Maximum Power Point Tracking for Photovoltaic Systems Under Partial Shading Conditions Using Bat Algorithm

The vibrant, noiseless, and low-maintenance characteristics of photovoltaic (PV) systems make them one of the fast-growing technologies in the modern era. This on-demand source of energy suffers from low-output efficiency compared with other alternatives. Given that PV systems must be installed in outdoor spaces, their efficiency is significantly affected by the inevitable complication called partial shading (PS). Partial shading occurs when different sections of the solar array are subjected to different levels of solar irradiance, which then leads to a multiple-peak function in the output characteristics of the system. Conventional tracking techniques, along with some nascent/novel approaches used for the tracking maximum power point (MPP), are unsatisfactory when subjected to PS, eventually leading to the reduced efficiency of the PV system. This study aims at investigating the use of the bat algorithm (BA), a nature-inspired metaheuristic algorithm for MPP tracking (MPPT) subjected to PS conditions. A brief explanation of the behavior of the PV system under the PS condition and the advantages of using BA for estimating the MPPT of the PV system under PS condition is discussed. The deployment of the BA for the MPPT in PV systems is then explained in detail highlighting the simulation results which verifies whether the proposed method is faster, more efficient, sustainable and more reliable than conventional and other soft computing-based methods. Three testing conditions are considered in the simulation, and the results indicate that the proposed technique has high efficiency and reliability even when subjected to an acute shading condition

Short-Term Forecasting of the Output Power of a Building-Integrated Photovoltaic System Using a Metaheuristic Approach

The rapidly increasing use of renewable energy resources in power generation systems in recent years has accentuated the need to find an optimum and efficient scheme for forecasting meteorological parameters, such as solar radiation, temperature, wind speed, and sun exposure. Integrating wind power prediction systems into electrical grids has witnessed a powerful economic impact, along with the supply and demand balance of the power generation scheme. Academic interest in formulating accurate forecasting models of the energy yields of solar energy systems has significantly increased around the world. This significant rise has contributed to the increase in the share of solar power, which is evident from the power grids set up in Germany (5 GW) and Bavaria. The Spanish government has also taken initiative measures to develop the use of renewable energy, by providing incentives for the accurate day-ahead forecasting. Forecasting solar power outputs aids the critical components of the energy market, such as the management, scheduling, and decision making related to the distribution of the generated power. In the current study, a mathematical forecasting model, optimized using differential evolution and the particle swarm optimization (DEPSO) technique utilized for the short-term photovoltaic (PV) power output forecasting of the PV system located at Deakin University (Victoria, Australia), is proposed. A hybrid self-energized datalogging system is utilized in this setup to monitor the PV data along with the local environmental parameters used in the proposed forecasting model. A comparison study is carried out evaluating the standard particle swarm optimization (PSO) and differential evolution (DE), with the proposed DEPSO under three different time horizons (1-h, 2-h, and 4-h). Results of the 1-h time horizon shows that the root mean square error (RMSE), mean relative error (MRE), mean absolute error (MAE), mean bias error (MBE), weekly mean error (WME), and variance of the prediction errors (VAR) of the DEPSO based forecasting is 4.4%, 3.1%, 0.03, −1.63, 0.16, and 0.01, respectively. Results demonstrate that the proposed DEPSO approach is more efficient and accurate compared with the PSO and DE

Zebrafish hoxd4a Acts Upstream of meis1.1 to Direct Vasculogenesis, Angiogenesis and Hematopoiesis

10.1371/journal.pone.0058857PLoS ONE83

Socially learned attitude change is not reduced in medicated patients with schizophrenia

Schizophrenia is often associated with distinctive or odd social behaviours. Previous work suggests this could be due to a general reduction in conformity; however, this work only assessed the tendency to publicly agree with others, which may involve a number of different mechanisms. In this study, we specifically investigated whether patients display a reduced tendency to adopt other people’s opinions (socially learned attitude change). We administered a computerized conformity task, assumed to rely on reinforcement learning circuits, to 32 patients with schizophrenia or schizo-affective disorder and 39 matched controls. Each participant rated 153 faces for trustworthiness. After each rating, they were immediately shown the opinion of a group. After approximately 1 hour, participants were unexpectedly asked to rate all the faces again. We compared the degree of attitude change towards group opinion in patients and controls. Patients presented equal or more social influence on attitudes than controls. This effect may have been medication induced, as increased conformity was seen with higher antipsychotic dose. The results suggest that there is not a general decline in conformity in medicated patients with schizophrenia and that previous findings of reduced conformity are likely related to mechanisms other than reinforcement based social influence on attitudes

αv integrins: key regulators of tissue fibrosis

Chronic tissue injury with fibrosis results in the disruption of tissue architecture, organ dysfunction and eventual organ failure. Therefore, the development of effective anti-fibrotic therapies is urgently required. During fibrogenesis, complex interplay occurs between cellular and extracellular matrix components of the wound healing response. Integrins, a family of transmembrane cell adhesion molecules, play a key role in mediating intercellular and cell-matrix interactions. Thus, integrins provide a major node of communication between the extracellular matrix, inflammatory cells, fibroblasts and parenchymal cells and, as such, are intimately involved in the initiation, maintenance and resolution of tissue fibrosis. Modulation of members of the αv integrin family has exhibited profound effects on fibrosis in multiple organs and disease states. In this review, we discuss the current knowledge of the mechanisms of αv-integrin-mediated regulation of fibrogenesis and show that the therapeutic targeting of specific αv integrins represents a promising avenue to treat patients with a broad range of fibrotic diseases

Murine Cytomegalovirus Infection of Neural Stem Cells Alters Neurogenesis in the Developing Brain

Congenital cytomegalovirus (CMV) brain infection causes serious neuro-developmental sequelae including: mental retardation, cerebral palsy, and sensorineural hearing loss. But, the mechanisms of injury and pathogenesis to the fetal brain are not completely understood. The present study addresses potential pathogenic mechanisms by which this virus injures the CNS using a neonatal mouse model that mirrors congenital brain infection. This investigation focused on, analysis of cell types infected with mouse cytomegalovirus (MCMV) and the pattern of injury to the developing brain.We used our MCMV infection model and a multi-color flow cytometry approach to quantify the effect of viral infection on the developing brain, identifying specific target cells and the consequent effect on neurogenesis. In this study, we show that neural stem cells (NSCs) and neuronal precursor cells are the principal target cells for MCMV in the developing brain. In addition, viral infection was demonstrated to cause a loss of NSCs expressing CD133 and nestin. We also showed that infection of neonates leads to subsequent abnormal brain development as indicated by loss of CD24(hi) cells that incorporated BrdU. This neonatal brain infection was also associated with altered expression of Oct4, a multipotency marker; as well as down regulation of the neurotrophins BDNF and NT3, which are essential to regulate the birth and differentiation of neurons during normal brain development. Finally, we report decreased expression of doublecortin, a marker to identify young neurons, following viral brain infection.MCMV brain infection of newborn mice causes significant loss of NSCs, decreased proliferation of neuronal precursor cells, and marked loss of young neurons

Degradation of Internalized αvβ5 Integrin Is Controlled by uPAR Bound uPA: Effect on β1 Integrin Activity and α-SMA Stress Fiber Assembly

Myofibroblasts (Mfs) that persist in a healing wound promote extracellular matrix (ECM) accumulation and excessive tissue contraction. Increased levels of integrin αvβ5 promote the Mf phenotype and other fibrotic markers. Previously we reported that maintaining uPA (urokinase plasminogen activator) bound to its cell-surface receptor, uPAR prevented TGFβ-induced Mf differentiation. We now demonstrate that uPA/uPAR controls integrin β5 protein levels and in turn, the Mf phenotype. When cell-surface uPA was increased, integrin β5 levels were reduced (61%). In contrast, when uPA/uPAR was silenced, integrin β5 total and cell-surface levels were increased (2–4 fold). Integrin β5 accumulation resulted from a significant decrease in β5 ubiquitination leading to a decrease in the degradation rate of internalized β5. uPA-silencing also induced α-SMA stress fiber organization in cells that were seeded on collagen, increased cell area (1.7 fold), and increased integrin β1 binding to the collagen matrix, with reduced activation of β1. Elevated cell-surface integrin β5 was necessary for these changes after uPA-silencing since blocking αvβ5 function reversed these effects. Our data support a novel mechanism by which downregulation of uPA/uPAR results in increased integrin αvβ5 cell-surface protein levels that regulate the activity of β1 integrins, promoting characteristics of the persistent Mf

Efficacy of a Non-Hypercalcemic Vitamin-D2 Derived Anti-Cancer Agent (MT19c) and Inhibition of Fatty Acid Synthesis in an Ovarian Cancer Xenograft Model

BACKGROUND:Numerous vitamin-D analogs exhibited poor response rates, high systemic toxicities and hypercalcemia in human trials to treat cancer. We identified the first non-hypercalcemic anti-cancer vitamin D analog MT19c by altering the A-ring of ergocalciferol. This study describes the therapeutic efficacy and mechanism of action of MT19c in both in vitro and in vivo models. METHODOLOGY/PRINCIPAL FINDING:Antitumor efficacy of MT19c was evaluated in ovarian cancer cell (SKOV-3) xenografts in nude mice and a syngenic rat ovarian cancer model. Serum calcium levels of MT19c or calcitriol treated animals were measured. In-silico molecular docking simulation and a cell based VDR reporter assay revealed MT19c-VDR interaction. Genomewide mRNA analysis of MT19c treated tumors identified drug targets which were verified by immunoblotting and microscopy. Quantification of cellular malonyl CoA was carried out by HPLC-MS. A binding study with PPAR-Y receptor was performed. MT19c reduced ovarian cancer growth in xenograft and syngeneic animal models without causing hypercalcemia or acute toxicity. MT19c is a weak vitamin-D receptor (VDR) antagonist that disrupted the interaction between VDR and coactivator SRC2-3. Genome-wide mRNA analysis and western blot and microscopy of MT19c treated xenograft tumors showed inhibition of fatty acid synthase (FASN) activity. MT19c reduced cellular levels of malonyl CoA in SKOV-3 cells and inhibited EGFR/phosphoinositol-3kinase (PI-3K) activity independently of PPAR-gamma protein. SIGNIFICANCE:Antitumor effects of non-hypercalcemic agent MT19c provide a new approach to the design of vitamin-D based anticancer molecules and a rationale for developing MT19c as a therapeutic agent for malignant ovarian tumors by targeting oncogenic de novo lipogenesis

Elevation in Body Temperature to Fever Range Enhances and Prolongs Subsequent Responsiveness of Macrophages to Endotoxin Challenge

Macrophages are often considered the sentries in innate immunity, sounding early immunological alarms, a function which speeds the response to infection. Compared to the large volume of studies on regulation of macrophage function by pathogens or cytokines, relatively little attention has been devoted to the role of physical parameters such as temperature. Given that temperature is elevated during fever, a long-recognized cardinal feature of inflammation, it is possible that macrophage function is responsive to thermal signals. To explore this idea, we used LPS to model an aseptic endotoxin-induced inflammatory response in BALB/c mice and found that raising mouse body temperature by mild external heat treatment significantly enhances subsequent LPS-induced release of TNF-α into the peritoneal fluid. It also reprograms macrophages, resulting in sustained subsequent responsiveness to LPS, i.e., this treatment reduces “endotoxin tolerance” in vitro and in vivo. At the molecular level, elevating body temperature of mice results in a increase in LPS-induced downstream signaling including enhanced phosphorylation of IKK and IκB, NF-κB nuclear translocation and binding to the TNF-α promoter in macrophages upon secondary stimulation. Mild heat treatment also induces expression of HSP70 and use of HSP70 inhibitors (KNK437 or Pifithrin-µ) largely abrogates the ability of the thermal treatment to enhance TNF-α, suggesting that the induction of HSP70 is important for mediation of thermal effects on macrophage function. Collectively, these results support the idea that there has been integration between the evolution of body temperature regulation and macrophage function that could help to explain the known survival benefits of fever in organisms following infection