University of Valencia

About: University of Valencia is a education organization based out in Valencia, Spain. It is known for research contribution in the topics: Population & Neutrino. The organization has 27096 authors who have published 65669 publications receiving 1765689 citations. The organization is also known as: Universitat de València & UV.

Socio-cultural factors and entrepreneurial activity An overview

Abstract: Scholars who study entrepreneurship have lent great value by exploring the factors that explain how entrepreneurs create new businesses and thus, how societies and economies grow and prosper. Although there has considerable research based on psychological and economic approaches to entrepreneurship, the influence of socio-cultural factors on enterprise development remains under studied. Therefore, the aim of this paper is to integrate, from a theoretical perspective, the socio-cultural factors and entrepreneurial activity. In this sense, the article points out that the institutional approach could be an apt framework to develop future research analyzing the socio-cultural factors that influence the decisions to create new businesses. Also, a brief overview of the content of each of the papers included in this special issue is presented.

Anal cancer: ESMO-ESSO-ESTRO clinical practice guidelines for diagnosis, treatment and follow-up

Abstract: Squamous cell carcinoma of the anus (SCCA) is a rare cancer but its incidence is increasing throughout the world, and is particularly high in the human immunodeficiency virus positive (HIV+) population. A multidisciplinary approach is mandatory (involving radiation therapists, medical oncologists, surgeons, radiologists and pathologists). SCCA usually spreads in a loco-regional manner within and outside the anal canal. Lymph node involvement at diagnosis is observed in 30%–40% of cases while systemic spread is uncommon with distant extrapelvic metastases recorded in 5%–8% at onset, and rates of metastatic progression after primary treatment between 10 and 20%. SCCA is strongly associated with human papilloma virus (HPV, types 16–18) infection. The primary aim of treatment is to achieve cure with loco-regional control and preservation of anal function, with the best possible quality of life. Treatment dramatically differs from adenocarcinomas of the lower rectum. Combinations of 5FU-based chemoradiation and other cytotoxic agents (mitomycin C) have been established as the standard of care, leading to complete tumour regression in 80%–90% of patients with locoregional failures in the region of 15%. There is an accepted role for surgical salvage. Assessment and treatment should be carried out in specialised centres treating a high number of patients as early as possible in the clinical diagnosis. To date, the limited evidence from only 6 randomised trials [1,2,3,4,5,6,7] , the rarity of the cancer, and the different behaviour/natural history depending on the predominant site of origin, (the anal margin, anal canal or above the dentate line) provide scanty direction for any individual oncologist. Here we aim to provide guidelines which can assist medical, radiation and surgical oncologists in the practical management of this unusual cancer.

Human Capital in Growth Regressions: How much Difference Does Data Quality Make?

Abstract: We construct estimates of educational attainment for a sample of 21 OECD countries. Our series incorporate previously unexploited information and remove sharp breaks in the data that can only reflect changes in classification criteria. We then construct indicators of the information content of our estimates and a number of previously available data sets and examine their performance in several growth specifications. We find a clear positive correlation between data quality and the size and significance of human capital coefficients in growth regressions. Using an extension of the classical errors in variables model to correct for measurement error bias, we construct a set of meta-estimates of the coefficient of years of schooling in an aggregate Cobb-Douglas production function. Our results suggest that the value of this parameter is likely to be above 0.60. (JEL: O40, I20, O30, C19)

A Survey of Active Learning Algorithms for Supervised Remote Sensing Image Classification

Abstract: Defining an efficient training set is one of the most delicate phases for the success of remote sensing image classification routines. The complexity of the problem, the limited temporal and financial resources, as well as the high intraclass variance can make an algorithm fail if it is trained with a suboptimal dataset. Active learning aims at building efficient training sets by iteratively improving the model performance through sampling. A user-defined heuristic ranks the unlabeled pixels according to a function of the uncertainty of their class membership and then the user is asked to provide labels for the most uncertain pixels. This paper reviews and tests the main families of active learning algorithms: committee, large margin, and posterior probability-based. For each of them, the most recent advances in the remote sensing community are discussed and some heuristics are detailed and tested. Several challenging remote sensing scenarios are considered, including very high spatial resolution and hyperspectral image classification. Finally, guidelines for choosing the good architecture are provided for new and/or unexperienced user.