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Needs for innovation in network: Problematizing the role of policy, producer, and user addressing AMR issue
Full text linkGli antibiotici sono stati e sono tuttora medicinali essenziali per il trattamento delle malattie umane. Sono fondamentali per curare le infezioni tradizionali e le malattie rare. Tuttavia, fin dalla loro scoperta era già noto il problema dell’antibiotico resistenza. L’Antimicrobial Resistance (AMR) è quel fenomeno che avviene quando un battere riesce a sopravvivere in presenza di un antimicrobico, come ad esempio un antibiotico. Il problema è di rilevanza mondiale sia dal lato sanitario, attualmente, infatti l’AMR produce attualmente 1 milione di morti annui, sia dal lato economico, 50 trilioni di dollari annui (spese sanitarie). La causa che maggiormente influenza il fenomeno dell’AMR è l’uso improprio e l’abuso di antibiotico. Quasi il 70% degli antibiotici venduti a livello globale viene utilizzato nel settore della produzione di carne animale. L’introduzione dell’antibiotico nella produzione di carne animale ha radici risalenti all’industrializzazione del secondo dopoguerra. Il suo utilizzo, da essere inizialmente pensato per andare a migliorare la salute degli animali si è presto rilevato essere una risorsa economica, che sembra oramai in molte realtà industriali, endemicamente incorporato. L’Industria della carne italiana, considerata la best in class a livello mondiale per la varietà e la qualità dei suoi prodotti, risulta però essere tra le più colpite dal fenomeno dell’AMR. Altre nazioni, la Svezia in prima linea, sono state pionieristicamente innovative in tal senso, ma non esenti dei grandi sacrifici connessi al cambiamento, che hanno dovuto affrontare per innovare il loro sistema produttivo. Le politiche d’innovazione in atto per contrastare l’AMR a livello globale hanno l’obiettivo di ridurre l’utilizzo degli antibiotici nell’industria alimentare. Tuttavia, tali politiche sembrerebbero voler di imporre il peso economico e i rischi connessi che comporta l’innovazione, esclusivamente a carico dei produttori dell’industria alimentare, mentre i benefici ricadrebbero agli attori del network e alla società intera a lungo termine. L’obiettivo di questo lavoro, basato su una ricerca di carattere empirico, è quello di comprendere e analizzare le componenti chiave del network, le loro interazioni e le loro influenze per comprendere, quali siano i fattori chiave che fungono da driver o, viceversa, rallentino o ostacolino il cambiamento necessario per affrontare il problema dell’Antimicrobial Resistance, o come recentemente, è stata definita, della Pandemia Silenziosa.Antibiotics have been and nowadays are yet essential medicines for human diseases treatment. Antibiotics are vital for treating traditional infections as well as rare diseases. However, since the antibiotic was discovered, was known the related Antibiotic-Resistant issue, commonly called Antimicrobial Resistance (AMR). Antimicrobial Resistance is a phenomenon that occurs when bacteria become able to survive in presence of an antimicrobial, e.g. an antibiotic. The problem is of global relevance on the health side since currently, the AMR produces 1 million deaths per year, as well as on the economic side: 100 trillion dollars per year are the estimated costs in terms of the public health system, loss of productivity and so on. The cause that mainly affects the phenomenon is the misuse and the abuse of antibiotics. 70% of antibiotics sold globally were used on animal-meat food production. The introduction of antibiotics on animal-meat food production has its roots in the industrialisation and mass production era of the second post-war period. The use of antibiotics in the animal-meat food industry was embedded initially, to enhance animal health. Nevertheless, right from the very early stages, it was revealed as an economic resource, that seems endemically embedded in several animal-meat production regimes, so far. The Italian meat industry considered the best in class worldwide for the variety and quality of its products, is however among the most affected by the phenomenon of AMR. Other nations, Sweden at the forefront, have been pioneering in this regard, but not exempt from the great sacrifices associated with change, which they have had to face to innovate their production system. The innovation policies in place to combat AMR globally aim to reduce the use of antibiotics in the food industry. However, such policies would seem to want to impose the economic weight and risks associated with innovation, exclusively on the producers of the food industry, while the benefits would fall to the actors of the network and to the entire society in the long term. The goal of this study, based on empirical research, is to understand and analyse the key components of the network, their interactions and their influences to better understand, what are the key factors that act as drivers or, on the contrary, they slow down or hinder the change needed to deal with AMR issue, or as was recently defined as the Silent Pandemic. Abstract (Italian version) Gli antibiotici sono stati e sono tuttora medicinali essenziali per il trattamento delle malattie umane. Sono fondamentali per curare le infezioni tradizionali e le malattie rare. Tuttavia, fin dalla loro scoperta era già noto il problema dell’antibiotico resistenza. L’Antimicrobial Resistance (AMR) è quel fenomeno che avviene quando un battere riesce a sopravvivere in presenza di un antimicrobico, come ad esempio un antibiotico. Il problema è di rilevanza mondiale sia dal lato sanitario, attualmente, infatti l’AMR produce attualmente 1 milione di morti annui, sia dal lato economico, 50 trilioni di dollari annui (spese sanitarie). La causa che maggiormente influenza il fenomeno dell’AMR è l’uso improprio e l’abuso di antibiotico. Quasi il 70% degli antibiotici venduti a livello globale viene utilizzato nel settore della produzione di carne animale. L’introduzione dell’antibiotico nella produzione di carne animale ha radici risalenti all’industrializzazione del secondo dopoguerra. Il suo utilizzo, da essere inizialmente pensato per andare a migliorare la salute degli animali si è presto rilevato essere una risorsa economica, che sembra oramai in molte realtà industriali, endemicamente incorporato. L’Industria della carne italiana, considerata la best in class a livello mondiale per la varietà e la qualità dei suoi prodotti, risulta però essere tra le più colpite dal fenomeno dell’AMR. Altre nazioni, la Svezia in prima linea, sono state pionieristicamente innovative in tal senso, ma non esenti dei grandi sacrifici connessi al cambiamento, che hanno dovuto affrontare per innovare il loro sistema produttivo. Le politiche d’innovazione in atto per contrastare l’AMR a livello globale hanno l’obiettivo di ridurre l’utilizzo degli antibiotici nell’industria alimentare. Tuttavia, tali politiche sembrerebbero voler di imporre il peso economico e i rischi connessi che comporta l’innovazione, esclusivamente a carico dei produttori dell’industria alimentare, mentre i benefici ricadrebbero agli attori del network e alla società intera a lungo termine. L’obiettivo di questo lavoro, basato su una ricerca di carattere empirico, è quello di comprendere e analizzare le componenti chiave del network, le loro interazioni e le loro influenze per comprendere, quali siano i fattori chiave che fungono da driver o, viceversa, rallentino o ostacolino il cambiamento necessario per affrontare il problema dell’Antimicrobial Resistance, o come recentemente, è stata definita, della Pandemia Silenziosa
Neurofuzzy min-max networks implementation on FPGA
No full textMany industrial applications concerning pattern recognition techniques often demand to develop suited low cost embedded systems in charge of performing complex classification tasks in real time. To this aim it is possible to rely on FPGA for designing effective and low cost solutions. Among neurofuzzy classification models, Min-Max networks constitutes an interesting tool, especially when trained by constructive, robust and automatic algorithms, such as ARC and PARC. In this paper we propose a parallel implementation of a Min-Max classifier on FPGA, designed in order to find the best compromise between model latency and resources needed on the FPGA. We show that by rearranging the equations defining the adopted membership function for the hidden layer neurons, it is possible to substantially reduce the number of logic elements needed, without increasing the model latency, i.e. without any need to lower the classifier working frequency
Best Student Paper Award
No full textMany industrial applications concerning pattern recognition techniques often demand to develop suited low cost embedded systems in charge of performing complex classification tasks in real time. To this aim it is possible to rely on FPGA for designing effective and low cost solutions. Among neurofuzzy classification models, Min-Max networks constitutes an interesting tool, especially when trained by constructive, robust and automatic algorithms, such as ARC and PARC. In this paper we propose a parallel implementation of a Min-Max classifier on FPGA, designed in order to find the best compromise between model latency and resources needed on the FPGA. We show that by rearranging the equations defining the adopted membership function for the hidden layer neurons, it is possible to substantially reduce the number of logic elements needed, without increasing the model latency, i.e. without any need to lower the classifier working frequency
Resistance to change and Antimicrobial resistance. Antibiotics as a value adding resource in animal-based food industry network: experiences from Italy (Marche Region) and Sweden
No full textThe paper was published at the 36th IMP conference in Örebro, Sweden in 2020
FPGA targeted implementation of a neurofuzzy system for real time TCP/IP traffic classification
No full textAs Internet traffic grows rapidly, it is necessary to monitor and control TCP/IP flows in order to ensure the quality of service and to filter out unwanted traffic by automatic, effective and inexpensive technical solutions. To this aim, especially when dealing with Gbit/s links, real time TCP/IP traffic classification can be performed by dedicated high speed processing devices, avoiding computationally expensive deep packet inspection techniques and relying only on packet features independent of payload content. In this paper we propose to employ an FPGA to design a stand-alone device using only information available at network layer, namely packet sizes, directions and inter-arrival times, to perform flow classification according to application layer protocol (such as HTTP, FTP, SSH, POP3, etc.). The classification system is based on neurofuzzy Min-Max networks, trained by Adaptive Resolution procedures (ARC and PARC algorithms). In order to deal with very high speed links and a lar
Graph Coverage: an FPGA-targeted Implementation
No full textClassification systems specifically designed to deal with fully labeled graphs are gaining importance in many application fields. The main computational bottleneck in such systems is the dissimilarity measure between pairs of graphs. In this paper we propose to accelerate in hardware such computations, relying on the Graph Coverage as the core inexact graph matching procedure, targeting the design to FPGA as an inexpensive way to design specific co-processing devices. A comparison in terms of computational time between the proposed system and a software implementation on a standard workstation shows encouraging results. © 2013 IEEE
A novel algorithm for online inexact string matching and its FPGA implementation
Full text linkAmong the basic cognitive skills of the biological brain in humans and other mammals, a fundamental one is the ability to recognize inexact patterns in a sequence of objects or events. Accelerating inexact string matching procedures is of utmost importance when dealing with practical applications where huge amounts of data must be processed in real time, as usual in bioinformatics or cybersecurity. Inexact matching procedures can yield multiple shadow hits, which must be filtered, according to some criterion, to obtain a concise and meaningful list of occurrences. The filtering procedures are often computationally demanding and are performed offline in a post-processing phase. This paper introduces a novel algorithm for online approximate string matching (OASM) able to filter shadow hits on the fly, according to general purpose priority rules that greedily assign priorities to overlapping hits. A field-programmable gate array (FPGA) hardware implementation of OASM is proposed and compared with a serial software version. Even when implemented on entry-level FPGAs, the proposed procedure can reach a high degree of parallelism and superior performance in time compared to the software implementation, while keeping low the usage of logic elements. This makes the developed architecture very competitive in terms of both performance and cost of the overall computing system
Sustainable Customer Relationships Management: A Conceptual Framework for Integrating CRM and Sustainability
No full textThis study explores the intersection of two literature streams within business interactions theory: Customer Relationship Management (CRM) and sustainability. Specifically, this research integrates the strategic, collaborative, analytical, and operational dimensions of CRM with the environmental, social, and economic pillars of sustainability. The proposed conceptual framework identifies twelve sections, revealing how each CRM dimension may contribute to a firm’s sustainability development. The findings emphasise CRM’s potential to enhance social well-being, drive environmentally friendly innovation, and identify sustainable investments for long-term stakeholder relationships. Hence, the research provides a conceptual framework highlighting a novel perspective on CRM by determining its crucial role in supporting a firm’s sustainable development. The current study may be a significant guide for scholars to address future research on the topic and for firms to understand how CRM can improve sustainable development principles in business strategy
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