Research on effectiveness of technology transfer in technology alliances: Evidence from Turkish SMEs

Many SMEs homed in newly industrialised countries are successful international players despite limited technological infrastructure and R&D resources. This study bridges a gap in the extant literature by examining the relationships between characteristics of partnership relationships, knowledge sharing and the effectiveness of technology transfer in partnerships between SMEs in developing countries and firms from developed countries. By studying data from Turkish SMEs and using partial least squares structural equation modelling, we find that explicit knowledge sharing forms the basis of technology transfer. Moreover, our findings demonstrate that explicit knowledge sharing is strongly contingent upon formalised technical support while trust and technical support seemed to be important antecedents of tacit knowledge sharing

A bronze mirror with Aphrodite and Eros from Nicomedia in Bithynia (northwestern Turkey)

The Archeological and Ethnographical Museum of Kocaeli has in its collection a small, disc–shaped bronze mirror decorated with a relief scene, whose protagonist is the goddess Aphrodite. The scene shows Aphrodite seated left of centre on a rock. She is accompanied by two figures, a female who stands on a pedestal in front of her and her young son, Eros, who is behind her. This formerly unpublished object was found in Nicomedia in Bithynia, and has been dated to the fourth century BC. This paper will give a detailed presentation of the mirror relief scene, focus on its art–historical contextualisation and argue a first century BC. date for this object

Characterizing the optical nature of the blazar S5 1803+784 during its 2020 flare

We report the results from our study of the blazar S5 1803+784 carried out using the quasi-simultaneous $B$, $V$, $R$, and $I$ observations from May 2020 to July 2021 on 122 nights. Our observing campaign detected the historically bright optical flare during MJD 59063.5$-$MJD 59120.5. We also found the source in its brightest ($R_{mag}$= 13.617) and faintest ($R_{mag}$= 15.888) states till date. On 13 nights, covering both flaring and non-flaring periods, we searched for the intraday variability using the power-enhanced $F-$test and the nested ANOVA test. We found significant variability in 2 out of these 13 nights. However, no such variability was detected during the flaring period. From the correlation analysis, we observed that the emission in all optical bands were strongly correlated with a time lag of $\sim$ 0 days. To get insights into its dominant emission mechanisms, we generated the optical spectral energy distributions of the source on 79 nights and estimated the spectral indices by fitting the simple power law. Spectral index varied from 1.392 to 1.911 and showed significant variations with time and $R-$band magnitude. We have detected a mild bluer-when-brighter trend (BWB) during the whole monitoring period while a much stronger BWB trend during the flare. We also carried out a periodicity search using four different methods and found no significant periodicity during our observation duration. Based on the analysis during the flaring state of the source one can say that the emissions most likely originate from the jet rather than the accretion disk.Comment: 17 pages, 8 figures, 7 tables, accepted for publication in The Astrophysical Journal (ApJ

On the critical level-curvature distribution

The parametric motion of energy levels for non-interacting electrons at the Anderson localization critical point is studied by computing the energy level-curvatures for a quasiperiodic ring with twisted boundary conditions. We find a critical distribution which has the universal random matrix theory form ${\bar P}(K)\sim |K|^{-3}$ for large level-curvatures $|K|$ corresponding to quantum diffusion, although overall it is close to approximate log-normal statistics corresponding to localization. The obtained hybrid distribution resembles the critical distribution of the disordered Anderson model and makes a connection to recent experimental data.Comment: 4 pages, 3 figure

A network biology approach to prostate cancer

There is a need to identify genetic mediators of solid-tumor cancers, such as prostate cancer, where invasion and distant metastases determine the clinical outcome of the disease. Whole-genome expression profiling offers promise in this regard, but can be complicated by the challenge of identifying the genes affected by a condition from the hundreds to thousands of genes that exhibit changes in expression. Here, we show that reverse-engineered gene networks can be combined with expression profiles to compute the likelihood that genes and associated pathways are mediators of a disease. We apply our method to non-recurrent primary and metastatic prostate cancer data, and identify the androgen receptor gene (AR) among the top genetic mediators and the AR pathway as a highly enriched pathway for metastatic prostate cancer. These results were not obtained on the basis of expression change alone. We further demonstrate that the AR gene, in the context of the network, can be used as a marker to detect the aggressiveness of primary prostate cancers. This work shows that a network biology approach can be used advantageously to identify the genetic mediators and mediating pathways associated with a disease

An evolving network model with community structure

Many social and biological networks consist of communities—groups of nodes within which connections are dense, but between which connections are sparser. Recently, there has been considerable interest in designing algorithms for detecting community structures in real-world complex networks. In this paper, we propose an evolving network model which exhibits community structure. The network model is based on the inner-community preferential attachment and inter-community preferential attachment mechanisms. The degree distributions of this network model are analysed based on a mean-field method. Theoretical results and numerical simulations indicate that this network model has community structure and scale-free properties

A preferential attachment model with random initial degrees

In this paper, a random graph process ${G(t)}_{t\geq 1}$ is studied and its degree sequence is analyzed. Let $(W_t)_{t\geq 1}$ be an i.i.d. sequence. The graph process is defined so that, at each integer time $t$, a new vertex, with $W_t$ edges attached to it, is added to the graph. The new edges added at time t are then preferentially connected to older vertices, i.e., conditionally on $G(t-1)$, the probability that a given edge is connected to vertex i is proportional to $d_i(t-1)+\delta$, where $d_i(t-1)$ is the degree of vertex $i$ at time $t-1$, independently of the other edges. The main result is that the asymptotical degree sequence for this process is a power law with exponent $\tau=\min\{\tau_{W}, \tau_{P}\}$, where $\tau_{W}$ is the power-law exponent of the initial degrees $(W_t)_{t\geq 1}$ and $\tau_{P}$ the exponent predicted by pure preferential attachment. This result extends previous work by Cooper and Frieze, which is surveyed.Comment: In the published form of the paper, the proof of Proposition 2.1 is incomplete. This version contains the complete proo

Paying for parking : improving stated-preference surveys

This article describes an experiment which introduced random ranges into the variables used for the design of a stated preference survey and its effects on willingness to pay for parking. User behaviour at the time of parking was modelled to determine their willingness to pay in order to get to their final destination more quickly. Calculating willingness to pay is fundamental during the social and economic assessment of projects. It is important to correctly model how car parks and their users interact in order to get values which represent reality as closely as possible. Willingness to pay is calculated using a stated preference survey and by calibrating multinomial logit models, taking variable tastes into account. It is shown that a value with a low variability can be obtained for willingness to pay by correctly establishing the context of the choice and randomly changing the variables around an average value