bluuebunny/crossref_metadata_2025 huggingface dataset:
Osteoblast Growth in Quaternized Silicon Carbon Nitride Coatings for Dental Implants
Authors: Zhu Haochen , Xia Xinyi , Chiang Chao-Ching , Watson Levings Rachael S. , Correa Justin , Rocha Fernanda Regina Godoy , Ghivizzani Steve C. , Ren Fan , Neal Dan , Calderon Patricia dos Santos , Esquivel-Upshaw Josephine F.
Published: November 2024

The demand for dental implants has increased, establishing them as the standard of care for replacing missing teeth. Several factors contribute to the success or failure of an implant post-placement. Modifications to implant surfaces can enhance the biological interactions between bone cells and the implant, promoting better outcomes. Surface coatings have been developed to electrochemically alter implant surfaces, aiming to reduce healing time, enhance bone growth, and prevent bacterial adhesion. Quaternized silicon carbon nitride (QSiCN) is a novel material with unique electrochemical and biological properties. This study aimed to assess the influence of QSiCN, silicon carbide nitride (SiCN), and silicon carbide (SiC) coatings on the viability of osteoblast cells on nanostructured titanium surfaces. The experiment utilized thirty-two titanium sheets with anodized TiO2 nanotubes featuring nanotube diameters of 50 nm and 150 nm. These sheets were divided into eight groups (n = 4): QSiCN-coated 50 nm, QSiCN-coated 150 nm, SiCN-coated 50 nm, SiCN-coated 150 nm, SiC-coated 50 nm, SiC-coated 150 nm, non-coated 50 nm, and non-coated 150 nm. Preosteoblast MC3T3-E1 Subclone 4 cells (ATCC, USA) were used to evaluate osteoblast viability. After three days of cell growth, samples were assessed using scanning electron microscopy (SEM). The results indicated that QSiCN coatings significantly increased osteoblast proliferation (p < 0.005) compared to other groups. The enhanced cell adhesion observed with QSiCN coatings is likely due to the positive surface charge imparted by N+.
Influence of Finishing Process Parameters of HDF Boards on Selected Properties of Coatings in Modern UV Lines and Their Relation to Energy Consumption
Authors: Tokarczyk Maciej , Lis Barbara , Krystofiak Tomasz
Published: November 2024

This study analyzes the influence of energy generated by emitters on the adhesive properties of varnish coatings in multilayer UV systems. The experimental material, in the form of a cell board finished with UV varnish products, was prepared on a prototype line under the conditions of Borne Furniture in Gorzów Wielkopolski. The roughness and wettability were measured using a OneAttension tensiometer integrated with a topographic module, taking into account the Wenzel coefficient. The adhesion of the examined systems was verified using the PositiTest AT-A automatic pull-off device. Energy consumption by the prototype production line was compared to the standard line, utilizing mercury emitters and mercury emitters with added gallium. Energy consumption was calculated for selected variants. The influence of the Wenzel coefficient on the wettability angle was observed. Significant differences between contact angles (CA and CAc) were noted for coatings formed with sealers (stages I and II). The largest discrepancies, reaching up to 30 degrees, were recorded at the lowest UVA and UVV doses of 26 mJ/cm2. In adhesion tests, values below 1 MPa were obtained. Insufficient energy doses in the curing process of UV systems led to delamination between the coatings. Five variants were selected where delamination within the substrate predominated (˃90% A) and were characterized by the lowest energy consumption in the processes. Topographic images helped identify the presence of various surface microstructures at different stages of the production cycle. The greatest energy savings, up to 50%, were achieved in stages III and IV of the technological process.
Study on the Damage Mechanism of an H62-Cu/7075-Al Tribo-Pair Under the Influences of Current Direction and Density
Authors: Chen Pengfei , Zhang Yanyan , Song Chenfei
Published: November 2024

In the present study, we used 7075 Al-H62 Cu and H62 Cu-7075 Al pairs to study the effects of current density and direction on their tribological properties and on the damage caused by the current-carrying friction and wear. We found that, when the current density increased from 0 A/mm2 to 79.61 A/mm2, the coefficients of friction for both pairs decreased. Results obtained after wear indicate that the current direction influences the electromigration between the two tracks, leading to different kinds of damage on the worn surface. In the case of the 7075 Al-H62 Cu pair, damage mainly involved mechanical wear at low current densities. As the current density increased, electro-erosion damage gradually became more dominant. Under the action of a large electric arc, the material surface was severely eroded, and a dense oxide film formed on the material contact surface, ultimately leading to the failure of electrical conduction between the materials. In the case of the H62 Cu-7075 Al pair, damage mainly involved mechanical wear. A layer of copper film was found on the surface of the worn aluminum pin, which caused its mass to be greater than it was before wear.
Comparative Evaluation of Bone–Implant Contact in Various Surface-Treated Dental Implants Using High-Resolution Micro-CT in Rabbits’ Bone
Authors: Zieliński Rafał , Puszkarz Adam K. , Piętka Tomasz , Sowiński Jerzy , Sadowska-Sowińska Monika , Kołkowska Agata , Simka Wojciech
Published: November 2024

This study evaluated the bone-to-implant contact (BIC) of various surface-treated dental implants using high-resolution micro-CT in rabbit bone, focusing on the effects of different treatments on osseointegration and implant stability before and after bone demineralization. Six male New Zealand White rabbits were used. Four implant types were tested: machined surface with anodizing, only etching, sandblasting with Al2O3 + etching, and sandblasting with TiO2 + etching. Implants were scanned with high-resolution micro-CT before and after demineralization. Parameters like implant volume, surface area, and BIC were determined using specific software tools. During demineralization, the BIC changed about 6% for machined surface with anodizing, 5% for only etching, 4% for sandblasting with Al2O3 + etching, and 10% for sandblasting with TiO2 + etching. Demineralization reduced BIC percentages, notably in the machined surface with anodizing and sandblasting with TiO2 + etching groups. Etching and sandblasting combined with etching showed higher initial BIC compared to anodizing alone. Demineralization negatively impacted the BIC across all treatments. This study underscores the importance of surface modification in implant integration, especially in compromised bone. Further research with larger sample sizes and advanced techniques is recommended.
First Principles Study of Bismuth Vacancy Formation in (111)-Strained BiFeO3
Authors: Xia Lu , Tybell Thomas , Selbach Sverre M.
Published: November 2024

Epitaxial strain is known to significantly influence the structural and functional properties of oxide thin films. However, its impact on point defect concentration has been less explored. Due to the challenges in experimentally measuring thin-film stoichiometry, computational studies become crucial. In this work, we use first-principles calculations based on density functional theory to investigate the formation and stability of Bi vacancies and Bi-O vacancy pairs in BiFeO3 (BFO) under (111) epitaxial strain. Our results demonstrate that compressive strain (−4%) decreases the formation enthalpy of Bi vacancies by 0.88 eV, whereas tensile strain (4%) increases it by 0.39 eV. Out-of-plane (OP) Bi-O vacancy pairs exhibit enhanced stability under both compressive and tensile strain, with formation enthalpy reductions of 1.49 eV and 1.05 eV, respectively. In contrast, in-plane (IP) vacancy pairs are stabilized under compressive strain but are insensitive to tensile strain. Finally, we discuss how these findings influence Bi stoichiometry during thin-film growth and the role of local strain fields in the formation of conducting domain walls.
Analysis of Vibration Characteristics for Rotating Braided Fiber-Reinforced Composite Annular Plates with Perforations
Authors: Zhang Haibiao , Li Zhen , Wang Shixun , Liu Tao , Wang Qingshan
Published: November 2024

In the current study, a comprehensive numerical model for analyzing the vibrational characteristics of braided fiber-reinforced composite (BFRC) rotating annular plate with perforations under diverse boundary constraints was introduced. This model employs the differential quadrature finite element method (DQFEM), which was developed based on the first-order shear deformation theory (FSDT) and coordinate transformation approach. The BFRC material, specifically a two-dimensional biaxial orthogonal fabric, was utilized to fabricate the annular plate with two distinct types of holes: circular and sector-shaped. The model’s convergence, accuracy, numerical stability, and reliability were confirmed through comparative assessments utilizing data from the literature, from ABAQUS software, and from experimental findings. The analysis focuses on studying the influences of structural properties, material parameters, and boundary restraints on the frequencies of vibration for BFRC rotating annular plates with holes. This theoretical model helps provide scientific basis and technical guidance for the stability and lightweight design of rotating annular plates, such as rotor structures in aircraft engines.
Evaluation of Admixture Silane Added into Cementitious Pastes
Authors: Lamari Bruna Aparecida , Jochem Lidiane Fernanda , Gleize Philippe Jean Paul , Silvestro Laura , Onghero Lucas , Casagrande Cézar Augusto
Published: November 2024

This manuscript evaluated the performance of silanes in cementitious matrices in the partial replacement of superplasticizers by silanes. For this, pastes with a water/cement ratio of 0.186 were produced and the superplasticizer admixture based on polycarboxylate esters was partially substituted by three types of silanes—vinyltriethoxysilane silanes (VTES), n-(2-aminoethyl)-3-aminopropyltrimethoxysilane (AEAPTMS), and methacryloxypropyltrimethox-ysilane (MCPTMS)—in two substitutions levels (20% and 40%), and then tested in Portland cement pastes. Specific gravity, trapped air, mini-slump, and hydration kinetics (evaluated by isothermal calorimetry up to 48 h) of the pastes were determined in the fresh state. Thus, in the hardened state, the compressive and flexural strength tests (7 and 28 days), specific gravity, and absorption by immersion of the pastes were carried out. The results showed that the substitution of 20% and 40% of VTES and AEAPTMS considerably reduced the workability and increased the air content of the pastes in comparison to the reference sample. In contrast, the incorporation of 20% and 40% of MCPTMS did not significantly affect these properties. The presence of silane, for all analyzed samples, had a delaying effect on the hydration process: the maximum delay verified had a hydration peak in approximately 36 h for the 40% MCPTMS sample and the minimum delay verified had a hydration peak in approximately 11 h for the 20% VTES sample. The replacement of 20% and 40% by any of the silanes progressively reduced the flexural strength at both 7 and 28 days. In the compressive strength, as well as in the tensile strength in flexion, there was a decrease in the results when compared to the reference, except for the MCPTMS, at 7 and 28 days. In immersion absorption, all samples showed high percentages of absorption and void index when compared to the reference.
Cu Pillar Electroplating Using a Synthetic Polyquaterntum Leveler and Its Coupling Effect on SAC305/Cu Solder Joint Voiding
Authors: Li Wenjie , Li Zhe , Zeng Fang-Yuan , Zhang Qi , Guo Liwei , Li Dan , Ma Yong-Hui , Liu Zhi-Quan
Published: November 2024

With the advancement of high-integration and high-density interconnection in chip manufacturing and packaging, Cu bumping technology in wafer- and panel- level packaging is developed to micrometer-sized structures and pitches to accommodate increased I/O numbers on high-end integrated circuits. Driven by this industrial demand, significant efforts have been dedicated to Cu electroplating techniques for improved pillar shape control and solder joint reliability, which substantially depend on additive formulations and electroplating parameters that regulate the growth morphology, crystal structure, and impurity incorporation in the process of electrodeposition. It is necessary to investigate the effect of an additive on Cu pillar electrodeposition, and to explore the Kirkendall voids formed during the reflowing process, which may result from the additive-induced impurity in the electrodeposited Cu pillars. In this work, a self-synthesized polyquaterntum (PQ) was made out with dual suppressor and leveler effects, and was combined with prototypical accelerator bis- (sodium sulfopropyl)-disulfide (SPS) for patterned Cu pillar electroplating. Then, Sn96.5/Ag3.0/Cu0.5 (SAC305) solder paste were screen printed on electroplated Cu pillars and undergo reflow soldering. Kirkendall voids formed at the joint interfaces were observed and quantified by SEM. Finally, XRD, and EBSD were employed to characterize the microstructure under varying conditions. The results indicate that PQ exhibits significant suppressive and levelled properties with the new structure of both leveler and suppressor. However, its effectiveness is dependent on liquid convection. PQ and SPS work synergistically, influencing the polarization effect in various convective environments. Consequently, uneven adsorption occurs on the surface of the Cu pillars, which results in more Kirkendall voids at the corners than at the center along the Cu pillar surface.
Material Characteristics of Compressed Dry Masonry Made of Medium-Size Elements with Perlite Aggregate
Authors: Piekarczyk Adam , Drobiec Łukasz
Published: November 2024

Dry masonry is a type of construction that is nowadays used to a limited extent in the construction sector, including the housing sector. A lack of codified computational methods enabling engineers to design consciously is one of the factors limiting the development of dry walls. This article presents results from testing an innovative solution for dry masonry made of medium-size elements with expanded perlite aggregate. Material with this type of aggregate has a low bulk density (390 ± 10% kg/m3), which allows the production of large blocks and significantly reduces the value of the thermal conductivity coefficient λ = 0.084 ± 0.003 W/m·K. The results obtained were used to determine material parameters for designing a structure mainly exposed to vertical load. The important practical significance of the presented research results from the lack of provisions, specifications or standards allowing for the design, calculation and construction of dry masonry; it is not possible to analyse the behaviour of this type of structure and to design it consciously and safely. The presented research is therefore an important source of information on mechanical parameters essential for the design of structures and provides tools for this. As a result of the tests of nine panels, the mean compressive strength was determined (1.085 N/mm2), and then the procedure of “design assisted by testing” implemented into Eurocode was used to determine characteristic (0.873 N/mm2) and design compressive strength (0.565 N/mm2). Using the relationships σ-ε, an attempt was made to identify material models for the linear and non-linear analysis of the structure and for designing cross-sections. The material models were made considering increased non-linear deformations of a structure under low stresses (the compression toe) which are true and typical for dry masonry. A specific deformability of dry masonry, slightly different to that in masonry structures joined together with mortar, also affects the reduction factor for load-bearing capacity due to second-order effects. Reduction factors determined from true non-linear deformations were lower than the values specified by EC6 for masonry structures.
Evaluation of Pore-Former Size and Volume Fraction on Tape Cast Porous 430 Stainless Steel Substrates for Plasma Spraying
Authors: Yan Yifei , Kesler Olivera
Published: November 2024

Porous 430L stainless steel disks made by tape casting with various pore-former sizes and volume fractions were evaluated as substrates for solid oxide cell (SOC) fabrication by plasma spraying. This work reports the substrate properties relevant to the SOC operation of disks made by using extra fine metal powder with dense sintering to minimize the fine porosity between particles. In contrast, the coarse porosity is introduced by the pore former. We found that the 60 μm pore former at a 45 vol% fraction has the best application fit; it gives an adequate gas permeability of 3.11 × 10−13 m2 and an average open pore size of 45.90 μm. Compared to a commercial substrate with a similar porosity perimeter/steel area ratio, the porosity and gas permeability are 1.6 and 3 times higher, respectively. The detected maximum surface pore is 49 μm, allowing gas-tight electrolytes fabricated by plasma spray deposition.
Mechanical Characterization of Sustainable Mortars with Recycled Aggregates from Construction and Demolition Wastes: An Experimental Investigation
Authors: Soldati Luca , Bacciocchi Michele , Tarantino Angelo Marcello
Published: November 2024

The use of recycled aggregates in the production of concrete and mortar represents a sustainable way to reintroduce these constituents—which are typically treated as waste and disposed of—in the production chain, providing new value to potentially polluting materials. The effect of recycled aggregates has been widely studied in the production of concrete due to the directions of National Standards in Italy; however, their role in the manufacturing of mortar must be investigated further due to the high variability that can be observed in the literature. In particular, the aim of this paper is the mechanical characterization of sustainable mortars defined by different mix designs and different binders, in which the aggregates are gradually replaced by a recycled sand obtained from the grinding of construction and demolition wastes, which could include old concrete, clay bricks, and minimal amounts of other kinds of residual materials. This investigation is carried out through experimentation, taking into account four different mortar compositions defined by an increasing percentage of recycled constituents. Virgin aggregates are also studied for the sake of comparison. The results, accomplished through a three-point bending test and an unconfined compression test, show that it is still possible to maintain acceptable mechanical properties by using these wastes as aggregates in spite of a decrease in the analyzed values. In general, the mean reductions with respect to the use of natural aggregates are about 30–40% and 35–55%, respectively, for compressive and flexural strengths. It should be highlighted that some experimental sets provide a maximum reduction of 70–80%, but the results are still within the limitations of the standards. This aspect can be considered to be a good compromise since the production of this sustainable construction material can represent a solution that is able to reduce the extreme exploitation of natural resources, the pressure on landfills, and the consumption of energy, which are related to the construction industry.
Intelligent Optimization and Impact Analysis of Energy Efficiency and Carbon Reduction in the High-Temperature Sintered Ore Production Process
Authors: Yuan Yuxing , Sun Jingchao , Zhang Lei , Yan Su , Du Tao , Na Hongming
Published: November 2024

The coordinated optimization of energy conservation, efficiency improvement, and pollution reduction in the sintering production process is vital for the efficient and sustainable development of the sintering department. However, previous studies have shown shortcomings in the multi-objective collaborative optimization of sintering systems and the quantification of pollutant impacts. To address these, this paper proposes a multi-objective optimization method integrated with the NSGA-III algorithm and establishes an integrated system optimization model for sintered ore production and high-temperature waste heat recovery. The results demonstrate significant improvements: energy utilization efficiency increased by 0.67%, energy consumption decreased by 17.3 MJ/t, production costs were reduced by 11.45 CNY/t, and the emissions of CO2, SO2, and NOx were reduced by 0.464 kg/t, 0.034 kg/t, and 0.008 kg/t, respectively. Additionally, the study identified optimal configuration parameters and analyzed the quantitative impact of several key factors on multiple indicators. The results also show that reducing the water content of the mixture, decreasing the middling coal content in the fuel, and increasing the thickness of the material layer are effective strategies to reduce energy consumption and pollutant emissions in the sintering process. Overall, implementing these optimizations can bring significant economic and environmental benefits to the steel industry.
Automatic Extraction and Visualization of Interaction Networks for German Fairy Tales
Authors: Schmidt David , Puppe Frank
Published: November 2024

Interaction networks are a method of displaying the significant characters in a narrative text and their interactions. We automatically construct interaction networks from dialogues in German fairy tales by the Brothers Grimm and subsequently visualize these networks. This requires the combination of algorithms for several tasks: coreference resolution for the identification of characters and their appearances, as well as speaker/addressee detection and the detection of dialogue boundaries for the identification of interactions. After an evaluation of the individual algorithms, the predicted networks are evaluated against benchmarks established by networks based on manually annotated coreference and speaker/addressee information. The evaluation focuses on specific components of the predicted networks, such as the nodes, as well as the overall network, employing a newly devised score. This is followed by an analysis of various types of errors that the algorithms can make, like a coreference resolution algorithm not realizing that the frog has transformed into a prince, and their impact on the created networks. We find that the quality of many predicted networks is satisfactory for use cases in which the reliability of edges and character types are not of critical importance. However, there is considerable room for improvement.
A Review on Machine Learning Deployment Patterns and Key Features in the Prediction of Preeclampsia
Authors: Pedersen Louise , Mazur-Milecka Magdalena , Ruminski Jacek , Wagner Stefan
Published: November 2024

Previous reviews have investigated machine learning (ML) models used to predict the risk of developing preeclampsia. However, they have not addressed the intended deployment of these models throughout pregnancy, nor have they detailed feature performance. This study aims to provide an overview of existing ML models and their intended deployment patterns and performance, along with identified features of high importance. This review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. The search was performed in January and February 2024. It included all papers published before March 2024 obtained from the scientific databases: PubMed, Engineering Village, the Association for Computing Machinery, Scopus, and Web of Science. Of a total of 198 identified studies, 18 met the inclusion criteria. Among these, 11 showed the intent to use the ML model as a single-use tool, two intended a dual-use, and two intended multiple-use. Ten studies listed the features of the highest importance, with systolic and diastolic blood pressure, mean arterial pressure, and hypertension frequently mentioned as critical predictors. Notably, three of the four studies proposing dual or multiple-use models were conducted in 2023 and 2024, while the remaining study is from 2009. No single ML model emerged as superior across the subgroups of PE. Incorporating body mass index alongside hypertension and either mean arterial pressure, diastolic blood pressure, or systolic blood pressure as features may enhance performance. The deployment patterns mainly focused on single use during gestational weeks 11+0 to 14+1.
Hybridization and Optimization of Bio and Nature-Inspired Metaheuristic Techniques of Beacon Nodes Scheduling for Localization in Underwater IoT Networks
Authors: Draz Umar , Ali Tariq , Yasin Sana , Chaudary Muhammad Hasanain , Ayaz Muhammad , Aggoune El-Hadi M. , Yasin Isha
Published: November 2024

This research introduces a hybrid approach combining bio- and nature-inspired metaheuristic algorithms to enhance scheduling efficiency and minimize energy consumption in Underwater Acoustic Sensor Networks (UASNs). Five hybridized algorithms are designed to efficiently schedule nodes, reducing energy costs compared to existing methods, and addressing the challenge of unscheduled nodes within the communication network. The hybridization techniques such as Elephant Herding Optimization (EHO) with Genetic Algorithm (GA), Firefly Algorithm (FA), Levy Firefly Algorithm (LFA), Bacterial Foraging Algorithm (BFA), and Binary Particle Swarm Optimization (BPSO) are used for optimization. To implement these optimization techniques, the Scheduled Routing Algorithm for Localization (SRAL) is introduced, aiming to enhance node scheduling and localization. This framework is crucial for improving data delivery, optimizing Route REQuest (RREQ) and Routing Overhead (RO), while minimizing Average End-to-End (AE2E) delays and localization errors. The challenges of node localization, RREQ reconstruction at the beacon level, and increased RO, along with End-to-End delays and unreliable data forwarding, have a significant impact on overall communication in underwater environments. The proposed framework, along with the hybridized metaheuristic algorithms, show great potential in improving node localization, optimizing scheduling, reducing energy costs, and enhancing reliable data delivery in the Internet of Underwater Things (IoUT)-based network.
A Bilevel Approach to the Facility Location Problem with Customer Preferences Under a Mill Pricing Policy
Authors: Calvete Herminia I. , Galé Carmen , Hernández Aitor , Iranzo José A.
Published: November 2024

This paper addresses the facility location problem under a mill pricing policy, integrating customers’ behavior through the concept of preferences. The problem is modeled as a bilevel optimization problem, where the existence of ties in customers’ preferences can lead to an ill-posed bilevel problem due to the possible existence of multiple optima to the lower-level problem. As the commonly employed optimistic and pessimistic strategies are inadequate for this problem, a specific approach is proposed bearing in mind the customers’ rational behavior. In this work, we propose a novel formulation of the problem as a bilevel model in which each customer faces a lexicographic biobjective problem in which the preference is maximized and the total cost of accessing the selected facility is minimized. This allows for a more accurate representation of customer preferences and the resulting decisions regarding facility location and pricing. To address the complexities of this model, we apply duality theory to the lower-level problems and, ultimately, reformulate the bilevel problem as a single-level mixed-integer optimization problem. This reformulation incorporates big-M constants, for which we provide valid bounds to ensure computational tractability and solution quality. The computational study conducted allows us to assess, on the one hand, the effectiveness of the proposed reformulation to address the bilevel model and, on the other hand, the impact of the length of the customer preference lists and fixed opening cost for facilities on the computational time and the optimal solution.
Design and Optimization of Microfluidic Vortex Diode
Authors: Tadyszak Krzysztof , Jäger Alessandro , Pánek Jiří , Hrubý Martin
Published: November 2024

The performed research presents modeling results for designing microfluidic vortex diodes. These devices rectify fluid flow and can be used in many applications on micro and macro scales. The modeling, utilizing computational fluid dynamics (CFD) with the turbulence model RANS k-ε in COMSOL Multiphysics, has led to optimizing diodicity—the reversed-to-forward flow pressure drop ratio. The goal was to find the best flow-rectifying geometry within the 2D vortex-type design by changing the wall geometry, diode shape, and inflow velocities, identifying significant parameters and dependencies. Improving diodicity can be achieved by increasing the radius r1 of the central channel, increasing the entire diode radius r2, decreasing the width w of the rectangular channel, and reducing its length L. Additionally, changing the circular shape of the diode to an elliptical one can improve diodicity. The significance of this research is evident in the potential applications of these devices in microfluidic setups where fixed-geometry unidirectional flow is required, e.g., mixing, filtration, cell separation, and drug delivery, or on industrial scales, e.g., energy harvesting, wastewater treatment, and water sterilization.
Screening for Potential Antiviral Compounds from Cyanobacterial Secondary Metabolites Using Machine Learning
Authors: Zhang Tingrui , Sun Geyao , Cheng Xueyu , Cao Cheng , Cai Zhonghua , Zhou Jin
Published: November 2024

The secondary metabolites of seawater and freshwater blue-green algae are a rich natural product pool containing diverse compounds with various functions, including antiviral compounds; however, high-efficiency methods to screen such compounds are lacking. Advanced virtual screening techniques can significantly reduce the time and cost of novel antiviral drug identification. In this study, we used a cyanobacterial secondary metabolite library as an example and trained three models to identify compounds with potential antiviral activity using a machine learning method based on message-passing neural networks. Using this method, 364 potential antiviral compounds were screened from >2000 cyanobacterial secondary metabolites, with amides predominating (area under the receiver operating characteristic curve value: 0.98). To verify the actual effectiveness of the candidate antiviral compounds, HIV virus reverse transcriptase (HIV-1 RT) was selected as a target to evaluate their antiviral potential. Molecular docking experiments demonstrated that candidate compounds, including kororamide, mollamide E, nostopeptolide A3, anachelin-H, and kasumigamide, produced relatively robust non-covalent bonding interactions with the RNase H active site on HIV-1 RT, supporting the effectiveness of the proposed screening model. Our data demonstrate that artificial intelligence-based screening methods are effective tools for mining potential antiviral compounds, which can facilitate the exploration of various natural product libraries.
Study of Bacillus cereus as an Effective Multi-Type A Trichothecene Inactivator
Authors: García-García Fernando Abiram , Cristiani-Urbina Eliseo , Morales-Barrera Liliana , Rodríguez-Peña Olga Nelly , Hernández-Portilla Luis Barbo , Campos Jorge E. , Flores-Ortíz Cesar Mateo
Published: November 2024

Type A trichothecenes are common mycotoxins in stored cereal grains, where co-contamination is likely to occur. Seeking new microbiological options capable of inactivating more than one type A trichothecene, this study aimed to analyze facultative anaerobe bacteria isolated from broiler proventriculus. For this purpose, type A trichothecenes were produced in vitro, and a facultative anaerobic bacterial consortium was obtained from a broiler’s proventriculus. Then, the most representative bacterial strains were purified, and trichothecene inactivating assays were performed. Finally, the isolate with the greatest capacity to remove all tested mycotoxins was selected for biosorption assays. The results showed that when the consortium was tested, neosolaniol (NEO) was the most degraded mycotoxin (64.55%; p = 0.008), followed by HT-2 toxin (HT-2) (22.96%; p = 0.008), and T-2 toxin (T-2) (20.84%; p = 0.014). All isolates were bacillus-shaped and Gram-positive, belonging to the Bacillus and Lactobacillus genera, of which B. cereus was found to remove T-2 (28.35%), HT-2 (32.84%), and NEO (27.14%), where biosorption accounted for 86.10% in T-2, 35.59% in HT-2, and 68.64% in NEO. This study is the first to prove the capacity of B. cereus as an effective inactivator and binder of multi-type A trichothecenes.
Microbial Biodiversity in Sediment from the Amuyo Ponds: Three Andean Hydrothermal Lagoons in Northern Chile
Authors: Vilo Claudia , Fábrega Francisca , Campos Víctor L. , Gómez-Silva Benito
Published: November 2024

The Amuyo Ponds (APs) are a group of three brackish hydrothermal lagoons located at 3700 m above sea level in a pre-Andean setting in the Atacama Desert. Each pond shows a conspicuous green (GP), red (RP), or yellow (YP) coloration, and discharges water rich in arsenic and boron into the Caritaya River (Camarones Basin, northern Chile). Microorganisms are subjected to harsh environmental conditions in these ponds, and the microbial composition and diversity in the Amuyo Ponds’ sediments are unknown. The microbial life colonizing AP sediments was explored by metagenomics analyses, showing a diverse microbial life dominated by members of the bacterial domain, with nearly 800 bacterial genome sequences, and sequences associated with Archaea, Eukarya, and viruses. The genus Pseudomonas was more abundant in GP and YP sediments, while the genera Pseudomonas, Aeromonas, and Shewanella were enriched in RP sediments. Archaeal composition was similar in all sediments, and enriched with methanogens sequences from the Archaeoglobi and Halobacteria classes. Abundant fungi sequences were detected in all sediments from the phyla Blastocladiomycota and Ascomycota. We also report putative functional capabilities related to virulence and defense genes, the biosynthesis of secondary metabolites, and tolerance to arsenic. Thirteen bacterial and fourteen viral metagenome-assembled genomes were reconstructed and informed here. This work expands our knowledge on the richness of the microorganisms in the APs and open further studies on the ecology and genomics of this striking Andean geosite.
Indoor Airborne Microplastics: Human Health Importance and Effects of Air Filtration and Turbulence
Authors: Gaylarde Christine C. , Baptista Neto José Antonio , da Fonseca Estefan M.
Published: November 2024

Microplastics (MPs) are omnipresent particles that receive special attention because of their persistent nature and their potential impact on human disease and on the environment. Most MPs are generated by the degradation of larger plastic items such as clothing, car tires, and discarded plastic materials. In indoor environments, where human beings spend most of their time, aerial MP levels are higher, and the majority are fibers produced from textiles. Airborne MPs indoors are a greater potential danger to humans than MPs ingested in food and drink. Fragments small enough to remain substantially suspended in the air column, the small airborne microparticles that are measured as PM10 and PM2.5, become available for assimilation by human beings through respiration, potentially producing various health problems. Larger MPs act by ingestion and skin contact. MPs can carry microorganisms and micropollutants adsorbed to their surfaces, facilitating their uptake and survival within the human body. Indoor airborne MPs thus represent emerging pollutants of fast-growing concern that are especially important as potential invaders of the human respiratory system, reaching the alveoli of the lungs and finally entering the circulatory system and other tissues. Since this direct human exposure to MP contamination via indoor air is so important, we discuss in this article the ways in which MP concentration and dispersal in indoor air can be affected by air turbulence that is induced by anthropogenic objects such as air conditioners, filters, and purifiers. Much evidence is equivocal and further research is necessary.
Selective Leaching of Lithium and Beyond: Sustainable Eggshell-Mediated Recovery from Spent Li-Ion Batteries
Authors: Shalchian Hossein , Khalili Maryam , Kiani-Rashid Alireza , Nateq Behzad , Vegliò Francesco
Published: November 2024

This study introduces an innovative strategy for the selective leaching of lithium from spent Li-ion batteries. Based on thermodynamic assessments and exploiting waste eggshells as a source of calcium carbonate, an impressive 38% of lithium was dissolved selectively through mechanical milling and water leaching, outperforming conventional thermochemical methods. Afterwards, a hydrogen peroxide-assisted sulfuric acid leaching was also implemented to solubilize targeted elements (Mn, Co, Ni, and Li), with an exceptional 99% efficiency in Mn removal from the leachate using potassium permanganate and a pH range of 1.5 to 3.5. Selective separations of Co and Ni were then facilitated utilizing CYANEX 272 and n-heptane. This comprehensive study presents a promising and sustainable avenue for the effective recovery of Li and associated co-elements from spent lithium batteries.
Predicting Cyclist Speed in Urban Contexts: A Neural Network Approach
Authors: Montoya-Zamora Ricardo , Ramírez-Granados Luisa , López-Lara Teresa , Hernández-Zaragoza Juan Bosco , Guzmán-Cruz Rosario
Published: November 2024

Bicycle use has become more important today, but more information and planning models are needed to implement bike lanes that encourage cycling. This study aimed to develop a methodology to predict the speed a cyclist can reach in an urban environment and to provide information for planning cycling infrastructure. The methodology consisted of obtaining GPS data on longitude, latitude, elevation, and time from a smartphone of two groups of cyclists to calculate the speeds and slopes through a model based on a recurrent short-term memory (LSTM) type neural network. The model was trained on 70% of the dataset, with the remaining 30% used for validation and varying training epochs (100, 200, 300, and 600). The effectiveness of recurrent neural networks in predicting the speed of a cyclist in an urban environment is shown with determination coefficients from 0.77 to 0.96. Average cyclist speeds ranged from 6.1 to 20.62 km/h. This provides a new methodology that offers valuable information for various applications in urban transportation and bicycle line planning. A limitation can be the variability in GPS device accuracy, which could affect speed measurements and the generalizability of the findings.
Machine Learning-Based Optimization Models for Defining Storage Rules in Maritime Container Yards
Authors: Ambrosino Daniela , Xie Haoqi
Published: November 2024

This paper proposes an integrated approach to define the best consignment strategy for storing containers in an export yard of a maritime terminal. The storage strategy identifies the rules for grouping homogeneous containers, which are defined simultaneously with the assignment of each group of containers to the available blocks (bay-locations) in the yard. Unlike recent literature, this study focuses specifically on weight classes and their respective limits when establishing the consignment strategy. Another novel aspect of this work is the integration of a data-driven algorithm and operations research. The integrated approach is based on unsupervised learning and optimization models and allows us to solve large instances within a few seconds. Results obtained by spectral clustering are treated as input datasets for the optimization models. Two different formulations are described and compared: the main difference lies in how containers are assigned to bay-locations, shifting from a time-consuming individual container assignment to the assignment of groups of containers, which offers significant advantages in computational efficiency. Experimental tests are organized into three campaigns to evaluate the following: (i) The computational time and solution quality (i.e., space utilization) of the proposed models; (ii) The performance of these models against a benchmark model; (iii) The practical effectiveness of the proposed solution approach.
Synthesis of Side-Chain Liquid Crystalline Polyacrylates with Bridged Stilbene Mesogens
Authors: Konishi Gen-ichi , Sawatari Yuki , Iwai Riki , Tanaka Takuya , Shimomura Yoshimichi , Tokita Masatoshi
Published: November 2024

In recent years, π-conjugated liquid crystalline molecules with optoelectronic functionalities have garnered considerable attention, and integrating these molecules into side-chain liquid crystalline polymers (SCLCPs) holds potential for developing devices that are operational near room temperature. However, it is difficult to design SCLCPs with excellent processability because liquid crystalline mesogens are rigid rods, have low solubility in organic solvents, and have a high isotropization temperature. Recently, we developed near-room-temperature π-conjugated nematic liquid crystals based on “bridged stilbene”. In this work, we synthesized a polyacrylate SCLCP incorporating a bridged stilbene that exhibited a nematic phase near room temperature and could maintain liquid crystallinity for more than three months. We conducted a thorough phase structure analysis and evaluated the optical properties. The birefringence values of the resulting polymers were higher than those of the corresponding monomers because of the enhanced order parameters due to the polymer effect. In addition, the synthesized polymers inherited mesogen-derived AIE properties, with high quantum yields (Φfl = 0.14–0.35) in the solid state. It is noteworthy that the maximum fluorescence wavelength exhibited a redshift of greater than 27 nm as a consequence of film formation. Thus, several unique characteristics of the SCLCPs are unattainable with small molecular systems.
N-glycosylation Modification Reveals Insights into the Oxidative Reactions of Liver in Wuzhishan Pigs
Authors: Ren Yuwei , Wang Feng , Sun Ruiping , Zhang Yan , Zheng Xinli , Liu Hailong , Chen Linlin , Lin Yanning , Zhao Yujie , Liang Mingxia , Chao Zhe
Published: November 2024

Although porcine liver contributes to their growth and development by nutrition production and energy supply, oxidative stress-induced hepatocyte damage is inevitable during metabolism. N-glycosylation is a common modification in oxidation; nevertheless, the effects of N-glycosylation on pig liver oxidative reactions remain undefined. In this study, liver proteins with N-glycosylation were detected in Wuzhishan (WZS) pigs between 4 and 8 months old and Large White (LW) pigs at 4 months old based on LC-MS/MS. The results showed that the number of differentially expressed proteins (DEPs) was larger between different pig cultivars than that between WZS pigs at various growth periods. The enriched pathways of DEPs were mainly related to oxidative reactions, and 10 proteins were finally selected that primarily consisted of CYPs, GSTs and HSPs with expressions significantly correlating to liver size and weight. The oxidative genes shared N-glycosylation-modified models of N-x-S and N-G. Five out of 10 proteins were upregulated in WZS pigs compared to LW pigs at 4 months old, while five proteins increased in WZS pigs from 4 to 8 months old. In conclusion, this research provides valuable information on the N-glycosylation motifs in liver oxidation genes of WZS pigs.
Thermodynamic Evaluation of Novel 1,2,4-Triazolium Alanine Ionic Liquids as Sustainable Heat-Transfer Media
Authors: Liang Kunhao , Yao Haiyun , Qiao Jing , Gao Shan , Zong Mingji , Liu Fengshou , Yang Qili , Liang Lanju , Fang Dawei
Published: November 2024

Ionic liquids, which are widely recognized as environmentally friendly solvents, stand out as promising alternatives to traditional heat-transfer fluids due to their outstanding heat-storage and heat-transfer capabilities. In the course of our ongoing research, we successfully synthesized ionic liquids 1-ethyl-4-alkyl-1,2,4-triazolium alanine [Taz(2,n)][Ala], where (n = 4, 5); in this study, we present comprehensive data on their density, surface tension, isobaric molar heat capacity, and thermal conductivity for the first time. The key thermophysical parameters influencing the heat-transfer process, such as thermal expansibility, compressibility, isochoric heat capacity, and heat-storage density, were meticulously calculated from experimental data. Upon comparison with previously reported ionic liquids and commercially utilized heat-transfer fluids, [Taz(2,n)][Ala] demonstrated superior heat-storage and heat-transfer performance, particularly in terms of heat-storage density (~2.63 MJ·m−3·K−1), thermal conductivity (~0.190 W·m−1·K−1), and melting temperature (~226 K). Additionally, the presence of the alanine anion in [Taz(2,n)][Ala] provides more possibilities for its functional application.
Widely Targeted Metabolomics Method Reveals Differences in Volatile and Nonvolatile Metabolites in Three Different Varieties of Raw Peanut by GC–MS and HPLC–MS
Authors: Fu Jiantao , An Yuxing , Yao Dao , Chen Lijun , Zhou Liwen , Shen Dachun , Dai Sixing , Lu Yinglin , Sun Donglei
Published: November 2024

The aim of the present study was to comprehensively analyze and identify the metabolites of different varieties of raw peanut, as well as provide a reference for the utilization of different varieties of peanuts. In this study, three varieties of peanuts, namely ZKH1H, ZKH13H, and CFD, were investigated via ultrahigh-performance liquid chromatography (UPLC) and widely targeted metabolomics methods based on tandem mass spectrometry (MS) and solid-phase microextraction-gas chromatography–mass spectrometry (SPME-GC–MS). In total, 417 nonvolatile and 55 volatile substances were detected. The nonvolatile substances were classified into the following 10 categories: organic acids and derivatives (28.9%); organic oxygen compounds (21.9%); lipids and lipid-like molecules (12.6%); organoheterocyclic compounds (9.9%); nucleosides, nucleotides, and analogues (9.4%); benzenoids (7.8%); phenylpropanoids and polyketides (6.1%); organic nitrogen compounds (2.7%); lignans, neolignans, and related compounds (0.5%); and alkaloids and their derivatives (0.3%). The volatile compounds (VOCs) were classified into the following eight categories: organic oxygen compounds (24.1%); organic cyclic compounds (20.4%); organic nitrogen compounds (13%); organic acids and their derivatives (13%); lipids and lipid-like molecules (11.2%); benzenoids (11.1%); hydrocarbons (3.7%); and homogeneous non-metallic compounds (3.7%). Differentially abundant metabolites among the different peanut varieties (ZKH13H vs. CFD, ZKH1H vs. CFD, and ZKH1H vs. ZKH13H) were investigated via multivariate statistical analyses, which identified 213, 204, and 157 nonvolatile differentially abundant metabolites, respectively, and 12, 11, and 10 volatile differentially abundant metabolites, respectively. KEGG metabolic pathway analyses of the differential non-VOCs revealed that the most significant metabolic pathways among ZKH13H vs. CFD, ZKH1H vs. CFD, and ZKH1H vs. ZKH13H were galactose metabolism, purine metabolism, and aminoacyl-tRNA, while the nitrogen metabolism pathway was identified as a significant metabolic pathway for the VOCs. The present findings provide a theoretical foundation for the development and utilization of these three peanut species, as well as for the breeding of new peanut varieties.