bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparative Study of the Protective and Neurotrophic Effects of Neuronal and Glial Progenitor Cells-Derived Conditioned Media in a Model of Glutamate Toxicity In Vitro
Authors: Leonov Georgy , Salikhova Diana , Shedenkova Margarita , Bukharova Tatiana , Fatkhudinov Timur , Goldshtein Dmitry
Published: December 2023

Cell therapy represents a promising approach to the treatment of neurological diseases, offering potential benefits not only by cell replacement but also through paracrine secretory activities. However, this approach includes a number of limiting factors, primarily related to safety. The use of conditioned stem cell media can serve as an equivalent to cell therapy while avoiding its disadvantages. The present study was a comparative investigation of the antioxidant, neuroprotective and neurotrophic effects of conditioned media obtained from neuronal and glial progenitor cells (NPC-CM and GPC-CM) on the PC12 cell line in vitro. Neuronal and glial progenitor cells were obtained from iPSCs by directed differentiation using small molecules. GPC-CM reduced apoptosis, ROS levels and increased viability, expressions of the antioxidant response genes HMOX1 and NFE2L2 in a model of glutamate-induced oxidative stress. The neurotrophic effect was evidenced by a change in the morphology of pheochromocytoma cells to a neuron-like phenotype. Moreover, neurite outgrowth, expression of GAP43, TUBB3, MAP2, SYN1 genes and increased levels of the corresponding MAP2 and TUBB3 proteins. Treatment with NPC-CM showed moderate antiapoptotic effects and improved cell viability. This study demonstrated the potential application of CM in the field of regenerative medicine.
Deep Learning-Based Prediction of Alzheimer’s Disease Using Microarray Gene Expression Data
Authors: Abdelwahab Mahmoud M. , Al-Karawi Khamis A. , Semary Hatem E.
Published: December 2023

Alzheimer’s disease is a genetically complex disorder, and microarray technology provides valuable insights into it. However, the high dimensionality of microarray datasets and small sample sizes pose challenges. Gene selection techniques have emerged as a promising solution to this challenge, potentially revolutionizing AD diagnosis. The study aims to investigate deep learning techniques, specifically neural networks, in predicting Alzheimer’s disease using microarray gene expression data. The goal is to develop a reliable predictive model for early detection and diagnosis, potentially improving patient care and intervention strategies. This study employed gene selection techniques, including Singular Value Decomposition (SVD) and Principal Component Analysis (PCA), to pinpoint pertinent genes within microarray datasets. Leveraging deep learning principles, we harnessed a Convolutional Neural Network (CNN) as our classifier for Alzheimer’s disease (AD) prediction. Our approach involved the utilization of a seven-layer CNN with diverse configurations to process the dataset. Empirical outcomes on the AD dataset underscored the effectiveness of the PCA–CNN model, yielding an accuracy of 96.60% and a loss of 0.3503. Likewise, the SVD–CNN model showcased remarkable accuracy, attaining 97.08% and a loss of 0.2466. These results accentuate the potential of our method for gene dimension reduction and classification accuracy enhancement by selecting a subset of pertinent genes. Integrating gene selection methodologies with deep learning architectures presents a promising framework for elevating AD prediction and promoting precision medicine in neurodegenerative disorders. Ongoing research endeavors aim to generalize this approach for diverse applications, explore alternative gene selection techniques, and investigate a variety of deep learning architectures.
Extracting Technicians’ Skills for Human–Machine Collaboration in Aircraft Assembly
Authors: Tian Yaling , Li Ji , Dan Junjie , Shu Yongsheng , Liu Chang , Li Ruijie , Liu Shiyong
Published: December 2023

Research on the efficiency and quality issues faced in aircraft assembly was conducted in this article. A new method of human–machine collaborative riveting was proposed, which combined the flexibility of manual collaboration with the precise control of automatic riveting. The research works include: (1) a theoretical model of pneumatic hammer riveting was established to clarify the principle and parameters of riveting process. (2) A smart bucking bar was designed to support the data collection and extraction of manual collaborative riveting process. (3) An automatic riveting experimental platform was designed to test the automatic riveting process incorporating the extracted manual riveting process parameters, and further an optimization strategy was proposed for the automatic riveting process. (4) A human–machine collaborative riveting experimental platform was developed to conduct the verification work. Through the theoretical analysis, experimental research, system scheme design, and process parameters optimization, the application and verification of human–machine collaborative assembly technology have been achieved. This technology is expected to be comprehensively promoted in the field of aircraft manufacturing, and for breaking through the current difficulties of low production efficiency and poor assembly quality control.
Assessing the Soundscape Characteristics of Historical Urban Environments: An Analysis of the Historical Erbil Citadel and Its Environments
Authors: Jaff Asmaa Ahmed Mustafa , Erçin Çilen , Onur Zeynep
Published: December 2023

This research addresses the neglect of sensory features, specifically the soundscape, in studies focused on preserving historic areas. The aim was to contribute to soundscape research by examining the effect of sound on the perception of urban historical places and the impact of the “renewal and transformation” process on audio-visual experiences. This study focused on the historical Erbil Citadel as a case study area, known for its extensive cultural history. Sound sources in the region were identified, recorded, and analyzed using software to calculate the Sound Pressure Level (SPL). The sound sources assessed as a result of the analysis were examined using Schafer’s sound characteristics. In this study, data was collected through a soundwalk study in the historical Erbil Citadel, and its surroundings were identified. The characteristics of the sounds were determined from the sound recordings, enabling the distinction of sounds contributing to the city’s identity. A route was established in its current state, and it was identified which regional precautions should be taken to preserve the sound identity of the city.
Strength Formation and Failure Mechanism Analysis of Cement-Stabilized Laterite Granules Based on Numerical Simulation
Authors: Zou Guilian , Yang Bo , Yu Jiangmiao , Yang Susu , Chen Qi
Published: December 2023

The poor grading and significant differences in the mechanical properties of laterite granules in West Africa limit the application of this typical material in road structures. In this paper, the poorly graded laterite granule was blended with fine sand and stabilized with cement to improve the strength of laterite granules. An innovative combination of laboratory tests and numerical simulation analysis using the numerical simulation software PFC2D 5.0 was used to investigate the cement-stabilized laterite granule’s strength formation and failure mechanisms. Laboratory test results show that when the sand content is 40%, the grading curve is close to the maximum theoretical density lines (MTDLs), and the unconfined compressive strength of cement-stabilized laterite granules increased by 35.2% as the cement dosage increased from 2.5% to 5.0%. Numerical simulation tests show that the strength failure of cement-stabilized laterite granules is shear. The failure surface is tilted and through with the axial direction, and the compressive and tensile stresses between the particles cause the failure of the specimen. The simulation test results are close to the laboratory test results, and the deviation rate is less than 10%. It can guide the optimal grading design and strength prediction of cement-stabilized laterite granular materials and provides a basis for reducing laboratory tests and accurate design for such research in the future.
In Vitro Organoid-Based Assays Reveal SMAD4 Tumor-Suppressive Mechanisms for Serrated Colorectal Cancer Invasion
Authors: Tong Kevin , Bandari Manisha , Carrick Jillian N. , Zenkevich Anastasia , Kothari Om A. , Shamshad Eman , Stefanik Katarina , Haro Katherine S. , Perekatt Ansu O. , Verzi Michael P.
Published: December 2023

Colon cancer is the third most prominent cancer and second leading cause of cancer-related deaths in the United States. Up to 20% of colon cancers follow the serrated tumor pathway driven by mutations in the MAPK pathway. Loss of SMAD4 function occurs in the majority of late-stage colon cancers and is associated with aggressive cancer progression. Therefore, it is important to develop technology to accurately model and better understand the genetic mechanisms behind cancer invasion. Organoids derived from tumors found in the Smad4KO BRAFV600E/+ mouse model present multiple phenotypes characteristic of invasion both in ex vivo and in vivo systems. Smad4KO BRAFV600E/+ tumor organoids can migrate through 3D culture and infiltrate through transwell membranes. This invasive behavior can be suppressed when SMAD4 is re-expressed in the tumor organoids. RNA-Seq analysis reveals that SMAD4 expression in organoids rapidly regulates transcripts associated with extracellular matrix and secreted proteins, suggesting that the mechanisms employed by SMAD4 to inhibit invasion are associated with regulation of extracellular matrix and secretory pathways. These findings indicate new models to study SMAD4 regulation of tumor invasion and an additional layer of complexity in the tumor-suppressive function of the SMAD4/Tgfβ pathway.
Generation of a Zebrafish Knock-In Model Recapitulating Childhood ETV6::RUNX1-Positive B-Cell Precursor Acute Lymphoblastic Leukemia
Authors: Zapilko Veronika , Moisio Sanni , Parikka Mataleena , Heinäniemi Merja , Lohi Olli
Published: December 2023

Approximately 25% of children with B-cell precursor acute lymphoblastic leukemia (pB-ALL) harbor the t(12;21)(p13;q22) translocation, leading to the ETV6::RUNX1 (E::R) fusion gene. This translocation occurs in utero, but the disease is much less common than the prevalence of the fusion in newborns, suggesting that secondary mutations are required for overt leukemia. The role of these secondary mutations remains unclear and may contribute to treatment resistance and disease recurrence. We developed a zebrafish model for E::R leukemia using CRISPR/Cas9 to introduce the human RUNX1 gene into zebrafish etv6 intron 5, resulting in E::R fusion gene expression controlled by the endogenous etv6 promoter. As seen by GFP fluorescence at a single-cell level, the model correctly expressed the fusion protein in the right places in zebrafish embryos. The E::R fusion expression induced an expansion of the progenitor cell pool and led to a low 2% frequency of leukemia. The introduction of targeted pax5 and cdkn2a/b gene mutations, mimicking secondary mutations, in the E::R line significantly increased the incidence in leukemia. Transcriptomics revealed that the E::R;pax5mut leukemias exclusively represented B-lineage disease. This novel E::R zebrafish model faithfully recapitulates human disease and offers a valuable tool for a more detailed analysis of disease biology in this subtype.
Cannabis Use among Cancer Survivors: Use Pattern, Product Type, and Timing of Use
Authors: Osaghae Ikponmwosa , Chido-Amajuoyi Onyema Greg , Khalifa Banda A. A. , Talluri Rajesh , Shete Sanjay
Published: December 2023

Despite growing interest in the use of cannabis for the treatment of cancer-related symptoms, there are limited studies that have assessed the use pattern, type, and mode of delivery of cannabis products used by cancer survivors. This study describes the current state of the use pattern, product type, and mode of delivery of cannabis used by cancer survivors. This was a cross-sectional study of cancer survivors from 41 U.S. states who received treatment at the largest NCI-designated comprehensive cancer center. The weighted prevalence of the use patterns, product types, and modes of delivery of cannabis used by cancer survivors was estimated. A total of 1886 cancer survivors were included in the study, with 915 (48% [95% CI: 45–51]) reporting ever using cannabis. Of survivors who had ever used cannabis, 36% (95% CI: 33–40) were current users. Among survivors who reported cannabis use after diagnosis, 40% used cannabis during and after cancer treatment, 35% used cannabis during treatment, and 25% used cannabis after completing their cancer treatment. Additionally, 48% of survivors reported an increase in cannabis use since cancer diagnosis. The commonest types of cannabis products used by cancer survivors were dry leaf cannabis (71%), cannabidiol (CBD) oil (46%), and cannabis candy (40%). Moreover, cancer survivors frequently used baked goods (32%), creams and gels (21%), and tinctures (18%). Furthermore, among ever users, the predominant mode of use was cannabis inhalation/smoking (69%) compared to eating/drinking (59%). More so, the common mode of inhalation/smoking of cannabis products were rolled cannabis cigarettes (79%), pipes (36%), water pipes (34%), vaporizers or vapes (14%), and e-cigarette devices (14%). A substantial number of cancer survivors use cannabis during cancer treatment, with increased use following cancer diagnosis. The forms and modes of delivery of cannabis varied among survivors, with most survivors inhaling or smoking cannabis. There is a need to educate healthcare providers (HCPs) and survivors on current evidence of cannabis use and strengthen cannabis regulatory frameworks to optimize benefits and minimize adverse events from cannabis use during cancer treatment.
BENDI: Improving Cognitive Assessments in Toddlers and Children with Down Syndrome Using Stealth Assessment
Authors: Tenorio Marcela , Arango Paulina S. , Aparicio Andrés
Published: December 2023

Cognitive assessment is a fundamental step in diagnosing intellectual and developmental disabilities, designing interventions, and evaluating their impact. However, developed and developing countries have different access to tools designed for these purposes. Our goal was to develop a battery for cognitive assessment mediated by digital technology that allows the exploration of cognitive domains (inhibitory control, attention, motor ability, and context memory) in children with Down Syndrome (DS) in Chile. Four tasks, based on established experimental paradigms modified to provide a game-like experience, were tested in 68 children with DS from 20 months to 12 years of age. We present evidence of reliability based on internal consistency and split-half analyses, with results ranging from adequate to excellent. Regarding validity, factorial and correlational analyses show evidence consistent with what was theoretically expected of internal structure, convergence, and divergence with other measures. Expected age trajectories were observed as well. Our data offer evidence that supports the use of tasks based on touch-screen devices for cognitive assessment in the population with DS. The tasks also have a low cultural load, so they could be validated and used in other contexts without the need for an adaptation process.
The Influence of Niobium and Zirconium Addition on the Structural and Mechanical Properties of Yttrium Nitride: A First-Principles Study
Authors: Alruqi Adel Bandar
Published: December 2023

Yttrium nitride (YN) is a hard and refractory material with a high melting point. It is a semiconductor that has been investigated for its potential applications in the field of semiconductor technology, including as a material for electronic devices. It is also of interest for its optical properties and its potential for use in optoelectronics. However, investigating its mechanical properties for a possible application in optical coatings has not been completed. This study involved the exploration of the mechanical properties of YN alloyed with niobium (Nb) and zirconium (Zr) for possible application in optical coatings using a first-principles approach. The result showed that the addition of Nb and Zr into the YN matrix had a profound effect on the mechanical properties of the modeled structures, with the Y-N-Nb (CYN_5) sample having the best mechanical properties. The bulk modulus was the most affected, with an increase of 26.48%, while the Vickers hardness had the smallest increase of 6.128% compared with those of pure YN. The modeled structures were thus found to be ideal alternative materials for optical coatings due to their improved mechanical properties.
Modeling of Solid Particle Erosion for a Water–Sand Impingement System Using OpenFOAM
Authors: Narváez Mateo , Cruzatty Cristian , Valencia Esteban , Hidalgo Víctor , Luo Xianwu , Torres Alejandra , Erazo José , Altamirano Gonzalo , Cando Edgar
Published: December 2023

The development of accurate methodologies for a thorough comprehension of the erosion phenomenon is a challenging and necessary task. This study entailed an exhaustive analysis, incorporating empirical data obtained from an experiment involving the impingement of a sand and water jet on a submerged stainless-steel plate and numerical simulations, employing the Oka Erosion model that was compilated in OpenFOAM. The primary focus of this study was to generate W-shaped profiles delineating the impingement zone, derived both from experimental observations and the developed numerical model. This comparative approach facilitated a robust evaluation of the model’s efficacy in replicating erosion patterns. The outcomes of this analysis revealed a concurrence between the experimental and simulated erosion contours, affirming the model’s proficiency in representing erosion phenomena. Nevertheless, a minor discrepancy was noted, characterized by a slight underestimation of erosion rate and thickness loss. Furthermore, the investigation unveiled a noteworthy time-dependent trend in mass loss from the experimental data denoting a pseudo stabilization of the erosion rate across the time. This research contributes to the refinement of erosion modeling parameters and underscores the nature of time-dependent erosion behavior, a pivotal consideration for optimizing material durability.
Optimal Model-Free Finite-Time Control Based on Terminal Sliding Mode for a Coaxial Rotor
Authors: Glida Hossam , Sentouh Chouki , Rath Jagat
Published: December 2023

This study focuses on addressing the tracking control problem for a coaxial unmanned aerial vehicle (UAV) without any prior knowledge of its dynamic model. To overcome the limitations of model-based control, a model-free approach based on terminal sliding mode control is proposed for achieving precise position and rotation tracking. The terminal sliding mode technique is utilized to approximate the unknown nonlinear model of the system, while the global stability with finite-time convergence of the overall system is guaranteed using the Lyapunov theory. Additionally, the selection of control parameters is addressed by incorporating the accelerated particle swarm optimization (APSO) algorithm. Finally, numerical simulation tests are provided to demonstrate the effectiveness and feasibility of the proposed design approach, which demonstrates the capability of the model-free control approach to achieve accurate tracking control even without prior knowledge of the system’s dynamic model.
Multispectral Remote Sensing Data Application in Modelling Non-Extensive Tsallis Thermodynamics for Mountain Forests in Northern Mongolia
Authors: Sandlersky Robert , Petrzhik Nataliya , Jargalsaikhan Tushigma , Shironiya Ivan
Published: December 2023

The imminent threat of Mongolian montane forests facing extinction due to climate change emphasizes the pressing need to study these ecosystems for sustainable development. Leveraging multispectral remote sensing data from Landsat 8 OLI TIRS (2013–2021), we apply Tsallis non-extensive thermodynamics to assess spatiotemporal fluctuations in the absorbed solar energy budget (exergy, bound energy, internal energy increment) and organizational parameters (entropy, information increment, q-index) within the mountain taiga–meadow landscape. Using the principal component method, we discern three functional subsystems: evapotranspiration, heat dissipation, and a structural-informational component linked to bioproductivity. The interplay among these subsystems delineates distinct landscape cover states. By categorizing ecosystems (pixels) based on these processes, discrete states and transitional areas (boundaries and potential disturbances) emerge. Examining the temporal dynamics of ecosystems (pixels) within this three-dimensional coordinate space facilitates predictions of future landscape states. Our findings indicate that northern Mongolian montane forests utilize a smaller proportion of received energy for productivity compared to alpine meadows, which results in their heightened vulnerability to climate change. This approach deepens our understanding of ecosystem functioning and landscape dynamics, serving as a basis for evaluating their resilience amid ongoing climate challenges.
Research on the Threshold Determination Method of the Duffing Chaotic System Based on Improved Permutation Entropy and Poincaré Mapping
Authors: Zhou Jing , Li Yaan , Wang Mingzhou
Published: December 2023

The transition from a chaotic to a periodic state in the Duffing chaotic oscillator detection system is crucial in detecting weak signals. However, accurately determining the critical threshold for this transition remains a challenging problem. Traditional methods such as Melnikov theory, the Poincaré section quantitative discrimination method, and experimental analyses based on phase diagram segmentation have limitations in accuracy and efficiency. In addition, they require large computational data and complex algorithms while having slow convergence. Improved permutation entropy incorporates signal amplitude information on the basis of permutation entropy and has better noise resistance. According to the characteristics of improved permutation entropy, a threshold determination method for the Duffing chaotic oscillator detection system based on improved permutation entropy (IPE) and Poincaré mapping (PM) is proposed. This new metric is called Poincaré mapping improved permutation entropy (PMIPE). The simulation results and the verification results of real underwater acoustic signals indicate that our proposed method outperforms traditional methods in terms of accuracy, simplicity, and stability.
Mitigating the Effects of Design for Manufacturability on Design Iteration Cycles in Advanced Integrated Circuit Design
Authors: Wu Chan-Liang , Lu Chih-Wen
Published: December 2023

In integrated circuit (IC) design for advanced manufacturing processes, iterative improvement processes are an approach commonly used for improving design quality, particularly for low-energy, high-frequency circuits. Layout-dependent effects (LDEs) affect IC design and fabrication, resulting in differences in circuit functionality and performance in presimulation versus postsimulation. These differences can greatly increase the length of design iteration cycles. Foundries have attempted to accelerate the iterative design process by providing process design kit libraries to IC designers. However, these kits can neither fully mitigate the negative affect of LDEs on design for manufacturability (DFM) nor eliminate the difference between presimulation and postsimulation results. To address this problem, this study proposed a novel algorithm-based design process in which an IC designer can use layout parasitic extraction to extract the DFM parameters of all components in a circuit prior to the routing process; these parameters include netlists that describe the internal connectivity of components as well as their interconnectivity with other components. Accordingly, the IC designer can determine the effects of DFM parameters on the circuit and modify them in advance if necessary. When the LDEs generated by device placement have been confirmed to not affect circuit properties, physical verification of the routing of metal wires in the IC layout can be performed. In this verification, postsimulations only need to focus on problems regarding the wire loading and timing effects of metal routing. The proposed design process is useful for mitigating LDEs in IC design and considerably reduces the time required for iterative improvement processes. Specifically, this study provides a method of enhancing design iteration cycles and provides guidelines for analyzing factors that hinder IC device functionality and performance. In sum, various problems can be resolved by separately extracting the DFM parameters associated with LDEs and parasitic parameters associated with routing.
A Fault Identification Method for Metal Oxide Arresters Combining Suppression of Environmental Temperature and Humidity Interference with a Stacked Autoencoder
Authors: Shu Shengwen , Zhang Xiaoyao , Wang Guobin , Zeng Jinglan , Ruan Ying
Published: December 2023

Most existing methods aiming to solve the fault identification problem of metal oxide arresters (MOAs) are limited by strong subjectivity in judgment, the significant impact of environmental temperature and humidity on the online monitoring of the resistance current, and poor generalization ability. Therefore, in this article, we propose an MOA fault identification method that combines suppressing environmental temperature and humidity interference with a stacked autoencoder (SAE). Firstly, a functional relationship model between resistance current and environmental temperature and humidity is established. Then, a temperature and humidity interference suppression method based on weighted nonlinear surface modeling is proposed to normalize the resistance current to the same reference temperature and humidity conditions. Finally, an MOA fault identification method combining the suppression of environmental temperature and humidity interference with an SAE is proposed. Furthermore, a comprehensive comparison is conducted on the recall, accuracy, F1-score, and average accuracy of support vector machine, random forest, logistic regression, and SAE classification algorithms in three different scenarios to demonstrate the effectiveness of the proposed method. The results indicate that environmental temperature and humidity interference suppression for resistive current prior to MOA fault classification significantly reduce the number of false alarms. Compared with other methods, the MOA fault identification method, which combines environmental temperature and humidity interference suppression with an SAE, has the highest average accuracy of 99.7%.
Adjustable Capability Evaluation of Integrated Energy Systems Considering Demand Response and Economic Constraints
Authors: Li Yang , Li Rongqiang , Shi Linjun , Wu Feng , Zhou Jianhua , Liu Jian , Lin Keman
Published: December 2023

The coupling between multiple energy sources such as electricity, gas, and heat is strengthened in an integrated energy system (IES), and this, in turn, improves the operational flexibility of the IES. As an upper-level energy supply system, an IES can play a role as virtual energy storage, which can provide regulating power to smooth out the volatility from large-scale renewable energy generation. The establishment of an aggregating virtual energy storage model for IESs has become an important issue. Under this background, a multi-objective optimization-based adjustable capacity evaluation method is proposed in this paper. Firstly, the mathematical model of an IES considering the coupling of multiple kinds of energy forms is proposed. Then, an aggregating model considering demand response and economic constraints is established to demonstrate the adjustable capacity of the IES. In addition, multi-objective optimization is used to identify parameters in the proposed model, and the normal boundary intersection (NBI) method is used to solve the problem. Finally, a simulation example is provided to verify the effectiveness and feasibility of the proposed method. The external energy demand boundary of the IES can be modeled as virtual energy storage, and the coupling relations of electricity and gas can be presented. Case studies demonstrate that economic constraints narrow the adjustable capacity of the IES while the demand response extends it.
Migration of Artificial Turf Fibers from Artificial Turf Sports Field and Their Ingestion by Goldfish
Authors: Takahashi Kanoko , Fujinuma Ryosuke , Yoshitomi Tomoyasu , Shimizu Yasuo , Kobayashi Makito
Published: December 2023

Various artificial materials and facilities are sources of microplastics, including artificial turf sports fields. In artificial turf fields, polyethylene fibers are attached to a basal cloth with adhesives. In the present study, we investigated whether the fibers in the field were detached from the basal cloth or torn in the field, and whether they moved to the surrounding ditches that were connected to sewage pipes. In the field, we collected fibers shorter in length compared to the original and these were free from basal cloth, indicating the tearing of the fibers due to players’ activities. We also collected fibers from the ditches, which indicated a migration of the fibers from the field into the ditches. These results suggest that the fibers in ditches could enter sewage treatment plants and be released into the aquatic environment as microplastics. We also examined whether goldfish, Carassius auratus, ingested these fibers, and observed that the fish ingested them with feed while the fish did not without feed. These results indicate that the fiber ingestion by the fish occurred unintentionally when they swallowed their feed. The present study demonstrated that artificial turf fibers in sports fields could turn into microplastics that can be ingested by wild fishes.
Diversity Patterns and Determinants of Soil Microorganisms and Nematodes along Elevation Gradients in a Temperate Forest in South Korea
Authors: Lee Hae-In , Dong Ke , Lee Min-Ki , Lee Yong-Ju , Sim Hyung-Seok , Putra Ari Bima , Lee Chang-Bae
Published: December 2023

The elevational patterns of soil microbial and nematodes diversity (SMND) and the determinants remain controversial. Moreover, how the SMND are modified simultaneously with an elevational gradient has not yet been established. In this study, we investigated the elevational patterns of the SMND and the relative importance among/within tree factors (i.e., tree diversity, identity, and quantity) and environmental factors (i.e., climate and soil) on the SMND. For this purpose, we analyzed datasets from 27 plots across nine elevation bands in the temperate forests of Mt. Gariwang, South Korea. We performed multimodel inference tests and subsequently conducted a variance partitioning to determine the most prominent factors controlling each SMND and compare the relative contribution of the trees and environmental effects. Our results revealed that bacterial and fungal diversity decreased along the elevation gradient. However, nematode diversity did not change significantly, indicating that site-specific environmental conditions may be more influential than the elevation per se. Moreover, this indicates that bacterial diversity was affected by the pH and functional dispersion of the leaf size, and that fungal diversity was governed only by the pH. However, nematode diversity was driven by aboveground biomass, ammonium-nitrogen, and tree size diversity. In summary, the soil microbial diversity was more strongly controlled by the environmental factors, whereas the tree factors were more important for nematodes. Our results show that the elevational patterns and determinants of SMND differed among the taxonomic groups in the common micro-food web. These findings provide new insights into the factors controlling the SMND in a temperate forest and expand the local knowledge of soil biodiversity which is necessary for promoting its mainstreaming. Thus, our results contribute to establishing a basis for more targeted and effective biodiversity conservation and management practices in forest ecosystems.
Tree Biomass Modeling Based on the Exploration of Regression and Artificial Neural Networks Approaches
Authors: Kalkanlı Genç Şerife , Diamantopoulou Maria J. , Özçelik Ramazan
Published: December 2023

Understanding the dynamics of tree biomass is a significant factor in forest ecosystems, and accurate quantitative knowledge of its development provides support for the optimization of forest management. This work aimed to employ innovative practices in tree biomass modeling, artificial neural network approaches along with the least-squares regression methodology, in order to construct reliable and accurate estimation and prediction models that contribute to solving the emerging problems in the field of sustainable forest management. Based on this aim, different modeling strategies were developed and explored. The nonlinear seemingly unrelated regression (NSUR) methodology, the generalized regression (GRNN), the resilient propagation (RPNN) and the Bayesian regularization (BRNN) artificial neural network algorithms were utilized for the construction of reliable biomass models to attain the most accurate and reliable tree biomass components and total tree biomass estimations. The work showed that GRNN models provided a significantly better performance compared with the other modeling methodologies tested. Considering the non-parametric nature of the GRNN neural network algorithm, the fact that it was designed for nonlinear regression-type problems capable of dealing with small datasets, this modeling approach warrants consideration as an effective alternative to nonlinear regression or to other neural network approaches to the field of tree biomass modeling.
Physiological Mechanisms of Bretschneidera sinensis Hemsl. Seed Dormancy Release and Germination
Authors: Zhong Lijun , Dong Hongxing , Deng Zhijun , Li Jitao , Xu Li , Mou Jiaolin , Deng Shiming
Published: December 2023

Bretschneidera sinensis, the sole species of Bretschneidera, belonging to the family Akaniaceae, is a tertiary paleotropical flora. It is considered an endangered species by the International Union for Conservation of Nature (IUCN). It has an important protective and scientific value. The study of its seed dormancy and germination mechanisms contributes to better protection. In this study, the dormancy of fresh mature B. sinensis seeds released via low-temperature wet stratification was studied. In addition, the endogenous phytohormone levels, antioxidant enzyme activity, soluble sugar content, and the key metabolic enzyme activities of seeds at different stratification time nodes were determined. The goal was to analyze the mechanisms of seed dormancy release and germination comprehensively. Results show that low-temperature wet stratification under 5 °C can release seed dormancy effectively. During the seed dormancy release, the seed germination rate was positively correlated with soluble sugar, GA3, and IAA levels, as well as G-6-PDH, SOD, POD, CAT, and APX activity, but it was negatively correlated with MDH activity and ABA content. These imply that dormancy release might be attributed to the degradation of endogenous ABA and the oxidation of reactive oxygen species induced by low-temperature wet stratification. GA3, IAA, and the metabolism of energy substrates may be correlated with the induction and promotion of germination.
Extraction of Soluble Salts and Iron Sulfides from the Wood of the “Huaguangjiao I” Shipwreck
Authors: Wang Xueyu , Li Naisheng
Published: December 2023

Shipwreck wood often contains soluble salts and iron sulfides, which pose a threat to its stability. Therefore, desalination treatment must be carried out during protection. In this study, deionized water and ethylene diamine tetraacetic acid disodium salt (EDTA-2Na) solution were used to extract soluble salts and iron sulfides from the 511 wood components of the “Huaguangjiao I” shipwreck. The extraction lasted for 1120 days, during which extraction progress was monitored by measuring the electrical conductivity and iron content of the soaking solution. The results indicated that the extraction experiment reached its endpoint when the conductivity of the soaking solution was maintained at 80~100 μs/cm and the iron content was maintained at 8~15 mg/L. More than 143.35 kg of iron were extracted from the wood of the “Huaguangjiao I” shipwreck. After extraction, the content of soluble salt ions in the wood were less than 5 μg/g, with an iron content below 5%. The wood has returned to its original color and with a certain degree of degradation. “Huaguangjiao I” was the first large-scale marine shipwreck to complete the desalination treatment of all wooden components. This study provides guidance for the desalination treatment of large-scale wooden shipwrecks.
Tree Crown Affects Biomass Allocation and Its Response to Site Conditions and the Density of Platycladus orientalis Linnaeus Plantation
Authors: He Lulu , Zhang Xuan , Wang Xiaoxia , Ullah Haseen , Liu Yadong , Duan Jie
Published: December 2023

Tree crown plays a crucial role in the process of photosynthesis and the formation of biomass. The site conditions and stand density have a significant impact on tree and crown growth, as well as biomass formation. Understanding crown growth and its influence on the allometric growth of the biomass of various organs under diverse site conditions and densities is critical to comprehending forest adaptation to climate change and management. This study examined the growth of trees, crown, and biomass in 36 plots of young Platycladus orientalis plantations across three site conditions (S1: thin soil on the sunny slope; S2: thick soil on the sunny slope; S3: thin soil on the shady slope) and four densities (D1: ≤1500 plants/hm2; D2: 1501–2000 plants/hm2; D3: 2001–3000 plants/hm2; and D4: ≥3001 plants/hm2). The findings of this study showed that S3 demonstrated the best tree growth, with considerably higher DBH and V than S1 and S2. In addition, as the number of trees grew, the average diameter at breast height (DBH), height (H), and volume (V) all decreased greatly. Poor site (S1) suppressed the canopy, decreasing crown width (CW), crown length (CL), crown ratio (CR), crown surface area (CCSA), and crown volume (CCV), while increasing crown efficiency (CEFF). This same trend was seen in D4, where CR, CCSA, and CCV were all much smaller than the other densities, but CEFF was the highest. Subjective and objective indicators were less responsive to changes in crown growth than crown composite indicators like CCSA, CCV, CEFF, and CR. Site condition and density had a major impact on biomass accumulation, with S1 and D4 having a much lower biomass than S2, S3, D1, D2, and D3. More biomass was allocated to the stem in S3 and D1, and more biomass was allocated to branches and leaves in S2, S3, D1, D2, and D3, resulting in a nearly isotropic growth of branches and leaves. The effect of crown indicators on the biomass of each organ varied according to site condition and density. In varied site conditions, crown and DBH ratio (RCD) contributed the most to stem biomass, whereas CL contributed the most to branch and root biomass. CL had the largest effect on biomass accumulation at various densities. This study demonstrates how site condition and density affect tree and crown development and biomass accumulation, providing theoretical guidance for plantation management under climate change.
Perceiving Migrants as a Threat: The Role of the Estimated Number of Migrants and Symbolic Universes
Authors: Kosic Ankica , Andreassi Silvia , Cordella Barbara , De Dominicis Serena , Gennaro Alessandro , Iuso Salvatore , Kerusauskaite Skaiste , Mannarini Terri , Reho Matteo , Rocchi Giulia , Rochira Alessia , Signore Fulvio , Salvatore Sergio
Published: December 2023

As immigration is one of the dominant issues in contemporary public discourse, it is important to explain the mechanism of prejudice against immigrants from a cultural psychology perspective. Several studies in the literature have confirmed a significant relationship between perceptions of the estimated size of the immigrant population and negative attitudes towards them. This study aims to investigate whether this relationship is moderated by symbolic universes, i.e., affect-laden generalized worldviews. The study involves a representative sample of 3020 Italians who participated in a computer-assisted web survey and completed a questionnaire containing items measuring their estimates of the size of the migrant population in Italy, political orientation, cultural worldviews (symbolic universes), and the perceived threat posed by migrants. The results confirm that the relationship between the estimated size of the migrant population and the perceived threat is moderated by symbolic universes, being stronger for participants who hold both pessimistic and idealizing symbolic universes. The results are interpreted within the framework of semiotic cultural psychology theory.
Epigenetic Profiling of Type 2 Diabetes Mellitus: An Epigenome-Wide Association Study of DNA Methylation in the Korean Genome and Epidemiology Study
Authors: Seo Hyein , Park Jae-Ho , Hwang Jin-Taek , Choi Hyo-Kyoung , Park Soo-Hyun , Lee Jangho
Published: December 2023

Diabetes is characterized by persistently high blood glucose levels and severe complications and affects millions of people worldwide. In this study, we explored the epigenetic landscape of diabetes using data from the Korean Genome and Epidemiology Study (KoGES), specifically the Ansung–Ansan (AS–AS) cohort. Using epigenome-wide association studies, we investigated DNA methylation patterns in patients with type 2 diabetes mellitus (T2DM) and those with normal glucose regulation. Differential methylation analysis revealed 106 differentially methylated probes (DMPs), with the 10 top DMPs prominently associated with TXNIP, PDK4, NBPF20, ARRDC4, UFM1, PFKFB2, C7orf50, and ABCG1, indicating significant changes in methylation. Correlation analysis highlighted the association between the leading DMPs (e.g., cg19693031 and cg26974062 for TXNIP and cg26823705 for NBPF20) and key glycemic markers (fasting plasma glucose and hemoglobin A1c), confirming their relevance in T2DM. Moreover, we identified 62 significantly differentially methylated regions (DMRs) spanning 61 genes. A DMR associated with PDE1C showed hypermethylation, whereas DMRs associated with DIP2C, FLJ90757, PRSS50, and TDRD9 showed hypomethylation. PDE1C and TDRD9 showed a strong positive correlation between the CpG sites included in each DMR, which have previously been implicated in T2DM-related processes. This study contributes to the understanding of epigenetic modifications in T2DM. These valuable insights can be utilized in identifying potential biomarkers and therapeutic targets for effective management and prevention of diabetes.
Effectiveness of Self-Care Education for Chronic Neck Pain: A Systematic Review and Meta-Analysis
Authors: Valenza-Peña Geraldine , Martín-Núñez Javier , Heredia-Ciuró Alejandro , Navas-Otero Alba , López-López Laura , Valenza Marie Carmen , Cabrera-Martos Irene
Published: December 2023

Self-care programs for chronic neck pain are relevant to everyday life and can lead to long- term improvement. More studies on their effectiveness, key components and appropriate duration are needed. The aim of this study was to determine the effectiveness of self-care programs for patients with chronic neck pain. A systematic review and meta-analysis of randomized controlled trials was conducted according to the PRISMA guidelines. After searching in PubMed, Web of Science, Scopus and ScienceDirect, eleven studies met the inclusion criteria. Self-care education interventions typically consisted of education (i.e., pain neuro-science education or general educational concepts) accompanied by exercise or manual therapy. The most frequent components were addressing physical and psychological symptoms and engaging in self-care strategies. The least frequent ones were monitoring and recording symptoms and discussing with providers of medical care. The duration of the interventions ranged from three sessions to six months. Finally, individual and supervised modalities were the most frequent. After pooling the data, a meta-analysis was carried out according to four variables (i.e., pain, disability, kinesiophobia and catastrophization) and showed significant results (p < 0.05) in favor of self-care interventions. This systematic review and meta-analysis suggests that self-education interventions improve pain, psychological pain-related variables and disability in patients with chronic neck pain. The most frequently used components were addressing physical and psychological symptoms and engaging in self-care strategies. Future trials should focus on including other components, such as discussing symptoms with providers of medical care or self-monitoring symptoms. Additional areas of focus include more homogeneous doses and comparator treatments, as well as studies with better evidence to reach more solid conclusions.
Evaluating the Benefits of Flood Warnings in the Management of an Urban Flood-Prone Polder Area
Authors: Duque Felipe , O’Donnell Greg , Liu Yanli , Song Mingming , O’Connell Enda
Published: December 2023

Polders are low-lying areas located in deltas, surrounded by embankments to prevent flooding (river or tidal floods). They rely on pumping systems to remove water from the inner rivers (artificial rivers inside the polder area) to the outer rivers, especially during storms. Urbanized polders are especially vulnerable to pluvial flooding if the drainage, storage, and pumping capacity of the polder is inadequate. In this paper, a Monte Carlo (MC) framework is proposed to evaluate the benefits of rainfall threshold-based flood warnings when mitigating pluvial flooding in an urban flood-prone polder area based on 24 h forecasts. The framework computes metrics that give the potential waterlogging duration, maximum inundated area, and pump operation costs by considering the full range of potential storms. The benefits of flood warnings are evaluated by comparing the values of these metrics across different scenarios: the no-warning, perfect, deterministic, and probabilistic forecast scenarios. Probabilistic forecasts are represented using the concept of “predictive uncertainty” (PU). A polder area located in Nanjing was chosen for the case study. The results show a trade-off between the metrics that represent the waterlogging and the pumping costs, and that probabilistic forecasts of rainfall can considerably enhance these metrics. The results can be used to design a rainfall threshold-based flood early warning system (FEWS) for a polder area and/or evaluate its benefits.