Industry experience of developing day-ahead photovoltaic plant forecasting system based on machine learning

This article highlights the industry experience of the development and practical implementation of a short-term photovoltaic forecasting system based on machine learning methods for a real industry-scale photovoltaic power plant implemented in a Russian power system using remote data acquisition. One of the goals of the study is to improve photovoltaic power plants generation forecasting accuracy based on open-source meteorological data, which is provided in regular weather forecasts. In order to improve the robustness of the system in terms of the forecasting accuracy, we apply newly derived feature introduction, a factor obtained as a result of feature engineering procedure, characterizing the relationship between photovoltaic power plant energy production and solar irradiation on a horizontal surface, thus taking into account the impacts of atmospheric and electrical nature. The article scrutinizes the application of different machine learning algorithms, including Random Forest regressor, Gradient Boosting Regressor, Linear Regression and Decision Trees regression, to the remotely obtained data. As a result of the application of the aforementioned approaches together with hyperparameters, tuning and pipelining of the algorithms, the optimal structure, parameters and the application sphere of different regressors were identified for various testing samples. The mathematical model developed within the framework of the study gave us the opportunity to provide robust photovoltaic energy forecasting results with mean accuracy over 92% for mostly-sunny sample days and over 83% for mostly cloudy days with different types of precipitation. © 2020 by the authors. Licensee MDPI, Basel, Switzerland

ESR observations of paramagnetic centers in intrinsic hydrogenated microcrystalline silicon

Paramagnetic centers in hydrogenated microcrystalline silicon, µc-Si:H have been studied using dark and light-induced electron-spin resonance (ESR). In dark ESR measurements only one center is observed. The g values obtained empirically from powder-pattern line-shape simulations are g=2.0096 and g'=2.0031. We suggest that this center may be due to defects in the crystalline phase. During illumination at low temperatures, an additional ESR signal appears. This signal is best described by two powder patterns indicating the presence of two centers. One center is asymmetric (gi=1.999, g'=1.996), while the other is characterized by large, unresolved broadening such that unique g values cannot be obtained. The average g value for this center is 1.998. The light-induced signal, which we interpret as coming from carriers trapped in the band tails at the crystalline grain boundaries, remains for at least several minutes after the light is turned off. Although the time scales of the decay curves are very different for two samples prepared by different techniques, both decays can be fitted using the assumption of recombination due to distant pairs of electrons and holes trapped in localized band-tail states

ICTs and the Challenge of Health System Transition in Low and Middle-Income Countries

The aim of this paper is to contribute to debates about how governments and other stakeholders can influence the application of ICTs to increase access to safe, effective and affordable treatment of common illnesses, especially by the poor. First, it argues that the health sector is best conceptualized as a ‘knowledge economy’. This supports a broadened view of health service provision that includes formal and informal arrangements for the provision of medical advice and drugs. This is particularly important in countries with a pluralistic health system, with relatively underdeveloped institutional arrangements. It then argues that reframing the health sector as a knowledge economy allows us to circumvent the blind spots associated with donor-driven ICT-interventions and consider more broadly the forces that are driving e-health innovations. It draws on small case studies in Bangladesh and China to illustrate new types of organization and new kinds of relationship between organizations that are emerging. It argues that several factors have impeded the rapid diffusion of ICT innovations at scale including: the limited capacity of innovations to meet health service needs, the time it takes to build new kinds of partnership between public and private actors and participants in the health and communications sectors and the lack of a supportive regulatory environment. It emphasises the need to understand the political economy of the digital health knowledge economy and the new regulatory challenges likely to emerge. It concludes that governments will need to play a more active role to facilitate the diffusion of beneficial ICT innovations at scale and ensure that the overall pattern of health system development meets the needs of the population, including the poor

A Neurophysiologically Plausible Population Code Model for Feature Integration Explains Visual Crowding

An object in the peripheral visual field is more difficult to recognize when surrounded by other objects. This phenomenon is called “crowding”. Crowding places a fundamental constraint on human vision that limits performance on numerous tasks. It has been suggested that crowding results from spatial feature integration necessary for object recognition. However, in the absence of convincing models, this theory has remained controversial. Here, we present a quantitative and physiologically plausible model for spatial integration of orientation signals, based on the principles of population coding. Using simulations, we demonstrate that this model coherently accounts for fundamental properties of crowding, including critical spacing, “compulsory averaging”, and a foveal-peripheral anisotropy. Moreover, we show that the model predicts increased responses to correlated visual stimuli. Altogether, these results suggest that crowding has little immediate bearing on object recognition but is a by-product of a general, elementary integration mechanism in early vision aimed at improving signal quality

Expression and role of PAICS, a de novo purine biosynthetic gene in prostate cancer

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/143605/1/pros23533_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/143605/2/pros23533.pd

Development of a RAD-Seq Based DNA Polymorphism Identification Software, AgroMarker Finder, and Its Application in Rice Marker-Assisted Breeding

Abstract Rapid and accurate genome-wide marker detection is essential to the marker-assisted breeding and functional genomics studies. In this work, we developed an integrated software, AgroMarker Finder (AMF: http://erp.novelbio.com/AMF), for providing graphical user interface (GUI) to facilitate the recently developed restriction-site associated DNA (RAD) sequencing data analysis in rice. By application of AMF, a total of 90,743 high-quality markers (82,878 SNPs and 7,865 InDels) were detected between rice varieties JP69 and Jiaoyuan5A. The density of the identified markers is 0.2 per Kb for SNP markers, and 0.02 per Kb for InDel markers. Sequencing validation revealed that the accuracy of genome-wide marker detection by AMF is 93%. In addition, a validated subset of 82 SNPs and 31 InDels were found to be closely linked to 117 important agronomic trait genes, providing a basis for subsequent marker-assisted selection (MAS) and variety identification. Furthermore, we selected 12 markers from 31 validated InDel markers to identify seed authenticity of variety Jiaoyuanyou69, and we also identified 10 markers closely linked to the fragrant gene BADH2 to minimize linkage drag for Wuxiang075 (BADH2 donor)/Jiachang1 recombinants selection. Therefore, this software provides an efficient approach for marker identification from RAD-seq data, and it would be a valuable tool for plant MAS and variety protection

Functional Relationship between Protein Disulfide Isomerase Family Members during the Oxidative Folding of Human Secretory Proteins

We systematically depleted PDI family members and show that whereas ERp72 and P5 contributed minimally to oxidative protein folding, PDI and ERp57 were the predominant catalysts. Depletion of PDI or ERp57 alone modestly delayed folding, but depletion of both led to generalized protein misfolding and degradation

Visual Performance Fields: Frames of Reference

Performance in most visual discrimination tasks is better along the horizontal than the vertical meridian (Horizontal-Vertical Anisotropy, HVA), and along the lower than the upper vertical meridian (Vertical Meridian Asymmetry, VMA), with intermediate performance at intercardinal locations. As these inhomogeneities are prevalent throughout visual tasks, it is important to understand the perceptual consequences of dissociating spatial reference frames. In all studies of performance fields so far, allocentric environmental references and egocentric observer reference frames were aligned. Here we quantified the effects of manipulating head-centric and retinotopic coordinates on the shape of visual performance fields. When observers viewed briefly presented radial arrays of Gabors and discriminated the tilt of a target relative to homogeneously oriented distractors, performance fields shifted with head tilt (Experiment 1), and fixation (Experiment 2). These results show that performance fields shift in-line with egocentric referents, corresponding to the retinal location of the stimulus

Targeting the ERG oncogene with splice-switching oligonucleotides as a novel therapeutic strategy in prostate cancer

This is the author accepted manuscript. The final version is available from Springer Nature via the DOI in this recordBackground The ERG oncogene, a member of the ETS family of transcription factor encoding genes, is a genetic driver of prostate cancer. It is activated through a fusion with the androgen-responsive TMPRSS2 promoter in 50% of cases. There is therefore significant interest in developing novel therapeutic agents that target ERG. We have taken an antisense approach and designed morpholino-based oligonucleotides that target ERG by inducing skipping of its constitutive exon 4. Methods We designed antisense morpholino oligonucleotides (splice-switching oligonucleotides, SSOs) that target both the 5′ and 3′ splice sites of ERG’s exon 4. We tested their efficacy in terms of inducing exon 4 skipping in two ERG-positive cell lines, VCaP prostate cancer cells and MG63 osteosarcoma cells. We measured their effect on cell proliferation, migration and apoptosis. We also tested their effect on xenograft tumour growth in mice and on ERG protein expression in a human prostate cancer radical prostatectomy sample ex vivo. Results In VCaP cells, both SSOs were effective at inducing exon 4 skipping, which resulted in a reduction of overall ERG protein levels up to 96 h following a single transfection. SSO-induced ERG reduction decreased cell proliferation, cell migration and significantly increased apoptosis. We observed a concomitant reduction in protein levels for cyclin D1, c-Myc and the Wnt signalling pathway member β-catenin as well as a marker of activated Wnt signalling, p-LRP6. We tested the 3′ splice site SSO in MG63 xenografts in mice and observed a reduction in tumour growth. We also demonstrated that the 3′ splice site SSO caused a reduction in ERG expression in a patient-derived prostate tumour tissue cultured ex vivo. Conclusions We have successfully designed and tested morpholino-based SSOs that cause a marked reduction in ERG expression, resulting in decreased cell proliferation, a reduced migratory phenotype and increased apoptosis. Our initial tests on mouse xenografts and a human prostate cancer radical prostatectomy specimen indicate that SSOs can be effective for oncogene targeting in vivo. As such, this study encourages further in vivo therapeutic studies using SSOs targeting the ERG oncogene.Prostate Cancer U