Study of drift-field solar cells damaged by low-energy protons Progress report, Jun. 15 - Aug. 10, 1965

Irradiation damage of drift-field solar cells by low energy protons - calibration of irradiation apparatus and monitoring equipmen

Antiproton annihilation on light nuclei at very low energies

The recent experimental data obtained by the OBELIX group on $\bar{p}$D and $\bar{p}^4$He total annihilation cross sections are analyzed. The combined analysis of these data with existing antiprotonic atom data allows, for the first time, the imaginary parts of the S-wave scattering lengths for the two nuclei to be extracted. The obtained values are: $Im a^{sc}_0 = [- 0.62 \pm 0.02 ({stat}) \pm 0.04 ({sys})] fm$ for $\bar{p}$D and $Im a^{sc}_0 = [- 0.36\pm 0.03({stat})^{+0.19}_{-0.11}({sys})] fm$ for $\bar{p}^4$He. This analysis indicates an unexpected behaviour of the imaginary part of the $\bar{p}$-nucleus S-wave scattering length as a function of the atomic weight A: $|Im a^{sc}_0|$ ($\bar{p}$p) > $|Im a^{sc}_0|$ ($\bar{p}$D) > $|Im a^{sc}_0|$ ($\bar{p}^4$He).Comment: 13 pages, 5 figure

A variable neurodegenerative phenotype with polymerase gamma mutation

mtDNA replication and repair, causes mitochondrial diseases including autosomal dominant progressive external ophthalmoplegia (PEO),1 childhood hepato-encephalopathy (Alpers– Huttenlocher syndrome), adult-onset spinocerebellar ataxia, and sensory nerve degeneration with dysarthria and ophthalmoparesis (SANDO)

Learning to handle parameter perturbations in Combinatorial Optimization: An application to facility location

We present an approach to couple the resolution of Combinatorial Optimization problems with methods from Machine Learning. Specifically, our study is framed in the context where a reference discrete optimization problem is given and there exist data for many variations of such reference problem (historical or simulated) along with their optimal solution. Those variations can be originated by disruption but this is not necessarily the case. We study how one can exploit these to make predictions about an unseen new variation of the reference instance. The methodology is composed by two steps. We demonstrate how a classifier can be built from these data to determine whether the solution to the reference problem still applies to a perturbed instance. In case the reference solution is only partially applicable, we build a regressor indicating the magnitude of the expected change, and conversely how much of it can be kept for the perturbed instance. This insight, derived from a priori information, is expressed via an additional constraint in the original mathematical programming formulation. We present the methodology through an application to the classical facility location problem and we provide an empirical evaluation and discuss the benefits, drawbacks and perspectives of such an approach. Although it cannot be used in a black-box manner, i.e., it has to be adapted to the specific application at hand, we believe that the approach developed here is general and explores a new perspective on the exploitation of past experience in Combinatorial Optimization

Nanomedicine, an emerging therapeutic strategy for oral cancer therapy

Oral cavity and oropharyngeal carcinomas (oral cancer) represents a significant cause of morbidity and mortality. Despite efforts in improving early diagnosis and treatment, the 5-year survival rate of advanced stage of the disease is less than 63%. The field of nanomedicine has offered promising diagnostic and therapeutic advances in cancer. Indeed, several platforms have been clinically approved for cancer therapy, while other promising systems are undergoing exploration in clinical trials. With its ability to deliver drugs, nucleic acids, and MRI contrast agents with high efficiency, nanomedicine platforms offer the potential to improve drug efficacy and tolerability. The aim of the present mini-review is to summarize the current preclinical status of nanotechnology systems for oral cancer therapy. The nanoplatforms for delivery of chemopreventive agents presented herein resulted in significantly higher anti-tumor activity than free forms of the drug, even against a chemo-resistant cell line. Impressive results have also been obtained using nanoparticles to deliver chemotherapeutics, resulting in reduced toxicity both in vitro and in vivo. Nanoparticles have also led to improvements in efficacy of photodynamic therapies through the development of targeted magnetic nanoparticles. Finally, gene therapy using nanoparticles demonstrated promising results specifically with regards to inhibition of gene expression. Of the few in vivo studies that have been reported, many of these used animal models with several limitations, which will be discussed herein. Lastly, we will discuss several future perspectives in oral cancer nanoparticle-based therapy and the development of appropriate animal models, distinguishing between oral cavity and oropharyngeal carcinoma