Background: Gaps exist in early identification and prevention of cardiorenal complications (CRCs) in type 2 diabetes (T2D). Aim: To investigate global variations in burden and treatment patterns of CRCs, including albuminuria, high cardiovascular (CV) risk, and early echocardiographic findings, among individuals with T2D in primary care settings. This is an ongoing patient-centric program that collects data on early diagnostic tests during disease journey to support critical decision-making. Method: 'Take CaRe of Me', a subset of DISCOVER CaReMe Registry, is a multicountry, prospective, cloud-based data repository on routine care for adults (>18 years) with T2D, without cardiorenal disease history at screening (per medical records). We present preliminary descriptive analysis (until May-2021) from 6 countries. Results: Among 4686 patients (mean age: 55.7±11.3 years; 46.2% men), average T2D duration was 8.4±7.2 years (N=4534) and mean glycated hemoglobin (HbA1c) was 8.3±3.0% (N=4409). About 32.3% had total cholesterol >180mg/dL (N= 4362); 51.4% had low-density lipoprotein cholesterol >70mg/dL (N=3985). Mean estimated glomerular filtration rate was 94.6±23.2mL/min/1.73m2 (N=479) and mean urine albumin:creatinine ratio (UACR) was 62.9±181.9mg/g (N=3869). Overall, 66.3% had HbA1c >7%; as per UACR and European Society of Cardiology (ESC) 2019, 32.7% had high renal risk (UACR >30mg/g), and 37.0% had high/very high CV risk (Table 1). On echocardiography (N=417), 8.9% (n=37) had diastolic dysfunction, 20.6% (n=86) had left ventricular hypertrophy, 16.5% (n=69) had left atrial enlargement, and 8.6% (n=36) had valvular diseases. Among high/very high CV risk (N=1861) and high renal risk (N=1390), biguanides were most commonly prescribed antidiabetics in all lines of therapy (n=502, 26.9%; n=346, 24.8%), followed by biguanides+sulfonylureas (n=154, 8.3%; n=126, 9.1%), respectively. As first-line therapy, 42.4% (693/1635) with high/very high CV risk, 44.6% (531/1191) with high renal risk, and 44.2% (518/1172) with both risks received antidiabetics; around 2% of them received dipeptidyl peptidase-4 inhibitors (DPP-4i), sodium-glucose cotransporter-2 inhibitors (SGLT2i) or DPP4i+SGLT2i. Overall, less than 2% of patients with high/very high CV or renal or both risks received glucagon-like peptide-1 agonists. Other therapies (N=4229) included antilipids (98.4%), antihypertensives (23.2%), and antiplatelets (2.4%).Table 1Glycemic Control and CRCs in T2DOverallArgentinaEgyptIndiaMalaysiaMexicoPhilippinesn(%)HbA1c(%)N=4409N=389N=193N=1650N=30N=1573N=574<71488(33.7)170(43.7)65(33.7)557(33.8)11(36.7)470(29.9)215(37.5)7-102012(45.6)169(43.4)94(48.7)788(47.8)14(46.7)707(44.9)240(41.8)>10909(20.6)50(12.9)34(17.6)305(18.5)5(16.7)396(25.2)119(20.7)UACR(mg/g)*N=3869N=339N=157N=1509N=29N=1561N=274A1(<30)2605(67.3)244(72)100(63.7)927(61.4)17(58.6)1171(75%)146(53.3)A2(30-300)1104(28.5)89(26.3)52(33.1)508(33.7)11(37.9)332(21.3)112(40.9)A3(>300)160(4.1)6(1.8)5(3.2)74(4.9)1(3.4)58(3.7)16(5.8)CV risk*N=4686N=399N=196N=1671N=30N=1618N=772Low2592(55.3)190(47.6)87(44.4)825(49.4)15(50)972(60.1)503(65.2)Moderate362(7.7)11(2.8)14(7.1)196(11.7)2(6.7)87(5.4)52(6.7)High/Very High1732(37)198(49.6)95(48.5)650(38.9)13(43.3)559(34.5)217(28.1)*Risk defined per UACR and ESC 2019. Open table in a new tab *Risk defined per UACR and ESC 2019. Discussion: Among patients with T2D without cardiorenal disease, 32.7% and 37.0% had early signs of high renal risk and high/very high CV risk. Thus, channeling attention to early markers like UACR and echocardiography through enhanced screening enables timely diagnosis and adequate treatment with novel antihyperglycemics that also reduce cardiorenal risk at an early stage.

Background: With an age-adjusted prevalence of 10.1% to 16.3% per 1000 population, the burden of type 2 diabetes (T2D) in Gulf Cooperation Council (GCC) region exceeds the global rate (8.3%). Due to delays in diagnosis, referral and access to medications, only 11–41% patients achieve glycaemic control in the region. Utilisation of artificial intelligence (AI) can facilitate clinical decisions based on algorithm-identified gaps. Aim: We present the framework of HealthGate, an AI-based integrated healthcare ecosystem, designed to improve outcomes in individuals with T2D alongside enhancing local virtual healthcare capabilities in the GCC region. Method: The HealthGate platform works as a gateway between healthcare professionals (HCPs) and patients using unique identification numbers and identifier codes, to facilitate patient data access through the Intellin®, Gendius' application. Patients can access HealthGate application using HCP identifier code and periodically enter their data manually or through connected glucose monitoring, medication and compliance devices and Apps; these can be tracked by HCPs via two-way data synchronisation after obtaining patient consent. Results: HealthGate algorithms can analyse patients' data using real-time, supervised machine learning to provide individually tailored, clinically validated educational content and guidance on a regular basis on patients' interface—driving patient engagement and self‑monitoring. Additionally, HealthGate will encourage telemedicine through online consultations, e-prescriptions and drug delivery services, and home investigations partnering with other collaborators. The platform can integrate over 150 connected monitoring devices and Apps and share metabolic disease information with HCPs via a secure dashboard. The key indicators of HealthGate will be regularly assessed (Table 1). Table 1. Key parameters and outcomes of HealthGateTabled 1ParametersOutcomesKey data elementsVital signs, clinical characteristics, lifestyle habits, investigations (blood sugar, HbA1c, serum chemistry), medications (schedule/dose)Artificial intelligence-based outputs•Daily reminders on patient interface•Trend graphs on health care providers' (HCP) interface•Alerts to HCPs and patients about alarming values•Algorithm-based dashboard reports on non-users, at-risk patients, application use rate at regular intervals•Number of app downloads•Daily active users•App rating and retention rateImpactIndividualEnhanced drug complianceGlycaemic controlControlled co‑morbiditiesImproved lifestyle, quality of lifeReduced hypoglycaemia, retinopathy, cardio-renal eventsHealth system•Reduced microvascular and macrovascular complications•Risk stratification for early intervention•Optimal utilisation of healthcare resources•Enhanced clinical decision making by knowledge sharing•Reduced hospitalisations and premature mortality Open table in a new tab Discussion: This AI-based approach will streamline the management of people with T2D across tiers of healthcare through real-time data sharing with HCPs. Patient engagement and empowerment through HealthGate app will result in improved glycaemic control, medication adherence and early identification of vascular complications in the GCC region. The knowledge sharing across the region will foster multi‑disciplinary clinical decisions with high precision, resulting in early referrals and better access to care by sharing burden of existing healthcare infrastructure in the region. HealthGate will also open an opportunity to generate interoperable real-world data on diagnostics, goal achievements and burden of vascular complications in the region.

This work shows the convenience or not of the inclusion of wind energy systems operating in junction with photovoltaic systems, oriented to power small stand alone telecommunication systems. A PV generator, a wind generator and a battery system compose the basic hybrid system analyzed. Simple models are used to predict the power generation for the wind and PV generators. An hourly measured year of global horizontal irradiance and wind speed (at 10m height) in 6 different locations in Spain representative of different irradiance and wind speed correlations were used. Simulations have been performed to obtain the size ratios: Battery - PV array generator - Wind turbine, that lead to a predefined loss of load hours (LOLH). For a defined LOLH there are an infinite number of potential ratios battery-PV-wind. Only the economic criteria (including the battery lifetime dependence with the SOC evolution) will lead to obtain the optimum system size. For some locations, with a considerable wind resource (i.e. good solar-wind correlation), the use of a small wind generator can reduce not only the number of a PV system faults, but also the PV array peak power to be installed. Nevertheless economic aspects, as the ratio price/W for wind, photovoltaic or battery, can modify these results. System costs can be analyzed in function of the different parameters: location (irradiance and wind speed correlation), load profile, PV/wind/battery costs ratios. This work shows that the use of small wind turbines in photovoltaic stand-alone installations for telecommunications can reduce the final system cost in function, among others, of the correlation wind speed/irradiance for a given location and the different technology prices.

Background:Limited information is available regarding medication use in COPD patients from Latin America. This study evaluated the type of medication used and the adherence to different inhaled treatments in stable COPD patients from the Latin American region.Methods:This was an observational, cross-sectional, multinational, and multicenter study in COPD patients attended by specialist doctors from seven Latin American countries. Adherence to inhaled therapy was assessed using the Test of Adherence to Inhalers (TAI) questionnaire. The type of medication was assessed as: short-acting β-agonist (SABA) or short-acting muscarinic antagonist (SAMA) only, long-acting muscarinic antagonist (LAMA), long-acting β-agonist (LABA), LABA/LAMA, inhaled corticosteroid (ICS), ICS/LABA, ICS/LAMA/LABA, or other.Results:In total, 795 patients were included (59.6% male), with a mean age of 69.5±8.7 years and post-bronchodilator FEV1 of 50.0%±18.6%. The ICS/LAMA/LABA (32.9%) and ICS/LABA (27.7%) combinations were the most common medications used, followed by LABA/LAMA (11.3%), SABA or SAMA (7.9%), LABA (6.4%), LAMA (5.8%), and ICS (4.3%). The types of medication most commonly used in each Global Initiative for Chronic Obstructive Lung Disease (GOLD) 2013 category were ICS/LABA (A: 32.7%; B: 19.8%; C: 25.7%; D: 28.2%) and ICS/LAMA/LABA (A: 17.3%; B: 30.2%; C: 33%; D: 41.1%). The use of long-acting bronchodilators showed the highest adherence (good or high adherence >50%) according to the TAI questionnaire.Conclusion:COPD management in specialist practice in Latin America does not follow the current guideline recommendations and there is an overuse of ICSs in patients with COPD from this region. Treatment regimens including the use of long-acting bronchodilators are associated with the highest adherence.

The atmospheric Linke Turbidity index is determined from solar radiation measurements of global irradiance for different weather stations of Mexico. The Linke turbidity index is obtained from ESRA clear sky model by adjusting the index value that gives the smallest difference between the model and the measured irradiances. Clear days were identified in the solar database of selected stations and the monthly mean value for the turbidity is compared with Linke values worldwide provided from Meteotest through their internet services. Significant differences are found in some cases; but in most cases, the measured variability shows agreement with the Meteotest values.

Reference solar irradiance spectra are needed to specify key parameters of solar technologies such as photovoltaic cell efficiency, in a comparable way. The IEC 60904-3 and ASTM G173 standards present such spectra for Direct Normal Irradiance (DNI) and Global Tilted Irradiance (GTI) on a 37 degrees tilted sun-facing surface for one set of clear-sky conditions with an air mass of 1.5 and low aerosol content. The IEC/G173 standard spectra are the widely accepted references for these purposes. Hence, the authors support the future replacement of the outdated ISO 9845 spectra with the IEC spectra within the ongoing update of this ISO standard. The use of a single reference spectrum per component of irradiance is important for clarity when comparing and rating solar devices such as PV cells. However, at some locations the average spectra can differ strongly from those defined in the IEC/G173 standards due to widely different atmospheric conditions and collector tilt angles. Therefore, additional subordinate standard spectra for other atmospheric conditions and tilt angles are of interest for a rough comparison of product performance under representative field conditions, in addition to using the main standard spectrum for product certification under standard test conditions. This simplifies the product selection for solar power systems when a fully-detailed performance analysis is not feasible (e.g. small installations). Also, the effort for a detailed yield analyses can be reduced by decreasing the number of initial product options. After appropriate testing, this contribution suggests a number of additional spectra related to eight sets of atmospheric conditions and tilt angles that are currently considered within ASTM and ISO working groups. The additional spectra, called subordinate standard spectra, are motivated by significant spectral mismatches compared to the IEC/G173 spectra (up to 6.5%, for PV at 37 tilt and 10-15% for CPV). These mismatches correspond to potential accuracy improvements for a quick estimation of the average efficiency by applying the appropriate subordinate standard spectrum instead of the IEC/G173 spectra. The applicability of these spectra for PV performance analyses is confirmed at five test sites, for which subordinate spectra could be intuitively selected based on the average atmospheric aerosol optical depth (AOD) and precipitable water vapor at those locations. The development of subordinate standard spectra for DNI and concentrating solar power (CSP) and concentrating PV (CPV) is also considered. However, it is found that many more sets of atmospheric conditions would be required to allow the intuitive selection of DNI spectra for the five test sites, due in particular to the stronger effect of AOD on DNI compared to GTL The matrix of subordinate GTL spectra described in this paper are recommended to appear as an option in the annex of future standards, in addition to the obligatory use of the main spectrum from the ASTM G173 and IEC 60904 standards.

Senegal has a great solar potential, so it could be used to shift from a diesel-based power generation to cheaper renewable energy resources. To exploit this inexhaustible natural resource, the global horizontal irradiation remains one of the key parameters for any solar energy project at a given location. This work establishes a multiple linear regression approach to estimate the solar radiation in the Senegalese territories using the information of the global network of weather geostationary satellites (Meteosat and GOES), satellites database and the ground measurement data available in the website of the World Radiation Data Center (WRDC) as inputs to the model. Jointly a set of multivariate regression models, a statistical analysis between Meteonorm data and outputs of different linear combinations are presented in this work, which also gives the opportunity to appreciate the precision and consistency of each solar radiation model on different locations in the study area.

•We present an in-depth review of pyrheliometer calibration standard protocols.•Harmonization of the ISO and ASTM standards is proposed.•The proposed procedure clarifies and simplifies data processing.•Impact of some experimental conditions on 19 calibration instruments is analyzed.•Calibration results of most pyrheliometers depend on solar elevation and wind speed.

Downward-facing shadow cameras might play a major role in future energy meteorology. Shadow cameras directly image shadows on the ground from an elevated position. They are used to validate other systems (e.g. all-sky imager based nowcasting systems, cloud speed sensors or satellite forecasts) and can potentially provide short term forecasts for solar power plants. Such forecasts are needed for electricity grids with high penetrations of renewable energy and can help to optimize plant operations. In this publication, two key applications of shadow cameras are briefly presented.

The present paper presents a very simple energy yield model fitted using the annual DNI and the latitude as main inputs, considering a solar tower CSP plant, with 100 MW of net energy output and 6 hours of thermal storage. Furthermore, a mask of suitable areas for CSP power tower installations in Chile is also shown. The mapping of solar radiation components has been calculated from multi-regressive models based on ground based measurements, existing maps of solar resources and atmospheric parameters. An analysis of the available data bases in Chile is also done in order to obtain useful information for the development of the work.

(1) Institute of Solar Research, German Aerospace Center (DLR), Almería, Spain (Pascal.Kuhn@dlr.de, marco.wirtz@eonerc.rwth-aachen.de, Stefan.Wilbert@dlr.de, Natalie.Hanrieder@dlr.de, Bijan.Nouri@dlr.de), (2) Earth Observation Center, German Aerospace Center (DLR), Weßling Oberpfaffenhofen, Germany (niels.killius@dlr.de), (3) Departamento de Ingeniería Eléctrica y Térmica, Universidad de Huelva, Huelva, Spain (jlbosch@gmail.com), (4) Dept. of Mechanical and Aerospace Engineering, UCSD Center for Energy Research, University of California, USA (g3wang@eng.ucsd.edu, jkleissl@eng.ucsd.edu), (5) CIEMAT, Energy Department Renewable Energy Division, Madrid, Spain (Lourdes.ramirez@aei.gob.es, lf.zarzalejo@ciemat.es), (6) Institute of Networked Energy Systems, German Aerospace Center (DLR), Oldenburg, Germany (Marion.Schroedter-Homscheidt@dlr.de, Detlev.Heinemann@dlr.de), (7) Laboratory of Atmospheric Physics, Department of Physics, University of Patras, Patras, Greece (akaza@upatras.gr), (8) MINES ParisTech, PSL Research University, Sophia Antipolis CEDEX, France (philippe.blanc@mines-paristech.fr), (9) Institute of Solar Research, German Aerospace Center (DLR), Cologne, Germany (Robert.Pitz-Paal@dlr.de)

Understanding the long-term temporal variability of solar resource is fundamental in any assessment of solar energy potential. The variability of the solar resource (as shown by historical solar data) plays a significant role in the statistical description of the future performance of a solar power plant, thus influencing its financing conditions. In particular, solar-power financing is mainly based on a statistical quantification of the solar resource. In this work, a methodology for generating meteorological years representative of a given annual probability of exceedance of solar irradiation is presented, which can be used as input in risk assessment for securing competitive financing for Concentrating Solar Thermal Power (CSTP) projects. This methodology, which has been named EVA, is based on the variability and seasonality of monthly Direct Normal solar Irradiation (DNI) values and uses as boundary condition the annual DNI value representative for a given probability of exceedance. The results are validated against a 34-year series of net energy yield calculated at hourly intervals from measured solar irradiance data and meteorological, and they are also supplemented with the analysis of uncertainty associated to the probabilities of exceedance estimates. Relations between DNI and CSTP energy yields at different time scales are also analyzed and discussed.

Cloud height information is crucial for various applications. This includes solar nowcasting systems. Multiple methods to obtain the altitudes of clouds are available. In this paper, cloud base heights derived from the European Centre for Medium-Range Weather Forecasts (ECMWF) and three low-cost and low-maintenance ground based systems are presented and compared against ceilometer measurements on 59 days with variable cloud conditions in southern Spain. All three ground based systems derive cloud speeds in absolute units of [m/s] from which cloud heights are determined using angular cloud speeds derived from an all-sky imager. The cloud speed in [m/s] is obtained from (1) a cloud shadow speed sensor (CSS), (2) a shadow camera (SC) or (3) derived from two all-sky imagers. Compared to 10-min median ceilometer measurements for cloud heights below 5000 m, the CSS-based system shows root-mean squared deviations (RMSD) of 996 m (45%), mean absolute deviations (MAD) of 626 m (29%) and a bias of-142 m (- 6%). The SC-based system has an RMSD of 1193 m (54%), a MAD of 593 m (27%) and a bias of 238 m (11%). The two all-sky imagers based system show deviations of RMSD 826 m (38%), MAD of 432 m (20%) and a bias of 202 m (9%). The ECMWF derived cloud heights deviate from the ceilometer measurements with an RMSD 1206 m (55%), MAD of 814 m (37%) and a bias of- 533 m (- 24%). Due to the multi-layer nature of clouds and systematic differences between the considered approaches, benchmarking cloud heights is an extremely difficult task. The limitations of such comparisons are discussed. This study aims at determining the best approach to derive cloud heights for camera based solar nowcasting systems. The approach based on two all-sky imagers is found to be the most promising, having the overall best accuracy and the most obtained measurements.

With ramp rate regulations for photovoltaic plants being discussed in many countries, the speed of clouds has gained significant importance lately. Besides, measuring cloud velocities and directions is of interest for validations of numerical weather predictions and solar nowcasting systems. Recently, the Cloud Shadow Speed Sensor (CSS) was developed and validated in San Diego for low cumulus clouds. In this publication, the CSS is studied under different weather and cloud conditions in the desert of Tabemas in southem Spain. Furthermore, a novel shadow camera based low-cost, low-maintenance approach to determine cloud shadow motion vectors is presented and used as a reference to benchmark the CSS. In comparison, the absolute velocities derived from the CSS and the shadow camera on 59 days for +/- 5 min temporal medians show deviations of RMSD 2.1 m/s (28.0%), MAD 1.2 m/s (15.7%) and a bias of -0.2 m/s (2.8%). Deviations of the cloud shadow direction are RMSD 47.9 degrees (26.6%), MAD 25.3 degrees (14.0%) and bias 3.7 degrees (2.0%). An adaption of the CSS software yields 91% more measurements on 59 days in comparison to the previously used algorithms at the expense of reduced accuracies, both for the measured velocities and for the measured directions. The CSS and the novel shadow camera based reference system enable long-time, low-maintenance ground measurements of cloud shadow speeds, which were previously not available. The distinct advantages and limitations of the two systems are discussed. In addition to the comparisons between the shadow camera system and the CSS on 59 days, the detection rates of the CSS are classified and measured on 223 days by analyzing CSS radiometer signals. Depending on the shading strength and shading durations, detection rates vary between 3.7% and 21.6%. Furthermore, the basic assumption as well as possible correction approaches of the linear cloud edge - curve fitting method are studied. The CSS was found to be a robust tool with great potential. However, optically thin clouds with diffuse edges pose a challenge and the detection rate leaves room for improvements. The newly developed shadow camera system provides more measurements which scatter less but needs certain geographical requirements. The shadow camera is found to be a feasible validation tool for cloud (shadow) motion vectors.

All-sky imager based systems can be used to measure a number of cloud properties. Configurations consisting of two all-sky imagers can be used to derive cloud heights for weather stations, aviation and nowcasting of solar irradiance. One key question for such systems is the optimal distance between the all-sky imagers. This problem has not been studied conclusively in the literature. To the best of our knowledge, no previous in-field study of the optimal camera distance was performed. Also, comprehensive modeling is lacking. Here, we address this question with an in-field study on 93 days using 7 camera distances between 494 m and 2562 m and one specific cloud height estimation approach. We model the findings and draw conclusions for various configurations with different algorithmic methods and camera hardware. The camera distance is found to have a major impact on the accuracy of cloud height determinations. For the used 3 megapixel cameras, cloud heights up to 12,000 m and the used algorithmic approaches, an optimal camera distance of approximately 1500 m is determined. Optimal camera distances can be reduced to less than 1000 m if higher camera resolutions (e.g. 6 megapixel) are deployed. A step-by-step guide to determine the optimal camera distance is provided.