1,217 research outputs found
Stress and Mental Workload Monitoring in Pilots Using a Physiological Signals Approach
No full textL'abstract è presente nell'allegato / the abstract is in the attachmen
The role of neurolytic celiac plexus block in the treatment of pancreatic cancer pain
No full textPancreatic carcinoma, an important leading cause of cancer death, has increased steadily
in incidence and still has a poor prognosis. Pain is one of the most frequent symptoms,
affecting more than 75% of patients. It is often present in the early stages of disease and
may be severe and difficult to treat. Abdominal viscera, including pancreas, liver,
gallbladder, adrenal, kidney, and the gastrointestinal tract from the level of the gastroesophageal
junction to the splenic flexure of the colon are innervated, at least in part, via
the celiac plexus. Thus, painful tumors in these viscera may have pain relieved through the
use of a neurolytic celiac plexus block (NCPB). Although some investigators questioned
the role and the efficacy of NCPB in the treatment of upper abdominal cancer pain, most
of them have suggested that it may represent the optimal treatment, especially for
pancreatic cancer pain. In this report we have reviewed the techniques, results, and
complications of NCPB for the treatment of pancreatic cancer pai
About twin primes and distribution of primes
No full textThis paper give us a demonstration of twin primes conjecture using approximation of function �(iupsilon) that we introduce in section 6. Section 1-5 give us introduction to terminology and a clarification on (iupsilon) terms. In particular section
5 is really important because of its Lemma. Section 7 reassume foregoing explanations and it give us two theorems and one corollary;the theorem 7.2 give us exact approximation of twin primes counting function
Unveiling Mental Workload via PPG: Morphological and Respiratory Feature–Driven Machine Learning Classification
No full textThe integration of the latest artificial intelligence (AI)-based technologies in high-risk operational sectors requires, as an essential prerequisite, the availability of reliable feedback on the mental workload (MWL) perceived by the operator. In this context, the analysis of variations in physiological signals remains one of the most promising and scalable approaches for estimating MWL in varied application scenarios. This study proposes the development of a predictive model solely based on the analysis of the photoplethysmographic (PPG) signal, a technology that is easily integrable into wearable systems and already widely used in clinical and consumer applications. In addition to the traditional variables associated with heart rate variability (HRV), which have been explored in previous literature, this work introduces an innovative analysis of morphological parameters of the individual pulse wave, which have not been previously investigated in the context of MWL. Furthermore, by reconstructing the respiratory contribution from the PPG signal, additional features related to respiratory variability were derived. The machine learning models were trained using the publicly available MAUS dataset, which includes recordings from 22 subjects exposed to controlled cognitive workload conditions through the N-back test. The obtained results, with an accuracy of 81.5% in the binary classification between low and high MWL levels, confirm the effectiveness of the proposed approach and highlight its potential for continuous, non-invasive monitoring of mental workload through a single wearable sensor
SUPTraining project: development of an e-learning platform for the sustainable use of pesticides
No full textTodesignandvalidate,incollaborationwithotherEuropeanexpertsandtwocertification organisations, a new e-learning platform to train professional users, advisors and distributors to the use of PPPs for their sustainable use in a multi-institutional EU research project funded under Erasmus+ framework
• develop an useful tool to get prepared for relative national certificate test
• build a common basis for any European stakeholders willing to start the process of trans-
ferring the SUPTraining outputs to another contex
An Efficient Artificial Intelligence Energy Management System for Urban Building Integrating Photovoltaic and Storage
No full textThe emerging leading role of green energy in our society pushes the investigation of new economic and technological solutions. Green energies and smart communities increase efficiency with the use of digital solutions for the benefits of inhabitants and companies. The paper focuses on the development of a methodology for the energy management, combining photovoltaics and storage systems, considering as the main case study a multi-story building characterized by a high density of households, used to generate data which allow feasibility foresights. The physical model of the algorithm is composed by two main elements: the photovoltaics modules and the battery energy storage system. In addition, to gain information about the real-time consumption a machine learning module is included in our approach to generate predictions about the near future demand. The benefits provided by the method are evaluated with an economic analysis, which computes the return of the investment using the real consumptions of a Boarding School, located in Turin (Italy). The case study analyzed in this article showed an increase in purchased energy at the minimum price from 25% to 91% and a 55% reduction in the electricity bill compared to most solutions on the market, with no additional costs and a stabilizing effect on the grid. Finally, the economic analysis shows that the proposed method is a profitable investment, with a breakeven point of thirteen years, due to the very simple implementation and the zero additional cost requested
Software-based solutions for the optimization of a building electric bill using integrated PV and storage systems: a case study
No full textGreen energies are establishing themselves as a training sector in the last decade, enabling economic and technological opportunities still to be investigated. This article proposes a solution for energy management, merging photovoltaics and storage systems, focusing on the city urban environment and taking as the main case study the typical multi-storey building characterized by high density of households. The proposed solution optimizes the cost of the electrical bill using a predictive algorithm, stem from an economical analysis based on the production and consumption of the system
Preliminary study of a pilot performance monitoring system based on physiological signals
No full textThe rising operating costs and the decreasing availability of pilots push the aviation market towards
Single Pilot Operations. Due to the related need for a cockpit assistant able to understand pilots’ cognitive
workload and stress and the lack of robust solutions, the relationship of these conditions with variations in
physiological parameters is being studied. In this paper, initial computer cognitive tests were performed on
thirty healthy volunteers, providing the physiological parameters of PPG, EDA, and temperature under four
mental workloads and stress conditions. A statistical approach was performed to identify these cognitive
states’ 16 out of 43 most representative characteristics
Residents perceptions of non-dietary pesticide exposure risk. Knowledge gaps and challenges for targeted awareness-raising material in Italy
No full textCurrently there arc no tools to accurately estimate pesticides exposure risk for residents and bystanders. European Member States have to develop specific measures and communication strategies to prevent and minimize non-occupational pesticides exposure. Moreover, these measures should be compliant with the requirements of the Directive on Sustainable Use of Pesticides. Unfortunately, there is a high degree of uncertainties in the assessment of the non-dietary exposure risk for residents, therefore risk communication passes through a deep understanding of exposure risk perception.The objective of this pilot study is to assess citizens' risk perception of non-dietary exposure to pesticides, and to assist policy-makers and risk communicators in developing targeted awareness-raising materials for residents and bystanders.Through a household survey, conducted in the rural area of the province of Piacenza (IT) we investigated knowledge, health risk perceptions, and information sources related to non-dietary exposure to agricultural pesticides in residents' indoor and outdoor environment. The factors that push individuals to give importance to several possible pollution sources and to mitigation measures or precaution, in order to protect themselves from possible exposure sources, were also investigated.Results show that even if the air quality of the residential area is not judged negatively, pesticides are perceived as air pollutants that could lead to an actual exposure and, are correlated to the health status. The perception of risk, however, does not seem to be dependent only on the distance between homes and fields. The interpretative hypothesis that the perception of the relationship between air quality and health is influenced by the cultural issue and by psycho-sensory factors and not supported by proper information, even if with some differences among age groups, it seems to be confirmed. To better transfer knowledge and communication, the commitment of those who are recognised as "competent" (doctors and researchers) is critical. (C) 2019 Elsevier B.V. All rights reserved
Established and Outsiders at the Same Time - Self-Images and We-Images of Palestinians in the West Bank and in Israel
No full textPalestinians frequently present a harmonizing and homogenizing we-image of their own national we-group, as a way of counteracting Israeli attempts to sow divisions among them, whether through Israeli politics or through the dominant public discourse in Israel. However, a closer look reveals the fragility of this homogenizing we-image which masks a variety of internal tensions and conflicts. By applying methods and concepts from biographical research and figurational sociology, the articles in this volume offer an analysis of the Middle East conflict that goes beyond the polar opposition between “Israelis” and “Palestinians”. On the basis of case studies from five urban regions in Palestine and Israel (Bethlehem, Ramallah, East Jerusalem, Haifa and Jaffa), the authors explore the importance of belonging, collective self-images and different forms of social differentiation within Palestinian communities. For each region this is bound up with an analysis of the relevant social and socio-political contexts, and family and life histories. The analysis of (locally) different figurations means focusing on the perspective of Palestinians as members of different religious, socio-economic, political or generational groupings and local group constellations – for instance between Christians and Muslims or between long-time residents and refugees. The following scholars have contributed to this volume: Ahmed Albaba, Johannes Becker, Hendrik Hinrichsen, Gabriele Rosenthal, Nicole Witte, Arne Worm and Rixta Wundrak. Gabriele Rosenthal is a sociologist and professor of Qualitative Methodology at the Center of Methods in Social Sciences, University of Göttingen. Her major research focus is the intergenerational impact of collective and familial history on biographical structures and actional patterns of individuals and family systems. Her current research deals with ethnicity, ethno-political conflicts and the social construction of borders. She is the author and editor of numerous books, including The Holocaust in Three Generations (2009), Interpretative Sozialforschung (2011) and, together with Artur Bogner, Ethnicity, Belonging and Biography (2009)
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