Counterfactual Building and Evaluation via eXplainable Support Vector Data Description

Increasingly in recent times, the mere prediction of a machine learning algorithm is considered insufficient to gain complete control over the event being predicted. A machine learning algorithm should be considered reliable in the way it allows to extract more knowledge and information than just having a prediction at hand. In this perspective, the counterfactual theory plays a central role. By definition, a counterfactual is the smallest variation of the input such that it changes the predicted behaviour. The paper addresses counterfactuals through Support Vector Data Description (SVDD), empowered by explainability and metric for assessing the counterfactual quality. After showing the specific case in which an analytical solution may be found (under Euclidean distance and linear kernel), an optimisation problem is posed for any type of distances and kernels. The vehicle platooning application is the use case considered to demonstrate how the outlined methodology may offer support to safety-critical applications as well as how explanation may shed new light into the control of the system at hand

Privileged burial in the Pava Pieve (Siena, 8th century AD)

During the 6th archaeological excavation campaign performed at the «Pieve di Pava» (San Giovanni d’Asso, Siena, Italy) in the summer of 2009, a stone-lined burial of a high-status single individual (US 2378) was discovered, covered by a monolithic slab and placed in front of the altar. The tomb is about 160 cm long, 40 cm wide and over 70 cm deep. The skeletal remains of a young male (18-20 years), not in anatomical connection, were found on the floor of the tomb. 14C dating revealed a period between 650 and 688 AD. Stable isotope analysis (18O, 13C, 15N) attested that he was a member of the local community, with a diet quite rich in animal proteins. We are in presence of the secondary burial of an eminent personage, perhaps a saint, likely to have been transported to the church in a sack of perishable material, possibly textile, which caused their alignment along a curved line, as clearly demonstrated by the circular delimitation of the bones. The body was probably used for the re-consecration of the church, following the restoration works of the 8th century. The paleopathological study diagnosed a case of acromesomelic dysplasia, a congenital anomaly with disproportionate limbs: short, enlarged distal segments (radius-ulna and tibia), almost normal proximal segments (humerus and femur), short stature of about 150 cm, and bilateral fibular agenesis. Tibiae malformation and fibulae agenesis led to bilateral talipes valgus, with major walking problems. Extensive enthesopathies in the upper limbs indicate the use of crutches

Reference gene selection for gene expression studies using RT-qPCR in virus-infected planthoppers

<p>Abstract</p> <p>Background</p> <p>Planthoppers not only severely affect crops by causing mechanical damage when feeding but are also vectors of several plant virus species. The analysis of gene expression in persistently infected planthoppers might unveil the molecular basis of viral transmission. Quantitative real-time RT-PCR (RT-qPCR) is currently the most accurate and sensitive method used for quantitative gene expression analysis. In order to normalize the resulting quantitative data, reference genes with constant expression during the experimental procedures are needed.</p> <p>Results</p> <p>Partial sequences of the commonly used reference genes actin (ACT), α1-tubulin (TUB), glyceraldehyde 3-phosphate dehydrogenase (GAPDH), elongation factor 1 alpha (EF1A), ribosomal protein S18 (RPS18) and polyubiquitin C (UBI) from <it>Delphacodes kuscheli</it>, a planthopper capable of persistently transmitting the plant fijivirus <it>Mal de Río Cuarto virus </it>(MRCV), were isolated for the first time. Specific RT-qPCR primers were designed and the expression stability of these genes was assayed in MRCV-infective and naïve planthoppers using geNorm, Normfinder and BestKeeper tools. The overall analysis showed that UBI, followed by 18S and ACT, are the most suitable genes as internal controls for quantitative gene expression studies in MRCV-infective planthoppers, while TUB and EF1A are the most variable ones. Moreover, EF1A was upregulated by MRCV infection.</p> <p>Conclusions</p> <p>A RT-qPCR platform for gene expression analysis in the MRCV-infected planthopper vector <it>Delphacodes kuscheli </it>was developed. Our work is the first report on reference gene selection in virus-infected insects, and might serve as a precedent for future gene expression studies on MRCV and other virus-planthopper pathosystems.</p

Status of the Cylindical-GEM project for the KLOE-2 Inner Tracker

The status of the R&D on the Cylindrical-GEM (CGEM) detector foreseen as Inner Tracker for KLOE-2, the upgrade of the KLOE experiment at the DAFNE phi-factory, will be presented. The R&D includes several activities: i) the construction and complete characterization of the full-size CGEM prototype, equipped with 650 microns pitch 1-D longitudinal strips; ii) the study of the 2-D readout with XV patterned strips and operation in magnetic field (up to 1.5T), performed with small planar prototypes in a dedicated test at the H4-SPS beam facility; iii) the characterization of the single-mask GEM technology for the realization of large-area GEM foils.Comment: 4 pages, 10 figures, Presented at Vienna Conference on Instrumentation (Feb 15-20, 2010, Vienna, Austria). Submitted to the Proceeding

Resistive Plate Chambers with Gd-coated electrodes as thermal neutron detectors

Abstract Resistive Plate Chambers (RPCs) are wide spread, cheap, easy-to-build and large size detectors, used mainly to reveal ionising particles in high-energy physics experiments. Here a technique, consisting in coating the inner surface of the bakelite electrodes with a mixture of linseed oil and Gd 2 O 3 is reported. This allows to make RPCs sensitive also to thermal neutrons, making them suitable to be employed for industrial, medical or de-mining applications. Thermal neutron-sensitive RPCs can be operated at atmospheric pressure, are lightweighted, have low γ -ray sensitivity and are easy to handle even when large areas have to be covered. This paper reports the results of the first test of this detector, performed at the Geel Linear Accelerator (GELINA) in Belgium

A Monitoring Framework with Integrated Sensing Technologies for Enhanced Food Safety and Traceability

A novel and low-cost framework for food traceability, composed by commercial and proprietary sensing devices, for the remote monitoring of air, water, soil parameters and herbicide contamination during the farming process, has been developed and verified in real crop environments. It offers an integrated approach to food traceability with embedded systems supervision, approaching the problem to testify the quality of the food product. Moreover, it fills the gap of missing low-cost systems for monitoring cropping environments and pesticides contamination, satisfying the wide interest of regulatory agencies and final customers for a sustainable farming. The novelty of the proposed monitoring framework lies in the realization and the adoption of a fully automated prototype for in situ glyphosate detection. This device consists of a custom-made and automated fluidic system which, leveraging on the Molecularly Imprinted Polymer (MIP) sensing technology, permits to detect unwanted glyphosate contamination. The custom electronic mainboard, called ElectroSense, exhibits both the potentiostatic read-out of the sensor and the fluidic control to accomplish continuous unattended measurements. The complementary monitored parameters from commercial sensing devices are: temperature, relative humidity, atmospheric pressure, volumetric water content, electrical conductivity of the soil, pH of the irrigation water, total Volatile Organic Compounds (VOCs) and equivalent CO (Formula presented.). The framework has been validated during the olive farming activity in an Italian company, proving its efficacy for food traceability. Finally, the system has been adopted in a different crop field where pesticides treatments are practiced. This has been done in order to prove its capability to perform first level detection of pesticide treatments. Good correlation results between chemical sensors signals and pesticides treatments are highlighted

Breath analysis for early detection of malignant pleural mesothelioma: Volatile organic compounds (VOCs) determination and possible biochemical pathways

Malignant pleural mesothelioma (MPM) is a rare neoplasm, mainly caused by asbestos exposure, with a high mortality rate. The management of patients with MPM is controversial due to a long latency period between exposure and diagnosis and because of non-specific symptoms generally appearing at advanced stage of the disease. Breath analysis, aimed at the identification of diagnostic Volatile Organic Compounds (VOCs) pattern in exhaled breath, is believed to improve early detection of MPM. Therefore, in this study, breath samples from 14 MPM patients and 20 healthy controls (HC) were collected and analyzed by Thermal Desorption-Gas Chromatography-Mass Spectrometry (TD-GC/MS). Nonparametric test allowed to identify the most weighting variables to discriminate between MPM and HC breath samples and multivariate statistics were applied. Considering that MPM is an aggressive neoplasm leading to a late diagnosis and thus the recruitment of patients is very difficult, a promising data mining approach was developed and validated in order to discriminate between MPM patients and healthy controls, even if no large population data are available. Three different machine learning algorithms were applied to perform the classification task with a leave-one-out cross-validation approach, leading to remarkable results (Area Under Curve AUC = 93%). Ten VOCs, such as ketones, alkanes and methylate derivates, as well as hydrocarbons, were able to discriminate between MPM patients and healthy controls and for each compound which resulted diagnostic for MPM, the metabolic pathway was studied in order to identify the link between VOC and the neoplasm. Moreover, five breath samples from asymptomatic asbestos-exposed persons (AEx) were exploratively analyzed, processed and tested by the validated statistical method as blinded samples in order to evaluate the performance for the early recognition of patients affected by MPM among asbestos-exposed persons. Good agreement was found between the information obtained by gold-standard diagnostic methods such as computed tomography CT and model output

Infusion mechanisms in brain white matter and its dependence of microstructure: an experimental study of hydraulic permeability

Objective: Hydraulic permeability is a topic of deep interest in biological materials because of its important role in a range of drug delivery-based therapies. The strong dependence of permeability on the geometry and topology of pore structure and the lack of detailed knowledge of these parameters in the case of brain tissue makes the study more challenging. Although theoretical models have been developed for hydraulic permeability, there is limited consensus on the validity of existing experimental evidence to complement these models. In the present study, we measure the permeability of white matter (WM) of fresh ovine brain tissue considering the localised heterogeneities in the medium using an infusion based experimental set up, iPerfusion. We measure the flow across different parts of the WM in response to applied pressures for a sample of specific dimensions and calculate the permeability from directly measured parameters. Furthermore, we directly probe the effect of anisotropy of the tissue on permeability by considering the directionality of tissue on the obtained values. Additionally, we investigate whether WM hydraulic permeability changes with post-mortem time. To our knowledge, this is the first report of experimental measurements of the localised WM permeability, showing the effect of axon directionality on permeability. This work provides a significant contribution to the successful development of intra-tumoural infusion-based technologies, such as convection-enhanced delivery (CED), which are based on the delivery of drugs directly by injection under positive pressure into the brain