Potential pollinators of Fragaria ananassa (Rosales: Rosaceae) in the Perico valleys of Jujuy (Argentina)

The aims of this study were to identify and estimate the potential pollinators of Fragaria ananassa Duch. “strawberry”, through the analysis of pollen carried out on their bodies. The study was carried out on a commercial farm in Las Pampitas, located in the Perico valleys, Jujuy province (Argentina). Floral visitors and other arthropods were sampled and identified, and their diversity was analyzed. The samples of insects selected to obtain the pollen carried were processed following the acetolysis technique. The potential pollinators of the strawberry crop were estimated by calculating the pollination probability index. The floral visitors corresponded to representatives of Hymenoptera, Diptera, Hemiptera, Lepidoptera, Coleoptera and even Araneae. Apis mellifera L. was the most frequent floral visitor and presented more strawberry pollen than other selected insects. The pollination probability index estimated that this species had a high probability of being a pollinator. Other pollinators such as Allograpta exotica Wiedemann, Halictidae, Meliponini and even Thripidae could complement the action of the honeybee. This is the first contribution to the knowledge of the pollination of F. ananassa in the agroecosystems of Jujuy.

Infection Probability Index: Implementation of an Automated Chronic Wound Infection Marker

The number of people suffering from chronic wounds is increasing due to demographic changes and the global epidemics of obesity and diabetes. Innovative imaging techniques within the field of chronic wound diagnostics are required to improve wound care by predicting and detecting wound infections to accelerate the application of treatments. For this reason, the infection probability index (IPI) is introduced as a novel infection marker based on thermal wound imaging. To improve usability, the IPI was implemented to automate scoring. Visual and thermal image pairs of 60 wounds were acquired to test the implemented algorithms on clinical data. The proposed process consists of (1) determining various parameters of the IPI based on medical hypotheses, (2) acquiring data, (3) extracting camera distortions using camera calibration, and (4) preprocessing and (5) automating segmentation of the wound to calculate (6) the IPI. Wound segmentation is reviewed by user input, whereas the segmented area can be refined manually. Furthermore, in addition to proof of concept, IPIs’ correlation with C-reactive protein (CRP) levels as a clinical infection marker was evaluated. Based on average CRP levels, the patients were clustered into two groups, on the basis of the separation value of an averaged CRP level of 100. We calculated the IPIs of the 60 wound images based on automated wound segmentation. Average runtime was less than a minute. In the group with lower average CRP, a correlation between IPI and CRP was evident.

Testing of Drought Exceedance Probability Index (DEPI) for Turkey using PERSIANN data for 2000-2021 period

Drought is a climatic event that threatens the environment and human life with an ambiguity of location and time. Recently, droughts can be analyzed for different periods with the help of different mathematical methods and developing technology. This study aims to perform a drought analysis in 126 designated study points of Turkey. The analyzed data includes monthly total precipitation values between March 2000 and February 2021, obtained from PERSIANN system (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks). Monthly precipitation totals of these designated points were used as input parameters in the Drought Exceedance Probability Index (DEPI) which is a new drought analysis method. The analysis was conducted separately for the whole of Turkey from January to December. Moreover, the findings were compared with the Standardized Precipitation Index (SPI), a globally accepted and commonly used drought index, to measure the drought detection performance of DEPI. SPI was calculated for periods of 6, 12 and 24 months. Pearson correlation coefficients between drought values of SPI-6, SPI-12 and SPI-24 and DEPI results were calculated. The second part of the study includes possible trend of drought determined by the Mann-Kendall trend analysis method. Both DEPI and SPI results and trend analysis results were mapped and visualized with the help of ArcGIS package program. The highest correlation is between DEPI and SPI-12 with 0.75, while the lowest correlation is between DEPI and SPI-24 with a value of 0.62. SPI monthly drought maps indicated the wettest months were January and February, while the driest months were March and July. Besides the DEPI monthly drought maps, the wettest months were October and November, while the driest months were May and June. The Mann-Kendall trend maps showed a significant increase in drought for summer.

Pengembangan Usaha Agroindustri Noni (mengkudu) dengan Pendekatan Decission Support System

Noni or pace (Morinda citrifolia) is a medicinal plant with much interest from entrepreneurs in the traditional medicine industry and researchers in various countries. This study aimed to design the development of an agro-industry business (UD. ZAM) to increase competitiveness. The design of this research was descriptive using the expert system method. The analysis technique employed the MSME DSS software version 2.0 with a legal, marketing, management, human resources, environmental, and financial analysis model to design a Decision Support System. The results obtained were that UD. ZAM already had complete business legalization, such as Company Registration Certificate (TDP) 13.07.5.47.25386, Trading Business License (SIUP) 503/0087/411/2015, Taxpayer Identification Number (NPWP) 72.691.633.1-626.000, and Permit Industrial Business (IUI) 503/3212/411/2015, and P-IRT NO2133509103570-21. Therefore, with the license certificate, UD. ZAM was legal. In the marketing of noni products so far, it is export-oriented, which has advantages so that it can be developed. In terms of production performance, it shows the required production process and aspects of human resources provided by UD. ZAM standard regional minimum wage (UMR) and employment in rural areas, in a high feasibility environment, because it was easy to obtain materials and in financial aspects such as the assumption of an interest rate of 15%, break event point (BEP) quantity 25,833.87 and ( BEP) sales 261.397.03.77, benefit coast ratio (BCR) 2.35, payback period 1.23, net present value (NPV) 18.066.137.185.78, probability index (PI) 11, 28, and internal rate of return (IRR) 56.44. Keywords: Noni Agroindustry; Decision Support System (DSS).Mengkudu (Morinda citrifolia) adalah tanaman obat yang banyak peminatnya dari kalangan pengusaha industri obat tradisional dan peneliti diberbagai negara. Penelitian ini bertujuan untuk merancang pengembangan usaha agroindustri UD. ZAM untuk meningkatkan daya saing. Rancangan penelitian ini adalah deskriptif menggunakan metode expert system. Teknik analisis menggunakan software DSS UMKM version 2.0 dengan model analisis aspek hukum, aspek pemasaran, aspek produksi, aspek manajemen dan sumber daya manusia, aspek lingkungan, dan aspek keuangan. Hasil penelitian yang diperoleh adalah UD. ZAM telah memiliki kelengkapan legalisasi usaha Tanda Daftar Perusahaan (TDP) 13.07.5.47.25386, Surat Izin Usaha Perdagangan (SIUP) 503/0087/411/2015, Nomor Pokok Wajib Pajak (NPWP) 72.691.633.1-626.000, Izin Usaha Industri (IUI) 503/3212/411/2015, dan P-IRT NO2133509103570-21. Pemasaran produk noni selama ini berorientasi ekspor yang memiliki kelebihan kepastian pasar sehingga layak untuk dikembangkan, pada aspek kinerja produksi menunjukkan tingkat kelayakan rendah, aspek sumber daya manusia sistem upah yang diberikan oleh UD. ZAM standart Upah Minimum Regional (UMR) dan memberi lapangan pekerjaan pada masyarakat pedesaan, pada aspek kinerja lingkungan tingkat kelayakan tinggi, karena selama ini mudah untuk mendapatkan bahan baku, pada aspek keuangan seperti asumsi tingkat bunga sebesar 15%, break event point (BEP) kuantitas 25.833.87 maupun (BEP) penjualan 261.397.03,77,benefit coast ratio (BCR) 2,35, payback period 1,23, net present value (NPV) 18.066.137.185,78, probability index (PI) 11,28, dan internal rate of return(IRR) 56,44 maka layak dikembangkan lebih lanjut

Prosperity or Real Estate Bubble? Exuberance Probability Index of Real Housing Prices in Chile

In this paper, we approached the concept of real estate bubble, analyzing the risk its bursting could generate for the Chilean financial market. Specifically, we analyzed the relationship between real housing prices, the economic activity index, and mortgage interest rates denominated in inflation-linked units from 1994 to 2020. The analysis was based on a second order Markov switching model with the predetermined variables mentioned later, whose parameters were obtained through the expectation–maximization algorithm. Then, we built a probability index as early warning indicator for potential imbalances in the real estate price that could put financial market stability at risk. The indicator is important to evaluate economic policy calibrations in time. A main finding was that the real housing price had a non-linear relationship with economic activity and the mortgage interest rate. Therefore, the evolution of the real estate price has been consistent with fundamental macroeconomic variables, even under a high growth regime, with increases above 12% per year. About 92% of housing price variability derived from changing macrofinancial conditions, suggesting a low margin of speculative behavior.

Optimal design of an off-grid hybrid renewable energy system considering generation and load uncertainty: the case of Zanjan city, Iran

In this paper, designing a hybrid stand-alone photovoltaic/wind energy system with battery storage (PV/WT/Batt) is presented to minimize the total cost of the hybrid system and considering reliability constraints for Zanjan city in Iran country considering generation and load uncertainties. The total cost includes the cost of the system components and load losses cost and also deficit power probability-hourly interruption probability index, which is defined as the reliability constraint. The optimal size of the system components is found using an improved crow search algorithm based on mutation and crossover operators of the genetic algorithm to prevent premature convergence. The optimal designing of the hybrid system is implemented considering the uncertainty of photovoltaic and wind resources as well as the load demand of the system based on the probability distribution functions of uncertain parameters using Monte Carlo simulation. The simulations are implemented in two deterministic and probabilistic scenarios. In the deterministic scenario, the optimal design of various combinations of the hybrid system is investigated in view of the system cost and deficit power probability probability-hourly interruption probability index based on the improved crow search algorithm with and without the cost of load loss. The results of the deterministic scenario showed that the system cost is increased considering the cost of load loss, but the system load is supplied with higher reliability. Also, the deterministic results cleared the superiority of the improved crow search algorithm compared with conventional crow search algorithm and particle swarm optimization methods. Moreover, the results of the system designing showed that considering the uncertainty, the system cost increases, and the reliability is significantly improved. The results cleared that the system cost in deterministic and probabilistic designing is obtained 1.0108 M$ and 1.210 M$, respectively for load supply equal to 153.87 MWh. So, due to the inherent nature of the uncertainty in the renewable resources power generation as well as continuous load changes, a probabilistic approach of the hybrid system designing is necessary to know the accurate cost and reliability. Article highlights Effective performance of the proposed method in system designing with lowest cost and higher reliability. Achieving to a more reliable hybrid energy system with considering cost of load losses in designing. Increasing the system the cost and improving the reliability considering uncertainties of generation and load.

Application of C-N fractal model, factor analysis, and geochemical mineralization probability index (GMPI) for delineating geochemical anomalies related to Mn-Fe deposit and associated Cu mineralization in west-central Sinai, Egypt

The west-central Sinai area includes one of the most productive manganese deposits in Egypt (Um Bogma Mn-Fe ore). The explored area is covered by a Carboniferous and Cambro-Ordovician sedimentary succession overlying Precambrian basement rocks. The purpose of this study is to delineate geochemical anomalies of ore and related elements and track their dispersion trains, which may lead to discovery of unknown ore deposits. For this purpose, 143 stream sediment samples were analyzed and the data were interpreted using the concentration-number (C-N) fractal model, factor analysis, and the geochemical mineralization probability index. Geochemical thresholds obtained from the C-N fractal model, factor scores, and GMPI were used for constructing geochemical anomaly maps and delineating probable anomalous sites. The spatial distribution of Mn, Cu, Co, Pb, and Zn anomalies was correlated to Mn and Cu mineralization sites whereas those of Fe and Cr were consistent with mafic rock distributions. Factor analysis revealed significant element associations for mineralization (Cu, Co, Mn, Zn, Pb), country rock composition (Fe, Cr), and element mobility (Cd, Zn). The spatial distribution of ore elements (Mn, Cu) delineated by the factor score and GMPI distribution maps was confirmed and more accurately interpreted using geochemical anomaly maps constructed based on the fractal-derived thresholds. Based on the current study, recent Cu and Mn mineralization sites may be suggested. Cobalt, Zn, Pb, and Cd are suggested as efficient pathfinder elements for marine Mn deposits. A dispersion sequence of Cd>Mn>Co>Pb>Zn>Cu>Cr>Fe was proposed based on the threshold distribution patterns of these elements.Supplementary material:https://doi.org/10.6084/m9.figshare.c.5463511

Evaluating the Performance of Five Asset-based Wealth Indices in Predicting Socioeconomic Position in Rural Bangladesh

Social scientists have developed numerous asset-based wealth indices to assess and target socioeconomic inequalities globally. However, there are no systematic studies of the relative performance of these different measures as proxies for socioeconomic position. In this study, we compare how five asset-based wealth indices—the International Wealth Index (IWI), the Standard of Living portion of the Multi-Dimensional Poverty Index (MPI-SL), the Poverty Probability Index (PPI), the Absolute Wealth Estimate (AWE), and the DHS Wealth Index (DHS)—predict benchmarks of socioeconomic position across 11 communities in rural Bangladesh. All indices were highly correlated. The IWI best explained variation in individual and community ranking of economic well-being, while the PPI best explained variation both between and within communities for total household wealth and a general measure of subjective social status.

POS0757 SYSTEMIC LUPUS ERYTHEMATOSUS (SLE) DIAGNOSED DURING HOSPITALIZATION: CLINICAL PHENOTYPE AND PERFORMANCE OF THE SLE RISK PROBABILITY INDEX (SLERPI)

Background:Systemic Lupus Erythematosus (SLE) can first present with severe or critical disease leading to hospitalization. Prompt recognition of the disease in hospitalized patients may lead to early institution of treatment and improve outcomes. We have recently developed a clinician-friendly algorithm for SLE diagnosis based on classical clinical and serological SLE features [SLE Risk Probability Index (SLERPI)]1.Objectives:To determine the clinical phenotype of SLE patients first diagnosed during hospitalization, the interval between hospitalization and SLE diagnosis and the potential impact of SLERPI on early diagnosis.Methods:Mixed prospective (from June 2020 to January 2021) and retrospective study of SLE patients from “Attikon” cohort (n=820)2. Clinical phenotype was divided into 10 core domains (neuropsychiatric, thrombosis, nephritis, serosal, haematologic, pulmonary, cardiovascular, gastrointestinal, skin-joints, other). Chart review and patient interview was performed to assess the lag time between 1) the onset of symptoms and 2) the hospitalization and the final diagnosis. Demographic and clinical characteristics, SLERPI and SLICC damage index were recorded for each patient at the time of diagnosis. SLE diagnosis was based on at least one of the three existing classification criteria.Results:Out of 820 SLE patients, 202 (24.6%) diagnosed during hospitalization were included. Among them, 185 patients (91.5%) were hospitalized because of a lupus related feature, while in the remaining 17 SLE patients, hospitalization was due to non-lupus related manifestations. The most common lupus-related clinical phenotype leading to hospital admission was neuropsychiatric lupus (n=51, 25.2%) with cerebrovascular events constituting the dominant clinical syndrome (n=8/51). Thrombotic events (n=32, 15.8%), mainly pulmonary embolism (n=20/32), cytopenias (n=32, 15.8%), lupus nephritis (n=30, 14.8%), skin-joint disease (n=26, 12.8%) and serositis (n=24, 11.8%) were also common as dominant manifestations. Pulmonary disease (n=16, 7.9%), heart disease (n= 4, 1.9%) and gastrointestinal disease (n=2, 0.9%) were less common. On admission, 11.3% of patients (n=23) had symptoms from at least 2 clinical domains as defined. Most patients (93.5%) had multisystem disease while only 6.5% had organ-dominant disease. Early diagnosis (within 3 months from hospitalization) was established in 86.6% while 27 patients had their SLE diagnosis more than 3 months from hospitalization. The mean lag time between the hospitalization and the diagnosis was approximately 14 months (SD 19.9). Overall, the mean interval between the onset of symptoms and the diagnosis was 48.2 months (SD 73.2). Importantly, a SLERPI >7 (suggesting probable SLE) at hospitalization was present in 92.5% of SLE patients with delayed diagnosis.Conclusion:One out of four SLE patients first present with moderate to severe disease necessitating hospitalization, while in approximately 15% of such patients, diagnosis is initially missed. Application of the SLERPI may facilitate early SLE diagnosis.References:[1]Adamichou C et al. Ann Rheum Dis. 2021; DOI: 10.1136/annrheumdis-2020-219069.[2]D Nikolopoulos et al. Lupus 2020; doi: 10.1177/0961203320908932.Acknowledgements:This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 742390)Disclosure of Interests:None declared