bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis of the serum proteome profile of wild stump-tailed macaques (Macaca arctoides) seropositive for Zika virus antibodies in Thailand
Authors: Ruengket Pakorn , Roytrakul Sittiruk , Tongthainan Daraka , Boonnak Kobporn , Taruyanon Kanokwan , Sangkharak Bencharong , Fungfuang Wirasak
Published: November 2024

Zika virus (ZIKV) is a member of the Flaviviridae virus family and poses a significant global health concern. ZIKV is transmitted by Aedes mosquitoes, and it has been implicated in various neurological conditions associated with fetal brain development. ZIKV has two transmission cycles: a sylvatic cycle in which nonhuman primates are infected via arboreal mosquito bites, and an interhuman (urban) cycle in which the virus is transmitted among primates by Aedes mosquitoes. ZIKV was first discovered in wild macaques, and the danger posed by the virus is increased due to the close proximity between humans and wild animals in modern society. However, data regarding the extent and role of infection in nonhuman primates are limited. Thus, there is an urgent need for improved surveillance, diagnostic methods, and public health interventions to effectively combat ZIKV transmission and its associated health impacts in Southeast Asia. In this study, we used a proteomics and bioinformatics approach to profile serum proteins in wild stump-tailed macaques seropositive for neutralizing antibodies against ZIKV. A total of 9,532 total proteins were identified, and 338 differentially expressed proteins were identified between naïve and seropositive animals. A total of 52 important proteins were used to construct a serum proteomic profile. These 52 important proteins were associated with immune and inflammatory responses (36.54%), neurological damage (23.08%), viral activities (21.15%), the apoptosis signaling pathway (9.61%), and other pathways (9.61%). Our proteomic profile identified proteins that inhibit the apoptosis pathway, intracellular resource competition with the virus, and neurological damage due to ZIKV and the host immune and defense responses.
Optimal Feature Selection and Classification for Parkinson’s Disease Using Deep Learning and Dynamic Bag of Features Optimization
Authors: Aarti  , Gowroju Swathi , Begum Mst Ismat Ara , Hosen A. S. M. Sanwar
Published: November 2024

Parkinson’s Disease (PD) is a neurological condition that worsens with time and is characterized bysymptoms such as cognitive impairment andbradykinesia, stiffness, and tremors. Parkinson’s is attributed to the interference of brain cells responsible for dopamine production, a substance regulating communication between brain cells. The brain cells involved in dopamine generation handle adaptation and control, and smooth movement. Convolutional Neural Networks are used to extract distinctive visual characteristics from numerous graphomotor sample representations generated by both PD and control participants. The proposed method presents an optimal feature selection technique based on Deep Learning (DL) and the Dynamic Bag of Features Optimization Technique (DBOFOT). Our method combines neural network-based feature extraction with a strong optimization technique to dynamically choose the most relevant characteristics from biological data. Advanced DL architectures are then used to classify the chosen features, guaranteeing excellent computational efficiency and accuracy. The framework’s adaptability to different datasets further highlights its versatility and potential for further medical applications. With a high accuracy of 0.93, the model accurately identifies 93% of the cases that are categorized as Parkinson’s. Additionally, it has a recall of 0.89, which means that 89% of real Parkinson’s patients are accurately identified. While the recall for Class 0 (Healthy) is 0.75, meaning that 75% of the real healthy cases are properly categorized, the precision decreases to 0.64 for this class, indicating a larger false positive rate.
Human Perception of the Emotional Expressions of Humanoid Robot Body Movements: Evidence from Survey and Eye-Tracking Measurements
Authors: Gao Wa , Shen Shiyi , Ji Yang , Tian Yuan
Published: November 2024

The emotional expression of body movement, which is an aspect of emotional communication between humans, has not been considered enough in the field of human–robot interactions (HRIs). This paper explores human perceptions of the emotional expressions of humanoid robot body movements to study the emotional design of the bodily expressions of robots and the characteristics of the human perception of these emotional body movements. Six categories of emotional behaviors, including happiness, anger, sadness, surprise, fear, and disgust, were designed by imitating human emotional body movements, and they were implemented on a Yanshee robot. A total of 135 participants were recruited for questionnaires and eye-tracking measurements. Statistical methods, including K-means clustering, repeated analysis of variance (ANOVA), Friedman’s ANOVA, and Spearman’s correlation test, were used to analyze the data. According to the statistical results of emotional categories, intensities, and arousals perceived by humans, a guide to grading the designed robot’s bodily expressions of emotion is created. By combining this guide with certain objective analyses, such as fixation and trajectory of eye movements, the characteristics of human perception, including the perceived differences between happiness and negative emotions and the trends of eye movements for different emotional categories, are described. This study not only illustrates subjective and objective evidence that humans can perceive robot bodily expressions of emotions through only vision but also provides helpful guidance for designing appropriate emotional bodily expressions in HRIs.
Compassionate Care with Autonomous AI Humanoid Robots in Future Healthcare Delivery: A Multisensory Simulation of Next-Generation Models
Authors: Hernandez Joannes Paulus Tolentino
Published: November 2024

The integration of AI and robotics in healthcare raises concerns, and additional issues regarding autonomous systems are anticipated. Effective communication is crucial for robots to be seen as “caring”, necessitating advanced mechatronic design and natural language processing (NLP). This paper examines the potential of humanoid robots to autonomously replicate compassionate care. The study employs computational simulations using mathematical and agent-based modeling to analyze human–robot interactions (HRIs) surpassing Tetsuya Tanioka’s TRETON. It incorporates stochastic elements (through neuromorphic computing) and quantum-inspired concepts (through the lens of Martha Rogers’ theory), running simulations over 100 iterations to analyze complex behaviors. Multisensory simulations (visual and audio) demonstrate the significance of “dynamic communication”, (relational) “entanglement”, and (healthcare system and robot’s function) “superpositioning” in HRIs. Quantum and neuromorphic computing may enable humanoid robots to empathetically respond to human emotions, based on Jean Watson’s ten caritas processes for creating transpersonal states. Autonomous AI humanoid robots will redefine the norms of “caring”. Establishing “pluralistic agreements” through open discussions among stakeholders worldwide is necessary to align innovations with the values of compassionate care within a “posthumanist” framework, where the compassionate care provided by Level 4 robots meets human expectations. Achieving compassionate care with autonomous AI humanoid robots involves translating nursing, communication, computer science, and engineering concepts into robotic care representations while considering ethical discourses through collaborative efforts. Nurses should lead the design and implementation of AI and robots guided by “technological knowing” in Rozzano Locsin’s TCCN theory.
Preferential Stripping Analysis of Post-Transition Metals (In and Ga) at Bi/Hg Films Electroplated on Graphene-Functionalized Graphite Rods
Authors: Ghaffari Nastaran , Jahed Nazeem , Abader Zareenah , Baker Priscilla G. L. , Pokpas Keagan
Published: November 2024

In this study, we introduce a novel electrochemical sensor combining reduced graphene oxide (rGO) sheets with a bismuth–mercury (Bi/Hg) film, electroplated onto pencil graphite electrodes (PGEs) for the high-sensitivity detection of trace amounts of gallium (Ga3+) and indium (In3+) in water samples using square wave anodic stripping voltammetry (SWASV). The electrochemical modification of PGEs with rGO and bimetallic Bi/Hg films (ERGO-Bi/HgF-PGE) exhibited synergistic effects, enhancing the oxidation signals of Ga and In. Graphene oxide (GO) was accumulated onto PGEs and reduced through cyclic reduction. Key parameters influencing the electroanalytical performance, such as deposition potential, deposition time, and pH, were systematically optimized. The improved adsorption of Ga3+ and In3+ ions at the Bi/Hg films on the graphene-functionalized electrodes during the preconcentration step significantly enhanced sensitivity, achieving detection limits of 2.53 nmol L−1 for Ga3+ and 7.27 nmol L−1 for In3+. The preferential accumulation of each post-transition metal, used in transparent displays, to form fused alloys at Bi and Hg films, respectively, is highlighted. The sensor demonstrated effective quantification of Ga3+ and In3+ in tap water, with detection capabilities well below the USEPA guidelines. This study pioneers the use of bimetallic films to selectively and simultaneously detect the post-transition metals In3+ and Ga3+, highlighting the role of graphene functionalization in augmenting metal film accumulation on cost-effective graphite rods. Additionally, the combined synergistic effects of Bi/Hg and graphene functionalization have been explored for the first time, offering promising implications for environmental analysis and water quality monitoring.
Effect of High Heat Flux of Helium and Hydrogen Plasma Jet on the Material Properties of Piezoelectric PZT-Ceramics
Authors: Sotnikova Galina Yu. , Ankudinov Alexander V. , Voronin Alexander V. , Gavrilov Gennady A. , Glazov Alexey L. , Goryainov Valery Yu. , Zaitseva Nina V. , Nashchekin Alexey V. , Passet Rostislav S. , Vorob’ev Alexander A. , Sotnikov Andrey V.
Published: November 2024

A set of experimental and measurement techniques to study the influence of a plasma jet on the main material parameters of piezoelectric ceramics has been presented. A series of plasma experiments has been carried out using a pulsed plasma jet system. It allows of a metered-dose exposure to plasma of different composition and fluence with a constant particle flux density of 1021/m2, energy flux density of 0.1 MJ/m2 and average particle energy of 100–200 eV in a pulse duration of 15 μs. The study of the effects that a repeated exposure to an extreme heat flux of helium and hydrogen plasmas has on the near-surface layer structure and basic material parameters of mass-produced piezoelectric ceramic samples has been presented. The main result of the research is an experimental confirmation of the surface micro-structuring starting after just a few cycles of plasma exposure while only a slight decrease of the main material parameters as well as the preservation of polarization has been observed for two types of different compositions of PZT-ceramics. A further increase in the number of exposure pulses leads to practically no change of main material parameters of both ceramics, even showing a tendency for recovery instead.
SWA: SoftWare for Analog Design Automation
Authors: Susa Hidekana , Mori Kenji , Sugawara Mitsutoshi , Matsuzawa Akira
Published: November 2024

We have developed SWA: SoftWare for Analog design automation. Its commands can describe analog and mixed-signal (AMS) layouts and schematics to replace the graphic editor with a program reflecting the knowledge of design experts. Also, it is able to utilize variables to parameterize schematics and layouts to fulfill design needs. We programmed a 10b 1 GS/s DAC using SWA with 8.3 K lines of code, which is about 1/10 compared with conventional programs. The programmed DAC is configurable with multiple voltages and multiple resolutions from 4 to 12 bits. The DAC schematic and layout generation with DRC and LVS SWA API can be finished in about 1 min.
Identification of Primary Metabolite Profiles Reveals Quality Characteristics of Citrus maxima ‘Shatian Yu’ from Different Origins
Authors: Peng Yujiao , Li Meixin , Song Fangfei , Liu Shuilan , Qin Yuxiang , Hu Baoqing , Cui Xueyu
Published: November 2024

Citrus maxima ‘Shatian Yu’ displays varying nutritional profiles influenced by its production area. This study evaluated pomelo fruits from four primary and one developing ‘Shatian Yu’ production area. Notably, ‘Shatian Yu’ from the Guilin area exhibited higher sugar and alcohol content, suggesting enhanced taste. Principal component analysis and OPLS-DA revealed significant metabolite differences among production areas. In Guilin, variations were observed in a few substances, including sugars, alcohols, and phenolic acids. When compared with Rong City, Guilin showed a decrease in four phenolic acids and an increase in three organic acids, eighteen amino acids, eighteen lipids, and one vitamin. This comprehensive analysis provides valuable insights for the development of ‘Shatian Yu’ cultivation, highlighting the impact of production areas on fruit quality.
Are the Sleep–Wake Cycle and Sleep Duration Ethnically Determined? A Comparison of Tibetan and Japanese Children’s Sleep
Authors: Su Ping , Taniike Masako , Ohno Yuko , Mohri Ikuko
Published: November 2024

Background: Several environmental factors affect sleep. We investigated the sleep and sleep-related habits of preschool children living in Tibet and conducted an international comparison with those in Japan. Methods: We conducted a community-based cross-sectional study using the Chinese version of the Japanese Sleep Questionnaire for Preschoolers (JSQ-P-C) and compared the results with previous data on Japanese children. Results: The sleep status of 3113 children aged 3–6 years old in Qinghai province was evaluated. The average wake time and bedtime of the Tibetan children were 7:20 ± 0:31 and 21:16 ± 0:43, respectively. Their mean nocturnal sleep duration was 10.0 ± 0.7 h. In comparing 3-year-old children, the time for which they viewed TV in Tibet was shorter (65.5 ± 44.6 min) than that in Japan (149.7 ± 76.6 min), and the mother’s bedtime was earlier in Tibet (21:28 ± 2:14) than in Japan (23:20 ± 1:05). However, the bedtime and sleep duration of the Tibetan children (21:17 ± 0:37 and 10.0 ± 0.7 h) were fairly similar to those of the Japanese children (21:24 ± 1:57 and 9.8 ± 0.8 h). Conclusions: The late bedtime and short nocturnal sleep duration of Tibetan toddlers were the same as those of Japanese toddlers despite considerable differences in their lifestyle and environment.
Selenium Biofortification of Allium Species
Authors: Golubkina Nadezhda , Nemtinov Victor , Amagova Zarema , Skrypnik Liubov , Nadezhkin Sergey , Murariu Otilia Cristina , Tallarita Alessio Vincenzo , Caruso Gianluca
Published: November 2024

Allium species have great potential in the production of functional food via selenium biofortification. This review is devoted to the specificity of Allium plant biofortification with Se, including the genetic peculiarities, effect of the chemical form of the microelement, methods of supply, sulfur and AMF effects, and hormonal regulation. The biosynthesis of methylated Se amino acids and the beneficial effect of Se treatment on secondary metabolite accumulation and plant yield are discussed. Special attention is paid to the production of functional foods based on Allium plants enriched in different ways: bread with leek leaf powder, Allium microgreens and seedlings, and ‘Black garlic’ biofortified with Se. Further focus is provided to the high variability of Allium crop yield and quality under Se supply governed by genetic factors and environmental stresses, and to the need for plant growth technology optimization to obtain the predicted nutritional characteristics of the derived functional product with high anti-carcinogenic activity.
Evade Unknown Pursuer via Pursuit Strategy Identification and Model Reference Policy Adaptation (MRPA) Algorithm
Authors: Su Zitao , Zheng Shuang , Xu Zhiqiang , Cheng Lili , Tao Chengyang , Qie Rongkai , Feng Weijia , Zhang Zhaoxiang , Xu Yuelei
Published: November 2024

The game of pursuit–evasion has always been a popular research subject in the field of Unmanned Aerial Vehicles (UAVs). Current evasion decision making based on reinforcement learning is generally trained only for specific pursuers, and it has limited performance for evading unknown pursuers and exhibits poor generalizability. To enhance the ability of an evasion policy learned by reinforcement learning (RL) to evade unknown pursuers, this paper proposes a pursuit UAV attitude estimation and pursuit strategy identification method and a Model Reference Policy Adaptation (MRPA) algorithm. Firstly, this paper constructs a Markov decision model for the pursuit–evasion game of UAVs that includes the pursuer’s attitude and trains an evasion policy for a specific pursuit strategy using the Soft Actor–Critic (SAC) algorithm. Secondly, this paper establishes a novel relative motion model of UAVs in pursuit–evasion games under the assumption that proportional guidance is used as the pursuit strategy, based on which the pursuit UAV attitude estimation and pursuit strategy identification algorithm is proposed to provide adequate information for decision making and policy adaptation. Furthermore, a Model Reference Policy Adaptation (MRPA) algorithm is presented to improve the generalizability of the evasion policy trained by RL in certain environments. Finally, various numerical simulations imply the precision of pursuit UAV attitude estimation and the accuracy of pursuit strategy identification. Also, the ablation experiment verifies that the MRPA algorithm can effectively enhance the performance of the evasion policy to deal with unknown pursuers.
Rapid Optimization of Active Disturbance Rejection Controller Parameters for Quadrotor UAVs Using Kriging Surrogate Modeling
Authors: Zhou Wenya , Zhang Shuyue , Hu Xinhan , Zong Fei
Published: November 2024

The Active Disturbance Rejection Controller (ADRC), celebrated for its superior resistance to interference, presents itself as an exemplary solution for the development of control systems that are designed to accommodate substantial changes in payload weight for quadrotor Unmanned Aerial Vehicles (UAVs) and to endure robust side winds along with other challenging operational scenarios. Despite the inherent complexity due to the numerous parameters required for the configuration of the ADRC, an innovative method utilizing the Kriging surrogate optimization algorithm has been introduced to automate and expedite the generation of these controller parameters. The development of the ADRC begins with the dynamics model of the quadrotor UAV, followed by the identification of key design parameters. These parameters are then rapidly optimized through the Kriging surrogate optimization algorithm. The controller’s effectiveness is confirmed by implementing the ADRC on Pixhawk flight control hardware, with a comparative analysis of the attitude response under various operating conditions, thereby validating the ADRC’s superior anti-disturbance performance.
Leveraging Large Language Models for Efficient Alert Aggregation in AIOPs
Authors: Zha Junjie , Shan Xinwen , Lu Jiaxin , Zhu Jiajia , Liu Zihan
Published: November 2024

Alerts are an essential tool for the detection of anomalies and ensuring the smooth operation of online service systems by promptly notifying engineers of potential issues. However, the increasing scale and complexity of IT infrastructure often result in “alert storms” during system failures, overwhelming engineers with a deluge of often correlated alerts. Therefore, effective alert aggregation is crucial in isolating root causes and accelerating failure resolution. Existing approaches typically rely on either semantic similarity or statistical methods, both of which have significant limitations, such as ignoring causal relationships or struggling to handle infrequent alerts. To overcome these drawbacks, we propose a novel two-phase alert aggregation approach. We employ temporal–spatial clustering to group alerts based on their temporal proximity and spatial attributes. In the second phase, we utilize large language models to trace the cascading effects of service failures and aggregate alerts that share the same root cause. Experimental evaluations on datasets from real-world cloud platforms demonstrate the effectiveness of our method, achieving superior performance compared to traditional aggregation techniques.
Study on the Pilot-Scale Technology of Ginkgolide B Synthesis by Coprinus comatus
Authors: Zhang Zhicai , Wang Feng , Xu Ling
Published: November 2024

Ginkgo biloba extract (EGB) has been approved by the Food and Drug Administration in the United States for clinical studies on memory disorders. Ginkgolide B (GB) is the major terpene lactone component of EGB and is a specific and potent antagonist of platelet-activating factor (PAF). In a previous study, we reported the medium composition for the conversion of ginkgolides to GB by Coprinus comatus. In the present study, we applied the response surface methodology (RSM) to optimize the conversion conditions in a 20 L fermenter and applied HPLC-MS/MS, circular dichroism (CD) and infrared (IR) spectroscopy analyses, and nuclear magnetic resonance (NMR) to further confirm the sample structure. The optimal conversion conditions consisted of 12.7 L/min of ventilation, a 156 h conversion time, a 132 rpm rotating speed, a 0.04 MPa fermenter pressure, and a 27.8 °C conversion temperature. Under the optimal conditions, the GB conversion rate was 98.62%, and the GB content of the sample was higher than 98%. HPLC-MS/MS, CD, IR, and NMR analyses showed that the molecular formula of the sample was C20H24O10 and the chemical structure of the sample was in good agreement with the standard GB. Our current study lays the groundwork for the industrial production of GB.
Aerobic Stability of High-Moisture Corn Ensiled with Lactiplantibacillus plantarum During Prolonged Air Exposure
Authors: Duvnjak Marija , Bogunović Igor , Kljak Kristina
Published: November 2024

The evaluation of the aerobic stability of silages primarily involves monitoring temperature, while changes in composition are often neglected. In the present study, the effect of aeration on high-moisture corn ensiled with Lactiplantibacillus plantarum was investigated and compared with that of the control without inoculant. The corn used in this study was grown in five plots in a split-plot experimental design, and each plot represented the repetition of silage preparation, both with and without inoculant. In the silages, the temperature changes and the content of acids and alcohols were monitored during the 6 days of aeration, while the content of the main nutrients was compared before and after 6 days of aeration. The temperature difference between the silages and the environment was below 3 °C during the entire aeration period, regardless of the ensiling method. The content of lactic acid was higher in L. plantarum silages, while the contents of acetic and propionic acid, methanol and ethanol were higher in the control (p < 0.001). The content of all compounds changed during the aeration period (p < 0.05), regardless of the ensiling method and the stable silage temperature. Aeration affected the content of soluble crude protein and starch (p < 0.05), suggesting starch degradation in high-moisture corn during aeration. Therefore, in addition to monitoring silage temperature, monitoring lactic and acetic acid and the main nutrients should be considered, as the nutritional value of high-moisture corn could decrease during aeration.
Using Paleoecological Methods to Study Long-Term Disturbance Patterns in High-Elevation Whitebark Pine Ecosystems
Authors: Hartley Jordin , Watt Jennifer , Brunelle Andrea
Published: November 2024

Pinus albicaulis (whitebark pine) is a keystone species, providing food and habitat to wildlife, in high-elevation ecological communities. In recent years, this important species has been negatively impacted by changes in fire regimes, increased Dendroctonus ponderosae (mountain pine beetle) outbreaks associated with human landscape and climate modification, and the continued impact of the non-native Cronartium ribicola (white pine blister rust). This research investigates changes in fire occurrence, the establishment of Pinus albicaulis, and fuel availability at a high-elevation site in the Sawtooth National Recreation Area, Idaho, USA. Charcoal and pollen analyses were used to reconstruct fire and vegetation patterns for Phyllis Lake, Idaho, USA, over the past ~8200 cal y BP. We found that significant fire episodes occurred when the pollen accumulation rates (PARs) indicated more arboreal fuel availability, and we identified that Pinus albicaulis became well established at the site ~7200 cal y BP. The high-elevation nature of Phyllis Lake (2800 m) makes this record unique, as there are not many paleorecords at this high elevation from the Northern Rocky Mountains, USA. Additional high-elevation sites in Pinus albicaulis habitats will provide critical insight into the long-term dynamics of this threatened species.
Cost Effectiveness of Chip Seal and Hot Mix Asphalt Pavements
Authors: Žlender Bojan , Gürer Cahit , Varga Rok , Jelušič Primož
Published: November 2024

Chip seal pavements, consisting of one or more layers of asphalt binder and fine aggregate, can be mechanically characterized as a surface treatment that enhances evenness and trafficability. This paper examines the geotechnical aspects of chip seal applicability compared to traditional hot mix asphalt pavements. An analytical model was employed to design unpaved roads and determine the required thickness of unbound layers. Eight optimization models were developed for hot mix asphalt pavements and four for chip seal pavements, aimed at achieving optimal designs for various input parameters. These outcomes were used to conduct a multi-parametric analysis, incorporating an optimization loop for each combination of design variables. The results indicate that, under low traffic conditions, a chip seal pavement structure can be up to 40% less expensive than an optimal hot mix asphalt pavement structure, particularly when the subgrade has low bearing capacity and is exposed to unfavorable climatic conditions. However, at medium traffic loads, with good subgrade bearing capacity and favorable climate, the chip seal pavement structure incurs costs that are 25% higher than those of the hot asphalt pavement structure. In addition, chip seal pavements should always be designed with integrated geosynthetic reinforcement to minimize construction costs, and chip seal is not as sensitive to frost as hot mix asphalt.
High Temperature Effects on Global Heritage Stone Resources: A Systematic Review
Authors: Lobarinhas Roberta , Dionísio Amélia , Paneiro Gustavo
Published: November 2024

Throughout history, natural stone has been a crucial building material due to its strength, durability, and aesthetic qualities. Today, it continues to be a valuable resource, representing both a cultural heritage asset and a significant economic material. However, the increasing frequency of heat waves and fires driven by climate change poses a growing threat to stone building materials. This paper reviews the scientific attention given to the effects of high temperatures on Global Heritage Stone Resources (GHSRs), an international classification designed to enhance the recognition and status of building stones. Through a systematic SCOPUS search with refined filtering criteria, the study aims to quantify the existing research on these heritage stones. The search applied the standardized lithotype terms from GHSR publications to ensure consistency, followed by the exclusion of irrelevant terms when identified. Additionally, a relevance filter was applied to restrict the number of articles per lithotype and ensure that only the most pertinent studies were considered. Key findings from the literature reveal that exposure to high temperatures (ranging from 200 °C to 900 °C) significantly affected the studied GHSRs, leading to thermal micro-fissuring, increased porosity, and changes in water absorption, which compromise the mechanical properties of the stones. Moreover, these conditions can result in irreversible chemical transformations, exacerbating the deterioration of cultural heritage assets. The study emphasizes the critical need for research to better understand how these stone materials behave when exposed to high temperatures. It also provides a relevant framework for future investigations aimed at predicting and mitigating the effects of external threats such as fires.
Cultural Heritage at Risk in World Conflicts: Digital Tools’ Contribution to Its Preservation
Authors: Neglia Grazia , Angrisano Mariarosaria , Mecca Ippolita , Fabbrocino Francesco
Published: November 2024

Cultural heritage is, today, particularly exposed to the devastation resulting from natural phenomena, but it is even more exposed to the destruction caused by man-made ones. Consequently, it is critical to adopt suitable and concrete provisions for its preservation and conservation. The conflict that has been raging in Ukraine since February 2022 has spotlighted problems related to cultural heritage, which is increasingly considered a military target. Digital transformation and technologies integrated with legal tools can contribute to making the system of protection and recovery of cultural assets more effective and efficient by redefining methodologies to safeguard and interact with them. This paper proposes a framework for integrating legal and digital tools that are functional for the preservation, conservation, and enhancement of cultural heritage. To define it, on the one hand, the legal instruments in force were analysed, and on the other, a literature review on the digital technologies currently available was carried out. The role of digital transformation in the cultural sphere was also examined, especially in light of Ukraine’s experience with the application of digital technologies to protect and recover cultural heritage during the current conflict.
Biological Characteristics, Pathogenicity, and Sensitivity to Fungicides of Four Species of Lasiodiplodia on Avocado Fruits
Authors: Chen Yingying , Lan Xiaomei , He Rui , Wang Meng , Zhang Yu , Yang Ye
Published: November 2024

This study focuses on four species of Lasiodiplodia (L. euphorbiaceicola, L. mahajangana, L. theobromae, and L. pseudotheobromae), which are associated with avocado stem end rot (SER) in Hainan, China. The factors affecting the growth of Lasiodiplodia, pathogenicity to avocado and other tropical fruits, and sensitivity to 12 fungicides, were tested. All Lasiodiplodia spp. isolates were grown between 10 °C and 40 °C, with optimal growth temperature ranging from 28 to 30 °C; the lethal temperature ranged from 51 to 53 °C for 10 min. Optimal growth pH ranged from 5 to 6. The most suitable medium was PDA, the preferred carbon sources were D–fructose and soluble starch, and the preferred nitrogen sources were yeast and beef extract. All Lasiodiplodia spp. isolates were highly pathogenic to avocado fruit. In addition, their pathogenicity to six tropical fruits (banana guava, mango, papaya, pitaya, and soursop) was evaluated, and the results reveal that all four species of Lasiodiplodia are able to infect these fruits to various degrees of severity. The pathogenicity of both L. theobromae and L. pseudotheobromae was the highest among all the species tested. All Lasiodiplodia spp. isolates were highly susceptible to the fungicides fludioxonil, carbendazim, thiophanate–methyl, tetramycin, iprodione, tebuconazole, prochloraz, and imazalil, which are good candidates for controlling avocado SER. The results of the present study provide important information on the biological characteristics of these four species of Lasiodiplodia and provide a basis for the management of SER in avocado.
Chromosome-Scale Genome of the Fern Cibotium barometz Unveils a Genetic Resource of Medicinal Value
Authors: Qin Guole , Pan Denglang , Long Ying , Lan Huiying , Guan Delong , Song Jing
Published: November 2024

Ferns represent the second-largest group of vascular plants, yet their genomic resources lag far behind. Here, we present a chromosome-scale genome assembly of Cibotium barometz (L.) J. Sm., a medicinally important fern species. The 3.49 Gb genome, assembled into 66 chromosomes with 99.41% sequence anchorage, revealed an exceptionally high proportion (83.93%) of repetitive elements, dominated by recently expanded LTR retrotransposons. We identified 30,616 protein-coding genes, providing insights into fern-specific gene families. Genomic analyses uncover the evolutionary dynamics of 513 key biosynthetic genes, particularly those involved in terpenoid and flavonoid production. Expression profiling across tissues revealed tissue-specific regulation of these pathways, with notable upregulation of chalcone synthase genes in roots. Our structural analysis of 1-deoxy-d-xylulose-5-phosphate synthase, a key enzyme in terpenoid biosynthesis, demonstrated high conservation across land plants while highlighting fern-specific adaptations. The identification of multiple isoforms for key enzymes points to potential gene-duplication events or the evolution of fern-specific variants. This genome provides a foundation for understanding fern biology, evolution, and the molecular basis of their medicinal properties. It also offers valuable resources for conservation efforts and pharmacological research, paving the way for sustainable utilization of this valuable medicinal plant and advancing our understanding of plant diversity and natural product biosynthesis.
Student Engagement and the Role of Technology
Authors: Hess Salinda , Tremblay Francine
Published: November 2024

This paper examines our collective exploratory research on Anthropology and Sociology students at Concordia University. As teaching faculty members at Concordia, we have all observed a significant shift in our student population over the past fifteen years. They appear to be more detached and less involved in their studies, a phenomenon that has piqued our collective curiosity. Our first insight into the possible reasons behind this shift came from Rob Beamish’s The Promise of Sociology (2010), where he explored the relationship between technology and knowledge. Inspired by Beamish, we sought to understand the relationship between technology and students’ performance. At the beginning of this research, we never imagined that the world would be under lockdown because of a pandemic (2020–2022) and forced to rely on technology; anyone teaching at the height of COVID-19 was obligated to use technology, which makes Beamish’s argument an even more relevant place to start. Lastly, we delved into the potential impact of technology on students’ health.
Investigation of Critical Aspects of Roughness Assessment for Airfield Pavements
Authors: Armeni Angeliki , Plati Christina , Loizos Andreas
Published: November 2024

One of the main priorities of airport authorities is to maintain a high level of serviceability of runway pavements due to the high safety requirements for aircraft at high speeds. Accordingly, the assessment of the functional condition of airfield pavements is crucial for the proper operation of an airport. The most critical functional parameter appears to be pavement roughness. It characterizes the condition of the runway surface and is directly related to the safety of aircraft flights, as it affects the handling characteristics and braking performance of the aircraft, the increase in operating costs, and the wear of the aircraft. Worldwide, there are several indices for assessing the roughness of airfield pavements. This study aims to compare some of these indices to assess their ability to capture the characteristics of airfield pavement roughness. For this purpose, roughness data were collected along a runway with flexible pavement at a regional airport in southeast Europe and corresponding indices were estimated. The analysis of the data leads to the most efficient index for assessing the roughness of airfield surfaces to date. However, the need for a new index that expresses the response of the aircraft remains a critical issue.
Multi-Objective Optimization Algorithm Based Bidirectional Long Short Term Memory Network Model for Optimum Sizing of Distributed Generators and Shunt Capacitors for Distribution Systems
Authors: Alluri Amarendra , Gampa Srinivasa Rao , Gutta Balaji , Basam Mahesh Babu , Jasthi Kiran , Roy Nibir Baran , Das Debapriya
Published: November 2024

In this paper, a multi-objective grey wolf optimization (GWO) algorithm based Bidirectional Long Short Term Memory (BiLSTM) network machine learning (ML) model is proposed for finding the optimum sizing of distributed generators (DGs) and shunt capacitors (SHCs) to enhance the performance of distribution systems at any desired load factor. The stochastic traits of evolutionary computing methods necessitate running the algorithm repeatedly to confirm the global optimum. In order to save utility engineers time and effort, this study introduces a BiLSTM network-based machine learning model to directly estimate the optimal values of DGs and SHCs, rather than relying on load flow estimates. At first, a multi-objective grey wolf optimizer determines the most suitable locations and capacities of DGs and SHCs at the unity load factor and the same locations are used to obtain optimum sizing of DGs and SHCs at other load factors also. The base case data sets consisting of substation apparent power, real power load, reactive power load, real power loss, reactive power loss and minimum node voltage at various load factors in per unit values are taken as input training data for the machine learning model. The optimal sizes of the DGs and SHCs for the corresponding load factors obtained using GWO algorithm are taken as target data sets in per unit values for the machine learning model. An adaptive moment estimation (adam) optimization approach is employed to train the BiLSTM ML model for identifying the ideal values of distributed generations and shunt capacitors at different load factors. The efficacy of the proposed ML-based sizing algorithm is demonstrated via simulation studies.
A Multi-Scale Convolutional Neural Network with Self-Knowledge Distillation for Bearing Fault Diagnosis
Authors: Yu Jiamao , Hu Hexuan
Published: November 2024

Efficient bearing fault diagnosis not only extends the operational lifespan of rolling bearings but also reduces unnecessary maintenance and resource waste. However, current deep learning-based methods face significant challenges, particularly due to the scarcity of fault data, which impedes the models’ ability to effectively learn parameters. Additionally, many existing methods rely on single-scale features, hindering the capture of global contextual information and diminishing diagnostic accuracy. To address these challenges, this paper proposes a Multi-Scale Convolutional Neural Network with Self-Knowledge Distillation (MSCNN-SKD) for bearing fault diagnosis. The MSCNN-SKD employs a five-stage architecture. Stage 1 uses wide-kernel convolution for initial feature extraction, while Stages 2 through 5 integrate a parallel multi-scale convolutional structure to capture both global contextual information and long-range dependencies. In the final two stages, a self-distillation process enhances learning by allowing deep-layer features to guide shallow-layer learning, improving performance, especially in data-limited scenarios. Extensive experiments on multiple datasets validate the model’s high diagnostic accuracy, computational efficiency, and robustness, demonstrating its suitability for real-time industrial applications in resource-limited environments.
Designing a Tactile Document UI for 2D Refreshable Tactile Displays: Towards Accessible Document Layouts for Blind People
Authors: Alzalabny Sara , Moured Omar , Müller Karin , Schwarz Thorsten , Rapp Bastian , Stiefelhagen Rainer
Published: November 2024

Understanding document layouts is vital for enhancing document exploration and information retrieval for sighted individuals. However, for blind and visually impaired people, it becomes challenging to have access to layout information using typical assistive technologies such as screen readers. In this paper, we examine the potential benefits of presenting documents on two-dimensional (2D) refreshable tactile displays. These displays enable the tactile perception of 2D data, offering the advantage of dynamic and interactive functionality. Despite their potential, the development of user interfaces (UIs) for such displays has not advanced significantly. Thus, we propose a design of an intelligent tactile user interface (TUI), incorporating touch and audio feedback to represent documents in a tactile format. Our exploratory study for evaluating this approach revealed satisfaction from participants with the experience of directly viewing documents in their true form, rather than relying on screen-reading interpretations. Additionally, participants offered recommendations for incorporating additional features and refining the approach in future iterations. To facilitate further research and development, we have made our dataset and models publicly available.
R-Spondin 1 Suppresses Inflammatory Cytokine Production in Human Cortical Astrocytes
Authors: Logan Robert , Bhatta Sagar , Sutova Hande Eda , Hafler Brian P. , Miller Sean J.
Published: November 2024

Background/Objectives: Wnt signaling pathways are essential in various biological processes, including embryonic development and tissue homeostasis, and are implicated in many diseases. The R-Spondin (RSpo) family, particularly RSpo1, plays a significant role in modulating Wnt signaling. This study aims to explore how RSpo1 binding to astrocytic LGR6 receptors influences central nervous system (CNS) homeostasis, particularly in the context of inflammation. Methods: Human-induced pluripotent stem cell-derived astrocytes were treated with RSpo1 to assess its impact on inflammatory cytokine release. A proteomic analysis was conducted using a Human Cytokine Array Kit to measure differential protein expression. Pathway enrichment analysis was performed to identify affected signaling pathways. Results: RSpo1 treatment led to a suppression of inflammatory cytokines such as IL-10, IFN-γ, and IL-23 in astrocytes, while TNF-α and CXCL12 levels were increased. Pathway analysis revealed significant alterations in key signaling pathways, including cytokine–cytokine receptor interaction, chemokine signaling, and TNF signaling pathways, suggesting RSpo1’s role in modulating immune responses within the CNS. Conclusions: RSpo1 significantly influences inflammatory responses in astrocytes by modulating cytokine release and altering key signaling pathways. These findings enhance our understanding of the interaction between cell-specific Wnt signaling and CNS inflammation, suggesting potential therapeutic applications of RSpo1 in neuroinflammatory and neurodegenerative diseases.
Enhanced Bioavailability and Immune Benefits of Liposome-Encapsulated Vitamin C: A Combination of the Effects of Ascorbic Acid and Phospholipid Membranes
Authors: McGarry Sage V. , Cruickshank Dina , Iloba Ifeanyi , Jensen Gitte S.
Published: November 2024

The bioavailability of vitamin C, or ascorbic acid, depends on limiting transport mechanisms that may be bypassed by liposome-encapsulation. The goal for this study was to evaluate the uptake, antioxidant, and immune-modulating effects of liposome-encapsulated vitamin C (LEC) using Lypo-Spheric® technology, compared to three controls: ascorbic acid (AA), the phospholipid fraction composing the liposome, and placebo. A double-blinded placebo-controlled cross-over study design involved twelve healthy participants attending four clinic visits. At each visit, a baseline blood draw was performed, followed by consumption of 1 g LEC, 1 g AA, the phospholipid component of LEC, or placebo. Additional blood draws were performed at 2, 4, and 6 h. Consuming LEC and AA increased blood levels of vitamin C; the levels were significantly higher after consuming LEC at all timepoints when compared to AA (p < 0.01). LEC consumption increased serum antioxidant capacity (p < 0.01 at 2 h) and protection. Consuming LEC increased IFN-γ levels at 6 h, while consuming the phospholipid fraction rapidly decreased inflammatory cytokines IL-6, MCP-1, and MIP-1α at 2 h. Consuming LEC provided enhanced vitamin C bioavailability and antioxidant protection compared to AA. Consuming the phospholipids had anti-inflammatory effects. The results suggest that LEC provides antioxidant and immune benefits above AA, useful in preventive medicine.
Adjunctive Therapies in Rheumatoid Arthritis
Authors: González Heredia Tonatiuh , Hernández Corona Diana Mercedes , Méndez del Villar Miriam , Guzmán Ornelas Milton Omar , Corona Meraz Fernanda Isadora , Chávez Tostado Mariana , Diosdado Pardo Grecia Elizabeth , Pérez Padilla Arely Jaqueline , Pérez Villalobos Fátima Berenice , Montaño Vargas Perla Yareli , Morales García Paola
Published: November 2024

Rheumatoid arthritis is an autoimmune pathology that follows a chronic course characterized by the involvement of the synovial membrane of joints all over the body. Clinically, the disease is characterized by persistent and painful immune-mediated inflammation, which culminates in bone deformations and joint movement limitation. Alternative therapies, such as garlic, ginger, curcumin, and resveratrol, are beneficial given their anti-inflammatory properties. These alternative therapies are a secondary option for treating the clinical manifestations of rheumatoid arthritis, helping to improve the patient’s quality of life further and preventing future complications.
The Two-Thirds Power Law Derived from a Higher-Derivative Action
Authors: Boulanger Nicolas , Buisseret Fabien , Dierick Frédéric , White Olivier
Published: November 2024

The two-thirds power law is a link between angular speed ω and curvature κ observed in voluntary human movements: ω is proportional to κ2/3. Squared jerk is known to be a Lagrangian leading to the latter law. However, it leads to unbounded movements and is therefore incompatible with quasi-periodic dynamics, such as the movement of the tip of a pen drawing ellipses. To solve this drawback, we give a class of higher-derivative Lagrangians that allow for both quasi-periodic and unbounded movements, and at the same time lead to the two-thirds power law. The current study extends this framework and investigates a wider class of Lagrangians admitting generalised conservation laws.