1,721,033 research outputs found
LoRaWAN AI-Powered Digital Twins for Smart Water Distribution Networks
No full textWater Distribution Networks (WDNs) are complex, dynamic systems critical to modern society but increasingly difficult to manage due to urbanization, fluctuating demands, and resource constraints. To address these challenges, Smart Water Distribution Networks (SWDNs) utilize Internet of Things (IoT) devices and protocols like Long Range Wide Area Network
(LoRaWAN) for real-time monitoring and analysis, enabling smarter and more efficient water management. This demo
presents SWIM (Smart Water Interaction & Monitoring), an innovative application designed to modernize SWDNs. SWIM
integrates Digital Twins (DTs), established simulation tools like EPANET, and Machine Learning (ML) to provide predictive
analytics, anomaly detection, and real-time control. By employing neural networks, SWIM achieves high-accuracy hydraulic
predictions with minimal input data. Built on IoTs and Low Power Wide Area Networks (LPWANs), SWIM delivers scalable,
efficient, and user-friendly solutions. It aligns with the principles of Industry 5.0, demonstrating the potential to revolutionize water distribution networks and ensure their sustainability in the face of modern challenges
Atypical antipsychotics: Drop-out as efficacy indicator
No full textIntroduction. The drop-out rate studies can be considered among the most reliable methods to estimate the effectiveness of drugs in everyday clinical practice. Aim. Estimation of effectiveness of the atypical antipsychotics through the study of drop-out rates; examination of the causes of drop-out and response predictors. Material and Method. The data concerning 793 patients who have benefited from the direct distribution of atypical antipsychotics at the Mental Health Department (DSM) of Massa Carrara from the 01/01/2000 to the 31/12/2002. Results. The data of 56 patients in treatment with clozapine, 339 with risperidone, 289 with olanzapine and 109 to you with quetiapine was examined. 40.9% of the patients have interrupted the treatment. The patients treated with quetiapine and clozapine have demonstrated the lowest drop-out rate. In patients treated with olanzapine, quetiapine and risperidone the onset age was lower in the drop-out group. The level of instruction was more elevated in the drop-out group of patients treated with olanzapine and risperidone. The bipolar patients continue the therapy with olanzapine and risperidone for longer, while quetiapine and clozapine result more effective in patients affected by disorders of schizophrenic spectrum. The percentage of ulterior interruptions of therapy for specific side-effects are similar in the four groups. Conclusions. The tallied differences, given the heterogeneity of the sample, the absence of standardized data collection systems, can only be sprones for hypotheses that need confirmation. Anyhow this research, carried out in authentic conditions, outside of the rigid protocols of the randomized clinical research, has supplied new information on profile of effectiveness and tolerability of atypical antipsychotics
Dynamic simulation of an adsorption system for solar air conditioning
No full textCopenhagen, Denmark, September 2008 - paper SOR 05 – M2-0
Interventi di razionalizzazione energetica nei supermercati. Analisi dello stato dell'arte ed esempi di applicazione
No full text
Simulazione dinamica di un impianto di condizionamento dell’aria con macchine refrigeranti ad adsorbimento alimentate ad energia solare
No full textLXIII Congresso nazionale A.T.I., Palermo, Settembre 200
L'OSteosintesi Endomidollare "di minima" come Ausilio della Fissazione Esterna nelle Fratture Diafisarie
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