Soliton solutions of Calogero model in harmonic potential

A classical Calogero model in an external harmonic potential is known to be integrable for any number of particles. We consider here reductions which play a role of "soliton" solutions of the model. We obtain these solutions both for the model with finite number of particles and in a hydrodynamic limit. In the latter limit the model is described by hydrodynamic equations on continuous density and velocity fields. Soliton solutions in this case are finite dimensional reductions of the hydrodynamic model and describe the propagation of lumps of density and velocity in the nontrivial background.Comment: 25 pages, 2 figure

Bloch Approximation in Homogenization and Applications

The classical problem of homogenization of elliptic operators with periodically oscillating coefficients is revisited in this paper. As is well known, the homogenization process in a classical framework is concerned with the study of asymptotic behavior of solutions $u^\varepsilon$ of boundary value problems associated with such operators when the period $\varepsilon>0$ of the coefficients is small. In a previous work by C. Conca and M. Vanninathan [SIAM J. Appl. Math., 57 (1997), pp. 1639--1659], a new proof of weak convergence as $\varepsilon\to 0$ towards the homogenized solution was furnished using Bloch wave decomposition. Following the same approach here, we go further and introduce what we call Bloch approximation, which will provide energy norm approximation for the solution $u^\varepsilon$. We develop several of its main features. As a simple application of this new object, we show that it contains both the first and second order correctors. Necessarily, the Bloch approximation will have to capture the oscillations of the solution in a sharper way. The present approach sheds new light and offers an alternative for viewing classical results

Efficient and Unbiased Estimation of Population Size

Population sizing from still aerial pictures is of wide applicability in ecological and social sciences. The problem is long standing because current automatic detection and counting algorithms are known to fail in most cases, and exhaustive manual counting is tedious, slow, difficult to verify and unfeasible for large populations. An alternative is to multiply population density with some reference area but, unfortunately, sampling details, handling of edge effects, etc., are seldom described. For the first time we address the problem using principles of geometric sampling. These principles are old and solid, but largely unknown outside the areas of three dimensional microscopy and stereology. Here we adapt them to estimate the size of any population of individuals lying on an essentially planar area, e.g. people, animals, trees on a savanna, etc. The proposed design is unbiased irrespective of population size, pattern, perspective artifacts, etc. The implementation is very simple—it is based on the random superimposition of coarse quadrat grids. Also, an objective error assessment is often lacking. For the latter purpose the quadrat counts are often assumed to be independent. We demonstrate that this approach can perform very poorly, and we propose (and check via Monte Carlo resampling) a new theoretical error prediction formula. As far as efficiency, counting about 50 (100) individuals in 20 quadrats, can yield relative standard errors of about 8% (5%) in typical cases. This fact effectively breaks the barrier hitherto imposed by the current lack of automatic face detection algorithms, because semiautomatic sampling and manual counting becomes an attractive option

Electrografting of BTSE: Zn films for advanced steel-aluminum joining by plastic deformation

This article presents the application of an adhesion promoting highly crosslinked ultrathin organic-inorganic hybrid layer applied to steel which promotes the subsequent joining process based on plastic deformation. The tensile shear results show that a significant increase of the bond strength between low-alloy steel (DC04) and aluminum (AW1050A H111), upon cold-pressure welding (CPW), could be achieved. Electrografting of an ultra-thin film of 1,2-bis(triethoxysilyl)ethane (BTSE) films on the steel surface was done from ethanolic solutions containing zinc ions. Based on surface spectroscopic analysis it is shown that silanol moieties present in the organosilane deposits can form stable chemical bonds with both the iron oxide covered steel and the aluminum oxide covered aluminum alloy. The successful modification of metal oxide surfaces with BTSE has been demonstrated via SEM-EDX, AFM, PM-IRRAS, and XPS measurements. In addition, electrochemical analysis of the BTSE:Zn films showed that the films lead to very good corrosion properties even at low thicknesses

Advances in the slow freezing cryopreservation of microencapsulated cells

Over the past few decades, the use of cell microencapsulation technology has been promoted for a wide range of applications as sustained drug delivery systems or as cells containing biosystems for regenerative medicine. However, difficulty in their preservation and storage has limited their availability to healthcare centers. Because the preservation in cryogenic temperatures poses many biological and biophysical challenges and that the technology has not been well understood, the slow cooling cryopreservation, which is the most used technique worldwide, has not given full measure of its full potential application yet. This review will discuss the different steps that should be understood and taken into account to preserve microencapsulated cells by slow freezing in a successful and simple manner. Moreover, it will review the slow freezing preservation of alginate-based microencapsulated cells and discuss some recommendations that the research community may pursue to optimize the preservation of microencapsulated cells, enabling the therapy translate from bench to the clinic

4D Printing: The Development of Responsive Materials Using 3D-Printing Technology

Additive manufacturing, widely known as 3D printing, has revolutionized the production of biomaterials. While conventional 3D-printed structures are perceived as static, 4D printing introduces the ability to fabricate materials capable of self-transforming their configuration or function over time in response to external stimuli such as temperature, light, or electric field. This transformative technology has garnered significant attention in the field of biomedical engineering due to its potential to address limitations associated with traditional therapies. Here, we delve into an in-depth review of 4D-printing systems, exploring their diverse biomedical applications and meticulously evaluating their advantages and disadvantages. We emphasize the novelty of this review paper by highlighting the latest advancements and emerging trends in 4D-printing technology, particularly in the context of biomedical applications.The authors would like to acknowledge grants from the Universidad de Buenos Aires, UBACYT 20020150100056BA and PIDAE 2022 (Martín F. Desimone), and from CONICET PIP 0826 (Martín F. Desimone), and PIBAA 28720210100962CO (Sofia Municoy), which supported this work

Characterization of PFGR-derived fibrin scaffold interactome by 2DE and LC-MS/MS

Comunicaciones a congreso

Spatial representation of temporal information through spike timing dependent plasticity

We suggest a mechanism based on spike time dependent plasticity (STDP) of synapses to store, retrieve and predict temporal sequences. The mechanism is demonstrated in a model system of simplified integrate-and-fire type neurons densely connected by STDP synapses. All synapses are modified according to the so-called normal STDP rule observed in various real biological synapses. After conditioning through repeated input of a limited number of of temporal sequences the system is able to complete the temporal sequence upon receiving the input of a fraction of them. This is an example of effective unsupervised learning in an biologically realistic system. We investigate the dependence of learning success on entrainment time, system size and presence of noise. Possible applications include learning of motor sequences, recognition and prediction of temporal sensory information in the visual as well as the auditory system and late processing in the olfactory system of insects.Comment: 13 pages, 14 figures, completely revised and augmented versio

Self-organization in the olfactory system: one shot odor recognition in insects

We show in a model of spiking neurons that synaptic plasticity in the mushroom bodies in combination with the general fan-in, fan-out properties of the early processing layers of the olfactory system might be sufficient to account for its efficient recognition of odors. For a large variety of initial conditions the model system consistently finds a working solution without any fine-tuning, and is, therefore, inherently robust. We demonstrate that gain control through the known feedforward inhibition of lateral horn interneurons increases the capacity of the system but is not essential for its general function. We also predict an upper limit for the number of odor classes Drosophila can discriminate based on the number and connectivity of its olfactory neurons