bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimization of Redundant Degrees of Freedom in Robotic Flat-End Milling Based on Dynamic Response
Authors: Liu Jinyu , Zhao Yiyang , Niu Yuqin , Cao Jiabin , Zhang Lin , Zhao Yanzheng
Published: February 2024

With the advantages of large working space, low cost and more flexibility, industrial robots have become an important carrier in intelligent manufacturing. Due to the low rigidity of robotic milling systems, cutting vibrations are inevitable and have a significant impact on surface quality and machining accuracy. To improve the machining performance of the robot, a posture optimization approach based on the dynamic response index is proposed, which combines posture-dependent dynamic characteristics with surface quality for robotic milling. First, modal tests are conducted at sampled points to estimate the posture-dependent dynamic parameters of the robotic milling system. The modal parameters at the unsampled points are further predicted using the inverse distance weighted method. By combining posture-independent modal parameters with calibrating the cutting forces, a dynamic model of a robotic milling system is established and solved with a semi-discretization method. A dynamic response index is then introduced, calculated based on the extraction of the vibration signal peaks. The optimization model is validated through milling experiments, demonstrating that optimizing redundant angles significantly enhances milling stability and quality.
Monte Carlo Simulation of Electron Interactions in an MeV-STEM for Thick Frozen Biological Sample Imaging
Authors: Wang Liguo , Yang Xi
Published: February 2024

A variety of volume electron microscopy techniques have been developed to visualize thick biological samples. However, the resolution is limited by the sliced section thickness (>30–60 nm). To preserve biological samples in a hydrated state, cryo-focused ion beam scanning electron microscopy has been developed, providing nm resolutions. However, this method is time-consuming, requiring 15–20 h to image a 10 μm thick sample with an 8 nm slice thickness. There is a pressing need for a method that allows the rapid and efficient study of thick biological samples while maintaining nanoscale resolution. The remarkable ability of mega-electron-volt (MeV) electrons to penetrate thick biological samples, even exceeding 10 μm in thickness, while maintaining nanoscale resolution, positions MeV-STEM as a suitable microscopy tool for such applications. Our research delves into understanding the interactions between MeV electrons and frozen biological specimens through Monte Carlo simulations. Single elastic scattering, plural elastic scattering, single inelastic scattering, and plural inelastic scattering events have been simulated. The electron trajectories, the beam profile, and the intensity change of electrons in each category have been investigated. Additionally, the effects of the detector collection angle and the focal position of the electron beam were investigated. As electrons penetrated deeper into the specimen, single and plural elastic scattered electrons diminished, and plural inelastic scattered electrons became dominant, and the beam profile became wider. Even after 10 μm of the specimen, 42% of the MeV electrons were collected within 10 mrad. This confirms that MeV-STEM can be employed to study thick biological samples.
Optimization of Buoy Shape for Wave Energy Converter Based on Particle Swarm Algorithm
Authors: Ge Wei , Ji Shui , Jin Yeqing , He Shijie , Chen Hailong , Liu Hengxu
Published: February 2024

In order to improve the wave energy capture rate of the buoy of a wave energy generation device, this paper proposes a multi-degree of freedom method to optimize the shape of the buoy with maximum wave energy capture. Firstly, a multi-degree of freedom wave energy converter was designed, and the buoy shape was defined using a B-spline curve to generate the shape vector; then, a numerical model of the multi-degree of freedom wave energy converter was established and numerical calculations were carried out using AQWA/WEC-Sim software; on this basis, the particle swarm optimization algorithm was introduced to find the buoy shape corresponding to the maximum wave energy capture. Finally, the optimization of the buoy shape was in irregular waves. The results show that as the wave energy capture increased, the buoy shape tended to be flatter, with a smaller taper, and the optimal buoy shape had a better motion response than the conventional cone buoy. Eventually, the correctness of the buoy shape optimization method was verified through experimental testing.
Exploring the Antifungal Activity of Various Natural Extracts in a Sustainable Saccharomyces cerevisiae Model Using Cell Viability, Spot Assay, and Turbidometric Microbial Assays
Authors: Letsiou Sophia , Pyrovolou Katerina , Konteles Spyros J. , Trapali Maria , Krisilia Sophia , Kokla Vasiliki , Apostolaki Alexandra , Founda Violeta , Houhoula Dimitra , Batrinou Anthimia
Published: February 2024

Saccharomyces cerevisiae is a sustainable yeast with many applications in the food industry. Here, we study the use of a Saccharomyces cerevisiae model composed of three different industrial strains (a wine, a beer and a baker’s strain) to assess the antifungal activity of three organic plant-based extracts (Hypericum perforatum 10% w/w, Pistacia lentiscus var. Chia 20% w/w and Rosmarinus officinalis 6% w/w). Three different methods were employed (agar disc diffusion, spot assay, and growth curve analysis). Only the Rosmarinus officinalis extract (6% w/w) exhibited inhibitory activity against all the tested yeast strains in the agar disc diffusion method. In the spot assay, all extracts and their carrier oils (sunflower oil and caprylic triglyceride) exerted similar mild antifungal activity. In the growth curve analysis, all extracts significantly lowered the growth rate of the yeasts, but this was not observed for the carrier oils. The results highlighted that it is important to consider more than one method for testing the antimicrobial activity of different compounds. The three yeast strains exhibited differences in their susceptibility to pharmaceutical antifungals, and the beer and baker’s yeasts were resistant to itraconazole. Moreover, polyphenols were detected in all natural extracts which may be linked to their antifungal activity. Our results suggest that we might consider multiple use of these natural extracts in the food industry as food additives or even preservatives to delay food spoilage.
Experimental Study and Bearing Capacity Calculation of Compression-Reinforced Concrete Columns Strengthened with Ultra-High-Performance Concrete
Authors: Liu Xianhui , Pan Meiqing , Li Weizhao , Jing Chenggui , Chang Wenlong , Zhang Haoyang
Published: February 2024

A total of five ultra-high-performance concrete (UHPC)-strengthened reinforced concrete (RC) columns and one RC column were built and subjected to eccentric compression testing to examine the force performance of UHPC-strengthened eccentrically compressed plain RC columns. This experimental study examined the crack progression, the damage morphology, the deformation ability, the maximum load-carrying capacity, and the ductile properties of the eccentrically compressed columns. It also investigated the impacts of eccentricity, the reinforcement thickness, and the addition of steel fibers on the effectiveness of reinforcement. The cracking load, peak load, and ductility coefficient of the UHPC-reinforced specimens were increased by 100.28%, 172.30%, and 56.30%, respectively, compared with the RC column at an initial eccentricity of 50 mm. As the eccentricity distance increased, the bearing capacity of the UHPC eccentrically compressed specimens decreased, and the deformation capacity increased. Increasing the steel fiber dosage within the appropriate range decreased the crack width of the specimen. The addition of 2% steel fiber resulted in a 24.8% increase in cracking load, an 8.96% increase in peak load, and a 2.60% increase in ductility coefficient compared to the addition of 1% steel fiber. However, the reinforcing effect of UHPC was weakened under high eccentric pressures. Based on the theory of concrete structure and mechanical principles, the formula for calculating the compressive bearing capacity of RC columns strengthened with high-performance concrete was proposed. The results of calculating the positive section bearing capacity of eccentrically compressed RC columns reinforced with high-performance concrete are in good agreement with the test values. The results of this paper provide an experimental basis and theoretical foundation for the cross-sectional design of UHPC eccentrically compressed columns.
State–Space Modelling and Stability Analysis of Solid-State Transformers for Resilient Distribution Systems
Authors: Mishra Dillip Kumar , Abbasi Mohammad Hossein , Eskandari Mohsen , Paudel Saroj , Sahu Sourav K. , Zhang Jiangfeng , Li Li
Published: February 2024

Power grids are currently undergoing a significant transition to enhance operational resilience and elevate power quality issues, aiming to achieve universal access to electricity. In the last few decades, the energy sector has witnessed substantial shifts toward modernizing distribution systems by integrating innovative technologies. Among the innovations, the solid-state transformer (SST) is referred to as a promising technology due to its flexible power control (better reliability) and high efficacy (by decreasing losses) compared with traditional transformers. The design of SST has combined three-stage converters, i.e., the input, isolation, and output stages. The key objective of this design is to implement a modern power distribution system to make it a more intelligent and reliable device in practice. As the power converters are used in SST, they exhibit non-linear behavior and can introduce high-frequency components, making stability more challenging for the system. Besides, the stability issue can be even more complicated by integrating the distributed energy resources into the distribution system. Thus, the stability of SST must be measured prior to /during the design. To determine stability, state-space modeling, and its controller design are important, which this paper explains in detail. Indeed, the system’s stability is measured through the controllability and observability test. Further, the stability analysis is performed using frequency and time-domain diagrams: the Bode plot, Nyquist plot, Nichols chart, Root locus, pole-zero plot, and Eigen plot. Finally, the SST Simulink model is tested and validated through real-time digital simulation using the OPALRT simulator to show its effectiveness and applicability. The stability performance of the proposed SST is evaluated and shows the effectiveness of the controller design of each converter circuit.
Model for Determining the Psycho-Emotional State of a Person Based on Multimodal Data Analysis
Authors: Shakhovska Nataliya , Zherebetskyi Oleh , Lupenko Serhii
Published: February 2024

The paper aims to develop an information system for human emotion recognition in streaming data obtained from a PC or smartphone camera, using different methods of modality merging (image, sound and text). The objects of research are the facial expressions, the emotional color of the tone of a conversation and the text transmitted by a person. The paper proposes different neural network structures for emotion recognition based on unimodal flows and models for the margin of the multimodal data. The analysis determined that the best classification accuracy is obtained for systems with data fusion after processing each channel separately and obtaining individual characteristics. The final analysis of the model based on data from a camera and microphone or recording or broadcast of the screen, which were received in the “live” mode, gave a clear understanding that the quality of the obtained results is highly dependent on the quality of the data preparation and labeling. This is directly related to the fact that the data on which the neural network is trained is highly qualified. The neural network with combined data on the penultimate layer allows a psycho-emotional state recognition accuracy of 0.90 to be obtained. The spatial distribution of emotion analysis was also analyzed for each data modality. The model with late fusion of multimodal data demonstrated the best recognition accuracy.
Assessing Environmental Justice at the Urban Scale: The Contribution of Lichen Biomonitoring for Overcoming the Dichotomy between Proximity-Based and Distribution-Based Approaches
Authors: Contardo Tania , Loppi Stefano
Published: February 2024

In this study, we tested the use of lichen biomonitoring techniques for the assessment of air quality disparities at the urban scale. We based our evaluation on the results of a previous lichen biomonitoring study carried out in Milan (Northern Italy), which estimates the contamination by potentially toxic elements (PTEs) and its distribution over the area, also providing an evaluation of the main emission sources. Therefore, we used the traditional methodologies for environmental justice assessment: the proximity-based and the distribution-based approaches. The workflow we propose is a data-driven selection of emission sources that contributes to overcoming the dichotomy between the two approaches and is now widely debated in the scientific community. A socio-economic deprivation index was elaborated for each census unit of Milan city and then related to the proximity of the emission sources previously selected. The results suggested that in the surrounding of industries and railways, the deprivation is higher, while the proximity of main roads is inhabited by wealthier populations. The distribution-based approach was run through a quantile regression analysis, and the outcome indicated that among the wealthier groups, an increase in contamination is followed by an increase in socio-economic deprivation, whilst among the deprived groups, people with greater economic opportunities tend, however, to live in worse air quality conditions due to the proximity of communication routes. This study poses the potential to review the classical methods of EJ assessment, providing a reliable workflow applicable in urban areas—the most vulnerable in terms of air quality disparities in the present and in the future.
Understanding the Inter-Model Spread of PDO’s Impact on Tropical Cyclone Frequency over the Western North Pacific in CMIP6 Models
Authors: Feng Jiawei , Cao Jian , Wang Boyang , Zhao Kai
Published: February 2024

This work investigates the inter-model diversity of the Pacific Decadal Oscillation’s (PDO) impact on tropical cyclone frequency (TCF) over the Western North Pacific (WNP) from the historical simulation of twenty-two Coupled Model Intercomparison Project Phase 6 (CMIP6) models. The impact of the PDO is expressed as the TCF difference between the positive and negative PDO phases. The comparison between the models with high PDO skill and low PDO skill shows that the PDO-related sea surface temperature (SST) gradient between the western and central tropical Pacific plays an important role in changing the large-scale atmospheric dynamic fields for TC genesis and, thus, the TCF over the WNP. This SST gradient also significantly contributes to the inter-model spread of PDO’s impact on TCF across the 22 CMIP6 models. We, therefore, stress that the PDO-related eastward SST gradient between the western and central tropical Pacific triggers the lower troposphere westerly and eastward extending of the monsoon trough over the WNP. The moistening of the atmosphere and enhancing ascending motion in the mid-troposphere promote convection, leading to the easterly wind anomaly over the upper troposphere, which reduces the vertical wind shear. Those favorable dynamic conditions consistently promote the TC formation over the southeastern part of the Western North Pacific. Our results highlight that PDO could impact the WNP TCF through its associated tropical SST gradient.
Improvement of Stable Atmospheric Boundary Simulation with High-Spatiotemporal-Resolution Nudging over the North China Plain
Authors: Xu Tingting , Peng Zhuohao , Wang Yan , Wan Chaoyue , Liu Shenlan , Jiang Shuqiao , Tang Xiaolu , Zhao Xilin
Published: February 2024

The WRF model often struggles to accurately replicate specific characteristics of the atmospheric boundary layer, particularly under highly stable conditions. In this study, we reconstructed an OBS-nudging module using meteorological data with high spatiotemporal resolution, then coupled it in the WRF model (WRF-OBS) to improve stable boundary layer (SBL) simulation over the North China Plain (NCP). The results showed that WRF-OBS improved the simulation of SBL characteristics and reduced the deviation from observations significantly. The correlations (R2) between WRF-OBS simulations and observations of 2 m temperature, relative humidity, and 10 m wind speed at 460 stations across the NCP were 0.72, 0.56, and 0.75, respectively, which were much higher than the values for results from the unassimilated WRF model (WRF-BS). The simulated vertical profiles of temperature, relative humidity, and wind were generally consistent with observations at Pingyuan station. The meteorological factors which caused heavy air pollution was also investigated based on WRF-OBS simulation. The SBL characteristics obtained from WRF-OBS showed that light wind persisted over the NCP region during the period of heavy pollution, and Pingyuan was affected by warm and humid air. Vertically, the persistent temperature inversion at Pingyuan station was one of the main drivers of the heavy pollution. The WRF-OBS simulation captured the characteristics of the two temperature inversion layers very well. The two inversion layers covered the NCP, with a horizontal scale of approximately 200 km, and created very stable conditions, preventing the vertical diffusion of pollutants and maintaining high PM2.5 concentrations.
Mathematical Models and Simulations
Authors: Nastasi Giovanni
Published: February 2024

In this editorial, we present the Special Issue of the scientific journal Axioms entitled “Mathematical Models and Simulations” [...]
Democratic Erosion of Data-Opolies: Decentralized Web3 Technological Paradigm Shift Amidst AI Disruption
Authors: Calzada Igor
Published: February 2024

This article investigates the intricate dynamics of data monopolies, referred to as “data-opolies”, and their implications for democratic erosion. Data-opolies, typically embodied by large technology corporations, accumulate extensive datasets, affording them significant influence. The sustainability of such data practices is critically examined within the context of decentralized Web3 technologies amidst Artificial Intelligence (AI) disruption. Additionally, the article explores emancipatory datafication strategies to counterbalance the dominance of data-opolies. It presents an in-depth analysis of two emergent phenomena within the decentralized Web3 emerging landscape: People-Centered Smart Cities and Datafied Network States. The article investigates a paradigm shift in data governance and advocates for joint efforts to establish equitable data ecosystems, with an emphasis on prioritizing data sovereignty and achieving digital self-governance. It elucidates the remarkable roles of (i) blockchain, (ii) decentralized autonomous organizations (DAOs), and (iii) data cooperatives in empowering citizens to have control over their personal data. In conclusion, the article introduces a forward-looking examination of Web3 decentralized technologies, outlining a timely path toward a more transparent, inclusive, and emancipatory data-driven democracy. This approach challenges the prevailing dominance of data-opolies and offers a framework for regenerating datafied democracies through decentralized and emerging Web3 technologies.
Towards Automation in Radiotherapy Planning: A Deep Learning Approach for the Delineation of Parotid Glands in Head and Neck Cancer
Authors: Kakkos Ioannis , Vagenas Theodoros P. , Zygogianni Anna , Matsopoulos George K.
Published: February 2024

The delineation of parotid glands in head and neck (HN) carcinoma is critical to assess radiotherapy (RT) planning. Segmentation processes ensure precise target position and treatment precision, facilitate monitoring of anatomical changes, enable plan adaptation, and enhance overall patient safety. In this context, artificial intelligence (AI) and deep learning (DL) have proven exceedingly effective in precisely outlining tumor tissues and, by extension, the organs at risk. This paper introduces a DL framework using the AttentionUNet neural network for automatic parotid gland segmentation in HN cancer. Extensive evaluation of the model is performed in two public and one private dataset, while segmentation accuracy is compared with other state-of-the-art DL segmentation schemas. To assess replanning necessity during treatment, an additional registration method is implemented on the segmentation output, aligning images of different modalities (Computed Tomography (CT) and Cone Beam CT (CBCT)). AttentionUNet outperforms similar DL methods (Dice Similarity Coefficient: 82.65% ± 1.03, Hausdorff Distance: 6.24 mm ± 2.47), confirming its effectiveness. Moreover, the subsequent registration procedure displays increased similarity, providing insights into the effects of RT procedures for treatment planning adaptations. The implementation of the proposed methods indicates the effectiveness of DL not only for automatic delineation of the anatomical structures, but also for the provision of information for adaptive RT support.
The Role of Insulin-like Growth Factor (IGF) System in the Corneal Epithelium Homeostasis—From Limbal Epithelial Stem Cells to Therapeutic Applications
Authors: Woronkowicz Małgorzata , Roberts Harry , Skopiński Piotr
Published: February 2024

The corneal epithelium, comprising three layers of cells, represents the outermost portion of the eye and functions as a vital protective barrier while concurrently serving as a critical refractive structure. Maintaining its homeostasis involves a complex regenerative process facilitated by the functions of the lacrimal gland, tear film, and corneal nerves. Crucially, limbal epithelial stem cells located in the limbus (transitional zone between the cornea and the conjunctiva) are instrumental for the corneal epithelium integrity by replenishing and renewing cells. Re-epithelialization failure results in persistent defects, often associated with various ocular conditions including diabetic keratopathy. The insulin-like growth factor (IGF) system is a sophisticated network of insulin and other proteins essential for numerous physiological processes. This review examines its role in maintaining the corneal epithelium homeostasis, with a special focus on the interplay with corneal limbal stem cells and the potential therapeutic applications of the system components.
The Expression of the Claudin Family of Proteins in Colorectal Cancer
Authors: Cox Kristin E. , Liu Shanglei , Hoffman Robert M. , Batra Surinder K. , Dhawan Punita , Bouvet Michael
Published: February 2024

Claudins (CLDN1–CLDN24) are a family of tight junction proteins whose dysregulation has been implicated in tumorigeneses of many cancer types. In colorectal cancer (CRC), CLDN1, CLDN2, CLDN4, and CLDN18 have been shown to either be upregulated or aberrantly expressed. In the normal colon, CLDN1 and CLDN3–7 are expressed. Although a few claudins, such as CLDN6 and CLDN7, are expressed in CRC their levels are reduced compared to the normal colon. The present review outlines the expression profiles of claudin proteins in CRC and those that are potential biomarkers for prognostication.
Structural and Functional Characterization of Lipoxygenases from Diatoms by Bioinformatics and Modelling Studies
Authors: Giordano Deborah , Bonora Simone , D’Orsi Ilenia , D’Alelio Domenico , Facchiano Angelo
Published: February 2024

Lipoxygenases make several biological functions in cells, based on the products of the catalyzed reactions. In diatoms, microalgae ubiquitous in aquatic ecosystems, lipoxygenases have been noted for the oxygenation of fatty acids with the production of oxylipins, which are involved in many physiological and pathological processes in marine organisms. The interest in diatoms’ lipoxygenases and oxylipins has increased due to their possible biotechnological applications, ranging from ecology to medicine. We investigated using bioinformatics and molecular docking tools the lipoxygenases of diatoms and the possible interaction with substrates. A large-scale analysis of sequence resources allowed us to retrieve 45 sequences of lipoxygenases from diatoms. We compared and analyzed the sequences by multiple alignments and phylogenetic trees, suggesting the possible clustering in phylogenetic groups. Then, we modelled the 3D structure of representative enzymes from the different groups and investigated in detail the structural and functional properties by docking simulations with possible substrates. The results allowed us to propose a classification of the lipoxygenases from diatoms based on their sequence features, which may be reflected in specific structural differences and possible substrate specificity.
A Complex Pattern of Gene Expression in Tissue Affected by Viperid Snake Envenoming: The Emerging Role of Autophagy-Related Genes
Authors: Oliveira Ana Karina de , Rucavado Alexandra , Escalante Teresa , Gutiérrez José María , Fox Jay W.
Published: February 2024

Viperid snake venoms induce severe tissue damage, characterized by the direct toxic action of venom components, i.e., phospholipases A2 (PLA2s) and metalloproteinases (SVMPs), concomitantly with the onset of endogenous inflammatory processes, in an intricate scenario of tissue alterations. Understanding the expression of relevant genes in muscle tissue will provide valuable insights into the undergoing pathological and inflammatory processes. In this study, we have used the Nanostring technology to evaluate the patterns of gene expression in mouse skeletal muscle 1 h, 6 h, and 24 h after injection of the venoms of Bothrops asper and Daboia russelii, two medically relevant species in Latin America and Asia, respectively, with somewhat different clinical manifestations. The dose of venoms injected (30 µg) induced local pathological effects and inflammation in muscle tissue. We focused our analysis on genes related to extracellular matrix (ECM) metabolism, immune system, programmed cell death, and autophagy. The results revealed a complex pattern of expression of genes. Regarding ECM metabolism and regulation, up-regulated genes included proteinase inhibitor Serpine 1, thrombospondin 1, collagens 1A1 and 4A1 (at 1 h in the case of B. asper), TIMP1, MMP-3 (at 24 h), and lysil oxidase (LOX). In contrast, collagen chains 5A3 and 5A1 were down-regulated, especially at 6 h. Transforming growth factor β (TGF-β) and several genes related to myofibroblast regulation were also up-regulated, which might be related to the development of fibrosis. Several genes related to cytokine and chemokine synthesis and regulation and NFκB signaling were also up-regulated. Our observations show a variable expression of genes associated with programmed cell death and autophagy, thus revealing a hitherto unknown role of autophagy in tissue affected by snake venoms. These results provide clues to understanding the complex pattern of gene expression in tissue affected by viperid snake venoms, which likely impacts the final pathophysiology of damaged tissue in envenomings.
Fine Wrinkle Improvement through Bioactive Materials That Modulate EDAR and BNC2 Gene Expression
Authors: Lee Seonju , Ye Sanghyun , Kim Mina , Lee Hyejin , Jun Seung-Hyun , Kang Nae-Gyu
Published: February 2024

Skin aging is a multifaceted biological phenomenon influenced by a combination of intrinsic or extrinsic factors. There is an increasing interest in anti-aging materials including components that improve skin wrinkles. Despite the availability of several such wrinkle-improving materials, the demand for ingredients with outstanding efficacy is increasing. Therefore, this study aimed to explore the mechanisms of wrinkle-related genes reported in previous genome-wide association studies (GWASs), identify materials that regulate these genes, and develop an effective anti-wrinkle formula containing the active ingredients that regulate the expression of these genes. We selected two candidate genes, EDAR and BNC2, that are reportedly related to periorbital wrinkles. We investigated their functions in the skin through in vitro experiments using human skin cell lines (keratinocytes and fibroblasts). Moreover, we identified ingredients that regulate the expression of these two genes and confirmed their efficacy through in vitro experiments using the skin cell lines. Finally, we developed a formula containing these ingredients and confirmed that it enhanced dermal collagen in the 3D skin and improved fine wrinkles under the eyes more effectively than retinol in humans, when applied for 8 weeks. Our results are significant and relevant, as we have discovered a special formula for wrinkle improvement with reliable efficacy that surpasses the efficacy of retinol and does not cause side-effects such as skin irritation.
Species-Specific Transcription Factors Associated with Long Terminal Repeat Promoters of Endogenous Retroviruses: A Comprehensive Review
Authors: Hossain Md Jakir , Nyame Perpetual , Monde Kazuaki
Published: February 2024

Endogenous retroviruses (ERVs) became a part of the eukaryotic genome through endogenization millions of years ago. Moreover, they have lost their innate capability of virulence or replication. Nevertheless, in eukaryotic cells, they actively engage in various activities that may be advantageous or disadvantageous to the cells. The mechanisms by which transcription is triggered and implicated in cellular processes are complex. Owing to the diversity in the expression of transcription factors (TFs) in cells and the TF-binding motifs of viruses, the comprehensibility of ERV initiation and its impact on cellular functions are unclear. Currently, several factors are known to be related to their initiation. TFs that bind to the viral long-terminal repeat (LTR) are critical initiators. This review discusses the TFs shown to actively associate with ERV stimulation across species such as humans, mice, pigs, monkeys, zebrafish, Drosophila, and yeast. A comprehensive summary of the expression of previously reported TFs may aid in identifying similarities between animal species and endogenous viruses. Moreover, an in-depth understanding of ERV expression will assist in elucidating their physiological roles in eukaryotic cell development and in clarifying their relationship with endogenous retrovirus-associated diseases.
Metabolomic Profiling of Mice with Tacrolimus-Induced Nephrotoxicity: Carnitine Deficiency in Renal Tissue
Authors: Nishida Sho , Ishima Tamaki , Kimura Natsuka , Iwami Daiki , Nagai Ryozo , Imai Yasushi , Aizawa Kenichi
Published: February 2024

Tacrolimus (TAC)-induced chronic nephrotoxicity (TAC nephrotoxicity) has a detrimental effect on long-term kidney graft survival. However, the pathogenesis of TAC nephrotoxicity remains largely unknown. We explored it by focusing on metabolic changes in renal tissues. In this study, mice were separated into TAC and control groups (n = 5/group). TAC was administered to the TAC group (1 mg/kg/d for 28 days) subcutaneously. The control group was similarly treated with normal saline. Renal tissue metabolomes were evaluated. Renal fibrosis was observed only in the TAC group. Metabolomic analysis showed that carnitine and related metabolites were substantially lower in the TAC group than in the control group, presumably due to impaired biosynthesis and reabsorption. Low carnitine levels impair antioxidation in renal tissues and β-oxidation in mitochondria, which may lead to renal tissue damage. This metabolomic analysis revealed that carnitine deficiency in renal tissue appears to explain TAC nephrotoxicity.
Delivery of a Hepatitis C Virus Vaccine Encoding NS3 Linked to the MHC Class II Chaperone Protein Invariant Chain Using Bacterial Ghosts
Authors: Chi Yulang , Zhang Shikun , Ji Shouping
Published: February 2024

Efficient delivery of a DNA plasmid into antigen-presenting cells (APCs) is a potential strategy to enhance the immune responses of DNA vaccines. The bacterial ghost (BG) is a potent DNA vaccine delivery system that targets APCs. In the present work, we describe a new strategy of using E. coli BGs as carriers for an Ii-linked Hepatitis C Virus (HCV) NS3 DNA vaccine that improved both the transgene expression level and the antigen-presentation level in APCs. BGs were prepared from DH5α cells, characterized via electron microscopy and loaded with the DNA vaccine. The high transfection efficiency mediated using BGs was first evaluated in vitro, and then, the immune protective effect of the BG-Ii-NS3 vaccine was determined in vivo. It was found that the antibody titer in the sera of BG-Ii-NS3-challenged mice was higher than that of Ii-NS3-treated mice, indicating that the BGs enhanced the humoral immune activity of Ii-NS3. The cellular immune protective effect of the BG-Ii-NS3 vaccine was determined using long-term HCV NS3 expression in a mouse model in which luciferase was used as a reporter for HCV NS3 expression. Our results showed that the luciferase activity in BG-Ii-NS3-treated mice was significantly reduced compared with that in Ii-NS3-treated mice. The CTL assay results demonstrated that BG-Ii-NS3 induced a greater NS3-specific T-cell response than did Ii-NS3. In summary, our study demonstrated that BGs enhanced both the humoral and cellular immune response to the Ii-NS3 DNA vaccine and improved its immune protection against HCV infection.
Interferon Lambda Signaling Restrains Experimental Autoimmune Encephalomyelitis
Authors: Sherwani Mohammad Asif , Duesman Samuel J. , Hel Zdenek , Raman Chander , Yusuf Nabiha
Published: February 2024

IFN-λ is a type III interferon (IFN) with pleiotropic functions in modulating immune responses. To address its function in autoimmune neuroinflammation, we evaluated the development and progression of experimental autoimmune encephalitis (EAE) in IFNLR1 KO (Ifnlr1−/−) and C57Bl/6 (WT) mice following immunization with MOG35–55 peptide. The results show that Ifnlr1−/− mice developed significantly more severe EAE than WT littermates with a similar day of onset, suggesting the potential of IFN-λ in reducing disease severity. We next interrogated whether IFN-λ differentially modulates EAE induced by encephalitogenic Th1 cells or Th17 cells. Encephalitogenic Th1 or Th17 generated from WT donors were transferred into WT or Ifnlr1−/− recipient mice. Whereas encephalitogenic Th1 cells induced more severe EAE in Ifnlr1−/− than WT recipients, the disease severity induced by encephalitogenic Th17 cells was similar. Additionally, in vitro experiments showed that Ifnlr1−/− macrophages promoted the expansion of myelin peptide-reactive Th17 cells but not Th1 cells. Early in the disease, the spinal cords of EAE mice displayed a significantly greater proportion of Ly6C-Ly6G+ cells with CXCR2+CD62Llo phenotype, indicating activated neutrophils. These findings suggest that IFN-λ signaling restrains activation and migration of neutrophils to the CNS, potentially attenuating neutrophil-mediated disease progression in autoimmune neuroinflammation. Recombinant IFN-λ can be used as a potential therapeutic target for treatment of patients with multiple sclerosis as it has fewer side effects due to the restricted expression of its receptor.
Simulated Dopamine Modulation of a Neurorobotic Model of the Basal Ganglia
Authors: Prescott Tony J. , Montes González Fernando M. , Gurney Kevin , Humphries Mark D. , Redgrave Peter
Published: February 2024

The vertebrate basal ganglia play an important role in action selection—the resolution of conflicts between alternative motor programs. The effective operation of basal ganglia circuitry is also known to rely on appropriate levels of the neurotransmitter dopamine. We investigated reducing or increasing the tonic level of simulated dopamine in a prior model of the basal ganglia integrated into a robot control architecture engaged in a foraging task inspired by animal behaviour. The main findings were that progressive reductions in the levels of simulated dopamine caused slowed behaviour and, at low levels, an inability to initiate movement. These states were partially relieved by increased salience levels (stronger sensory/motivational input). Conversely, increased simulated dopamine caused distortion of the robot’s motor acts through partially expressed motor activity relating to losing actions. This could also lead to an increased frequency of behaviour switching. Levels of simulated dopamine that were either significantly lower or higher than baseline could cause a loss of behavioural integration, sometimes leaving the robot in a ‘behavioral trap’. That some analogous traits are observed in animals and humans affected by dopamine dysregulation suggests that robotic models could prove useful in understanding the role of dopamine neurotransmission in basal ganglia function and dysfunction.
Advancements in Brain Research: The In Vivo/In Vitro Electrochemical Detection of Neurochemicals
Authors: Xu Xiaoxuan , Zuo Yimei , Chen Shu , Hatami Amir , Gu Hui
Published: February 2024

Neurochemicals, crucial for nervous system function, influence vital bodily processes and their fluctuations are linked to neurodegenerative diseases and mental health conditions. Monitoring these compounds is pivotal, yet the intricate nature of the central nervous system poses challenges. Researchers have devised methods, notably electrochemical sensing with micro-nanoscale electrodes, offering high-resolution monitoring despite low concentrations and rapid changes. Implantable sensors enable precise detection in brain tissues with minimal damage, while microdialysis-coupled platforms allow in vivo sampling and subsequent in vitro analysis, addressing the selectivity issues seen in other methods. While lacking temporal resolution, techniques like HPLC and CE complement electrochemical sensing’s selectivity, particularly for structurally similar neurochemicals. This review covers essential neurochemicals and explores miniaturized electrochemical sensors for brain analysis, emphasizing microdialysis integration. It discusses the pros and cons of these techniques, forecasting electrochemical sensing’s future in neuroscience research. Overall, this comprehensive review outlines the evolution, strengths, and potential applications of electrochemical sensing in the study of neurochemicals, offering insights into future advancements in the field.
Innovative Closed Cavity Façades (CCF) with Inner Shading and Advanced Coatings for Enhancing Thermal Performance in the Tropics
Authors: Al-Tamimi Nedhal , Al Kahlout Ahmad Fadel , Qahtan Abdultawab M. , Alqanoo Anas A. M.
Published: February 2024

In its simplest terms, a closed-cavity façade (CCF) is a sealed, unventilated enclosure equipped with motorized shading devices, internal double or triple glazing, and external single glazing. This technology effectively controls solar energy and daylight entry into buildings. This research aims to enhance the thermal efficiency of CCFs in tropical climates using Venetian blinds (VB) and advanced glass coatings. EnergyPlus and DesignBuilder were employed to assess various CCF designs and compare them to a single glazing unit (SGU) with grey coatings. This was inspired by a residential case study on Penang Island, Malaysia. The findings indicate that CCFs surpass SGUs in thermal performance and occupant comfort, particularly in Malaysia’s humid tropical climate. CCFs reduced operating temperatures by a monthly percentage ranging from 33.5% to 68.75% in all operations. On an annual basis, temperature reductions ranged from 27.5% to 80.25%, with maximum decreases between 2 °C and 4 °C and minimum decreases between 0.5 °C and 1 °C compared to SGU units. The results show that CCFs outperform SGUs in thermal performance and comfort, reducing operating temperatures by 33.5% to 68.75% monthly and 27.5% to 80.25% annually. Temperature reductions ranged between 2 °C and 4 °C at maximum and 0.5 °C and 1 °C at minimum compared to SGU. Notably, Venetian blinds with nano-coatings (83/58) and low-E coatings (83/23) (Tvis/Tsol) were the most effective. This study highlights the importance of selecting appropriate coatings for CCFs, and demonstrates their potential in enhancing interior temperatures and comfort in Malaysia’s climate. The findings emphasize the significant impact of innovative glazing technologies on improving operational temperatures and occupant comfort using closed-cavity façades in the tropics.
Cross-Laminated Timber (CLT) in Compression Perpendicular to the Plane: Experimental Analysis on the Column below the Wall Load Configuration
Authors: Mendes Rodrigo Adolfo Benitez , Benincá Matheus Erpen , Subhani Mahbube , Acosta Andrey Pereira , de Avila Delucis Rafael , Désir Jean Marie , Morsch Inácio Benvegnu , Ilgın Hüseyin Emre , Karjalainen Markku
Published: February 2024

This study investigates the load-bearing properties of cross-laminated timber (CLT) under compression perpendicular to the grain. Different series of CLT panels with varying layups, layer thicknesses, and overall depths were tested. Also, the compression perpendicular to the grain properties of CLT plate specimens is compared against clear wood and cubic CLT specimens. The results show a 30% reduction in modulus perpendicular to the grain for cubic samples compared to clear specimens. Increasing the number of layers from three to five leads to a 21% higher modulus, while increasing the overall depth from 105 to 175 mm results (with the same number of layers) in a 17% reduction. The overall depth significantly affects the CLT’s modulus and strength under compression perpendicular to the grain. The study also compares two analytical models for determining the transversal compression factor, kc,90. Although the models showed satisfactory results for thinner CLTs, their accuracy decreased with greater panel depth. These findings enhance the understanding of CLT panels for structural applications.
Integration of Augmented Reality and Building Information Modeling for Enhanced Construction Inspection—A Case Study
Authors: Pan Nai-Hsin , Isnaeni Nurani Nanda
Published: February 2024

This research addresses a significant challenge in the construction industry: the traditional reliance on CAD drawings and manual methods for building inspection and monitoring. This article presents a transformative proposal utilizing Augmented Reality (AR) to revolutionize these processes. The proposed model is based on an innovative integration of AR technology with Building Information Modeling (BIM), aiming to enhance data life-cycle management and improve the efficiency of construction management practices. The main goal of the article is to demonstrate the practical feasibility and benefits of this AR-BIM integration in construction management, particularly in the realms of inspection and monitoring. This involves developing and testing an accessible, user-friendly, and affordable AR application prototype for mobile devices, employing multiple markers, as a potential replacement for traditional methods. The research methodology comprises five phases, starting with the conversion of 2D CAD drawings into 3D BIM, followed by the simulation of AR-BIM integration at a construction site using a commercial AR application. This is succeeded by assessing the applicability of the commercial AR app and developing a multiple-marker AR application prototype suitable for general platforms. The final phase encompasses the testing and evaluation of this prototype. The findings suggest that the integration of 3D BIM with AR technology is not only feasible, but also beneficial in replacing paper-based processes, thereby enhancing information sharing, communication, and overall project execution efficiency. However, the accuracy of the superimposition between virtual and actual objects needs improvement to reduce discrepancies between as-built and as-planned scenarios. These results hold significant potential for transforming construction project execution by replacing traditional methods with more efficient digital solutions. Future research directions include extensive testing in various construction scenarios, improving model complexity handling, exploring the application of machine learning algorithms for data analysis, and expanding the study to encompass other stages of the construction lifecycle.
Feasibility of Preparing Steel Slag–Ground Granulated Blast Furnace Slag Cementitious Materials: Synergistic Hydration, Fresh, and Hardened Properties
Authors: Sun Jianwei , Hou Shaoyun , Guo Yuehao , Cao Xinying , Zhang Dongdong
Published: February 2024

Steel slag and GBFS are wastes generated during the steel and iron smelting process, characterized by their considerable production rates and extensive storage capacities. After grinding, they are often used as supplementary cementitious materials. However, the intrinsic slow hydration kinetics of steel slag–GBFS cementitious material (SGM) when exposed to a pure water environment result in prolonged setting times and diminished early-age strength development. The incorporation of modifiers such as gypsum, clinker, or alkaline activators can effectively improve the various properties of SGM. This comprehensive review delves into existing research on the utilization of SGM, examining their hydration mechanisms, workability, setting time, mechanical strengths, durability, and shrinkage. Critical parameters including the performance of base materials (water-to-cement ratio, fineness, and composition) and modifiers (type, alkali content, and dosage) are scrutinized to understand their effects on the final properties of the cementitious materials. The improvement mechanisms of various modifiers on properties are discussed. This promotes resource utilization of industrial solid wastes and provides theoretical support for the engineering application of SGM.
Towards a Reliable Design of Geopolymer Concrete for Green Landscapes: A Comparative Study of Tree-Based and Regression-Based Models
Authors: Wang Ranran , Zhang Jun , Lu Yijun , Ren Shisong , Huang Jiandong
Published: February 2024

The design of geopolymer concrete must meet more stringent requirements for the landscape, so understanding and designing geopolymer concrete with a higher compressive strength challenging. In the performance prediction of geopolymer concrete compressive strength, machine learning models have the advantage of being more accurate and faster. However, only a single machine learning model is usually used at present, there are few applications of ensemble learning models, and model optimization processes is lacking. Therefore, this paper proposes to use the Firefly Algorithm (AF) as an optimization tool to perform hyperparameter tuning on Logistic Regression (LR), Multiple Logistic Regression (MLR), decision tree (DT), and Random Forest (RF) models. At the same time, the reliability and efficiency of four integrated learning models were analyzed. The model was used to analyze the influencing factors of geopolymer concrete and determine the strength of their influencing ability. According to the experimental data, the RF-AF model had the lowest RMSE value. The RMSE value of the training set and test set were 4.0364 and 8.7202, respectively. The R value of the training set and test set were 0.9774 and 0.8915, respectively. Therefore, compared with the other three models, RF-AF has a stronger generalization ability and higher prediction accuracy. In addition, the molar concentration of NaOH was the most important influencing factors, and its influence was far greater than the other possible factors including NaOH content. Therefore, it is necessary to pay more attention to NaOH molarity when designing geopolymer concrete.