Archivio della ricerca della Scuola Superiore Sant'Anna
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CloudSim 7G: An Integrated Toolkit for Modeling and Simulation of Future Generation Cloud Computing Environments
Get PDFBackground: Cloud Computing has established itself as an efficient and cost-effective paradigm for the execution of web-based applications, and scientific workloads, that need elasticity and on-demand scalability capabilities. However, the evaluation of novel resource provisioning and management techniques is a major challenge due to the complexity of large-scale data centers. Therefore, Cloud simulators are an essential tool for academic and industrial researchers, to investigate the effectiveness of novel algorithms and mechanisms in large-scale scenarios.
Aim: This paper proposes CloudSim 7G, the seventh generation of CloudSim, which features a re-engineered and generalized internal architecture to facilitate the integration of multiple CloudSim extensions within the same simulated environment.
Methods: As part of the new design, we introduced a set of standardized interfaces to abstract common functionalities and carried out extensive refactoring and refinement of the codebase.
Results: The result is a substantial reduction in lines of code with no loss in functionality, significant improvements in run-time performance and memory efficiency (up to 25∖% less heap memory allocated), as well as increased flexibility, ease-of-use, and extensibility of the framework.
Conclusion: These improvements benefit not only CloudSim developers but also researchers and practitioners using the framework for modeling and simulating next-generation Cloud Computing environments
Field inoculation with a local arbuscular mycorrhizal (AM) fungal consortium promotes sunflower agronomic traits without changing the composition of AM fungi coexisting inside the crop roots
Get PDFImproving reliability and effectiveness of microbial inoculants in crops is a pressing necessity due to recent in- creases in price of synthetic fertilizers and environmental concerns related to their application. Usually, field in- oculation of beneficial microbes, such as arbuscular mycorrhizal fungi (AMF), manipulates abundance and species composition, making it difficult to disentangle their independent effects. In this study, we investigated for the first time the mechanisms behind the agronomic performance of sunflower after field inoculation with a local AM fungal consortium under high and low soil fertility. The abundance of AMF in roots was promoted by inocu- lation more in low than high soil fertility. In both soil conditions, up to 68 % of the AM fungal taxa retrieved in roots were shared between the inoculated and control plants, confirming minor changes in AM fungal commu- nity composition. On the contrary, the structure of AM fungal community was modified by inoculation. Inocula- tion improved grain yield by 16 % in low soil fertility, oil yield up to 36 %, and enhanced grain content of nutri- ents under both soil conditions. The best predictor of agronomic performance of sunflower was percentage of AM fungal root colonization in high soil fertility and percentage of vesicles in low fertility. The structure of AM fun- gal community was not correlated with crop functional parameters under high soil fertility, while under low fer- tility the occurrence of Rhizophagus sp. VTX00105 in roots was the best predictor. Overall, our results demon- strated that local AM fungal inoculants do not affect root AM fungal composition, but increases abundance and modifies the structure of AM fungal community in roots. These modifications are associated with improvements in sunflower grain and oil yield, and in seed nutritional value, especially in low soil fertility. However, the mech- anisms behind the functioning of field inoculum on crop performance were revealed to be context-dependent
The EU Nature Restoration Law (NRL) and the Common Agricultural Policy (CAP): State of the Art and Future Challenges for Italian Water Resources
Get PDFAmong its various targets on restoring natural habitats and ecosystems in the EU, the recently adopted Nature Restoration Law (NRL) introduces ambitious targets for restoring surface water bodies (SWBs) as well. Simultaneously, the Italian CAP Strategic Plan for the implementation of the Common Agricultural Policy 2023–2027 has been designed to enhance sustainable agricultural practices, including water resource management. This paper provides a comparative analysis of the synergies, gaps, and challenges between these two regulatory frameworks, focusing on sustainable water use in Italian agriculture. A two-level comparative matrix methodology is employed to evaluate the alignment between the NRL’s objectives for freshwater ecosystems and the measures taken by the Italian CAP Strategic Plan on water resources. The results highlight key areas of convergence, existing shortcomings, and necessary steps for aligning Italian agricultural policies with the EU’s water restoration goals. The findings offer insights for policymakers, researchers, and stakeholders engaged in water governance, biodiversity conservation, and agricultural sustainability
Diving back two hundred million years: yawn contagion in fish
Get PDFYawning is a widespread and automatic behavior in vertebrates. Yawn contagion, responding with a
yawn to others’ yawns, helps synchronize motor activities, particularly in social animals, promoting
coordination within groups. While primarily observed in social, endothermic species, yawn contagion
remains unconfirmed in ectotherms. We discovered yawn contagion in zebrafish (Danio rerio). Using a
deep learning model to distinguish yawning from breathing, we found that fish not only yawn but also
“catch” yawns from others. The presence of yawn contagion in fish raises important evolutionary
questions, particularly regarding its origin. According to evolutionary biology theories, on one hand, it
could be a shared trait among vertebrates, with the secondary loss of this phenomenon in some taxa.
On the other hand, it may be a result of convergent evolution, emerging independently in different
evolutionary lineages as a response to the need for synchronization of motor actions within social
groups
Implementing the Learning from Excellence approach to support continuous quality improvement in breast cancer care: a mixed-method study across Italian regions
No full textPurpose – The aim of this study is to describe the application of the Learning from Excellence (LfE) approach in supporting a learning-oriented use of performance measures and continuous quality improvement in breast cancer (BC) care.
Design/methodology/approach – Using a mix-method research, the BC pathway is evaluated among 12 Italian regions/autonomous provinces sharing the same Performance Measurement System. The study was conducted in three stages: (1) identification of the best performing geographical areas through quantitative evidence; (2) analysis of the best practices with qualitative methods; (3) professional engagement and quality improvement, and involvement of stakeholders.
Findings – In the quantitative phase, the performances of 50 geographical areas were analyzed, leading to the identification of two best performing areas. After the characterization of the organizational determinants featuring the best performers’ practices, the professionals were involved through on-site workshops, implementing a learning-oriented use of performance measures, benchmarking and team reflexivity on complementing performance measures with experience-based information. The models of the two areas were compared and hypothesis of care improvement were discussed. Feedback, reflexivity, networking and culture reinforcement were enacted among all the network professionals. In the last stage, the results were publicly presented allowing all stakeholders to recognize and appreciate the collaborative effort produced for the care of BC women and, leveraging on the logic of benchmarking, the stakeholders where able to identify generable performance improvements.
Originality/value – This study provides evidence about the potential benefits of implementing LfE as a total quality management practice for care pathways
Unveiling host-seeking behaviour in entomopathogenic nematodes via lab-on-a-chip technology
Get PDFEntomopathogenic nematodes (EPNs) can be employed as biological control agents (BCAs) for many insect pests’ sustainable management. Despite their widespread use, our understanding of EPNs biology, particularly interactions with their hosts, remains limited. Advancing knowledge of EPNs ecology and host interactions is crucial for optimising their efficacy in pest management. This study pioneers an interdisciplinary approach, at the interface of engineering and applied entomology, to investigate the behaviour of the EPN Steinernema carpocapsae. A novel method combining microfluidics, machine learning, and optical flow is presented. A lab-on-a-chip platform was designed to enable accurate investigation of EPN response to stimuli. A convolutional neural network (CNN) identified nematodes and distinguished their responses to host-derived cues achieving 0.94 accuracy and 1.00 precision in detecting stimulus presence at video-level, classifying EPN behaviour within a controlled environment that simulates host conditions. Optical flow analysis revealed differences in motor activity of EPN upon exposure to stimuli, providing new insights into their dynamic responses. Steinernema carpocapsae exhibited more intense activity in presence of host-borne cues (p = 0.0055). Support vector machine (SVM) and multilayer perceptron (MLP) classifiers distinguished stimulus contexts from optical flow features, with an area under the receiver operating characteristic (ROC) curve of 0.71. These results highlight that, although S. carpocapsae is typically considered an ambusher, it may actively engage in host-seeking behaviour, suggesting a shift in our understanding of its search strategies. This methodology significantly enhances the detection and understanding of EPN responses to cues, advancing their potential in precision biocontrol programs for sustainable pest management actions. Science4Impact statement (S4IS): This study develops a novel lab-on-a-chip platform integrating artificial intelligence (AI) for the precise investigation of host-seeking behaviours in the entomopathogenic nematode Steinernema carpocapsae, a biological control agent (BCA) with potential for sustainable pest management. By combining microfluidic design with deep learning, the platform accurately assesses nematode responses to host-derived cues, providing new insights into its foraging adaptability beyond conventional techniques. This research can help researchers and agricultural stakeholders by enhancing understanding of BCA behaviour, optimising pest control applications, and informing evidence-based decisions on sustainable crop protection. The findings also support quality assurance in biological control validation by offering a rigorous framework for evaluating nematode effectiveness under realistic conditions, promoting its broader adoption in integrated pest management strategies
Prefazione, in Amy Allen, “La fine del progresso. Decolonizzare i fondamenti normativi della teoria critica”
No full textEvaluation of a Haptic-Actuated Glove for Remote Human-Robot Interaction (HRI): A Proof of Concept
No full textTraditional teleoperation systems rely primarily on visual feedback, often via virtual reality (VR) head-mounted displays, which may be insufficient in complex or dynamic environments, increasing the risk of collisions. Thus, haptic feedback was investigated to enhance Unmanned Ground Vehicles (UGV) teleoperation by improving obstacle detection. The haptic feedback was provided to the operator using a glove equipped with two motors that gave tactile cues based on obstacle proximity. Thus, the glove applied low torques to the operator’s hand. Therefore, an experiment was conducted on 30 participants to observe the effect of the haptic-actuated glove. So, a dataset was gathered, and different metrics were computed from the data to evaluate participants’ awareness, control precision, and responsiveness. Hence, the results proved the advantages of controlling mobile robots in complex environments for high-precision applications, such as hazardous material handling, exploration, search, and rescue
VERA: A Video Emotion Response Analysis Platform for Research Studies
No full textVERA (Video Emotion Response Analysis) is an advanced software platform designed to use multimedia content. Thanks to an intuitive and modular interface, VERA allows users to observe any video content, manage controlled viewing sessions, and simultaneously record audio, video, and further information by participants.
The software was developed with contributions from Prof. Beatrice Lazzerini and Prof. Cosimo Antonio Prete of the University of Pisa
The organizational dimension in rare and complex diseases care management: an application of RarERN Path© methodology in ataxias, dystonia and phenylketonuria
Get PDFAbstract Background and methods The organization of care profoundly impacts the variability in the quality of care provided to patients and the equity of access to care. The lack of coordination of care, of communication among healthcare providers, healthcare professionals, and patients, and the duplication of services provided to the patients represent some paradigmatic examples of organizational barriers to deliver high-quality patient-centered care and to promote equitable access to healthcare services. Patient care pathways (PCPs) are valuable tools for the (re)design and the (re)definition of the provision of healthcare services to patients. This work represents the first application of the RarERN Path© methodology for the (re)design of Patient Care Pathways (PCPs) to Ataxias, Dystonia, and Phenylketonuria (PKU). The study was conducted with the support of Academic Partners and in collaboration with experts from two of the 24 European Reference Networks for rare diseases (ERN RND and MetabERN). Results The application of some of the phases of RarERN Path© methodology enabled the translation of the good practices already in place in the centers of expertise into a common optimized PCP, one for each of the three diseases, integrating the expertise of some reference centers of excellence with the patients’ perspectives, and principally focusing on the organization of care. Conclusions The PCPs proposed for progressive ataxias, dystonia, and PKU provide insight into the value of specialized centers in diagnosing and managing patients with rare and complex conditions and are the results of a co-designed optimized process integrating the good practices of the centers of excellence and expertise with the perspectives of the patients’ representatives. This integrated approach allowed for the re-design and optimization of the organizational dimensions of the patient’s care pathways