bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of Different Calcium Sources on Mechanical Properties of Metakaolin Geopolymers
Authors: Wang Yiren , Zhang Jiangtao , Liu Jie , Fan Deke , Qu Haiyang , Zhou Lingzhu , Zheng Sen
Published: April 2024

Metakaolin-based geopolymers have substantial potential as replacements for cement, but their relatively inferior mechanical properties restrict their application. This paper aims to enhance the mechanical properties of metakaolin-based geopolymers by incorporating appropriate amounts of calcium sources. CaCO3, Ca(OH)2, and CaSO4 are three types of calcium sources commonly found in nature and are widely present in various industrial wastes. Thus, the effects of these three calcium sources on the performance of metakaolin-based geopolymers were studied. Through the analysis of the mechanical properties, heat-release behavior during hydration, hydration products, and microstructure of geopolymers, the effectiveness of the aforementioned calcium sources in improving the performance of metakaolin-based geopolymer was evaluated, and the mechanisms of action were elucidated. The results indicate that the pozzolanic reaction between CH and MK could promote MK hydration and increase the proportion of CASH gel in the hydration products, thereby facilitating the setting of the geopolymer and enhancing its strength. CS could react with the active aluminates in MK to form ettringite, thus forming a higher early strength. CC had a lower reactivity with MK and does not improve the performance of MK-based geopolymers.
Thermal Stability and Non-Linear Optical and Dielectric Properties of Lead-Free K0.5Bi0.5TiO3 Ceramics
Authors: Czaja Piotr , Szostak Elżbieta , Hetmańczyk Joanna , Zachariasz Piotr , Majda Dorota , Suchanicz Jan , Karolus Małgorzata , Bochenek Dariusz , Osińska Katarzyna , Jędryka Jarosław , Kityk Andriy , Piasecki Michał
Published: April 2024

Lead-free K0.5Bi0.5TiO3 (KBT) ceramics with high density (~5.36 g/cm3, 90% of X-ray density) and compositional purity (up to 90%) were synthesized using a solid-state reaction method. Strongly condensed KBT ceramics revealed homogenous local microstructures. TG/DSC (Thermogravimetry-differential scanning calorimetry) techniques characterized the thermal and structural stability of KBT. High mass stability (>0.4%) has proven no KBT thermal decomposition or other phase precipitation up to 1000 °C except for the co-existing K2Ti6O13 impurity. A strong influence of crystallites size and sintering conditions on improved dielectric and non-linear optical properties was reported. A significant increase (more than twice) in dielectric permittivity (εR), substantial for potential applications, was found in the KBT-24h specimen with extensive milling time. Moreover, it was observed that the second harmonic generation (λSHG = 532 nm) was activated at remarkably low fundamental beam intensity. Finally, spectroscopic experiments (Fourier transform Raman and far-infrared spectroscopy (FT-IR)) were supported by DFT (Density functional theory) calculations with a 2 × 2 × 2 supercell (P42mc symmetry and C4v point group). Moreover, the energy band gap was calculated (Eg = 2.46 eV), and a strong hybridization of the O-2p and Ti-3d orbitals at Eg explained the nature of band-gap transition (Γ → Γ).
Properties and Performance of Epoxy Resin/Boron Acid Composites
Authors: Rudawska Anna , Frigione Mariaenrica , Sarcinella Antonella , Brunella Valentina , Di Lorenzo Ludovica , Olewnik-Kruszkowska Ewa
Published: April 2024

This research study focused on the effect of adding boric acid to epoxy resin in order to obtain a composite material with improved properties and performance. To this end, a fine powder of boric acid (H3BO3) was introduced into epoxy resin in different amounts, i.e., 0.5 g, 1.0 g, and 1.5 g. As the matrix of the epoxy composites, styrene-modified epoxy resin based on bisphenol A (BPA) (Epidian 53) was used. It was cross-linked with two types of curing agents, i.e., an amine (ET) and a polyamide (PAC). The mechanical properties of the obtained epoxy composites (in terms of compressive strength, compressive modulus, and compressive strain) were determined at room temperature in order to assess the effect of the addition of boron acid and of the type of curing agent employed to cure the epoxy on these characteristics. Calorimetric measurements were made to highlight any changes in the glass transition temperature (Tg) as a result of the addition of boric acid to epoxy resin. Finally, flammability tests were performed on both Epidian 53/PAC and Epidian 53/ET epoxy composites to analyze their fire behavior and consequently establish the effectiveness of the selected additive as a flame retardant.
Integrating Experimental and Computational Analyses for Mechanical Characterization of Titanium Carbide/Aluminum Metal Matrix Composites
Authors: Farid Waqas , Li Hailin , Wang Zhengyu , Cui Huijie , Kong Charlie , Yu Hailiang
Published: April 2024

This study investigates the mechanical properties of titanium carbide/aluminum metal matrix composites (AMMCs) using both experimental and computational methods. Through accumulative roll bonding (ARB) and cryorolling (CR) processes, AA1050 alloy surfaces were reinforced with TiCp particles to create the Al–TiCp composite. The experimental analysis shows significant improvements in tensile strength, yield strength, elastic modulus, and hardness. The finite element analysis (FEA) simulations, particularly the microstructural modeling of RVE−1 (the experimental case model), align closely with the experimental results observed through scanning electron microscopy (SEM). This validation underscores the accuracy of the computational models in predicting the mechanical behavior under identical experimental conditions. The simulated elastic modulus deviates by 5.49% from the experimental value, while the tensile strength shows a 6.81% difference. Additionally, the simulated yield strength indicates a 2.85% deviation. The simulation data provide insights into the microstructural behavior, stress distribution, and particle–matrix interactions, facilitating the design optimization for enhanced performance. The study also explores the influence of particle shapes and sizes through Representative Volume Element (RVE) models, highlighting nuanced effects on stress–strain behavior. The microstructural evolution is examined via transmission electron microscopy (TEM), revealing insights regarding grain refinement. These findings demonstrate the potential of Al–TiCp composites for lightweight applications.
Performance of High-Dose Reclaimed Asphalt Mixtures (RAPs) in Hot In-Place Recycling Based on Balanced Design
Authors: Jiang Lei , Shen Junan , Wang Wei
Published: April 2024

This study endeavors to employ a balanced design methodology, aiming to equilibrate the resistance to rutting and cracking exhibited by hot in-place recycling asphalt mixtures containing a high dose of reclaimed asphalt pavement (RAP). The primary goal is to ascertain the optimal amount of new binder necessary for practical engineering applications, ensuring a balanced rutting and crack resistance performance of recycled asphalt mixtures. The investigation mainly employed wheel-tracking tests and semi-circular bending tests to assess the rutting and cracking performance of recycled asphalt mixtures with a different dose of RAP (in China, it is common to use RAP with 80% and 90% content as additives for preparing hot in-place recycling asphalt mixtures), and varying quantities of new binders (10%, 20%, and 30% of the binder content in the total RAP added). The results indicated that the addition of new binder reduced the resistance to rutting of the recycling asphalt mixtures but improved their resistance to cracking. Furthermore, for the recycling asphalt mixture with 80% RAP content aged for 5 days, the optimal new binder content is 1.52%, while the mixture with 90% RAP content requires 1.23% of new binder. After 10 days of aging, the optimal new binder content for the recycling asphalt mixture with 80% RAP content is 1.55%, while the mixture with 90% RAP content requires 1.28% of new binder.
Effect of Laser Scan Speed on Defects and Texture Development of Pure Chromium Metal Fabricated via Powder Bed Fusion-Laser Beam
Authors: Kim Yong Seong , Gokcekaya Ozkan , Matsugaki Aira , Nakano Takayoshi
Published: April 2024

Chromium (Cr) metal has garnered significant attention in alloy systems owing to its exceptional properties, such as a high melting point, low density, and superior oxidation and corrosion resistance. However, its processing capabilities are hindered by its high ductile–brittle transition temperature (DBTT). Recently, powder bed fusion-laser beam for metals (PBF-LB/M) has emerged as a promising technique, offering the fabrication of net shapes and precise control over crystallographic texture. Nevertheless, research investigating the mechanism underlying crystallographic texture development in pure Cr via PBF-LB/M still needs to be conducted. This study explored the impact of scan speed on relative density and crystallographic texture. At the optimal scan speed, an increase in grain size attributed to epitaxial growth was observed, resulting in the formation of a <100> cubic texture. Consequently, a reduction in high-angle grain boundaries (HAGB) was achieved, suppressing defects such as cracks and enhancing relative density up to 98.1%. Furthermore, with increasing densification, Vickers hardness also exhibited a corresponding increase. These findings underscore the efficacy of PBF-LB/M for processing metals with high DBTT properties.
Assessment of Changes in Abrasive Wear Resistance of a Welded Joint of Low-Alloy Martensitic Steel Using Microabrasion Test
Authors: Ligier Krzysztof , Napiórkowski Jerzy , Lemecha Magdalena
Published: April 2024

Martensitic low-alloy steels are widely used in machine construction. Due to their declared weldability, arc welding is most often used to join elements made of this type of steel. However, the high temperature associated with welding causes unfavourable changes in the microstructure, resulting in reduced abrasion resistance. Therefore, it is important to know the tribological properties of the welded joint. This article presents the results of a study on the abrasion wear resistance of a welded joint of an abrasion-resistant steel. This study tested a welded joint of an abrasive-resistant steel produced by the arc welding method. Wear testing of the welded joint was carried out under laboratory conditions by the ball-cratering method in the presence of abrasive slurry on the cross-section of the welded joint. Based on the test results, the change in the abrasive wear rate of the material as a function of the distance from the welded joint axis was determined. It was also found that the thermal processes accompanying welding caused structural changes that increased the wear rate index value. Adverse changes in the tribological properties of a welded material persist up to a distance of approx. 20 mm from the weld centre.
Catalytic Oxidation of Chlorobenzene over Amorphous Manganese-Chromium Catalysts Supported by UiO-66-Derived ZrOx
Authors: Zhu Pengfei , Yuan Qiaosen , Li Na , Hu Zhaoxia , Chen Shouwen
Published: April 2024

The development of efficient catalysts with longevity to remove chlorobenzene is challenging due to Cl poisoning. Herein, a series of Mn-Cr/ZrOx catalysts supported by Zr-based metal-organic framework (UiO-66)-derived ZrOx was prepared and investigated for chlorobenzene (CB) catalytic oxidation. MnCr/ZrOx-M prepared via a wet impregnation method presented an amorphous structure, indicating the homogeneous dispersion of Cr and Mn, which improved acid and redox properties. 40Mn7Cr3/ZrOx-M exhibited the best catalytic activity for chlorobenzene oxidation with T90 of 293 °C, which is mainly due to the strong interaction between manganese and chromium promoted by the large specific surface area of the ZrOx support. Furthermore, 40Mn7Cr3/ZrOx-M presented excellent stability for chlorobenzene oxidation.
Progress and Challenges of Additive Manufacturing of Tungsten and Alloys as Plasma-Facing Materials
Authors: Howard Logan , Parker Gabriel D. , Yu Xiao-Ying
Published: April 2024

Tungsten (W) and W alloys are considered as primary candidates for plasma-facing components (PFCs) that must perform in severe environments in terms of temperature, neutron fluxes, plasma effects, and irradiation bombardment. These materials are notoriously difficult to produce using additive manufacturing (AM) methods due to issues inherent to these techniques. The progress on applying AM techniques to W-based PFC applications is reviewed and the technical issues in selected manufacturing methods are discussed in this review. Specifically, we focus on the recent development and applications of laser powder bed fusion (LPBF), electron beam melting (EBM), and direct energy deposition (DED) in W materials due to their abilities to preserve the properties of W as potential PFCs. Additionally, the existing literature on irradiation effects on W and W alloys is surveyed, with possible solutions to those issues therein addressed. Finally, the gaps in possible future research on additively manufactured W are identified and outlined.
Innovative Design of Cooling System for a High-Torque Electric Machine Integrated with Power Electronics
Authors: Sadeghianjahromi Ali , Bradley Stuart I. , McMahon Richard A.
Published: April 2024

The growth of electrical machine applications in high-torque environments such as marine propulsion and wind energy is encouraging the development of higher-power-density machines at ever higher efficiencies and under competitive pressure to meet higher demands. In this study, numerical simulations are performed to investigate the characteristics of air cooling applied to a 3 MW high-torque internal permanent magnet electric machine with integrated power electronics. The whole system of the main machine and two converters at either end are modelled with all details. Effects of different parameters on the total pressure drop and air flow rate to the machine and converters are examined. Results show that by changing the converter outlet hole size, the air flow rate to the machine and converter can be adjusted. Air guides and pin vents reveal excellent performance in the distribution of air to laminations and windings with a penalty of some increase in pressure drop, which is more pronounced when using smaller outlet holes. Furthermore, the air return manifold increases the pressure drop and causes a reduction in air flow rate to the converter. Insulation between compression plate and laminations is an unavoidable component used in electric machines and acts as a thermal insulator. However, it can also significantly augment pressure drop, especially in combination with smaller outlet holes. Thermal studies of the integrated power electronics illustrate that components’ temperatures are less than the temperature limit, confirming enough air through the converter. Analysis of power electronics in the case of fan failure provides the operational time window for the operators to respond.
A New Sliding-Mode Observer-Based Deadbeat Predictive Current Control Method for Permanent Magnet Motor Drive
Authors: Zhang Zixuan , Xu Qiangren , Wang Yicheng
Published: April 2024

This article proposes a new deadbeat predictive current control (DPCC) method based on a sliding-mode observer (SMO), which is applied in the field of permanent magnet motor control. A novel DPCC control method based on SMO is proposed according to the inherent issues of DPCC, which can effectively suppress internal parameter mismatch disturbances and external disturbances in the current loop. The mathematical model and derivation process of the proposed method are introduced. A simulation model is built and the effectiveness of the proposed method is verified. An experimental platform is built and the superiority of the proposed method is verified based on comparative experiments. Experimental results show that the proposed algorithm has strong robustness to the motor parameter mismatch. Compared with extended state observer (ESO) and adaptive observer (AO), the proposed algorithm has faster response speed and higher steady-state accuracy.
A Walking Trajectory Tracking Control Based on Uncertainties Estimation for a Drilling Robot for Rockburst Prevention
Authors: Gu Jinheng , He Shicheng , Dai Jianbo , Wei Dong , Yan Haifeng , Tan Chao , Wang Zhongbin , Si Lei
Published: April 2024

A walking trajectory tracking control approach for a walking electrohydraulic control system is developed to reduce the walking trajectory tracking deviation and enhance robustness. The model uncertainties are estimated by a designed state observer. A saturation function is used to attenuate sliding mode chattering in the designed sliding mode controller. Additionally, a walking trajectory tracking control strategy is proposed to improve the walking trajectory tracking performance in terms of response time, tracking precision, and robustness, including walking longitudinal and lateral trajectory tracking controllers. Finally, simulation and experimental results are employed to verify the trajectory tracking performance and observability of the model uncertainties. The results testify that the proposed approach is better than other comparative methods, and the longitudinal and lateral trajectory tracking average absolute errors are controlled in 10.23 mm and 22.34 mm, respectively, thereby improving the walking trajectory tracking performance of the walking electrohydraulic control system for the coal mine drilling robot for rockburst prevention.
An Improved Fourier-Based Method for Path Generation of Planar Four-Bar Linkages without Prescribed Timing
Authors: Qian Yahui , Zhong Hong , Wang Tao , Wang Liangmo
Published: April 2024

Four-bar linkages are critical fundamental elements of many mechanical systems, and their design synthesis is often mathematically complicated with iterative numerical solutions. Analytical methods based on Fourier coefficients can circumvent these difficulties but have issues with time parameters assignment for path generation without prescribed time in previous studies. In this paper, an improved Fourier-based point-to-point combination method is presented, which generates more points by Fourier approximation and assigns the time parameters to the given points while allowing discarding solutions with order defects. This method relies on the Fourier coefficients, improving the accuracy of synthesis solutions, and simplifying the computational procedure. Time parameters are assigned directly to the given points, which avoids the complex calculations to find intersection points in the given path, eliminates combinations that would lead to solutions with order defects, and simplifies the assessment process of synthesis results. The parameters obtained by the point-to-point combination method can be used as the parameters of the input dyad, skipping the first set of design equations for faster calculation. Several examples are presented to demonstrate the advantages of the proposed synthesis method, which is easy-understanding, computationally efficient, and yields more accurate solutions than available synthesis methods.
Investigation of the Effect of Pumping Depth and Frequency of Flapping Hydrofoil on Suspended Matter Discharge Characteristics
Authors: Hua Ertian , Xiang Mingwang , Wang Tao , Song Yabo , Lu Caiju , Sun Qizong
Published: April 2024

In order to study the effect of the pumping depth and pumping frequency of the flapping hydrofoil device on suspended solids in the waters, this paper takes raceway aquaculture as an example, and introduces a flapping hydrofoil device to improve the discharge of suspended solids in the raceway, in response to the problem of the deposition of suspended solids from fish faeces and bait residues in water. The CFD method was used to compare and analyze the discharge of suspended solids at different pumping depths, and the combined effect of the two was studied according to different combinations of pumping frequency and pumping depth. The results proved that the flapping hydrofoil motion can improve the bottom hydrodynamic insufficiency in ecological waters and thus enhance the discharge effect of suspended particles in water. In addition, the pumping depth of the flapping hydrofoil is too deep for the movement to be disturbed by the bottom surface, while the thrust generated by the flapping hydrofoil is weakened if the depth is too shallow. When the pump water depth is 1.1 H, the reversed Kármán vortex street is more stable under the balancing effect of the bottom surface and gravity, and the rate curve of the flapping hydrofoil acting on the discharge of suspended particles is better. From our comprehensive consideration of the joint effect of the pumping depth and pumping frequency, we recommend the use of a 1.1 H of pumping depth and 2.0 Hz pumping frequency in combination to achieve the best effect of discharging suspended particles. This study provides valuable insights into the actual engineering applications of flapping hydrofoil devices for improving water quality and ecological sustainability in raceway aquaculture.
Experimental Evaluation of Effect of Leaves on Railroad Tracks in Loss of Braking
Authors: Kumar Nikhil , Radmehr Ahmad , Ahmadian Mehdi
Published: April 2024

This study aims to comprehensively assess the lubrication effect of leaves on wheel–rail contact dynamics using the Virginia Tech-Federal Railroad Administration (VT-FRA) Roller Rig, which closely simulates field conditions with precision and repeatability. Railway operators grapple with the seasonally recurring challenge of leaf contamination, which can cause partial loss of braking and lead to undesired events such as station overruns. Better understanding the adhesion-reducing impact of leaf contamination significantly improves railway engineering practices to counter their effects on train braking and traction. This experimental study evaluates the reduction in traction and braking forces (collectively called “adhesion”) as a function of leaf volume, using two leaf species that commonly grow along U.S. railroad tracks. The test methods rely on the chosen leaves’ transpiration characteristics while ensuring the result’s reproducibility. Leaves were symmetrically positioned on the wheel surface, centered around the mid-rib area within the wear band, and taped on the edges far from the wear band. The critical test parameters (i.e., wheel load, wheel velocity, and percentage creepage) are kept constant among the tests. At the same time, leaf volume is reduced from a maximum amount that covers the entire wheel surface (100% coverage) to no leaves (0%). The latter is used as the baseline. The percentage creepage is kept constant at an exaggerated amount of 2% to accelerate the test time. The results indicate a nonlinear relationship between leaf volume and the loss of braking. Even a small amount of leaf contamination causes a significant reduction in adhesion by as much as 50% compared with no contamination (i.e., baseline). Increasing leaf volume results in contact saturation, beyond which adhesion is not reduced. The minimum adhesion observed in this study is 20% of the maximum adhesion that occurs when no leaf contamination is present.
Efficient List Intersection Algorithm for Short Documents by Document Reordering
Authors: Jia Lianyin , Li Dongyang , Zhou Haihe , Xia Fengling
Published: April 2024

List intersection plays a pivotal role in various domains such as search engines, database systems, and social networks. Efficient indexes and query strategies can significantly enhance the efficiency of list intersection. Existing inverted index-based algorithms fail to utilize the length information of documents and require excessive list intersections, resulting in lower efficiency. To address this issue, in this paper, we propose the LDRpV (Length-based Document Reordering plus Verification) algorithm. LDRpV filters out documents that are unlikely to satisfy the intersection results by reordering documents based on their length, thereby reducing the number of candidates. Additionally, to minimize the number of list intersection operations, an intersection and verification strategy is designed, where only the first m lists are intersected, and the resulting candidate set is directly verified. This approach effectively improves the efficiency of list intersection. Experimental results on four real datasets demonstrate that LDRpV can achieve a maximum efficiency improvement of 46.69% compared to the most competitive counterparts.
Deep-Representation-Learning-Based Classification Strategy for Anticancer Peptides
Authors: Khan Shujaat
Published: April 2024

Cancer, with its complexity and numerous origins, continues to provide a huge challenge in medical research. Anticancer peptides are a potential treatment option, but identifying and synthesizing them on a large scale requires accurate prediction algorithms. This study presents an intuitive classification strategy, named ACP-LSE, based on representation learning, specifically, a deep latent-space encoding scheme. ACP-LSE can demonstrate notable advancements in classification outcomes, particularly in scenarios with limited sample sizes and abundant features. ACP-LSE differs from typical black-box approaches by focusing on representation learning. Utilizing an auto-encoder-inspired network, it embeds high-dimensional features, such as the composition of g-spaced amino acid pairs, into a compressed latent space. In contrast to conventional auto-encoders, ACP-LSE ensures that the learned feature set is both small and effective for classification, giving a transparent alternative. The suggested approach is tested on benchmark datasets and demonstrates higher performance compared to the current methods. The results indicate improved Matthew’s correlation coefficient and balanced accuracy, offering insights into crucial aspects for developing new ACPs. The implementation of the proposed ACP-LSE approach is accessible online, providing a valuable and reproducible resource for researchers in the field.
Enhanced YOLOX with United Attention Head for Road Detetion When Driving
Authors: Wu Yuhuan , Wu Yonghong
Published: April 2024

Object detection plays a crucial role in autonomous driving assistance systems. It requires high accuracy for prediction, a small size for deployment on mobile devices, and real-time inference speed to ensure safety. In this paper, we present a compact and efficient algorithm called YOLOX with United Attention Head (UAH-YOLOX) for detection in autonomous driving scenarios. By replacing the backbone network with GhostNet for feature extraction, the model reduces the number of parameters and computational complexity. By adding a united attention head before the YOLO head, the model effectively detects the scale, position, and contour features of targets. In particular, an attention module called Spatial Self-Attention is designed to extract spatial location information, demonstrating great potential in detection. In our network, the IOU Loss (Intersection of Union) has been replaced with CIOU Loss (Complete Intersection of Union). Further experiments demonstrate the effectiveness of our proposed methods on the BDD100k dataset and the Caltech Pedestrian dataset. UAH-YOLOX achieves state-of-the-art results by improving the detection accuracy of the BDD100k dataset by 1.70% and increasing processing speed by 3.37 frames per second (FPS). Visualization provides specific examples in various scenarios.
µ-Integrable Functions and Weak Convergence of Probability Measures in Complete Paranormed Spaces
Authors: Zeng Renying
Published: April 2024

This paper works with functions defined in metric spaces and takes values in complete paranormed vector spaces or in Banach spaces, and proves some necessary and sufficient conditions for weak convergence of probability measures. Our main result is as follows: Let X be a complete paranormed vector space and Ω an arbitrary metric space, then a sequence {μn} of probability measures is weakly convergent to a probability measure μ if and only if limn→∞∫Ωg(s)dμn=∫Ωg(s)dμ for every bounded continuous function g: Ω → X. A special case is as the following: if X is a Banach space, Ω an arbitrary metric space, then {μn} is weakly convergent to μ if and only if limn→∞∫Ωg(s)dμn=∫Ωg(s)dμ for every bounded continuous function g: Ω → X. Our theorems and corollaries in the article modified or generalized some recent results regarding the convergence of sequences of measures.
Existence of Solutions to a System of Fractional q-Difference Boundary Value Problems
Authors: Tudorache Alexandru , Luca Rodica
Published: April 2024

We are investigating the existence of solutions to a system of two fractional q-difference equations containing fractional q-integral terms, subject to multi-point boundary conditions that encompass q-derivatives and fractional q-derivatives of different orders. In our main results, we rely on various fixed point theorems, such as the Leray–Schauder nonlinear alternative, the Schaefer fixed point theorem, the Krasnosel’skii fixed point theorem for the sum of two operators, and the Banach contraction mapping principle. Finally, several examples are provided to illustrate our findings.
Depth-Optimized Quantum Circuits for ASCON: AEAD and HASH
Authors: Oh Yujin , Jang Kyungbae , Baksi Anubhab , Seo Hwajeong
Published: April 2024

Quantum computing advancements pose security challenges for cryptography. Specifically, Grover’s search algorithm affects the reduction in the search complexity of symmetric-key encryption and hash functions. Recent efforts have been made to estimate the complexity of Grover’s search and evaluate post-quantum security. In this paper, we propose a depth-optimized quantum circuit implementation for ASCON, including both symmetric-key encryption and hashing algorithms, as a part of the lightweight cryptography standardization by NIST (National Institute of Standards and Technology). As far as we know, this is the first implementation of a quantum circuit for the ASCON AEAD (Authenticated Encryption with Associated Data) scheme, which is a symmetric-key algorithm. Also, our quantum circuit implementation of the ASCON-HASH achieves a reduction of more than 88.9% in the Toffoli depth and more than 80.5% in the full depth compared to the previous work. As per our understanding, the most effective strategy against Grover’s search involves minimizing the depth of the quantum circuit for the target cipher. We showcase the optimal Grover’s search cost for ASCON and introduce a proposed quantum circuit optimized for depth. Furthermore, we utilize the estimated cost to evaluate post-quantum security strength of ASCON, employing the relevant evaluation criteria and the latest advancements in research.
Two-Stage Probe-Based Search Optimization Algorithm for the Traveling Salesman Problems
Authors: Rahman Md. Azizur , Ma Jinwen
Published: April 2024

As a classical combinatorial optimization problem, the traveling salesman problem (TSP) has been extensively investigated in the fields of Artificial Intelligence and Operations Research. Due to being NP-complete, it is still rather challenging to solve both effectively and efficiently. Because of its high theoretical significance and wide practical applications, great effort has been undertaken to solve it from the point of view of intelligent search. In this paper, we propose a two-stage probe-based search optimization algorithm for solving both symmetric and asymmetric TSPs through the stages of route development and a self-escape mechanism. Specifically, in the first stage, a reasonable proportion threshold filter of potential basis probes or partial routes is set up at each step during the complete route development process. In this way, the poor basis probes with longer routes are filtered out automatically. Moreover, four local augmentation operators are further employed to improve these potential basis probes at each step. In the second stage, a self-escape mechanism or operation is further implemented on the obtained complete routes to prevent the probe-based search from being trapped in a locally optimal solution. The experimental results on a collection of benchmark TSP datasets demonstrate that our proposed algorithm is more effective than other state-of-the-art optimization algorithms. In fact, it achieves the best-known TSP benchmark solutions in many datasets, while, in certain cases, it even generates solutions that are better than the best-known TSP benchmark solutions.
Shortage Policies for a Jump Process with Positive and Negative Batch Arrivals in a Random Environment
Authors: Barron Yonit
Published: April 2024

We study a continuous-review stock management of a retailer for a single item in a limited storage (buffer) in a random environment. The stock level fluctuates according to two independent compound Poisson processes with discrete amounts of items (batches) that enter and leave the storage facility. The storage facility is controlled by a three-parameter base-stock replenishment policy. All items exceeding the storage capacity are transferred to an unlimited foreign facility. In addition, a restricted backlogging possibility is permitted; additional demands for items are lost sales. We further assume a random shelf life, the possibility of total inventory collapse, and a random lead time. Applying Markov theory, we derive the optimal control parameters minimizing the long-run expected total cost. A sensitivity analysis is conducted focusing on the comparison between the pure lost-sales policy and a partial backordering policy. Accordingly, we identify cases where one policy is cost effective compared to the other, particularly with respect to the batch patterns (sign, rate, average, and variability), and the associated costs.
Adaptive Parallel Scheduling Scheme for Smart Contract
Authors: Yang Wenjin , Ao Meng , Sun Jing , Wang Guoan , Li Yongxuan , Li Chunhai , Shao Zhuguang
Published: April 2024

With the increasing demand for decentralized systems and the widespread usage of blockchain, low throughput and high latency have become the biggest stumbling blocks in the development of blockchain systems. This problem seriously hinders the expansion of blockchain and its application in production. Most existing smart contract scheduling solutions use static feature analysis to prevent contract conflicts during parallel execution. However, the conflicts between transactions are complex; static feature analysis is not accurate enough. In this paper, we first build the dependency between smart contracts by analyzing the features. After numerous experiments, we propose a conflict model to adjust the relationship between threads and conflict to achieve high throughput and low latency. Based on these works, we propose adaptive parallel scheduling for smart contracts on the blockchain. Our adaptive parallel scheduling can distinguish conflicts between smart contracts and dynamically adjust the execution strategy of smart contracts based on the conflict factors we define. We implement our scheme on ChainMaker, one of the most popular open-source permissioned blockchains, and build experiments to verify our solution. Regarding latency, our solution demonstrates remarkable efficiency compared with the fully parallel scheme, particularly in high-conflict transaction scenarios, where our solution achieves latency levels just one-twentieth of the fully parallel scheme. Regarding throughput, our solution significantly outperforms the fully parallel scheme, achieving 30 times higher throughput in high-conflict transaction scenarios. These results highlight the superior performance and effectiveness of our solution in addressing latency and throughput challenges, particularly in environments with high transaction conflicts.
A Graph-Based Keyword Extraction Method for Academic Literature Knowledge Graph Construction
Authors: Zhang Lin , Li Yanan , Li Qinru
Published: April 2024

In this paper, we construct an academic literature knowledge graph based on the relationship between documents to facilitate the storage and research of academic literature data. Keywords are an important type of node in the knowledge graph. To solve the problem that there are no keywords in some documents for several reasons in the process of knowledge graph construction, an improved keyword extraction algorithm called TP-CoGlo-TextRank is proposed by using word frequency, position, word co-occurrence frequency, and a word embedding model. By combining the word frequency and position in the document, the importance of words is distinguished. By introducing the GloVe word-embedding model, which brings the external knowledge of documents into the TextRank algorithm, and combining the internal word co-occurrence frequency in the documents, the word-adjacency relationship is transferred non-uniformly. Finally, the words with the highest scores are combined into phrases if they are adjacent in the original text. The validity of the TP-CoGlo-TextRank algorithm is verified by experiments. On this basis, the Neo4j graph database is used to store and display the academic literature knowledge graph, to provide data support for research tasks such as text clustering, automatic summarization, and question-answering systems.
Dynamic Behavior and Bifurcation Analysis of a Modified Reduced Lorenz Model
Authors: Al-Kaff Mohammed O. , AlNemer Ghada , El-Metwally Hamdy A. , Elsadany Abd-Elalim A. , Elabbasy Elmetwally M.
Published: April 2024

This study introduces a newly modified Lorenz model capable of demonstrating bifurcation within a specified range of parameters. The model demonstrates various bifurcation behaviors, which are depicted as distinct structures in the diagram. The study aims to discover and analyze the existence and stability of fixed points in the model. To achieve this, the center manifold theorem and bifurcation theory are employed to identify the requirements for pitchfork bifurcation, period-doubling bifurcation, and Neimark–Sacker bifurcation. In addition to theoretical findings, numerical simulations, including bifurcation diagrams, phase pictures, and maximum Lyapunov exponents, showcase the nuanced, complex, and diverse dynamics. Finally, the study applies the Ott–Grebogi–Yorke (OGY) method to control the chaos observed in the reduced modified Lorenz model.
Ride-Hailing Matching with Uncertain Travel Time: A Novel Interval-Valued Fuzzy Multi-Objective Linear Programming Approach
Authors: Supian Sudradjat , Subiyanto  , Megantara Tubagus Robbi , Bon Abdul Talib
Published: April 2024

This study introduces an innovative approach to tackle multi-objective linear programming (MOLP) problems amidst uncertainty, employing interval-valued fuzzy numbers. The method is tailored to resolve ride-hailing matching challenges encompassing uncertain travel times. Findings reveal that managing uncertainty parameters within interval-valued fuzzy MOLP is achieved through strategic reformulations, focusing on constraint coefficients, resulting in streamlined linear programming formulations conducive to solution simplicity. The efficacy of the proposed model in efficiently handling ride-hailing matching quandaries is demonstrated. Moreover, this study delves into the prospective applications of the developed method, including its potential for generalization to address non-linear programming (NLP) issues pertinent to the ride-hailing domain. This research advances decision-making processes under uncertainty and paves the way for broader applications beyond ride-hailing.
Cyanotoxin Occurrence and Diversity in 98 Cyanobacterial Blooms from Swedish Lakes and the Baltic Sea
Authors: Dirks Caroline , Cappelli Paolo , Blomqvist Maria , Ekroth Susanne , Johansson Malin , Persson Max , Drakare Stina , Pekar Heidi , Zuberovic Muratovic Aida
Published: April 2024

The Drinking Water Directive (EU) 2020/2184 includes the parameter microcystin LR, a cyanotoxin, which drinking water producers need to analyze if the water source has potential for cyanobacterial blooms. In light of the increasing occurrences of cyanobacterial blooms worldwide and given that more than 50 percent of the drinking water in Sweden is produced from surface water, both fresh and brackish, the need for improved knowledge about cyanotoxin occurrence and cyanobacterial diversity has increased. In this study, a total of 98 cyanobacterial blooms were sampled in 2016–2017 and identified based on their toxin production and taxonomical compositions. The surface water samples from freshwater lakes throughout Sweden including brackish water from eight east coast locations along the Baltic Sea were analyzed for their toxin content with LC-MS/MS and taxonomic composition with 16S rRNA amplicon sequencing. Both the extracellular and the total toxin content were analyzed. Microcystin’s prevalence was highest with presence in 82% of blooms, of which as a free toxin in 39% of blooms. Saxitoxins were found in 36% of blooms in which the congener decarbamoylsaxitoxin (dcSTX) was detected for the first time in Swedish surface waters at four sampling sites. Anatoxins were most rarely detected, followed by cylindrospermopsin, which were found in 6% and 10% of samples, respectively. As expected, nodularin was detected in samples collected from the Baltic Sea only. The cyanobacterial operational taxonomic units (OTUs) with the highest abundance and prevalence could be annotated to Aphanizomenon NIES-81 and the second most profuse cyanobacterial taxon to Microcystis PCC 7914. In addition, two correlations were found, one between Aphanizomenon NIES-81 and saxitoxins and another between Microcystis PCC 7914 and microcystins. This study is of value to drinking water management and scientists involved in recognizing and controlling toxic cyanobacteria blooms.
An Isotonic Drink Containing Pacific Cod (Gadus macrocephalus) Processing Waste Collagen Hydrolysate for Bone and Cartilage Health
Authors: Zarubin Nikita Yu. , Kharenko Elena N. , Bredikhina Olga V. , Lavrukhina Elizaveta V. , Rysakova Kira S. , Novikov Vitaly Yu. , Leonov Georgy E. , Vakhrushev Igor V. , Zolotarev Konstantin V. , Mikhailov Anton N. , Mikhailova Marina V.
Published: April 2024

Malnutrition is one of the major factors of bone and cartilage disorders. Pacific cod (Gadus macrocephalus) processing waste is a cheap and highly promising source of bioactive substances, including collagen-derived peptides and amino acids, for bone and cartilage structure stabilization. The addition of these substances to a functional drink is one of the ways to achieve their fast intestinal absorption. Collagen hydrolysate was obtained via enzymatic hydrolysis, ultrafiltration, freeze-drying, and grinding to powder. The lyophilized hydrolysate was a light gray powder with high protein content (>90%), including collagen (about 85% of total protein) and a complete set of essential and non-essential amino acids. The hydrolysate had no observed adverse effect on human mesenchymal stem cell morphology, viability, or proliferation. The hydrolysate was applicable as a protein food supply or a structure-forming food component due to the presence of collagen fiber fragments. An isotonic fitness drink (osmolality 298.1 ± 2.1 mOsm/L) containing hydrolysate and vitamin C as a cofactor in collagen biosynthesis was prepared. The addition of the hydrolysate did not adversely affect its organoleptic parameters. The production of such functional foods and drinks is one of the beneficial ways of fish processing waste utilization.
Direct Degradation of Fresh and Dried Macroalgae by Agarivorans albus B2Z047
Authors: Gong Ya , Shang Dan-Dan , Sun Cheng-Lin , Du Zong-Jun , Chen Guan-Jun
Published: April 2024

Marine macroalgae are increasingly recognized for their significant biological and economic potential. The key to unlocking this potential lies in the efficient degradation of all carbohydrates from the macroalgae biomass. However, a variety of polysaccharides (alginate, cellulose, fucoidan, and laminarin), are difficult to degrade simultaneously in a short time. In this study, the brown alga Saccharina japonica was found to be rapidly and thoroughly degraded by the marine bacterium Agarivorans albus B2Z047. This strain harbors a broad spectrum of carbohydrate-active enzymes capable of degrading various polysaccharides, making it uniquely equipped to efficiently break down both fresh and dried kelp, achieving a hydrolysis rate of up to 52%. A transcriptomic analysis elucidated the presence of pivotal enzyme genes implicated in the degradation pathways of alginate, cellulose, fucoidan, and laminarin. This discovery highlights the bacterium’s capability for the efficient and comprehensive conversion of kelp biomass, indicating its significant potential in biotechnological applications for macroalgae resource utilization.
Exploring the Efficacy of Hydroxybenzoic Acid Derivatives in Mitigating Jellyfish Toxin-Induced Skin Damage: Insights into Protective and Reparative Mechanisms
Authors: Geng Hao , Li Rongfeng , Teng Lichao , Yu Chunlin , Wang Wenjie , Gao Kun , Li Aoyu , Liu Song , Xing Ronge , Yu Huahua , Li Pengcheng
Published: April 2024

The escalation of jellyfish stings has drawn attention to severe skin reactions, underscoring the necessity for novel treatments. This investigation assesses the potential of hydroxybenzoic acid derivatives, specifically protocatechuic acid (PCA) and gentisic acid (DHB), for alleviating Nemopilema nomurai Nematocyst Venom (NnNV)-induced injuries. By employing an in vivo mouse model, the study delves into the therapeutic efficacy of these compounds. Through a combination of ELISA and Western blot analyses, histological examinations, and molecular assays, the study scrutinizes the inflammatory response, assesses skin damage and repair mechanisms, and investigates the compounds’ ability to counteract venom effects. Our findings indicate that PCA and DHB significantly mitigate inflammation by modulating critical cytokines and pathways, altering collagen ratios through topical application, and enhancing VEGF and bFGF levels. Furthermore, both compounds demonstrate potential in neutralizing NnNV toxicity by inhibiting metalloproteinases and phospholipase-A2, showcasing the viability of small-molecule compounds in managing toxin-induced injuries.
Anti-Melanogenic Effects of Takifugu flavidus Muscle Hydrolysate in B16F10 Melanoma Cells and Zebrafish
Authors: Hu Jinjin , Chen Bei , Qu Shuaijie , Liu Shuji , Yang Xiaoyu , Qiao Kun , Su Yongchang , Liu Zhihui , Chen Xiaoe , Liu Zhiyu , Wang Qin
Published: April 2024

Abnormal melanogenesis can lead to hyperpigmentation. Tyrosinase (TYR), a key rate-limiting enzyme in melanin production, is an important therapeutic target for these disorders. We investigated the TYR inhibitory activity of hydrolysates extracted from the muscle tissue of Takifugu flavidus (TFMH). We used computer-aided virtual screening to identify a novel peptide that potently inhibited melanin synthesis, simulated its binding mode to TYR, and evaluated functional efficacy in vitro and in vivo. TFMH inhibited the diphenolase activities of mTYR, reducing TYR substrate binding activity and effectively inhibiting melanin synthesis. TFMH indirectly reduced cAMP response element-binding protein phosphorylation in vitro by downregulating melanocortin 1 receptor expression, thereby inhibiting expression of the microphthalmia-associated transcription factor, further decreasing TYR, tyrosinase related protein 1, and dopachrome tautomerase expression and ultimately impeding melanin synthesis. In zebrafish, TFMH significantly reduced black spot formation. TFMH (200 μg/mL) decreased zebrafish TYR activity by 43% and melanin content by 52%. Molecular dynamics simulations over 100 ns revealed that the FGFRSP (T-6) peptide stably binds mushroom TYR via hydrogen bonds and ionic interactions. T-6 (400 μmol/L) reduced melanin content in B16F10 melanoma cells by 71% and TYR activity by 79%. In zebrafish, T-6 (200 μmol/L) inhibited melanin production by 64%. TFMH and T-6 exhibit good potential for the development of natural skin-whitening cosmetic products.