Unconscious processing of invisible visual stimuli

Unconscious processing of subliminal visual information, as illustrated by the above-chance accuracy in discriminating invisible visual stimuli, is evident in both blindsight patients and healthy human observers. However, the dependence of such unconscious processing on stimulus properties remains unclear. Here we studied the impact of stimulus luminance and stimulus complexity on the extent of unconscious processing. A testing stimulus presented to one eye was rendered invisible by a masking stimulus presented to the other eye, and healthy human participants made a forced-choice discrimination of the stimulus identity followed by a report of the perceptual awareness. Without awareness of the stimulus existence, participants could nevertheless reach above-chance accuracy in discriminating the stimulus identity. Importantly, the discrimination accuracy for invisible stimuli increased with the stimulus luminance and decreased with the stimulus complexity. These findings suggested that the input signal strength and the input signal complexity can affect the extent of unconscious processing without altering the subjective awareness

Inhibition of Bcl-2 Sensitizes Mitochondrial Permeability Transition Pore (MPTP) Opening in Ischemia-Damaged Mitochondria

Background Mitochondria are critical to cardiac injury during reperfusion as a result of damage sustained during ischemia, including the loss of bcl-2. We asked if bcl-2 depletion not only leads to selective permeation of the outer mitochondrial membrane (MOMP) favoring cytochrome crelease and programmed cell death, but also favors opening of the mitochondrial permeability transition pore (MPTP). An increase in MPTP susceptibility would support a role for bcl-2 depletion mediated cell death in the calcium overload setting of early reperfusion via MPTP as well as later in reperfusion via MOMP as myocardial calcium content normalizes. Methods Calcium retention capacity (CRC) was used to reflect the sensitivity of the MPTP opening in isolated cardiac mitochondria. To study the relationship between bcl-2 inhibition and MPTP opening, mitochondria were incubated with a bcl-2 inhibitor (HA14-1) and CRC measured. The contribution of preserved bcl-2 content to MPTP opening following ischemia-reperfusion was explored using transgenic bcl-2 overexpressed mice. Results CRC was decreased in mitochondria following reperfusion compared to ischemia alone, indicating that reperfusion further sensitizes to MPTP opening. Incubation of ischemia-damaged mitochondria with increasing HA14-1concentrations increased calcium-stimulated MPTP opening, supporting that functional inhibition of bcl-2 during simulated reperfusion favors MPTP opening. Moreover, HA14-1 sensitivity was increased by ischemia compared to non-ischemic controls. Overexpression of bcl-2 attenuated MPTP opening in following ischemia-reperfusion. HA14-1 inhibition also increased the permeability of the outer membrane in the absence of exogenous calcium, indicating that bcl-2 inhibition favors MOMP when calcium is low. Conclusions The depletion and functional inhibition of bcl-2 contributes to cardiac injury by increasing susceptibility to MPTP opening in high calcium environments and MOMP in the absence of calcium overload. Thus, ischemia-damaged mitochondria with decreased bcl-2 content are susceptible to MPTP opening in early reperfusion and MOMP later in reperfusion when cytosolic calcium has normalized

Revisiting Co-Occurring Directions: Sharper Analysis and Efficient Algorithm for Sparse Matrices

We study the streaming model for approximate matrix multiplication (AMM). We are interested in the scenario that the algorithm can only take one pass over the data with limited memory. The state-of-the-art deterministic sketching algorithm for streaming AMM is the co-occurring directions (COD), which has much smaller approximation errors than randomized algorithms and outperforms other deterministic sketching methods empirically. In this paper, we provide a tighter error bound for COD whose leading term considers the potential approximate low-rank structure and the correlation of input matrices. We prove COD is space optimal with respect to our improved error bound. We also propose a variant of COD for sparse matrices with theoretical guarantees. The experiments on real-world sparse datasets show that the proposed algorithm is more efficient than baseline methods

Temporal and spatial variability of temperature and precipitationover East Africa from 1951 to 2010

This study presents temporal and spatial changes in temperature and precipitation over East Africa (EA) from 1951 to 2010. The study utilized monthly Climate Research Unit (CRU) rainfall and temperature datasets, and Global Precipitation Climate Centre (GPCC) rainfall datasets. Sequential Mann–Kendall test statistic was used for trend analysis. The CRU data performs better than GPCC data in reproducing EA annual rainfall cycle. Overall decrease and increase in rainfall and temperature trends were observed, respectively, with the reduction in the March–May rainfall being significant. The highest rate of change in annual rainfall was experienced in the 1960s at −21.76 mm/year. Although there has been increase in temperature from the late 1960s to date, sudden change in its trend change happened in 1994. The increase in temperature reached a significant level in the year 1992. The highest warming rate of 0.05 °C/year was observed in the 1990s. The highest drying rate was recorded in the 1960s at −21.76 mm/year. There was an observed change in rainfall trend in the year 1953 and about four times in 1980, although the changes are insignificant throughout the study period except for 1963 when a positive significant change occurred at 5 % significance level. The highest amount of rainfall was recorded in the 1960s. Generally, positive rainfall and temperature anomalies are observed over the northern sector of the study area and opposite conditions are noted in the southern sector. The results of this study provide a reliable basis for future climate monitoring, as well as investigating extreme weather phenomena in EA

MoTiAC: Multi-Objective Actor-Critics for Real-Time Bidding

Online real-time bidding (RTB) is known as a complex auction game where ad platforms seek to consider various influential key performance indicators (KPIs), like revenue and return on investment (ROI). The trade-off among these competing goals needs to be balanced on a massive scale. To address the problem, we propose a multi-objective reinforcement learning algorithm, named MoTiAC, for the problem of bidding optimization with various goals. Specifically, in MoTiAC, instead of using a fixed and linear combination of multiple objectives, we compute adaptive weights overtime on the basis of how well the current state agrees with the agent's prior. In addition, we provide interesting properties of model updating and further prove that Pareto optimality could be guaranteed. We demonstrate the effectiveness of our method on a real-world commercial dataset. Experiments show that the model outperforms all state-of-the-art baselines.Comment: 8 Pages, Extensive Experiment