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Accelerated environmental impacts are a growing concern in the modern world. Electric mobility and the transition to a cleaner energy matrix have become increasingly discussed topics. In this context, this work presents a framework for controlling an electric vehicle (EV)-charging station integrated into a microgrid application as a basis for creating the infrastructure integrated into a smart grid concept. Considering the electrification of the transportation sector future perspectives, a brief review is conducted on the impacts of EV fleet growth in different countries and how smart-charging technologies are identified as solutions for mitigating the negative effects of energy and power consumption associated with EV-charging stations. An analysis of the technical characteristics and the tools that enable the deployment of a fleet-charging operator are examined, specifically focusing on the communication protocol for EVs, such as the OCPP (Open Charge Point Protocol) parameterization/configuration. A new EV-charging station control method is proposed to manage the impacts of distributed solar photovoltaic generation and mitigate the effects of the duck curve. Finally, an integration architecture via IEC 61850 for these elements is proposed, in a practical implementation for variable power control, considering different strategies to deal with distributed generation impact using EV-fleet-charging power demand dynamic management.

Extraction of global structural regularities provides general 'gist' of our everyday visual environment as it does the gist of abnormality for medical experts reviewing medical images. We investigated whether naïve observers could learn this gist of medical abnormality. Fifteen participants completed nine adaptive training sessions viewing four categories of unilateral mammograms: normal, obvious-abnormal, subtle-abnormal, and global signals of abnormality (mammograms with no visible lesions but from breasts contralateral to or years prior to the development of cancer) and receiving only categorical feedback. Performance was tested pre-training, post-training, and after a week's retention on 200 mammograms viewed for 500 ms without feedback. Performance measured as d' was modulated by mammogram category, with the highest performance for mammograms with visible lesions. Post-training, twelve observed showed increased d' for all mammogram categories but a subset of nine, labelled learners also showed a positive correlation of d' across training. Critically, learners learned to detect abnormality in mammograms with only the global signals, but improvements were poorly retained. A state-of-the-art breast cancer classifier detected mammograms with lesions but struggled to detect cancer in mammograms with the global signal of abnormality. The gist of abnormality can be learned through perceptual/incidental learning in mammograms both with and without visible lesions, subject to individual differences. Poor retention suggests perceptual tuning to gist needs maintenance, converging with findings that radiologists' gist performance correlates with the number of cases reviewed per year, not years of experience. The human visual system can tune itself to complex global signals not easily captured by current deep neural networks.

Hyperkyhosis is thought to be a fall risk factor in older adults. This large study of older men found that fall risk increased with greater kyphosis measured with the blocks method, but did not find an association between kyphosis and falls when measured by the commonly used the Cobb angle method.IntroductionResearch suggests an association between hyperkyphosis and falls in community-dwelling older adults, though this has not been investigated within large, population-based studies. This study sought to determine whether two measures of kyphosis prospectively predict fall risk over 3 years among older men.MethodsWithin the Osteoporotic Fractures in Men Study (MrOS), we conducted two 3-year prospective studies of 2346 and 2928 men. The first group had kyphosis measured by the Cobb angle at visit 1, while the second group had kyphosis assessed with the blocks method at visit 3; both groups then self-reported falls tri-annually for 3 years. Poisson regression with GEE was used to obtain relative risks (RR) of falls.ResultsThe fall rates over 3 years were 651/1000 person-years among the visit 1 sample (mean age 74 ± 6 years) and 839/1000 person-years among the visit 3 sample (mean age 79 ± 5 years). In adjusted models of the visit 3 sample, the risk of falls was increased by 12% for each standard deviation increase (1.4 blocks) in the number of blocks required to achieve a neutral head and neck position (RR = 1.12, 95% CI = 1.06, 1.18). The Cobb angle was not associated with falls in the visit 1 sample.ConclusionsAlthough the Cobb angle did not predict falls in community-dwelling older men over 3 years, the blocks method of measuring kyphosis was predictive of falls in this population. This difference could be due to the Cobb angle's focus on thoracic kyphosis, whereas the blocks method may additionally capture abnormal cervical spine curvature.

Abstract The application of automation techniques to water pump systems, combined with modern control techniques, has been increasing the hydraulic and energy efficiency of such systems. In this context, the objective of this work is to present an intelligent method of flow control based on Brain Emotional Learning Basic Intelligent Control (BELBIC), which will be applied to an experimental workbench of a pumping system, located in the Energy Efficiency and Energy Quality Laboratory (LEEQE) at Federal University of Pernambuco (UFPE). The parameters of this controller are optimized with a particle swarm optimization (PSO) technique with minimization of Integral Absolute Error (IAE). Initial tests were performed in a computational environment so that the system’s performance could be pre-tested, thereby the dynamics of the system was modeled from real data generated in the process. The experimental results were obtained through the implementation of this control system in a programmable logic controller (PLC), which was the device responsible for all the automation of the workbench previously mentioned. The data of this workbench were collected using a supervisory system exclusively developed for this work. These data were then used to analyze the performance of the proposed control system, which demonstrated that its behavior was efficient.

Accelerated environmental impacts are a growing concern in the modern world. Electric mobility and the transition to a cleaner energy matrix have become increasingly discussed topics. In this context, this work presents a framework for controlling an electric vehicle (EV)-charging station integrated into a microgrid application as a basis for creating the infrastructure integrated into a smart grid concept. Considering the electrification of the transportation sector future perspectives, a brief review is conducted on the impacts of EV fleet growth in different countries and how smart-charging technologies are identified as solutions for mitigating the negative effects of energy and power consumption associated with EV-charging stations. An analysis of the technical characteristics and the tools that enable the deployment of a fleet-charging operator are examined, specifically focusing on the communication protocol for EVs, such as the OCPP (Open Charge Point Protocol) parameterization/configuration. A new EV-charging station control method is proposed to manage the impacts of distributed solar photovoltaic generation and mitigate the effects of the duck curve. Finally, an integration architecture via IEC 61850 for these elements is proposed, in a practical implementation for variable power control, considering different strategies to deal with distributed generation impact using EV-fleet-charging power demand dynamic management. [ABSTRACT FROM AUTHOR]

Hyperkyphosis commonly affects older persons and is associated with morbidity and mortality. Many have hypothesized that hyperkyphosis increases fall risk. Within this prospective study of older adults, kyphosis was significantly associated with incident falls over 1 year. Measures of hyperkyphosis could enhance falls risk assessments during primary care office visits.IntroductionTo determine the association between four measures of kyphosis and incident and injurious falls in older persons.MethodsCommunity-dwelling adults aged 65 and older (n = 72) residing in southern California were invited to participate in a prospective cohort study. Participants had kyphosis assessed four ways. Two standing measures included a flexicurve ruler placed against the back to derive a kyphotic index and the Debrunner kyphometer, a protractor used to measure the kyphotic angle in degrees. Two lying measures included the blocks method (number of 1.7 cm blocks needed to achieve a neutral head position while lying supine) and traditional Cobb angle calculation derived from DXA based lateral vertebral assessment. Baseline demographic, clinical, and other health information (including a timed up and go (TUG) test) were assessed at a clinic visit. Participants were followed monthly through email or postcard for 1 year, with falls outcomes confirmed through telephone interview.ResultsMean age was 77.8 (± 7.1) among the 52 women and 20 men. Over 12 months, 64% of participants experienced at least one incident fall and 35% experienced an injurious fall. Each standard deviation increase in kyphosis resulted in more than doubling the adjusted odds of an incident fall, even after adjusting for TUG. Odds of injurious falls were less consistent across measures; after adjusting for TUG, only the blocks method was associated with injurious falls.ConclusionsEach kyphosis measure was independently associated with incident falls. Findings were inconsistent for injurious falls; the blocks measure suggested the strongest association. If these findings are replicated, the blocks measure could be incorporated into office visits as a quick and efficient tool to identify patients at increased fall risk.

Electric vehicle (EV) charging may impose a substantial power demand on existing low voltage (LV) and medium voltage (MV) networks, which are usually not prepared for high power demands in short time intervals. The influx of E-mobility may require an increase in grid reinforcements, but these can be reduced and optimized by a combination of new technologies, tools, and strategies, such as the deployment of solar PV generation integrated with aggregated energy storage systems. One of the challenges in the implementation of charging infrastructures in public stations is coupling the projected sizes of energy demand and power requirements in each location for each charger. This paper describes a method to estimate projected values for energy consumption and power demand in EV fast charging stations (CS). The proposed ideas were applied in a concept facility located in Campinas, Brazil, in a structure equipped with two 50 kW DC Fast Chargers, local 12.5 kW/13.2 kWp PV generation (to reduce energy impacts to the grid), and a 100 kW/200 kWh storage system, using electrochemical batteries (to minimize peak power requirements).

Objective: The purpose of this study was to evaluate a sit to stand test with the walk test for the identification of unilateral cranial cruciate ligament rupture in dogs. Materials and Methods: Peak vertical force and vertical impulse were measured on a pressure‐sensitive walkway, during a sit to stand test and walk test, and in 10 dogs with unilateral cranial cruciate ligament rupture and 18 non‐lame dogs. Data collected were used to calculate symmetry indices (SI) of ipsilateral and contralateral hindlimbs (HL), diagonal limb pairs (DLP) and ipsilateral limb pairs (ILP). Results: The symmetry indices of peak vertical force of HL during the walk test and sit to stand test were 100% and 90% sensitive for discriminating lame and non‐lame dogs respectively. The symmetry indices of vertical impulse of HLs during the walk test and sit to stand test were 100% and 50% sensitive for discriminating lame and non‐lame dogs respectively. Analysis of ipsilateral and diagonal limb pairs did not improve the discrimination in either test. The time taken to collect data from the sit to stand test data was shorter than for the walk test. Clinical Significance: Whilst the sit to stand test required a shorter time for collection of data than the walk test, it did not accurately identify all dogs with lameness associated with CCLR, and thus has relatively limited clinical utility in its tested form. [ABSTRACT FROM AUTHOR]

In type 1 diabetes (T1D) development, proinflammatory cytokines (PIC) released by immune cells lead to increased reactive oxygen species (ROS) production in β-cells. Nonetheless, the temporality of the events triggered and the role of different ROS sources remain unclear. Isolated islets from C57BL/6J wild-type (WT), NOX1 KO and NOX2 KO mice were exposed to a PIC combination. We show that cytokines increase O2•− production after 2 h in WT and NOX1 KO but not in NOX2 KO islets. Using transgenic mice constitutively expressing a genetically encoded compartment specific H2O2 sensor, we show, for the first time, a transient increase of cytosolic/nuclear H2O2 in islet cells between 4 and 5 h during cytokine exposure. The H2O2 increase coincides with the intracellular NAD(P)H decrease and is absent in NOX2 KO islets. NOX2 KO confers better glucose tolerance and protects against cytokine-induced islet secretory dysfunction and death. However, NOX2 absence does not counteract the cytokine effects in ER Ca2+ depletion, Store-Operated Calcium Entry (SOCE) increase and ER stress. Instead, the activation of ER stress precedes H2O2 production. As early NOX2-driven ROS production impacts β-cells’ function and survival during insulitis, NOX2 might be a potential target for designing therapies against early β-cell dysfunction in the context of T1D onset.

Purpose: The purpose of this paper is to identify the key aspects of transformation of universities towards sustainability, such as the ideal characteristics of the "sustainable university", and the drivers and barriers in the transformation, by comparing the strategies of seven universities world-wide. Design/methodology/approach: A systems transformation analysis of seven case studies has been applied through a self-evaluation based on the tridimensional Framework-Level-Actors (FLA) method. Findings: The study shows that none of the three dimensions of change is predominant over the others. The main barrier to be overcome is the lack of incentive structure for promoting changes at the individual level. The main drivers for change are the presence of "connectors" with society, the existence of coordination bodies and projects, and the availability of funding, all of which are important for progress. Enhancing interdisciplinarity is a strategic objective at almost all of these universities, while transformative learning is less present. A common characteristic for most of the institutions is establishing and supporting networks of expertise within the universities. These universities show important strategic efforts and initiatives that drive and nucleate change for sustainable development, the result of a combination of drivers. Practical implications: The FLA-method has proved useful for being used at the level of comparing case-studies through a bird's-eye perspective. Originality/value: The paper demonstrates the application of a simple tool that gives a global perspective on transformational strategies used in seven cases world-wide in the search for commonalities and differences. (Contains 3 tables, 2 figures and 2 notes.)