Revisiting causality, coalgebraically

In this paper we recast the classical Darondeau–Degano’s causal semantics of concurrency in a coalgebraic setting, where we derive a compact model. Our construction is inspired by the one of Montanari and Pistore yielding causal automata, but we show that it is instance of an existing categorical framework for modeling the semantics of nominal calculi, whose relevance is further demonstrated. The key idea is to represent events as names, and the occurrence of a new event as name generation. We model causal semantics as a coalgebra over a presheaf, along the lines of the Fiore–Turi approach to the semantics of nominal calculi. More specifically, we take a suitable category of finite posets, representing causal relations over events, and we equip it with an endofunctor that allocates new events and relates them to their causes. Presheaves over this category express the relationship between processes and causal relations among the processes’ events. We use the allocation operator to define a category of well-behaved coalgebras: it models the occurrence of a new event along each transition. Then we turn the causal transition relation into a coalgebra in this category, where labels only exhibit maximal events with respect to the source states’ poset, and we show that its bisimilarity is essentially Darondeau–Degano’s strong causal bisimilarity. This coalgebra is still infinite-state, but we exploit the equivalence between coalgebras over a class of presheaves and History Dependent automata to derive a compact representation, where states only retain the poset of the most recent events for each atomic subprocess, and are isomorphic up to order-preserving permutations. Remarkably, this reduction of states is automatically performed along the equivalence

Deep belief network based audio classification for construction sites monitoring

In this paper, we propose a Deep Belief Network (DBN) based approach for the classification of audio signals to improve work activity identification and remote surveillance of construction projects. The aim of the work is to obtain an accurate and flexible tool for consistently executing and managing the unmanned monitoring of construction sites by using distributed acoustic sensors. In this paper, ten classes of multiple construction equipment and tools, frequently and broadly used in construction sites, have been collected and examined to conduct and validate the proposed approach. The input provided to the DBN consists in the concatenation of several statistics evaluated by a set of spectral features, like MFCCs and mel-scaled spectrogram. The proposed architecture, along with the preprocessing and the feature extraction steps, has been described in details while the effectiveness of the proposed idea has been demonstrated by some numerical results, evaluated by using real-world recordings. The final overall accuracy on the test set is up to 98% and is a significantly improved performance compared to other state-of-the-are approaches. A practical and real-time application of the presented method has been also proposed in order to apply the classification scheme to sound data recorded in different environmental scenarios

Randomized comparison of power Doppler ultrasound-directed excisional biopsy with standard excisional biopsy for the characterization of lymphadenopathies in patients with suspected lymphoma.

PURPOSE: The sensitivity of lymph node excisional biopsy requires validation. Power Doppler ultrasound (US) helps predict the malignant status of lymphadenopathies. We used power Doppler US to select for biopsy the lymph node most suspected of malignancy. PATIENTS AND METHODS: One hundred fifty-two patients having lymphadenopathies with clinical suspicion of lymphoma were divided into two well-matched groups and randomly assigned to undergo either standard or power Doppler US-directed lymph node excisional biopsy. RESULTS: Histology showed a malignancy in 64% of patients in the standard group (lymphoma, 49 patients; carcinoma, two patients) and in 87% of patients in the US-assisted group (lymphoma, 62 patients; carcinoma, one patient). There were significantly fewer biopsy-related complications in the assisted group than in the standard group. During the follow-up of the patients with lymph nodes reported as being reactive, 14 of 29 patients in the standard group were rebiopsied and were found to have lymphoma (13 patients) or carcinoma at the subsequent lymph node histology, whereas none of the patients in the assisted group (nine patients) required a second biopsy. Thus, biopsy provided false-negative results for malignancy in 21% of patients affected by lymphoma in the standard group and ever in the assisted group (P <.01). CONCLUSION: Power Doppler US is an accurate tool for screening lymphadenopathies to be removed by excisional biopsy in patients with suspected lymphoma

High number of circulating CD34+ cells in patients with myelophthisis.

Hematopoietic Stem Cells High number of circulating CD34+ cells in patients with myelophthisis Six patients with bone marrow micrometastases from solid cancers presented with increased numbers of circulating CD34+ cells; the CD34+ cell counts were very high in some cases. By contrast, no patient with metastatic cancer without bone marrow involvement showed raised numbers of circulating hemopoietic progenitors. haematologica 2005; 90:976-977 (http:/

A Class of Automata for the Verification of Infinite, Resource-Allocating Behaviours

Process calculi for service-oriented computing often feature generation of fresh resources. So-called nominal automata have been studied both as semantic models for such calculi, and as acceptors of languages of finite words over infinite alphabets. In this paper we investi-gate nominal automata that accept infinite words. These automata are a generalisation of deterministic Muller automata to the setting of nominal sets. We prove decidability of complement, union, intersection, emptiness and equivalence, and determinacy by ultimately periodic words. The key to obtain such results is to use finite representations of the (otherwise infinite-state) defined class of automata. The definition of such operations enables model checking of process calculi featuring infinite behaviours, and resource allocation, to be implemented using classical automata-theoretic methods

Endocrine Disrupting Chemicals and Type 1 Diabetes

Type 1 diabetes (T1D) is the most common chronic metabolic disease in children and adolescents. The etiology of T1D is not fully understood but it seems multifactorial. The genetic background determines the predisposition to develop T1D, while the autoimmune process against -cells seems to be also determined by environmental triggers, such as endocrine disrupting chemicals (EDCs). Environmental EDCs may act throughout dierent temporal windows as single chemical agent or as chemical mixtures. They could aect the development and the function of the immune system or of the beta-cells function, promoting autoimmunity and increasing the susceptibility to autoimmune attack. Human studies evaluating the potential role of exposure to EDCs on the pathogenesis of T1D are few and demonstrated contradictory results. The aim of this narrative review is to summarize experimental and epidemiological studies on the potential role of exposure to EDCs in the development of T1D.We highlight what we know by animals about EDCs\u2019 eects on mechanisms leading to T1D development and progression. Studies evaluating the EDC levels in patients with T1D were also reported. Moreover, we discussed why further studies are needed and how they should be designed to better understand the causal mechanisms and the next prevention interventions

Robust Satellite-Based Identification and Monitoring of Forests Having Undergone Climate-Change-Related Stress

Climate-induced drought events are responsible for forest decline and mortality in different areas of the world. Forest response to drought stress periods may be different, in time and space, depending on vegetation type and local factors. Stress analysis may be carried out by using field methods, but the use of remote sensing may be needed to highlight the effects of climate-change-induced phenomena at a larger spatial and temporal scale. In this context, satellite-based analyses are presented in this work to evaluate the drought effects during the 2000s and the possible climatological forcing over oak forests in Southern Italy. To this aim, two approaches based on the well-known Normalized Difference Vegetation Index (NDVI) were used: one based on NDVI values, averaged over selected decaying and non-decaying forests; another based on the Robust Satellite Techniques (RST). The analysis of the first approach mainly gave us overall information about 1984-2011 rising NDVI trends, despite a general decrease around the 2000s. The second, more refined approach was able to highlight a different drought stress impact over decaying and non-decaying forests. The combined use of the RST-based approach, Landsat satellite data, and Google Earth Engine (GEE) platform allowed us to identify in space domain and monitor over time significant oak forest changes and climate-driven effects (e.g., in 2001) from the local to the Basilicata region scale. By this way, the decaying status of the Gorgoglione forest was highlighted two years before the first visual field evidence (e.g., dryness of apical branches, bark detachment, root rot disease). The RST exportability to different satellite sensors and vegetation types, the availability of suitable satellite data, and the potential of GEE suggest the possibility of long-term monitoring of forest health, from the local to the global scale, to provide useful information to different end-user classes

Unusual onset of a case of chronic recurrent multifocal osteomyelitis

Background: Chronic recurrent multifocal osteomyelitis (CRMO) is a rare condition that commonly affects the clavicle and pelvis. Case presentation: We report here a case a 12 years old girl with CRMO arising with recurrent episodes of left supraorbital headache, followed by the appearance of a periorbital dyschromia. Magnetic resonance imaging (MRI) of the skull and orbits revealed an important subacute inflammatory process. Few months after, the child presented a painful swelling of the left clavicle; the histological examination of the related biopsy allowed to establish the diagnosis of CRMO. Conclusion: CRMO presenting as acute headache involving neurocranium is rare; to our knowledge this is the first recognized case in the world literature. This pathological condition is frequently misdiagnosed as infection or neoplasm and needs a deep investigation for the differential diagnosis. The physical, laboratoristic and instrumental diagnostic investigations of the patient and the treatment employed are described in detail

VoxLogicA : A Spatial Model Checker for Declarative Image Analysis

Spatial and spatio-temporal model checking techniques have a wide range of application domains, among which large scale distributed systems and signal and image analysis.We explore a new domain, namely (semi-)automatic contouring in Medical Imaging, introducing the tool VoxLogicA which merges the state-of-the-art library of computational imaging algorithms ITK with the unique combination of declarative specification and optimised execution provided by spatial logic model checking. The result is a rapid, logic based analysis development methodology. The analysis of an existing benchmark of medical images for segmentation of brain tumours shows that simple VoxLogicA analysis can reach state-of-the-art accuracy, competing with best-in-class algorithms, with the advantage of explainability and easy replicability. Furthermore, due to a two-orders-of-magnitude speedup compared to the existing generalpurpose spatio-temporal model checker topochecker, VoxLogicA enables interactive development of analysis of 3D medical images, which can greatly facilitate the work of professionals in this domain