The use of Artificial Neural Networks to adjust and robustness study of experience tables of maintenance in disability

Pricing and, more important, reserving "life / death" and "disability" risks are strictly defined by the regulation, which imposes particular constraints on the technical rate and the laws of occurrence or maintenance. However, the assessment of portfolios reserving differs from the standard one proposed by the BCAC. Insurance companies are increasingly forced toseek the construction of experience tables to manage these risks, especially since it is unrealistic today to expect offset losses by financial products. Traditional adjustment methods, in actuarial literature, usually used to smooth the recovery curve rate estimated usually by the robust Adjusted Kaplan‐Meier estimator, induce a model error due a boundary bias. The available data are usually sparse and poor quality on the border. Thus a boundary bias is due to weight allocation by the fixed symmetric argument outside the support of the gross curve, when smoothing close to the boundary is carried out. The objective of this work is the use of Artificial Neural Networks (ANN) for adjustment and smoothing experience tables of maintenance in disability applied to a two cycles real set data. The artificial neural networks are parametric nonlinear models able to play an "universal approximator" role achieving a local and global approximation. Two architectures networks are particularly suited to model and smooth gross output rates: Feedforward Neural Networks (FNN) and Radial Basis Functions (RBF) Networks. The robustness of the ANN globally and especially at the edge of curve can be also studied. Graphical tests are used to compare output surfaces rates obtained by neural networks with those obtained by Whittaker‐Henderson framework

Étude comparative des performances en production de quelques générations de Solanum tuberosum consommées au Maroc

La qualité des tubercules de différentes générations de pomme de terre issues de la variété française Désirée est étudiée par différentes méthodes statistiques. Quelque soit la génération, la germination de tubercules est contrôlée par la température, l’humidité relative et l’hydratation des tubercules. Une corrélation positive existe entre le calibre, le poids des tubercules et la formation des germes; cette dernière est réduite à partir de la 3ème génération probablement à cause d’une différenciation excessive des cellules composant les tubercules et de leur manque en réserves énergétiques. Aucune différence significative n’est décelée entre les trois premières générations qui se sont montrées homogènes pour les calibres, les poids, la différenciation des cellules et leur teneur en grains d’amidon. Au-delà de la 3ème génération des différences notables entre les tubercules sont observées et la production est réduite. Toutes les générations sont sensibles au stress hydrique, mais ce sont les générations âgées qui sont les plus vulnérables à un manque d’eau et à une attaque par les micro-organismes

BIG HEALTH DATA: A SYSTEMATIC MAPPING STUDY

The Big Data, a result of the digital revolution, offers several opportunities in the field of health. Indeed, appliances and applications permanently connected to humans and the global digitalization of medical documents produce a vast health data: "Big Health Data". This data is the subject of several projects in the world given the opportunities offered to optimize this area. This paper focuses on quantifying the production of scientific articles about Big Health Data research and the most investigated Big Health Data topics. It also presents a mapping of countries producing articles about this subject. In remote sensing using real time categories, we aimed to quantify articles dealing with “big data architectures”, technologies and data sources used. A systematic mapping study was conducted with a set of seven research questions by investigating articles from two digital libraries: Scopus and Springer. The study concern articles published in 2017 and the first half of 2018. The results are illustrated by diagrams answering each question from which a set of recommendations are concluded in this area of research. The study shows that this Data is used the most in studies of oncology. Statistics show that while remote sensing and monitoring is a hot topic, real-time use is not as interesting. It was found that there’s a lack in studies interested in big data technologies used in real time remote sensing in the field of health. In conclusion, we recommend more focus on research area treating architecture in remote sensing real time Big Health Data systems combined with geolocation

TRPV6 Determines the Effect of Vitamin D3 on Prostate Cancer Cell Growth

Despite remarkable advances in the therapy and prevention of prostate cancer it is still the second cause of death from cancer in industrialized countries. Many therapies initially shown to be beneficial for the patients were abandoned due to the high drug resistance and the evolution rate of the tumors. One of the prospective therapeutical agents even used in the first stage clinical trials, 1,25-dihydroxyvitamin D3, was shown to be either unpredictable or inefficient in many cases. We have already shown that TRPV6 calcium channel, which is the direct target of 1,25-dihydroxyvitamin D3 receptor, positively controls prostate cancer proliferation and apoptosis resistance (Lehen'kyi et al., Oncogene, 2007). However, how the known 1,25-dihydroxyvitamin D3 antiproliferative effects may be compatible with the upregulation of pro-oncogenic TRPV6 channel remains a mystery. Here we demonstrate that in low steroid conditions 1,25-dihydroxyvitamin D3 upregulates the expression of TRPV6, enchances the proliferation by increasing the number of cells entering into S-phase. We show that these pro-proliferative effects of 1,25-dihydroxyvitamin D3 are directly mediated via the overexpression of TRPV6 channel which increases calcium uptake into LNCaP cells. The apoptosis resistance of androgen-dependent LNCaP cells conferred by TRPV6 channel is drastically inversed when 1,25-dihydroxyvitamin D3 effects were combined with the successful TRPV6 knockdown. In addition, the use of androgen-deficient DU-145 and androgen-insensitive LNCaP C4-2 cell lines allowed to suggest that the ability of 1,25-dihydroxyvitamin D3 to induce the expression of TRPV6 channel is a crucial determinant of the success or failure of 1,25-dihydroxyvitamin D3-based therapies

Impact of peanut shells, olive pomace, and plaster on the dielectric properties of PA6

Polyamide 6 (PA6) is among the most widely used technical polymers due to its excellent balance between performance and cost. The diversity of its applications reflects its main qualities (good mechanical properties, thermal stability, resistance to many solvents and bases, etc.). PA6 is often used as an electrical insulator, and in this study, we have shown that we can keep this property by using Plaster (PL) as reinforcement, just as we can by incorporating bio-reinforcements including peanut shell powder (PSP) or olive pomace powder (OPP) to modify this behavior. This was achieved by studying the electrical and dielectric properties of PA6 and PA6/PSP, PA6/OPP, and PA6/PL composites using impedance spectroscopy in the glass transition region ranging from 20°C to 50°C in a range frequency 1Hz - 1MHz. The results show that the PA6/PSP and PA6/OPP composites exhibited low resistance; therefore, very good electrical conductivity was recorded. However, PA6/PL inherits almost the same characteristics as PA6. The present study asserts that the presence of charges in the composite's interfacial region greatly influences the electrical and dielectric behavior and that this behavior is strongly affected near the Tg