bluuebunny/crossref_metadata_2025 huggingface dataset:
Unbalanced Expression of Structural Genes in Carotenoid Pathway Contributes to the Flower Color Formation of the Osmanthus Cultivar ‘Yanzhi Hong’
Authors: Zhang Min , Chai Zi-Han , Zhang Cheng , Chen Lin
Published: September 2024

Carotenoids are important natural pigments that are responsible for the fruit and flower colors of many plants. The composition and content of carotenoid can greatly influence the color phenotype of plants. However, the regulatory mechanism underling the divergent behaviors of carotenoid accumulation, especially in flower, remains unclear. In this study, a new cultivar Osmanthus fragrans ‘Yanzhi Hong’ was used to study the regulation of carotenoid pigmentation in flower. Liquid chromatograph–mass spectrometer (LC-MS) analysis showed that β-carotene, phytoene, lycopene, γ-carotene, and lutein were the top five pigments enriched in the petals of ‘Yanzhi Hong’. Through transcriptome analysis, we found that the expression of the structural genes in carotenoid pathway was imbalanced: most of the structural genes responsible for lycopene biosynthesis were highly expressed throughout the flower developmental stages, while those for lycopene metabolism kept at a relatively lower level. The downregulation of LYCE, especially at the late developmental stages, suppressed the conversion from lycopene to α-carotene but promoted the accumulation of β-carotene, which had great effect on the carotenoid composition of ‘Yanzhi Hong’. Ethylene response factor (ERF), WRKY, basic helix-loop-helix (bHLH), v-myb avian myeloblastosis viral oncogene homolog (MYB), N-Acetylcysteine (NAC), auxin response factor (ARF), and other transcription factors (TFs) have participated in the flower color regulation of ‘Yanzhi Hong’, which formed co-expression networks with the structural genes and functioned in multiple links of the carotenoid pathway. The results suggested that the cyclization of lycopene is a key link in determining flower color. The modification of the related TFs will break the expression balance between the upstream and downstream genes and greatly influence the carotenoid profile in flowers, which can be further used for creating colorful plant germplasms.
Downregulation of TASK-3 Channel Induces Senescence in Granulosa Cells of Bovine Cystic Ovarian Follicles
Authors: Kim Chang-Woon , Kim Eun-Jin , Woo Min Seok , Cao Dang Long , Cirunduzi Asifiwe Clarisse , Ryu Ji Hyeon , Kong Il-Keun , Lee Dong Kun , Hong Seong-Geun , Han Jaehee , Kang Dawon
Published: September 2024

Ovarian cysts are linked to hormone imbalances and altered gene expressions, but the connection between cysts and ion channel expression is understudied. This study explored the role of TWIK-related acid-sensitive K+ (TASK) channels in bovine ovarian cyst formation. The ovarian follicles were split into small (5 to 10 mm in diameter) and large (>25 mm in diameter) groups. Among the measured K+, Na+, and Cl− concentrations in follicular fluid (FF) obtained from small-sized follicles (SFs) and large-sized follicles (LFs), the K+ concentration was significantly lower in LFFF. Quantitative PCR, Western blot, and immunocytochemistry data revealed that TASK-3 expression levels significantly decreased by approximately 50% in LFs and granulosa cells obtained from LFs (LFGCs) compared to the corresponding controls. The TASK-3 protein was localized to the plasma membranes of GCs. The diameters of LFGCs were larger than those of SFGCs. The cell swelling response to exposure to a hypotonic solution (200 mOsm/L) was highly reduced in TASK-3-overexpressing cells compared to vector-transfected cells. TASK-3-knockdown cells showed arrested growth. Senescence markers were detected in LFGCs and TASK-3-knockdown cells. These findings suggest that reduced TASK-3 expression in LFs is associated with the inhibition of GC growth, leading to senescence and cyst formation.
Role of Gut Microbial Metabolites in Cardiovascular Diseases—Current Insights and the Road Ahead
Authors: Datta Sayantap , Pasham Sindhura , Inavolu Sriram , Boini Krishna M. , Koka Saisudha
Published: September 2024

Cardiovascular diseases (CVDs) are the leading cause of premature morbidity and mortality globally. The identification of novel risk factors contributing to CVD onset and progression has enabled an improved understanding of CVD pathophysiology. In addition to the conventional risk factors like high blood pressure, diabetes, obesity and smoking, the role of gut microbiome and intestinal microbe-derived metabolites in maintaining cardiovascular health has gained recent attention in the field of CVD pathophysiology. The human gastrointestinal tract caters to a highly diverse spectrum of microbes recognized as the gut microbiota, which are central to several physiologically significant cascades such as metabolism, nutrient absorption, and energy balance. The manipulation of the gut microbial subtleties potentially contributes to CVD, inflammation, neurodegeneration, obesity, and diabetic onset. The existing paradigm of studies suggests that the disruption of the gut microbial dynamics contributes towards CVD incidence. However, the exact mechanistic understanding of such a correlation from a signaling perspective remains elusive. This review has focused upon an in-depth characterization of gut microbial metabolites and their role in varied pathophysiological conditions, and highlights the potential molecular and signaling mechanisms governing the gut microbial metabolites in CVDs. In addition, it summarizes the existing courses of therapy in modulating the gut microbiome and its metabolites, limitations and scientific gaps in our current understanding, as well as future directions of studies involving the modulation of the gut microbiome and its metabolites, which can be undertaken to develop CVD-associated treatment options. Clarity in the understanding of the molecular interaction(s) and associations governing the gut microbiome and CVD shall potentially enable the development of novel druggable targets to ameliorate CVD in the years to come.
Insights into the Detoxification of Spruce Monoterpenes by the Eurasian Spruce Bark Beetle
Authors: Naseer Aisha , Singh Vivek Vikram , Sellamuthu Gothandapani , Synek Jiří , Mogilicherla Kanakachari , Kokoska Ladislav , Roy Amit
Published: September 2024

Plant defence mechanisms, including physical barriers like toughened bark and chemical defences like allelochemicals, are essential for protecting them against pests. Trees allocate non-structural carbohydrates (NSCs) to produce secondary metabolites like monoterpenes, which increase during biotic stress to fend off pests like the Eurasian spruce bark beetle, ESBB (Ips typographus). Despite these defences, the ESBB infests Norway spruce, causing significant ecological damage by exploiting weakened trees and using pheromones for aggregation. However, the mechanism of sensing and resistance towards host allelochemicals in ESBB is poorly understood. We hypothesised that the exposure of ESBB to spruce allelochemicals, especially monoterpenes, leads to an upsurge in the important detoxification genes like P450s, GSTs, UGTs, and transporters, and at the same time, genes responsible for development must be compromised. The current study demonstrates that exposure to monoterpenes like R-limonene and sabiene effectively elevated detoxification enzyme activities. The differential gene expression (DGE) analysis revealed 294 differentially expressed (DE) detoxification genes in response to R-limonene and 426 DE detoxification genes in response to sabiene treatments, with 209 common genes between the treatments. Amongst these, genes from the cytochrome P450 family 4 and 6 genes (CP4 and CP6), esterases, glutathione S-transferases family 1 (GSTT1), UDP-glucuronosyltransferase 2B genes (UDB), and glucose synthesis-related dehydrogenases were highly upregulated. We further validated 19 genes using RT-qPCR. Additionally, we observed similar high expression levels of detoxification genes across different monoterpene treatments, including myrcene and α-pinene, suggesting a conserved detoxification mechanism in ESBB, which demands further investigation. These findings highlight the potential for molecular target-based beetle management strategies targeting these key detoxification genes.
Bioavailability as Proof to Authorize the Clinical Testing of Neurodegenerative Drugs—Protocols and Advice for the FDA to Meet the ALS Act Vision
Authors: Niazi Sarfaraz K.
Published: September 2024

Although decades of intensive drug discovery efforts to treat neurodegenerative disorders (NDs) have failed, around half a million patients in more than 2000 studies continue being tested, costing over USD 100 billion, despite the conclusion that even those drugs which have been approved have no better effect than a placebo. The US Food and Drug Administration (FDA) has established multiple programs to innovate the treatment of rare diseases, particularly NDs, providing millions of USD in funding primarily by encouraging novel clinical trials to account for issues related to study sizes and adopting multi-arm studies to account for patient dropouts. Instead, the FDA should focus on the primary reason for failure: the poor bioavailability of drugs reaching the brain (generally 0.1% at most) due to the blood–brain barrier (BBB). There are several solutions to enhance entry into the brain, and the FDA must require proof of significant entry into the brain as the prerequisite to approving Investigational New Drug (IND) applications. The FDA should also rely on factors other than biomarkers to confirm efficacy, as these are rarely relevant to clinical use. This study summarizes how the drugs used to treat NDs can be made effective and how the FDA should change its guidelines for IND approval of these drugs.
A Path towards SDGs: Investigation of the Challenges in Adopting 3D Concrete Printing in India
Authors: Shivendra Bandoorvaragerahalli Thammannagowda , Shahaji  , Sharath Chandra Sathvik , Singh Atul Kumar , Kumar Rakesh , Kumar Nitin , Tantri Adithya , Naganna Sujay Raghavendra
Published: September 2024

In recent years, three dimensional concrete printing (3DCP) has gained traction as a promising technology to mitigate the carbon footprint associated with construction industry. However, despite its environmental benefits, studies frequently overlook its impact on social sustainability and its overall influence on project success. This research investigates how strategic decisions by firms shape the tradeoffs between economic, environmental, and social sustainability in the context of 3DCP adoption. Through interviews with 20 Indian industry leaders, it was found that companies primarily invest in 3DCP for automation and skilled workforce development, rather than solely for environmental reasons. The lack of incentives for sustainable practices in government procurement regulations emerges as a significant barrier to the widespread adoption of 3DCP. Our study identifies five key strategies firms employ to promote sustainability through 3DCP and proposes actionable measures for government intervention to stimulate its advancement. Addressing these issues is crucial for realizing the full societal and environmental benefits of 3DCP technology.
Novel Tricarbonylrhenium-Anthrapyrazole Complexes with DNA-Binding and Antitumor Properties: In Vitro and In Vivo Pharmacokinetic Studies with 99mTc-Analogue
Authors: Paparidis Georgios , Akrivou Melpomeni , Psomas George , Vizirianakis Ioannis S. , Hatzidimitriou Antonios , Gabriel Catherine , Sarigiannis Dimosthenis , Papagiannopoulou Dionysia
Published: September 2024

Organometallic complexes of fac-tricarbonylrhenium have been shown to exhibit anticancer properties. Anthrapyrazole anticancer agents act as DNA intercalators and topoisomerase IIα inhibitors, leading to double-strand breaks (DBS) and cell cycle arrest. This work involves the synthesis and biological evaluation of novel fac-tricarbonyl-rhenium complexes with anthrapyrazole derivatives. The anthrapyrazole moiety was synthesized from 1,8-dihydroxyanthraquinone, and three ligands L1, L2 and L3 were prepared. Ligand L1 coordinates via the phenolic O and pyrazole N as bidentate chelator forming the fac-[Re(CO)3(κ2-N,O)(MeOH)]-type complex, ReL1. Ligand L2 contains a pendant picolylamine N,N′-chelating system, forming the bidentate fac-[Re(CO)3(κ2-N,N′)Br]-type complex, ReL2. Ligand L3 contains a pendant picolylaminomonoacetic acid chelating system, forming a tridentate fac-[Re(CO)3(κ3-N,N′,O)]-type complex, ReL3. Complex ReL4 contains a picolylamine chelator, forming a complex with structure fac-[Re(CO)3(κ2-N,N′)Br], which was synthesized as a model for ReL2, and its coordination mode was resolved by X-ray crystallography. The complexes were characterized spectroscopically, and their biological properties were evaluated in vitro, in terms of DNA binding as well as for the cytotoxicity against CT-26 tumor cell line. Tumor cell cytotoxicity was high for ligand L2 and complex ReL2, exhibiting IC50 values of 0.36 and 0.64 μΜ, respectively. The most promising complex ReL2 was evaluated further by the preparation of its congener γ-emitting technetium-99m radio-complex, 99mTcL2. The in vitro uptake in CT26 tumor cells and the in vivo uptake in CT26 tumor-bearing mice of 99mTcL2 was determined, and its pharmacokinetic profile was established. These data indicate that the 99mTc complex has suitable properties to enter tumor cells in vitro and in vivo, and therefore ReL2 is promising for further evaluation.
An Investigation of Lanthanum Recovery from an Aqueous Solution by Adsorption (Ion Exchange)
Authors: Chan Michael , Doan Huu , Dang-Vu Trong
Published: September 2024

Lanthanum (La(III)) is one of the high-demand rare earth elements with applications in various products. However, La(III) in mining waste streams and electronic waste also poses environmental and health concerns. Therefore, the recovery of La(III) in the waste is needed. In the present study, the adsorption of La(III) with Dowex 50W-X8, Amberchrom50WX4, Amberlyst 15, and Amberchrom 50WX2 was evaluated using a shaker water bath. Dowex 50W-X8 was found to be the best adsorbent and was used to investigate the effect of the shaker speed (RPM = 50–150), adsorbent dosage (1.0–4.0 g), pH (2.0–7.0), and temperature (20–40 °C) on adsorption. La(III) adsorption was found to increase with the shaker speed, as expected. On the other hand, the adsorption capacity decreased with the adsorbent amount. Also, the highest La(III) adsorption was observed at pH = 6.0. La(III) percentage removal did not vary significantly with a temperature from 20 °C to 40 °C. However, the first-order kinetic rate constant decreased moderately with increases in temperature. The adsorption of La(III) by Dowex 50-X8 followed the Freundlich isotherm model better than the Langmuir model. In addition, the adsorption kinetics were represented well by the pseudo-first-order kinetic model. Moreover, enthalpy and Gibbs free energy changes were found to be negative, indicating an exothermic and thermodynamically favorable adsorption process.
Design and Deployment of a Floating Porous Screen Breakwater in a Mesotidal Environment
Authors: Lieberthal Brandon , Perry Richard , Younce Elisabeth , Hanley Liam , Bryant Mary , Huguenard Kimberly
Published: September 2024

The performance of an intermediate-scale modular, permeable, floating breakwater comprised of an array of vertical screens is optimized and tested. A distinctive attribute of this breakwater design is its adaptive capacity to fluctuating water levels owing to its floating configuration, thereby preserving its efficacy during high tide and storm tide scenarios—an advancement over conventional bottom-mounted structures. The initial validation of the concept was tested in a laboratory wave basin in regular waves, which demonstrated promising results for three porous panels. Next, the breakwater’s design parameters were optimized using a finite difference computational fluid dynamics software, (FLOW-3D version 2023R2), considering porosity, spacing, and panel count. A scaled prototype, representative of a 1:2 ratio was then deployed during the summer of 2022 along the coast of Castine, ME, within a mesotidal, semi-sheltered system characterized by tidal currents and waves. Notably, the breakwater succeeded in attenuating half of the wave energy for periods shorter than 4 s, evidenced by transmission coefficients below 0.5, making this technology suitable for locally generated waves with shorter periods. During storm events, instantaneous transmission coefficients decreased to as low as 0.25, coinciding with significant wave heights exceeding 0.8 m. Additionally, the efficacy of wave attenuation improved slightly over time as biofoulants adhered to the structure, thereby enhancing drag and mass.
Correction: Jung et al. Heat Integration of Liquid Hydrogen-Fueled Hybrid Electric Ship Propulsion System. J. Mar. Sci. Eng. 2023, 11, 2157
Authors: Jung Wongwan , Lee Jinkwang , Chang Daejun
Published: September 2024

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Unveiling the Hidden Links: Anatomical and Radiological Insights into Primary Hip Osteoarthritis
Authors: Tiburzi Valerio , Ciccullo Carlo , Farinelli Luca , Di Carlo Marco , Salaffi Fausto , Bandinelli Francesca , Gigante Antonio Pompilio
Published: September 2024

Background: Hip osteoarthritis (HOA) is a disease with globally rising incidence that leads to disability and morbidity, overall, in older populations, and might be primary or secondary to numerous risk factors. The most common idiopathic HOA is generally a diagnosis of exclusion, with pathogenetic mechanisms largely still misunderstood. We aimed to investigate the correlation between femoral–acetabular and spinopelvic anatomical and computed tomography (CT) characteristics, and the presence of primary OA. Methods: We retrospectively analyzed CT scans from 2019 to 2021, excluding patients under 45 years or with conditions affecting the pelvis, sacrum, or lower limbs. Femoral, acetabular, and spinopelvic parameters were measured; signs of OA were analyzed in the hip and knee joints. Patients were categorized into two groups: A (isolated hip OA) and B (no OA); patients with hip OA, also presenting knee OA, were excluded from this study. Results: In total, 232 cases were examined; statistical analyses compared CT parameters between 129 subjects from Group A and 103 patients of Group B. Group A showed a mean femoral version of 16 ± 4.53 degrees, significantly higher than Group B’s 13.16 ± 4.37 degrees (p = 0.0001). Other parameters showed no significant differences. Conclusion: This study highlights an association between femoral version and primary hip OA.
Monobloc vs. Modular Radial-Head Arthroplasty for Complex Elbow Trauma: Long-Term Follow-Up and Comparative Evaluation
Authors: Factor Shai , Gurel Ron , Tordjman Daniel , Eisenberg Gilad , Pritsch Tamir , Rosenblatt Yishai
Published: September 2024

Introduction: Mason Type 3 radial-head fractures are typically treated with open reduction and internal fixation (ORIF) or radial-head arthroplasty (RHA). Prosthetic options include traditional monobloc implants and newer modular implants designed to match patient anatomy. While short- and medium-term outcomes of metallic RHA are generally favorable, this study aims to compare the long-term outcomes of patients treated with monobloc versus modular implants. Methods: The medical records of all the patients who underwent RHA at a level I trauma center between 2000 and 2011 were retrospectively reviewed. Patients who were available for follow-up were invited for reassessment, which included physical examination, questionnaires for the assessment of elbow pain and function, and follow-up radiographs. Results: Out of 35 patients who had RHA, 13 (37%) had a monobloc prosthesis and 22 (63%) had a modular prosthesis. Out of the patients that could be traced, 4 patients from the monobloc group and 10 patients from the modular group agreed to participate in the study. The mean follow-up time was 15 years in the monobloc group and 12.4 years in the modular group. Patients in the modular group demonstrated superior functional outcomes compared to the monobloc group, with statistically significant improvements in MEPS and DASH scores and a non-significant trend towards better ASES scores and VAS scores. Physical examination revealed a decline in function in the operated arm for both groups, with statistically significant differences favoring the modular group in elbow flexion and extension. Radiographic analysis showed varying degrees of implant loosening, with the modular group exhibiting less loosening compared to the monobloc group. Mild degenerative changes and heterotopic ossification were also observed, predominantly in the modular group. Conclusions: The results suggest that modular implants offer superior functional outcomes compared to monobloc implants. The modular group showed statistically significant improvements in elbow flexion and extension. These findings indicate that modular implants may be a more favorable option for enhancing patient outcomes. Further research with larger sample sizes is recommended to confirm these trends and to better understand the long-term benefits of modular implants.
Heritage Value Assessment and Landscape Preservation of Traditional Chinese Villages Based on the Daily Lives of Local Residents: A Study of Tangfang Village in China and the UNESCO HUL Approach
Authors: Li Junjun , Wang Jin , Li Xun
Published: September 2024

Traditional Chinese villages, recognized as national heritage sites, are invaluable cultural assets. Since 2012, efforts have focused on their preservation, though issues remain such as prioritizing authenticity over usability and material over cultural elements. This paper adopts the Historic Urban Landscape (HUL) approach, emphasizing the integration of physical heritage with daily life to shift value assessment. The fundamental argument of this paper is that the HUL method can serve as a new tool for preserving the historical heritage and landscape of rural areas, particularly in the context of assessing and formulating preservation frameworks for traditional Chinese villages. Through the case study of Tangfang village’s new conservation plan, the research demonstrates that the value of traditional villages lies in the continuous interaction between daily activities and physical space, including landscape, functional, and spiritual dimensions. The study concludes that a preservation framework based on local residents’ daily lives ensures more effective heritage conservation and landscape preservation by addressing both material and human values.
Evolution of Resilience Spatiotemporal Patterns and Spatial Correlation Networks in African Regional Economies
Authors: Jiang Daliang , Zhu Wanyi , Zhang Zhenke
Published: September 2024

This paper comprehensively utilizes the entropy-TOPSIS method, Lyapunov index, and kernel density estimation to measure the spatiotemporal evolution characteristics of regional economic resilience in 52 African countries (regions) from 2008 to 2019. It also examines the spatial network characteristics of regional economic resilience in each country (region) through gravity models and social network analysis. The findings reveal that: (1) Although the resilience of African regional economies fluctuates, it generally shows an improving trend. Traditional economic powers and regional giants such as Libya, Nigeria, South Africa, Egypt, Morocco, and Tunisia demonstrate outstanding performance in economic resilience. (2) In terms of scale resilience, the countries along the North African Mediterranean coast exhibit particularly prominent advantages. However, the overall performance of Africa in fiscal resilience and openness resilience tends to be weak. Industrial resilience is influenced by colonial legacies and tends to stabilize. (3) The differences in economic resilience values and the fluctuation trajectories of economic resilience levels converge. North African economies exhibit resilience far higher than the mean and other regions, while East, West, and Central Africa consistently perform below the mean in the long term. Southern Africa’s gap from the mean is relatively small, leading to a stalemate. The fluctuation amplitude of differences within each region varies. (4) The overall level of resilience in African regional economies has steadily improved, displaying a trend of polarization. There is evident spatial polarization in West Africa, with Southern Africa demonstrating a trend of multipolarity transitioning towards bipolarity. Conversely, North Africa strengthens its features of bipolar differentiation, while East and Central Africa exhibit tendencies towards multipolarity. (5) Despite some fluctuations in the spatial network of regional economic resilience around 2016, connections among African countries have become increasingly tight, gradually forming three major spatial correlation network clusters: the North African Mediterranean coast, the West–Central African Pan-Gulf of Guinea region, and the East–South African Rift Valley region. Nigeria holds a prominent position as a regional core. Zambia, Cameroon, and the Central African Republic have played certain regional core roles at different times. Nigeria and South Africa also demonstrate significant intermediary roles, while Zambia, Cameroon, and Burkina Faso act as bridges in different periods of network connections. Based on the characteristics of spatial correlation networks, African regions gradually form four major cohesive subgroups and eight sub-subgroups.
Assessing Land-Cover Change Trends, Patterns, and Transitions in Coalfield Counties of Eastern Kentucky, USA
Authors: K C Suraj , Gyawali Buddhi R. , Lucas Shawn , Antonious George F. , Chiluwal Anuj , Zourarakis Demetrio
Published: September 2024

Surface coal mining and reclamation have greatly reshaped eastern Kentucky’s landscape affecting its socioeconomic, environmental and climatic aspects. This study examined the land-cover changes, trends and patterns in Floyd, Knott, Letcher, Magoffin, Martin, Perry, and Pike counties from 2004 to 2019. Using a random forest classifier, land cover was categorized into seven major classes, i.e., water, barren land, developed land, forest, shrubland, herbaceous, and planted/cultivated, majorly based on Landsat images. The Kappa accuracy ranged from 75 to 89%. The results showed a notable increase in forest area from 5052 sq km to 5305 sq km accompanied by a substantial decrease in barren land from 179 sq km to 91 sq km from 2004 to 2019. These findings demonstrated that reclamation activities positively impacted the forest expansion and reduced the barren land of the study area. Key land-cover transitions included barren land to shrubland/herbaceous, forest to shrubland, and shrubland to forest, indicating vegetation growth from 2004 to 2019. An autocorrelation analysis indicated similar land-cover types clustered together, showing effective forest restoration efforts. As surface coal mining and reclamation significantly influenced the landscapes of the coalfield counties in eastern Kentucky, this study provides a holistic perspective for understanding the repercussions of these transformations, including their effects on humans, society, and environmental health.
Spatiotemporal Variation and Prediction of Carbon Storage in Terrestrial Ecosystems at Multiple Development Stages in Beijing City Based on the Plus and Integrated Valuation of Ecosystem Services and Tradeoffs Models
Authors: Wang Peian , Liu Chen , Dai Linlin
Published: September 2024

Terrestrial ecosystems play a critical role in the global carbon cycle, and their carbon sequestration capacity is vital for mitigating the impacts of climate change. Changes in land use and land cover (LULC) dynamics significantly alter this capacity. This study scrutinizes the LULC evolution within the Beijing metropolitan region from 1992 to 2022, evaluating its implications for ecosystem carbon storage. It also employs the Patch-Generating Land Use Simulation (PLUS) model to simulate LULC patterns under four scenarios for 2035: an Uncontrolled Scenario (UCS), a Natural Evolution Scenario (NES), a Strict Control Scenario (SCS), and a Reforestation and Wetland Expansion Scenario (RWES). The InVEST model is concurrently used to assess and forecast ecosystem carbon storage under each scenario. Key insights from the study are as follows: (1) from 1992 to 2022, Beijing’s LULC exhibited a phased developmental trajectory, marked by an expansion of urban and forested areas at the expense of agricultural land; (2) concurrently, the region’s ecosystem carbon storage displayed a fluctuating trend, peaking initially before declining, with higher storage in the northwest and lower in the central urban zones; (3) by 2035, ecosystem carbon storage is projected to decrease by 1.41 Megatons under the UCS, decrease by 0.097 Megatons under the NES, increase by 1.70 Megatons under the SCS, and increase by 11.97 Megatons under the RWES; and (4) the study underscores the efficacy of policies curtailing construction land expansion in Beijing, advocating for sustained urban growth constraints and intensified afforestation initiatives. This research reveals significant changes in urban land use types and the mechanisms propelling these shifts, offering a scientific basis for comprehending LULC transformations in Beijing and their ramifications for ecosystem carbon storage. It further provides policymakers with substantial insights for the development of strategic environmental and urban planning initiatives.
German Noun Plurals in Simultaneous Bilingual vs. Successive Bilingual vs. Monolingual Kindergarten Children: The Role of Linguistic and Extralinguistic Variables
Authors: Korecky-Kröll Katharina , Camber Marina , Uzunkaya-Sharma Kumru , Dressler Wolfgang U.
Published: September 2024

(1) Background: The complex phenomenon of German noun plural inflection is investigated in three groups of German-speaking kindergarten children: (a) monolinguals (1L1), (b) simultaneous bilinguals (2L1) also acquiring Croatian, and (c) successive bilinguals (L2) acquiring Turkish as L1. Predictions of the usage-based schema model and of Natural Morphology concerning different linguistic variables are used to explore their impact on plural acquisition in the three groups of children. (2) Methods: A longitudinal study (from mean age 3;1 to 4;8) is conducted using two procedures (a formal plural test and spontaneous recordings in kindergarten), and the data are analyzed using generalized linear (mixed-effects) regression models in R. (3) Results: All children produce more errors in the metalinguistically challenging test compared to spontaneous speech, with L2 children being particularly disadvantaged. Socioeconomic status (henceforth SES) and teachers’ plural type frequency are most relevant for 1L1 children, and kindergarten exposure is more relevant for L2 children, while the linguistic variables are more important for 2L1 children. (4) Conclusions: The main predictions of the schema model and of Natural Morphology are largely confirmed. All of the linguistic variables investigated show significant effects in some analyses, but morphotactic transparency turns out to be the most relevant variable for all three groups of children.
Magnesium Sulfate, Rosuvastatin, Sildenafil and Their Combination in Chronic Hypoxia-Induced Pulmonary Hypertension in Male Rats
Authors: Hojda Silvana-Elena , Chis Irina Camelia , Clichici Simona
Published: September 2024

Previous experimental findings have led to considerable interest in the beneficial effects on pulmonary hypertension (PH) produced by sildenafil and in the pleiotropic effects of rosuvastatin and their positive role in the process of pulmonary angiogenesis. However, magnesium sulfate, the most abundant intracellular cation, is essential in vascular endothelial functionality due to its anti-inflammatory and vasodilatory effects. Therefore, the present study aims to assess these treatment regimens and how they could potentially provide some additional benefits in PH therapy. Fourteen days after chronic-hypoxia PH was induced, rosuvastatin, sildenafil and magnesium sulfate were administered for an additional fourteen days to male Wistar rats. The Fulton Index, right ventricle (RV) anterior wall thickness, RV internal diameter and pulmonary arterial (PA) acceleration time/ejection time were evaluated, and another four biochemical parameters were calculated: brain natriuretic peptide, vascular endothelial growth factor, nitric oxide metabolites and endothelin 1. The present study demonstrates that sildenafil and rosuvastatin have modest effects in reducing RV hypertrophy and RV systolic pressure. The drug combination of sildenafil + rosuvastatin + magnesium sulfate recorded statistically very highly significant results on all parameters; through their positive synergistic effects on vascular endothelial function, oxidative stress and pathological RV remodeling, they attenuated PH in the chronic hypoxia pulmonary hypertension (CHPH) rat model.
Tracing In-Hospital COVID-19 Outcomes: A Multistate Model Exploration (TRACE)
Authors: Mohammadi Hamed , Marateb Hamid Reza , Momenzadeh Mohammadreza , Wolkewitz Martin , Rubio-Rivas Manuel
Published: September 2024

This study aims to develop and apply multistate models to estimate, forecast, and manage hospital length of stay during the COVID-19 epidemic without using any external packages. Data from Bellvitge University Hospital in Barcelona, Spain, were analyzed, involving 2285 hospitalized COVID-19 patients with moderate to severe conditions. The implemented multistate model includes transition probabilities and risk rates calculated from transitions between defined states, such as admission, ICU transfer, discharge, and death. In addition to examining key factors like age and gender, diabetes, lymphocyte count, comorbidity burden, symptom duration, and different COVID-19 waves were analyzed. Based on the model, patients hospitalized stay an average of 11.90 days before discharge, 2.84 days before moving to the ICU, or 34.21 days before death. ICU patients remain for about 24.08 days, with subsequent stays of 124.30 days before discharge and 35.44 days before death. These results highlight hospital stays’ varying durations and trajectories, providing critical insights into patient flow and healthcare resource utilization. Additionally, it can predict ICU peak loads for specific subgroups, aiding in preparedness. Future work will integrate the developed code into the hospital’s Health Information System (HIS) following ISO 13606 EHR standards and implement recursive methods to enhance the model’s efficiency and accuracy.
Biomarkers and Data Visualization of Insulin Resistance and Metabolic Syndrome: An Applicable Approach
Authors: Sotiropoulos Christos , Giormezis Nikolaos , Pertsas Vayianos , Tsirkas Theodoros
Published: September 2024

Type 2 diabetes, prediabetes, and insulin resistance (IR) are widespread yet often undetected in their early stages, contributing to a silent epidemic. Metabolic Syndrome (MetS) is also highly prevalent, increasing the chronic disease burden. Annual check-ups are inadequate for early detection due to conventional result formats that lack specific markers and comprehensive visualization. The aim of this study was to evaluate low-budget biochemical and hematological parameters, with data visualization, for identifying IR and MetS in a community-based laboratory. In a cross-sectional study with 1870 participants in Patras, Greece, blood samples were analyzed for key cardiovascular and inflammatory markers. IR diagnostic markers (TyG-Index, TyG-BMI, Triglycerides/HDL ratio, NLR) were compared with HOMA-IR. Innovative data visualization techniques were used to present metabolic profiles. Notable differences in parameters of cardiovascular risk and inflammation were observed between normal-weight and obese people, highlighting BMI as a significant risk factor. Also, the inflammation marker NHR (Neutrophils to HDL-Cholesterol Ratio) Index was successful at distinguishing the obese individuals and those with MetS from normal individuals. Additionally, a new diagnostic index of IR, combining BMI (Body Mass Index) and NHR Index, demonstrated better performance than other well-known indices. Lastly, data visualization significantly helped individuals understand their metabolic health patterns more clearly. BMI and NHR Index could play an essential role in assessing metabolic health patterns. Integrating specific markers and data visualization in routine check-ups enhances the early detection of IR and MetS, aiding in better patient awareness and adherence.
How Can Promoting Skeletal Muscle Health and Exercise in Children and Adolescents Prevent Insulin Resistance and Type 2 Diabetes?
Authors: Calcaterra Valeria , Magenes Vittoria Carlotta , Bianchi Alice , Rossi Virginia , Gatti Alessandro , Marin Luca , Vandoni Matteo , Zuccotti Gianvincenzo
Published: September 2024

Skeletal muscle secretome, through its paracrine and endocrine functions, contributes to the maintenance and regulation of overall physiological health. We conducted a narrative review on the role of skeletal muscle and exercise in maintaining glucose homeostasis, driving insulin resistance (IR), and preventing type 2 diabetes in pediatric populations, especially in the context of overweight and obesity. Myokines such as interleukin (IL)-6, IL-8, and IL-15, as well as irisin, myonectin, and myostatin, appear to play a crucial role in IR. Skeletal muscle can also become a target of obesity-induced and IR-induced inflammation. In the correlation between muscle, IR, and inflammation, the role of infiltration of the immune cells and the microvasculature may also be considered. It remains unclear which exercise approach is the best; however, combining aerobic exercise with resistance training seems to be the most effective strategy for managing IR, with high-intensity activities offering superior metabolic benefits and long-term adherence. Encouraging daily participation in enjoyable and engaging exercise is key for long-term commitment and effective glucose metabolism management. Promoting physical activity in children and adolescents must be a top priority for public health, not only in terms of individual quality of life and well-being but also for community health.
TADocs: Teacher–Assistant Distillation for Improved Policy Transfer in 6G RAN Slicing
Authors: Mu Xian , Xu Yao , Li Dagang , Liu Mingzhu
Published: September 2024

Network slicing is an advanced technology that significantly enhances network flexibility and efficiency. Recently, reinforcement learning (RL) has been applied to solve resource management challenges in 6G networks. However, RL-based network slicing solutions have not been widely adopted. One of the primary reasons for this is the slow convergence of agents when the Service Level Agreement (SLA) weight parameters in Radio Access Network (RAN) slices change. Therefore, a solution is needed that can achieve rapid convergence while maintaining high accuracy. To address this, we propose a Teacher and Assistant Distillation method based on cosine similarity (TADocs). This method utilizes cosine similarity to precisely match the most suitable teacher and assistant models, enabling rapid policy transfer through policy distillation to adapt to the changing SLA weight parameters. The cosine similarity matching mechanism ensures that the student model learns from the appropriate teacher and assistant models, thereby maintaining high performance. Thanks to this efficient matching mechanism, the number of models that need to be maintained is greatly reduced, resulting in lower computational resource consumption. TADocs improves convergence speed by 81% while achieving an average accuracy of 98%.
Global–Local Query-Support Cross-Attention for Few-Shot Semantic Segmentation
Authors: Xie Fengxi , Liang Guozhen , Chien Ying-Ren
Published: September 2024

Few-shot semantic segmentation (FSS) models aim to segment unseen target objects in a query image with scarce annotated support samples. This challenging task requires an effective utilization of support information contained in the limited support set. However, the majority of existing FSS methods either compressed support features into several prototype vectors or constructed pixel-wise support-query correlations to guide the segmentation, which failed in effectively utilizing the support information from the global–local perspective. In this paper, we propose Global–Local Query-Support Cross-Attention (GLQSCA), where both global semantics and local details are exploited. Implemented with multi-head attention in a transformer architecture, GLQSCA treats every query pixel as a token, aggregates the segmentation label from the support mask values (weighted by the similarities with all foreground prototypes (global information)), and supports pixels (local information). Experiments show that our GLQSCA significantly surpasses state-of-the-art methods on the standard FSS benchmarks PASCAL-5i and COCO-20i.
Shift Pruning-Based SCL Decoding for Polar Codes
Authors: Wang Desheng , Yin Jihang , Xu Yonggang , Yang Xuan , Yan Jiaqi , Hua Gang
Published: September 2024

In the context of the high-speed development of 5G communications, high-performance decoding schemes for polar codes are a hot spot in channel coding research. Shift pruning successive cancellation list (SP-SCL) decoding aims to recover the correct path by shift pruning in the extra SCL decoding. However, the current SP-SCL decoding is inflexible in determining the shift positions. In this paper, a flexible shift pruning SCL (FSP-SCL) decoding is proposed. Firstly, the reasons for movement and the eliminated states of the correct path are analyzed in detail using the path metric range (PMR), and on this basis, the validity of the method adopted in this paper for determining the shift priority of the information bits is verified. Secondly, the FSP-SCL decoding proposes two methods for determining the shift positions. One is the log-likelihood ratio (LLR) threshold method, which compares the LLR values of the eliminated paths on the shift bit with the corresponding LLR threshold to determine the shift positions. The other is the path distance method. It combines the minimum distance between the eliminated paths and the received vector with the path metrics to determine the shift positions. Both methods are more flexible and practical, as they can calculate the corresponding shift positions online based on a specific shift bit, avoiding the high complexity caused by the simulation method. Finally, this paper designs various experimental schemes to verify the decoding performance of the FSP-SCL. The experimental results show that in terms of error-correction performance, the LLR threshold-based FSP-SCL (FSPL (LLR threshold)) decoding, the path distance-based FSP-SCL (FSPL (path distance)) decoding and the existing SP-SCL decoding are roughly equal overall. In terms of decoding complexity, FSPL (LLR threshold) decoding is slightly better than FSPL (path distance) decoding, and the decoding complexity of both is lower than that of SP-SCL decoding, with the difference being more pronounced in the medium to high SNR regions.
Reliability Analysis of (n, k)-Bubble-Sort Networks Based on Extra Conditional Fault
Authors: Zhao Lina , Wang Shiying , Dou Feng
Published: September 2024

Given a graph G=(V(G),V(E)), a non-negative integer g and a set of faulty vertices F⊆V(G), the g-extra connectivity of G, denoted by κg(G), is the smallest cardinality of F, whose value of deletion, if exists, will disconnect G and give each remaining component at least g+1 vertices. The g-extra diagnosability of the graph G, denoted by tg(G), is the maximum cardinality of the set F of fault vertices that the graph can guarantee to identify under the condition that each fault-free component has more than g vertices. In this paper, we determine that g-extra connectivity of (n,k)-bubble-sort network Bn,k is κg(Bn,k)=n+g(k−2)−1 for 4≤k≤n−1 and 0≤g≤n−k. Afterwards, we show that g-extra diagnosability of Bn,k under the PMC model (4≤k≤n−1 and 0≤g≤n−k) and MM* model (4≤k≤n−1 and 0≤g≤min{n−k−1,k−2}) is tg(Bn,k)=n+g(k−1)−1, respectively.
A Spacetime RBF-Based DNNs for Solving Unsaturated Flow Problems
Authors: Liu Chih-Yu , Ku Cheng-Yu , Chen Wei-Da
Published: September 2024

This study presents a novel approach for modeling unsaturated flow using deep neural networks (DNNs) integrated with spacetime radial basis functions (RBFs). Traditional methods for simulating unsaturated flow often face challenges in computational efficiency and accuracy, particularly when dealing with nonlinear soil properties and complex boundary conditions. Our proposed model emphasizes the capabilities of DNNs in identifying complex patterns and the accuracy of spacetime RBFs in modeling spatiotemporal data. The training data comprise the initial data, boundary data, and radial distances used to construct the spacetime RBFs. The innovation of this approach is that it introduces spacetime RBFs, eliminating the need to discretize the governing equation of unsaturated flow and directly providing the solution of unsaturated flow across the entire time and space domain. Various error evaluation metrics are thoroughly assessed to validate the proposed method. This study examines a case where, despite incomplete initial and boundary data and noise contamination in the available boundary data, the solution of unsaturated flow can still be accurately determined. The model achieves RMSE, MAE, and MRE values of 10−4, 10−3, and 10−4, respectively, demonstrating that the proposed method is robust for solving unsaturated flow in soils, providing insights beyond those obtainable with traditional methods.
Pre-Trained Language Model Ensemble for Arabic Fake News Detection
Authors: Al-Zahrani Lama , Al-Yahya Maha
Published: September 2024

Fake news detection (FND) remains a challenge due to its vast and varied sources, especially on social media platforms. While numerous attempts have been made by academia and the industry to develop fake news detection systems, research on Arabic content remains limited. This study investigates transformer-based language models for Arabic FND. While transformer-based models have shown promising performance in various natural language processing tasks, they often struggle with tasks involving complex linguistic patterns and cultural contexts, resulting in unreliable performance and misclassification problems. To overcome these challenges, we investigated an ensemble of transformer-based models. We experimented with five Arabic transformer models: AraBERT, MARBERT, AraELECTRA, AraGPT2, and ARBERT. Various ensemble approaches, including a weighted-average ensemble, hard voting, and soft voting, were evaluated to determine the most effective techniques for boosting learning models and improving prediction accuracies. The results of this study demonstrate the effectiveness of ensemble models in significantly boosting the baseline model performance. An important finding is that ensemble models achieved excellent performance on the Arabic Multisource Fake News Detection (AMFND) dataset, reaching an F1 score of 94% using weighted averages. Moreover, changing the number of models in the ensemble has a slight effect on the performance. These key findings contribute to the advancement of fake news detection in Arabic, offering valuable insights for both academia and the industry