Dissipative quantum metrology in manybody systems of identical particles

Estimation of physical parameters is a must in almost any part of science and technology. The enhancement of the performances in this task, e.g., beating the standard classical shot-noise limit, using available physical resources is a major goal in metrology. Quantum metrology in closed systems has indicated that entanglement in such systems may be a useful resource. However, it is not yet fully understood whether in open quantum systems such enhancements may still show up. Here, we consider a dissipative (open) quantum system of identical particles in which a parameter of the open dynamics itself is to be estimated. We employ a recently-developed dissipative quantum metrology framework, and investigate whether the entanglement produced in the course of the dissipative dynamics may help the estimation task. Specifically, we show that even in a Markovian dynamics, in which states become less distinguishable in time, at small enough times entanglement generated by the dynamics may offer some advantage over the classical shot-noise limit.Comment: 9 pages, 2 figure

Correlations in quantum thermodynamics: Heat, work, and entropy production

We provide a characterization of energy in the form of exchanged heat and work between two interacting constituents of a closed, bipartite, correlated quantum system. By defining a binding energy we derive a consistent quantum formulation of the first law of thermodynamics, in which the role of correlations becomes evident, and this formulation reduces to the standard classical picture in relevant systems. We next discuss the emergence of the second law of thermodynamics under certain---but fairly general---conditions such as the Markovian assumption. We illustrate the role of correlations and interactions in thermodynamics through two examples.Comment: 16 page

A new family of matrix product states with Dzyaloshinski-Moriya interactions

We define a new family of matrix product states which are exact ground states of spin 1/2 Hamiltonians on one dimensional lattices. This class of Hamiltonians contain both Heisenberg and Dzyaloshinskii-Moriya interactions but at specified and not arbitrary couplings. We also compute in closed forms the one and two-point functions and the explicit form of the ground state. The degeneracy structure of the ground state is also discussed.Comment: 15 pages, 1 figur

Review paper: Experimental models of absence epilepsy

Introduction: Absence epilepsy is a brief non-convulsive seizure associated with sudden abruptness in consciousness. Because of the unpredictable occurrence of absence seizures and the ethical issues of human investigation on the pathogenesis and drug assessment, researchers tend to study animal models. This paper aims to review the advantages and disadvantages of several animal models of nonconvulsive induced seizure. Methods: The articles that were published since 1990 were assessed. The publications that used genetic animals were analyzed, too. Besides, we reviewed possible application methods of each model, clinical types of seizures induced, purposed mechanism of epileptogenesis, their validity, and relevance to the absence epileptic patients. Results: The number of studies that used genetic models of absence epilepsy from years of 2000 was noticeably more than pharmacological models. Genetic animal models have a close correlation of electroencephalogram features and epileptic behaviors to the human condition. Conclusion: The validity of genetic models of absence epilepsy would motivate the researchers to focus on genetic modes in their studies. As there are some differences in the pathophysiology of absence epilepsy between animal models and humans, the development of new animal models is necessary to understand better the epileptogenic process and, or discover novel therapies for this disorder. © 2020 Iran University of Medical Sciences. All rights reserved

The balanced scorecard as a strategic management tool in hospital pharmacies: an experimental study

Purpose: A balanced scorecard (BSC) is an applied tool for implementing strategic management in various organizations. Implementing strategic management using the BSC approach has not received much attention in pharmacy departments. This study aims to provide a model for the strategic management of pharmacy departments using the BSC framework. Design/methodology/approach: This experimental study was conducted from 2015 to 2018 in a 300-bed hospital and regional healthcare centers affiliated with the Petroleum Industry Health Organization in Tehran province, Iran. After carefully reviewing the organization's mission and vision, the strategic objectives were determined via the internal matrix and the external matrix (IE matrix), and the strengths–weaknesses–opportunities–threats matrix (SWOT matrix) were examined. Then, six BSC measures and interventions were identified, and each was examined from the perspectives of finance, patient satisfaction, internal processes and learning/growth. Finally, the proposed strategy was evaluated. Findings: Results showed significant increases in patient satisfaction and gross profit. The observed increase range, from 0.09 to 0.29, indicates more effective operational management for optimal resource utilization. In addition, the pharmacy department was able to save US $539,137 by implementing prepared protocols for expensive medications. Similarly, the pharmacy department saved$442,899 during the two years of our strategic management plan by implementing the standard mechanism for returning unused medications to the pharmacy department after patients were discharged from various treatment units. Originality/value: This study is among the first studies to demonstrate the simultaneous development, implementation and evaluation of the proposed strategy using the BSC in a pharmacy department in a public healthcare center. The BSC application improved the optimal use of resources and reduced costs while increasing patient satisfaction. It appears that the application of such an intervention may be as valuable to public pharmacies as it is to other private centers

EVALUATION OF DIFFERENT PARAMETERS FOR PLANT CLASSIFICATION BY PRE-TRAINED DEEP LEARNING MODELS WITH BIGEARTHNET DATASET

Vegetation monitoring and mapping are essential for a diverse range of environmental problems such as forest management, food resources, and climate change assessment. Several methods have been developed to classify different vegetation types based on remote sensing (RS) data. Land use classification has been revolutionized with the advent of neural networks. Various vegetation types were classified using multispectral Sentinel-2 satellite images due to their high spatial resolution and spectral information. Deep Convolutional Neural Network is considered a promising method for classifying remote sensing images with high spatial resolution due to its powerful feature extraction capabilities. However, large labeled datasets are required for better classification performance, so we have used pre-trained ResNet networks with 152 layers, 50 layers, and 101 layers trained on Big Earth Net (BEN). In order to obtain the best network performance and evaluate the sensitivity of the parameters in this study, we have performed two experiments: 1) the effect of different patch sizes and 2) increasing the number of images. The results demonstrate that ResNet 152 shows the highest accuracy with patches of 120 × 120 pixels, with an accuracy of 76.62%, and ResNet 50 is the best with an accuracy of 76.2% since the process of this network does not take much time

Exact symmetry breaking ground states for quantum spin chains

We introduce a family of spin-1/2 quantum chains, and show that their exact ground states break the rotational and translational symmetries of the original Hamiltonian. We also show how one can use projection to construct a spin-3/2 quantum chain with nearest neighbor interaction, whose exact ground states break the rotational symmetry of the Hamiltonian. Correlation functions of both models are determined in closed form. Although we confine ourselves to examples, the method can easily be adapted to encompass more general models.Comment: 4 pages, RevTex. 4 figures, minor changes, new reference

The serotonergic psychedelic N,N-dipropyltryptamine alters information-processing dynamics in cortical neural circuits

Most of the recent work in psychedelic neuroscience has been done using non-invasive neuroimaging, with data recorded from the brains of adult volunteers under the influence of a variety of drugs. While this data provides holistic insights into the effects of psychedelics on whole-brain dynamics, the effects of psychedelics on the meso-scale dynamics of cortical circuits remains much less explored. Here, we report the effects of the serotonergic psychedelic N,N-diproptyltryptamine (DPT) on information-processing dynamics in a sample of in vitro organotypic cultures made from rat cortical tissue. Three hours of spontaneous activity were recorded: an hour of pre-drug control, and hour of exposure to 10$\mu$M DPT solution, and a final hour of washout, once again under control conditions. We found that DPT reversibly alters information dynamics in multiple ways: first, the DPT condition was associated with higher entropy of spontaneous firing activity and reduced the amount of time information was stored in individual neurons. Second, DPT also reduced the reversibility of neural activity, increasing the entropy produced and suggesting a drive away from equilibrium. Third, DPT altered the structure of neuronal circuits, decreasing the overall information flow coming into each neuron, but increasing the number of weak connections, creating a dynamic that combines elements of integration and disintegration. Finally, DPT decreased the higher-order statistical synergy present in sets of three neurons. Collectively, these results paint a complex picture of how psychedelics regulate information processing in meso-scale cortical tissue. Implications for existing hypotheses of psychedelic action, such as the Entropic Brain Hypothesis, are discussed.Comment: 19 pages, 2 figure

Chemical composition, free-radical-scavenging and insecticidal activities of the aerial parts of Stachys byzantina

Stachys byzantina K. Koch. is an Iranian endemic species of the genus Stachys L., which comprises about 300 species, and is one of the largest genera of the family Lamiaceae. A combination of solid phase extraction (SPE) and high pressure liquid chromatography (HPLC) of the methanolic extract of the aerial parts of S. byzantina afforded three phenylethanoids, 2'-O-arabinosyl verbascoside (1), verbascoside (2), aeschynanthoside C (3) and three flavones apigenin 7-O-glucoside (4), apigenin 7-O-(6-p-coumaroyl)-glucoside (5) and apigenin (6). The structures of these compounds were determined by spectroscopic methods. Free-radical-scavenging and insecticidal properties of the crude extracts, the fractions and the isolated compounds were assessed.