A smart process controller framework for Industry 4.0 settings

This paper presents a smart supervisory framework for a single process controller, designed for Industry 4.0 shop floors. This digitization of a full supervisory suite for a single process controller enables self-awareness, self-diagnosis, self-prognosis, and self-healing (by definition, these "self" elements are missing from other supervisory frameworks diagnosing numerous controllers in parallel). The proposed framework is aligned with the concept of a Cyber Physical System (CPS), since its implementation generates a rich cyber physical entity of the controlled process. This CPS entity can either be considered as the process digital twin, or can provide a solid basis for generating it. Finally, the framework includes the main characteristics of Industry 4.0, such as advanced use of Artificial Intelligence (AI) and big data analysis. The framework is based on four modules: (1) Control and Awareness module—performing both continuous process control and adjustments, as well as machine learning (ML) and statistical process control (SPC) for identifying abnormalities that require further diagnosis; (2) Process -diagnosis module—performing continual (recurrent) analysis of the process state and trends; (3) Prognosis and Healing module—performing prognosis and automated intervention via parameter changes, re-configurations, and automated maintenance; (4) External Interaction Platform—an interactive module for interfacing with experts, presenting them with the process analysis information and obtaining feedback from them as part of a learning process. Using an implementation showcase to illustrate the methodological framework’s applicability, we demonstrate its real-world potential. The proposed framework could serve as a guide for implementing smart process control and maintenance systems in Industry 4.0 shop floors. It could also provide a firm basis for comparison with future suggested frameworks. Future research directions could include pursuing improvements to the proposed process control framework and validating the framework by case studies of its implementation.

     

Effect of Freezer Programs on Real-Time Storage Results of Dissolution Profiles

Carstensen and Rhodes¹ have suggested that when, in stability programs, assays cannot be performed immediately after the protocol-designated storage time, then freezing them until such a time when assays can be performed would be a reasonable manner to retain the protocol schedule. They caution, however, that such a procedure may not be valid for dissolution data. The article to follow deals with real-time data showing that such a process is feasible for Nalidixic Acid tablets (and presumably for other tablets as well), and that, furthermore, the dissolution pattern would seem to be “frozen” as well.     

Modeling of precipitation hardening in Mg-based alloys

This work deals with the development of Mg-based alloys with enhanced properties at elevated temperatures. This is achieved by precipitation of binary phases such as MgZn₂ and Mg₂Sn during the aging of these alloys. The aim of the present work is to develop and calibrate a model for precipitation hardening in Mg-based alloys, as different types of precipitates form simultaneously. The modified Langer-Schwartz approach, while taking into account nucleation, growth and coarsening of the new phase precipitations, was used for the analysis of precipitates’ evolution and precipitation hardening during aging of Mg-based alloys. Two strengthening mechanisms associated with particle-dislocation interaction (shearing and bypassing) were considered to be operating simultaneously due to particle size-distribution. Parameters of the model, R _N i and k _{σ i} , were found by fitting of calculated densities and average sizes of precipitates with ones estimated from experiments. The effective diffusion coefficients of phase formation processes, which determine the strengthening kinetics, were estimated from the hardness maximum positions on the aging curves.     

Effects of situational demand upon social enjoyment and preference in schizotypy.

The socioemotional functioning of schizophrenic and schizotypic individuals is marked by withdrawal, poor organization, and limited emotional displays. Such behavioral tendencies and lack of social enjoyment in schizotypy could be linked to the relative situational demands or role ambiguity inherent in specific social activities. To determine whether high-schizotypy individuals prefer more clearly role-defined social activities (e.g., visiting relatives) to more ambiguous, novel situations (e.g., going alone to a party), the authors gathered reports from 52 high-schizotypy and 60 low-schizotypy individuals on their enjoyment and frequency of engaging in social situations varying in relative situational demand. Parallel reports were obtained from knowledgeable others. Group × Situational Demand interactions revealed the hypothesized pattern of reduced frequency and enjoyment ratings for ambiguous or novel situations by the high-schizotypy participants in both self and others' reports. Groups were more comparable in their reported frequency and enjoyment of less ambiguous situations. Results suggest the importance of situational demands in the socioemotional experience and behavioral withdrawal in schizotypy. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

High affinity presentation of an autoantigenic peptide in type I diabetes by an HLA class II protein encoded in a haplotype protecting from disease

Tissue composition and the distribution of body mass are described for four genera of East African Bovidae (Madoqua, Gazella, Damaliscus, Hippotragus) with supporting data from four others (Neotragus, Oryx, Tragelaphus, Connochaetes). These species are high in muscle mass, an adaptation convergent with other high-speed terrestrial cursors, bounders, and saltators. The segments below the elbow/cubitus and knee/stifle/genu joints in small bovids are both lighter in percent of total body mass (8.6% TBM) and less heavily muscled (10-15% of total limb musculature) than those segments in macaques (13.6% TBM, 20-25% of the limb musculature). Bovid species differ from one another in the regional distribution of muscle mass. Madoqua kirkii (4-5 kg) concentrates muscle in the lumbar extensors and hindlimbs; large species such as Damaliscus doreas (50-60 kg) and Hippotragus niger (160-220 kg) distribute it more evenly between the lumbar and cervical regions and between the hindlimbs and forelimbs. Gazella dorcas (10-20 kg) is quantitatively intermediate in those characteristics. The redistribution of muscle mass with increasing size correlates with the loss of axial bending of the vertebral column: in small, hindlimb dominant, 'dorsomobile' species such as Madoqua sagittal mobility increases stride length through 'extended' suspension; in large 'dorsostable' species such as Damaliscus and Hippotragus the vertebral column resists bending, consequently abbreviating or omitting this non-contact phase of the gait cycle. Locomotor adaptation as it is reflected in size, shape, and musculoskeletal structure is the key to habitat choice, dietary specialization, social structure, and male agonistic behavior and, therefore, central to the fabric of behavioral ecology.     

Generalization of the Gram-Charlier/Edgeworth Series and Application to Time-Frequency Analysis

We derive a general equation relating probability densities and as special cases we the obtain Gram-Charlier and Edgeworth series. This allows us to generalize these methods and clarify a number of issues pertaining to both probability theory and time-frequency analysis. In particular we show how the Gram-Charlier and Edgeworth series are related to the kernel method of time-frequency analysis. The approach allows us to construct densities that satisfy given constraints such as joint moments or conditional moments. Also, we show that the kernel has to be signal dependent and that to obtain a proper distribution it should be the ratio of two characteristic functions.