Novel Techniques and Their Applications to Health Foods, Agricultural and Medical Biotechnology: Functional Genomics and Basic Epigenetic Controls in Plant and Animal Cells

Selected applications of novel techniques for analyzing Health Food formulations, as well as for advanced investigations in Agricultural and Medical Biotechnology aimed at defining the multiple connections between functional genomics and epigenomic, fundamental control mechanisms in both animal and plant cells are being reviewed with the aim of unraveling future developments and policy changes that are likely to open new niches for Biotechnology and prevent the shrinking or closing of existing markets. Amongst the selected novel techniques with applications in both Agricultural and Medical Biotechnology are: immobilized bacterial cells and enzymes, microencapsulation and liposome production, genetic manipulation of microorganisms, development of novel vaccines from plants, epigenomics of mammalian cells and organisms, and biocomputational tools for molecular modeling related to disease and Bioinformatics. Both fundamental and applied aspects of the emerging new techniques are being discussed in relation to their anticipated, marked impact on future markets and present policy changes that are needed for success in either Agricultural or Medical Biotechnology. The novel techniques are illustrated with figures presenting the most important features of representative and powerful tools which are currently being developed for both immediate and long term applications in Agriculture, Health Food formulation and production, pharmaceuticals and Medicine. The research aspects are naturally emphasized in our review as they are key to further developments in Biotechnology; however, the course adopted for the implementation of biotechnological applications, and the policies associated with biotechnological applications are clearly the determining factors for future Biotechnology successes, be they pharmaceutical, medical or agricultural

Depinning and dynamics of AC driven vortex lattices in random media

We study the different dynamical regimes of a vortex lattice driven by AC forces in the presence of random pinning via numerical simulations. The behaviour of the different observables is charaterized as a function of the applied force amplitude for different frequencies. We discuss the inconveniences of using the mean velocity to identify the depinnig transition and we show that instead, the mean quadratic displacement of the lattice is the relevant magnitude to characterize different AC regimes. We discuss how the results depend on the initial configuration and we identify new hysteretic effects which are absent in the DC driven systems.Comment: 6 pages, 4 figure

Constraining New Physics with D meson decays

Latest Lattice results on $D$ form factors evaluation from first principles show that the standard model (SM) branching ratios prediction for the leptonic $D_s \to \ell \nu_\ell$ decays and the semileptonic SM branching ratios of the $D^0$ and $D^+$ meson decays are in good agreement with the world average experimental measurements. It is possible to disprove New Physics hypothesis or find bounds over several models beyond the SM. Using the observed leptonic and semileptonic branching ratios for the D meson decays, we performed a combined analysis to constrain non standard interactions which mediate the $c\bar{s}\to l\bar{\nu}$ transition. This is done either by a model independent way through the corresponding Wilson coefficients or in a model dependent way by finding the respective bounds over the relevant parameters for some models beyond the standard model. In particular, we obtain bounds for the Two Higgs Doublet Model Type-II and Type III, the Left-Right model, the Minimal Supersymmetric Standard Model with explicit R-Parity violation and Leptoquarks. Finally, we estimate the transverse polarization of the lepton in the $D^0$ decay and we found it can be as high as $P_T=0.23$.Comment: 28 pages, 8 figures, 3 tables. Improved and extended analysis with updated form factors from Lattice QC

Probabilistic Load Forecasting Based on Adaptive Online Learning

Load forecasting is crucial for multiple energy management tasks such as scheduling generation capacity, planning supply and demand, and minimizing energy trade costs. Such relevance has increased even more in recent years due to the integration of renewable energies, electric cars, and microgrids. Conventional load forecasting techniques obtain singlevalue load forecasts by exploiting consumption patterns of past load demand. However, such techniques cannot assess intrinsic uncertainties in load demand, and cannot capture dynamic changes in consumption patterns. To address these problems, this paper presents a method for probabilistic load forecasting based on the adaptive online learning of hidden Markov models. We propose learning and forecasting techniques with theoretical guarantees, and experimentally assess their performance in multiple scenarios. In particular, we develop adaptive online learning techniques that update model parameters recursively, and sequential prediction techniques that obtain probabilistic forecasts using the most recent parameters. The performance of the method is evaluated using multiple datasets corresponding with regions that have different sizes and display assorted time-varying consumption patterns. The results show that the proposed method can significantly improve the performance of existing techniques for a wide range of scenarios.Ramon y Cajal Grant RYC-2016-19383 Basque Government under the grant "Artificial Intelligence in BCAM number EXP. 2019/00432" Iberdrola Foundation under the 2019 Research Grant

Minimax Forward and Backward Learning of Evolving Tasks with Performance Guarantees

For a sequence of classification tasks that arrive over time, it is common that tasks are evolving in the sense that consecutive tasks often have a higher similarity. The incremental learning of a growing sequence of tasks holds promise to enable accurate classification even with few samples per task by leveraging information from all the tasks in the sequence (forward and backward learning). However, existing techniques developed for continual learning and concept drift adaptation are either designed for tasks with time-independent similarities or only aim to learn the last task in the sequence. This paper presents incremental minimax risk classifiers (IMRCs) that effectively exploit forward and backward learning and account for evolving tasks. In addition, we analytically characterize the performance improvement provided by forward and backward learning in terms of the tasks’ expected quadratic change and the number of tasks. The experimental evaluation shows that IMRCs can result in a significant performance improvement, especially for reduced sample sizes.Funding in direct support of this work has been provided by projects PID2022-137063NBI00, PID2022-137442NB-I00, CNS2022-135203, and CEX2021-001142-S funded by MCIN/AEI/10.13039/501100011033 and the European Union “NextGenerationEU”/PRTR, BCAM Severo Ochoa accreditation CEX2021-001142-S / MICIN / AEI/ 10.13039/501100011033 funded by the Ministry of Science and Innovation, and programes ELKARTEK, IT1504-22, and BERC-2022-2025 funded by the Basque Government

Displaced vertices and long-lived charged particles in the NMSSM with right-handed sneutrinos

We study LHC signatures of displaced vertices and long-lived charged particles within the context of the Next-to-Minimal Supersymmetric Standard Model with right-handed (RH) sneutrinos. In this construction the RH neutrino can be produced directly from Higgs decays or in association with a RH sneutrino when the latter is the lightest supersymmetric particle. The RH neutrino is generally long-lived, since its decay width is proportional to the neutrino Yukawa, a parameter which is predicted to be small. The RH neutrino late decay can therefore give rise to displaced vertices at the LHC, which can be identified through the decay products, which involve two leptons (2ℓ + https://static-content.springer.com/image/art%3A10.1007%2FJHEP05%282014%29035/MediaObjects/13130_2014_8145_Figa_HTML.gifT ) or a lepton with two jets (ℓjj). We simulate this signal for the current LHC configuration (a centre of mass of 8 TeV and an integrated luminosity of LL = 20 fb−1), and a future one (13 TeV and LL = 100 fb−1). We show that a region of the parameter space of this model can be probed and that the RH neutrino mass can be reconstructed from the end-point of the two-lepton invariant mass distribution or the central value of the mass distribution for two jets plus one lepton. Another exotic signature of this construction is the production of a long-lived stau. If the stau is the next-to-lightest supersymmetric particle, it can decay through diagrams involving the small neutrino Yukawa, and would escape the detector leaving a characteristic trail. We also simulate this signal for various benchmark points and show that the model can be within the reach of the future run of the LHC

Sinc method in spectrum completion and inverse Sturm-Liouville problems

Cardinal series representations for solutions of the Sturm-Liouville equation $-y''+q(x)y=\rho^{2}y$, $x\in(0,L)$ with a complex valued potential $q(x)$ are obtained, by using the corresponding transmutation operator. Consequently, partial sums of the series approximate the solutions uniformly with respect to $\rho$ in any strip $\left|\text{Im}\rho\right|<C$ of the complex plane. This property of the obtained series representations leads to their applications in a variety of spectral problems. In particular, we show their applicability to the spectrum completion problem, consisting in computing large sets of the eigenvalues from a reduced finite set of known eigenvalues, without any information on the potential $q(x)$ as well as on the constants from boundary conditions. Among other applications this leads to an efficient numerical method for computing a Weyl function from two finite sets of the eigenvalues. This possibility is explored in the present work and illustrated by numerical tests. Finally, based on the cardinal series representations obtained, we develop a method for the numerical solution of the inverse two-spectra Sturm-Liouville problem and show its numerical efficiency