Hegelian Spirits in Sellarsian Bottles

Though Wilfrid Sellars portrayed himself as a latter-day Kantian, I argue here that he was at least as much a Hegelian. Several themes Sellars shares with Hegel are investigated: the sociality and normativity of the intentional, categorial change, the rejection of the given, and especially their denial of an unknowable thing-in-itself. They are also united by an emphasis on the unity of things—the belief that things do ‘‘hang together.’’ Hegel’s unity is idealist; Sellars’ is physicalist; the differences are substantial, but so are the resonances

Dynamic behavior and damping capacity of auxetic foam pads

A novel set of auxetic (negative Poisson's ratio) open cell polyurethane foam has been developed and tested under dynamic loading conditions to assess the viscoelastic response under white noise random excitation and compressive cycling. Foam pads normalized to standard ISO 13753 have been tested at room temperature and frequency bandwidth 10-500 Hz to assess transmissibility characteristics for possible antivibration glove applications. The results show that the ISO 13753 normalized transmissibility for these foams falls below 0.6 above 100 Hz, with lower peak maximum stresses under indentation compared to conventional open cell solids. These results suggest possible use of the auxetic foam for pads or linens against « white fingers« vibration applications. Further tests have been conducted on cyclic compressive loading up to 3 Hz and loading ratios of 0.95 for loading histories up to 100000 cycles. The damping capacity of the auxetic foams showed and increase by a factor 10 compared to the conventional foams used to manufacture the negative Poisson's ratio ones, and stiffness degradation stabilized after few tens on cycles

Quantum trajectories for time-dependent adiabatic master equations

We develop a quantum trajectories technique for the unraveling of the quantum adiabatic master equation in Lindblad form. By evolving a complex state vector of dimension $N$ instead of a complex density matrix of dimension $N^2$, simulations of larger system sizes become feasible. The cost of running many trajectories, which is required to recover the master equation evolution, can be minimized by running the trajectories in parallel, making this method suitable for high performance computing clusters. In general, the trajectories method can provide up to a factor $N$ advantage over directly solving the master equation. In special cases where only the expectation values of certain observables are desired, an advantage of up to a factor $N^2$ is possible. We test the method by demonstrating agreement with direct solution of the quantum adiabatic master equation for $8$-qubit quantum annealing examples. We also apply the quantum trajectories method to a $16$-qubit example originally introduced to demonstrate the role of tunneling in quantum annealing, which is significantly more time consuming to solve directly using the master equation. The quantum trajectories method provides insight into individual quantum jump trajectories and their statistics, thus shedding light on open system quantum adiabatic evolution beyond the master equation.Comment: 17 pages, 7 figure

Insights into Activation Mechanisms of Store-Operated TRPC1 Channels in Vascular Smooth Muscle.

In vascular smooth muscle cells (VMSCs), the stimulation of store-operated channels (SOCs) mediate Ca2+ influx pathways which regulate important cellular functions including contraction, proliferation, migration, and growth that are associated with the development of vascular diseases. It is therefore important that we understand the biophysical, molecular composition, activation pathways, and physiological significance of SOCs in VSMCs as these maybe future therapeutic targets for conditions such as hypertension and atherosclerosis. Archetypal SOCs called calcium release-activated channels (CRACs) are composed of Orai1 proteins and are stimulated by the endo/sarcoplasmic reticulum Ca2+ sensor stromal interaction molecule 1 (STIM1) following store depletion. In contrast, this review focuses on proposals that canonical transient receptor potential (TRPC) channels composed of a heteromeric TRPC1/C5 molecular template, with TRPC1 conferring activation by store depletion, mediate SOCs in native contractile VSMCs. In particular, it summarizes our recent findings which describe a novel activation pathway of these TRPC1-based SOCs, in which protein kinase C (PKC)-dependent TRPC1 phosphorylation and phosphatidylinositol 4,5-bisphosphate (PIP2) are obligatory for channel opening. This PKC- and PIP2-mediated gating mechanism is regulated by the PIP2-binding protein myristoylated alanine-rich C kinase (MARCKS) and is coupled to store depletion by TRPC1-STIM1 interactions which induce Gq/PLCβ1 activity. Interestingly, the biophysical properties and activation mechanisms of TRPC1-based SOCs in native contractile VSMCs are unlikely to involve Orai1

Zero-noise extrapolation for quantum-gate error mitigation with identity insertions

Quantum-gate errors are a significant challenge for achieving precision measurements on noisy intermediate-scale quantum (NISQ) computers. This paper focuses on zero-noise extrapolation (ZNE), a technique that can be implemented on existing hardware, studying it in detail and proposing modifications to existing approaches. In particular, we consider identity insertion methods for amplifying noise because they are hardware agnostic. We build a mathematical formalism for studying existing ZNE techniques and show how higher order polynomial extrapolations can be used to systematically reduce depolarizing errors. Furthermore, we introduce a method for amplifying noise that uses far fewer gates than traditional methods. This approach is compared with existing methods for simulated quantum circuits. Comparable or smaller errors are possible with fewer gates, which illustrates the potential for empowering an entirely new class of moderate-depth circuits on near term hardware

The Relationship of Money Ethics on Tax Evasion with Intrinsic Religiosity, Extrinsic Religiosity, and Materialism as Moderating Variables (Case on Private Taxpayers Listed in Kpp Pratama Ternate)

This study aims to find out the influence of money ethics on tax evasion with intrinsic religiosity, extrinsic religiosity, and materialism as moderating variables. The sample is selected by using convinience sampling method with sample size of a 100 respondents as primary data. This study uses simple regression and moderated regression analysis for hypothesis testing. The result of this study shows that money ethics has an effect on tax evasion, intrinsic religiosity moderarates the relationship between money ethics and tax evasion. Extrinsic religiosity does not moderate the relationship bertween money ethics and tax evasion. Materialism moderates the relationship between money ethics and tax evasion

Solving the riddle of codon usage preferences: a test for translational selection

Translational selection is responsible for the unequal usage of synonymous codons in protein coding genes in a wide variety of organisms. It is one of the most subtle and pervasive forces of molecular evolution, yet, establishing the underlying causes for its idiosyncratic behaviour across living kingdoms has proven elusive to researchers over the past 20 years. In this study, a statistical model for measuring translational selection in any given genome is developed, and the test is applied to 126 fully sequenced genomes, ranging from archaea to eukaryotes. It is shown that tRNA gene redundancy and genome size are interacting forces that ultimately determine the action of translational selection, and that an optimal genome size exists for which this kind of selection is maximal. Accordingly, genome size also presents upper and lower boundaries beyond which selection on codon usage is not possible. We propose a model where the coevolution of genome size and tRNA genes explains the observed patterns in translational selection in all living organisms. This model finally unifies our understanding of codon usage across prokaryotes and eukaryotes. Helicobacter pylori, Saccharomyces cerevisiae and Homo sapiens are codon usage paradigms that can be better understood under the proposed model

Identification of future environmental challenges in Pakistan by 2025 through environment foresight

Technology foresight is defined as “the process involved in systematically attempting to look into the longer term future of science, technology, the economy and society with the aim of identifying the areas of strategic research and the emerging generic technologies likely to yield the greatest economic and social benefits.” Technology foresight on environment sector was carried out under the supervision of Pakistan Technology Board on the theme “Environment 2025: Our future, our choices”. Social, technological, environmental, economical, political and values (STEEPV) is an internationally recognized tool for brainstorming used in conducting technology foresight worldwide and was used by environment panel for collection of issues and drivers, opinions, policies and projects for future of environment in Pakistan. More than 20 experts participated in the expert panel brainstorming workshops. A diverse panel was formed with representation from R and D organizations, Ministry of Environment, researchers and professors in universities, NGO and private sector organizations. A consensus was achieved by the panel on top four most important issues in environment sector which include; (a) water (b) loss of biodiversity, (c) solid waste and (d) energy. Furthermore, the causes, remedies, policy recommendations and project proposals were identified for each of the four issues.Key words: Technology foresight, environmental degradation, water as a resource, biodiversity loss, solid waste, energy, panel discussion, STEEPV, priority areas

Smart Content Recognition from Images Using a Mixture of Convolutional Neural Networks

With rapid development of the Internet, web contents become huge. Most of the websites are publicly available, and anyone can access the contents from anywhere such as workplace, home and even schools. Nevertheless, not all the web contents are appropriate for all users, especially children. An example of these contents is pornography images which should be restricted to certain age group. Besides, these images are not safe for work (NSFW) in which employees should not be seen accessing such contents during work. Recently, convolutional neural networks have been successfully applied to many computer vision problems. Inspired by these successes, we propose a mixture of convolutional neural networks for adult content recognition. Unlike other works, our method is formulated on a weighted sum of multiple deep neural network models. The weights of each CNN models are expressed as a linear regression problem learned using Ordinary Least Squares (OLS). Experimental results demonstrate that the proposed model outperforms both single CNN model and the average sum of CNN models in adult content recognition.Comment: To be published in LNEE, Code: github.com/mundher/NSF