61 research outputs found

    A Critical Overview of Privacy-Preserving Approaches for Collaborative Forecasting

    Full text link
    Cooperation between different data owners may lead to an improvement in forecast quality - for instance by benefiting from spatial-temporal dependencies in geographically distributed time series. Due to business competitive factors and personal data protection questions, said data owners might be unwilling to share their data, which increases the interest in collaborative privacy-preserving forecasting. This paper analyses the state-of-the-art and unveils several shortcomings of existing methods in guaranteeing data privacy when employing Vector Autoregressive (VAR) models. The paper also provides mathematical proofs and numerical analysis to evaluate existing privacy-preserving methods, dividing them into three groups: data transformation, secure multi-party computations, and decomposition methods. The analysis shows that state-of-the-art techniques have limitations in preserving data privacy, such as a trade-off between privacy and forecasting accuracy, while the original data in iterative model fitting processes, in which intermediate results are shared, can be inferred after some iterations

    Morphological correlates of corticosteroid-induced changes in prefrontal cortex-dependent behaviors

    Get PDF
    Imbalances in the corticosteroid milieu have been implicated in several neuropsychiatric disorders, including depression and schizo-phrenia. Prefrontal cortex (PFC) dysfunction is also a hallmark of these conditions, causing impairments in executive functions such as behavioral flexibility and working memory. Recent studies have suggested that the PFC might be influenced by corticosteroids released during stress. To test this possibility, we assessed spatial working memory and behavioral flexibility in rats submitted to chronic adrenalectomy or treatment with corticosterone (25 mg/kg) or the synthetic glucocorticoid dexamethasone (300 μg/kg); the behavioral analysis was complemented by stereological evaluation of the PFC (prelimbic, infralimbic, and anterior cingulate regions), the adjacent retrosplenial and motor cortices, and the hippocampal formation. Dexamethasone treatment resulted in a pronounced impairment in working memory and behavioral flexibility, effects that correlated with neuronal loss and atrophy of layer II of the infralimbic, prelimbic, and cingulate cortices. Exposure to corticosterone produced milder impairments in behavioral flexibility, but not in working memory, and reduced the volume of layer II of all prefrontal areas. Interestingly, adrenalectomy-induced deleterious effects only became apparent on the reverse learning task and were not associated with structural alterations in the PFC. None of the experimental procedures influenced the morphology of retrosplenial or motor cortices, but stereological measurements confirmed previously observed effects of corticosteroids on hippocampal structure. Our results describe, for the first time, that imbalances in the corticosteroid environment can induce degeneration of specific layers of the PFC; these changes appear to be the morphological correlate of corticosteroid-induced impairment of PFC-dependent behavior(s).German Academic Exchange - grant Acções Integradas Luso-Alemãs.Portuguese Rectors’ Conference

    “Clicking” an ionic liquid to a potent antimicrobial peptide: on the route towards improved stability

    Get PDF
    A covalent conjugate between an antibacterial ionic liquid and an antimicrobial peptide was produced via “click” chemistry, and found to retain the parent peptide’s activity against multidrug-resistant clinical isolates of Gram-negative bacteria, and antibiofilm action on a resistant clinical isolate of Klebsiella pneumoniae, while exhibiting much improved stability towards tyrosinase-mediated modifications. This unprecedented communication is a prelude for the promise held by ionic liquids -based approaches as tools to improve the action of bioactive peptides.info:eu-repo/semantics/publishedVersio

    Turning a Collagenesis-Inducing Peptide Into a Potent Antibacterial and Antibiofilm Agent Against Multidrug-Resistant Gram-Negative Bacteria

    Get PDF
    Antimicrobial resistance is becoming one the most serious health threats worldwide, as it not only hampers effective treatment of infectious diseases using current antibiotics, but also increases the risks of medical procedures like surgery, transplantation, bone and dental implantation, chemotherapy, or chronic wound management. To date, there are no effective measures to tackle life-threatening nosocomial infections caused by multidrug resistant bacterial species, of which Gram-negative species within the so-called "ESKAPE" pathogens are the most worrisome. Many such bacteria are frequently isolated from severely infected skin lesions such as diabetic foot ulcers (DFU). In this connection, we are pursuing new peptide constructs encompassing antimicrobial and collagenesis-inducing motifs, to tackle skin and soft tissue infections by exerting a dual effect: antimicrobial protection and faster healing of the wound. This produced peptide 3.1-PP4 showed MIC values as low as 1.0 and 2.1 ÎĽM against Escherichia coli and Pseudomonas aeruginosa, respectively, and low toxicity to HFF-1 human fibroblasts. Remarkably, the peptide was also potent against multidrug-resistant isolates of Klebsiella pneumoniae, E. coli, and P. aeruginosa (MIC values between 0.5 and 4.1 ÎĽM), and hampered the formation of/disaggregated K. pneumoniae biofilms of resistant clinical isolates. Moreover, this notable hybrid peptide retained the collagenesis-inducing behavior of the reference cosmeceutical peptide C16-PP4 ("Matrixyl"). In conclusion, 3.1-PP4 is a highly promising lead toward development of a topical treatment for severely infected skin injuries.info:eu-repo/semantics/publishedVersio

    Wind power probabilistic forecast in the reproducing Kernel Hilbert space

    Get PDF
    Wind power probabilistic forecast is a key input in decision-making problems under risk, such as stochastic unit commitment, operating reserve setting and electricity market bidding. While the majority of the probabilistic forecasting methods are based on quantile regression, the associated limitations call for new approaches. This paper described a new quantile regression model based on the Reproducing Kernel Hilbert Space (RKHS) framework. In particular, two versions of the model, off-line and on-line, were implemented and tested for a real wind farm. Results showed the superiority of the on-line approach in terms of performance, robustness and computational cost. Additionally, it was observed that, in the presence of correlated data, the optimal on-line learning may cause unreliable modelling. Potential solutions to this effect are also described and implemented in the paper

    Disclosure of a promising lead to tackle complicated skin and skin structure infections: antimicrobial and antibiofilm actions of peptide PP4-3.1

    Get PDF
    Efficient antibiotics are being exhausted, which compromises the treatment of infections, including complicated skin and skin structure infections (cSSTI) often associated with multidrug resistant (MDR) bacteria, methicillin-resistant S. aureus (MRSA) being the most prevalent. Antimicrobial peptides (AMP) are being increasingly regarded as the new hope for the post-antibiotic era. Thus, future management of cSSTI may include use of peptides that, on the one hand, behave as AMP and, on the other, are able to promote fast and correct skin rebuilding. As such, we combined the well-known cosmeceutical pentapeptide-4 (PP4), devoid of antimicrobial action but possessing collagenesis-boosting properties, with the AMP 3.1, to afford the chimeric peptide PP4-3.1. We further produced its N-methyl imidazole derivative, MeIm-PP4-3.1. Both peptide-based constructs were evaluated in vitro against Gram-negative bacteria, Gram-positive bacteria, and Candida spp. fungi. Additionally, the antibiofilm activity, the toxicity to human keratinocytes, and the activity against S. aureus in simulated wound fluid (SWF) were assessed. The chimeric peptide PP4-3.1 stood out for its potent activity against Gram-positive and Gram-negative bacteria, including against MDR clinical isolates (0.8 ≤ MIC ≤ 5.7 µM), both in planktonic form and in biofilm matrix. The peptide was also active against three clinically relevant species of Candida fungi, with an overall performance superior to that of fluconazole. Altogether, data reveal that PP4-3.1 is as a promising lead for the future development of new topical treatments for severe skin infections.info:eu-repo/semantics/publishedVersio

    Functional Scalability and Replicability Analysis for Smart Grid Functions: The InteGrid Project Approach

    Get PDF
    The evolution of the electrical power sector due to the advances in digitalization, decarbonization and decentralization has led to the increase in challenges within the current distribution network. Therefore, there is an increased need to analyze the impact of the smart grid and its implemented solutions in order to address these challenges at the earliest stage, i.e., during the pilot phase and before large-scale deployment and mass adoption. Therefore, this paper presents the scalability and replicability analysis conducted within the European project InteGrid. Within the project, innovative solutions are proposed and tested in real demonstration sites (Portugal, Slovenia, and Sweden) to enable the DSO as a market facilitator and to assess the impact of the scalability and replicability of these solutions when integrated into the network. The analysis presents a total of three clusters where the impact of several integrated smart tools is analyzed alongside future large scale scenarios. These large scale scenarios envision significant penetration of distributed energy resources, increased network dimensions, large pools of flexibility, and prosumers. The replicability is analyzed through different types of networks, locations (country-wise), or time (daily). In addition, a simple replication path based on a step by step approach is proposed as a guideline to replicate the smart functions associated with each of the clusters
    • …