335 research outputs found
Approximate and pseudo-amenability of various classes of Banach algebras
We continue the investigation of notions of approximate amenability that were
introduced in work of the second and third authors. It is shown that every
boundedly approximately contractible Banach algebra has a bounded approximate
identity.
Among our other results, it is shown that the Fourier algebra of the free
group on two generators is not approximately amenable. Further examples are
obtained of -semigroup algebras which are approximately amenable but
not amenable; using these, we show that bounded approximate amenability need
not imply sequential approximate amenability. Results are also given for Segal
subalgebras of , where is a locally compact group, and the algebras
of -pseudofunctions on a discrete group (of which
the reduced -algebra is a special case).Comment: 35 pages, revision of Jan '08 preprint. Abstract and MSC added;
bibliograpy updated; slight tweaks to Section 4; and correction of a few
typos. The final version is to appear in J. Funct. Ana
Photonic stop bands in quasi-random nanoporous anodic alumina structures
The existence of photonic stop bands in the self-assembled arrangement of
pores in porous anodic alumina structures is investigated by means of rigorous
2D finite- difference time-domain calculations. Self-assembled porous anodic
alumina shows a random distribution of domains, each of them with a very
definite triangular pattern, constituting a quasi-random structure. The
observed stop bands are similar to those of photonic quasicrystals or random
structures. As the pores of nanoporous anodic alumina can be infiltrated with
noble metals, nonlinear or active media, it makes this material very attractive
and cost-effective for applications including inhibition of spontaneous
emission, random lasing, LEDs and biosensors
General Latent Feature Modeling for Data Exploration Tasks
This paper introduces a general Bayesian non- parametric latent feature model
suitable to per- form automatic exploratory analysis of heterogeneous datasets,
where the attributes describing each object can be either discrete, continuous
or mixed variables. The proposed model presents several important properties.
First, it accounts for heterogeneous data while can be inferred in linear time
with respect to the number of objects and attributes. Second, its Bayesian
nonparametric nature allows us to automatically infer the model complexity from
the data, i.e., the number of features necessary to capture the latent
structure in the data. Third, the latent features in the model are
binary-valued variables, easing the interpretability of the obtained latent
features in data exploration tasks
Linear and Second-order Optical Response of the III-V Mono-layer Superlattices
We report the first fully self-consistent calculations of the nonlinear
optical properties of superlattices. The materials investigated are mono-layer
superlattices with GaP grown on the the top of InP, AlP and GaAs (110)
substrates. We use the full-potential linearized augmented plane wave method
within the generalized gradient approximation to obtain the frequency dependent
dielectric tensor and the second-harmonic-generation susceptibility. The effect
of lattice relaxations on the linear optical properties are studied. Our
calculations show that the major anisotropy in the optical properties is the
result of strain in GaP. This anisotropy is maximum for the superlattice with
maximum lattice mismatch between the constituent materials. In order to
differentiate the superlattice features from the bulk-like transitions an
improvement over the existing effective medium model is proposed. The
superlattice features are found to be more pronounced for the second-order than
the linear optical response indicating the need for full supercell calculations
in determining the correct second-order response.Comment: 9 pages, 4 figures, submitted to Phy. Rev.
Recommended from our members
Emergence of Sensory Representations Using Prediction in Partially Observable Environments
n order to explore and act autonomously in an environment,an agent can learn from the sensorimotor information that is capturedwhile acting. By extracting the regularities in this sensorimotor stream,it can build a model of the world, which in turn can be used as a basis foraction and exploration. It requires the acquisition of compact representa-tions from possibly high dimensional raw observations. In this paper, wepropose a model which integrates sensorimotor information over time,and project it in a sensory representation. It is trained by preformingsensorimotor prediction. We emphasize on a simple example the role ofmotor and memory for learning sensory representations
An Algorithmic Approach to Missing Data Problem in Modeling Human Aspects in Software Development
Background: In our previous research, we built defect prediction models by using confirmation bias metrics. Due to confirmation bias developers tend to perform unit tests to make their programs run rather than breaking their code. This, in turn, leads to an increase in defect density. The performance of prediction model that is built using confirmation bias was as good as the models that were built with static code or churn metrics.
Aims: Collection of confirmation bias metrics may result in partially "missing data" due to developers' tight schedules, evaluation apprehension and lack of motivation as well as staff turnover. In this paper, we employ Expectation-Maximization (EM) algorithm to impute missing confirmation bias data.
Method: We used four datasets from two large-scale companies. For each dataset, we generated all possible missing data configurations and then employed Roweis' EM algorithm to impute missing data. We built defect prediction models using the imputed data. We compared the performances of our proposed models with the ones that used complete data.
Results: In all datasets, when missing data percentage is less than or equal to 50% on average, our proposed model that used imputed data yielded performance results that are comparable with the performance results of the models that used complete data.
Conclusions: We may encounter the "missing data" problem in building defect prediction models. Our results in this study showed that instead of discarding missing or noisy data, in our case confirmation bias metrics, we can use effective techniques such as EM based imputation to overcome this problem
Growth and development status in the first two years of uninfected children born from HIV positive mothers
Recently prevention of HIV transmission from mother to child by antiretroviral regimens has resulted in growing the numbers of HIV exposed but uninfected children (HIV-EU). The aim of present study was evaluation of growth and neurodevelopment status among less than 2-year-old HIV exposed uninfected children. A cohort study was carried out at Vali-e-Asr Hospital (Tehran-Iran). Thirty-nine HIV-EU neonates were recruited (2014 to 2016). Neonates and infants with concern to growth and neurodevelopment status were evaluated at 6, 12, 18, and 24 months by an expert physician. Neurodevelopment assessment was based on WHO Milestones Chart and Age and Stage Questionnaire. Of all children, 22 were male, and 17 were female. Regarding growth indices, although mean birth weight in half of the neonates was lower than normal population; no postnatal descending trend was observed in their growth chart. No significant differences were found between two groups' height and head circumference. Among the neurodevelopmental parameters measured, in 6th months of life, 2 cases had abnormality in the gross motor while at 12 months, 6 cases had delay in language, social problem, and motor disorders. At 18 and 24 months, 7 infants showed developmental problems of which 71.4 of their mothers were younger than others (age<25 years, P=0.009). Prevalence of neurodevelopmental disorders including delay in language, motor, and social domains was common among HIV-EU children. As several environmental factors may involve the etiology of neurodevelopmental disorders, nearly-full postnatal control and prevention seem necessary. © 2018 Tehran University of Medical Sciences. All rights reserved
Growth and development status in the first two years of uninfected children born from HIV positive mothers
Recently prevention of HIV transmission from mother to child by antiretroviral regimens has resulted in growing the numbers of HIV exposed but uninfected children (HIV-EU). The aim of present study was evaluation of growth and neurodevelopment status among less than 2-year-old HIV exposed uninfected children. A cohort study was carried out at Vali-e-Asr Hospital (Tehran-Iran). Thirty-nine HIV-EU neonates were recruited (2014 to 2016). Neonates and infants with concern to growth and neurodevelopment status were evaluated at 6, 12, 18, and 24 months by an expert physician. Neurodevelopment assessment was based on WHO Milestones Chart and Age and Stage Questionnaire. Of all children, 22 were male, and 17 were female. Regarding growth indices, although mean birth weight in half of the neonates was lower than normal population; no postnatal descending trend was observed in their growth chart. No significant differences were found between two groups' height and head circumference. Among the neurodevelopmental parameters measured, in 6th months of life, 2 cases had abnormality in the gross motor while at 12 months, 6 cases had delay in language, social problem, and motor disorders. At 18 and 24 months, 7 infants showed developmental problems of which 71.4 of their mothers were younger than others (age<25 years, P=0.009). Prevalence of neurodevelopmental disorders including delay in language, motor, and social domains was common among HIV-EU children. As several environmental factors may involve the etiology of neurodevelopmental disorders, nearly-full postnatal control and prevention seem necessary. © 2018 Tehran University of Medical Sciences. All rights reserved
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