A neural network system for transformation of regional cuisine style

We propose a novel system which can transform a recipe into any selected regional style (e.g., Japanese, Mediterranean, or Italian). This system has two characteristics. First the system can identify the degree of regional cuisine style mixture of any selected recipe and visualize such regional cuisine style mixtures using barycentric Newton diagrams. Second, the system can suggest ingredient substitutions through an extended word2vec model, such that a recipe becomes more authentic for any selected regional cuisine style. Drawing on a large number of recipes from Yummly, an example shows how the proposed system can transform a traditional Japanese recipe, Sukiyaki, into French style

Expression pattern of CXC chemokine receptor-4 is correlated with lymph node metastasis in human invasive ductal carcinoma

BACKGROUND: The stromal cell-derived factor-1/CXC chemokine receptor-4 (SDF-1/CXCR4) signal has been shown to be important in various immunological reactions. Recent studies have suggested that CXCR4 is expressed in certain cancer cells and that they use this chemokine receptor efficiently for metastasis formation. METHOD: The expression of CXCR4 was evaluated by immunohistochemical study in 79 surgically resected invasive ductal carcinomas, and the relation between the staining pattern and clinicopathological features was examined. RESULTS: CXCR4 was diffusely and homogeneously expressed in 59 cancers, which were further divided into 28 high-expression and 31 low-expression cancers by their staining intensity. The other 20 cancers showed heterogeneous immunoreactivity in tumor tissue, which was defined as focal type. In comparison with the diffuse type, focal type tumors showed significantly more extensive lymph node metastasis, because the number and extent of metastatic nodes were larger in the focal than the diffuse type. In the diffuse type, the rate of node-positive cases did not show a difference in staining intensity. However, high-CXCR4 tumors showed more extensive nodal metastasis in comparison with low-expression tumors. In contrast, the expression pattern of CXCR4 did not have a significant correlation with hematogeneous metastasis. The overall survival of these patients tended to be better in the diffuse type than in the focal type, although the difference was not statistically significant. CONCLUSION: The expression pattern of CXCR4 was significantly correlated with the degree of lymph node metastasis in breast cancers. Our data suggest that CXCR4 might be particularly important in facilitating metastasis through the lymphatic system

A computational neuroscience perspective on subjective wellbeing within the active inference framework

Understanding and promoting subjective wellbeing (SWB) has been the topic of increasing research, due in part to its potential contributions to health and productivity. To date, the conceptualization of SWB has been grounded within social psychology and largely focused on self-report measures. In this paper, we explore the potentially complementary tools and theoretical perspectives offered by computational neuroscience, with a focus on the active inference (AI) framework. This framework is motivated by the fact that the brain does not have direct access to the world; to select actions, it must instead infer the most likely external causes of the sensory input it receives from both the body and the external world. Because sensory input is always consistent with multiple interpretations, the brain’s internal model must use background knowledge, in the form of prior expectations, to make a “best guess” about the situation it is in and how it will change by taking one action or another. This best guess arises by minimizing an error signal representing the deviation between predicted and observed sensations given a chosen action—quantified mathematically by a variable called free energy (FE). Crucially, recent proposals have illustrated how emotional experience may emerge within AI as a natural consequence of the brain keeping track of the success of its model in selecting actions to minimize FE. In this paper, we draw on the concepts and mathematics in AI to highlight how different computational strategies can be used to minimize FE—some more successfully than others. This affords a characterization of how diverse individuals may adopt unique strategies for achieving high SWB. It also highlights novel ways in which SWB could be effectively improved. These considerations lead us to propose a novel computational framework for understanding SWB. We highlight several parameters in these models that could explain individual and cultural differences in SWB, and how they might inspire novel interventions. We conclude by proposing a line of future empirical research based on computational modelling that could complement current approaches to the study of wellbeing and its improvement

Magnetic Properties of Amorphous (Fe_<1-x>Cr_x)-P-C and (Co_<1-x>Fe_x)-B-Si Alloys

The magnetization measurement of amorphous (Fe_Cr_x)-P-C and (Co_Fe_x)-B-Si alloys have been made from liq. He temperature to room temperature and the magnetic moments, the temperature dependence of demagnetization and the exchange stiffness constants are determined. The composition dependence of the magnetic moment is similar to that of the crystalline Fe-Cr and Co-Fe alloys but this is not the case with the exchange stiffness constant

Quantum arbitrary waveform generator

Controlling the waveform of light is the key for a versatile light source in classical and quantum electronics. Although pulse shaping of classical light is a mature technique and has been used in various fields, more advanced applications would be realized by a light source that generates arbitrary quantum light with arbitrary temporal waveform. We call such a device a quantum arbitrary waveform generator (Q-AWG). The Q-AWG must be able to handle versatile quantum states of light, which are fragile. Thus, the Q-AWG requires a radically different methodology from classical pulse shaping. In this paper, we invent an architecture of Q-AWGs that can operate semi-deterministically at a repetition rate over GHz in principal. We demonstrate its core technology via generating highly non-classical states with waveforms that have never been realized before. This result would lead to powerful quantum technologies based on Q-AWGs such as practical optical quantum computing.Comment: 24 pages, 5 figure

Active auroral arc powered by accelerated electrons from very high altitudes

オーロラ粒子の加速領域が超高高度まで広がっていたことを解明 －オーロラ粒子の加速の定説を覆す発見－. 京都大学プレスリリース. 2021-01-20.Bright, discrete, thin auroral arcs are a typical form of auroras in nightside polar regions. Their light is produced by magnetospheric electrons, accelerated downward to obtain energies of several kilo electron volts by a quasi-static electric field. These electrons collide with and excite thermosphere atoms to higher energy states at altitude of ~ 100 km; relaxation from these states produces the auroral light. The electric potential accelerating the aurora-producing electrons has been reported to lie immediately above the ionosphere, at a few altitudes of thousand kilometres1. However, the highest altitude at which the precipitating electron is accelerated by the parallel potential drop is still unclear. Here, we show that active auroral arcs are powered by electrons accelerated at altitudes reaching greater than 30, 000 km. We employ high-angular resolution electron observations achieved by the Arase satellite in the magnetosphere and optical observations of the aurora from a ground-based all-sky imager. Our observations of electron properties and dynamics resemble those of electron potential acceleration reported from low-altitude satellites except that the acceleration region is much higher than previously assumed. This shows that the dominant auroral acceleration region can extend far above a few thousand kilometres, well within the magnetospheric plasma proper, suggesting formation of the acceleration region by some unknown magnetospheric mechanisms