Age model and pollen analysis from site GIK16867 in the northern Angola Basin

Sporomorphs and dinoflagellate cysts from site GIK16867 in the northern Angola Basin record the vegetation history of the West African forest during the last 700 ka in relation to changes in salinity and productivity of the eastern Gulf of Guinea. During most cool and cold periods, the Afromontane forest, rather than the open grass-rich dry forest, expanded to lower altitudes partly replacing the lowland rain forest of the borderlands east of the Gulf of Guinea. Except in Stage 3, when oceanic productivity was high during a period of decreased atmospheric circulation, high oceanic productivity is correlated to strong winds. The response of marine productivity in the course of a climatic cycle, however, is earlier than that of wind vigour and makes wind-stress-induced oceanic upwelling in the area less likely. Monsoon variation is well illustrated by the pollen record of increased lowland rain forest that is paired to the dinoflagellate cyst record of decreased salinity forced by increased precipitation and run-off.

A Simple Model Describes Development of Early Peaks in Oomycete Zoospore Inoculum Detected in Southern UK Outdoors Horticultural Reservoirs

The numbers of water-borne oomycete propagules in outdoor reservoirs used in horticultural nurseries within the UK are investigated in this study. Water samples were recovered from 11 different horticultural nurseries in the southern UK during Jan-May in two ‘cool’ years (2010.and 2013; winter temperatures 2.0 and 0.4oC below UK Met Office 30 year winter average respectively) and two ‘warm’ years (2008 and 2012; winter temperatures 1.2 and 0.9oC above UK Met Office 30 year winter average respectively). Samples were analysed for total number of oomycete colony forming units (CFU), predominantly members of the families Saprolegniaceae and Pythiaceae, and these were combined to give monthly mean counts. The numbers of CFU were investigated with respect to prevailing climate in the region: mean monthly air temperatures calculated by using daily observations from the nearest climatological station. The investigations show that the number of CFU during spring can be explained by a linear first-order equation and a statistically significant r2 value of 0.66 with the simple relationship: [CFU] = a(T-Tb )-b, where a is the rate of inoculum development with temperature T, and b is the baseload population at temperatures below Tb. Despite the majority of oomycete CFU detected being non-phytopathogenic members of the Saprolegniaceae, total oomycete CFU counts are still of considerable value as indicators of irrigation water treatment efficacy and cleanliness of storage tanks. The presence/absence of Pythium spp. was also determined for all samples tested, and Pythium CFU were found to be present in the majority, the exceptions all being particularly cold months (January and February 2010 and January 2008). A simple scenario study (+2 deg C) suggests that abundance of water-borne oomycetes during spring could be affected by increased temperatures due to climate change.

Outer crust of a cold non-accreting magnetar

The outer-crust structure and composition of a cold, non-accreting magnetar are studied. We model the outer crust to be made of fully equilibrated matter where ionized nuclei form a Coulomb crystal embedded in an electron gas. The main effects of the strong magnetic field are those of quantizing the electron motion in Landau levels and of modifying the nuclear single-particle levels producing, on average, an increased binding of nucleons in nuclei present in the Coulomb lattice. The effect of a homogeneous and constant magnetic field on nuclear masses has been predicted by using a covariant density functional in which induced currents and axial deformation due to the presence of a magnetic field that breaks time-reversal symmetry have been included self-consistently in the nucleon and meson equations of motion. Although not yet observed, for Ba 1016 G both effects contribute to produce different compositions - odd-mass nuclei are frequently predicted - and to increase the neutron-drip pressure as compared to a typical neutron star. Specifically, in such a regime, the magnetic-field effects on nuclei favor the appearance of heavier nuclei at low pressures. As B increases, such heavier nuclei are also preferred up to larger pressures. For the most extreme magnetic field considered, B=1018 G, and for the models studied, almost the whole outer crust is made of 4092Zr52.

Convective Cold Pools over the Atlas Mountains and Their Influence on the Saharan Heat Low

The West African Monsoon (WAM) and its representation in numerical models are strongly influenced by the Saharan Heat Low (SHL), a low-pressure system driven by radiative heating over the central Sahara and ventilated by the cold and moist inflow from adjacent oceans. It has recently been shown that a significant part of the southerly moisture flux into the SHL originates from convective cold pools over the Sahel. These density currents driven by evaporation of rain are largely absent in models with parameterized convection. This crucial issue has been hypothesized to contribute to the inability of many climate models to reproduce the variability of the WAM. Here, the role of convective cold pools approaching the SHL from the Atlas Mountains, which are a strong orographic trigger for deep convection in Northwest Africa, is analyzed. Knowledge about the frequency of these events, as well as their impact on large-scale dynamics, is required to understand their contribution to the variability of the SHL and to known model uncertainties. The first aspect is addressed through the development of an objective and automated method for the generation of multi-year climatologies not available before. The algorithm combines freely available standard surface observations with satellite microwave data. Representativeness of stations and influence of their spatial density are addressed by comparison to a satellite-only climatology. Applying this algorithm to data from automated weather stations and manned synoptic stations in and south of the Atlas Mountains reveals the frequent occurrence. On the order of 6 events per month are detected from May to September when the SHL is in its northernmost position. The events tend to cluster into several-days long convectively active periods, often with strong events on consecutive days. This study is the first to diagnose dynamical impacts of such periods on the SHL, based on simulations of two example cases using the Weather Research and Forecast (WRF) model at convection-permitting resolution. Sensitivity experiments with artificially removed cold pools as well as different resolutions and parameterizations are conducted. Results indicate increases in surface pressure of more than 1 hPa and significant moisture transports into the desert over several days. This moisture affects radiative heating and thus the energy balance of the SHL. Even though cold pool events north of the SHL are less frequent when compared to their Sahelian counterparts, it is shown that they gain importance due to their temporal clustering on synoptic timescale. Together with studies focusing on the Sahel, this work emphasizes the need for improved parameterization schemes for deep convection in order to produce more reliable climate projections for the WAM.

Waterpower : a geophysical and archaeological investigation of the waterpower system at the West Point Foundry, Cold Spring, New York

Waterpower: A Geophysical and Archaeological Investigation of the Waterpower System at the West Point Foundry, Cold Spring, New York, describes the results of ground penetrating radar surveys and archaeological excavation undertaken by Michigan Technological University (MTU) archaeologists during the summer of 2003 at the West Point Foundry, Cold Spring, New York. 2003 constituted MTU's second field season at the foundry. Fieldwork concentrated on the foundry's waterpower system, an intricate network of surface and subsurface drains, races, flumes, waterwheels, turbines, dams, and ponds that powered operations and regulated water flow throughout the site. Archaeologists utilized non-destructive geophysical technology, which expedited survey, facilitated placement of excavation units, and provided a model for future archaeogeophysical research at industrial sites. Features discovered during excavation provided valuable information pertaining to the waterpower system's construction and its functions. Data from ground penetrating radar surveys, archaeological excavation, historical photographs, documents, and maps permitted the development of a provisional chronology of the development of various components of the West Point Foundry's waterpower system. Information gathered during this project serves as an aid in sit interpretation and rehabilitation.

Collaborative filtering and deep learning based recommendation system for cold start items

Recommender system is a specific type of intelligent systems, which exploits historical user ratings on items and/or auxiliary information to make recommendations on items to the users. It plays a critical role in a wide range of online shopping, e-commercial services and social networking applications. Collaborative filtering (CF) is the most popular approaches used for recommender systems, but it suffers from complete cold start (CCS) problem where no rating record are available and incomplete cold start (ICS) problem where only a small number of rating records are available for some new items or users in the system. In this paper, we propose two recommendation models to solve the CCS and ICS problems for new items, which are based on a framework of tightly coupled CF approach and deep learning neural network. A specific deep neural network SADE is used to extract the content features of the items. The state of the art CF model, timeSVD++, which models and utilizes temporal dynamics of user preferences and item features, is modified to take the content features into prediction of ratings for cold start items. Extensive experiments on a large Netflix rating dataset of movies are performed, which show that our proposed recommendation models largely outperform the baseline models for rating prediction of cold start items. The two proposed recommendation models are also evaluated and compared on ICS items, and a flexible scheme of model retraining and switching is proposed to deal with the transition of items from cold start to non-cold start status. The experiment results on Netflix movie recommendation show the tight coupling of CF approach and deep learning neural network is feasible and very effective for cold start item recommendation. The design is general and can be applied to many other recommender systems for online shopping and social networking applications. The solution of cold start item problem can largely improve user experience and trust of recommender systems, and effectively promote cold start items.

Collaborative filtering and deep learning based hybrid recommendation for cold start problem

Recommender systems (RS) are used by many social networking applications and online e-commercial services. Collaborative filtering (CF) is one of the most popular approaches used for RS. However traditional CF approach suffers from sparsity and cold start problems. In this paper, we propose a hybrid recommendation model to address the cold start problem, which explores the item content features learned from a deep learning neural network and applies them to the timeSVD++ CF model. Extensive experiments are run on a large Netflix rating dataset for movies. Experiment results show that the proposed hybrid recommendation model provides a good prediction for cold start items, and performs better than four existing recommendation models for rating of non-cold start items.

Good is generally more alike than bad in the information ecology: Investigating the case of (the ABC model of) group stereotypes

On most if not all evaluatively relevant dimensions such as the temperature level, taste intensity, and nutritional value of a meal, one range of adequate, positive states is framed by two ranges of inadequate, negative states, namely too much and too little. This distribution of positive and negative states in the information ecology results in a higher similarity of positive objects, people, and events to other positive stimuli as compared to the similarity of negative stimuli to other negative stimuli. In other words, there are fewer ways in which an object, a person, or an event can be positive as compared to negative. Oftentimes, there is only one way in which a stimulus can be positive (e.g., a good meal has to have an adequate temperature level, taste intensity, and nutritional value). In contrast, there are many different ways in which a stimulus can be negative (e.g., a bad meal can be too hot or too cold, too spicy or too bland, or too fat or too lean). This higher similarity of positive as compared to negative stimuli is important, as similarity greatly impacts speed and accuracy on virtually all levels of information processing, including attention, classification, categorization, judgment and decision making, and recognition and recall memory. Thus, if the difference in similarity between positive and negative stimuli is a general phenomenon, it predicts and may explain a variety of valence asymmetries in cognitive processing (e.g., positive as compared to negative stimuli are processed faster but less accurately). In my dissertation, I show that the similarity asymmetry is indeed a general phenomenon that is observed in thousands of words and pictures. Further, I show that the similarity asymmetry applies to social groups. Groups stereotyped as average on the two dimensions agency / socio-economic success (A) and conservative-progressive beliefs (B) are stereotyped as positive or high on communion (C), while groups stereotyped as extreme on A and B (e.g., managers, homeless people, punks, and religious people) are stereotyped as negative or low on C. As average groups are more similar to one another than extreme groups, according to this ABC model of group stereotypes, positive groups are mentally represented as more similar to one another than negative groups. Finally, I discuss implications of the ABC model of group stereotypes, pointing to avenues for future research on how stereotype content shapes social perception, cognition, and behavior.

Finite element modeling of tube deformation during cold pilgering

A three-dimensional finite element model of cold pilgering of stainless steel tubes is developed in this paper. The objective is to use the model to increase the understanding of forces and deformations in the process. The focus is on the influence of vertical displacements of the roll stand and axial displacements of the mandrel and tube. Therefore, the rigid tools and the tube are supported with elastic springs. Additionally, the influences of friction coefficients in the tube/mandrel and tube/roll interfaces are examined. A sensitivity study is performed to investigate the influences of these parameters on the strain path and the roll separation force. The results show the importance of accounting for the displacements of the tube and rigid tools on the roll separation force and the accumulative plastic strain.

An approximate method for the solution of an influence function foil rolling model

Fleck and Johnson (Int. J. Mech. Sci. 29 (1987) 507) and Fleck et al. (Proc. Inst. Mech. Eng. 206 (1992) 119) have developed foil rolling models which allow for large deformations in the roll profile, including the possibility that the rolls flatten completely. However, these models require computationally expensive iterative solution techniques. A new approach to the approximate solution of the Fleck et al. (1992) Influence Function Model has been developed using both analytic and approximation techniques. The numerical difficulties arising from solving an integral equation in the flattened region have been reduced by applying an Inverse Hilbert Transform to get an analytic expression for the pressure. The method described in this paper is applicable to cases where there is or there is not a flat region.