A system design for human factors studies of speech-enabled Web browsing

This paper describes the design of a system which will subsequently be used as the basis of a range of empirical studies aimed at discovering how best to harness speech recognition capabilities in multimodal multimedia computing. Initial work focuses on speech-enabled browsing of the World Wide Web, which was never designed for such use. System design is complete, and is being evaluated via usability testing

Fr\'echet frames, general definition and expansions

We define an {\it $(X_1,\Theta, X_2)$-frame} with Banach spaces $X_2\subseteq X_1$, $|\cdot|_1 \leq |\cdot|_2$, and a $BK$-space (\Theta, \snorm[\cdot]). Then by the use of decreasing sequences of Banach spaces ${X_s}_{s=0}^\infty$ and of sequence spaces ${\Theta_s}_{s=0}^\infty$, we define a general Fr\' echet frame on the Fr\' echet space $X_F=\bigcap_{s=0}^\infty X_s$. We give frame expansions of elements of $X_F$ and its dual $X_F^*$, as well of some of the generating spaces of $X_F$ with convergence in appropriate norms. Moreover, we give necessary and sufficient conditions for a general pre-Fr\' echet frame to be a general Fr\' echet frame, as well as for the complementedness of the range of the analysis operator $U:X_F\to\Theta_F$.Comment: A new section is added and a minor revision is don

Regularity properties of distributions through sequences of functions

We give necessary and sufficient criteria for a distribution to be smooth or uniformly H\"{o}lder continuous in terms of approximation sequences by smooth functions; in particular, in terms of those arising as regularizations $(T\ast\phi_{n})$.Comment: 10 page

The application of natural organic compounds in bakery industry

Investigations include the analysis of the impact of commercial products: complex additive (0.1, 0.3, and 0.5%), L-ascorbic acid (0.002, 0.004 and 0.012%), diacetyl ester of tartaric acid with monoglycerides (DATEM E472e, 0.1, 0.3, and 0.5%), α-amylase (0.002, 0.006 and 0.012%), xylanase (0.004, 0.012 and 0.024%), alcohol extract of rosemary, thyme or sage (0.5, 1.0 and 2.0%), as well as the combination of complex additive and rosemary, thyme and sage extract on rheological characteristics of dough. The study includes amylograph, farinograph and extensograph analysis of dough with and without additives (control sample). The volume of lost CO2 gas (mL) is the lowest in dough samples with an added combination of complex additive and thyme extract (0.05 and 0.5%) and rosemary extract (2.0%). In the samples with thyme extract (1.0%) added, the volume of lost gas is at a level of samples with added complex additive, DATEM, and L-ascorbic acid

Evolutionary biology for the 21st century

New theoretical and conceptual frameworks are required for evolutionary biology to capitalize on the wealth of data now becoming available from the study of genomes, phenotypes, and organisms - including humans - in their natural environments.Molecular and Cellular BiologyOrganismic and Evolutionary Biolog

Second Life of Lithium-Ion Batteries of Electric Vehicles: A Short Review and Perspectives

Technological advancement in storage systems has currently stimulated their use in miscellaneous applications. The devices have gained prominence due to their increased performance and efficiency, together with the recent global appeal for reducing the environmental impacts caused by generating power or by combustion vehicles. Many technologies have been developed to allow these devices to be reused or recycled. In this sense, the use of lithium-ion batteries, especially in electric vehicles, has been the central investigative theme. However, a drawback of this process is discarding used batteries. This work provides a short review of the techniques used for the second-life batteries of electric vehicles and presents the current positioning of the field, the steps involved in the process of reuse and a discussion on important references. In conclusion, some directions and perspectives of the field are shown

Communal mastery and associations with depressive and PTSD symptomatology among urban trauma-exposed women.

Objective: Racial and ethnic minority women from low-resource urban communities experience disproportionately high rates of trauma exposure. Higher rates of lifetime trauma exposure are strongly associated with subsequent psychological sequela, specifically depression and posttraumatic stress disorder (PTSD). Communal mastery is the ability to cope with challenges and achieve goals by being closely interconnected with friends, family, and significant others. Yet, it is unknown if communal mastery is protective specifically against PTSD and depressive symptoms. Method: Participants (N = 131) were Black and Latina women (88.5% Black, mean monthly income: < $750) recruited from an urban outpatient obstetric-gynecological clinic at an academic medical center. Participants completed an online questionnaire that assessed trauma history, PTSD and depressive symptoms, types of individualistic coping, social support, and communal mastery. Results: Hierarchical multiple regression models demonstrated that communal mastery is uniquely associated with fewer PTSD symptoms (β = −.23, p = .003). More severe trauma history, more use of passive coping skills, and poorer social support were also significantly associated with PTSD symptoms, explaining over half of the variance in PTSD symptoms. Although significantly correlated, communal mastery was not uniquely associated with fewer depressive symptoms (β = −.13, p = .201). Conclusions: These findings suggest that connectedness as assessed through communal mastery serves as an important shield against the effects of traumatic stress for Black and Latina women. Future research would benefit by exploring interventions that aim to increase communal mastery in order to help highly trauma-exposed racial and ethnic minority women in low-resource environments

HOMFLY and superpolynomials for figure eight knot in all symmetric and antisymmetric representations

Explicit answer is given for the HOMFLY polynomial of the figure eight knot $4_1$ in arbitrary symmetric representation R=[p]. It generalizes the old answers for p=1 and 2 and the recently derived results for p=3,4, which are fully consistent with the Ooguri-Vafa conjecture. The answer can be considered as a quantization of the \sigma_R = \sigma_{[1]}^{|R|} identity for the "special" polynomials (they define the leading asymptotics of HOMFLY at q=1), and arises in a form, convenient for comparison with the representation of the Jones polynomials as sums of dilogarithm ratios. In particular, we construct a difference equation ("non-commutative A-polynomial") in the representation variable p. Simple symmetry transformation provides also a formula for arbitrary antisymmetric (fundamental) representation R=[1^p], which also passes some obvious checks. Also straightforward is a deformation from HOMFLY to superpolynomials. Further generalizations seem possible to arbitrary Young diagrams R, but these expressions are harder to test because of the lack of alternative results, even partial.Comment: 14 page

Introduction to Khovanov Homologies. I. Unreduced Jones superpolynomial

An elementary introduction to Khovanov construction of superpolynomials. Despite its technical complexity, this method remains the only source of a definition of superpolynomials from the first principles and therefore is important for development and testing of alternative approaches. In this first part of the review series we concentrate on the most transparent and unambiguous part of the story: the unreduced Jones superpolynomials in the fundamental representation and consider the 2-strand braids as the main example. Already for the 5_1 knot the unreduced superpolynomial contains more items than the ordinary Jones.Comment: 33 page

Neural-Based Ensembles and Unorganized Machines to Predict Streamflow Series from Hydroelectric Plants

Estimating future streamflows is a key step in producing electricity for countries with hydroelectric plants. Accurate predictions are particularly important due to environmental and economic impact they lead. In order to analyze the forecasting capability of models regarding monthly seasonal streamflow series, we realized an extensive investigation considering: six versions of unorganized machines—extreme learning machines (ELM) with and without regularization coefficient (RC), and echo state network (ESN) using the reservoirs from Jaeger’s and Ozturk et al., with and without RC. Additionally, we addressed the ELM as the combiner of a neural-based ensemble, an investigation not yet accomplished in such context. A comparative analysis was performed utilizing two linear approaches (autoregressive model (AR) and autoregressive and moving average model (ARMA)), four artificial neural networks (multilayer perceptron, radial basis function, Elman network, and Jordan network), and four ensembles. The tests were conducted at five hydroelectric plants, using horizons of 1, 3, 6, and 12 steps ahead. The results indicated that the unorganized machines and the ELM ensembles performed better than the linear models in all simulations. Moreover, the errors showed that the unorganized machines and the ELM-based ensembles reached the best general performances