Support Vector Regression for Rainfall-Runoff Modeling in Urban Drainage: A Comparison with the EPA's Storm Water Management Model

Rainfall-runoff models can be classified into three types: physically based models, conceptual models, and empirical models. In this latter class of models, the catchment is considered as a black box, without any reference to the internal processes that control the transformation of rainfall to runoff. In recent years, some models derived from studies on artificial intelligence have found increasing use. Among these, particular attention should be paid to Support Vector Machines (SVMs). This paper shows a comparative study of rainfall-runoff modeling between a SVM-based approach and the EPA's Storm Water Management Model (SWMM). The SVM is applied in the variant called Support Vector regression (SVR). Two different experimental basins located in the north of Italy have been considered as case studies. Two criteria have been chosen to assess the consistency between the recorded and predicted flow rates: the root-mean square error (RMSE) and the coefficient of determination. The two models showed comparable performance. In particular, both models can properly model the hydrograph shape, the time to peak and the total runoff. The SVR algorithm tends to underestimate the peak discharge, while SWMM tends to overestimate it. SVR shows great potential for applications in the field of urban hydrology, but currently it also has significant limitations regarding the model calibration

Effect of microplastics on urban wastewater disinfection and impact on effluent reuse: Sunlight/H2O2 vs solar photo-Fenton at neutral pH

The interference of three types of microplastics (MPs) on the inactivation of Escherichia coli (E. coli) by advanced oxidation processes (AOPs) (namely, sunlight/H2O2 and solar photo-Fenton (SPF) with Ethylenediamine-N,N ' disuccinic acid (EDDS)), in real secondary treated urban wastewater was investigated for the first time. Inactivation by sunlight/H2O2 treatment decreased as MPs concentration and H2O2 dose were increased. Noteworthy, an opposite behaviour was observed for SPF process where inactivation increased as MPs concentration was increased. Biofilm formation and microbial attachment on surfaces of post-treated MPs were observed on polyethylene (PE) and polyvinyl chloride (PVC) MPs by field emission scanning electron microscopy. In presence of PE MPs, a complete inactivation of E. Coli was achieved by SPF with EDDS (Fe:EDDS = 1:2) after 90 min treatment unlike of sunlight/H2O2 treatment (-4.0 log reduction, 40 mg/L H2O2 dose, 90 min treatment). The lower efficiency of sunlight/H2O2 process could be attributed to the blocking/scattering effect of MPs on sunlight, which finally reduced the intracellular photo Fenton effect. A reduced E. coli regrowth was observed in presence of MPs. SPF (Fe:EDDS = 1:1) with PE MPs was less effective in controlling bacterial regrowth (-120 CFU/100 mL) than sunlight/H2O2 (-10 CFU/100 mL) after 48 h of post-treatment. These results provide useful information about possible interference of MPs on urban wastewater disinfection by solar driven AOPs and possible implications for effluent reuse

machine learning models for spring discharge forecasting

Nowadays, drought phenomena increasingly affect large areas of the globe; therefore, the need for a careful and rational management of water resources is becoming more pressing. Considering that most of the world's unfrozen freshwater reserves are stored in aquifers, the capability of prediction of spring discharges is a crucial issue. An approach based on water balance is often extremely complicated or ineffective. A promising alternative is represented by data-driven approaches. Recently, many hydraulic engineering problems have been addressed by means of advanced models derived from artificial intelligence studies. Three different machine learning algorithms were used for spring discharge forecasting in this comparative study: M5P regression tree, random forest, and support vector regression. The spring of Rasiglia Alzabove, Umbria, Central Italy, was selected as a case study. The machine learning models have proven to be able to provide very encouraging results. M5P provides good short-term predictions of monthly average flow rates (e.g., in predicting average discharge of the spring after 1 month, R2=0.991, RAE=14.97%, if a 4-month input is considered), while RF is able to provide accurate medium-term forecasts (e.g., in forecasting average discharge of the spring after 3 months, R2=0.964, RAE=43.12%, if a 4-month input is considered). As the time of forecasting advances, the models generally provide less accurate predictions. Moreover, the effectiveness of the models significantly depends on the duration of the period considered for input data. This duration should be close to the aquifer response time, approximately estimated by cross-correlation analysis

NEW REMAINS OF CASATIA THERMOPHILA (CETACEA, MONODONTIDAE) FROM THE LOWER PLIOCENE MARINE VERTEBRATE-BEARING LOCALITY OF ARCILLE (TUSCANY, ITALY)

An incomplete cranium, three cervicals (including the axis) and two likely lumbars of a monodontid cetacean are here described from lower Pliocene (ca. 5.1–4.5 Ma) marine sandstones cropping out at Arcille (Grosseto Province, Tuscany, Italy). This fossil find comes from the same locality as the holotype of Casatia thermophila, which it resembles in terms of overall size and cranial morphology, and especially, by displaying a similarly depressed portion of the dorsal surface of the premaxillae anterior to the premaxillary sac fossae and medial to the anteromedial sulci. Our new find is thus assigned to C. thermophila, and significant anatomical parts that are missing in the holotype are described in order to improve the diagnosis of this monodontid species. Some dentigerous fragments of the maxillae hint at a homodont and polydont dentition, which in turn suggests a ram prey capture method that differs from the highly derived suction method that is proper of extant monodontids. This second find of C. thermophila from the warm-water Arcille palaeoenvironment lends further support to the hypothesis that monodontids once thrived in tropical and subtropical habitats

Proteomics Insights into Medullary Sponge Kidney Disease: Review of the Recent Results of an Italian Research Collaborative Network

Background: Medullary sponge kidney (MSK) disease is a rare and neglected congenital condition typically associated with nephrocalcinosis/nephrolithiasis, urinary concentration defects, and cystic anomalies in the precalyceal ducts that, although sporadic in the general population, is relatively frequent in renal stone formers. The physiopathologic mechanism associated with this disease is not fully understood, and omics technologies may help address this gap. Summary: The aim of this review was to provide an overview of the current state of the application of proteomics in the study of this rare disease. In particular, we focused on the results of our recent Italian collaborative studies that, analyzing the MSK whole and extracellular vesicle urinary content by mass spectrometry, have displayed the existence of a large and multifactorial MSK-associated biological machinery and identified some main regulatory biological elements able to discriminate patients affected by this rare disorder from those with idiopathic calcium nephrolithiasis and autosomal dominant polycystic kidney disease (including laminin subunit alpha 2, ficolin 1, mannan-binding lectin serine protease 2, complement component 4-binding protein β, sphingomyelin, ephrins). Key Messages: The application of omics technologies has provided new insights into the comprehension of the physiopathology of the MSK disease and identified novel potential diagnostic biomarkers that may replace in future expensive and invasive radiological tests (including CT) and select novel therapeutic targets potentially employable, whether validated in a large cohort of patients, in the daily clinical practice

A rare case of solitary brain Langerhans cell histiocytosis with intratumoral hemorrhage in a patient affected by Turner syndrome

Langerhans cell histiocytosis (LCH) is a rare disease involving clonal proliferation of cells with characteristics similar to bone marrow-derived Langerhans cells. The case of a young woman, affected by Turner syndrome and a solitary intraparenchymal LCH associated with an osteolytic lesion of the overlying skull, is presented

Heparanase and Renal Fibrosis

n/

Comparative analysis of digital models from 3D photogrammetry and structured light scanning for the study of tetrapod tracks

The present work aims at analyzing the acquisition capacity of different digital reconstruction techniques for three-dimensional models, in the frame of the study of the remarkable Middle Triassic (Ladinic) tetrapod ichnoassemblage from the Quarziti del Monte Serra Formation (Monti Pisani, Tuscany, central Italy). Tracks stored in different Italian museum collections were processed and analyzed through two different digital acquisition methodologies, namely, digital photogrammetry and structured light scanning (with the EinScan Pro HD scanner model, capable of a maximum resolution of 0.2 mm) to evaluate which of these techniques is most suitable for the study of small- to medium-sized tetrapod tracks. Two models were created for each sample, one for each acquisition methodology. These models were processed using the software Meshmixer, Meshlab and CloudCompare, to locate any possible error in the mesh, correct them and compare the models with each other in terms of quality and graphical rendering, respectively. The RStudio software was also used to verify and control, by using statistical tests, the normal distribution of the data, as well as to further process them. We noticed that the average number of triangles is higher for the meshes obtained via photogrammetry; likewise, the values of the metric “Per Face Quality according to triangle shape and aspect ratio – Mean ratio of triangle”, available on Meshlab and used here to evaluate the quality of a mesh, is higher. Photogrammetry is thus preferable in the study of centimetric tracks as it allows for very high levels of mesh detail. That said, more experience and a deeper understanding of the acquisition process by the operator are needed for fruitfully exploiting the full potentialities of photogrammetr

Sphingomyelin and medullary sponge kidney disease: a biological link identified by omics approach

Background: Molecular biology has recently added new insights into the comprehension of the physiopathology of the medullary sponge kidney disease (MSK), a rare kidney malformation featuring nephrocalcinosis and recurrent renal stones. Pathogenesis and metabolic alterations associated to this disorder have been only partially elucidated.Methods: Plasma and urine samples were collected from 15 MSK patients and 15 controls affected by idiopathic calcium nephrolithiasis (ICN). Plasma metabolomic profile of 7 MSK and 8 ICN patients was performed by liquid chromatography combined with electrospray ionization tandem mass spectrometry (UHPLC-ESI-MS/MS). Subsequently, we reinterrogated proteomic raw data previously obtained from urinary microvesicles of MSK and ICN focusing on proteins associated with sphingomyelin metabolism. Omics results were validated by ELISA in the entire patients' cohort.Results: Thirteen metabolites were able to discriminate MSK from ICN (7 increased and 6 decreased in MSK vs. ICN). Sphingomyelin reached the top level of discrimination between the two study groups (FC: -1.8, p < 0.001). Ectonucleotide pyrophophatase phosphodiesterase 6 (ENPP6) and osteopontin (SPP1) resulted the most significant deregulated urinary proteins in MSK vs. ICN (p < 0.001). ENPP6 resulted up-regulated also in plasma of MSK by ELISA.Conclusion: Our data revealed a specific high-throughput metabolomics signature of MSK and indicated a pivotal biological role of sphingomyelin in this disease

Cavernous malformation of the optic chiasm: An uncommon location

Cavernous malformations (CMs) of the optic chiasm are rare lesions often presenting with acute chiasmal syndrome or a progressive visual loss. The case of a 48-year-old female with an intrachiasmatic CM is presented