79 research outputs found
Investigation of Allotropic ß→α-Sn Transition in High Tin Content Solder Alloys with Different Microscopy and Spectroscopy Techniques
In the microelectronics, β-Sn (white tin) is the base material of the solder alloys and surface finishes. The so-called “tin pest” phenomenon is the spontaneous allotropic transition of ß-Sn to the semiconductor α-Sn (gray tin) below 13.2°C. In this work, different microscopy and spectroscopy techniques were applied to characterize the tin pest phenomenon in the case of different solder alloys and inoculator materials as well as to study the applicability of these techniques in tin pest research. The optical imaging technique was used to compare the surface marks of the allotropic transition in the case of different inoculator materials. The development of the transition towards the sample bodies was studied on metallurgical cross-sections. Electrical resistance measurements were applied to determine the different phases of the transition in the case of different alloys and inoculators. The grain sliding and α -Sn expansion during the transition was observed by scanning electron microscopy and focused ion beam - scanning ionic microscopy. The ratio of the transitioned tin and the duration of the transition process was determined by Mössbauer spectroscopy. Our results have shown that the transition phases can considerably differ at the different alloys and inoculators, like different nucleation, growth, and the saturation phase. The accurate characterization of the transition in the given material combinations is possible only with the combined application of the applied analytical methods
Production Technology and Competitiveness In the Hungarian Manufacturing Industry
Following the big transformations of the 1990s, enterprise structure and technological level seem to
have become stabilised in Hungary. Under these circumstances it is especially interesting to identify
the elements responsible for competitiveness in general, and the role technology plays in development
in particular, according to managers experienced in production and marketing. This empirical
study – based on in-depth interviews and field research – summarises characteristics of the technological
level in the sectors examined, role of technology and labour in production, effects of foreign
direct investment, relations between competition and firm-level factors determining competitiveness,
and concludes by summing up those most frequently mentioned proposals that should be incorporated
into economic policy according to managers. Main findings indicate that more qualified,
more intensive and cheaper labour can be substituted for high technology. The competitiveness of an
enterprise is not determined by technology alone, but rather by a combination of technology, the parameters
of available labour and the costs of investment increasing productivity. The insufficiency
of inter-company relations, together with a shortage of available assets necessary for investment
constitute the major threat undermining the competitiveness of enterprises in present-day Hungary
Statistical mechanics of spatial evolutionary games
We discuss the long-run behavior of stochastic dynamics of many interacting
players in spatial evolutionary games. In particular, we investigate the effect
of the number of players and the noise level on the stochastic stability of
Nash equilibria. We discuss similarities and differences between systems of
interacting players maximizing their individual payoffs and particles
minimizing their interaction energy. We use concepts and techniques of
statistical mechanics to study game-theoretic models. In order to obtain
results in the case of the so-called potential games, we analyze the
thermodynamic limit of the appropriate models of interacting particles.Comment: 19 pages, to appear in J. Phys.
Application of spatio-temporal data in site-specific maize yield prediction with machine learning methods
In order to meet the requirements of sustainability and to determine yield drivers and limiting factors, it is now more likely that traditional yield modelling will be carried out using artificial intelligence (AI). The aim of this study was to predict maize yields using AI that uses spatio-temporal training data. The paper has advanced a new method of maize yield prediction, which is based on spatio-temporal data mining. To find the best solution, various models were used: counter-propagation artificial neural networks (CP-ANNs), XY-fused Querynetworks (XY-Fs), supervised Kohonen networks (SKNs), neural networks with Rectangular Linear Activations (ReLU), extreme gradient boosting (XGBoost), support-vector machine (SVM), and different subsets of the independent variables in five vegetation periods. Input variables for modelling included: soil parameters (pH, P2O5, K2O, Zn, clay content, ECa, draught force, Cone index), micro-relief averages, and meteorological parameters for the 63 treatment units in a 15.3 ha research field. The best performing method (XGBoost) reached 92.1% and 95.3% accuracy on the training and the test sets. Additionally, a novel method was introduced to treat individual units in a lattice system. The lattice-based smoothing performed an additional increase in Area under the curve (AUC) to 97.5% over the individual predictions of the XGBoost model. The models were developed using 48 different subsets of variables to determine which variables consistently contributed to prediction accuracy. By comparing the resulting models, it was shown that the best regression model was Extreme Gradient Boosting Trees, with 92.1% accuracy (on the training set). In addition, the method calculates the influence of the spatial distribution of site-specific soil fertility on maize grain yields. This paper provides a new method of spatio-temporal data analyses, taking the most important influencing factors on maize yields into account
The Gifted and Gifted Education in Hungary
The real challenge is to see value that is not yet in its true form. Becoming gifted is a process, during which characteristics of giftedness are present throughout, but not necessarily in a form perceptible or acceptable to the environment. Giftedness does not hide itself, only to the extent that the environment believes it hidden. Perception defines the pattern that manifests itself.
The beginning of the 20th century is a success story of Hungarian gifted education. Outstanding teachers and their students have reached outstanding achievements through gifted education linked to everyday education. Their methods and ideas are durable, and are therefore worth recalling
Demonstration of Metabolic and Cellular Effects of Portal Vein Ligation Using Multi-Modal PET/MRI Measurements in Healthy Rat Liver.
OBJECTIVES: In the early recognition of portal vein ligation (PVL) induced tumor progression, positron emission tomography and magnetic resonance imaging (PET/MRI) could improve diagnostic accuracy of conventionally used methods. It is unknown how PVL affects metabolic patterns of tumor free hepatic tissues. The aim of this preliminary study is to evaluate the effect of PVL on glucose metabolism, using PET/MRI imaging in healthy rat liver. MATERIALS AND METHODS: Male Wistar rats (n = 30) underwent PVL. 2-deoxy-2-(18F)fluoro-D-glucose (FDG) PET/MRI imaging (nanoScan PET/MRI) and morphological/histological examination were performed before (Day 0) and 1, 2, 3, and 7 days after PVL. Dynamic PET data were collected and the standardized uptake values (SUV) for ligated and non-ligated liver lobes were calculated in relation to cardiac left ventricle (SUVVOI/SUVCLV) and mean liver SUV (SUVVOI/SUVLiver). RESULTS: PVL induced atrophy of ligated lobes, while non-ligated liver tissue showed compensatory hypertrophy. Dynamic PET scan revealed altered FDG kinetics in both ligated and non-ligated liver lobes. SUVVOI/SUVCLV significantly increased in both groups of lobes, with a maximal value at the 2nd postoperative day and returned near to the baseline 7 days after the ligation. After PVL, ligated liver lobes showed significantly higher tracer uptake compared to the non-ligated lobes (significantly higher SUVVOI/SUVLiver values were observed at postoperative day 1, 2 and 3). The homogenous tracer biodistribution observed before PVL reappeared by 7th postoperative day. CONCLUSION: The observed alterations in FDG uptake dynamics should be taken into account during the assessment of PET data until the PVL induced atrophic and regenerative processes are completed
In depth evaluation of the prognostic and predictive utility of PTEN immunohistochemistry in colorectal carcinomas: performance of three antibodies with emphasis on intracellular and intratumoral heterogeneity.
BACKGROUND: Phosphatase and tensin homolog deleted in chromosome 10 (PTEN) loss of function is frequently detected in advanced colorectal cancer. Its detection is thought to have prognostic significance and it is being considered to predict responsiveness to anti-EGFR therapy. Unfortunately, while immunohistochemical assessment of PTEN expression is widespread, it lacks standardization and the results are hardly comparable across the available publications. METHODS: Retrospectively collected, formalin-fixed and paraffin-embedded colorectal tumor tissue samples from 55 patients were combined into tissue microarray (TMA) blocks. We used three different PTEN antibodies to determine the frequency, intensity and intracellular pattern of PTEN immunohistochemical labeling: Neomarkers, Dako and CellSignaling. We evaluated the aforementioned parameters in selected regions of colorectal cancers and in their lymph node metastases by using three scoring methods that take into consideration both staining frequency and intensity (H1-H3-score). We also evaluated intracellular localization. RESULTS: The Dako and CellSignaling antibodies stained predominantly cytoplasms, while the Neomarkers antibody specifically stained cell nuclei. PTEN H-scores were significantly lower in all tumor areas as compared to the normal colonic mucosa based on staining with the DAKO and CellSignaling antibodies. Intratumoral regional differences or differences between matching tumors and metastases were not detected with any of the antibodies. Neither Dako, neither CellSignaling, nor the Neomarkers antibodies revealed a significant correlation between PTEN expression and pT, Dukes/MAC and clinical stage. KRAS status, histological grade correlated with PTEN H-scores based on staining with the Neomarkers antibody. PTEN H-scores did not correlate with MMR status. PTEN H-scores did not show any correlation with relapse-free survival based on staining with either antibody. CONCLUSIONS: While PTEN expression decreased in colorectal cancer according to two antibodies, neither of the three applied PTEN antibodies could justify significant correlation with clinicopathological data, nor had prognostic value. Thus, we might conclude that immunohistochemical PTEN investigation remains a challenge requiring more standardized evaluation on larger number of cases to clarify its utility as a prognostic and predictive tool in CRC. The standardization of immunohistochemical method is key in the evaluation process, which is further discussed
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