOL accumulation, fire activity, tree-species composition, and stand structure at the landscape scale. Modular and flexible representations of key biophysical processes that underpin 21st-century ecological change are an essential next step in vegetation simulation to reduce uncertainty in future projections and to support innovative environmental decision making. We show that coupling a new permafrost and SOL module to an existing forest landscape model increases the model&rsquo;s utility for projecting forest futures at high latitudes. Process-based models that represent relevant dynamics will catalyze opportunities to address previously intractable questions about boreal forest resilience, biogeochemical cycling, and feedbacks to regional and global climate.&emsp;</p

English-learning infants’ perception of word stress patterns

Adult speakers of different free stress languages (e.g., English, Spanish) differ both in their sensitivity to lexical stress and in their processing of suprasegmental and vowel quality cues to stress. In a head-turn preference experiment with a familiarization phase, both 8-month-old and 12-month-old English-learning infants discriminated between initial stress and final stress among lists of Spanish-spoken disyllabic nonwords that were segmentally varied (e.g. [ˈnila, ˈtuli] vs [luˈta, puˈki]). This is evidence that English-learning infants are sensitive to lexical stress patterns, instantiated primarily by suprasegmental cues, during the second half of the first year of life

Voltage-Controlled Optics of a Quantum Dot

We show how the optical properties of a single semiconductor quantum dot can be controlled with a small dc voltage applied to a gate electrode. We find that the transmission spectrum of the neutral exciton exhibits two narrow lines with $\sim 2$ $\mu$eV linewidth. The splitting into two linearly polarized components arises through an exchange interaction within the exciton. The exchange interaction can be turned off by choosing a gate voltage where the dot is occupied with an additional electron. Saturation spectroscopy demonstrates that the neutral exciton behaves as a two-level system. Our experiments show that the remaining problem for manipulating excitonic quantum states in this system is spectral fluctuation on a $\mu$eV energy scale.Comment: 4 pages, 4 figures; content as publishe

Linearization Errors in Discrete Goal-Oriented Error Estimation

Goal-oriented error estimation provides the ability to approximate the discretization error in a chosen functional quantity of interest. Adaptive mesh methods provide the ability to control this discretization error to obtain accurate quantity of interest approximations while still remaining computationally feasible. Traditional discrete goal-oriented error estimates incur linearization errors in their derivation. In this paper, we investigate the role of linearization errors in adaptive goal-oriented error simulations. In particular, we develop a novel two-level goal-oriented error estimate that is free of linearization errors. Additionally, we highlight how linearization errors can facilitate the verification of the adjoint solution used in goal-oriented error estimation. We then verify the newly proposed error estimate by applying it to a model nonlinear problem for several quantities of interest and further highlight its asymptotic effectiveness as mesh sizes are reduced. In an adaptive mesh context, we then compare the newly proposed estimate to a more traditional two-level goal-oriented error estimate. We highlight that accounting for linearization errors in the error estimate can improve its effectiveness in certain situations and demonstrate that localizing linearization errors can lead to more optimal adapted meshes

Synthesis for Polynomial Lasso Programs

We present a method for the synthesis of polynomial lasso programs. These programs consist of a program stem, a set of transitions, and an exit condition, all in the form of algebraic assertions (conjunctions of polynomial equalities). Central to this approach is the discovery of non-linear (algebraic) loop invariants. We extend Sankaranarayanan, Sipma, and Manna's template-based approach and prove a completeness criterion. We perform program synthesis by generating a constraint whose solution is a synthesized program together with a loop invariant that proves the program's correctness. This constraint is non-linear and is passed to an SMT solver. Moreover, we can enforce the termination of the synthesized program with the support of test cases.Comment: Paper at VMCAI'14, including appendi