Off-diagonal disorder in the Anderson model of localization

We examine the localization properties of the Anderson Hamiltonian with additional off-diagonal disorder using the transfer-matrix method and finite-size scaling. We compute the localization lengths and study the metal-insulator transition (MIT) as a function of diagonal disorder, as well as its energy dependence. Furthermore we investigate the different influence of odd and even system sizes on the localization properties in quasi one-dimensional systems. Applying the finite-size scaling approach in conjunction with a nonlinear fitting procedure yields the critical parameters of the MIT. In three dimensions, we find that the resulting critical exponent of the localization length agrees with the exponent for the Anderson model with pure diagonal disorder.Comment: 12 pages including 4 EPS figures, accepted for publication in phys. stat. sol. (b

High throughput imaging cytometer with acoustic focussing

We demonstrate an imaging flow cytometer that uses acoustic levitation to assemble cells and other particles into a sheet structure. This technique enables a high resolution, low noise CMOS camera to capture images of thousands of cells with each frame. While ultrasonic focussing has previously been demonstrated for 1D cytometry systems, extending the technology to a planar, much higher throughput format and integrating imaging is non-trivial, and represents a significant jump forward in capability, leading to diagnostic possibilities not achievable with current systems. A galvo mirror is used to track the images of the moving cells permitting exposure times of 10 ms at frame rates of 50 fps with motion blur of only a few pixels. At 80 fps, we demonstrate a throughput of 208 000 beads per second. We investigate the factors affecting motion blur and throughput, and demonstrate the system with fluorescent beads, leukaemia cells and a chondrocyte cell line. Cells require more time to reach the acoustic focus than beads, resulting in lower throughputs; however a longer device would remove this constraint

Моделирование структуры топливно-энергетического баланса региона в условиях применения концепции устойчивого развития для достижения стратегических показателей регионального развития

Purpose: is to study the possibilities of applying the concept of sustainable development in the fuel and energy complex of the region to achieve strategic development goals, modeling the structure of the fuel and energy balance based on the principles of sustainable regional development.Methods: the study is based on the application of the principles of sustainable development to the planning of new urban spaces, which allowed us to consider the possibilities of their implementation in the fuel and energy balance model.Results: the study of the possibilities of applying the concept of sustainable development and their impact on the fuel and energy balance is based on the example of Primorsky Krai. The essence of the fuel and energy balance as a tool for the implementation of strategic goals of the national economy is studied. The implementation of the regional development strategy and its role in the formation of the fuel and energy balance of the region are evaluated. Key initiatives for the development of the region, including the construction of new urban spaces, have been identified. Based on the data on the planned population, the need for electric and thermal energy is determined. A scenario analysis of the fuel and energy balance and risk assessment of the implementation of the developed scenarios have been carried out. The authors propose to supplement the fuel and energy balance model with indicators of the usage of secondary energy sources for the production of electric and heat energy. It is revealed that modeling the structure of consumption and production of energy sources paying attention to long-term strategies and trends in energy development contributes to forecasting the achievement of planned indicators.Сonclusions and Relevance: the expansion of the fuel and energy balance model paying attention to secondary energy sources, will allow for more accurate forecasts of the need for primary energy sources, monitor and analyze trends in the implementation of initiatives for the use of secondary energy sources, determine the economy of primary fuel and energy sources in kind, which will contribute to the implementation of the principles of sustainable development of the region's economy.Цель работы – моделирование структуры топливно-энергетического баланса региона на основе изучения возможностей применения концепции устойчивого развития в топливно-энергетическом комплексе для достижения стратегических целей развития региона.Метод или методология проведения работы. Исследование основано на применении принципов устойчивого развития к планированию новых городских пространств, что позволило рассмотреть возможности их внедрения в модель топливно-энергетического баланса региона.Результаты работы. Исследование возможностей применения концепции устойчивого развития и их влияние на топливно-энергетический баланс исследовано на примере Приморского края: рассмотрено значение топливно-энергетического баланса как инструмента реализации стратегических целей национальной экономики, оценена реализация стратегии развития региона и ее роль в формировании топливно-энергетического баланса, определены ключевые инициативы развития региона, в том числе строительство новых городских пространств, на основе данных о планируемой численности населения определена потребность в электрической и тепловой энергии, проведен сценарный анализ топливно-энергетического баланса и оценка рисков реализации разработанных сценариев. Авторами предложено дополнить модель топливно-энергетического баланса показателями, которые позволят учесть использование вторичных энергетических ресурсов для производства электрической и тепловой энергии. Выявлено, что моделирование структуры потребления и производства энергетических ресурсов с учетом долгосрочных стратегий программ развития и тенденций развития энергетики способствует прогнозированию достижения плановых показателей.Выводы. Расширение модели топливно-энергетического баланса с учетом вторичных энергетических ресурсов позволит осуществлять более точные прогнозы потребности в первичных энергетических ресурсах, отслеживать и анализировать тенденции по реализации инициатив использования вторичных энергетических ресурсов, определять экономию первичных топливно-энергетических ресурсов в натуральном выражении. Использование вторичных энергетических ресурсов для производства электрической и тепловой энергии будет способствовать реализации принципов устойчивого развития экономики региона

Quantum Bayes rule

We state a quantum version of Bayes's rule for statistical inference and give a simple general derivation within the framework of generalized measurements. The rule can be applied to measurements on N copies of a system if the initial state of the N copies is exchangeable. As an illustration, we apply the rule to N qubits. Finally, we show that quantum state estimates derived via the principle of maximum entropy are fundamentally different from those obtained via the quantum Bayes rule.Comment: REVTEX, 9 page

Coarse graining molecular dynamics with graph neural networks

Coarse graining enables the investigation of molecular dynamics for larger systems and at longer timescales than is possible at an atomic resolution. However, a coarse graining model must be formulated such that the conclusions we draw from it are consistent with the conclusions we would draw from a model at a finer level of detail. It has been proved that a force matching scheme defines a thermodynamically consistent coarse-grained model for an atomistic system in the variational limit. Wang et al. [ACS Cent. Sci. 5, 755 (2019)] demonstrated that the existence of such a variational limit enables the use of a supervised machine learning framework to generate a coarse-grained force field, which can then be used for simulation in the coarse-grained space. Their framework, however, requires the manual input of molecular features to machine learn the force field. In the present contribution, we build upon the advance of Wang et al. and introduce a hybrid architecture for the machine learning of coarse-grained force fields that learn their own features via a subnetwork that leverages continuous filter convolutions on a graph neural network architecture. We demonstrate that this framework succeeds at reproducing the thermodynamics for small biomolecular systems. Since the learned molecular representations are inherently transferable, the architecture presented here sets the stage for the development of machine-learned, coarse-grained force fields that are transferable across molecular systems

PEITC-mediated inhibition of mRNA translation is associated with both inhibition of mTORC1 and increased eIF2α phosphorylation in established cell lines and primary human leukemia cells.

Increased mRNA translation drives carcinogenesis and is an attractive target for the development of new anti-cancer drugs. In this work, we investigated effects of phenethylisothiocyanate (PEITC), a phytochemical with chemopreventive and anti-cancer activity, on mRNA translation. PEITC rapidly inhibited global mRNA translation in human breast cancer-derived MCF7 cells and mouse embryonic fibroblasts (MEFs). In addition to the known inhibitory effects of PEITC on mTORC1 activity, we demonstrate that PEITC increased eIF2α phosphorylation. PEITC also increased formation of stress granules which are typically associated with eIF2α phosphorylation and accumulation of translationally stalled mRNAs. Analysis of genetically modified MEFs demonstrated that optimal inhibition of global mRNA translation by PEITC was dependent on eIF2α phosphorylation, but not mTORC1 inhibition. We extended this study into primary leukemic B cells derived from patients with chronic lymphocytic leukaemia (CLL). CLL cells were stimulated in vitro with anti-IgM to mimic binding of antigen, a major driver of this leukemia. In CLL cells, PEITC increased eIF2α phosphorylation, inhibited anti-IgM-induced mTORC1 activation and decreased both basal and anti-IgM-induced global mRNA translation. PEITC also inhibited transcription and translation of MYC mRNA and accumulation of the MYC oncoprotein, in anti-IgM-stimulated cells. Moreover, treatment of CLL cells with PEITC and the BTK kinase inhibitor ibrutinib decreased anti-IgM-induced translation and induced cell death to a greater extent than either agent alone. Therefore, PEITC can inhibit both global and mRNA specific translation (including MYC) via effects on multiple regulatory pathways. Inhibition of mRNA translation may contribute to the chemopreventive and anti-cancer effects of PEITC

When lack of control enhances closeness to others : the case of unemployment and economic threat

When personal control is threatened, people often turn to their own group and show negativity towards others. In three studies, we tested an alternative prediction that the salient lack of personal control (vs. control) experienced in the context of unemployment can lead to connectedness and more positive perception of similar others (e.g., members of groups affected by unemployment or the economic crisis). In two European countries, we found experimental (Study 1: Poland) and correlational (Study 2: Spain) evidence that a lowered sense of control of unemployed people was related to more favorable intergroup evaluations. Furthermore, when lack of control related to unemployment threat was experimentally induced, participants perceived a Greek outgroup more positively, and this effect was mediated by identification with and similarity to this group (Study 3). We discuss the role of the shared experience of collective uncontrollability in promoting positive intergroup relation

Human Computer Interaction Meets Psychophysiology: A Critical Perspective

Human computer interaction (HCI) groups are more and more often exploring the utility of new, lower cost electroencephalography (EEG) interfaces for assessing user engagement and experience as well as for directly controlling computers. While the potential benefits of using EEG are considerable, we argue that research is easily driven by what we term naïve neurorealism. That is, data obtained with psychophysiological devices have poor reliability and uncertain validity, making inferences on mental states difficult. This means that unless sufficient care is taken to address the inherent shortcomings, the contributions of psychophysiological human computer interaction are limited to their novelty value rather than bringing scientific advance. Here, we outline the nature and severity of the reliability and validity problems and give practical suggestions for HCI researchers and reviewers on the way forward, and which obstacles to avoid. We hope that this critical perspective helps to promote good practice in the emerging field of psychophysiology in HCI

Information field theory for cosmological perturbation reconstruction and non-linear signal analysis

We develop information field theory (IFT) as a means of Bayesian inference on spatially distributed signals, the information fields. A didactical approach is attempted. Starting from general considerations on the nature of measurements, signals, noise, and their relation to a physical reality, we derive the information Hamiltonian, the source field, propagator, and interaction terms. Free IFT reproduces the well known Wiener-filter theory. Interacting IFT can be diagrammatically expanded, for which we provide the Feynman rules in position-, Fourier-, and spherical harmonics space, and the Boltzmann-Shannon information measure. The theory should be applicable in many fields. However, here, two cosmological signal recovery problems are discussed in their IFT-formulation. 1) Reconstruction of the cosmic large-scale structure matter distribution from discrete galaxy counts in incomplete galaxy surveys within a simple model of galaxy formation. We show that a Gaussian signal, which should resemble the initial density perturbations of the Universe, observed with a strongly non-linear, incomplete and Poissonian-noise affected response, as the processes of structure and galaxy formation and observations provide, can be reconstructed thanks to the virtue of a response-renormalization flow equation. 2) We design a filter to detect local non-linearities in the cosmic microwave background, which are predicted from some Early-Universe inflationary scenarios, and expected due to measurement imperfections. This filter is the optimal Bayes' estimator up to linear order in the non-linearity parameter and can be used even to construct sky maps of non-linearities in the data.Comment: 38 pages, 6 figures, LaTeX; version accepted by PR