Система мониторинга и учета энергоресурсов

Система предназначена для автоматизации процесса получения объективных данных о фактическом потреблении энергоресурсов на объектах жилищного и нежилого фондов с использованием домовых и/или квартирных приборов учета.The system is designed to automate the process of obtaining objective data on the actual consumption of energy resources on the objects of housing and non-residential funds using house and / or apartment accounting devices

Structure determination of biogenic crystals directly from 3D electron diffraction data

Highly reflective assemblies of purine, pteridine, and flavin crystals are used in the coloration and visual systems of many different animals. However, structure determination of biogenic crystals by single-crystal XRD is challenging due to the submicrometer size and beam sensitivity of the crystals, and powder XRD is inhibited due to the small volumes of powders, crystalline impurity phases, and significant preferred orientation. Consequently, the crystal structures of many biogenic materials remain unknown. Herein, we demonstrate that the 3D electron diffraction (3D ED) technique provides a powerful alternative approach, reporting the successful structure determination of biogenic guanine crystals (from spider integument, fish scales, and scallop eyes) from 3D ED data confirmed by analysis of powder XRD data. The results show that all biogenic guanine crystals studied are the previously known β-polymorph. This study highlights the considerable potential of 3D ED for elucidating the structures of biogenic molecular crystals in the nanometer-to-micrometer size range. This opens up an important opportunity in the development of organic biomineralization, for which structural knowledge is critical for understanding the optical functions of biogenic materials and their possible applications as sustainable, biocompatible optical materials

Crystalline phase-change materials : disorder, medium-range order and electrical switching

In this study the focus lies on the crystalline phase of phase-change materials. The crystalline phase has an exceptional high degree of disorder and is characterized by a unique bonding mechanism, resonant bonding. The degree of disorder in the crystalline phase is comparable with the degree of disorder found in amorphous metals. As the resistivity of crystalline phase will be analyzed, it will be shown that the conduction mechanism is governed by disorder. Especially the annealing dependency of the resistivity can be correlated to a disorder induced localization of the charge carriers. As disorder plays a decisive role for the resistivity, the structural properties of crystalline phase-change materials and distortions in the short to medium range order are studied in detail. To analyze the degree of disorder neutron pair distribution measurements of crystalline phase change materials will be analyzed and discussed. To round this up and give a more device oriented perspective, ideas for future generation phase-change memory technologies based on disorder induced localization will be presented. Along with this, the preparation and characterization of current state-of-the-art phase change memory cells is investigated. In this phase-change memory characterization, the limits of the switching speed are tested

Crystalline phase-change materials : disorder, medium-range order and electrical switching

In this study the focus lies on the crystalline phase of phase-change materials. The crystalline phase has an exceptional high degree of disorder and is characterized by a unique bonding mechanism, resonant bonding. The degree of disorder in the crystalline phase is comparable with the degree of disorder found in amorphous metals. As the resistivity of crystalline phase will be analyzed, it will be shown that the conduction mechanism is governed by disorder. Especially the annealing dependency of the resistivity can be correlated to a disorder induced localization of the charge carriers. As disorder plays a decisive role for the resistivity, the structural properties of crystalline phase-change materials and distortions in the short to medium range order are studied in detail. To analyze the degree of disorder neutron pair distribution measurements of crystalline phase change materials will be analyzed and discussed. To round this up and give a more device oriented perspective, ideas for future generation phase-change memory technologies based on disorder induced localization will be presented. Along with this, the preparation and characterization of current state-of-the-art phase change memory cells is investigated. In this phase-change memory characterization, the limits of the switching speed are tested

Novel architecture for gated recurrent unit autoencoder trained on time series from electronic health records enables detection of ICU patient subgroups

Electronic health records (EHRs) are used in hospitals to store diagnoses, clinician notes, examinations, lab results, and interventions for each patient. Grouping patients into distinct subsets, for example, via clustering, may enable the discovery of unknown disease patterns or comorbidities, which could eventually lead to better treatment through personalized medicine. Patient data derived from EHRs is heterogeneous and temporally irregular. Therefore, traditional machine learning methods like PCA are ill-suited for analysis of EHR-derived patient data. We propose to address these issues with a new methodology based on training a gated recurrent unit (GRU) autoencoder directly on health record data. Our method learns a low-dimensional feature space by training on patient data time series, where the time of each data point is expressed explicitly. We use positional encodings for time, allowing our model to better handle the temporal irregularity of the data. We apply our method to data from the Medical Information Mart for Intensive Care (MIMIC-III). Using our data-derived feature space, we can cluster patients into groups representing major classes of disease patterns. Additionally, we show that our feature space exhibits a rich substructure at multiple scales

Electron crystallography and dedicated electron-diffraction instrumentation

Electron diffraction (known also as ED, 3D ED or microED) is gaining momentum in science and industry. The application of electron diffraction in performing nano-crystallography on crystals smaller than 1 µm is a disruptive technology that is opening up fascinating new perspectives for a wide variety of compounds required in the fields of chemical, pharmaceutical and advanced materials research. Electron diffraction enables the characterization of solid compounds complementary to neutron, powder X-ray and single-crystal X-ray diffraction, as it has the unique capability to measure nanometre-sized crystals. The recent introduction of dedicated instrumentation to perform ED experiments is a key aspect of the continued growth and success of this technology. In addition to the ultra-high-speed hybrid-pixel detectors enabling ED data collection in continuous rotation mode, a high-precision goniometer and horizontal layout have been determined as essential features of an electron diffractometer, both of which are embodied in the Eldico ED-1. Four examples of data collected on an Eldico ED-1 are showcased to demonstrate the potential and advantages of a dedicated electron diffractometer, covering selected applications and challenges of electron diffraction: (i) multiple reciprocal lattices, (ii) absolute structure of a chiral compound, and (iii) R-values achieved by kinematic refinement comparable to X-ray data