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Histopathological diagnosis using Formalin-Fixed Paraffin Embedded (FFPE) tissues is essential for the prognostic and therapeutic management of cancer patients. Pathologists are being confronted with increasing demands, from both clinicians and patients, to provide immunophenotypic and gene expression data from FFPE tissues to allow the planning of personalized therapeutic regimens. Recent improvements in the protocols for pre-analysis processing of pathological tissues aim to better preserve cellular details and to conserve antigens and nucleic acid sequences. These developments have been recently patented. The international protocol for the transporting of surgical specimens from the surgical theatre to the pathology department is to immerse the specimen in formalin. The alternative method of sealing the specimens into bags under a vacuum and then cooling is a well-accepted and environmentally safe procedure that overcomes the many drawbacks linked to transfer in formalin. Importantly, RNA is notoriously poorly preserved in FFPE tissue. Due to this, successful procedures for the extraction of genetic information from archival tissues have been the object of several studies and patents. Novel molecular approaches for RT-qPCR and gene array analysis on FFPE tissues are presented here. Moreover, a major advance is reported in this study, the observation that tissue fixation in cold conditions allows a much better preservation of nucleic acid sequences.

Abstract This paper presents the development of a finite element model used to numerically investigate the behaviour of an innovative defective tube isolation device. The high-speed plastic deformation by electro-hydraulic shock was proposed for plug installing in a steam generator tube simulator. The objective of the study was to evaluate the influence of the geometrical, material and hydraulic shock parameters upon the performance of the plugging procedure using an advanced 3-dimensional simulation model created in LS-DYNA general code. The computational model employs the Johnson–Cook plasticity model for SS321 to study the high strain rate, elastic–plastic dynamics of the process. The results of the simulations compared against experimental data have shown the great influence of the model parameters uncertainties on the success of the plug installation.

The paper introduces a step-down converter that exhibits a static conversion ratio of cubic nature, providing an output voltage which is much closer to the input voltage, and at the same duty cycle, compared to a wide class of one-transistor buck-type topologies. Although the proposed topology contains many components, its control is still simple, as it employs only one transistor. A dc analysis is performed, the semiconductor stresses are derived in terms of input and output voltages and output power, revealing that the semiconductor voltage stresses remain acceptable and anyway lower than in other cubic buck topology. All detailed design equations are provided. The state-space approach is used to analyze the converter in the presence of conduction losses and a procedure for calculating the individual power dissipation is provided. The feasibility of the proposed cubic buck topology is first validated by computer simulation and finally confirmed by an experimental 12 V–10 W prototype.

This study offers a comprehensive examination, both theoretically and experimentally, of the potential of methanol (M) as a sustainable aviation fuel (SAF) assessed in combination with kerosene (Ke—Jet-A aviation fuel + 5% Aeroshell oil). Different blends of methanol and kerosene (10%, 20%, and 30% vol. of (M) was added to Ke) were tested in an aviation micro turbo-engine under various operating regimes, such as idle, cruise, and maximum. Key engine parameters, including combustion temperature, fuel consumption, and thrust, were closely monitored during these trials. Essential performance indicators such as combustion efficiency, thermal efficiency, and specific consumption for all fuel blends under maximum operating conditions are also presented. Physical and chemical characteristics, such as viscosity, density, calorific value and flash point, were determined for each blend. Moreover, elemental analysis and FTIR spectroscopy were utilized to evaluate the chemical composition of the fuels. This study further investigated the air requirements for stoichiometric combustion and computed the resulting CO2 and H2O emissions. Experimental tests were conducted on the Jet Cat P80® micro turbo-engine, covering assessments of starting procedures, acceleration, deceleration, and pollutant emissions (CO and SO2) during various engine operating conditions. The results suggest that the examined fuel blends demonstrate stable engine performance at concentrations of 10% and 20% methanol. However, observations indicate that with an increase in methanol concentration, particularly at 30%, the stability of the engine at idle and, notably, at maximum speed decreases significantly. Specifically, at a 30% methanol concentration, the engine no longer operates stably, exhibiting significant rpm fluctuations, leading to the decision not to explore higher concentrations.

In recent years, the renewable energy had an increasing impact on the power systems operation conditions. The specialists are therefore focusing on identifying reliable solutions that can increase the safety in operation and improve the stability reserves. Robust algorithms that may provide effective solutions are thereby sought. This paper presents an algorithm based on which the steady-state stability limits is calculated for both N and N-1 conditions. A case study is performed using the Romanian power system characteristics.

Nowadays, companies are in the process of renewing their manufacturing lines by equipping them with modern five-axis CNC (computer numerical control) machining centers. The decision to select between different five-axis CNC machining centers, with similar technological capabilities is a difficult process, so the main goal of this work was to develop a method for assisting it. The proposed approach relies on seven technical criteria, four quantitative ones (traverse speed, thrust, spindle power, and spindle speed) which can be expressed by crisp numerical values, while the other three (flexibility, operation easiness, and setup time) are qualitative ones. The analytic hierarchy process (AHP) was used for ordering four variants of five-axis CNC milling machining centers. The qualitative criteria were processed using fuzzy systems to be expressed by crisp numerical values, suitable for AHP. Finally, the four variants of five-axis CNC milling machining centers were hierarchized and the best one was chosen. A sensitivity analysis was also unfolded to certify the robustness of the AHP.

The aim of this study was to determine whether emotional labor behavior has an effect on job satisfaction, and if there is an effect, to reveal whether communicative rational action has a moderator effect. This research was carried out in the banking sector. The sample group consisted of administrators of foreign capital bank managers (427) at all levels in Turkey. The collected data were analyzed with the IBM SPSS 21 program. Multiple regression analysis and SPSS PROCESS v3.5 (model1) methods were used in the analysis. According to the analysis, the three sub-dimensions of communicative rational action (practical-rational action, rational communication, and rational action) have a moderator role in the effect of emotional labor and job satisfaction. The other two sub dimensions (value–rational–action and firm family) do not have a moderator role in this effect. In the analysis made according to the total score of communicative rational action, the moderator role of communicative rational action in the effect of emotional labor and job satisfaction was determined. As a result of the research and analysis, it was determined that emotional labor has a positive effect on the phenomenon of job satisfaction.

Alpine grasslands on the Qinghai-Tibetan Plateau are sensitive and vulnerable to climate change and human activities. Climate warming and overgrazing have already caused degradation in a large fraction of alpine grasslands on this plateau. However, it remains unclear how human activities (mainly livestock grazing) regulates vegetation dynamics under climate change. Here, alpine grassland productivity (substituted with the normalized difference vegetation index, NDVI) is hypothesized to vary in a nonlinear trajectory to follow climate fluctuations and human disturbances. With generalized additive mixed modelling (GAMM) and residual-trend (RESTREND) analysis together, both magnitude and direction of climatic (in terms of temperature, precipitation, and radiation) and anthropogenic impacts on NDVI variation were examined across alpine meadows, steppes, and desert-steppes on the Qinghai-Tibetan Plateau. The results revealed that accelerating warming and greening, respectively, took place in 76.2% and 78.8% of alpine grasslands on the Qinghai-Tibetan Plateau. The relative importance of temperature, precipitation, and radiation impacts was comparable, between 20.4% and 24.8%, and combined to explain 66.2% of NDVI variance at the pixel scale. The human influence was strengthening and weakening, respectively, in 15.5% and 14.3% of grassland pixels, being slightly larger than any sole climatic variable across the entire plateau. Anthropogenic and climatic factors can be in opposite ways to affect alpine grasslands, even within the same grassland type, likely regulated by plant community assembly and species functional traits. Therefore, the underlying mechanisms of how plant functional diversity regulates nonlinear ecosystem response to climatic and anthropogenic stresses should be carefully explored in the future.

A broad range of intelligent metering solutions in the form of Automated Meter Reading (AMR) or Advanced Metering Infrastructure (AMI) are used today in electrical networks to meet the challenges posed by the development of electricity markets. In parallel, Load Profiling (LP-ing) techniques based on intelligent software solutions, can be used to support market access of small consumers who are not equipped with digital meters. This paper proposes a new approach to the LP clustering problem based on the Honey-Bee Mating Optimization (HBMO) algorithm. The results show a good behavior of the proposed algorithm in terms of robustness and stability with respect to the structure of the database. The proposed approach requires fewer parameters to be calibrated, in comparison with other alternative methods.