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  • Screening stability, thermochemistry, and chemical kinetics of 3-hydroxybutanoic acid as a bifunctional biodiesel additive
    • Mohamed A. Abdel-Rahman
    • Abolfazl Shiroudi
    • Jacek Czub
    • Hao Zhao
    2024 Pełny tekst JOURNAL OF PHYSICAL CHEMISTRY A

    The thermo-kinetic aspects of 3-hydroxybutyric acid (3-HBA) pyrolysis in the gas phase were investigated using density functional theory (DFT), specifically the M06-2X theoretical level in conjunction with the cc-pVTZ basis set. The obtained data were compared with benchmark CBS-QB3 results. The degradation mechanism was divided into 16 pathways, comprising 6 complex fissions and 10 barrierless reactions. Energy profiles were calculated and supplemented with computations of rate coefficients and branching ratios over the temperature range of 600–1700 K at a pressure of 1 bar using transition state theory (TST) and Rice–Ramsperger–Kassel–Marcus (RRKM) methods. Thermodynamics results indicated the presence of six stable conformers within a 4 kcal mol–1 energy range. The estimated chemical kinetics results suggested that TST and RRKM approaches are comparable, providing confidence in our calculations. The branching ratio analysis reveals that the dehydration reaction pathway leading to the formation of H2O and CH3CH═CHCO2H dominates entirely at T ≤ 650 K. At these temperatures, there is a minor contribution from the simple homolytic bond fission reaction, yielding related radicals [CH3•CHOH + •CH2CO2H]. However, at T ≥ 700 K, this reaction becomes the primary decomposition route. At T = 1700 K, there is a minor involvement of a reaction pathway resulting in the formation of CH3CH(OH)•CH2 + •CHO(OH) with an approximate contribution of 16%, and a reaction leading to [•CH3 + •CH2OHCH2CO2H] with around 9%.

  • Segmentation-Based BI-RADS ensemble classification of breast tumours in ultrasound images
    • Maciej Bobowicz
    • Mikołaj Badocha
    • Katarzyna Gwozdziewicz
    • Marlena Rygusik
    • Paulina Kalinowska
    • Edyta Szurowska
    • Tomasz Dziubich
    2024 Pełny tekst INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS

    Background: The development of computer-aided diagnosis systems in breast cancer imaging is exponential. Since 2016, 81 papers have described the automated segmentation of breast lesions in ultrasound images using arti- ficial intelligence. However, only two papers have dealt with complex BI-RADS classifications. Purpose: This study addresses the automatic classification of breast lesions into binary classes (benign vs. ma- lignant) and multiple BI-RADS classes based on a single ultrasonographic image. Achieving this task should reduce the subjectivity of an individual operator’s assessment. Materials and Methods: Automatic image segmentation methods (PraNet, CaraNet and FCBFormer) adapted to the specific segmentation task were investigated using the U-Net model as a reference. A new classification method was developed using an ensemble of selected segmentation approaches. All experiments were performed on publicly available BUS B, OASBUD, BUSI and private datasets. Results: FCBFormer achieved the best outcomes for the segmentation task with intersection over union metric values of 0.81, 0.80 and 0.73 and Dice values of 0.89, 0.87 and 0.82, respectively, for the BUS B, BUSI and OASBUD datasets. Through a series of experiments, we determined that adding an extra 30-pixel margin to the segmentation mask counteracts the potential errors introduced by the segmentation algorithm. An assembly of the full image classifier, bounding box classifier and masked image classifier was the most accurate for binary classification and had the best accuracy (ACC; 0.908), F1 (0.846) and area under the receiver operating char- acteristics curve (AUROC; 0.871) in the BUS B and ACC (0.982), F1 (0.984) and AUROC (0.998) in the UCC BUS datasets, outperforming each classifier used separately. It was also the most effective for BI-RADS classification, with ACC of 0.953, F1 of 0.920 and AUROC of 0.986 in UCC BUS. Hard voting was the most effective method for dichotomous classification. For the multi-class BI-RADS classification, the soft voting approach was employed. Conclusions: The proposed new classification approach with an ensemble of segmentation and classification approaches proved more accurate than most published results for binary and multi-class BI-RADS classifications.

  • Seismic performance assessment of steel structures considering soil effects
    • Farzin Kazemi
    • Neda Asgarkhani
    • Ahmed Manguri
    • Robert Jankowski
    2024 Pełny tekst

    Nowadays, extreme need for construction of buildings in rural area increased the floor number of buildings, in which, the soil under foundation can affect the performance of buildings. In this research, soil effects were investigated to show soil type effects on the performance levels of steel structures. To do this, the 2-, 4-, 6-, and 8-story structures were modeled using ETABS software; then, the models were verified in Opensees software for collapse state analysis. Incremental Dynamic Analyses (IDAs) are employed using far field, near field records having pulse like and no pulse effects. The results of analysis provide informations regarding the influence of soil types of B, C, D, and E on the seismic performance level of steel structures. The results confirmed that the soil types have remarkable effect on performance levels and it should be considered in seismic design process. To consider the soil types effects, it is recommended to compare the results of analysis achieved in this study to find out the percentage of variations, and use them as a reference for seismic design process. In addition, it is possible to have modification factors for amending the performance levels.

  • Seismic probabilistic assessment of steel and reinforced concrete structures including earthquake-induced pounding
    • Farzin Kazemi
    • Neda Asgarkhani
    • Ahmed Manguri
    • Robert Jankowski
    2024 Pełny tekst Archives of Civil and Mechanical Engineering

    Recent earthquakes demonstrate that prioritizing the retrofitting of buildings should be of the utmost importance for enhancing the seismic resilience and structural integrity of urban structures. To have a realistic results of the pounding effects in modeling process of retrofitting buildings, the present research provides seismic Probability Factors (PFs), which can be used for estimating collision effects without engaging in intricate and time-intensive analysis. To include the low-, to mid-rise buildings, the 3-Story, 5-Story, and 9-Story adjacent steel and Reinforced Concrete (RC) moment-resisting frames were modeled in OpenSees software capable to take into account the structure in a state of collapse during the analysis, which can provide the real condition of buildings under seismic excitations. Results of analysis confirmed that the impact force can considerably affect the moment–rotation curve of beams and columns, in which, it can affect the structural response of structures during earthquakes. Therefore, seismic PFs proposed to examine the possibility of changes in the performance levels and fragility assessments. Moreover, proposed PFs can be used as coefficient factors to facilitate the retrofitting process of buildings and improve the environmental effects.

  • Seismic response and performance prediction of steel buckling-restrained braced frames using machine-learning methods
    • Neda Asgarkhani
    • Farzin Kazemi
    • Anna Jakubczyk-Gałczyńska
    • Benyamin Mohebi
    • Robert Jankowski
    2024 Pełny tekst ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

    Nowadays, Buckling-Restrained Brace Frames (BRBFs) have been used as lateral force-resisting systems for low-, to mid-rise buildings. Residual Interstory Drift (RID) of BRBFs plays a key role in deciding to retrofit buildings after seismic excitation; however, existing formulas have limitations and cannot effectively help civil engineers, e.g., FEMA P-58, which is a conservative estimation method. Therefore, there is a need to provide a comprehensive tool for estimating seismic responses of Interstory Drift (ID) and RID with novel approaches to fulfill the shortcomings of existing formulas. The Machine Learning (ML) method is an interdisciplinary approach that makes it possible to solve these types of engineering problems. Therefore, the current study proposes ML algorithms to provide a prediction model for determining the seismic response, seismic performance curve, and seismic failure probability curve of BRBFs. To train ML-based prediction models, Nonlinear Time-History Analysis (NTHA) and Incremental Dynamic Analysis (IDA) were performed on the 2-, to 12-Story BRBFs subjected to 78 far-field ground motions, and 606944 data points were prepared for different prediction purposes. The results indicate that the considered approaches are justified. For instance, the proposed ML methods have the ability to predict the maximum ID, maximum RID and maximum roof ID with the accuracy of even 98.7%, 95.2%, and 93.8%, respectively, for the 4-Story BRBF. Moreover, a general preliminary estimation tool is introduced to provide predictions based on the input parameters considered in the study.

  • Selected aspects of performance of organic Rankine cycles incorporated into bioenergy with carbon capture and storage using gasification of sewage sludge
    • Kamil Stasiak
    • Paweł Ziółkowski
    • Dariusz Mikielewicz
    2024 Pełny tekst JOURNAL OF ENERGY RESOURCES TECHNOLOGY-TRANSACTIONS OF THE ASME

    The study aims to investigate the application of the Organic Rankine Cycle (ORC) in the bioenergy with carbon capture and storage (BECCS) using gasification of sewage sludge. The tool used in the investigation is the Aspen Plus software with REFPROP property methods for calculating fluid properties. The reason for this study is that a detailed analysis of the proposed BECCS process flow diagram indicates that a certain amount of waste heat is available in the exhaust gas from the high-to-intermediate pressure gas turbine. Some of this energy can be used by applying expansion in a low-pressure turbine, optionally by applying of regenerative water heating, which is then redirected to the combustion chamber, or finally by incorporating the ORC into the main cycle. For the ORC cycle, different configurations are studied, with regeneration and using different working fluids. For the highest efficiency of the cycle, the regenerative heating of high-pressure water is applied and a suitable ORC working fluid with optimal saturation parameters and mass flow is selected. Such modified proposed BECCS power plant hybrid systems with ORC are compared to the reference case with lower pressure expansion. A study of the heat duty and temperature distribution in heat exchangers is carried out. Five ORC fluids were investigated, namely ethanol, refrigerants R236-ea, R245-fa, R1233zd(E) and water, which gave a net efficiency of the whole power plant of 39.71%, 40.02%, 40.26%, 40.34% and 39.35% respectively, while the proposed BECCS reference case gave 38.89%.

  • Selected aspects of the operation of Dual Active Bridge DC/DC converters
    • Serafin Bachman
    • Marek Turzyński
    • Marek Jasinski
    2024 Pełny tekst Bulletin of the Polish Academy of Sciences-Technical Sciences

    This review paper discusses the concept of a bidirectional dual active bridge (DAB) DC/DC converter. Practical applications and control methods are explored, and various types of DAB converters are introduced and characterized. Aspects of operation are discussed, and enriched by the results of theoretical analyses, simulations, and experimental measurements of the original authors’ work.

  • Selected symmetrically substituted carbazoles: Investigation of anticancer activity and mechanisms of action at the cellular and molecular levels
    • Mateusz Olszewski
    2024 Pełny tekst

    DNA topoisomerases play a critical role as essential enzymes in controlling alterations in the topology of DNA. They achieve this by orchestrating the coordinated process of breaking and rejoining DNA strands, which is crucial for maintaining the proper structure of DNA during regular cellular development. The search for and development of new potential anticancer drugs is a challenging yet immensely important area of research that can contribute significantly to advancements in the treatment and combat of cancer-related diseases. In the scope of my doctoral work, research was conducted on three heterocyclic compounds derived from carbazole, aiming to identify their anticancer mechanism of action. The studies demonstrated that these compounds act as non-intercalating DNA inhibitors of human topoisomerase I and IIα. Among the three investigated compounds, 36a exhibited notably higher inhibitory activity against the IIα isoform compared to IIβ. Additionally, their cytotoxic and antiproliferative properties were determined, along with their ability to inhibit tyrosine protein kinases and induce cell death. The conducted experiments allowed to determine the main mechanisms of action of these anticancer compounds, which could in the future contribute to the design and synthesis of new potential drug candidates.

  • Selecting a transport and forwarding company for meeting a customer’s needs when organizing international road cargo transportation
    • Ievgenii Lebid
    • Nataliia Luzhanska
    • Iryna Lebid
    • Alexander Mazurenko
    • Inesa Halona
    • Kateryna Kovtsur
    • Tetiana Yarmak
    • Tetiana Sotnikova
    • Ievgen Medvediev
    2024 Pełny tekst Eastern-European Journal of Enterprise Technologies [ Восточно-Европейский журнал передовых технологий ]

    The object of this study is the process of planning the work of a manufacturing enterprise that needs transport and forwarding services when exporting goods to counterparties in different countries of the world. The problem being solved is predetermined by the need to devise recommendations for choosing a transport and forwarding company when serving an individual customer, based on its individual needs and conditions of cooperation. A simulation model for the selection of a transport and forwarding company was constructed and implemented to meet the customer’s needs when exporting goods, applying the GPSS World simulation automation package. The model provides for the optimization of the choice of a transport and forwarding company for servicing counterparties based on the assessment of their activity indicators over previous periods of cooperation. When building the model, the types of commercial conditions of the exporter’s cooperation with the transport and forwarding company, indicators of the quality assessment of the basic level of service and the duration of service at all stages of the foreign trade operation were taken into account. The application of the constructed model in practice will enable exporters and importers to choose a transport and forwarding company depending on the individual needs of customers in the delivery of goods. The simulation results reflect the performance indicators of the provision of transport and forwarding services by various specialized enterprises. This will make it possible to involve in the transport and forwarding service of a separate counterparty an organization that will meet all the requirements of goods buyer in accordance with the terms of the international economic contract. At the same time, the duration of choosing and agreeing the terms of cooperation could be reduced by 12–15 % while the efficiency of transport and forwarding services would increase by 13–16 %.

  • Selective H2 production from plastic waste through pyrolysis and in-line oxidative steam reforming
    • Mayra Suarez
    • Katarzyna Januszewicz
    • Maria Cortazar
    • Lopez Gartzen
    • Laura Santamaria
    • Martin Olazar
    • Maite Artetxe
    • Maider Amutio
    2024 Pełny tekst ENERGY

    This study deals with the proposal of pyrolysis and in-line oxidative steam reforming (P-OSR) for plastic waste valorization and assesses the potential of this strategy for the selective production of H2. Overall, the study aims at progressing towards the fine-tuning of the pyrolysis-reforming technology by co-feeding O2. Thus, a multi-point O2 injection system has been developed to ensure a suitable O2 distribution in the reforming reactor and avoid the formation of hot spots, as they may cause catalyst deactivation by metal sintering. Moreover, as O2 is directly supplied into the catalytic bed, pre-combustion of the volatile stream before contacting the catalyst is avoided and in-situ coke combustion is promoted. The P-OSR of HDPE was carried out in a two-step reaction system, which combines CSBR (conical spouted bed reactor) and FBR (fluidized bed reactor) technologies. The experiments were conducted in continuous mode and the influence of the main process conditions at zero time on stream was analyzed. Thus, the effect of reforming temperature was studied in the 550–750 °C range, that of the space time from 3.12 to 15.62 gcat min gHDPE−1, steam to plastic (S/P) ratio between 2 and 5 and equivalence ratio (ER) from 0 to 0.3. Under the optimum conditions (700 °C, S/P of 3, 12.5 gcat min gHDPE−1 and ER of 0.2), a H2 production of 25.0 wt% was obtained, which is only 28.6 % lower than that obtained in the conventional pyrolysis-steam reforming (P-SR) process. The results obtained confirm the potential of continuous P-OSR process for the selective production of H2.

  • Self-assembled concentric stripes of diamond particles by a pinning-depinning mechanism
    • Paulina Czarnecka-Trela
    • Adam M. Wojciechowski
    • Mariusz Mrózek
    • Maciej Głowacki
    • Robert Bogdanowicz
    • Wojciech Gawlik
    2024 Pełny tekst DIAMOND AND RELATED MATERIALS

    We describe the novel mechanism of spontaneous formation of the concentric stripe patterns of microdiamonds via gradual solvent evaporation from a suspension confined in a teardrop well. The self-organized patterns exhibit a series of arcs with regular spacings varying between hundreds of micrometers and millimeters. They result from an interplay between the directional forced circulation of the solvent and a stick-slip movement of its contact line during the gradual drying of the suspension. We reveal the mechanism of the phenomenon and discuss the effects of various parameters on the obtained structures.

  • Self-Calibrating Stress Measurement System Based on Multidirectional Barkhausen Noise Measurements
    • Leszek Piotrowski
    • Marek Chmielewski
    2024 Pełny tekst JOURNAL OF NONDESTRUCTIVE EVALUATION

    The system presented in this paper enables automatization of the two-dimensional calibration process (determination of Barkhausen noise (BN) intensity dependence on in-plane components of strain). Then, using dedicated software created by the authors in LabVIEW environment, and with the help of two dimensional calibration data one can effectively determine strain and stress distribution i.e. magnitude and orientation of main strain/stress components relative to measurement direction. BN signal measurements are performed using an advanced, multidirectional Barkhausen noise (BN) measuring sensor and a measurement system dedicated for cooperation with it. The system uses a robust algorithm for the strain components determination based on calibration surfaces, instead of usually applied curves, thus taking the influence of normal strain component directly into account instead of treating it as a correction factor (if not completely neglecting). The originality of the system arises also from the fact that this is the first BN measurement system that is self-calibrating (i.e. automatically loads the calibration sample in a pre-programmed way, performs BN signal measurements and calculates calibration planes), provided that the user possesses enough of the investigated material for calibration sample preparation.

  • Self-organising maps in the analysis of strains of human abdominal wall to identify areas of similar mechanical behaviour.
    • Mateusz Troka
    • Katarzyna Szepietowska
    • Izabela Lubowiecka
    2024 Pełny tekst Journal of the Mechanical Behavior of Biomedical Materials

    The study refers to the application of a type of artificial neural network called the Self-Organising Map (SOM) for the identification of areas of the human abdominal wall that behave in a similar mechanical way. The research is based on data acquired during in vivo tests using the digital image correlation technique (DIC). The mechanical behaviour of the human abdominal wall is analysed during changing intra-abdominal pressure. SOM allow to study simultaneously three variables in four time/load steps. The variables refer to the principal strains and their directions. SOM classifies all the abdominal surface data points into clusters that behave similarly in accordance with the 12 variables. The analysis of the clusters provides a better insight into abdominal wall deformation and its evolution under pressure than when observing a single mechanical variable. The presented results may provide a better understanding of the mechanics of the living human abdominal wall. It might be particularly useful when selecting proper implants as well as for the design of surgical meshes for the treatment of abdominal hernias, which would be mechanically compatible with identified regions of the human anterior abdominal wall, and possibly open the way for patient-specific solutions.

  • Self-Perceived Personal Brand Equity of Knowledge Workers by Gender in Light of Knowledge-Driven Organizational Culture: Evidence From Poland and the United States
    • Wioleta Kucharska
    2024 Pełny tekst SAGE Open

    This study contributes to the limited literature on the personal branding of knowledge workers by revealing that a culture that incorporates knowledge, learning, and collaboration supports (explicit and tacit) knowledge sharing among employees and that sharing matters for knowledge workers’ self-perceived personal brand equity. Analysis of 2,168 cases from the United States and Poland using structural equation modeling (SEM) showed that this knowledge-sharing mechanism differs by country and gender. Findings revealed that in the United States, the knowledge culture and collaboration culture are highly correlated and dominate the learning culture. In both countries, the mistake acceptance component of the learning culture is not supported by knowledge culture as strongly as is the climate component. These findings reveal a bias concerning the acceptance of mistakes as a potential source of learning observed if the culture of knowledge dominates. Moreover, this study uncovers some significant gender differences that might be caused by the gender stereotypes existing in STEM (science, technology, engineering, mathematics). Finally, the study confirms that knowledge workers’ personal branding is a potent motive to smoothen and increase the knowledge-sharing flow in knowledge-driven organizations.

  • Semi-definite programming and quantum information
    • Piotr Mironowicz
    2024 Pełny tekst Journal of Physics A-Mathematical and Theoretical

    This paper presents a comprehensive exploration of semi-definite programming (SDP) techniques within the context of quantum information. It examines the mathematical foundations of convex optimization, duality, and SDP formulations, providing a solid theoretical framework for addressing optimization challenges in quantum systems. By leveraging these tools, researchers and practitioners can characterize classical and quantum correlations, optimize quantum states, and design efficient quantum algorithms and protocols. The paper also discusses implementational aspects, such as solvers for SDP and modeling tools, enabling the effective employment of optimization techniques in quantum information processing. The insights and methodologies presented in this paper have proven instrumental in advancing the field of quantum information, facilitating the development of novel communication protocols, self-testing methods, and a deeper understanding of quantum entanglement.

  • Sensitive method for determination of benzoic acid in beverages and food samples using air–assisted hydrophobic deep eutectic solvent-based dispersive liquid-liquid microextraction
    • Hameed Haq
    2024 Sustainable Chemistry and Pharmacy

    A simple, reliable and rapid air–assisted hydrophobic deep eutectic solvent-based dispersive liquid–liquid microextraction (AA-HDES-DLLME) was developed for analysis of benzoic acid in various beverages and food samples. The final determination stage was performed via UV–visible spectrophotometry. The key parameters (extraction time, HDES type and volume, dispersant volume, pH and sample volume) of the AA-HDES-DLLME method were optimized in detailed using Box–Behnken design. Analysis of variance was used for statistical analysis. Under the optimized conditions, limit of detection (12.1 μg L−1), limit of quantification (40 μg L−1), linearity range (40–1000 μg L−1), and preconcentration factor (140) were determined. While the accuracy of the AA-HDES-DLLME method was investigated with the standard addition approach, its precision was investigated with intraday/interday studies. The method proved to be effective for routine analytical practice for a wide variety of samples. The novelty of the AA-HDES-DLLME method is that it enables the extraction of benzoic acid without the need for heating or centrifugation steps. In this way, the AA-HDES-DLLME method enabled selective extraction of benzoic acid in a shorter time and using less energy compared to similar studies.

  • Sensorless Control of Induction Motor Based on Super-Twisting Sliding Mode Observer With Speed Convergence Improvement
    • Lelisa Wogi
    • Marcin Morawiec
    • Tadele Ayana
    2024 Pełny tekst IEEE Access

    The super twisting sliding-mode observer (ST-SMO) has been proposed to achieve an effective method for alleviating low-order harmonics of measured quantities, issues related to DC drift, and suppression of chattering due to low-frequency sampling. The conventional ST-SMO, on the other hand, suffers from control delay in the convergence trajectory due to the system disturbance, resulting in decreased anti-disturbance capability and impacting the estimation accuracy and energy consumption. This paper proposed an ST-SMO with convergence improvement to address the issue related to the sliding mode controller along the sliding surface. A nonlinear sliding mode manifold is created to achieve the optimal ST-SMO convergence trajectory along the sliding surface. Then, a disturbance compensation term is added to the control law to eliminate the system control delay. In comparison to the conventional ST-SMO, the investigated method can effectively improve the anti-disturbance capability of the induction motor (IM) Observer, resulting in improved speed estimation (rotor flux control under applied load torque disturbances, speed reversal, and zero speed operation), good performance, and stability. The simulation and experimental studies are carried out for an induction motor with a 5.5kW rating. Both simulation and experimental results prove good robustness against the applied load torque disturbances and convergence of rotor speed to its actual value.

  • Sensorless Predictive Multiscalar-Based Control of the Five-Phase IPMSM
    • Deepak Vyas
    • Marcin Morawiec
    • Grzegorz Kostro
    • Andrzej JąDerko
    • Janusz Baran
    2024 Pełny tekst IEEE Access

    This article proposes multi-scalar variables based predictive control of sensorless multiphase interior permanent magnet synchronous machine. Estimated parameters from adaptive observers are used to implement the proposed control scheme. The control approach is divided into two parts: for the fundamental plane, torque and its dual quantity from the multi-scalar model are directly predicted by the controller, and torque density is improved by injecting a third harmonic current in the second plane. The multi-scalar model of the 3rd harmonic plane is controlled by classical linear controllers. The analysis of the five-phase interior permanent magnet synchronous machine is done deeply in the stationary reference frame. Moreover, the proposed control scheme is compared with traditional predictive control-based field-oriented control for the fundamental plane and the field-oriented control (linear controllers-based) for the second plane in the (d-q) reference frame. Compared with the previous control strategy, the proposed control structure provides a fastdynamic response, reduces the computation resources by eliminating the reference frame transformation to obtain control signals, and improves overall control dynamics. The performance of the proposed control scheme is formally validated by simulation and experimental results.

  • Separation of C6 hydrocarbons on sodium dithionite reduced graphene oxide aerogels
    • Maksymilian Plata Gryl
    • Roberto Castro Munoz
    • Emilia Gontarek-Castro
    • Grzegorz Boczkaj
    2024 JOURNAL OF CHROMATOGRAPHY A

    The ability of reduced graphene oxide aerogels (rGOAs) for challenging gas-phase separation was investigated with hexane isomers and benzene (C6 hydrocarbons) using inverse gas chromatography (IGC). For the first, rGOAs were synthesized with sodium dithionite (DTN) as a reductant. Experiments revealed that the most optimal DTN to graphene oxide mass ratio was 2:1, resulting in the highest specific surface area of 432.3 m2 g−1 and the highest degree of graphitization among analyzed samples. C6 hydrocarbon adsorption tests demonstrated the dominant role of the kinetic effect for the adsorption of branched and cyclic hexane isomers -the partition coefficient decreased as the molecule kinetic diameter increased. The contribution of thermodynamic effects was distinguished for molecules with uneven charge distribution. A comparison of the partition coefficient ratios for different pairs of hydrocarbons demonstrated the potential of rGOAs in separating various C6 hydrocarbons. The selectivity, calculated from binary-component adsorption tests of benzene (Bz)/cC6 equimolar mixture, was 13.7, 8.5 and 2.8 for DTN4, DTN2, and DTN1. The research indicates that rGOAs may have potential as adsorbents for the selective separation of hydrocarbons, however, the competitive adsorption and performance at high surface coverages of adsorbates have to be accounted for in further research to assess the applicability of rGOAs reliably.

  • Session-Based Recommendation with Graph Neural Networks with an Examination of the Impact of Local and Global Vectors
    • Justyna Głogowska
    • Dariusz Kobiela
    • Szymon Mielewczyk
    2024

    This study investigates the application of graph neural networks (GNN) in session-based recommendation systems (SR), focusing on a key modification involving the use of a global vector. Session-based recommendation systems often face challenges in accurately capturing user behavior due to the limited data available within individual sessions. The SR-GNN model, originally designed for automatic feature extraction from session graphs by leveraging rich connections between nodes, addresses these challenges effectively. In our experiments, we replaced the local vector with a global vector representing the entire session sequence, not just the last element. Our results show that both local and global vectors perform comparably, suggesting that the global vector is sufficient to capture the session context. Additionally, our study indicate that the SR-GNN algorithm maintains consistent performance across various datasets, with minor fluctuations depending on the dataset characteristics. The conducted experiments highlight the resilience and adaptability of the SR-GNN model in diverse scenarios, demonstrating its potential for use in session-based recommendation systems.