Dealing with Phrase Level Co-Articulation (PLC) in speech recognition: A first approach

Whereas nowadays within-word co-articulation effects are usually sufficiently dealt with in automatic speech recognition, this is not always the case with phrase level co-articulation effects (PLC). This paper describes a first approach in dealing with phrase level co-articulation by applying these rules on the reference transcripts used for training our recogniser and by adding a set of temporary PLC phones that later on will be mapped on the original phones. In fact we temporarily break down acoustic context into a general and a PLC context. With this method, more robust models could be trained because phones that are confused due to PLC effects like for example /v/-/f/ and /z/-/s/, receive their own models. A first attempt to apply this method is described

Improving information retrieval through correspondence analysis instead of latent semantic analysis

Both latent semantic analysis (LSA) and correspondence analysis (CA) are dimensionality reduction techniques that use singular value decomposition (SVD) for information retrieval. Theoretically, the results of LSA display both the association between documents and terms, and marginal effects; in comparison, CA only focuses on the associations between documents and terms. Marginal effects are usually not relevant for information retrieval, and therefore, from a theoretical perspective CA is more suitable for information retrieval. In this paper, we empirically compare LSA and CA. The elements of the raw document-term matrix are weighted, and the weighting exponent of singular values is adjusted to improve the performance of LSA. We explore whether these two weightings also improve the performance of CA. In addition, we compare the optimal singular value weighting exponents for LSA and CA to identify what the initial dimensions in LSA correspond to. The results for four empirical datasets show that CA always performs better than LSA. Weighting the elements of the raw data matrix can improve CA; however, it is data dependent and the improvement is small. Adjusting the singular value weighting exponent usually improves the performance of CA; however, the extent of the improved performance depends on the dataset and number of dimensions. In general, CA needs a larger singular value weighting exponent than LSA to obtain the optimal performance. This indicates that CA emphasizes initial dimensions more than LSA, and thus, margins play an important role in the initial dimensions in LSA

Geometric stoichiometry: unifying concepts of animal nutrition to understand how protein-rich diets can be “too much of a good thing”

Understanding the factors that control the growth of heterotrophic organisms is central to predicting food web interactions and biogeochemical cycling within ecosystems. We present a new framework, Geometric Stoichiometry (GS), that unifies the disciplines of Nutritional Geometry (NG) and Ecological Stoichiometry (ES) by extending the equations of ES to incorporate core NG concepts, including macromolecules as currencies and the ability of animals to select foods that balance deficits and excesses of nutrients. The resulting model is used to investigate regulation of consumer growth by dietary protein:carbohydrate ratio. Growth on protein-poor diets is limited by nitrogen. Likewise, we show that growth is also diminished on protein-rich diets and that this can be mechanistically explained by means of a metabolic penalty that arises when animals use protein for energy generation. These penalties, which are incurred when dealing with the costs of producing and excreting toxic nitrogenous waste, have not hitherto been represented in standard ES theory. In order to incorporate GS within ecosystem and biogeochemical models, a new generation of integrated theoretical and experimental studies based on unified concepts of NG and ES is needed, including measurements of food selection, biomass, growth and associated physiology, and involving metabolic penalties

Positive Body Image and Sexual Functioning in Dutch Female University Students: The Role of Adult Romantic Attachment

This study focused on links between romantic attachment, positive body image, and sexual functioning. Dutch female university students (N = 399) completed an online survey that included self-report items about body appreciation, sexual functioning, and romantic attachment. A proposed conceptual model was tested using structural equation modeling and a good fit to the data was found. Results revealed that attachment avoidance in a romantic context was negatively related to sexual arousal, vaginal lubrication, the ability to reach orgasm, and sexual satisfaction. Attachment anxiety was negatively related to body appreciation which, in turn, was positively related to sexual desire and arousal. Findings indicated that romantic attachment is meaningfully linked to body appreciation and sexual functioning. Therefore, the concept of adult attachment may be a useful tool for the treatment of sexual problems of young women

Grazing Rates of Calanus finmarchicus on Thalassiosira weissflogii Cultured under Different Levels of Ultraviolet Radiation

UVB alters photosynthetic rate, fatty acid profiles and morphological characteristics of phytoplankton. Copepods, important grazers of primary production, select algal cells based upon their size, morphological traits, nutritional status, and motility. We investigated the grazing rates of the copepod Calanus finmarchicus on the diatom Thalassiosira weissflogii cultured under 3 levels of ultraviolet radiation (UVR): photosynthetically active radiation (PAR) only (4 kJ-m−2/day), and PAR supplemented with UVR radiation at two intensities (24 kJ-m−2/day and 48 kJ-m−2/day). There was no significant difference in grazing rates between the PAR only treatment and the lower UVR treatment. However, grazing rates were significantly (∼66%) higher for copepods feeding on cells treated with the higher level of UVR. These results suggest that a short-term increase in UVR exposure results in a significant increase in the grazing rate of copepods and, thereby, potentially alters the flow rate of organic matter through this component of the ecosystem

An evidence-based framework for predicting the impact of differing autotroph-heterotroph thermal sensitivities on consumer-prey dynamics

Increased temperature accelerates vital rates, influencing microbial population and wider ecosystem dynamics, for example, the predicted increases in cyanobacterial blooms associated with global warming. However, heterotrophic and mixotrophic protists, which are dominant grazers of microalgae, may be more thermally sensitive than autotrophs, and thus prey could be suppressed as temperature rises. Theoretical and meta-analyses have begun to address this issue, but an appropriate framework linking experimental data with theory is lacking. Using ecophysiological data to develop a novel model structure, we provide the first validation of this thermal sensitivity hypothesis: increased temperature improves the consumer’s ability to control the autotrophic prey. Specifically, the model accounts for temperature effects on auto- and mixotrophs and ingestion, growth and mortality rates, using an ecologically and economically important system (cyanobacteria grazed by a mixotrophic flagellate). Once established, we show the model to be a good predictor of temperature impacts on consumer–prey dynamics by comparing simulations with microcosm observations. Then, through simulations, we indicate our conclusions remain valid, even with large changes in bottom-up factors (prey growth and carrying capacity). In conclusion, we show that rising temperature could, counterintuitively, reduce the propensity for microalgal blooms to occur and, critically, provide a novel model framework for needed, continued assessment

Global data set of long-term summertime vertical temperature profiles in 153 lakes

Climate change and other anthropogenic stressors have led to long-term changes in the thermal structure, including surface temperatures, deepwater temperatures, and vertical thermal gradients, in many lakes around the world. Though many studies highlight warming of surface water temperatures in lakes worldwide, less is known about long-term trends in full vertical thermal structure and deepwater temperatures, which have been changing less consistently in both direction and magnitude. Here, we present a globally-expansive data set of summertime in-situ vertical temperature profiles from 153 lakes, with one time series beginning as early as 1894. We also compiled lake geographic, morphometric, and water quality variables that can influence vertical thermal structure through a variety of potential mechanisms in these lakes. These long-term time series of vertical temperature profiles and corresponding lake characteristics serve as valuable data to help understand changes and drivers of lake thermal structure in a time of rapid global and ecological change

Global data set of long-term summertime vertical temperature profiles in 153 lakes

Measurement(s) : temperature of water, temperature profile Technology Type(s) : digital curation Factor Type(s) : lake location, temporal interval Sample Characteristic - Environment : lake, reservoir Sample Characteristic - Location : global Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.14619009Climate change and other anthropogenic stressors have led to long-term changes in the thermal structure, including surface temperatures, deepwater temperatures, and vertical thermal gradients, in many lakes around the world. Though many studies highlight warming of surface water temperatures in lakes worldwide, less is known about long-term trends in full vertical thermal structure and deepwater temperatures, which have been changing less consistently in both direction and magnitude. Here, we present a globally-expansive data set of summertime in-situ vertical temperature profiles from 153 lakes, with one time series beginning as early as 1894. We also compiled lake geographic, morphometric, and water quality variables that can influence vertical thermal structure through a variety of potential mechanisms in these lakes. These long-term time series of vertical temperature profiles and corresponding lake characteristics serve as valuable data to help understand changes and drivers of lake thermal structure in a time of rapid global and ecological change