A Data-Driven Based Dynamic Rebalancing Methodology for Bike Sharing Systems

Mobility in cities is a fundamental asset and opens several problems in decision making and the creation of new services for citizens. In the last years, transportation sharing systems have been continuously growing. Among these, bike sharing systems became commonly adopted. There exist two different categories of bike sharing systems: station-based systems and free-floating services. In this paper, we concentrate our analyses on station-based systems. Such systems require periodic rebalancing operations to guarantee good quality of service and system usability by moving bicycles from full stations to empty stations. In particular, in this paper, we propose a dynamic bicycle rebalancing methodology based on frequent pattern mining and its implementation. The extracted patterns represent frequent unbalanced situations among nearby stations. They are used to predict upcoming critical statuses and plan the most effective rebalancing operations using an entirely data-driven approach. Experiments performed on real data of the Barcelona bike sharing system show the effectiveness of the proposed approach

Long-Range 3D Self-Attention for MRI Prostate Segmentation

The problem of prostate segmentation from Magnetic Resonance Imaging (MRI) is an intense research area, due to the increased use of MRI in the diagnosis and treatment planning of prostate cancer. The lack of clear boundaries and huge variation of texture and shapes between patients makes the task very challenging, and the 3D nature of the data makes 2D segmentation algorithms suboptimal for the task. With this paper, we propose a novel architecture to fill the gap between the most recent advances in 2D computer vision and 3D semantic segmentation. In particular, the designed model retrieves multi-scale 3D features with dilated convolutions and makes use of a self-attention transformer to gain a global field of view. The proposed Long-Range 3D Self-Attention block allows the convolutional neural network to build significant features by merging together contextual information collected at various scales. Experimental results show that the proposed method improves the state-of-the-art segmentation accuracy on MRI prostate segmentation

Karst of Sicily and its conservation

In Sicily, karst is well developed and exhibits different types of landscapes due to the wide distribution of soluble rocks in different geological and environmental settings. Karst affects both carbonate rocks, outcropping in the northwest and central sectors of the Apennine chain and in the foreland area, and evaporite rocks, mainly gypsum, that characterize the central and the southern parts of the island. The carbonate and gypsum karsts show a great variety of surface landforms, such as karren, dolines, poljes, blind valleys, and fluvio-karst canyons, as well as cave systems. Karst areas in Sicily represent extraordinary environments for the study of solution forms. In addition, they are of great environmental value because they contain a variety of habitats that hold species of biogeographic significance. Unfortunately, karst areas are increasingly threatened by human activity, mainly in the form of grazing and other agricultural practices, wildfires, quarrying, urbanization, building of rural homes, and infrastructure development. The value of karst features has been recognized by the Sicilian Regional Government since 1981 when it enacted laws to create several nature reserves to preserve the peculiar karst landscapes, including caves. At present, the state of conservation of karst areas in Sicily may be considered to be at an acceptable level, yet numerous issues and difficulties need to be overcome for the effective protection and enhancement of karstlands

Geomorphological evolution of western Sicily, Italy

This paper proposes a morphoevolutionary model for western Sicily. Sicily is a chain–foredeep–foreland ­system still being built, with tectonic activity involving uplift which tends to create new relief. To reconstruct the ­morphoevolutionary model, geological, and geomorphological studies were done on the basis of field survey and aerial photographic interpretation. The collected data show large areas characterized by specific geological, geomorphological, and topographical settings with rocks, landforms, and landscapes progressively older from south to north Sicily. The achieved results display: (1) gradual emersion of new areas due to uplift, its interaction with the Quaternary ­glacio-eustatic oscillations of the sea level, and the following production of a flight of stair-steps of uplifted marine ­terraces in southern Sicily, which migrates progressively upward and inwards; in response to the uplift (2) triggering of down-cutting processes that gradually dismantle the oldest terraces; (3) competition between uplift and down-cutting processes, which is responsible for the genesis of river valleys and isolated rounded hills in central Sicily; (4) continuous deepening over time that results in the exhumation of older and more resistant rocks in northern Sicily, where the higher heights of Sicily are realized and the older forms are retained; (5) extensional tectonic event in the northern end of Sicily, that produces the collapse of large blocks drowned in the Tyrrhenian Sea and sealed by coastal-marine deposits during the Calabrian stage; (6) trigger of uplift again in the previously subsiding blocks and its interaction with coastal processes and sea level fluctuations, which produce successions of marine terraces during the Middle–Upper Pleistocene stages

Are zinc-bound metallothionein isoforms (I+II and III) involved in impaired thymulin production and thymic involution during ageing?

BACKGROUND: With advancing age, thymic efficiency shows progressive decline due to thymic involution allowing impaired cell-mediated immunity and the appearance of age-related diseases. The intrinsic cause of thymic involution is still undefined. Chronic inflammation and high glucocorticoids (GCs) may be involved. However, transgenic mice, with increased GC sensitivity and over expression of GC receptors, display delayed age-associated thymic involution. This fact suggests that other substances may affect thymic involution. Among them, both isoforms of metallothioneins (MTs) I+II and III are the major candidates because their increments leads to organ atrophy in constant stress and are induced by IL-6, which increases in ageing. Enhanced MTs in ageing allows constant sequester of zinc ions and no subsequent zinc release leading to low zinc ion bioavailability for thymic efficiency. This sequester is very limited in very old age. Thus, we have investigated the MTmRNA (I+II and III) in the thymus from young, old and very old mice. METHODS: MTmRNA and IL-6mRNA (RT-PCR) in the thymus from different donors were tested. Concomitantly, TECs proliferation, zinc ion bioavailability (ratio total thymulin/active thymulin), thymulin activity and corticosterone were tested from different donors. RESULTS: Both isoforms of MTmRNA and IL-6mRNA increase in old thymus coupled with low zinc ion bioavailability, reduced TECs proliferation, impaired thymulin activity and enhanced plasma corticosterone in comparison with young. Conversely, although the thymus is involuted in very old mice because of no changes in thymus weight in comparison to old mice, reduced MTmRNA, especially MT-I+II isoforms, and low IL6mRNA occur. Concomitantly, good zinc ion bioavailability, maintained TECs proliferation, satisfactory thymulin activity and reduced corticosterone are observed in very old mice. CONCLUSIONS: The concomitant increments by high IL-6 of both MT isoforms in the thymus from old mice may be involved in thymic involution because provoking low zinc ion bioavailability, which is relevant for thymic efficiency. By contrast, the limited increments of MTs by low IL-6 induce good zinc ion bioavailability and satisfactory thymic efficiency in very old mice. Therefore, abnormal increased MTs may provoke complete thymic involution during ageing and the possible appearance of age-related diseases. If their increments are instead limited by low inflammation, healthy ageing and longevity may be reached

ЗАСТОСУВАННЯ В СХЕМАХ ЗБАГАЧЕННЯ ТОНКОПОДРІБНЕНОЇ СИРОВИНИ УДОСКОНАЛЕНОГО МАГНІТНОГО ГІДРОЦИКЛОНУ

Проблема та її зв'язок з науковими і практичними задачами. Необхідна ступінь подрібнення руди перед її переробленням визначається характером вкраплення рудних мінералів, використанням різних методів збагачення сиро-вини, вимогами до якості концентратів, послідовністю технологічних процесів, що застосовуються у схемах переробки корисних копалин. Чим тонше кінцева крупність подрібнення руди, тим менше залишається мінеральних зростків і тим більше вірогідність отримання якісних концентратів

Aplicación guía PMBOK, para fortalecer gestión de cronograma, costos y calidad del proyecto mejoramiento I.E. 80147, Abelardo Gamarra, Distrito Sarín, Huamachuco

La presente tesis ha propuesto la Aplicación de Guía PMBOK, para fortalecer Gestión de Cronograma, Costos y Calidad del Proyecto Mejoramiento I.E. 80147, Abelardo Gamarra, Distrito Sarín - Huamachuco, para el cumplimiento de los plazos otorgados por el cliente en la fase 1 del proyecto Mejoramiento I.E. 80147, Abelardo Gamarra, Distrito Sarín Huamachuco. El método de estudio del presente trabajo de investigación fue deductivo, de enfoque mixto (cuantitativo y cualitativo), no experimental y de diseño transversal. Se realizó la aplicación de los 6 procesos de la gestión del cronograma, de los 4 procesos de la gestión de Costos y de los 3 procesos de la gestión de la calidad y se obtuvieron como resultado: planificar la gestión de cronograma, costos y calidad, por lo que se obtuvo el plan de gestión de cronograma, definir las actividades, se obtuvo la lista de hitos del proyecto; secuenciar las actividades, se obtuvo el diagrama de red del proyecto; estimar la duración, se obtuvo el periodo de trabajo de las actividades; desarrollar el cronograma, se obtuvo el cronograma base, costos base y la calidad base del proyecto, se obtuvo las técnicas para controlar el umbral del proyecto. Finalmente, la investigación brindó resultados positivos ante la propuesta de aplicación de la Guía PMBOK para fortalecer Gestión de Cronograma, Costos y Calidad, utilizando los lineamientos del PMBOK, para la fase 1 del servicio de Mejoramiento culminando el 10 de Mayo del 2022, reduciendo así en 8 días el plazo otorgado por el cliente (teniendo en cuenta la ampliación de 30 días por condiciones climáticas).This thesis has proposed the PMBOK Guide Application, to strengthen Schedule, Cost and Quality Management of the I.E. Improvement Project. 80147, Abelardo Gamarra, Sarin - Huamachuco District, for compliance with the deadlines granted by the client in phase 1 of the Improvement I.E., 80147, Abelardo Gamarra, Sarín Huamachuco District. The study method of this research work was deductive, with a mixed approach (quantitative and qualitative), non-experimental and with a cross-sectional design. The application of the 6 processes of schedule management, of the 4 processes of Cost management and of the 3 processes of quality management was carried out and the following results were obtained: planning the management of schedule, costs and quality , so the schedule management plan was obtained, define the activities, the list of project milestones was obtained; sequencing the activities, the network diagram of the project was obtained; estimate the duration, the work period of the activities was obtained; develop the schedule, the base schedule, base costs and the base quality of the project were obtained, the techniques to control the project threshold were obtained. Finally, the research provided positive results before the proposal for the application of the PMBOK Guide to strengthen Schedule, Cost and Quality Management, using the PMBOK guidelines, for phase 1 of the Improvement service ending on May 10, 2022, reducing thus in 8 days the term granted by the client (taking into account the extension of 30 days due to weather conditions). KEY WORD: Schedule, Cost and Quality Management PMBOK methodology, I.E. Abelardo Gamarra, Sarin, HuamachucoTesi

A Cone Beam Computed Tomography Annotation Tool for Automatic Detection of the Inferior Alveolar Nerve Canal

In recent years, deep learning has been employed in several medical fields, achieving impressive results. Unfortunately, these algorithms require a huge amount of annotated data to ensure the correct learning process. When dealing with medical imaging, collecting and annotating data can be cumbersome and expensive. This is mainly related to the nature of data, often three-dimensional, and to the need for well-trained expert technicians. In maxillofacial imagery, recent works have been focused on the detection of the Inferior Alveolar Nerve (IAN), since its position is of great relevance for avoiding severe injuries during surgery operations such as third molar extraction or implant installation. In this work, we introduce a novel tool for analyzing and labeling the alveolar nerve from Cone Beam Computed Tomography (CBCT) 3D volumes

The color out of space: learning self-supervised representations for Earth Observation imagery

The recent growth in the number of satellite images fosters the development of effective deep-learning techniques for Remote Sensing (RS). However, their full potential is untapped due to the lack of large annotated datasets. Such a problem is usually countered by fine-tuning a feature extractor that is previously trained on the ImageNet dataset. Unfortunately, the domain of natural images differs from the RS one, which hinders the final performance. In this work, we propose to learn meaningful representations from satellite imagery, leveraging its high-dimensionality spectral bands to reconstruct the visible colors. We conduct experiments on land cover classification (BigEarthNet) and West Nile Virus detection, showing that colorization is a solid pretext task for training a feature extractor. Furthermore, we qualitatively observe that guesses based on natural images and colorization rely on different parts of the input. This paves the way to an ensemble model that eventually outperforms both the above-mentioned techniques