Detrimental effects of alien mink predation on small mammal populations and cascading effects on plants in the Baltic Sea archipelago

Siirretty Doriast

Working memory and cued recall

Previous research has found that individuals with high working memory have greater recall capabilities than those with low working memory (Unsworth, Spiller, & Brewers, 2012). Research did not test the extent to which cues affect one’s recall ability in relation to working memory. The present study will examine this issue. Participants completed a working memory measure. Then, they were provided with cued recall tasks whereby they recalled Facebook friends. The cues varied to be no cues, ambiguous cues high in imageability, and cues directly related to Facebook. The results showed that there was no difference between individual’s ability to recall their Facebook friends and their working memory scores. However, those in the ambiguous cue condition were able to recall significantly fewer Facebook friends than those in the Facebook cue or no cue condition. Thus, this research shows that ambiguous cues can interfere with recall. However, further research is needed to see the extent that working memory moderates this effect

Breeding state and season affect interspecific interaction types: indirect resource competition and direct interference

Indirect resource competition and interference are widely occurring mechanisms of interspecific interactions. We have studied the seasonal expression of these two interaction types within a two-species, boreal small mammal system. Seasons differ by resource availability, individual breeding state and intraspecific social system. Live-trapping methods were used to monitor space use and reproduction in 14 experimental populations of bank voles Myodes glareolus in large outdoor enclosures with and without a dominant competitor, the field vole Microtus agrestis. We further compared vole behaviour using staged dyadic encounters in neutral arenas in both seasons. Survival of the non-breeding overwintering bank voles was not affected by competition. In the spring, the numbers of male bank voles, but not of females, were reduced significantly in the competition populations. Bank vole home ranges expanded with vole density in the presence of competitors, indicating food limitation. A comparison of behaviour between seasons based on an analysis of similarity revealed an avoidance of costly aggression against opponents, independent of species. Interactions were more aggressive during the summer than during the winter, and heterospecific encounters were more aggressive than conspecific encounters. Based on these results, we suggest that interaction types and their respective mechanisms are not either–or categories and may change over the seasons. During the winter, energy constraints and thermoregulatory needs decrease direct aggression, but food constraints increase indirect resource competition. Direct interference appears in the summer, probably triggered by each individual’s reproductive and hormonal state and the defence of offspring against conspecific and heterospecific intruders. Both interaction forms overlap in the spring, possibly contributing to spring declines in the numbers of subordinate species

dictyBase, the model organism database for Dictyostelium discoideum

dictyBase () is the model organism database (MOD) for the social amoeba Dictyostelium discoideum. The unique biology and phylogenetic position of Dictyostelium offer a great opportunity to gain knowledge of processes not characterized in other organisms. The recent completion of the 34 MB genome sequence, together with the sizable scientific literature using Dictyostelium as a research organism, provided the necessary tools to create a well-annotated genome. dictyBase has leveraged software developed by the Saccharomyces Genome Database and the Generic Model Organism Database project. This has reduced the time required to develop a full-featured MOD and greatly facilitated our ability to focus on annotation and providing new functionality. We hope that manual curation of the Dictyostelium genome will facilitate the annotation of other genomes

Alkalic-Type Epithermal Gold Deposit Model: Chapter R of Mineral Deposit Models for Resource Assessment

This report summarizes the primary characteristics of alkalic-type epithermal gold (Au) deposits and provides an updated descriptive model. These deposits, primarily of Mesozoic to Neogene age, are among the largest epithermal gold deposits in the world. Considered a subset of low-sulfidation epithermal deposits, they are spatially and genetically linked to small stocks or clusters of intrusions containing high alkali-element contents. Deposits occur as disseminations, breccia-fillings, and veins and may be spatially and genetically related to skarns and low-grade porphyry copper (Cu) or molybdenum (Mo) systems. Gold commonly occurs as native gold, precious metal tellurides, and as sub-micron gold in arsenian pyrite. Quartz, carbonate, fluorite, adularia, and vanadian muscovite/roscoelite are the most common gangue minerals. Alkalic-type gold deposits form in a variety of geological settings including continent-arc collision zones and back-arc or post-subduction rifts that are invariably characterized by a transition from convergent to extensional or transpressive tectonics. The geochemical compositions of alkaline igneous rocks spatially linked with these deposits span the alkaline-subalkaline transition. Their alkali enrichment may be masked by potassic alteration, but the unaltered or least altered rocks (1) have chondrite normalized patterns that are commonly light rare earth element (LREE) enriched, (2) are heavy rare earth element (HREE) depleted, and (3) have high large ion lithophile contents and variable enrichment of high-field strength elements. Radiogenic isotopes suggest a mantle derivation for the alkalic magmas but allow crustal contamination. Oxygen and hydrogen isotope compositions show that the fluids responsible for deposit formation are dominantly magmatic, although meteoric or other external fluids (seawater, evolved groundwater) also contributed to the ore-forming fluids responsible for these deposits. Carbon and sulfur isotope compositions in vein-hosted carbonates and sulfide gangue minerals, respectively, coincide with magmatic values, although a sedimentary source of carbon and sulfur is evident in several deposits. Deep-seated structures are critical for the upwelling of hydrous alkalic magmas and for focusing magmatic-hydrothermal fluids to the site of precious metal deposition. The source of gold, silver (Ag), tellurium (Te), vanadium (V), and fluorine (F) was probably the alkalic igneous rocks themselves, and the coexistence of native gold, gold tellurides, and roscoelite in several deposits is primarily a function of similar physicochemical conditions during deposition (for example, overlapping pH and oxygen fugacity (fO2). Potential environmental impacts related to the mining and processing of alkalic-type epithermal gold deposits include acid mine drainage with high levels of metals, especially zinc (Zn), copper, lead (Pb), and arsenic. However, because alkalic-type gold deposits typically contain carbonates, which contribute calcium and magnesium ions that increase water hardness, aquatic life may be afforded some protection. Impacts vary widely as a function of host rocks, climate, topography, and mining methods. Geologic mapping to (1) highlight the distribution of potassic alteration; (2) define fault density and orientation of structures; (3) determine the distribution of alkaline rocks and hydrothermal breccias; and (4) identify uniquely colored gangue minerals, such as fluorite and roscoelite, will be critical to exploration and future discoveries. Geophysical techniques that identify potassium (K) anomalies (for example, radiometric and spectroscopic surveys), as well as magnetic, resistivity, aeromagnetic, and gravity surveys, may help locate zones of high-permeability that control advecting hydrothermal fluids. Geochemical surveys that include analyses for Au, Ag, barium, Te, K, F, V, Mo, and mercury, which are key elements in these deposits, should be undertaken along with the measurement of other pathfinder elements such as arsenic, bismuth, Cu, iron, nickel, Pb, antimony, selenium, and Zn

Retrospective Loss: Looking Back to Improve Training of Deep Neural Networks

Deep neural networks (DNNs) are powerful learning machines that have enabled breakthroughs in several domains. In this work, we introduce a new retrospective loss to improve the training of deep neural network models by utilizing the prior experience available in past model states during training. Minimizing the retrospective loss, along with the task-specific loss, pushes the parameter state at the current training step towards the optimal parameter state while pulling it away from the parameter state at a previous training step. Although a simple idea, we analyze the method as well as to conduct comprehensive sets of experiments across domains - images, speech, text, and graphs - to show that the proposed loss results in improved performance across input domains, tasks, and architectures.Comment: Accepted at KDD 2020; The first two authors contributed equall

Zero-Shot Multi-View Indoor Localization via Graph Location Networks

Indoor localization is a fundamental problem in location-based applications. Current approaches to this problem typically rely on Radio Frequency technology, which requires not only supporting infrastructures but human efforts to measure and calibrate the signal. Moreover, data collection for all locations is indispensable in existing methods, which in turn hinders their large-scale deployment. In this paper, we propose a novel neural network based architecture Graph Location Networks (GLN) to perform infrastructure-free, multi-view image based indoor localization. GLN makes location predictions based on robust location representations extracted from images through message-passing networks. Furthermore, we introduce a novel zero-shot indoor localization setting and tackle it by extending the proposed GLN to a dedicated zero-shot version, which exploits a novel mechanism Map2Vec to train location-aware embeddings and make predictions on novel unseen locations. Our extensive experiments show that the proposed approach outperforms state-of-the-art methods in the standard setting, and achieves promising accuracy even in the zero-shot setting where data for half of the locations are not available. The source code and datasets are publicly available at https://github.com/coldmanck/zero-shot-indoor-localization-release.Comment: Accepted at ACM MM 2020. 10 pages, 7 figures. Code and datasets available at https://github.com/coldmanck/zero-shot-indoor-localization-releas

The Gene Ontology knowledgebase in 2023

The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO-a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations-evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)-mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project