A modified DEA model to estimate the importance of objectives with an application to agricultural economics

This paper demonstrates a connection between data envelopment analysis (DEA) and a non-interactive elicitation method to estimate the weights of objectives for decision-makers in a multiple attribute approach. This connection gives rise to a modified DEA model that allows us to estimate not only efficiency measures but also preference weights by radially projecting each unit onto a linear combination of the elements of the payoff matrix (which is obtained by standard multicriteria methods). For users of multiple attribute decision analysis the basic contribution of this paper is a new interpretation in terms of efficiency of the non-interactive methodology employed to estimate weights in a multicriteria approach. We also propose a modified procedure to calculate an efficient payoff matrix and a procedure to estimate weights through a radial projection rather than a distance minimization. For DEA users, we provide a modified DEA procedure to calculate preference weights and efficiency measures that does not depend on any observations in the dataset. This methodology has been applied to an agricultural case study in Spain.

Sustainable deployment of QTLs conferring quantitative resistance to crops: first lessons from a stochastic model

International audience

Evaluation of hemosponge in promoting dental socket healing after 3rd mandibular premolar extraction in a feline model

Aim: To investigate the healing process following use of collagen sponges in the dental socket after extraction. Wound complications during the study were also evaluated. Methods: 32 cats were included in this study. IV administration of the combination of diazepam (0.22 mg/kg) and ketamine (10 mg/kg) was used to induce general anesthesia. Surgical extraction of both 3rd mandibular premolars was performed. The open dental sockets were divided in two groups. In Group A, the open dental socket on the left side was closed using 4-0 Monocryl in simple interrupted pattern. In Group B, the right dental socket was filled with lyophilized hydrolyzed collagen and the buccal and lingual flaps were sutured using 4-0 Monocryl and simple interrupted pattern. Meloxicam (0.2 mg/kg) was used to manage the post-extraction pain in all cats. Ampicilline 20 mg/kg was used as prophylaxis. The wounds were observed during the study to evaluate any signs of inflammation or dehiscence. Radiographs were taken to compare healing of the socket 3 weeks after the procedure. A 1 mm biopsy punch sample was taken from sockets in all cats for comparison of the healing in both groups. Results: Hemorrhage occurred only in the sockets of Group A. Remission of radiolucent area occurred in both groups. Mean score of inflammation was lower and mean scores of fibrotic reaction and fibroplasia were higher in Group B (p<0.05). Conclusions: Use of hemosponge in alveolar socket may accelerate fibroplasia and formation of the connective tissue and reduce inflammation after tooth extraction. Therefore, post-extraction use of the hemostatic agent in the dental socket is recommended.

Analgesic synergism of gabapentin and carbamazepine in rat model of diabetic neuropathic pain

Purpose: To evaluate synergy in the analgesic effects of a combination therapy of carbamazepine (CBZ) and gabapentin (GBP) in diabetic neuropathic pain. Methods: Neuropathic pain was produced in rats by a single intraperitoneal injection of streptozotocin (STZ) at 60 mg/kg. CBZ, GBP, and their combination were orally administered at varying doses (GBP 30 - 180 mg/kg; CBZ 20 - 40 mg/kg) comparable to their therapeutic doses in humans. Nociceptive responses in the diabetic rats were assessed using hot plate test. Results: Hot plate latency significantly increased with oral administration of GBP at a dose of 180 mg/kg when compared with control group (p < 0.05), while at a dose of 90 mg/kg, the increase was not significant. Oral administration of CBZ at doses of 20 and 40 mg/kg did not produce any significant impact on hot plate latency. However, a combination of GBP at 90 mg/kg and CBZ at 20 mg/kg produced significant increase in latency, compared with control group and other groups (p < 0.05), except the group that received 180 mg/kg GBP. The combination of low dose GBP 30 mg/kg and carbamazepine 30 mg/kg had no significant effect on latency (p > 0.05). Conclusion: The results obtained in this study provide useful information on the combination therapy of GBP and CBZ, which may be applied in the treatment of pain in diabetic neuropathy.

DYNAMIC MODEL BASED STATE ESTIMATION IN A HEAVY DUTY DIESEL AFTERTREATMENT SYSTEM FOR ONBOARD DIAGNOSTICS AND CONTROLS

Estimating un-measurable states is an important component for onboard diagnostics (OBD) and control strategy development in diesel exhaust aftertreatment systems. This research focuses on the development of an Extended Kalman Filter (EKF) based state estimator for two of the main components in a diesel engine aftertreatment system: the Diesel Oxidation Catalyst (DOC) and the Selective Catalytic Reduction (SCR) catalyst. One of the key areas of interest is the performance of these estimators when the catalyzed particulate filter (CPF) is being actively regenerated. In this study, model reduction techniques were developed and used to develop reduced order models from the 1D models used to simulate the DOC and SCR. As a result of order reduction, the number of states in the estimator is reduced from 12 to 1 per element for the DOC and 12 to 2 per element for the SCR. The reduced order models were simulated on the experimental data and compared to the high fidelity model and the experimental data. The results show that the effect of eliminating the heat transfer and mass transfer coefficients are not significant on the performance of the reduced order models. This is shown by an insignificant change in the kinetic parameters between the reduced order and 1D model for simulating the experimental data. An EKF based estimator to estimate the internal states of the DOC and SCR was developed. The DOC and SCR estimators were simulated on the experimental data to show that the estimator provides improved estimation of states compared to a reduced order model. The results showed that using the temperature measurement at the DOC outlet improved the estimates of the CO , NO , NO2 and HC concentrations from the DOC. The SCR estimator was used to evaluate the effect of NH3 and NOX sensors on state estimation quality. Three sensor combinations of NOX sensor only, NH3 sensor only and both NOX and NH3 sensors were evaluated. The NOX only configuration had the worst performance, the NH3 sensor only configuration was in the middle and both the NOX and NH3 sensor combination provided the best performance.

Gravimetric and density profiling using the combination of surface acoustic waves and neutron reflectivity

A new approach is described herein, where neutron reflectivity measurements that probe changes in the density profile of thin films as they absorb material from the gas phase have been combined with a Love wave based gravimetric assay that measures the mass of absorbed material. This combination of techniques not only determines the spatial distribution of absorbed molecules, but also reveals the amount of void space within the thin film (a quantity that can be difficult to assess using neutron reflectivity measurements alone). The uptake of organic solvent vapours into spun cast films of polystyrene has been used as a model system with a view to this method having the potential for extension to the study of other systems. These could include, for example, humidity sensors, hydrogel swelling, biomolecule adsorption or transformations of electroactive and chemically reactive thin films. This is the first ever demonstration of combined neutron reflectivity and Love wave-based gravimetry and the experimental caveats, limitations and scope of the method are explored and discussed in detail.

Integration of a graph-based model indexer in commercial modelling tools

Softeam has over 20 years of experience providing UML-based modelling solutions, such as its Modelio modelling tool, and its Constellation enterprise model management and collaboration environment. Due to the increasing number and size of the models used by Softeam’s clients, Softeam joined the MONDO FP7 EU research project, which worked on solutions for these scalability challenges and produced the Hawk model indexer among other results. This paper presents the technical details and several case studies on the integration of Hawk into Softeam’s toolset. The first case study measured the performance of Hawk’s Modelio support using varying amounts of memory for the Neo4j backend. In another case study, Hawk was integrated into Constellation to provide scalable global querying of model repositories. Finally, the combination of Hawk and the Epsilon Generation Language was compared against Modelio for document generation: for the largest model, Hawk was two orders of magnitude faster.

Fluorescence of nitrobenzoxadiazole (NBD)-labeled lipids in model membranes is connected not to lipid mobility but to probe location

Nitrobenzoxadiazole (NBD)-labeled lipids are popular fluorescent membrane probes. However, the understanding of important aspects of the photophysics of NBD remains incomplete, including the observed shift in the emission spectrum of NBD-lipids to longer wavelengths following excitation at the red edge of the absorption spectrum (red-edge excitation shift or REES). REES of NBD-lipids in membrane environments has been previously interpreted as reflecting restricted mobility of solvent surrounding the fluorophore. However, this requires a large change in the dipole moment (Dm) of NBD upon excitation. Previous calculations of the value of Dm of NBD in the literature have been carried out using outdated semi-empirical methods, leading to conflicting values. Using up-to-date density functional theory methods, we recalculated the value of Dm and verified that it is rather small (B2 D). Fluorescence measurements confirmed that the value of REES is B16 nm for 1,2-dioleoyl-sn-glycero-3- phospho-L-serine-N-(NBD) (NBD-PS) in dioleoylphosphatidylcholine vesicles. However, the observed shift is independent of both the temperature and the presence of cholesterol and is therefore insensitive to the mobility and hydration of the membrane. Moreover, red-edge excitation leads to an increased contribution of the decay component with a shorter lifetime, whereas time-resolved emission spectra of NBD-PS displayed an atypical blue shift following excitation. This excludes restrictions to solvent relaxation as the cause of the measured REES and TRES of NBD, pointing instead to the heterogeneous transverse location of probes as the origin of these effects. The latter hypothesis was confirmed by molecular dynamics simulations, from which the calculated heterogeneity of the hydration and location of NBD correlated with the measured fluorescence lifetimes/REES. Globally, our combination of theoretical and experiment-based techniques has led to a considerably improved understanding of the photophysics of NBD and a reinterpretation of its REES in particular.

Study of Bone Biomineralization in 2D and 3D Cultures of a Human Osteosarcoma Cell Line As Osteoblast-like Model

This PhD project focuses on the study of the early stages of bone biomineralization in 2D and 3D cultures of osteoblast-like SaOS-2 osteosarcoma cells, exposed to an osteogenic cocktail. The efficacy of osteogenic treatment was assessed on 2D cell cultures after 7 days. A large calcium minerals production, an overexpression of osteogenic markers and of alkaline phosphatase activity occurred in treated samples. TEM microscopy and cryo-XANES micro-spectroscopy were performed for localizing and characterizing Ca-depositions. These techniques revealed a different localization and chemical composition of Ca-minerals over time and after treatment. Nevertheless, the Mito stress test showed in treated samples a significant increase in maximal respiration levels associated to an upregulation of mitochondrial biogenesis indicative of an ongoing differentiation process. The 3D cell cultures were realized using two different hydrogels: a commercial collagen type I and a mixture of agarose and lactose-modified chitosan (CTL). Both biomaterials showed good biocompatibility with SaOS-2 cells. The gene expression analysis of SaOS-2 cells on collagen scaffolds indicated an osteogenic commitment after treatment. and Alizarin red staining highlighted the presence of Ca-spots in the differentiated samples. In addition, the intracellular magnesium quantification, and the X-ray microscopy on mineral depositions, suggested the incorporation of Mg during the early stages of bone formation process., SaOS-2 cells treated with osteogenic cocktail produced Ca mineral deposits also on CTL/agarose scaffolds, as confirmed by alizarin red staining. Further studies are underway to evaluate the differentiation also at the genetic level. Thanks to the combination of conventional laboratory methods and synchrotron-based techniques, it has been demonstrated that SaOS-2 is a suitable model for the study of biomineralization in vitro. These results have contributed to a deeper knowledge of biomineralization process in osteosarcoma cells and could provide new evidences about a therapeutic strategy acting on the reversibility of tumorigenicity by osteogenic induction.

Comparative constitutional design for divided societies: a model to explain vonstitutional asymmetries

Comparative studies on constitutional design for divided societies indicate that there is no magic formula to the challenges that these societies pose, as lots of factors influence constitutional design. In the literature on asymmetric federalism, the introduction of constitutional asymmetries is considered a flexible instrument of ethnic conflict resolution, as it provides a mixture of the two main theoretical approaches to constitutional design for divided societies (i.e., integration and accommodation). Indeed, constitutional asymmetries are a complex and multifaceted phenomenon, as their degree of intensity can vary across constitutional systems, and there are both legal and extra-legal factors that may explain such differences. This thesis argues that constitutional asymmetries provide a flexible model of constitutional design and aims to explore the legal factors that are most likely to explain the different degrees of constitutional asymmetry in divided multi-tiered systems. To this end, the research adopts a qualitative methodology, i.e., Qualitative Comparative Analysis (QCA), which allows an understanding of whether a condition or combination of conditions (i.e., the legal factors) determine the outcome (i.e., high, medium, low degree of constitutional asymmetry, or constitutional symmetry). The QCA is conducted on 16 divided multi-tiered systems, and for each case, the degree of constitutional asymmetry was analyzed by employing standardized indexes on subnational autonomy, allowing for a more precise measure of constitutional asymmetry than has previously been provided in the literature. Overall, the research confirms the complex nature of constitutional asymmetries, as the degrees of asymmetries vary substantially not only across systems but also within cases among the dimensions of subnational autonomy. The outcome of the Qualitative Comparative Analysis also confirms a path of complex causality since the different degrees of constitutional asymmetry always depend on several legal factors, that combined produce a low, medium, or high degree of constitutional asymmetry or, conversely, constitutional symmetry.

Microenvironment and therapeutic modulation of myelofibrosis in an experimental mouse model.

Primary myelofibrosis(PMF) is the most severe form of Philadelphia-negative myeloproliferative neoplasms(MPNs), characterized by splenomegaly, extramedullary hematopoiesis and bone marrow(BM) fibrosis, with disease progression to leukemia and low survival. The best therapy currently available includes treatment with a JAK inhibitor(Ruxolitinib), which only ameliorates symptoms. Unfortunately, the pathogenesis of the disease is still poorly understood. It has been hypothesized that its progression may be determined by the presence of inflammatory cytokines produced by the bone marrow microenvironment that promote fibrosis. The three aims of this PhD thesis, using the Gata1low mouse model of myelofibrosis, were: 1. Investigate the presence of different cytokines in the bone marrow microenvironment; 2. Test the efficacy of treatment with Reparixin, a CXCR1/2 receptor inhibitor; 3. Test the efficacy of treatment with RB40.34 (P-selectin inhibitor), alone and in combination with Ruxolitinib. In the first study, we demonstrated by immunohistochemistry(IHC) the presence in the BM of Gata1low mice of elevated levels of CXCL1, and its receptors CXCR1/2, and TGF-β1. Particularly, the cells with higher expression of these cytokines were the megakaryocytes. In the second study, we found that treatment with Reparixin in Gata1low mice showed dose-dependent efficacy in reducing bone marrow and splenic fibrosis. Furthermore, by IHC analysis we demonstrated that the treatment induced a decrease in the expression of TGF-β1. In the third study, we found that treatment with RB40.34 in combination with Ruxolitinib normalizes the phenotype of Gata1low mice, reducing fibrosis and the content of TGF-β and CXCL1 in the bone marrow, and restoring the architecture of hematopoiesis in the bone marrow and spleen. In summary, these data provide preclinical evidence that treatment with Reparixin and RB40.34 in combination with Ruxolitinib are effective on reversing the myelofibrotic trait in the Gata1low mouse model and encourage clinical trials to validate these compounds in human patients with PMF.

Pharmacological targeting of P-selectin to halt the progression of myelofibrosis in the Gata1low mouse model

Primary myelofibrosis is a clonal hematopoietic disorder characterized by marked degrees of systemic inflammation. The release of pro-inflammatory factors by clonal hematopoietic cell populations cause the remodeling of a specialized microenvironment, defined niche, in which the hematopoietic stem cells reside. The main source of pro-inflammatory cytokines is represented by malignant megakaryocytes. The bone marrow and spleen from myelofibrosis patients, as well as those from the Gata1low mouse model of the disease, contain increased number of abnormal megakaryocytes. These cells express on their surface high levels of the adhesion receptor P-selectin that, by triggering a pathological megakaryocyte-neutrophil emperipolesis, lead to increased bioavailability of TGF-β1 in the microenvironment and disease progression. Gata1low mice develop with age a phenotype similar to that of patients with myelofibrosis. We previously demonstrated that deletion of the P-selectin gene in Gata1low mice prevented the development of the myelofibrotic phenotype in these mice. In the current study, we tested the hypothesis that pharmacological inhibition of P-selectin may rescue the fibrotic phenotype of Gata1low mice. To test this hypothesis, we have investigated the phenotype expressed by old Gata1low mice treated with the anti-mouse monoclonal antibody against P-selectin RB40.34, alone or in combination with the JAK2 inhibitor Ruxolitinib. The results showed that the combined therapy normalized the phenotype of Gata1low mice with limited toxicity by reducing fibrosis, TGF-β1 and CXCL1 content in the BM and spleen and by restoring hematopoiesis in the bone marrow and the normal architecture of the spleen. In conclusion, pharmacological inhibition of P-selectin was effective in targeting malignant megakaryocytes and the microenvironmental abnormalities that affect the hematopoietic stem cell compartment in this model. These results suggest that P-selectin and JAK1/2 inhibitors in combination may represent a valid therapeutic option for patients with myelofibrosis.

Cancers of unknown primary site (CUPs) as a model of metastatic process.

Cancers of unknown primary site (CUPs) are a rare group of metastatic tumours, with a frequency of 3-5%, with an overall survival of 6-10 month. The identification of tumour primary site is usually reached by a combination of diagnostic investigations and immunohistochemical testing of the tumour tissue. In CUP patients, these investigations are inconclusive. Since international guidelines for treatment are based on primary site indication, CUP treatment requires a blind approach. As a consequence, CUPs are usually empiric treated with poorly effective. In this study, we applied a set of microRNAs using EvaGreen-based Droplet Digital PCR in a retrospective and prospective collection of formalin-fixed paraffin-embedded tissue samples. We assessed miRNA expression of 155 samples including primary tumours (N=94), metastases of known origin (N=10) and metastases of unknown origin (N=50). Then, we applied the shrunken centroids predictive algorithm to obtain the CUP’s site(s)-of-origin. The molecular test was successfully applied to all CUP samples and provided a site-of-origin identification for all samples, potentially within a one-week time frame from sample inclusion. In the second part of the study we derived two CUP cell lines, and corresponding patient-derived xenografts (PDXs). CUP cell lines and PDXs underwent histological, molecular, and genomic characterization confirming the features of the original tumour. Tissues-of-origin prediction was obtained from the tumour microRNA expression profile and confirmed by single cell RNA sequencing. Genomic testing analysis identified FGFR2 amplification in both models. Drug-screening assays were performed to test the activity of FGFR2-targeting drug and the combination treatment with the MEK inhibitor trametinib, which proved to be synergic and exceptionally active, both in vitro and in vivo. In conclusion, our study demonstrated that miRNA expression profiling could be employed as diagnostic test. Then we successfully derived two CUP models from patients, used for therapy tests, bringing personalized therapy closer to CUP patients.

Developing a radiomic based machine learning model to identify patients with resected non-small-cell lung cancer at high risk of relapse

Background There is a wide variation of recurrence risk of Non-small-cell lung cancer (NSCLC) within the same Tumor Node Metastasis (TNM) stage, suggesting that other parameters are involved in determining this probability. Radiomics allows extraction of quantitative information from images that can be used for clinical purposes. The primary objective of this study is to develop a radiomic prognostic model that predicts a 3 year disease free-survival (DFS) of resected Early Stage (ES) NSCLC patients. Material and Methods 56 pre-surgery non contrast Computed Tomography (CT) scans were retrieved from the PACS of our institution and anonymized. Then they were automatically segmented with an open access deep learning pipeline and reviewed by an experienced radiologist to obtain 3D masks of the NSCLC. Images and masks underwent to resampling normalization and discretization. From the masks hundreds Radiomic Features (RF) were extracted using Py-Radiomics. Hence, RF were reduced to select the most representative features. The remaining RF were used in combination with Clinical parameters to build a DFS prediction model using Leave-one-out cross-validation (LOOCV) with Random Forest. Results and Conclusion A poor agreement between the radiologist and the automatic segmentation algorithm (DICE score of 0.37) was found. Therefore, another experienced radiologist manually segmented the lesions and only stable and reproducible RF were kept. 50 RF demonstrated a high correlation with the DFS but only one was confirmed when clinicopathological covariates were added: Busyness a Neighbouring Gray Tone Difference Matrix (HR 9.610). 16 clinical variables (which comprised TNM) were used to build the LOOCV model demonstrating a higher Area Under the Curve (AUC) when RF were included in the analysis (0.67 vs 0.60) but the difference was not statistically significant (p=0,5147).

Vocabulary Transfer and Knowledge Distillation for Language Model Compression

Natural Language Processing (NLP) has seen tremendous improvements over the last few years. Transformer architectures achieved impressive results in almost any NLP task, such as Text Classification, Machine Translation, and Language Generation. As time went by, transformers continued to improve thanks to larger corpora and bigger networks, reaching hundreds of billions of parameters. Training and deploying such large models has become prohibitively expensive, such that only big high tech companies can afford to train those models. Therefore, a lot of research has been dedicated to reducing a model’s size. In this thesis, we investigate the effects of Vocabulary Transfer and Knowledge Distillation for compressing large Language Models. The goal is to combine these two methodologies to further compress models without significant loss of performance. In particular, we designed different combination strategies and conducted a series of experiments on different vertical domains (medical, legal, news) and downstream tasks (Text Classification and Named Entity Recognition). Four different methods involving Vocabulary Transfer (VIPI) with and without a Masked Language Modelling (MLM) step and with and without Knowledge Distillation are compared against a baseline that assigns random vectors to new elements of the vocabulary. Results indicate that VIPI effectively transfers information of the original vocabulary and that MLM is beneficial. It is also noted that both vocabulary transfer and knowledge distillation are orthogonal to one another and may be applied jointly. The application of knowledge distillation first before subsequently applying vocabulary transfer is recommended. Finally, model performance due to vocabulary transfer does not always show a consistent trend as the vocabulary size is reduced. Hence, the choice of vocabulary size should be empirically selected by evaluation on the downstream task similar to hyperparameter tuning.