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Whilst simulating crop performance in different environments can help fill the knowledge gap and improve the adoption of crops that are currently neglected and underutilised in conventional agrifood systems, lack of experimental data remains a barrier to widespread modelling of these crops. To date, no attempt has been made to collate sub-species crop data that are specifically suited for modelling underutilised crops. This article describes the first attempt to develop a database for crop modelling data with a focus on European underutilised crops. Following a pilot study to identify crops with the potential across the EU, a structured dataset of detailed experimental data was developed by analysing more than 500 agronomic studies that were published across European agroclimatic zones from 1972 to 2022. The dataset contains minimum information for calibrating basic crop models for any location in the EU provided that enough experimental and environmental data are available. More specifically, the database includes crop phenology, yield, management practices, geographic and pedo-climatic details of select underutilised and neglected species. The information underwent a curation procedure to ensure its quality. The collated database will be used in CropBASE, the global knowledge base for underutilised crops.

Abstract In the context of data hiding reversible embedding of information into printable string encoded data may provide a solution to store extra bits for various applications. A previous work demonstrated how to leverage the unused configurations for Base45 and Base85 encodings to store data into files and QR‐codes. In this paper we show that adapting the encoding to the byte distribution statistics of various data and file types significantly improves the payload for Base45 encoded data like QR‐codes.

In anticipation of climate changes, strategic soil management, encompassing reduced tillage and optimized crop residue utilization, emerges as a pivotal strategy for climate impact mitigation. Evaluating the transition from conventional to conservative cropping systems, especially the equilibrium shift in the medium to long term, is essential. ARMOSA, a robust crop simulation model, adeptly responds to varied soil management practices such as no tillage, minimum tillage, and specific straw management options such as chopping and incorporating crop residue into the soil (with or without prior nitrogen and water addition before ploughing). It effectively captures dynamic fluctuations in total organic carbon over an extended period. While challenges persist in precisely predicting grain yield due to climatic intricacies, ARMOSA stands out as a valuable and versatile tool. The model excels in comprehending and simulating wheat cultivar responses in dynamic agricultural ecosystems, shedding light on phenological patterns, biomass accumulation, and soil organic carbon dynamics. This research significantly advances our understanding of the intricate complexities associated with past wheat cultivation in diverse environmental conditions. ARMOSA’s ability to inform decisions on conservation practices positions it as a valuable asset for researchers, agronomists, and policymakers navigating the challenges of sustainable agriculture amidst climate change. Its real-world significance lies in its potential to guide informed decisions, contributing to global efforts in sustainable agriculture and climate resilience.

Abstract This article presents the proposal of a novel encoding method for representing binary data in printable format. The encoding procedure reversibly transforms binary strings into printable letter sequences using a mapping from bit strings to an alphabet of 41 symbols taken from a subset of the English uppercase and lowercase letters. The decoding process reversibly recovers an original bit string from the encoded printable string. The encoding and decoding algorithms along with the properties of this coding are examined and discussed. In particular, the use of only URL‐safe and clearly visually distinguishable characters is emphasized.

Base45 encodes pairs of octets using 3 characters from an alphabet of 45 printable symbols. Previous works showed the ability to hide payload data into encoded strings by exploiting the unused configurations of the Base45 encoding. In this paper, we present Hide45, an algorithm for hiding data into Base45 encoded strings that optimizes the embedding capacity, according to the frequency distribution of the input data. Experimental tests show that an optimal assignment of bit configurations to the most frequent pairs of octets allows to reach a payload capacity very close to the theoretical capacity of the method, improving over a baseline assignment by up to 53%.

In this paper, we propose to exploit the unused configurations of a printable encoding such as Base41, Base45 or Base85 to create a side channel that can store extra data such as error detection or correction codes, integrity verification and authentication information or application defined data. After introducing the encoding of binary octet strings in printable form, we present some case studies that show possible applications of the unused configurations.

Adoption of zero-tillage practices with residue retention in field crops has been introduced as an alternative soil-management technique to counteract the resource degradation and high production costs derived from intensive tillage. In this sense, the biophysical models are valuable tools to evaluate and design the most suitable soil-management technique in view of future climate variability. The aim of this study was to use the ARMOSA process-based crop model to perform an assessment of tillage (T) and no-tillage (No-T) practices of durum-wheat-cropping systems in the Campania region (South of Italy) under current and future climate scenarios. First, the model was calibrated using measurements of soil water content at different depths, leaf area index, and aboveground biomass in the T and No-T treatments during the 2013–2014 season. Then, the model was further applied in the T and No-T treatments to future climate data for 2020–2100 that was generated by the COSMO-CLM model using the RCP4.5 and 8.5 paths. Results of the calibration depicted that the model can accurately simulate the soil-crop-related variables of both soil-management treatments, and thus can be applied to identify the most appropriate conservation agricultural practices in the durum-wheat system. The simulation of soil water content at different depths resulted in small relative root mean square errors (RRMSE < 15%) and an acceptable Pearson’s correlation coefficient (r > 0.51); and the goodness-of-fit indicators for simulated LAI and AGB resulted in acceptable RRMSE (RRMSE < 28%), and high r (r > 0.84) in both soil-management treatments. Future climate simulations showed that No-T management will deliver 10% more wheat yield than the T, with an annual average 0.31% year−1 increase of soil organic carbon, and an increase of 3.80% year−1 for N uptake, which can diminish the N leaching. These results suggest that No-T could be implemented as a more resilient management for farming system in view of climate uncertainty and scarcity of resources. Therefore, these findings support the potential of the ARMOSA model to evaluate the soil-crop response of the durum-wheat system under different management conditions and to design appropriate soil-management practices for current and future climate predictions.

Printable string encodings are widely used in several applications that cannot deal with binary data, the most known example being the mail system. In this paper, we investigate the potential of some of the proposed encodings to hide and carry extra information. We describe a framework for reversibly embedding data in printable string encodings, like Base45. The method leverages the characteristic of some encodings that are not surjective by using illegal configurations to embed one bit of information. With the assumption of uniformly distributed binary input data, an estimation of the expected payload can be computed easily. Results are reported for Base45 and Base85 encodings.

The article analyses the recent judgment of the Court of Justice of the European Union (CJEU) in Skanska Industrial. In its preliminary ruling, the CJEU recognised for the first time the so-called “economic succession doctrine” in damage claims concerning a breach of EU competition rules. In the judgment, the CJEU relied on its well-established case law. From this point of view, the ruling is “nothing extraordinary”. Nevertheless, the judgment represents an important milestone that contributes to the development of damage claims in Europe. The article first discusses the origins of the economic succession doctrine, which derives from the broad concept of “undertaking” developed by the CJEU case law and the so-called “single economic entity” doctrine. Afterwards, the article discusses the Skanska Industrial case, in particular by comparing the opinion of Advocate General (AG) Wahl with the CJEU ruling in the case. The article concludes by discussing the potential consequences of the CJEU ruling in Skanska Industrial on private enforcement of EU competition law, as well as the questions that remain open after the judgment. After Skanska Industrial, it remains unclear how the disclosure of evidence will take place in practice in the context of a damage claim following a corporate restructuring. Secondly, the limits of the economic succession doctrine remain unclear: it is unclear when a corporate restructuring indeed leads to the establishment of a “new” undertaking, free from the antitrust liability acquired by its predecessor. Finally, it remains unclear whether Skanska Industrial case law could also be extended to other remedies besides damage claims, such as actions requesting a court injunction, compensation for unjust enrichment, or a declaration that a contract is null and void. The article argues that in the coming years the CJEU will probably be called to clarify Skanska Industrial case law in order to answer these remaining questions.

Advanced Driver-Assistance Systems (ADASs) are used for increasing safety in the automotive domain, yet current ADASs notably operate without taking into account drivers’ states, e.g., whether she/he is emotionally apt to drive. In this paper, we first review the state-of-the-art of emotional and cognitive analysis for ADAS: we consider psychological models, the sensors needed for capturing physiological signals, and the typical algorithms used for human emotion classification. Our investigation highlights a lack of advanced Driver Monitoring Systems (DMSs) for ADASs, which could increase driving quality and security for both drivers and passengers. We then provide our view on a novel perception architecture for driver monitoring, built around the concept of Driver Complex State (DCS). DCS relies on multiple non-obtrusive sensors and Artificial Intelligence (AI) for uncovering the driver state and uses it to implement innovative Human–Machine Interface (HMI) functionalities. This concept will be implemented and validated in the recently EU-funded NextPerception project, which is briefly introduced.

This paper presents an algorithm aimed at the integrity protection of 3D models represented as a set of vertices and polygons. The proposed method defines a procedure to perform a fragile watermarking of the vertices’ data, namely 3D coordinates and polygons, introducing a very small error in the vertices’ coordinates. The watermark bit string is embedded into a secret vector space defined by the Karhunen–Loève transform derived from a key image. Experimental results show the good performance of the method and its security.

Abstract A prime goal in systems biology is the comprehensive use of existing high‐throughput genomic datasets to gain a better understanding of chromatin organization and genome function. In this report, we use chromatin immunoprecipitation (ChIP) data that map protein‐binding sites on the genome, and Hi‐C data that map interactions between DNA fragments in the genome in an integrative approach. We first reanalyzed the contact map of the human genome as determined with Hi‐C and found that long‐range interactions are highly nonrandom; the same DNA fragments are often found interacting together. We then show using ChIP data that these interactions can be explained by the action of the CCCTC‐binding factor (CTCF). These CTCF‐mediated interactions are found both within chromosomes and in between different chromosomes. This makes CTCF a major organizer of both the structure of the chromosomal fiber within each individual chromosome and of the chromosome territories within the cell nucleus.

This paper presents a fragile watermarking algorithm`m for the protection of the integrity of color images with alpha channel. The system is able to identify modified areas with very high probability, even with small color or transparency changes. The main characteristic of the algorithm is the embedding of the watermark by modifying the alpha channel, leaving the color channels untouched and introducing a very small error with respect to the host image. As a consequence, the resulting watermarked images have a very high peak signal-to-noise ratio. The security of the algorithm is based on a secret key defining the embedding space in which the watermark is inserted by means of the Karhunen–Loève transform (KLT) and a genetic algorithm (GA). Its high sensitivity to modifications is shown, proving the security of the whole system.

In this paper, we apply the quaternion framework for color images to a fragile watermarking algorithm with the objective of multimedia integrity protection (Quaternion Karhunen-Loève Transform Fragile Watermarking (QKLT-FW)). The use of quaternions to represent pixels allows to consider the color information in a holistic and integrated fashion. We stress out that, by taking advantage of the host image quaternion representation, we extract complex features that are able to improve the embedding and verification of fragile watermarks. The algorithm, based on the Quaternion Karhunen-Loève Transform (QKLT), embeds a binary watermark into some QKLT coefficients representing a host image in a secret frequency space: the QKLT basis images are computed from a secret color image used as a symmetric key. A computational intelligence technique (i.e., genetic algorithm) is employed to modify the host image pixels in such a way that the watermark is contained in the protected image. The sensitivity to image modifications is then tested, showing very good performance.

Simulation models can support quantitative and integrated analyses of agricultural systems. In this paper we describe VA.TE., a computer program developed to support the preparation and evaluation of nitrogen fertilising plans for livestock farms in the Lombardy region (northern Italy). The program integrates the cropping systems simulation model CropSyst with several regional agricultural databases, and provides the users with a simple framework for applying the model and interpreting results. VA.TE. makes good use of available data, integrating into a single relational database existing information about soils, climate, farms, animal breeds, crops and crop managements, and providing estimates of missing input variables. A simulation engine manages the entire simulation process: choice of farms to be simulated, model parameterisation, creation of model inputs, simulation of scenarios and analysis of model outputs. The program permits to apply at farm scale a model originally designed for the lower scale of homogeneous land parcel. It manages alternative simulation scenarios for each farm, helping to identify solutions to combine low nitrate losses and satisfactory crop yields. Example simulation results for three farms located on different soils and having varying levels of nitrogen surplus show that the integrated system (model + database) can manage various simulations automatically, and that strategies to improve N management can be refined by analysing the simulated amounts and temporal patterns of nitrogen leaching.We conclude by discussing the issues regarding the integration of existing regional databases with simulation models.