2D silhouette and 3D skeletal models for human detection and tracking

In this paper we propose a statistical model for detection and tracking of human silhouette and the corresponding 3D skeletal structure in gait sequences. We follow a point distribution model (PDM) approach using a Principal Component Analysis (PCA). The problem of non-lineal PCA is partially resolved by applying a different PDM depending of pose estimation; frontal, lateral and diagonal, estimated by Fisher's linear discriminant. Additionally, the fitting is carried out by selecting the closest allowable shape from the training set by means of a nearest neighbor classifier. To improve the performance of the model we develop a human gait analysis to take into account temporal dynamic to track the human body. The incorporation of temporal constraints on the model increase reliability and robustness.

CoMFA and homology-based models of the glycine binding site of N-methyl-D-aspartate receptor

Homology modeling was used to build 3D models of the N-methyl-D-aspartate (NMDA) receptor glycine binding site on the basis of an X-ray structure of the water-soluble AMPA-sensitive receptor. The docking of agonists and antagonists to these models was used to reveal binding modes of ligands and to explain known structure-activity relationships. Two types of quantitative models, 3D-QSAR/CoMFA and a regression model based on docking energies, were built for antagonists (derivatives of 4-hydroxy-2-quinolone, quinoxaline-2,3-dione, and related compounds). The CoMFA steric and electrostatic maps were superimposed on the homology-based model, and a close correspondence was marked. The derived computational models have permitted the evaluation of the structural features crucial for high glycine binding site affinity and are important for the design of new ligands.

Learning Effective and Interpretable Semantic Models using Non-Negative Sparse Embedding

In this paper, we introduce an application of matrix factorization to produce corpus-derived, distributional
models of semantics that demonstrate cognitive plausibility. We find that word representations
learned by Non-Negative Sparse Embedding (NNSE), a variant of matrix factorization, are sparse,
effective, and highly interpretable. To the best of our knowledge, this is the first approach which
yields semantic representation of words satisfying these three desirable properties. Though extensive
experimental evaluations on multiple real-world tasks and datasets, we demonstrate the superiority
of semantic models learned by NNSE over other state-of-the-art baselines.

ivlewbel: Uses heteroscedasticity to estimate mismeasured and endogenous regressor models

GMM estimation of triangular systems using heteroscedasticity based instrumental variables as in Lewbel (2012).

Efficient Network in Player and Partner Heterogeneity Models

This paper characterizes efficient networks in player and partner heterogeneity models for both the one-way flow and the two-way flow models. Player (partner) dependent network formation allows benefits and costs to be player (partner) heterogeneous which is an important extension for modeling social networks in the real world. Employing widely used assumptions, I show that efficient networks in the two way flow model are minimally connected and have star or derivative of star type architectures, whereas efficient networks in the one way flow model have wheel architectures.

Combining global climate and regional landscape models to improve prediction of invasion risk

Aim
It is widely acknowledged that species distributions result from a variety of biotic and abiotic factors operating at different spatial scales. Here, we aimed to (1) determine the extent to which global climate niche models (CNMs) can be improved by the addition of fine-scale regional data; (2) examine climatic and environmental factors influencing the range of 15 invasive aquatic plant species; and (3) provide a case study for the use of such models in invasion management on an island.

Location
Global, with a case study of species invasions in Ireland.

Methods
Climate niche models of global extent (including climate only) and regional environmental niche models (with additional factors such as human influence, land use and soil characteristics) were generated using maxent for 15 invasive aquatic plants. The performance of these models within the invaded range of the study species in Ireland was assessed, and potential hotspots of invasion suitability were determined. Models were projected forward up to 2080 based on two climate scenarios.

Results
While climate variables are important in defining the global range of species, factors related to land use and nutrient level were of greater importance in regional projections. Global climatic models were significantly improved at the island scale by the addition of fine-scale environmental variables (area under the curve values increased by 0.18 and true skill statistic values by 0.36), and projected ranges decreased from an average of 86% to 36% of the island.

Main conclusions
Refining CNMs with regional data on land use, human influence and landscape may have a substantial impact on predictive capacity, providing greater value for prioritization of conservation management at subregional or local scales.

Current Developments in Fluorescent PET (Photoinduced Electron Transfer) Sensors and Switches

Following a brief introduction to the principle of fluorescent PET (photoinduced electron transfer) sensors and switches, the outputs of laboratories in various countries from the past year or two are categorized and critically discussed. Emphasis is placed on the molecular design and the experimental outcomes in terms of target-induced fluorescence enhancements and input/output wavelengths. The handling of single targets takes up a major fraction of the review, but the extension to multiple targets is also illustrated. Conceptually new channels of investigation are opened up by the latter approach, e.g. ‘lab-on-a-molecule’ systems and molecular keypad locks. The growing trends of theoretically-fortified design and intracellular application are pointed out.

Pathways Project Final Report Volume 1: Field Investigation and Catchment Conceptual Models

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Executive Summary
The Pathways Project field studies were targeted at improving the understanding of contaminant transport along different hydrological pathways in Irish catchments, including their associated impacts on water quality and river ecology. The contaminants of interest were phosphorus, nitrogen and sediment. The working Pathways conceptual model included overland flow, interflow, shallow groundwater flow, and deep groundwater flow. This research informed the development of a set of Catchment Management Support Tools (CMSTs) comprising an Exploratory Tool, Catchment Characterization Tool (CCT) and Catchment Modelling Tool (CMT) as outlined in Pathways Project Final Reports Volumes 3 and 4.
In order to inform the CMST, four suitable study catchments were selected following an extensive selection process, namely the Mattock catchment, Co. Louth/Meath; Gortinlieve catchment, Co. Donegal; Nuenna catchment, Co. Kilkenny and the Glen Burn catchment, Co. Down. The Nuenna catchment is well drained as it is underlain by a regionally important karstified limestone aquifer with permeable limestone tills and gravels, while the other three catchments are underlain by poorly productive aquifers and low permeability clayey tills, and are poorly drained.
All catchments were instrumented, and groundwater, surface and near-surface water and aquatic ecology were monitored for a period of two years. Intensive water quality sampling during rainfall events was used to investigate the pathways delivering nutrients. The proportion of flow along each pathway was determined using chemical and physical hydrograph separation techniques, supported by numerical modelling.
The outcome of the field studies broadly supported the use of the initial four-pathway conceptual model used in the Pathways CMT (time-variant model). The artificial drainage network was found to be a significant contributing pathway in the poorly drained catchments, at low flows and during peak flows in wet antecedent conditions. The transition zone (TZ), i.e. the broken up weathered zone at the top of the bedrock, was also found to be an important pathway. It was observed to operate in two contrasting hydrogeological scenarios: in groundwater discharge zones the TZ can be regarded as being part of the shallow groundwater pathway, whereas in groundwater recharge zones it behaves more like interflow.
In the catchments overlying poorly productive aquifers, only a few fractures or fracture zones were found to be hydraulically active and the TZ, where present, was the main groundwater pathway. In the karstified Nuenna catchment, the springs, which are linked to conduits as well as to a diffuse fracture network, delivered the majority of the flow. These findings confirm the two-component groundwater contribution from bedrock but suggest that the size and nature of the hydraulically active fractures and the nature of the TZ are the dominant factors at the scale of a stream flow event.
Diffuse sources of nitrate were found to be typically delivered via the subsurface pathways, especially in the TZ and land drains in the poorly productive aquifer catchments, and via the bedrock groundwater in the Nuenna. Phosphorus was primarily transported via overland flow in both particulate and soluble forms. Where preferential flow paths existed in the soil and subsoil, soluble P, and to a lesser extent particulate P, were also transported via the TZ and in drains and ditches. Arable land was found to be the most important land use for
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the delivery of sediment, although channel bank and in-stream sources were the most significant in the Glen Burn catchment. Overland flow was found to be the predominant transport sediment pathway in the poorly productive catchments. These findings informed the development of the transport and attenuation equations used in the CCT and CMT. From an assessment of the relationship between physico-chemical and biological conditions, it is suggested that in the Nuenna, Glen Burn and Gortinlieve catchments, a relationship may exist between biological water quality and nitrogen concentrations, as well as with P. In the Nuenna, there was also a relationship between macroinvertebrate status and alkalinity.
Further research is recommended on the transport and delivery of phosphorus in groundwater, the transport and attenuation dynamics in the TZ in different hydrogeological settings and the relationship between macroinvertebrates and co-limiting factors. High resolution temporal and spatial sampling was found to be important for constraining the conceptual understanding of nutrient and sediment dynamics which should also be considered in future studies.

An improved TLBO with elite strategy for parameters identification of PEM fuel cell and solar cell models

Clean and renewable energy generation and supply has drawn much attention worldwide in recent years, the proton exchange membrane (PEM) fuel cells and solar cells are among the most popular technologies. Accurately modeling the PEM fuel cells as well as solar cells is critical in their applications, and this involves the identification and optimization of model parameters. This is however challenging due to the highly nonlinear and complex nature of the models. In particular for PEM fuel cells, the model has to be optimized under different operation conditions, thus making the solution space extremely complex. In this paper, an improved and simplified teaching-learning based optimization algorithm (STLBO) is proposed to identify and optimize parameters for these two types of cell models. This is achieved by introducing an elite strategy to improve the quality of population and a local search is employed to further enhance the performance of the global best solution. To improve the diversity of the local search a chaotic map is also introduced. Compared with the basic TLBO, the structure of the proposed algorithm is much simplified and the searching ability is significantly enhanced. The performance of the proposed STLBO is firstly tested and verified on two low dimension decomposable problems and twelve large scale benchmark functions, then on the parameter identification of PEM fuel cell as well as solar cell models. Intensive experimental simulations show that the proposed STLBO exhibits excellent performance in terms of the accuracy and speed, in comparison with those reported in the literature.

Sustained inhibition of deacetylases is required for the antitumor activity of the histone deactylase inhibitors panobinostat and vorinostat in models of colorectal cancer

Despite compelling preclinical data in colorectal cancer (CRC), the efficacy of HDACIs has been disappointing in the clinic. The goal of this study was to evaluate the effectiveness of vorinostat and panobinostat in a dose- and exposure-dependent manner in order to better understand the dynamics of drug action and antitumor efficacy. In a standard 72 h drug exposure MTS assay, notable concentration-dependent antiproliferative effects were observed in the IC50 range of 1.2-2.8 μmol/L for vorinostat and 5.1-17.5 nmol/L for panobinostat. However, shorter clinically relevant exposures of 3 or 6 h failed to elicit any significant growth inhibition and in most cases a >24 h exposure to vorinostat or panobinostat was required to induce a sigmoidal dose-response. Similar results were observed in colony formation assays where ≥ 24 h of exposure was required to effectively reduce colony formation. Induction of acetyl-H3, acetyl-H4 and p21 by vorinostat were transient and rapidly reversed within 12 h of drug removal. In contrast, panobinostat-induced acetyl-H3, acetyl-H4, and p21 persisted for 48 h after an initial 3 h exposure. Treatment of HCT116 xenografts with panobinostat induced significant increases in acetyl-H3 and downregulation of thymidylate synthase after treatment. Although HDACIs exert both potent growth inhibition and cytotoxic effects when CRC cells were exposed to drug for ≥ 24 h, these cells demonstrate an inherent ability to survive HDACI concentrations and exposure times that exceed those clinically achievable. Continued efforts to develop novel HDACIs with improved pharmacokinetics/phamacodynamics, enhanced intratumoral delivery and class/isoform-specificity are needed to improve the therapeutic potential of HDACIs and HDACI-based combination regimens in solid tumors.