Tests of Sample-recovery Models of Cued Recall

Sample-recovery models are a predominant class of episodic memory models that seek to explain why sometimes the representation of an experienced event is not retrieved or retrieved incorrectly. In these models, a correct retrieval occurs if the correct target item was sampled among the alternative studied item, then recovered correctly. In cued recall, participants output the representation of a single experienced event, a target, given a presented test stimulus and some defined relationship between the stimulus and the target. This relationship depends on the kind of cued recall and can rely on either studied or pre-experimental relationships. Sample-recovery models of this task share common testable properties related to both sampling and recovery, which we do across two experiments. Experiment 1 tests the property that sampling in sample-recovery models of cued recall is one process: they combine information about test stimulus and its relationship to the target into a single value and sample in a way consistent with the Luce choice rule. We test this assumption by testing whether manipulating the strengths of these relationships generates differential influence on performance in kinds of cued recall where different relationships between test stimulus and response are probed. The pattern of data is inconsistent with one sample process but is consistent with a sampling procedure that separately samples for a cue given the stimulus and a target given a cue. Experiment 2 tests the assumption that recovery performance is independent of other studied items. We allow some cue and target words to be related to some other untested studied words. Targets with a related word on the study list were associated with more correct responses than targets without one. This suggests that recovery in some way uses the memory for the other studied items to help retrieve. We consider how various models of sample-recovery may be adapted to account for these findings, with a particular focus on the Retrieving Effectively from Memory model

Tests Of Sample-recovery Models Of Cued Recall

Sample-recovery models are a predominant class of episodic memory models that seek to explain why sometimes the representation of an experienced event is not retrieved or retrieved incorrectly. In these models, a correct retrieval occurs if the correct target item was sampled among the alternative studied item, then recovered correctly. In cued recall, participants output the representation of a single experienced event, a target, given a presented test stimulus and some defined relationship between the stimulus and the target. This relationship depends on the kind of cued recall and can rely on either studied or pre-experimental relationships. Sample-recovery models of this task share common testable properties related to both sampling and recovery, which we do across two experiments. Experiment 1 tests the property that sampling in sample-recovery models of cued recall is one process: they combine information about test stimulus and its relationship to the target into a single value and sample in a way consistent with the Luce choice rule. We test this assumption by testing whether manipulating the strengths of these relationships generates differential influence on performance in kinds of cued recall where different relationships between test stimulus and response are probed. The pattern of data is inconsistent with one sample process but is consistent with a sampling procedure that separately samples for a cue given the stimulus and a target given a cue. Experiment 2 tests the assumption that recovery performance is independent of other studied items. We allow some cue and target words to be related to some other untested studied words. Targets with a related word on the study list were associated with more correct responses than targets without one. This suggests that recovery in some way uses the memory for the other studied items to help retrieve. We consider how various models of sample-recovery may be adapted to account for these findings, with a particular focus on the Retrieving Effectively from Memory model

Weed Seedbanks of the U.S. Corn Belt: Magnitude, Variation, Emergence, and Application

Seedbanks and seedling emergence of annual weeds were examined in arable fields at eight locations in the Corn Belt. Seed densities were estimated by direct seed extraction from each of several soil cores in each sampled plot. Average total seedbank densities ranged from 600 to 162 000 viable seed m⁻² among locations. Coefficients of variation (CV) typically exceeded 50%. CV for seed densities of individual species usually exceeded 100%, indicating strongly aggregated distributions. CV were lower for species with dense seed populations than those with sparse seed populations. Variance of total seedbank densities was unstable when \u3c 10 cores were examined per plot, but stabilized at all locations when ≥ 15 cores were analyzed, despite a 12-fold difference in plot size and 270-fold difference in seed density among locations. Percentage viable seed that emerged as seedlings in field plots ranged from \u3c 1% for yellow rocket to 30% for giant foxtail. Redroot pigweed and common lambsquarters were the most frequently encountered species. Emergence percentages of these species were related inversely to rainfall or air temperatures in April or May, presumably because anoxia and/or high temperatures induced secondary dormancy in nondormant seed. From 50 to 90% of total seed in the seedbank were dead. This information can be employed by bioeconomic weed management models, which currently use coarse estimates of emergence percentages to customize recommendations for weed control

Weed Seed Bank Emergence across the Corn Belt

Field experiments, conducted from 1991 to 1994, generated information on weed seedbank emergence for 22 site-years from Ohio to Colorado and Minnesota to Missouri. Early spring seedbank densities were estimated through direct extraction of viable seeds from soil cores. Emerged seedlings were recorded periodically, as were daily values for air and soil temperature, and precipitation. Percentages of weed seedbanks that emerged as seedlings were calculated from seedbank and seedling data for each species, and relationships between seedbank emergence and microclimatic variables were sought. Fifteen species were found in 3 or more site-years. Average emergence percentages (and coefficients of variation) of these species were as follows: giant foxtail, 31.2 (84%); velvetleaf, 28.2 (66); kochia, 25.7 (79); Pennsylvania smartweed, 25.1 (65); common purslane, 15.4 (135); common ragweed, 15.0 (110); green foxtail, 8.5 (72); wild proso millet, 6.6 (104); hairy nightshade, 5.2 (62); common sunflower, 5.0 (26); yellow foxtail, 3.4 (67); pigweed species, 3.3 (103); common lambsquarters, 2.7 (111); wild buckwheat, 2.5 (63), and prostrate knotweed, 0.6 (79). Variation among site-years, for some species, could be attributed to microclimate variables thought to induce secondary dormancy in spring. For example, total seasonal emergence percentage of giant foxtail was related positively to the 1st date at which average daily soil temperature at 5 to 10 cm soil depth reached 16 C. Thus, if soil warmed before mid April, secondary dormancy was induced and few seedlings emerged, whereas many seedlings emerged if soil remained cool until June

Weed Seed Bank Emergence across the Corn Belt

Field experiments, conducted from 1991 to 1994, generated information on weed seedbank emergence for 22 site-years from Ohio to Colorado and Minnesota to Missouri. Early spring seedbank densities were estimated through direct extraction of viable seeds from soil cores. Emerged seedlings were recorded periodically, as were daily values for air and soil temperature, and precipitation. Percentages of weed seedbanks that emerged as seedlings were calculated from seedbank and seedling data for each species, and relationships between seedbank emergence and microclimatic variables were sought. Fifteen species were found in 3 or more site-years. Average emergence percentages (and coefficients of variation) of these species were as follows: giant foxtail, 31.2 (84%); velvetleaf, 28.2 (66); kochia, 25.7 (79); Pennsylvania smartweed, 25.1 (65); common purslane, 15.4 (135); common ragweed, 15.0 (110); green foxtail, 8.5 (72); wild proso millet, 6.6 (104); hairy nightshade, 5.2 (62); common sunflower, 5.0 (26); yellow foxtail, 3.4 (67); pigweed species, 3.3 (103); common lambsquarters, 2.7 (111); wild buckwheat, 2.5 (63), and prostrate knotweed, 0.6 (79). Variation among site-years, for some species, could be attributed to microclimate variables thought to induce secondary dormancy in spring. For example, total seasonal emergence percentage of giant foxtail was related positively to the 1st date at which average daily soil temperature at 5 to 10 cm soil depth reached 16 C. Thus, if soil warmed before mid April, secondary dormancy was induced and few seedlings emerged, whereas many seedlings emerged if soil remained cool until June

Evasion of anti-growth signaling: a key step in tumorigenesis and potential target for treatment and prophylaxis by natural compounds

The evasion of anti-growth signaling is an important characteristic of cancer cells. In order to continue to proliferate, cancer cells must somehow uncouple themselves from the many signals that exist to slow down cell growth. Here, we define the anti-growth signaling process, and review several important pathways involved in growth signaling: p53, phosphatase and tensin homolog (PTEN), retinoblastoma protein (Rb), Hippo, growth differentiation factor 15 (GDF15), AT-rich interactive domain 1A (ARID1A), Notch, insulin-like growth factor (IGF), and Krüppel-like factor 5 (KLF5) pathways. Aberrations in these processes in cancer cells involve mutations and thus the suppression of genes that prevent growth, as well as mutation and activation of genes involved in driving cell growth. Using these pathways as examples, we prioritize molecular targets that might be leveraged to promote anti-growth signaling in cancer cells. Interestingly, naturally-occurring phytochemicals found in human diets (either singly or as mixtures) may promote anti-growth signaling, and do so without the potentially adverse effects associated with synthetic chemicals. We review examples of naturally-occurring phytochemicals that may be applied to prevent cancer by antagonizing growth signaling, and propose one phytochemical for each pathway. These are: epigallocatechin-3-gallate (EGCG) for the Rb pathway, luteolin for p53, curcumin for PTEN, porphyrins for Hippo, genistein for GDF15, resveratrol for ARID1A, withaferin A for Notch and diguelin for the IGF1-receptor pathway. The coordination of anti-growth signaling and natural compound studies will provide insight into the future application of these compounds in the clinical setting

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

Great expectations or small country living? Enabling small rural creative businesses with ICT.

Small businesses are prototypical rural business, but limited by distance. However, creative businesses are less constrained by space and hold great promise for rural development. Indeed, the rural is an attractive creative aesthetic milieu. Moreover, new broadband technologies seem to offer a solution to address connectivity; the social and spatial problem of being rural. Consequently, we ask how does broadband enable small rural creative firms. We sought out the practices and experiences of creative business owners, finding that broadband offered useful technical, creative, and business linking. However many were frustrated by poor technical performance. Furthermore, the accelerating pace of ICT worried respondents, who feared being left behind. Nonetheless for most-without broadband their rural location would have been impossible. We found that broadband has fostered creative rural businesses, but as new ways of making a small country living rather than stimulating a rural creative milieu. The digital promise of a creative transformation of the rural has not been realised in Scotland

Christianity as Public Religion::A Justification for using a Christian Sociological Approach for Studying the Social Scientific Aspects of Sport

The vast majority of social scientific studies of sport have been secular in nature and/or have tended to ignore the importance of studying the religious aspects of sport. In light of this, Shilling and Mellor (2014) have sought to encourage sociologists of sport not to divorce the ‘religious’ and the ‘sacred’ from their studies. In response to this call, the goal of the current essay is to explore how the conception of Christianity as ‘public religion’ can be utilised to help justify the use of a Christian sociological approach for studying the social scientific aspects of sport. After making a case for Christianity as public religion, we conclude that many of the sociological issues inherent in modern sport are an indirect result of its increasing secularisation and argue that this justifies the need for a Christian sociological approach. We encourage researchers to use the Bible, the tools of Christian theology and sociological concepts together, so to inform analyses of modern sport from a Christian perspective