Multi-Criteria Analysis in Compound Decision Processes. The AHP and the Architectural Competition for the Chamber of Deputies in Rome (Italy)

In 1967, a national architectural competition was released for a preliminary project proposal, aimed at the realization of the new building for the Chamber of Deputies in Rome. The outcomes of that competition were unusual: eighteen projects were declared joint winners, and no winner was consequently selected. With reference to that event, this research aims to examine the usefulness of the evaluation tools that are currently employed and the positive effects that one of these techniques would have had, as support for the identification of the “winner” project, are highlighted. Therefore, an hypothetical examination/adjustment of the decision process of that competition through the Analytic Hierarchy Process (AHP) is developed, analyzing the outputs obtained by the implementations of this technique on the final decision. In addition to confirming the usefulness of the evaluation tools for compound and conflicting decision processes, the results of this experiment led to a further understanding of the socio-cultural dynamics related to the original outcomes of the competition analyzed. View Full-Tex

Parallel selective sampling method for imbalanced and large data classification

We proposed a new algorithm to preprocess huge and imbalanced data.This algorithm, based on distance calculations, reduce both size and imbalance.The selective sampling method was conceived for parallel and distributed computing.It was combined with SVM obtaining optimized classification performances.Synthetic and real data sets were used to evaluate the classifiers performances. Several applications aim to identify rare events from very large data sets. Classification algorithms may present great limitations on large data sets and show a performance degradation due to class imbalance. Many solutions have been presented in literature to deal with the problem of huge amount of data or imbalancing separately. In this paper we assessed the performances of a novel method, Parallel Selective Sampling (PSS), able to select data from the majority class to reduce imbalance in large data sets. PSS was combined with the Support Vector Machine (SVM) classification. PSS-SVM showed excellent performances on synthetic data sets, much better than SVM. Moreover, we showed that on real data sets PSS-SVM classifiers had performances slightly better than those of SVM and RUSBoost classifiers with reduced processing times. In fact, the proposed strategy was conceived and designed for parallel and distributed computing. In conclusion, PSS-SVM is a valuable alternative to SVM and RUSBoost for the problem of classification by huge and imbalanced data, due to its accurate statistical predictions and low computational complexity

Evidence for a quadruplex structure in the polymorphic hs1.2 enhancer of the immunoglobulin heavy chain 3’ regulatory regions and its conservation in mammals

Regulatory regions in the genome can act through a variety of mechanisms that range from the occurrence of histone modifications to the presence of protein-binding loci for self-annealing sequences. The final result is often the induction of a conformational change of the DNA double helix, which alters the accessibility of a region to transcription factors and consequently gene expression. A similar to 300 kb regulatory region on chromosome 14 at the 3' end (3'RR) of immunoglobulin (Ig) heavy-chain genes shows very peculiar features, conserved in mammals, including enhancers and transcription factor binding sites. In primates, the 3'RR is present in two copies, both having a central enhancer named hs1.2. We previously demonstrated the association between different hs1.2 alleles and Ig plasma levels in immunopathology. Here, we present the analysis of a putative G-quadruplex structure (tetraplex) consensus site embedded in a variable number tandem repeat (one to four copies) of hs1.2 that is a distinctive element among the enhancer alleles, and an investigation of its three-dimensional structure using bioinformatics and spectroscopic approaches. We suggest that both the role of the enhancer and the alternative effect of the hs1.2 alleles may be achieved through their peculiar three-dimensional-conformational rearrangement

Development of Lumped Element Kinetic Inductance Detectors for the W-Band

We are developing a Lumped Element Kinetic Inductance Detector (LEKID) array able to operate in the W-band (75-110 GHz) in order to perform ground-based Cosmic Microwave Background (CMB) and mm-wave astronomical observations. The W-band is close to optimal in terms of contamination of the CMB from Galactic synchrotron, free-free, and thermal interstellar dust. In this band, the atmosphere has very good transparency, allowing interesting ground-based observations with large (>30 m) telescopes, achieving high angular resolution (<0.4 arcmin). In this work we describe the startup measurements devoted to the optimization of a W-band camera/spectrometer prototype for large aperture telescopes like the 64 m SRT (Sardinia Radio Telescope). In the process of selecting the best superconducting film for the LEKID, we characterized a 40 nm thick Aluminum 2-pixel array. We measured the minimum frequency able to break CPs (i.e. $h\nu=2\Delta\left(T_{c}\right)=3.5k_{B}T_{c}$) obtaining $\nu=95.5$ GHz, that corresponds to a critical temperature of 1.31 K. This is not suitable to cover the entire W-band. For an 80 nm layer the minimum frequency decreases to 93.2 GHz, which corresponds to a critical temperature of 1.28 K; this value is still suboptimal for W-band operation. Further increase of the Al film thickness results in bad performance of the detector. We have thus considered a Titanium-Aluminum bi-layer (10 nm thick Ti + 25 nm thick Al, already tested in other laboratories), for which we measured a critical temperature of 820 mK and a cut-on frequency of 65 GHz: so this solution allows operation in the entire W-band.Comment: 16th International Workshop on Low Temperature Detectors, Grenoble 20-24 July 2015, Journal of Low Temperature Physics, Accepte

Evolutive emergence and divergence of an Ig regulatory node: An environmental sensor getting cues from the aryl hydrocarbon receptor?

One gene, the immunoglobulin heavy chain (IgH) gene, is responsible for the expression of all the different antibody isotypes. Transcriptional regulation of the IgH gene is complex and involves several regulatory elements including a large element at the 3’ end of the IgH gene locus (3’RR). Animal models have demonstrated an essential role of the 3’RR in the ability of B cells to express high affinity antibodies and to express different antibody classes. Additionally, environmental chemicals such as aryl hydrocarbon receptor (AhR) ligands modulate mouse 3’RR activity that mirrors the effects of these chemicals on antibody production and immunocompetence in mouse models. Although first discovered as a mediator of the toxicity induced by the high affinity ligand 2,3,7,8-tetracholordibenzo-p-dioxin (dioxin), understanding of the AhR has expanded to a physiological role in preserving homeostasis and maintaining immunocompetence. We posit that the AhR also plays a role in human antibody production and that the 3’RR is not only an IgH regulatory node but also an environmental sensor receiving signals through intrinsic and extrinsic pathways, including the AhR. This review will 1) highlight the emerging role of the AhR as a key transducer between environmental signals and altered immune function; 2) examine the current state of knowledge regarding IgH gene regulation and the role of the AhR in modulation of Ig production; 3) describe the evolution of the IgH gene that resulted in species and population differences; and 4) explore the evidence supporting the environmental sensing capacity of the 3’RR and the AhR as a transducer of these cues. This review will also underscore the need for studies focused on human models due to the premise that understanding genetic differences in the human population and the signaling pathways that converge at the 3’RR will provide valuable insight into individual sensitivities to environmental factors and antibody-mediated disease conditions, including emerging infections such as SARS-CoV-2

Lumped element kinetic inductance detectors maturity for space-borne instruments in the range between 80 and 180 GHz

This work intends to give the state-of-the-art of our knowledge of the performance of LEKIDs at millimetre wavelengths (from 80 to 180~GHz). We evaluate their optical sensitivity under typical background conditions and their interaction with ionising particles. Two LEKID arrays, originally designed for ground-based applications and composed of a few hundred pixels each, operate at a central frequency of 100, and 150~GHz ($\Delta \nu / \nu$ about 0.3). Their sensitivities have been characterised in the laboratory using a dedicated closed-circle 100~mK dilution cryostat and a sky simulator, allowing for the reproduction of realistic, space-like observation conditions. The impact of cosmic rays has been evaluated by exposing the LEKID arrays to alpha particles ($^{241}$Am) and X sources ($^{109}$Cd) with a readout sampling frequency similar to the ones used for Planck HFI (about 200~Hz), and also with a high resolution sampling level (up to 2~MHz) in order to better characterise and interpret the observed glitches. In parallel, we have developed an analytical model to rescale the results to what would be observed by such a LEKID array at the second Lagrangian point.Comment: 7 pages, 2 tables, 13 figure

Niobium Silicon alloys for Kinetic Inductance Detectors

We are studying the properties of Niobium Silicon amorphous alloys as a candidate material for the fabrication of highly sensitive Kinetic Inductance Detectors (KID), optimized for very low optical loads. As in the case of other composite materials, the NbSi properties can be changed by varying the relative amounts of its components. Using a NbSi film with T_c around 1 K we have been able to obtain the first NbSi resonators, observe an optical response and acquire a spectrum in the band 50 to 300 GHz. The data taken show that this material has very high kinetic inductance and normal state surface resistivity. These properties are ideal for the development of KID. More measurements are planned to further characterize the NbSi alloy and fully investigate its potential.Comment: Accepted for publication on Journal of Low Temperature Physics. Proceedings of the LTD15 conference (Caltech 2013

Regularized Least Squares Cancer Classifiers from DNA microarray data

BACKGROUND: The advent of the technology of DNA microarrays constitutes an epochal change in the classification and discovery of different types of cancer because the information provided by DNA microarrays allows an approach to the problem of cancer analysis from a quantitative rather than qualitative point of view. Cancer classification requires well founded mathematical methods which are able to predict the status of new specimens with high significance levels starting from a limited number of data. In this paper we assess the performances of Regularized Least Squares (RLS) classifiers, originally proposed in regularization theory, by comparing them with Support Vector Machines (SVM), the state-of-the-art supervised learning technique for cancer classification by DNA microarray data. The performances of both approaches have been also investigated with respect to the number of selected genes and different gene selection strategies. RESULTS: We show that RLS classifiers have performances comparable to those of SVM classifiers as the Leave-One-Out (LOO) error evaluated on three different data sets shows. The main advantage of RLS machines is that for solving a classification problem they use a linear system of order equal to either the number of features or the number of training examples. Moreover, RLS machines allow to get an exact measure of the LOO error with just one training. CONCLUSION: RLS classifiers are a valuable alternative to SVM classifiers for the problem of cancer classification by gene expression data, due to their simplicity and low computational complexity. Moreover, RLS classifiers show generalization ability comparable to the ones of SVM classifiers also in the case the classification of new specimens involves very few gene expression levels

Sensors in the care of persons with visual- or visual-and-intellectual disabilities:Use, needs, practical issues, and ethical concerns

BACKGROUND: Sensor technology may improve the quality of life of persons with visual and/or intellectual disabilities. However, there is no general consensus on its utility and implementation. OBJECTIVE: In this exploratory study the aim was to provide an overview of sensors for persons with disabilities to address priorities and ethical concerns for future research. METHODS: Using a qualitative (Delphi) method, 17 interviews were carried out with 20 representatives in the field of visual- or visual-and-intellectual disabilities (in general: six experts in sensor technology, domotics, and eHealth, specific for persons with a visual or visual-and-intellectual disability: three client representatives; three caregivers; four care team managers; two developmental psychologists; one physician; and one paramedic; age ranges 25-61 years). Atlas.ti software was used to code data and major themes were identified using qualitative analyses. RESULTS: The most used sensors were for surveillance and health and the most desired were for behavior. Different sensors were considered most important for future implementation by the groups of participants, such as sensors for lighting, posture, and entertainment by client experts. Furthermore, the majority of participants agreed that sensors should be easy to use and understand and ethical issues (e.g. privacy, informed consent) should be considered. CONCLUSION: The current applications of sensor technology in clinical practice and future research needs were determined by interviewing experts, caregivers, and client experts