This paper develops an agent-based computational model of violent political revolutions in which a subjugated population of citizens and an armed revolutionary organisation attempt to overthrow a ...central authority and its loyal forces. The model replicates several patterns of rebellion consistent with major historical revolutions, and provides an explanation for the multiplicity of outcomes that can arise from an uprising. The relevance of the heterogeneity of scenarios predicted by the model can be understood by considering the recent experience of the Arab Spring involving several rebellions that arose in an apparently similar way, but resulted in completely different political outcomes: the successful revolution in Tunisia, the failed protests in Saudi Arabia and Bahrain, and civil war in Syria and Libya.
This study presents a comparative analysis of three predictive models with an increasing degree of flexibility: hidden dynamic geostatistical models (HDGM), generalised additive mixed models (GAMM), ...and the random forest spatiotemporal kriging models (RFSTK). These models are evaluated for their effectiveness in predicting
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concentrations in Lombardy (North Italy) from 2016 to 2020. Despite differing methodologies, all models demonstrate proficient capture of spatiotemporal patterns within air pollution data with similar out-of-sample performance. Furthermore, the study delves into station-specific analyses, revealing variable model performance contingent on localised conditions. Model interpretation, facilitated by parametric coefficient analysis and partial dependence plots, unveils consistent associations between predictor variables and
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concentrations. Despite nuanced variations in modelling spatiotemporal correlations, all models effectively accounted for the underlying dependence. In summary, this study underscores the efficacy of conventional techniques in modelling correlated spatiotemporal data, concurrently highlighting the complementary potential of Machine Learning and classical statistical approaches.
Niemann-Pick Type C (NPC) is a progressive and life limiting autosomal recessive disorder caused by mutations in either the NPC1 or NPC2 gene. Mutations in these genes are associated with abnormal ...endosomal-lysosomal trafficking, resulting in the accumulation of multiple tissue specific lipids in the lysosomes. The clinical spectrum of NPC disease ranges from a neonatal rapidly progressive fatal disorder to an adult-onset chronic neurodegenerative disease. The age of onset of the first (beyond 3 months of life) neurological symptom may predict the severity of the disease and determines life expectancy.NPC has an estimated incidence of ~ 1: 100,000 and the rarity of the disease translate into misdiagnosis, delayed diagnosis and barriers to good care. For these reasons, we have developed clinical guidelines that define standard of care for NPC patients, foster shared care arrangements between expert centres and family physicians, and empower patients. The information contained in these guidelines was obtained through a systematic review of the literature and the experiences of the authors in their care of patients with NPC. We adopted the Appraisal of Guidelines for Research & Evaluation (AGREE II) system as method of choice for the guideline development process. We made a series of conclusive statements and scored them according to level of evidence, strengths of recommendations and expert opinions. These guidelines can inform care providers, care funders, patients and their carers of best practice of care for patients with NPC. In addition, these guidelines have identified gaps in the knowledge that must be filled by future research. It is anticipated that the implementation of these guidelines will lead to a step change in the quality of care for patients with NPC irrespective of their geographical location.
The air in the Lombardy region, Italy, is one of the most polluted in Europe because of limited air circulation and high emission levels. There is a large scientific consensus that the agricultural ...sector has a significant impact on air quality. To support studies quantifying the role of the agricultural and livestock sectors on the Lombardy air quality, this paper presents a harmonised dataset containing daily values of air quality, weather, emissions, livestock, and land and soil use in the years 2016-2021, for the Lombardy region. The daily scale is obtained by averaging hourly data and interpolating other variables. In fact, the pollutant data come from the European Environmental Agency and the Lombardy Regional Environment Protection Agency, weather and emissions data from the European Copernicus programme, livestock data from the Italian zootechnical registry, and land and soil use data from the CORINE Land Cover project. The resulting dataset is designed to be used as is by those using air quality data for research.
Automatic image captioning has many important applications, such as the depiction of visual contents for visually impaired people or the indexing of images on the internet. Recently, deep ...learning-based image captioning models have been researched extensively. For caption generation, they learn the relation between image features and words included in the captions. However, image features might not be relevant for certain words such as verbs. Therefore, our earlier reported method included the use of motion features along with image features for generating captions including verbs. However, all the motion features were used. Since not all motion features contributed positively to the captioning process, unnecessary motion features decreased the captioning accuracy. As described herein, we use experiments with motion features for thorough analysis of the reasons for the decline in accuracy. We propose a novel, end-to-end trainable method for image caption generation that alleviates the decreased accuracy of caption generation. Our proposed model was evaluated using three datasets: MSR-VTT2016-Image, MSCOCO, and several copyright-free images. Results demonstrate that our proposed method improves caption generation performance.
Self-localization enables a system to navigate and interact with its environment. In this study, we propose a novel sparse semantic self-localization approach for robust and efficient indoor ...localization. “Sparse semantic” refers to the detection of sparsely distributed objects such as doors and windows. We use sparse semantic information to self-localize on a human-readable 2D annotated map in the sensor model. Thus, compared to previous works using point clouds or other dense and large data structures, our work uses a small amount of sparse semantic information, which efficiently reduces uncertainty in real-time localization. Unlike complex 3D constructions, the annotated map required by our method can be easily prepared by marking the approximate centers of the annotated objects on a 2D map. Our approach is robust to the partial obstruction of views and geometrical errors on the map. The localization is performed using low-cost lightweight sensors, an inertial measurement unit and a spherical camera. We conducted experiments to show the feasibility and robustness of our approach.
Introduction: The purpose of this study was to assess the overall survival (OS) and disease-free survival (DFS) of patients who underwent orbital exenteration for periorbital, conjunctival, and ...primary intraorbital carcinomas. Additionally, we assessed the outcomes of anterior retrograde temporalis muscle flap restoration. Methods: For all patients who had orbital exenteration in the previous five years, a non-comparative retrospective assessment of their medical records, histology, and radiographic imaging was carried out. We investigated the relationships between the various qualitative factors using Cramer’s V Kaplan–Meier (KM) analysis. For each of the patient’s categorical factors that were of relevance, estimates of the survival distribution were displayed, and log-rank tests were used to determine whether the survival distributions were equal. Results: This study looks at 19 participants. The sample is made up of 13 men (68%) and 6 women (32%). The degree of relationship (Cramer’s V index) between lymph node metastases (N) and the existence of distant metastases (M) is high, at 64%, and is statistically significant because the p-value is 0.0034 < 0.005. Lymph node metastases had a statistically significant impact on overall survival (p = 0.04 < 0.05). Thirteen of the nineteen patients tested had no palsy (68%). There was no one presenting a CSF leak. Conclusion: Our findings show how crucial it is to identify any lymph node involvement that orbital neoplasms may have. In patients who have received many treatments, sentinel lymph node biopsy (SLNB) may be used to determine the stage and spread of the cancer. To determine whether additional tumor characteristics may be explored, more expertise in the SLNB field for patients with orbital cancer who have received many treatments may be helpful. To prevent additional scarring and to be comparable to previous techniques for facial nerve lesions, the anterior retrograde approach and the transorbital procedure for temporal muscle flap in-setting are both effective methods.
In recent years, the number of pipes that have exceeded their service life has increased. For this reason, earthworm-type robots equipped with cameras have been developed to perform regularly ...inspections of sewer pipes. However, inspection methods have not yet been established. This paper proposes a method for anomaly detection from images in pipes using Generative Adversarial Network (GAN). A model that combines f-AnoGAN and Lightweight GAN is used to detect anomalies by taking the difference between input images and generated images. Since the GANs are only trained with non-defective images, they are able to convert an image containing defects into one without them. Subtraction images is used to estimate the location of anomalies. Experiments were conducted using actual images of cast iron pipes to confirm the effectiveness of the proposed method. It was also validated using sewer-ml, a public dataset.
The DTT tokamak, whose construction is starting in Frascati (Italy), will be equipped with an ECRH system of 16 MW for the first operation phase and with a total of 32 gyrotrons (170 GHz, ≥ 1 MW, 100 ...s), organized in 4 clusters of 8 units each in the final design stage. To transmit this large number of power beams from the gyrotron hall to the torus hall building a Quasi-Optical (QO) approach has been chosen by a multi-beam transmission line (MBTL) similar to the one installed at W7-X Stellarator. This compact solution, mainly composed of mirrors in “square arrangement” shared by 8 different beams, minimizes the mode conversion losses. The single-beam QOTL is used to connect each gyrotron MOU output to a beam-combiner mirror unit and, after the MBTL, from a beam-splitter mirror unit to the exvessel and launchers sections located in the equatorial and upper ports of 4 DTT sectors. A novelty introduced is that the mirrors of the TLs are embodied in a vacuum enclosure, using metal gaskets, to avoid atmospheric absorption losses and microwave leaks. The TL, designed for up to 1.5 MW per single power beam, will have a total optical path length between 84 m and 138 m from the gyrotrons to the launchers. The main straight section will travel along an elevated corridor ~10 m above the ground level. The development of the optical design reflects the constraints due to existing buildings and expected neutron flux during plasma operation. In addition, the power throughput of at least 90% should be achieved.
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