Paramagnetic reentrant effect in high purity mesoscopic AgNb proximity structures

We discuss the magnetic response of clean Ag coated Nb proximity cylinders in the temperature range 150 \mu K < T < 9 K. In the mesoscopic temperature regime, the normal metal-superconductor system shows the yet unexplained paramagnetic reentrant effect, discovered some years ago [P. Visani, A. C. Mota, and A. Pollini, Phys. Rev. Lett. 65, 1514 (1990)], superimposing on full Meissner screening. The logarithmic slope of the reentrant paramagnetic susceptibility chi_para(T) \propto \exp(-L/\xi_N) is limited by the condition \xi_N=n L, with \xi_N=\hbar v_F/2 \pi k_B T, the thermal coherence length and n=1,2,4. In wires with perimeters L=72 \mu m and L=130 \mu m, we observe integer multiples n=1,2,4. At the lowest temperatures, \chi_para compensates the diamagnetic susceptibility of the \textit{whole} AgNb structure.Comment: 4 pages, 4 figures (color

Diamagnetic response of cylindrical normal metal - superconductor proximity structures with low concentration of scattering centers

We have investigated the diamagnetic response of composite NS proximity wires, consisting of a clean silver or copper coating, in good electrical contact to a superconducting niobium or tantalum core. The samples show strong induced diamagnetism in the normal layer, resulting in a nearly complete Meissner screening at low temperatures. The temperature dependence of the linear diamagnetic susceptibility data is successfully described by the quasiclassical Eilenberger theory including elastic scattering characterised by a mean free path l. Using the mean free path as the only fit parameter we found values of l in the range 0.1-1 of the normal metal layer thickness d_N, which are in rough agreement with the ones obtained from residual resistivity measurements. The fits are satisfactory over the whole temperature range between 5 mK and 7 K for values of d_N varying between 1.6 my m and 30 my m. Although a finite mean free path is necessary to correctly describe the temperature dependence of the linear response diamagnetic susceptibility, the measured breakdown fields in the nonlinear regime follow the temperature and thickness dependence given by the clean limit theory. However, there is a discrepancy in the absolute values. We argue that in order to reach quantitative agreement one needs to take into account the mean free path from the fits of the linear response. [PACS numbers: 74.50.+r, 74.80.-g]Comment: 10 pages, 9 figure

Motility assessment of the ciliated tetrahymena pyriformis after exposition to toxic compounds using image analysis

PRAXIS XXI

Rice husk, brewer’s spent grain, and vine shoot trimmings as raw materials for sustainable enzyme production

Solid by-products with lignocellulosic structures are considered appropriate substrates for solid-state fermentation (SSF) to produce enzymes with diverse industrial applications. In this work, brewer’s spent grain (BSG), rice husk (RH), and vine shoot trimmings (VSTs) were employed as substrates in SSF with Aspergillus niger CECT 2088 to produce cellulases, xylanases, and amylases. The addition of 2% (NH4)2SO4 and 1% K2HPO4 to by-products had a positive effect on enzyme production. Substrate particle size influenced enzyme activity and the overall highest activities were achieved at the largest particle size (10 mm) of BSG and RH and a size of 4 mm for VSTs. Optimal substrate composition was predicted using a simplex centroid mixture design. The highest activities were obtained using 100% BSG for β-glucosidase (363 U/g) and endo-1,4-β-glucanase (189 U/g), 87% BSG and 13% RH for xylanase (627 U/g), and 72% BSG and 28% RH for amylase (263 U/g). Besides the optimal values found, mixtures of BSG with RH or VSTs proved to be alternative substrates to BSG alone. These findings demonstrate that SSF bioprocessing of BSG individually or in mixtures with RH and VSTs is an efficient and sustainable strategy to produce enzymes of significant industrial interest within the circular economy guidelines.This study was funded by the Recovery and Resilience Plan (PRR), Next Generation EU, for the period 2021–2026, through the integrated project be@t—Textile Bioeconomy (TC-C12-i01, Sustainable Bioeconomy No. 02/C12-i01/2022), and by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UIDB/04469/2020 unit (DOI 10.54499/UIDB/04469/2020).info:eu-repo/semantics/publishedVersio

Eco-friendly polymeric material for horticulture application

Poly(lactic acid) (PLA), was mixed with wood fibers, coffee grounds, fertilizer and a foaming agent to developed a ecofriendly material to be used in horticulture. The developed materials should have mechanical properties similar to PLA, increasing biodegradability and lower price. The materials were prepared by melt processing in an internal mixer at 190ºC and were characterized by several techniques. The mechanical properties of the bio-composites, measured by flexural tests, were similar to neat PLA even with a reduction of 40 wt. % of polymer. Biodegradation assessment by composting tests in aerobic environment demonstrated that the green materials developed exhibited higher biodegradability than PLA. Bio-composites containing wood fibers and fertilizer revealed to be the most suitable for horticulture application, since these can combine mechanical properties, biodegradability and fertilizer release. Moreover, this green material has two main advantages, it can be prepared using materials from natural resources and does not generate any residue after use

Indirect evidence of microbial modulation induced by encapsulated A. muciniphila

info:eu-repo/semantics/publishedVersio

Boreholes plans optimization methodology combining geostatistical simulation and simulated annealing

Nowadays, the prospection plans have the difficult task of ensuring a more complete and rich characterization of the rock mass for the purpose of optimizing costs and increasing safety in geotechnical projects. Currently, boreholes location and depth are mainly defined based on experience and know-how of professionals, as such, it is user-dependent. Hence, there is a lack of methodologies to help the decision-makers in defining the optimal location of boreholes (with relevant information). Therefore, this paper presents a methodology based on the use of geostatistical conditional simulation allied to a stochastic global optimization algorithm (Simulated Annealing) to develop optimized boreholes plans comparing a uni-objective and a multi-criteria optimization approaches. In this work, the optimized location is considered the one that minimizes uncertainty translated by either the average local variance or the average width of 95% probability intervals of simulated values at unsampled locations. This methodology was applied using preliminary information obtained from previously executed boreholes using as variable the empirical rock mass classification system, Rock Mass Rating, in a Chilean deposit.This research is inserted in LNEC project named P2I-RockGeoStat and was partially funded by FCT (Fundação para a Ciência e Tecnologia, Portugal) in the scope of project PEst-UID/CEC/00319/2013, included in ISISE project UID/ECl/04029/2013 as well as the PhD grant SFRH/BD/89627/2012, and by the Chilean Commission for Scientific and Technological Research, through Project CONICYT PIA Anillo ACT1407.info:eu-repo/semantics/publishedVersio

Borehole plan optimization in rock masses using geostatistical simulation

The economical and safety aspects related with geotechnical engineering, in detail with prospecting works, are significant and increasingly complex. Therefore, optimizing costs that simultaneously guarantee the quantity and quality of information to characterize the rock mass are, nowadays, one of the most important factors in underground works. The borehole plans, normally defined using the knowhow of a professional, imply large costs in the geotechnical industry, thus this paper presents a new methodology allowing the optimization of such plans. This methodology allies geostatistical techniques (turning bands simulation to model rock mass properties like the Rock Mass Rating or RMR) with a stochastic global optimization algorithm, Simulated Annealing (SA). It relies on sparse information about RMR and randomly generates new points that intend to represent possible locations for additional boreholes. Furthermore, SA is adapted to perform the optimization of a set of points with different depth coordinates in order to represent the reality of the mechanical boreholes, where the information is obtained along the hole. Considering the number of additional boreholes to drill, SA finds a global solution minimizing an objective function, which aims at quantifying the uncertainty on RMR at locations without information. An application to a gold mine deposit located in Chile is finally presented in order to illustrate and validate the methodology.Agência de Desenvolvimento Económico do Chile através do projeto Innova Chile-CORFO 11IDL2-10630Comissão Científica e Tecnológica de Investigação chilena através dos projetos CONICYT / FONDECYT / REGULAR / N°1130085 e CONICYT PIA Anillo ACT 1407P2I-RockGeoStat do LNE