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Presentazione del1° marzo 2023, ore 11:00nell’ambito del nuovo ciclo di seminari CNR-IRCrES:https://blog.ircres.cnr.it/?p=4941&nbsp

This case study focuses on the online training activities on Open Science delivered within the H2020 project Transforming Research through Innovative Practices for Linked Interdisciplinary Exploration (TRIPLE, Grant Agreement 863420). The project is dedicated to building a discovery platform for the Social Sciences and Humanities (SSH) and is committed to promoting and supporting the uptake of Open Science within research practices. In order to address SSH research and training communities’ needs for enhanced competencies on Open Science and for stronger support in the Findable, Accessible, Interoperable, Reusable (FAIR) management of digital training materials, two reusable outputs were produced. The work carried out is presented as a novel approach to tackle the issues related to FAIRifying research and training practices and to create training resources whose reusability and relevance reaches beyond the project lifetime and framework. The case study presents the methods by which the results were produced so as to encourage and enable their future adaptation and reuse. The TRIPLE Open Science training series (result 1) targets SSH researchers, research support personnel and infrastructure developers in need of practical tools and specific skills to integrate Open Science practices in their workflows. The training series provides 12 competence-oriented online training events in Open Access whose training materials are available as Open Educational Resources (OER). The TRIPLE Training Toolkit (result 2) targets training organisers and research performing organisations who wish to design and manage training events as OERs and increase the impact of their training following good practice. The Toolkit is an easily reproducible workflow designed to help trainers minimise the time they spend in managing training events following FAIR practice. The workflow follows a FAIR-by-design method to address the frequent findability and reusability issues related to the management of digital training resources.

Questo articolo è stato pubblicato sul Bollettino telematico di filosofia politica, dicembre 2006 ,http://bfp.sp.unipi.it/dida/streit/

Background. Sorafenib and other tyrosine kinase inhibitors are the current standard of care for hepatocellular carcinoma (HCC) recurring after liver transplantation (LT). Sorafenib is sometimes regarded as a scarcely effective treatment in this setting because of some studies showing a short overall survival (OS) indirectly compared with historical series of nontransplanted patients. Additional data from multicenter prospective studies are needed before drawing definite conclusions. Methods. Retrospective analyses of a large prospective multicenter dataset of sorafenib-treated HCC patients to report the characteristics and outcomes of LT recipients (n = 81). Results. At the baseline, LT patients had key prognostic features (high prevalence of metastatic disease, and low prevalence of macrovascular invasion, α-fetoprotein >400 ng/mL, ALBI grade >1, performance status >0) that differentiated them from the typical populations of non-LT patient reported in clinical trials and observational studies. Moreover, a relevant proportion of LT patients received concurrent locoregional (12.3%) and postprogression systemic treatments (34.2%), resulting in a median OS of 18.7 mo. Conclusions. Multimodal and sequential treatments are relatively frequent in post-LT HCC patients and contribute to a remarkable OS, together with favorable baseline characteristics. Despite the impossibility of matching with non-LT patients, our results indirectly suggest that the metastatic nature of post-LT recurrence and concurrent antirejection regimens should not discourage systemic treatments.

L’Agreement on Reforming Research Assessment è stato pubblicato il 20 luglio 2022, al termine di un processo avviato dalla Commissione europea all’inizio del 2021. L’articolo espone gli elementi fondamentali dell’accordo, ricostruisce la genesi e le tappe del processo e presenta il contesto culturale e politico in cui si è definito. Inoltre, vengono proposti alcuni primi elementi per la definizione di roadmap e piani d'azione necessari a tradurre i principi e gli impegni dell’accordo in una serie di criteri e indicatori per la valutazione di istituzioni, di progetti di ricerca e di singoli ricercatori. In conclusione sono presentate alcune riflessioni sulle sfide da affrontare e sulle opportunità che la riforma della valutazione offre.

The contribution aims at presenting the main elements of the European Initiative on Reforming Research Assessment, and its connections with, and implications for the adoption of Open Science practices. Gli Enti pubblici di ricerca per la Scienza Aperta - Primo convegno nazionale del gruppo di lavoro Open Science della CoPER Aula Marconi - Consiglio Nazionale delle Ricerche, Roma, 6-7 dicembre 2022 https://agenda.infn.it/e/ConvegnoOpenscienceCoPER2022 Organizzazione del convegno Giovanni De Simone (CNR),Stefano Bianco (INFN),Anna Grazia Chiodetti (INGV),Mario Locati (INGV) Organizzazione delle sessioni Emanuela Secinaro (INRIM),Roberta Maggi (CNR),Silvia Giannini (CNR),Susanna Terracini (INDAM), Francesco Lazzarini (ISPRA), PasqualeLubrano (INFN), Francesca Di Donato (CNR),Roberto Caso (UniTN),Angela Saraò (OGS),Alessandra Giorgetti (OGS),RobertaVigni(ISPRA),Antonella Gasperini (INAF) Segreteria Rita Ciampichetti, Valentina Desantis e Sara Santorsa (CNR) - Irene Piergentili, Lia Sabatini (INFN LNF) &nbsp

Al termine di un processo di consultazione avviato dalla Commissione europea all’inizio del 2021 e di una intensa fase di discussione e di redazione e che ha coinvolto oltre 350 istituzioni di tutta Europa, ERAC e ERA Forum, 20 luglio 2022 è stato pubblicato l’Agreement on reforming research assessment. L’accordo sarà/è stato aperto alla sottoscrizione di Università ed Enti di ricerca, di Agenzie dal 28 settembre e porterà alla costituzione di una Coalizione per la riforma del sistema di valutazione. Questa presentazione racconta la genesi del documento, e ne illustra il contenuto e lo scopo. Sessione della GenOA week 2022 dedicata alla Valutazione della ricerca. Il programma è disponibile qui:https://openscience.unige.it/genOAweek2022/agenda &nbsp

Seminario OA week 2022 - 27 e 28 ottobre 2022 sessione 28 ottobre 2022: Prospettive per una nuova valutazione della ricerca scientifica 10.00 saluti istituzionali e introduzione a cura del Gruppo OA UPO 10.15 L’Open Science nelle procedure di valutazione dell’ANVUR - Menico Rizzi (UPO, componente del Direttivo ANVUR) 10.45 La riforma della valutazione della ricerca in Europa - Francesca Di Donato (Istituto di Linguistica Computazionale "Antonio Zampolli" (ILC) - CNR di Pisa) 11.15 discussione e conclusioni Il seminario è visibile sul canale YouTube al link: https://www.youtube.com/channel/UCP5O3gVErOX3CH7yt12MUug, {"references":["Agreement on Reforming Research Assessment, https://ec.europa.eu/info/files/agreement-reforming-research-assessment_en"]}

Presentazione per la riunione di ConPER dell'8 giugno 2022. &nbsp

Gas chromatography with mass spectrometry detection (GC-MS) coupled with headspace-solid-phase microextraction (HS-SPME) was used to analyse the aroma profile of genuine saffron (Crocus sativus L.) and samples of this spice artificially adulterated with Calendula officinalis L. petals (calendula), Carthamus tinctorius L. petals (safflower) and Curcuma longa L. powdered rhizomes (turmeric). Preliminary analyses of genuine saffron and pure contaminants were performed to select the kind of SPME sorbent. Moreover, an experimental design combined with response surface methodology was applied to optimise the sample temperature and the fibre exposure time with the aim of enhancing the detection of the above adulterants in counterfeited saffron samples. The GC-MS chromatograms collected under the optimised conditions were finally handled by unsupervised and supervised multivariate statistical methods to differentiate the genuine saffron samples produced in three different Italian regions from artificially adulterated samples at 2–5% w/w contamination levels. Thirty genuine and 30 counterfeited (10 for each kind of adulterant) saffron samples were analysed. Principal component analysis was applied to assist the choice of the GC/MS data pre-treatment and classification of genuine and adulterated saffron samples was attempted by partial least square-discriminant analysis (PLS-DA). Predictive performance of PLS-DA models calibrated with 42 samples was finally tested on 18 saffron samples (9 genuine and 9 adulterated). All the external saffron samples were correctly classified regardless of the kind of contaminant, while in calibration, only a saffron sample contaminated with safflower was erroneously assigned to the group of genuine ones. Class modelling of genuine saffron performed by SIMCA (Soft Independent Model Class Analogy) exhibited a good sensitivity and 100% specificity for external adulterated samples.

When building classification models of complex systems with many classes, the traditional chemometric approaches such as discriminant analysis or soft independent modeling of class analogy often fail. Some people resort to advanced deep neural network, but this is only an option if there is access to very many samples. Another alternative often used is to build hierarchical models where subclasses are sort of peeled off one or a few at a time. Such approaches often outperform classical classification as well as deep neural network on small multi-class problems. The downside though is that it is very cumbersome to build such hierarchies of models. It requires substantial work of a skilled person. In this paper, we develop a fully automated approach for building hierarchical models and test the performance on a number of classification problems.

The development of an enantioselective enamine-catalysed addition of masked acetaldehyde to nitroalkenes via a rational approach helped to move away from the use of chloroform. The presented research allows the use of water as a reaction medium, therefore improving the industrial relevance of a protocol to access very important pharmaceutical intermediates. Critical to the success is the use of chemometrics-assisted 'Design of Experiments' (DoE) optimisation during the development of the presented new synthetic approach, which allows to investigate the chemical space in a rational way.

The multi-elemental composition of three typical Italian Pecorino cheeses, Protected Designation of Origin (PDO) Pecorino Romano (PR), PDO Pecorino Sardo (PS) and Pecorino di Farindola (PF), was determined by Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES). The ICP-OES method here developed allowed the accurate and precise determination of eight major elements (Ba, Ca, Fe, K, Mg, Na, P, and Zn). The ICP-OES data acquired from 17 PR, 20 PS, and 16 PF samples were processed by unsupervised (Principal Component Analysis, PCA) and supervised (Partial Least Square-Discriminant Analysis, PLS-DA) multivariate methods. PCA revealed a relatively high variability of the multi-elemental composition within the samples of a given variety, and a fairly good separation of the Pecorino cheeses according to the geographical origin. Concerning the supervised classification, PLS-DA has allowed obtaining excellent results, both in calibration (in cross-validation) and in validation (on the external test set). In fact, the model led to a cross-validated total accuracy of 93.3% and a predictive accuracy of 91.3%, corresponding to 2 (over 23) misclassified test samples, indicating the adequacy of the model in discriminating Pecorino cheese in accordance with its origin.

We investigate the case of Small-Medium Enterprises (SMEs) in Italy trying to understand if key performance indicators obtained from the financial statement are able to predict possible distress in a company with enough time to take some corrective actions. In order to test the hypotheses, a nonparametric supervised classification algorithm has been applied to a random sample of 100 non-listed SMEs, considering 50 companies that filed for bankruptcy during the period 2000-2011 and 50 companies still active on the market at the end of 2011. Results describe the Italian picture for SMEs during an economic crisis period. They show that, for the Italian case, it is possible to predict with enough time (4-5 years prior to failure) a distress situation in a firm through classification methods. Anyway, these methods are not predicting the health of a company but the possibility of the firm to access the credit system. The results are limited to the Italian SMEs context which is quite particular if compared with other countries in Europe. The dataset is limited in size but has been chosen to be representative of non-listed Italian companies.

International audience; In the food industry, thermal treatments are generally an essential step to increase the shelf life of the products. This is especially true for milk and dairy products in which heat treatments help to eliminate pathogenic organisms, minimize microbiological development, and improve some sensory properties. However, they can also induce biochemical, physico-chemical, and sensory changes in foods, and then adversely affect the final quality of the products. To assess the quality of milk and dairy products during heating, some non-destructive techniques exist. In this article, the application of spectroscopic non-destructive techniques (fluorescence, infrared, NMR) is analyzed to point out the pertinence by using them as tools to monitor milk and dairy product quality changes during heating. An overview of the last studies on the effect of different conventional and emerging methods of milk and dairy product heating on biochemical, physico-chemical, and sensory quality is also presented, as well as the perspectives of research in this topic.

The authors would like to add the following reference to the “Reference” section of their paper [...]

Bell pepper is the common name of the berry obtained from some varieties of the Capsicum annuum species. This agro-food is appreciated all over the world and represents one of the key ingredients of several traditional dishes. It is used as a fresh product, or dried and ground as a seasoning (e.g., paprika). Specific varieties of sweet pepper present organoleptic peculiarities and they have been awarded by quality marks as a further confirmation of their unicity (e.g., Piment d’Espelette, Pimiento de Herbón, Peperone di Senise). Due to the market value of this aliment, it can be subjected to frauds, such as adulterations and sophistication. The present study lays on these considerations and aims at developing a spectroscopy-based approach for authenticating Senise bell pepper and for detecting its adulteration with common paprika. In order to achieve this goal, 60 pure samples of bell pepper from Senise were analyzed by mid- and near-infrared spectroscopies. Then, in order to mimic the adulteration, 40 mixtures of Senise bell pepper and paprika were prepared and analyzed (by the same spectroscopic techniques). Eventually, two different multi-block classification approaches (sequential and orthogonalized partial least squares linear discriminant analysis and sequential and orthogonalized covariance selection linear discriminant analysis) were used to discriminate between pure and adulterated Senise bell pepper samples. Both proposed procedures achieved extremely successful results in external validation, correctly classifying all the (thirty-five) test samples, indicating that both approaches represent a winning solution for the investigated classification problem.

The volatiles of three typical Italian Pecorino cheeses were analysed by headspace solid-phase microextraction (HS-SPME) coupled with gas-chromatography with mass spectrometry detection (GC–MS) evaluating its potentiality to discriminate Protected Designation of Origin (PDO) Pecorino Romano (PR), PDO Pecorino Sardo (PS) and Pecorino di Farindola (PF). A Design of Experiments (DOE) was employed to optimize the extraction conditions in terms of sample temperature and exposure time in the HS-SPME/GC–MS procedure. Linear Discriminant Analysis (LDA) and Partial Least Squares-Discriminant Analysis (PLS-DA) were applied to the volatile composition data to classify samples. Both methods showed high calibration accuracy (100% of non-error rate in cross-validation) and good predictions (87.5% of correct classification, on the external validation set) providing a powerful tool for discriminating Pecorino cheeses, despite their production occurs in different production cycles, in nearby geographical areas and, in the case of PS/PR origins, the raw materials come from common sources.

Publisher's version (útgefin grein), In this review, we summarize the most recent advances in monitoring changes induced in fish and other seafood, and meat and meat products, following the application of traditional processing processes by means of conventional and emerging advanced techniques. Selected examples from the literature covering relevant applications of spectroscopic methods (i.e., visible and near infrared (VIS/NIR), mid-infrared (MIR), Raman, nuclear magnetic resonance (NMR), and fluorescence) will be used to illustrate the topics covered in this review. Although a general reluctance toward using and adopting new technologies in traditional production sectors causes a relatively low interest in spectroscopic techniques, the recently published studies have pointed out that these techniques could be a powerful tool for the non-destructive monitoring and process optimization during the production of muscle food products., This research received no external funding.

Development of local plant genetic resources grown in specific territories requires approaches that are able to discriminate between local and alien germplasm. In this work, three potato (Solanum tuberosum L.) local accessions grown in the area of Majella National Park (Abruzzo, Italy) and five commercial varieties cultivated in the same area were characterized using 22 morphological descriptors and microsatellite (SSR) DNA markers. Analysis of the DNA and of the plant, leaf, flower, and tuber morpho-agronomic traits allowed for a reliable discrimination of the local potato accessions, and provided a clear picture of their genetic relationships with the commercial varieties. Moreover, infrared spectroscopy was used to acquire a fingerprint of the tuber flesh composition. A total of 279 spectra, 70% of which were used in calibration and the remaining 30% for prediction, were processed using partial least squares discriminant analysis. About 97% of the calibration samples and 80% of the prediction samples were correctly classified according to the potato origin. In summary, the combination of the three approaches were useful in the characterization and valorization of local germplasm. In particular, the molecular markers suggest that the potato accession named Montenerodomo, cultivated in Majella National Park, can be considered a local variety and can be registered into the Regional Voluntary GR Register and entered into the foreseen protection scheme, as reported by the Italian regional laws.

Mountain karst ponds are sensitive environments, hosting complex trophic networks where amphibians play a major role, often as top predators. The diet of the Italian crested newt (Triturus carnifex) is still poorly known for populations occupying mountain karst ponds. These are traditionally used as livestock&rsquo, s watering points, leading to water pollution due to excreta and wading behavior. The aim of this paper is to understand the relationship between T. carnifex diet composition, assessed through the stomach flushing technique, and physical and chemical characteristics in mountain ponds, focusing on parameters altered by livestock pressure, such as ammonium concentration and dissolved oxygen. The high diversity of prey items found within the newts&rsquo, gut contents confirms the generalist diet even in mountain ponds. The number of prey taxa, their relative abundance and Shannon&ndash, Wiener diversity index show variations among the sampled sites, related to livestock organic pollution. Moreover, we report the very first European records of microplastic items in amphibians&rsquo, stomach content, which also represent the first evidence for Caudata worldwide. Our findings suggest that livestock pressure directly influences T. carnifex diet and highlight that the emerging issue of plastics is a threat even in remote high-altitude environments.

The elemental composition of 63 emmer samples produced in three different Italian territories, Monteleone di Spoleto (Umbria), Garfagnana (Tuscany) and National Park Gran Sasso-Laga (Abruzzo) were analyzed by Inductively Couples Plasma-Optical Emission Spectrometry (ICP-OES) combined with microwave-assisted digestion. The ICP-OES analytical method was validated to assess accuracy, precision and sensitivity. Recoveries were determined by the analysis of six genuine and six fortified emmer samples spiked at different concentrations. Recoveries (%) varied from 83 to 100% for the minor elements (Ba, Cu, Fe, Mn and Zn) detected in emmer in the 1−50 μg/g concentration range (acceptable recovery range 80–110%) and from 85 to 98% for the major elements (Ca, K, Mg and P) whose concentration in emmer was within 0.2−5 mg/g (acceptable recovery range 90–107%). The observed LOD and LOQ values ranged from 0.02 to 1.03 μg/gdry and from 0.07 to 3.44 μg/gdry, respectively, indicating a high sensitivity of the method. Analysis of Variance (ANOVA) was preliminarily applied to investigate the significance of the detected elements (Ba, Cu, Mn, Fe, Zn, Ca, K, Mg and P) as geographical markers. Eventually, Partial Least Squares-Discriminant Analysis (PLS-DA) was used to classify the samples according to their geographical origin. In order to validate the classification model, the 63 samples were divided into a training and a test set of 33 and 30 objects, respectively. The graphical investigation of the PLS-DA model highlighted that samples clearly group according to the geographical origin; this outcome is confirmed by the high accuracy achieved. In fact, the predictive model led to a correct classification rate of 100% for all the external samples. The investigation of the biplot and the application of the Variable Importance in Prediction (VIP) analysis indicated that all the elements except Cu contributed to the characterization of the three different geographical classes.

In recent years, both corporate governance and performance management have been subject to significant forces for change: externally (as a reaction to changing regulatory requirements around the world) and internally (new managerial practices and initiatives inside enterprises). These emerging trends affect all enterprises from all sectors whether they are historically subject to formal external and government regulation (such as the financial services sector or healthcare), listing requirements (public companies and multinational companies) or informally structured family businesses and SMEs where wider groups of stakeholders are beginning to become active. For all enterprises changes in the corporate governance and management control spheres can be seen to stimulate innovative management practice in order to address their potential impact on corporate performance. The scientific papers in this special issue of the International Journal of Business Performance Management contribute to the current response by scholars to these events using a broad range of theoretical and methodological approaches to extend and develop the state-of-the-art.

Social sciences and humanities (SSH) research is divided across a wide array of disciplines, sub-disciplines and languages. While this specialization makes it possible to investigate the extensive variety of SSH topics, it also leads to a fragmentation that prevents SSH research from reaching its full potential. The TRIPLE project brings answers to these issues by developing an innovative discovery platform for SSH data, researchers&rsquo, projects and profiles. Having started in October 2019, the project has already three main achievements that are presented in this paper: (1) the definition of main features of the GOTRIPLE platform, (2) its interoperability, (3) its multilingual, multicultural and interdisciplinary vocation. These results have been achieved thanks to different methodologies such as a co-design process, market analysis and benchmarking, monitoring and co-building. These preliminary results highlight the need for respecting diversity of practices and communities through coordination and harmonization.

This white paper has been elaborated by the Tools (R&D) Working Group, one of the 7 Working Groups launched by the OPERAS research infrastructure. The Working Group goal was to set up a list of tools and development which need to be done, to improve their usability for the OPERAS partners. The approach in OPERAS emphasizes the importance of building the open science scholarly communication infrastructure in Social Sciences and Humanities on community driven tools. In this perspective, the development of Open Source tools and the setup of a toolbox appear to be appropriate answers to the existing needs and evolutions in scholarly publishing. Following a first discussion in the Working Group, participants discussed the partners’ practices and needs to help focus the Working Group objectives on three functions: –– Peer review: interest in emerging practices such as open peer review, peer review tracking –– Authoring: interest in simple and all-in-one services, especially online and collaborative authoring –– Publishing: in particular, simple tools needed by small academic journals The main results of the Working Group are: –– Notes on observed trends –– A common approach and criteria for choosing tools –– A list of relevant tools, detailing features and functionalities –– An analysis of the current needs of the partners For Peer Review, the reviewing workflow is implemented in most Open Source software like Open Journal System (OJS) but developments are still needed to match the commercial software services. Similarly, the review tracking data available via services such as Publons is currently not open. The emerging trend for Open Peer Review represents an innovative area, both in terms of usage and tools. For Authoring, we see a bloom of new online and collaborative tools. Promising Open Source software for editing structured scholarly content are being developed and are near to production, alongside commercial tools such as Authorea or Overleaf. One of the main challenges, in this case, is to obtain a continuous production environment through interoperability. For Publishing, several Open Source software solutions are already used in production, but, as the level of service expected from a publication service is rising and includes a growing number of thirdparty services, the community is considering ways of working together to combine their effort to be comparable with the state of the art of the commercial solutions. The Operas partners are willing to go beyond this working group and consider engaging in follow-up projects, notably to help create a resource centre dedicated to providing the community with current information and support on scholarly communication software and tools, and to contribute to the effort in developing Open Source tools.