El papel de la experiencia en la relación entre confianza y resultados de la cooperación entre PYMEs en economías en transición

To achieve successful cooperative inter-firm relationships, trust between the partners is a key factor. As trust that is based on the self-commitment of the partners to behave in a non-opportunistic way (maxim-based trust) takes time to evolve and relies upon the cooperation experience of the partners, we expect that the positive performance impact of maxim-based trust grows over time. The purpose of this paper is to test the moderating effect of cooperation experience on the relationship between maxim-based trust and performance in the context of cooperating small and medium sized enterprises (SMEs) in two transformation economies (Czech Republic and Slovenia): Based on a sample of 124 SMEs, a moderated regression analysis reveals that trust and cooperation experience impact positively on performance. However, we could not detect a moderated relationship. We conclude that maxim-based trust may be an effective and efficent coordinating mechanism in the dynamic context of cooperating SMEs in transformation economies, but the absence of a moderating effect indicates that firms do not seem to increase the effects of maxim-based trust over time._______________________________________________La confianza es uno de los elementos principales que permiten obtener éxito en las relaciones de cooperación entre empresas. La confianza basada en el propio compromiso de las empresas and que no es fruto de un comportamiento oportunista (maxim-based trust) se desarrolla a través la experiencia en cooperación entre las empresas, por lo que surge con el tiempo. Por ello, consideramos que los efectos positivos de este tipo de confianza aumentan conforme pasa el tiempo. El objetivo de este trabajo es medir los efectos que la experiencia en cooperación provoca sobre la relación entre la confianza basada en el compromiso (maxim-based trust) and los resultados obtenidos de la misma en el caso de la colaboración entre pequeñas and medianas empresas (pymes) en dos economías en transición (República Checa and Eslovenia): El análisis de regresión moderada, basado en una muestra de 124 pymes, muestra que la confianza and la experiencia en cooperación ejercen un impacto positivo sobre los resultados, aunque no se observa relación moderada. Concluimos que la confianza basada en el compromiso (maximbased trust) puede ser un mecanismo de coordinación efectivo and eficiente en el contexto dinámico de la cooperación entre pymes en economías en transición. No obstante, la ausencia de efecto moderador indica que los efectos en las empresas de la confianza basada en la el compromiso no aumentan con el tiempo

Application Of Statistics In Engineering Technology Programs

Statistics is a critical tool for robustness analysis, measurement system error analysis, test data analysis, probabilistic risk assessment, and many other fields in the engineering world. Traditionally, however, statistics is not extensively used in undergraduate engineering technology (ET) programs, resulting in a major disconnect from industry expectations. The research question: How to effectively integrate statistics into the curricula of ET programs, is in the foundation of this paper. Based on the best practices identified in the literature, a unique “learning-by-using” approach was deployed for the Electronics Engineering Technology Program at Texas A&M University. Simple statistical concepts such as standard deviation of measurements, signal to noise ratio, and Six Sigma were introduced to students in different courses. Design of experiments (DOE), regression, and the Monte Carlo method were illustrated with practical examples before the students applied the newly understood tools to specific problems faced in their engineering projects. Industry standard software was used to conduct statistical analysis on real results from lab exercises. The result from a pilot project at Texas A&M University indicates a significant increase in using statistics tools in course projects by students.  Data from student surveys in selected classes indicate that students gained more confidence in statistics.   These preliminary results show that the new approach is very effective in applying statistics to engineering technology programs

Giants and dwarfs:the multilevel lobbying strategies of national interest organizations

The article addresses the bias in interest representation within the EU by examining the lobbying strategies of national interest organisations within the EU’s multilevel political system. Both our theoretical framework, which includes the determinants of a national interest organisation's decision to act at the EU level, and the data analysis from the INTEREURO Multi-Level Governance Module (MLG) (www.intereuro.eu) reveal three main findings. Firstly, the greatest differentiation among interest organisations (IOs) appears to be between those IOs from the older member states (Germany, the UK and the Netherlands), which exhibit above-average levels of activity, and those from the newer EU member states (Sweden, Slovenia), which exhibit below-average levels of activity. Secondly, the variations in IO activity levels are much greater from country to country than from one policy field to another. Thirdly, although the IOs from all five countries in our study are more likely to employ media and publishing strategies (information politics) than to mobilise their members and supporters (protest politics), we can still observe national patterns in their selection of strategies and in the intensity of their instrumentalisation

Exact and Approximate Stochastic Simulation of Intracellular Calcium Dynamics

In simulations of chemical systems, the main task is to find an exact or approximate solution of the chemical master equation (CME) that satisfies certain constraints with respect to computation time and accuracy. While Brownian motion simulations of single molecules are often too time consuming to represent the mesoscopic level, the classical Gillespie algorithm is a stochastically exact algorithm that provides satisfying results in the representation of calcium microdomains. Gillespie's algorithm can be approximated via the tau-leap method and the chemical Langevin equation (CLE). Both methods lead to a substantial acceleration in computation time and a relatively small decrease in accuracy. Elimination of the noise terms leads to the classical, deterministic reaction rate equations (RRE). For complex multiscale systems, hybrid simulations are increasingly proposed to combine the advantages of stochastic and deterministic algorithms. An often used exemplary cell type in this context are striated muscle cells (e.g., cardiac and skeletal muscle cells). The properties of these cells are well described and they express many common calcium-dependent signaling pathways. The purpose of the present paper is to provide an overview of the aforementioned simulation approaches and their mutual relationships in the spectrum ranging from stochastic to deterministic algorithms

Jointly Optimized Deep Neural Networks to Synthesize Monoenergetic Images from Single-Energy CT Angiography for Improving Classification of Pulmonary Embolism

Detector-based spectral CT offers the possibility of obtaining spectral information from which discrete acquisitions at different energy levels can be derived, yielding so-called virtual monoenergetic images (VMI). In this study, we aimed to develop a jointly optimized deep-learning framework based on dual-energy CT pulmonary angiography (DE-CTPA) data to generate synthetic monoenergetic images (SMI) for improving automatic pulmonary embolism (PE) detection in single-energy CTPA scans. For this purpose, we used two datasets: our institutional DE-CTPA dataset D1, comprising polyenergetic arterial series and the corresponding VMI at low-energy levels (40 keV) with 7892 image pairs, and a 10% subset of the 2020 RSNA Pulmonary Embolism CT Dataset D2, which consisted of 161,253 polyenergetic images with dichotomous slice-wise annotations (PE/no PE). We trained a fully convolutional encoder-decoder on D1 to generate SMI from single-energy CTPA scans of D2, which were then fed into a ResNet50 network for training of the downstream PE classification task. The quantitative results on the reconstruction ability of our framework revealed high-quality visual SMI predictions with reconstruction results of 0.984 ± 0.002 (structural similarity) and 41.706 ± 0.547 dB (peak signal-to-noise ratio). PE classification resulted in an AUC of 0.84 for our model, which achieved improved performance compared to other naïve approaches with AUCs up to 0.81. Our study stresses the role of using joint optimization strategies for deep-learning algorithms to improve automatic PE detection. The proposed pipeline may prove to be beneficial for

Numerical Analysis of Ca2+ Depletion in the Transverse Tubular System of Mammalian Muscle

AbstractCalcium currents were recorded in contracting and actively shortening mammalian muscle fibers. In order to characterize the influence of extracellular calcium concentration changes in the small unstirred lumina of the transverse tubular system (TTS) on the time course of the slow L-type calcium current (ICa), we have combined experimental measurements of ICa with quantitative numerical simulations of Ca2+ depletion. ICa was recorded both in calcium-buffered and unbuffered external solutions using the two-microelectrode voltage clamp technique (2-MVC) on short murine toe muscle fibers. A simulation program based on a distributed TTS model was used to calculate the effect of ion depletion in the TTS. The experimental data obtained in a solution where ion depletion is suppressed by a high amount of a calcium buffering agent were used as input data for the simulation. The simulation output was then compared with experimental data from the same fiber obtained in unbuffered solution. Taking this approach, we could quantitatively show that the calculated Ca2+ depletion in the transverse tubular system of contracting mammalian muscle fibers significantly affects the time-dependent decline of Ca2+ currents. From our findings, we conclude that ion depletion in the tubular system may be one of the major effects for the ICa decline measured in isotonic physiological solution under voltage clamp conditions

Liquid-crystalline blue phase III and structures of broken icosahedral symmetry

The structure of the liquid-crystalline blue phase III (BPIII) is still unknown and remains one of the mysteries of liquid-crystal physics. We take all icosahedral space-group symmetries of the reciprocal space for BPIII and study their thermodynamic stability within the frame of an extended de Gennes–Ginzburg–Landau free-energy expansion. The stability of the icosahedral structures is compared with that of the cholesteric phase and of the cubic blue phases. Strikingly, even though the extended model contains three extra parameters, we could not detect a region of parameter space where icosahedral structures are absolutely stable just below the isotropic phase

Biaxiality of chiral liquid crystals

Using the extended de Gennes–Ginzburg–Landau free energy expansion in terms of the anisotropic part Q αβ(x) of the dielectric tensor field, a connection between the phase biaxiality and the stability of various chiral liquid crystalline phases is studied. In particular, the cholesteric phase, the cubic blue phases, and the phases characterized by an icosahedral space group symmetry are analyzed in detail. Also, a general question concerning the applicability of the mean-field approximation in describing the chiral phases is addressed. By an extensive study of the model over a wide range of the parameters, a class of phenomena, not present in the original de Gennes–Ginzburg–Landau model, has been found. These include (a) reentrant phase transitions between the cholesteric and the cubic blue phases and (b) the existence of distinct phases of the same symmetry but of different biaxialities. The phase biaxiality serves here as an extra scalar order parameter. Furthermore, it has been shown that, due to the presence of competing bulk terms in the free energy, the stable phases may acquire a large degree of biaxiality, also in liquid crystalline materials composed of effectively uniaxial molecules. A study of icosahedral space group symmetries provides a partial answer to the question of whether or not an icosahedral quasicrystalline state can be stabilized in liquid crystals. Although, in general, the stability of icosahedral structures could be enhanced by the extra terms in the free energy, no absolutely stable icosahedral phase has been found

Identification of proteins in laser-microdissected small cell numbers by SELDI-TOF and Tandem MS

BACKGROUND: Laser microdissection allows precise isolation of specific cell types and compartments from complex tissues. To analyse proteins from small cell numbers, we combine laser-microdissection and manipulation (LMM) with mass spectrometry techniques. RESULTS: Hemalaun stained mouse lung sections were used to isolate 500–2,000 cells, enough material for complex protein profiles by SELDI-TOF MS (surface enhanced laser desorption and ionization/time of flight mass spectrometry), employing different chromatographic ProteinChip(® )Arrays. Initially, to establish the principle, we identified specific protein peaks from 20,000 laser-microdissected cells, combining column chromatography, SDS-PAGE, tryptic digestion, SELDI technology and Tandem MS/MS using a ProteinChip(® )Tandem MS Interface. Secondly, our aim was to reduce the labour requirements of microdissecting several thousand cells. Therefore, we first defined target proteins in a few microdissected cells, then recovered in whole tissue section homogenates from the same lung and applied to these analytical techniques. Both approaches resulted in a successful identification of the selected peaks. CONCLUSION: Laser-microdissection may thus be combined with SELDI-TOF MS for generation of protein marker profiles in a cell-type- or compartment-specific manner in complex tissues, linked with mass fingerprinting and peptide sequencing by Tandem MS/MS for definite characterization