Dendritic-Cell (DC)-Based Immunotherapy: Tumor Endothelial Marker 8 (TEM8) Gene Expression of DC Vaccines Correlates with Clinical Outcome

ABSTRACT\ud Previous studies have shown that tumor-endothelial markers (TEMs) are upregulated in immunosuppressive, pro-angiogenic dendritic cells (DCs) found in tumor microenvironments. \ud We reported that pro-angiogenic monocyte-derived DCs (Mo-DCs), utilized for therapeutic vaccination of cancer patients upon maturation, markedly differ in their ability to up-regulate tumor-endothelial marker 8 (TEM8) gene\ud expression. A DC vaccination trial of 17 advanced cancer patients (13 melanoma and 4 renal cell carcinoma), carried out at the Cancer Institute of Romagna (I.R.S.T.) in Meldola, highlighted a significant correlation between delayed-type hypersensitivity test (DTH) and overall survival (OS). In the study, relative TEM8 mRNA and protein expression levels (mature (m) vs. immature (i) DCs), in DCs obtained for therapeutic vaccines were evaluated by quantitative real-time RT-PCR and cytofluorimetric analysis, respectively. mDCs from six healthy donors were included for comparison purposes. Eight non-progressing patients, all DTH-positive, had a mean fold increase\ud (mfi) of 1.97 in TEM8 expression. Similarly, a TEM8 mRNA mfi = 2.7 was found in healthy donor mDCs. Conversely, mDCs from nine progressing patients, all but one with negative DTH, had a TEM8 mRNA mfi of 12.88. Thus, mDC TEM8 expression levels would seem to identify (p = 0.0018) patients who could benefit from DC therapeutic vaccination

3D Radiation hydrodynamics of a dynamical torus

We have developed a new dynamical model of the torus region in active galactic nucleus (AGN), using a three-dimensional radiation hydrodynamics algorithm. These new simulations have the specific aim to explore the role of radiatively-driven outflows, which is hotly debated in current literature as a possible explanation for the observed infrared emission from the polar regions of AGN. In this first paper, we only consider radiative effects induced by the primary radiation from the AGN. The simulations generate a disk & outflow structure that qualitatively agrees with observations, although the outflow is radial rather than polar, likely due to the lack of radiation pressure from hot dust. We find cut-offs between the wind and disk at gas temperatures of 1000 K and dust temperatures of 100 K, producing kinematic signatures that can be used for interpretation of high resolution infrared observations. We also produce line emission maps to aid in the interpretation of recent ALMA observations and future JWST observations. We investigate a number of simulation parameters, and find that the anisotropy of the radiation field is equally important to the Eddington factor, despite the anisotropy often being assumed to have a single sometimes arbitrary form in many previous works. We also find that supernovae can have a small but significant impact, but only at extremely high star formation rates.Comment: 2nd revision, Accepted in Ap

Time-Sensitive Bayesian Information Aggregation for Crowdsourcing Systems

Crowdsourcing systems commonly face the problem of aggregating multiple judgments provided by potentially unreliable workers. In addition, several aspects of the design of efficient crowdsourcing processes, such as defining worker's bonuses, fair prices and time limits of the tasks, involve knowledge of the likely duration of the task at hand. Bringing this together, in this work we introduce a new time--sensitive Bayesian aggregation method that simultaneously estimates a task's duration and obtains reliable aggregations of crowdsourced judgments. Our method, called BCCTime, builds on the key insight that the time taken by a worker to perform a task is an important indicator of the likely quality of the produced judgment. To capture this, BCCTime uses latent variables to represent the uncertainty about the workers' completion time, the tasks' duration and the workers' accuracy. To relate the quality of a judgment to the time a worker spends on a task, our model assumes that each task is completed within a latent time window within which all workers with a propensity to genuinely attempt the labelling task (i.e., no spammers) are expected to submit their judgments. In contrast, workers with a lower propensity to valid labeling, such as spammers, bots or lazy labelers, are assumed to perform tasks considerably faster or slower than the time required by normal workers. Specifically, we use efficient message-passing Bayesian inference to learn approximate posterior probabilities of (i) the confusion matrix of each worker, (ii) the propensity to valid labeling of each worker, (iii) the unbiased duration of each task and (iv) the true label of each task. Using two real-world public datasets for entity linking tasks, we show that BCCTime produces up to 11% more accurate classifications and up to 100% more informative estimates of a task's duration compared to state-of-the-art methods

Trust-Based Fusion of Untrustworthy Information in Crowdsourcing Applications

In this paper, we address the problem of fusing untrustworthy reports provided from a crowd of observers, while simultaneously learning the trustworthiness of individuals. To achieve this, we construct a likelihood model of the userss trustworthiness by scaling the uncertainty of its multiple estimates with trustworthiness parameters. We incorporate our trust model into a fusion method that merges estimates based on the trust parameters and we provide an inference algorithm that jointly computes the fused output and the individual trustworthiness of the users based on the maximum likelihood framework. We apply our algorithm to cell tower localisation using real-world data from the OpenSignal project and we show that it outperforms the state-of-the-art methods in both accuracy, by up to 21%, and consistency, by up to 50% of its predictions. Copyright © 2013, International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved

From Manifesta to Krypta: The Relevance of Categories for Trusting Others

In this paper we consider the special abilities needed by agents for assessing trust based on inference and reasoning. We analyze the case in which it is possible to infer trust towards unknown counterparts by reasoning on abstract classes or categories of agents shaped in a concrete application domain. We present a scenario of interacting agents providing a computational model implementing different strategies to assess trust. Assuming a medical domain, categories, including both competencies and dispositions of possible trustees, are exploited to infer trust towards possibly unknown counterparts. The proposed approach for the cognitive assessment of trust relies on agents' abilities to analyze heterogeneous information sources along different dimensions. Trust is inferred based on specific observable properties (Manifesta), namely explicitly readable signals indicating internal features (Krypta) regulating agents' behavior and effectiveness on specific tasks. Simulative experiments evaluate the performance of trusting agents adopting different strategies to delegate tasks to possibly unknown trustees, while experimental results show the relevance of this kind of cognitive ability in the case of open Multi Agent Systems

«All Aram» and «Upper and Lower Aram»: what the Sefire Inscription suggests us about the Aramaean ethnicity

The Aramaeans are always presented as an “undifferentiated group present from the Lower Khabur to the Mount Lebanon” (Sader 1992), without any ethnic affiliation. The construction of their identity may be given by two opposite viewpoints: their own perspective (internal view) and that perceived by other populations (external view). We will show this through the notion of “all Aram” in the Sefire inscription, and by looking at some passages from Assyrian records and the Bible. The first document is the longest Aramaic inscription (about 200 lines) found 25 km from Aleppo in 1930 and dated to the 8th century. It is a treaty stipulated between the unknown king of KTK, Bargaʼ yah and the king of Arpad Matiʻel. The other inscriptions concern, in particular, the records of Shalmaneser III and Tiglath-pileser III who occupied the Aramaean territories in the 9th-8th centuries, and some letters from Nippur

Optical and infrared properties of atomically thin semiconductors

Two-dimensional semiconductors are a topic of intense research and very attractive materials for new developments in different elds of semiconductor technology. These materials are promising candidates to satisfy the demand for faster and more compact electronics. They make new technological possibilities feasible, such as the realization and the commercial development of exible and semitransparent electronics. For these purposes, a deep knowledge of their electronic and optical properties is required. Besides the technological interest, numerous discoveries of fundamental physics were made with many others still to come. Recently for instance, superconductivity has been achieved in twisted bilayer graphene and high-temperature exciton condensation was observed in transition metal dichalcogenide heterostructures 1. The scope of this PhD is to investigate the infrared and optical properties of different two-dimensional semiconductor systems. To this end, various spectroscopic and time-resolved investigations on transition metal dichalcogenide monolayers and few-layer InSe crystals will be presented. First of all, the fabrication of exfoliated samples and van derWaals heterostructures has been successfully carried out and is described in detail. With this knowledge, the exciton physics of MoSe2 monolayer was studied. In particular, the effects of adsorbed gas molecules on the monolayer surface is discussed. It has been demonstrated that these adsorbates can localize excitons at low temperatures and that laser irradiation can release the binding of the physisorbed gas molecules. These results are of fundamental interest for spectroscopic investigations as well as relevant for opto-electronic devices as for instance gas sensors. Thereafter, several experiments were carried out with the use of the infrared free-electron laser FELBE. The general idea was to investigate the response of transition metal dichalcogenide monolayers in the far-infrared frequency range. An effect that was observed is a redshift of the trion induced by non-resonant infrared absorption. In fact, after the absorption of infrared radiation by free carriers, the energy and the momentum of the heated electron gas are transferred to the trion population, leading to a redshift of the trion resonance. By measuring the dynamics of this process, the cooling time of the electron-hole population and the far-infrared absorption of MoSe2 monolayer were extrapolated. The experiments conducted on few-layer InSe will be also presented in this thesis. The effects of hBN-encapsulation on the optical properties of InSe are discussed. The encapsulation in hBN does not only prevent the material from degradation, but also improves the optical quality by reducing the disorder potential in the crystal. Furthermore, the photoluminescence dynamics was investigated as a function of layer thickness and temperature. A bi-exponential decay was observed and the two contributions are attributed to the direct bandgap electron-hole transition and the defect assisted radiative recombination. Because of the direct-to-indirect bandgap crossover driven by the sample thickness, the dynamics gets slower while decreasing the number of layers. In particular, the fast component, i.e. the direct bandgap recombination, tends to disappear for thin InSe samples. Moreover, the photoluminescence lifetime decreases at high temperatures as a consequence of more effcient non-radiative recombination. Finally, heterostructures of MoSe2/WSe2 monolayer were fabricated and the rst spectroscopic results are presented. The interlayer exciton was observed and its dynamics was investigated

Facing Openness with Socio Cognitive Trust and Categories.

Typical solutions for agents assessing trust relies on the circulation of information on the individual level, i.e. reputational images, subjective experiences, statistical analysis, etc. This work presents an alternative approach, inspired to the cognitive heuristics enabling humans to reason at a categorial level. The approach is envisaged as a crucial ability for agents in order to: (1) estimate trustworthiness of unknown trustees based on an ascribed membership to categories; (2) learn a series of emergent relations between trustees observable properties and their effective abilities to fulfill tasks in situated conditions. On such a basis, categorization is provided to recognize signs (Manifesta) through which hidden capabilities (Kripta) can be inferred. Learning is provided to refine reasoning attitudes needed to ascribe tasks to categories. A series of architectures combining categorization abilities, individual experiences and context awareness are evaluated and compared in simulated experiments

The value of traditional rural landscape and nature protected areas in tourism demand: A study on agritourists' preferences

This study focuses on how traditional rural landscape and proximity to a Natura 2000 Site of Community Importance (SCI) might influence consumers\u2019 choice of an agritourism farm for a weekend stay. Data were collected in Umbria region\u2019s (Italy) agritourism farms in 2014 by interviewing 160 tourists. Results from a discrete choice experiment reveal that the most important feature affecting the interviewees\u2019 propensity to pay a premium price to stay in an agritourism farm is the well-preserved traditional landscape (willingness to pay 32.32\u20ac/night for two people), followed by the availability of a swimming pool (willingness to pay 20.95\u20ac/night for two people), the proximity to a historical village (willingness to pay 18.37\u20ac/night for two people) and, the location in a Natura 2000 SCI (willingness to pay 13.57\u20ac/night for two people). Furthermore, the results underline how the preservation of the traditional landscape and protection of the surrounding environment play a strategic role in developing agritourism and provide economic benefits to local communities