MeshPipe: a Python-based tool for easy automation and demonstration of geometry processing pipelines

The popularization of inexpensive 3D scanning, 3D printing, 3D publishing and AR/VR display technologies have renewed the interest in open-source tools providing the geometry processing algorithms required to clean, repair, enrich, optimize and modify point-based and polygonal-based models. Nowadays, there is a large variety of such open-source tools whose user community includes 3D experts but also 3D enthusiasts and professionals from other disciplines. In this paper we present a Python-based tool that addresses two major caveats of current solutions: the lack of easy-to-use methods for the creation of custom geometry processing pipelines (automation), and the lack of a suitable visual interface for quickly testing, comparing and sharing different pipelines, supporting rapid iterations and providing dynamic feedback to the user (demonstration). From the user's point of view, the tool is a 3D viewer with an integrated Python console from which internal or external Python code can be executed. We provide an easy-to-use but powerful API for element selection and geometry processing. Key algorithms are provided by a high-level C library exposed to the viewer via Python-C bindings. Unlike competing open-source alternatives, our tool has a minimal learning curve and typical pipelines can be written in a few lines of Python code.Peer ReviewedPostprint (published version

Potential of a terrestrial LiDAR-based system to characterise weed vegetation in maize crops

LiDAR (Light Detection And Ranging) is a remote-sensing technique for the measurement of the distance between the sensor and a target. A LiDAR-based detection procedure was tested for characterisation of the weed vegetation present in the inter-row area of a maize field. This procedure was based on the hypothesis that weed species with different heights can be precisely detected and discriminated using non-contact ranging sensors such as LiDAR. The sensor was placed in the front of an all-terrain vehicle, scanning downwards in a vertical plane, perpendicular to the ground, in order to detect the profile of the vegetation (crop and weeds) above the ground. Measurements were taken on a maize field on 3 m wide (0.45 m2) plots at the time of post-emergence herbicide treatments. Four replications were assessed for each of the four major weed species: Sorghum halepense, Cyperus rotundus, Datura ferox and Xanthium strumarium. The sensor readings were correlated with actual, manually determined, height values (r2 = 0.88). With canonical discriminant analysis the high capabilities of the system to discriminate tall weeds (S. halepense) from shorter ones were quantified. The classification table showed 77.7% of the original grouped cases (i.e., 4800 sampling units) correctly classified for S. halepense. These results indicate that LiDAR sensors are a promising tool for weed detection and discrimination, presenting significant advantages over other types of non-contact ranging sensors such as a higher sampling resolution and its ability to scan at high sampling rates.This research was funded by the Spanish CICyT (Project AGL 2008-04670-C03

VR-assisted architectural design in a heritage site: the Sagrada Família case study

Virtual Reality (VR) simulations have long been proposed to allow users to explore both yet-to-built buildings in architectural design, and ancient, remote or disappeared buildings in cultural heritage. In this paper we describe an on-going VR project on an UNESCO World Heritage Site that simultaneously addresses both scenarios: supporting architects in the task of designing the remaining parts of a large unfinished building, and simulating existing parts that define the environment that new designs must conform to. The main challenge for the team of architects is to advance towards the project completion being faithful to the original Gaudí’s project, since many plans, drawings and plaster models were lost. We analyze the main requirements for collaborative architectural design in such a unique scenario, describe the main technical challenges, and discuss the lessons learned after one year of use of the system.Peer ReviewedPostprint (published version

Digital reintegration of distributed mural paintings at different architectural phases: the case of St. Quirze de Pedret

Sant Quirze de Pedret is a Romanesque church located in Cercs (Catalonia, Spain) at the foothills of the Pyrenees. Its walls harbored one of the most important examples of mural paintings in Catalan Romanesque Art. However, in two different campaigns (in 1921 and 1937) the paintings were removed using the strappo technique and transferred to museums for safekeeping. This detachment protected the paintings from being sold in the art market, but at the price of breaking the integrity of the monument. Nowadays, the paintings are exhibited in the Museu Nacional d'Art de Catalunya - MNAC (Barcelona, Catalonia) and the Museu Diocesà i Comarcal de Solsona - MDCS (Solsona, Catalonia). Some fragments of the paintings are still on the walls of the church. In this work, we present the methodology to digitally reconstruct the church building at its different phases and group the dispersed paintings in a single virtual church, commissioned by the MDCS. We have combined 3D reconstruction (LIDAR and photogrammetric using portable artificial illumination) and modeling techniques (including texture transfer between different shapes) to recover the integrity of the monument in a single 3D virtual model. Furthermore, we have reconstructed the church building at different significant historical moments and placed actual paintings on its virtual walls, based on archaeological knowledge. This set of 3D models allows experts and visitors to better understand the monument as a whole, the relations between the different paintings, and its evolution over time.The project has been promoted by the Museu Diocesà i Comarcal de Solsona (special thanks are due to Carles Freixes and Lídia Fàbregas), co-financed by "La Caixa" Foundation and the Department of Culture of the Generalitat de Catalunya. Likewise, the work presented here counted with the support of MEIC (Spanish Government) project 3D4LIFE (TIN-2017-88515-C2), PRECA II of the Universitat de Barcelona (HAR2017-84451-P) and EHEM (JPICH0127 Conservation, Protection and Use, PCI2020-111979). The high-resolution photographs of the paintings are by Gaetano Alfano (Università degli Studi della Tuscia).Peer ReviewedPostprint (published version

Half of the patients with subepithelial tumours present borderline or pathologic anxiety-distress and carcinophobia: multicentre cohort study

Background and aims: minor nonspecific gastrointestinal sub-epithelial lesions (usually defined by the term 'tumor') are usually associated with a malignant illness and cancer. The aim of this study was to assess anxiety-distress and carcinophobia in patients referred to specialized monographic outpatient clinics for evaluation and treatment of this type of lesion.Methods: prospective, multicenter, cohort study. Specific self-reported questionnaires were used to report threat-ening life-experiences and to assess levels of distress (The Hospital Anxiety and Depression Scale) and cancer-related worries (The Cancer Worry Scale).Results: forty participants were included and analyzed at baseline. Pathologic and borderline anxiety were detected in 13 % (5/40, 95 % CI: 4-27 %) and 35 % (14/40, 95 % CI: 21-52 %) of participants, respectively, whereas, cancer-relat-ed worries (moderate to very high) were observed in 48 % (19/40, 95 % CI: 32-64 %) of participants. Pathologic global distress was identified in 25 % (10/40, 95 % CI: 13-42 %) of subjects. Higher educational level (university studies), a lack of lifetime psychiatric comorbidity and a lack of family history of cancer were associated with less anxiety, global distress and carcinophobia.Conclusions: almost half of the patients diagnosed with a minor nonspecific gastrointestinal subepithelial lesion pre-sented anxiety-distress and/or carcinophobia. Specific associ-ations with anxiety-distress reaction and fears were detected

Discriminating Crop, Weeds and Soil Surface with a Terrestrial LIDAR Sensor

In this study, the evaluation of the accuracy and performance of a light detection and ranging (LIDAR) sensor for vegetation using distance and reflection measurements aiming to detect and discriminate maize plants and weeds from soil surface was done. The study continues a previous work carried out in a maize field in Spain with a LIDAR sensor using exclusively one index, the height profile. The current system uses a combination of the two mentioned indexes. The experiment was carried out in a maize field at growth stage 12–14, at 16 different locations selected to represent the widest possible density of three weeds: Echinochloa crus-galli (L.) P.Beauv., Lamium purpureum L., Galium aparine L.and Veronica persica Poir.. A terrestrial LIDAR sensor was mounted on a tripod pointing to the inter-row area, with its horizontal axis and the field of view pointing vertically downwards to the ground, scanning a vertical plane with the potential presence of vegetation. Immediately after the LIDAR data acquisition (distances and reflection measurements), actual heights of plants were estimated using an appropriate methodology. For that purpose, digital images were taken of each sampled area. Data showed a high correlation between LIDAR measured height and actual plant heights (R 2 = 0.75). Binary logistic regression between weed presence/absence and the sensor readings (LIDAR height and reflection values) was used to validate the accuracy of the sensor. This permitted the discrimination of vegetation from the ground with an accuracy of up to 95%. In addition, a Canonical Discrimination Analysis (CDA) was able to discriminate mostly between soil and vegetation and, to a far lesser extent, between crop and weeds. The studied methodology arises as a good system for weed detection, which in combination with other principles, such as vision-based technologies, could improve the efficiency and accuracy of herbicide spraying

The Renal Range of the κ/λ sFLC Ratio: Best Strategy to Evaluate Multiple Myeloma in Patients With Chronic Kidney Disease

Background: Monoclonal serum free light chains (sFLC) are a well-known cause of renal impairment (RI) in patients with multiple myeloma (MM). As an indicator of monoclonality, sFLC ratio has acquired a key role in the diagnosis and monitorization of the disease. However, its interpretation is altered in patients with chronic kidney disease (CKD). This study aims to evaluate the modification of the sFLC ratio reference range in patients with CKD, and propose an optimal range for patients with CKD. Methods: Serum FLC κ/λ ratio and estimated glomerular filtration rate (eGFR) were retrospectively analyzed in 113 control patients (without hematologic disease), 63 patients with MM in complete remission and 347 patients with active MM. The three groups included patients with CKD (eGFR < 90). Results: In the group of patients without active MM (n = 176), the sFLC ratio increased at different stages of CKD without pathological significance, with an increase in the number of false positives specially when eGFR is ≤55 ml/ min. An optimal range was established for patients with eGFR ≤55 ml/min/1.73 m2: 0.82-3,6 with maximum sensitivity + specificity for that group with an improvement in the Area under the curve (AUC), 0.91 (0.84-0.97) compared with the current ranges proposed by Katzmann and Hutchinson. Conclusions: This study confirms the influence of eGFR on the interpretation of the sFLC ratio, showing a decreasing specificity in progressive CKD stages when using the reference sFLC range (Katzmann), especially in patients with eFGR ≤55. According to our results, we suggest a modified optimal range (0.82-3,6) for eGFR ≤55 ml/ min/1.73 m2. It is necessary to validate this modified range in larger and prospective studies