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Reordering graphs for node embedding
No full textThe complex connectivity patterns inherent in graphs are the biggest obstacle to applying ML algorithms, which are perfected for tabular data, to graphs. Graph embedding converts each node into a d-dimensional vector while preserving the structural graph features, thereby creating tabular structures in which each row corresponds to a node in the graph and contains d feature values. However, the embedding process is quite costly and requires accelerators such as GPUs. In this study, we propose approaches to improve the GPU-based graph embedding tools based on graph ordering. The experiments verify that reordering the graph can improve the embedding tools both in terms of speed and quality
The influence of lignin derivatives on the thermal properties and flammability of PLA+PET blends
Get PDFThis paper presents a detailed analysis of the thermal and flammability properties of polylactide- (PLA) and poly(ethylene terephthalate)- (PET) based polymer blends with biofillers, such as calcium lignosulfonate (CLS), lignosulfonamide (SA) and lignosulfonate modified with tannic acid (BMT) and gallic acid (BMG). Calorimetric studies revealed the presence of two glass transitions, one cold crystallization temperature, and two melting points, confirming the partial immiscibility of the PLA and PET phases. The additives had different effects on the temperatures and ranges of phase transformations—BMT restricted PLA chain mobility, while CLS acted as a nucleating agent that promoted crystallization. Thermogravimetric analyses (TGA) analyses showed that the additives significantly affected the thermal stability under oxidizing conditions, some (e.g., BMG) lowered the onset degradation temperature, while the others (BMT, SA) increased the residual char content. The additives also altered combustion behavior; particularly BMG that most effectively reduced flammability, promoted char formation, and extended combustion time. CLS reduced PET flammability more effectively than PLA, especially at higher PET content (e.g., 65% reduction in PET for 2:1/CLS). SA inhibited only PLA combustion, with strong effects at higher PLA content (up to 76% reduction for 2:1/SA). BMT mainly reduced PET flammability (48% reduction in 1:1/BMT), while BMG inhibited PET more strongly at lower PET content (76% reduction for 2:1/BMG). The effect of each additive also depended on the PLA:PET ratio in the blend. FTIR analysis of the char residues revealed functional groups associated with decomposition products of carboxylic acids and aromatic esters. Ultimately, only blends containing BMT and BMG met the requirements for flammability class FV-1, while SA met FV-2 classification. BMG was the most effective additive, offering enhanced thermal stability, ignition delay, and durable char formation, making it a promising bio- based flame retardant for sustainable polyester materials
Signature of current-induced nuclear spin polarization in (Bi1-xSbx)2Te3
No full textIn systems with spin-momentum locking, such as the surface states of three-dimensional topological insulators, a charge current is spin-polarized and spin-flip interactions between electron and nuclear spins can transfer this polarization to the nuclear spin system. When a nonzero bias voltage is applied, the nuclear polarization reaches a steady-state value. This polarization emerges as an effective in-plane magnetic field acting on electrons, called the Overhauser field, which causes an offset in-plane magnetoresistance perpendicular to the current, visible in experiments. The in-plane offset is measured in the three-dimensional topological insulator (Bi1-xSbx)2Te3, and the magnitude of the magnetic field offset is compared to the Overhauser field. We attribute the observed magnetic field offset to current-induced nuclear polarization in (Bi1-xSbx)2Te3, which forms an important step towards experimentally realizing an entropic inductor
A general framework for dynamic MAPF using multi-shot ASP and tunnels
Get PDFThe multi-agent path finding (MAPF) problem aims to find plans for multiple agents in an environment within a given time, such that the agents do not collide with each other or obstacles. Motivated by the execution and monitoring of these plans, we study dynamic MAPF (D-MAPF) problem, which allows changes such as agents entering/leaving the environment or obstacles being removed/moved. Considering the requirements of real-world applications in warehouses with the presence of humans, we introduce (1) a general definition for D-MAPF (applicable to variations of D-MAPF), (2) a new framework to solve D-MAPF (utilizing multi-shot computation and allowing different methods to solve D-MAPF), and (3) a new answer set programming-based method to solve D-MAPF (combining advantages of replanning and repairing methods, with a novel concept of tunnels to specify where agents can move). We have illustrated the strengths and weaknesses of this method by experimental evaluations, from the perspectives of computational performance and quality of solutions
Perspectives on deciphering thermotolerance mechanisms in Heliotropium thermophilum: integrating biochemical responses and gene expression patterns
No full textHigh temperature stress significantly impacts plant viability and productivity. Understanding thermotolerance mechanisms is essential for developing resilient crops. Heliotropium thermophilum , endemic to geothermal areas with extreme soil temperatures, serves as a model for studying plant high temperature stress responses. We aim to elucidate the biochemical and molecular mechanisms underlying thermotolerance in H. thermophilum . Biochemical assays quantified osmoprotectants (proline, soluble sugars, glycine-betaine, and total phenolics) and lipid peroxidation in H. thermophilum under different soil temperatures. Transcriptome analysis and quantitative Real-Time PCR were performed to validate the expression of genes involved in osmoprotectant biosynthesis, antioxidant defense, and cell wall modification. Glycine-betaine and proline levels increased by up to 189% and 104%, respectively, during peak stress. Elevated total phenolics correlated with reduced lipid peroxidation, indicating effective oxidative stress mitigation. Transcriptome analysis revealed significant upregulation of genes related to osmoprotectant biosynthesis, antioxidant defense, and cell wall modification, with notable expression of heat shock proteins and sugar transport genes. H. thermophilum employs an integrative biochemical and molecular strategy to withstand high soil temperatures, involving osmoprotectant accumulation, enhanced antioxidant defenses, and dynamic cell wall remodeling. These findings provide insights into thermotolerance mechanisms, offering potential targets for enhancing high temperature stress resilience in other crops. This study contributes to understanding plant-soil interactions and developing strategies to ensure agricultural productivity amid global climate change
Gadolinium doped ZnS particles as electrode material for supercapacitor application
Get PDFSupercapacitors (SC) have gained prominence among many advanced technologies because of their superior power density, fast charge/discharge capabilities, extended cycle lifespan, and remarkable operational stability. Recent advancements in ZnS nanostructures underscore their potential for high-performance SCs, especially when their morphology and surface characteristics are carefully engineered. Incorporating dopants into ZnS has proven effective in further enhancing its electrochemical performance. Adding dopants into the ZnS lattice results in defects, such as zinc and sulfur vacancies and interstitial atoms. In this study, ZnS doped with varying concentrations of Gd ions serves as an electrode material in supercapacitor devices. The influence of the induced defect states and Gd-ions concentration, characterized by photoluminescence, Raman, and electron paramagnetic resonance spectroscopy, on the electrochemical properties was demonstrated through cyclic voltammetry, potentiostatic electrochemical impedance spectroscopy, and galvanostatic cycling with potential limitation. The findings indicate that ZnS doped with a nominal concentration of 0.5% Gd has the highest specific capacitance value, achieving a maximum of 114.7 F/g at 2 mV/s, and demonstrates excellent cyclic stability, retaining about 98% of its capacity after 2000 cycles. It also showcases impressive performance in terms of energy and power density, with values reaching up to 15.93 Wh/kg and 1146 W/kg, respectively. These findings underscore the potential of Gd-doped ZnS as high-efficiency electrodes in supercapacitors, playing a crucial role in advancing sustainable and efficient energy storage solutions that effectively balance energy and power density
Transforming CO2 into energy storage solutions: MnCO3/electrochemically exfoliated graphene hybrid for supercapacitors and lithium-ion batteries
No full textThis study introduces a one-pot synthesis approach to fabricate MnCO3/electrochemically exfoliated graphene (EEG) hybrid material through an electrochemical synthesis route. Our approach involves the use of a sacrificial anode to induce electrochemical exfoliation of a graphite rod, while the electrolyte captures CO2 from the air to utilize it in the synthesis of MnCO3 through a simple and well-controlled route. The absence of any chemical carbon dioxide source in the solution stands as a significant advantage for MnCO3 production. This approach promotes the creation of a synergistic MnCO3/EEG hybrid, capitalizing on the advantages of both materials. In addition, this method offers a scalable and cost-effective approach to fabricate MnCO3/EEG hybrid. MnCO3/EEG was characterized and analyzed utilizing a variety of techniques, including Fourier transform infrared spectroscopy (FTIR), Raman Spectroscopy, X-Ray Diffractometry (XRD), thermal gravimetric analysis (TGA) and scanning electron microscope/ electron dispersive spectroscopy (SEM/EDS). Electrochemical properties of MnCO3/EEG hybrid structure were studied in a three-electrode configuration by using cyclic voltammetry (CV), and galvanostatic charge–discharge (GCD) tests. The produced hybrid material has been successfully employed in asymmetric supercapacitors as the positive electrode to check its energy storage capabilities. In a three-electrode electrochemical cell, the MnCO3/EEG hybrid structure exhibited a specific capacitance of 90.5 F g−1. Subsequently, when an asymmetric device was prepared and its performance was evaluated, it demonstrated a maximum energy density (E) of 15.7 Wh kg−1 and a power density (P) of 701 W kg−1. The cycling stability remained above 85% after 3000 cycles. Furthermore, the hybrid material exhibiting the highest performance in supercapacitor studies has been evaluated as an anode material for lithium-ion batteries. In line with this objective, a lithium-ion battery cell was prepared, and similar electrochemical tests were conducted. The same material demonstrated a high specific capacity of 1382 mAh g−1 in lithium-ion battery half-cell applications. The results could be evidence that the innovative synthesis method is a prominent candidate to produce cost-effective and high-quality hybrid structures for energy storage devices. Furthermore, it is worth noting that the methodology employed in this study holds the potential for broader applications, extending beyond MnCO3 and MnxOy
Event Segmentation In Episodic Memory: The Role Of Prediction Errors, Contextual Transitions, And Affective Modulation
Get PDFEpisodic memory allows us to structure continuous experience into discrete, meaningfulevents, yet the mechanisms that shape segmentation and how different factorsinfluence this process are not fully understood. This thesis investigates how predictionerrors, contextual stability, and affective processes influence event segmentation.Across a series of behavioral experiments, I show that stable contextual informationplays a more critical role in triggering event boundaries than prediction errorsalone. Furthermore, while high-reward associations during the ongoing experiencecan enhance memory, they do not consistently alter the segmented structure of theexperience. Finally, I demonstrate that retrospective cognitive reappraisal of emotionalevents can reorganize how past experiences are segmented and remembered.Together, these findings challenge traditional models that emphasize prediction errorsand highlight the flexible, dynamic nature of memory organization shaped byboth bottom-up and top-down influences
Hunting high or low: evaluating the effectiveness of high-interaction and low-interaction honeypots
No full textHoneypots are cybersecurity mechanisms that are set up as decoys in networks to lure and monitor attackers trying to compromise vulnerable systems. Two commonly used honeypot designs are high-interaction and low-interaction honeypots, which differ in the amount of interplay that the attackers are allowed to do. So far, the effectiveness of high-interaction and low-interaction honeypots has been understudied, making it difficult for security teams to choose between different honeypot technologies. The aim of this paper is to compare the effectiveness of high-interaction and low-interaction honeypots through real-world data. We deployed multiple Elasticsearch honeypot implementations to collect data: a closed-source high-interaction honeypot developed by the authors, and three types of open-source low-interaction honeypots (namely Elastichoney, Delilah and Elasticpot). The collected data came from 48 instances of high-interaction honeypots and 111 instances of low-interaction honeypots, over a period of 14 days. We found that low-interaction honeypots captured only a fraction of the attacks that high-interaction honeypots can catch. On the other hand, low-interaction honeypots are simpler, more efficient to run due to their low usage of resources, and easier to deploy. In our dataset, high-interaction honeypots captured 76.12% of the total attack packets and attracted 70.61% of the unique attacker IPs. In comparison, low-interaction honeypots performed a lot worse in collecting attack data; they only managed to capture 23.88% of the total attack packets and attracted 29.39% of the unique attacker IPs. In this paper, we present an experiment that evaluated and compared the effectiveness of high-interaction and low-interaction honeypots in terms of the amount and the type of information collected from attacks targeting them. It follows from our findings that it would be wiser to either concentrate solely on using high-interaction honeypots, or to increase the effectiveness of low-interaction ones by automatically changing each static value during deployment and/or by increasing the mimicking capabilities of low-interaction honeypots
Thermomechanical process modelling and simulation for additive manufacturing of nanoparticle dispersed Inconel 718 alloys
No full textIn this study, a coupled transient thermomechanical finite element model is developed to examine the laser powder bed fusion (L-PBF) process of the Inconel 718 (IN718) and Oxide Dispersion Strengthened (ODS) superalloys (ODS-IN718). The linear isotropic elastic perfectly plastic constitutive model is implemented for the mechanical part whereas all the thermophysical properties are defined as fully temperature dependent. This new model enables three states of the metal including powder, liquid, and solid phases in the continuum-based finite element simulations. Besides, it can meticulously simulate multi-layered samples to assess thermomechanical performance and residual stress between layers. First, benchmark problems are revisited to verify the high accuracy of the present model for predicting transient temperature profile and residual stress accumulation. Then, thermomechanical analysis of a single-track three-layer test case is performed to investigate the L-PBF process of IN718 and ODS-IN718 samples for various laser powers and scan speeds. Also, the thermal characterization of ODS-IN718 samples is experimentally conducted. It is demonstrated that the numerical melt pool dimensions provide good agreement with experiments with an average error of 17% for melt pool dimensions. Moreover, mechanical results reveal that high tensile residual stresses accumulate in the middle part of the track. The manufacturing quality of the IN718 and ODS-IN718 samples are comprehensively compared based on the variations of stress distribution at different layers for different laser scan speeds. Also, the optimal laser scan speed is achieved to minimize the residual stresses for the ODS-IN718 alloy. Overall, ODS-IN718 has a lower residual stress than IN718 especially at lower laser scan speeds due to the enhanced thermomechanical behavior attributed to the change in material properties due to the presence of dispersed particles