150 mW unsaturated output power at 3 µm from a single-mode-fiber erbium cascade laser

We report on an erbium cascade laser in a fluorozirconate fiber. Lasing on the transition 4I11/2 -> 4I13/2 at 2.71 µm is supported by colasing on the transition 4S3/2 -> 4I9/2 at 1.72 µm. This recycles the excitation that is lost via excited-state absorption and avoids the saturation of the output power. Threshold at 2.71 µm is 33 mW launched pump power at 791 nm. The measured slope efficiency of 22.6% is relatively close to the 29.1% stokes-efficiency limit. An output power of 158 mW is obtained, limited only by the 1.43 W power available from the Ti:sapphire pump laser. Output power is 15 and slope efficiency 2.5 times higher than reported in previous publications

Vacancy assisted arsenic diffusion and time dependent clustering effects in silicon

We present results of kinetic lattice Monte Carlo (KLMC) simulations of substitutional arsenic diffusion in silicon mediated by lattice vacancies. Large systems are considered, with 1000 dopant atoms and long range \textit{ab initio} interactions, to the 18th nearest lattice neighbor, and the diffusivity of each defect species over time is calculated. The concentration of vacancies is greater than equilibrium concentrations in order to simulate conditions shortly after ion implantation. A previously unreported time dependence in the applicability of the pair diffusion model, even at low temperatures, is demonstrated. Additionally, long range interactions are shown to be of critical importance in KLMC simulations; when shorter interaction ranges are considered only clusters composed entirely of vacancies form. An increase in arsenic diffusivity for arsenic concentrations up to $10^{19} \text{cm}^{-3}$ is observed, along with a decrease in arsenic diffusivity for higher arsenic concentrations, due to the formation of arsenic dominated clusters. Finally, the effect of vacancy concentration on diffusivity and clustering is studied, and increasing vacancy concentration is found to lead to a greater number of clusters, more defects per cluster, and a greater vacancy fraction within the clusters.Comment: 22 pages, 16 figure

Vacancy clustering and diffusion in silicon: Kinetic lattice Monte Carlo simulations

Diffusion and clustering of lattice vacancies in silicon as a function of temperature, concentration, and interaction range are investigated by Kinetic Lattice Monte Carlo simulations. It is found that higher temperatures lead to larger clusters with shorter lifetimes on average, which grow by attracting free vacancies, while clusters at lower temperatures grow by aggregation of smaller clusters. Long interaction ranges produce enhanced diffusivity and fewer clusters. Greater vacancy concentrations lead to more clusters, with fewer free vacancies, but the size of the clusters is largely independent of concentration. Vacancy diffusivity is shown to obey power law behavior over time, and the exponent of this law is shown to increase with concentration, at fixed temperature, and decrease with temperature, at fixed concentration.Comment: 14 pages, 12 figures. To appear in Physical Review

Baza de date a produselor din Uniunea Europeană UPD (Union Product Database)

The official source of up-to-date information on veterinary medicinal products authorized anywhere in the EU/EEA in light of Regulation (EU) 6/2019, entered into force Entry into force and applicability: 28 January 2022 is the UPD (Union Product Database). This aims to increase transparency on authorized veterinary medicinal products (PMVs) used in the EU/EEA, support the harmonization of information on PMVs and last but not least to become a reliable tool for veterinarians to analyze and compare therapeutic options available, as well as for the information of animal owners. UPD site: search / compare PM

Comercializarea produselor medicinale veterinare la distanță (on-line) și prin farmaciile comunitare

In this PPT, a presentation is made about the sale of veterinary medicinal products at a distance (online) and through community pharmacies in the light of the provisions of Regulation (EU) 2019/6 regarding the online sale of veterinary medicinal products and Romanian legislation. In Romania, remote retail (on-line) sales of veterinary medicinal products can be carried out: only through veterinary pharmacies authorized by a sanitary-veterinarian and veterinary pharmaceutical points registered by a sanitary-veterinary, and only with veterinary medicinal products that are issued without a medical prescription veterinarian. Every economic operator who wants to carry out remote retail trade activities must send a notification to ANSVSA (according to the model provided in Annex 3.1 of Order of the President of ANSVSA no. 83/2014). After verification for compliance with the legislation in force, ANSVSA enters the operator in the list of retailers, who are allowed to sell veterinary medicinal products online

Sparse Estimators and the Oracle Property, or the Return of Hodges' Estimator

We point out some pitfalls related to the concept of an oracle property as used in Fan and Li (2001, 2002, 2004) which are reminiscent of the well-known pitfalls related to Hodges' estimator. The oracle property is often a consequence of sparsity of an estimator. We show that any estimator satisfying a sparsity property has maximal risk that converges to the supremum of the loss function; in particular, the maximal risk diverges to infinity whenever the loss function is unbounded. For ease of presentation the result is set in the framework of a linear regression model, but generalizes far beyond that setting. In a Monte Carlo study we also assess the extent of the problem in finite samples for the smoothly clipped absolute deviation (SCAD) estimator introduced in Fan and Li (2001). We find that this estimator can perform rather poorly in finite samples and that its worst-case performance relative to maximum likelihood deteriorates with increasing sample size when the estimator is tuned to sparsity.Comment: 18 pages, 5 figure

On the Distribution of the Adaptive LASSO Estimator

We study the distribution of the adaptive LASSO estimator (Zou (2006)) in finite samples as well as in the large-sample limit. The large-sample distributions are derived both for the case where the adaptive LASSO estimator is tuned to perform conservative model selection as well as for the case where the tuning results in consistent model selection. We show that the finite-sample as well as the large-sample distributions are typically highly non-normal, regardless of the choice of the tuning parameter. The uniform convergence rate is also obtained, and is shown to be slower than $n^{-1/2}$ in case the estimator is tuned to perform consistent model selection. In particular, these results question the statistical relevance of the `oracle' property of the adaptive LASSO estimator established in Zou (2006). Moreover, we also provide an impossibility result regarding the estimation of the distribution function of the adaptive LASSO estimator.The theoretical results, which are obtained for a regression model with orthogonal design, are complemented by a Monte Carlo study using non-orthogonal regressors.Comment: revised version; minor changes and some material adde