On dentability and cones with a large dual

In this paper, we provide some equivalences on dentability in normed spaces. Among others we prove: the origin is a denting point of a pointed cone $C$ if and only if it is a point of continuity for such a cone and $\overline{C^*-C^*}=X^*$; $x$ is a denting point of a convex set $A$ if and only if $x$ is a point of continuity and a weakly strongly extreme point of $A$. We also analize how our results help us to shed some light on several open problems in the literature

A Set-Valued Lagrange Theorem based on a Process for Convex Vector Programming

In this paper, we present a new set-valued Lagrange multiplier theorem for constrained convex set-valued optimization problems. We introduce the novel concept of Lagrange process. This concept is a natural extension of the classical concept of Lagrange multiplier where the conventional notion of linear continuous operator is replaced by the concept of closed convex process, its set-valued analogue. The behaviour of this new Lagrange multiplier based on a process is shown to be particularly appropriate for some types of proper minimal points and, in general, when it has a bounded base

Influence of chemistry on the steady solutions of hydrogen gaseous detonations with friction losses

Agence Nationale de la Recherche | Ref. FASTD ANR-20-CE05-0011-0

Crystal engineering of high explosives through lone pair-p interactions: Insights for improving thermal safety

In this high-risk/high-reward study, we prepared complexes of a high explosive anion (picrate) with potentially explosive s-tetrazine-based ligands with the sole purpose of advancing the understanding of one of the weakest supramolecular forces: the lone pair-p interaction. This is a proof-of-concept study showing how lone pair-p contacts can be effectively used in crystal engineering, even of high explosives, and how the supramolecular architecture of the resulting crystalline phases influences their experimental thermokinetic properties. Herein we present XRD structures of 4 novel detonating compounds, all showcasing lone pair-p interactions, their thermal characterization (DSC, TGA), including the correlation of experimental thermokinetic parameters with crystal packing, and in silico explosion properties. This last aspect is relevant for improving the safety of high-energy materials.The financial support provided by the MUR - Dipartimenti di Eccellenza 2023–2027 (DICUS 2.0) to the Department of Chemistry ‘‘Ugo Schiff’’ of the University of Florence is acknowledged

Parameter Estimation of Modified Double-Diode and Triple-Diode Photovoltaic Models Based on Wild Horse Optimizer

The increase in industrial and commercial applications of photovoltaic systems (PV) has a significant impact on the increase in interest in studying the improvement of the efficiency of these systems. Estimating the efficiency of PV is considered one of the most important problems facing those in charge of manufacturing these systems, which makes it interesting to many researchers. The difficulty in estimating the efficiency of PV is due to the high non-linear current–voltage characteristics and power–voltage characteristics. In addition, the absence of ample efficiency information in the manufacturers’ datasheets has led to the development of an effective electrical mathematical equivalent model necessary to simulate the PV module. In this paper, an application for an optimization algorithm named Wild Horse Optimizer (WHO) is proposed to extract the parameters of a double-diode PV model (DDM), modified double-diode PV model (MDDM), triple-diode PV model (TDM), and modified triple-diode PV model (MTDM). This study focuses on two main objectives. The first concerns comparing the original models (DDM and TDM) and their modification (MDDM and MTDM). The second concerns the algorithm behavior with the optimization problem and comparing this behavior with other recent algorithms. The evaluation process uses different methods, such as Root Mean Square Error (RMSE) for accuracy and statistical analysis for robustness. Based on the results obtained by the WHO, the estimated parameters using the WHO are more accurate than those obtained by the other studied optimization algorithms; furthermore, the MDDM and MTDM modifications enhanced the original DDM and TDM efficiencies

Nitrated Fatty-Acids Distribution in Storage Biomolecules during Arabidopsis thaliana Development

The non-enzymatic interaction of polyunsaturated fatty acids with nitric oxide (NO) and de rived species results in the formation of nitrated fatty acids (NO2 -FAs). These signaling molecules can release NO, reversibly esterify with complex lipids, and modulate protein function through the post translational modification called nitroalkylation. To date, NO2 -FAs act as signaling molecules during plant development in plant systems and are involved in defense responses against abiotic stress conditions. In this work, the previously unknown storage biomolecules of NO2 -FAs in Arabidopsis thaliana were identified. In addition, the distribution of NO2 -FAs in storage biomolecules during plant development was determined, with phytosterol esters (SE) and TAGs being reservoir biomolecules in seeds, which were replaced by phospholipids and proteins in the vegetative, generative, and senescence stages. The detected esterified NO2 -FAs were nitro-linolenic acid (NO2 -Ln), nitro-oleic acid (NO2 -OA), and nitro-linoleic acid (NO2 -LA). The last two were detected for the first time in Arabidopsis. The levels of the three NO2 -FAs that were esterified in both lipid and protein storage biomolecules showed a decreasing pattern throughout Arabidopsis development. Esterification of NO2 -FAs in phospholipids and proteins highlights their involvement in both biomembrane dynamics and signaling processes, respectively, during Arabidopsis plant developmentThis research was funded by ERDF grants co-financed by the Spanish Ministry of Economy and Competitiveness (Project PGC2018-096405-B-I00); the Junta de Andalucía (group BIO286); the I+D+I project within the framework Programme of FEDER Andalucía 2014–2020 (Reference 1380901); the grants for I+D+I projects, on a competitive basis, within the scope of the Andalusian plan for research, development and innovation (Junta de Andalucía, PAIDI 2020, Reference: PY20_01002); and the funding for the recruitment of researchers under Action 9 and 10 of the Research Support Plan of the University of Jaén (2019–2020, R.02/10/2020; 2020–2021, R.01/01/2022)

Exploiting the S-Iteration Process for Solving Power Flow Problems: Novel Algorithms and Comprehensive Analysis

In recent studies, the competitiveness of the Newton-S-Iteration-Process (Newton-SIP) techniques to efficiently solve the Power Flow (PF) problems in both well and ill-conditioned systems has been highlighted, concluding that these methods may be suitable for industrial applications. This paper aims to tackle some of the open topics brought for this kind of techniques. Different PF techniques are proposed based on the most recently developed Newton-SIP methods. In addition, convergence analysis and a comparative study of four different Newton-SIP methods PF techniques are presented. To check the features of considered PF techniques, several numerical experiments are carried out. Results show that the considered Newton-SIP techniques can achieve up to an eighth order of convergence and typically are more efficient and robust than the Newton–Raphson (NR) technique. Finally, it is shown that the overall performance of the considered PF techniques is strongly influenced by the values of parameters involved in the iterative procedure

A data-driven methodology to design user-friendly tariffs in energy communities

In recent years, energy communities have emerged as a feasible solution to empower domestic end-users to engage in local power trading with their neighbours, in an attempt to improve the efficiency and economy of residential consumers. From a mercantilist point of view, launching local markets with eventual local electricity prices might be beneficial for community users as they are inhibited from external volatile prices and possible market imperfections. However, local pricing strategies should take into account users’ preferences and avoid undesirable effects of response fatigue (i.e. excessive number of response signals within a short-time period). This way, local electricity tariffs should be stable and send coherent response signals easily interpretable by users. In this sense, the necessity of developing proper designing tools for local electricity tariffs is clear. This paper focuses on this issue. In particular, the main novelties of this paper are twofold: on the one hand, the developed tool designs community tariffs over a year basis instead of daily spot prices, as made in existing approaches. Thereby, the resulting tariff keeps stable yearly similar to conventional tariffs offered by retailers worldwide. Secondly, the designed tariff takes into account the negative effects of response fatigue, so that the considered pricing mechanism limits the number of pricing signals sent to consumers, taking this feature as an external parameter. This way, the designer is able to tune up the total number of pricing signals that users received within a time period, thus ensuring that they are not discouraged to partake in the community. The proposed design approach is raised as a data-driven framework, taking advantage of real databases collecting demand, renewable generation and retailer prices. Such profiles serve as inputs for a designed bi-level Stackelberg-based problem, in which the reaction of prosumers is implicitly assumed. A case study is conducted on a benchmark energy community. Different tariff mechanisms are analysed such as flat, time-of-use and happy hours tariffs. The results obtained serve to validate the new proposal as well as analyse the effect of local market mechanisms in energy communities