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Exploring the effects of managerial behavior on stem workers' psychosocial experience /
No full textThe study intends to disclose the effect of managerial behaviour on the psychosocial experiences of STEM (science, technology, engineering, and mathematics) workers. Using two fundamental approaches to leadership – task-oriented and relationship-oriented behaviours – the paper seeks to reveal what characteristics of the two managerial behaviour styles shape positive and negative experiences of STEM workers’. To characterise employee psychological experiences in the workplace, neuroscience-based Rock’s SCARF (status, certainty, autonomy, relatedness, fairness) model was employed. A qualitative method was used, which enables an in-depth understanding of the phenomena. For this purpose, 50 STEM professionals in Lithuania participated in semi-structured interviews to collect qualitative data. The study revealed that status was one of the most sensitive psychosocial experiences of STEM workers, especially when it was positively influenced by managerial behaviour. Meanwhile, the most negative SCARF experiences of STEM workers were related to a reduced sense of fairness and relatedness. Furthermore, the study revealed both relationship- and task-oriented behaviour characteristics that positively or negatively affected the psychosocial experiences of STEM workers. STEM workers experienced more positive SCARF experiences due to the task-oriented behaviours of managers, whereas relationship-oriented managerial behaviour was mentioned more often as a cause of the formation of negative psychosocial experiences. Finally, the paper provides strong support for the assumption that the integration of both managerial behaviour styles ensures effective leadership, combining a goal-driven approach that prioritises efficiency, work organisation, and successful fulfilment of tasks
Enhancing prediction by incorporating entropy loss in volatility forecasting /
No full textIn this paper, we propose examining Heterogeneous Autoregressive (HAR) models using five different estimation techniques and four different estimation horizons to decide which performs better in terms of forecasting accuracy. Several different estimators are used to determine the coefficients of three selected HAR-type models. Furthermore, model lags, calculated using 5 min intraday data from the Standard & Poor’s 500 (SPX) index and the Chicago Board Options Exchange Volatility (VIX) index as the sole exogenous variable, enrich the models. For comparison and evaluation of the experimental results, we use three metrics: Quasi-Likelihood (QLIKE), Mean Absolute Error (MAE), and Mean Squared Error (MSE). An empirical study reveals that the Entropy Loss Function consistently achieves the best QLIKE results in all the horizons, especially in the weekly horizon. On the other hand, the performance of the Robust Linear Model implies that it can provide an alternative to the Entropy Loss Function when considering the results of the MAE and MSE metrics. Moreover, research shows that adding more informative lags, such as Realized Quarticity for the Heterogeneous Autoregressive model yielding the Realized Quarticity (HARQ) model, and incorporating the VIX index further improve the general results of the models. The results of the proposed Entropy Loss Function and Robust Linear Model suggest that they successfully achieve significant forecasting accuracy for HAR models across multiple forecasting horizons
Electron rich N-heterotriangulenes as host materials for OLEDs /
No full textTriphenylamine-based materials have been extensively studied as hole-transporting materials for organic semiconductor devices due to their high hole mobility and thermal stability. For example, they may be used as either hole-transporting layers in solar cells or p-type host materials in the emissive layer of OLEDs. Here, we present the development of a series of fused triarylamine derivatives in the form of N-heterotriangulene-based systems featuring electron-rich pendent groups and have investigated their structural properties using X-ray crystallography, and their optical and redox properties. Space-charge-limited current measurements were carried out to assess their potential to be used as p-type materials and the materials were applied as hosts in OLEDs with a solution-processed 4CzIPN-doped emissive layer. The best-performing devices exhibited a maximum external quantum efficiency of 6.9%. We have shown that the host can disperse the emitter molecules effectively and avoid dimer formation thereby enhancing OLED performance
Graphene-enhanced resonant arrays of silver nanoparticles for sustained detection of Raman signature /
No full textSurface-enhanced Raman Scattering spectroscopy has transformed trace analyte detection by harnessing localized surface plasmon resonance. Hybrid plasmonic–photonic modes have been shown to further improve enhancement factors by tailoring the resonant wavelength. Here, we use a surface lattice resonance-based platform tuned to amplify the Stokes-shifted Raman emission band produced by using capillarity-assisted Ag nanoparticle assembly. Additionally, we transferred graphene onto these substrates to evaluate its effect on the long-term retention of the analyte signal. We monitored the Raman signature of 2-naphthalenethiol on substrates with and without transferred graphene sheets over 1 year since initial exposure. Signal intensities from both the unprotected (U) and graphene-protected (G) samples were projected onto the principal components to evaluate the spectral traits and monitor how the spectra change over time. The results showed that both U and G samples initially exhibited a detection score of approximately 80%. While the U sample completely lost its Raman signal after 300 days, the G sample retained a detection score of about 30%, which remained stable even after 344 days. We attribute the retained signal on the G substrate to two phenomena: (i) graphene prevents the degradation of plasmonic particles and (ii) helps retain the analyte on the substrate. Moreover, the ratio of Raman peaks coinciding with the lattice resonance vs off-resonance peaks was higher compared to a reference measurement. This underscores the potential of graphene–silver hybrid platforms for applications requiring sustained analyte signature, where a long shelf life and prolonged detection over time could facilitate repeated measurements or continuous monitoring without the need for frequent sample replacement on site
Mechanical properties of fully recyclable 3D-printable materials used for application in patient-specific devices in radiotherapy /
No full textThe exponential growth of plastic production in the healthcare sector and the limited capacity of conventional recycling systems have created a global environmental challenge. Latest 3D printing technologies have the potential to solve this problem by enabling on-demand, localized manufacturing. This study aimed to investigate the mechanical properties of 3D-printed ABS composites with Bi2O3 fillers after multiple recycling and irradiation cycles to assess their suitability for creating robust, reusable supporting devices for radiotherapy. Filaments of PLA, ABS, and ABS composites enriched with 5 wt% and 10 wt% Bi2O3 were extruded, repeatedly recycled through shredding and re-extrusion up to ten times and irradiated to 70 Gy using a 6 MeV photon beam to simulate clinical radiotherapy conditions. In contrast to PLA, ABS demonstrated better recyclability; however, after ten recycling cycles, its tensile strength declined from 25.1 MPa to 20.9 MPa, and its Young’s modulus decreased from 2503.5 MPa to 1410.4 MPa. Incorporation of 5 wt% Bi2O3 into ABS significantly improved recyclability and mechanical retention. After ten recycling rounds, an ABS composite containing 5 wt% Bi2O3 retained tensile strength of 22.2 MPa, modulus of 1553.9 MPa, and strain at break of 14.4%. In contrast, the composite enforced with 10 wt% Bi2O3 showed slightly lower performance, likely due to filler agglomeration. Under irradiation, the ABS–5 wt% Bi2O3 composite exhibited minimal additional degradation, maintaining mechanical integrity superior to other materials. These results indicate that ABS–5 wt% Bi2O3 is a promising, recyclable material for durable, patient-specific devices in radiotherapy, supporting sustainability in medical manufacturing
Optimization of hybrid polymer matrices for enhanced mechanical and impact properties /
No full textThis research presents the optimization of preparing hybrid polymer matrices composed of thermosetting and thermoplastic to address the resistance against impact forces and mechanical characteristics of glass fiber reinforced polymer composites. A hybrid polymer composed of thermoplastic and thermoset were obtained at various ratios. A glass reinforcement in which glass microspheres were added to a thermoset resin at various percentages (0-10%) and a composite manufactured via hand layup followed by compression molding with 4 layers of fiber preserving a fiber volume fraction of 0.6. Mixture of hybrid polymers showing a better property against impact forces and mechanical features. Notably, 7-9% glass microspheres displayed an improved mechanical property, highlighting increasing in tensile strength at 7%. These results encourage the potential effect of hybrid matrices and micro-reinforcement in fabricating high featured composites considering for high impact engineering applications
Dinaminių charakteristikų ir virpesių valdymo adityviai pagamintose kompozitinėse struktūrose naudojant pjezoelektrinius vykdiklius tyrimas.
No full textThis dissertation investigates the dynamic characteristics of additively manufactured (AM) structures and develops an effective vibration control methodology by integrating macro fiber composite (MFC) actuators to suppress their vibration amplitudes. To achieve this, polylactic acid (PLA) and PLA-based composite structures including PLA reinforced with short carbon fibers (PLA-SCF), continuous carbon fibers (PLA-CCF), and continuous glass fibers (PLA-CGF) were fabricated with both unidirectional (0°–0°) and cross-ply (0°–90°) layer orientations. The influence of layer orientations on the dynamic characteristics (natural bending mode frequencies, bending mode shapes, amplitude spectrum, and damping) of each AM structure was investigated. Vibration amplitude suppression was then performed on these structures by applying a vibration control methodology using MFC actuators, identifying the orientation and structure exhibiting the maximum vibration suppression. Additionally, the effect of the signal phase (ranging from 0° to 360°) applied to the MFC actuators on the vibration amplitude was examined, and the phase that provides the maximum vibration suppression for each AM structure was determined. Non-destructive C-scanning was conducted to identify internal defects in the AM structures using the THz spectrometer (TPSTM Spectra 300 THz Pulsed Imaging and Spectroscopy from TeraView). Finally, a finite element based numerical simulation approach has been developed to study dynamic characteristics and vibration suppression behaviour of the AM structures using MFC actuators. The trends of the simulation results were thoroughly compared and validated with experimental results
Heat transfer enhancement in flue-gas systems with radiation-intensifying inserts: an analytical approach /
No full textA significant portion of energy losses in industrial systems arises from the inefficient use of high-temperature exhaust gases, emphasizing the need for enhanced heat recovery strategies. This study aims to improve energy efficiency by examining the effects of radiation-intensifying inserts on combined radiative and convective heat transfer in flue-gas heated channels. A systematic literature review revealed a research gap in understanding the interaction between these mechanisms in flue-gas heat exchangers. To address this, analytical calculations were conducted for two geometries: a radiation-intensifying plate between parallel plates and the same insert in a circular pipe. The analysis covered a range of gas-flue and wall temperatures (560–1460 K and 303–393 K, respectively), flow velocities, and spectral emissivity values. Key performance metrics included Reynolds and Nusselt numbers to assess flow resistance and heat transfer. Results indicated that flue-gas temperature has the most significant effect on total rate of heat transfer, and the insert significantly enhanced radiative heat transfer by over 60%, increasing flow resistance. A local Nusselt number minimum at a length-to-diameter ratio of approximately 26 suggested transitional flow behavior. These results provide valuable insights for the design of high-temperature heat exchangers, with future work planned to validate the findings experimentally
Sustainable innovations in Kurut drink production through replacing water with dairy whey to improve nutritional quality /
No full textThis study investigates a sustainable innovation in traditional Kurut drink production, providing insights into integrating environmental and nutritional strategies into the dairy industry. The objective was to conserve drinking water, valorize dairy whey and its permeate, and enhance the nutritional properties of the final product. Kurut, sourced from a manufacturing plant in Kyrgyzstan, was processed using methods replicating factory production with various liquid mediums. Physicochemical and sensory properties of water-based Kurut were compared with samples made using acid whey, sweet whey, and their permeates. Results showed that acid whey and its permeates improved consumer preference over water-based Kurut, offering a sustainable method to reduce waste and enhance product value. Whey incorporation enriched the amino acid profile, boosting essential nutrients. Although slightly less preferred, sweet whey-based Kurut contained higher mono- and polyunsaturated fatty acids, appealing to heart-health-focused markets. This innovation reinvents a traditional drink, restoring its milk-derived nutritional value and providing a viable pathway for the dairy industry to create sustainable, nutritious, and health-oriented products. The findings demonstrate how traditional practices can integrate modern sustainability and nutritional strategies to address environmental and consumer needs
Multi-stage neural network-based ensemble learning approach for wheat leaf disease classification /
No full textPrompt and accurate classification of wheat leaf diseases and their severity is essential for precise diagnosis, effective pesticide application, efficient disease control, and enhanced wheat production and quality. Nevertheless, the wide range of wheat diseases poses a significant challenge in terms of their identification, especially in intricate agricultural landscapes. The utilization of conventional models has major limitations in wheat disease detection, including dataset-specific performance, overfitting due to limited data, and high computational needs, making deployment in resource-constrained situations difficult. To address these challenges, this research proposes a multi-stage Convolutional Neural Network (CNN) based Ensemble Learning (EL) approach, which utilizes several concurrent CNN models with a bagged EL method to classify wheat leaf diseases. The various stages in the EL approach employ a multi-level framework to enhance feature extraction and capture complex data patterns. This improves the model’s emphasis on diseases while reducing the influence of complex backgrounds on disease identification. The proposed method, integrating pretrained CNNs and a bagging ensemble technique, achieved an accuracy of 86.78%, 98.28%, and 99.16% on the three publicly available datasets, outperforming the state-of-the-art models. These results demonstrate the potential of the proposed model for real-time disease diagnosis