Trademark or patent? The effects of market concentration,customer type and venture capital financing on start-ups’ initial IP applications

We analyse the initial IP applications of 4,703 start-ups in the U.S., distinguishing between trademark and patent applications. Our empirical results show that start-ups are more likely to file for trademarks instead of patents when entering markets with a higher market concentration. Furthermore, we find that start-ups that are primarily active in business-to-consumer markets instead of business-to-business markets are more likely to file trademarks. Finally, the involvement of a venture capitalist (VC) affects the initial IP application. VC-backed start-ups are more likely than other start-ups to file initial IP in the form of trademarks rather than patents. This paper contributes to research on the use of IP rights in start-ups and to the literature on new venture strategy.     

Surgical treatment of morbus Menière (author''s transl)

CFW mice were injected with methylmercury hydroxide (1, 2, 3, 5 or 10 mg/kg as mercury) on Day 8 of gestation. Mice treated with 3, 5 or 10 mg/kg averaged 1/3 fewer pups than controls. Pups from these treated animals weighed less than controls and the weight differences persisted through weaning but were no longer significant at 56 days of age. Mice exposed to methylmercury in utero showed significant differences from controls in their behavior in a 2-way active avoidance shuttle box and in a punishment situation but not when tested in an open field, a water escape runaway or a conditioned suppression paradigm. Neither the mothers nor progeny of the mice exposed prenatally to methylmercury showed bahavioral deficits.     

Ergebnisse einer Evaluierung von Energiekonzepten für Bürogebäude und Schlussfolgerungen für die Energieeffizienz und das Raumklima

Evaluation of energy concepts for office buildings – results and conclusions for energy efficiency and indoor climate. Office buildings have been in the public spotlight and subject to intensive scientific research since the 1970s. The trend towards extensively glazed façades over the last 15 years added a degree of urgency to the need for research into energy efficiency and occupant comfort. The associated public scolding of architects and engineers and the – in some cases questionable – technical discussions revealed information deficits. The research project entitled “Evaluation of energy concepts for office buildings (EVA)” aimed to reduce this information deficit. Overall, 19 office buildings were examined.     

Infection and pyospermia in male infertility. Is it really a problem?

Guns in the home are a factor in pediatric unintentional and intentional firearm injuries, yet the patterns of ownership and use are unclear. OBJECTIVES. To describe the prevalence of firearms in households containing children who go to pediatricians, the types of firearms owned, the purposes of such ownership, the conditions of firearm storage, and the social correlates of ownership. METHODS. Survey of parents attending 29 (urban, suburban, and rural) pediatric practices in Chicago, New Jersey, Houston, Utah, Georgia, Iowa, and South Carolina for well or sick child care during a 1-week study period. The main outcome measure was ownership of rifle/shotgun and/or handgun. RESULTS. Gun ownership was reported by 37% of 5233 respondent families: rifles (26%), handguns (17%), and powder firearm (32%). Ownership varied significantly across practices and geographical locations. Thirteen percent of 823 handguns and 1% of 1327 rifles were reported both unlocked and loaded. Recreation was the most common reason for both rifle (75%) and handgun (59%) ownership; 48% of handguns were kept for self-protection versus 21% of rifles. In logistic regression models, predictor variables for firearm ownership included rural area, single family dwelling, at least one adult male, and fewer preschool children (for handgun and rifle); mother with at least 12 years education (for handgun), and white mother (for rifle). CONCLUSIONS. The data presented suggest that US pediatricians routinely see children in families that own firearms, including a worrisome number that keep loaded and unlocked handguns. Until more detailed information becomes available, it is reasonable for pediatricians to be guided by these data, and so to counsel routinely about gun exposure.     

A stochastic framework for K-SVD with applications on face recognition

In recent years, the sparse representation modeling of signals has received a lot of attention due to its state-of-the-art performance in different computer vision tasks. One important factor to its success is the ability to promote representations that are well adapted to the data. This is achieved by the use of dictionary learning algorithms. The most well known of these algorithms is K-SVD. In this paper, we propose a stochastic framework for K-SVD called \(\alpha\)K-SVD. The \(\alpha\)K-SVD uses a parameter \(\alpha\) to control a compromise between exploring the space of dictionaries and improving a possible solution. The use of this heuristic search strategy was motivated by the fact that K-SVD uses a greedy search algorithm with fast convergence, possibly leading to local minimum. Our approach is evaluated on two public face recognition databases. The results show that our approach yields better results than K-SVD and LC-KSVD (a K-SVD adaptation to classification) when the sparsity level is low.     

So near and yet so far: New insight into properties of some well-known classifier paradigms

This article provides some new insight into the properties of four well-established classifier paradigms, namely support vector machines (SVM), classifiers based on mixture density models (CMM), fuzzy classifiers (FCL), and radial basis function neural networks (RBF). It will be shown that these classifiers can be formulated in a way such that they are functionally equivalent or at least highly similar. The interpretation of a specific classifier as being an SVM, CMM, FCL, or RBF then only depends on the objective function and the optimization algorithm used to adjust the parameters. The properties of these four paradigms, however, are very different: a discriminative classifier such as an SVM is expected to have optimal generalization capabilities on new data, a generative classifier such as a CMM also aims at modeling the processes from which the observed data originate, and a comprehensible classifier such as an FCL is intended to be parameterized and understood by human domain experts. We will discuss the advantages and disadvantages of these properties and show how they can be measured numerically in order to compare these classifiers. In such a way, the article aims at supporting a practitioner in assessing the properties of classifier paradigms and in selecting or combining certain paradigms for a given application problem.