bluuebunny/crossref_metadata_2025 huggingface dataset:
Growth Traits and Yield Performance of Japonica Hybrid Rice Bred by the New Strategy in the Yangtze River Region of China
Authors: Chen Yutiao , Song Jiayu , Hong Xiaofu , Zhang Huaijie , Hu Tiejun , Zhu Guanglong
Published: January 2025

Despite the successful breeding of hybrid japonica rice by the new strategy (the female parent with a restorer line containing an appropriate proportion of indica rice genes) in China, it remains unclear whether these cultivars exhibit a similar yield performance with the traditional high-yield hybrid cultivars in the Yangtze River region. Therefore, two field experiments were conducted in Fenghua City and Yuyao City, China, during the two growing seasons in 2019 and 2020. Six japonica hybrid rice cultivars and one control indica–japonica hybrid rice cultivar (Yongyou1540 [YY1540]) were chosen as the experimental materials in each year, and the seedling quality, grain yield, and yield components were evaluated. The results showed that the grain yield of YY1540 was 13.9 t ha−1 and 14.5 t ha−1 in 2019 and 2020, respectively, which was the highest among all cultivars in both years. However, the japonica hybrid rice cultivars CHY83 in 2019 and CHY112 in 2020 also achieved high yield performance with 13.7 t ha−1 and 14.0 t ha−1, respectively, which were not significantly difference from YY1540. The japonica hybrid cultivars with a high grain yield typically exhibited more spikelets per panicle, more spikelets per m2, and a higher harvest index than those with a lower grain yield. Increasing the total growth duration had a limited impact on the grain yield of japonica hybrid rice. However, the post-heading daily grain yield was significantly positively correlated with grain yield in japonica hybrid rice cultivars. Moreover, significant quadratic relationships were observed between plant height at maturity and grain yield and between seedling dry weight and grain yield. The optimal plant height at maturity and seedling dry weight for achieving a high grain yield in japonica hybrid rice were approximately 130 cm and 300 mg plant−1, respectively. This study provides useful information for breeding high-yield japonica hybrid cultivars.
UAV Remote Sensing Technology for Wheat Growth Monitoring in Precision Agriculture: Comparison of Data Quality and Growth Parameter Inversion
Authors: Liu Jikai , Wang Weiqiang , Li Jun , Mustafa Ghulam , Su Xiangxiang , Nian Ying , Ma Qiang , Zhen Fengxian , Wang Wenhui , Li Xinwei
Published: January 2025

The quality of the image data and the potential to invert crop growth parameters are essential for effectively using unmanned aerial vehicle (UAV)-based sensor systems in precision agriculture (PA). However, the existing research falls short in providing a comprehensive examination of sensor data quality and the inversion potential of crop growth parameters, and there is still ambiguity regarding how the quality of data affects the inversion potential. Therefore, this study explored the application potential of RGB and multispectral (MS) images acquired from three lightweight UAV platforms in the realm of PA: the DJI Mavic 2 Pro (M2P), Phantom 4 Multispectral (P4M), and Mavic 3 Multispectral (M3M). The reliability of pixel-scale data quality was evaluated based on image quality assessment metrics, and three winter wheat growth parameters, above-ground biomass (AGB), plant nitrogen content (PNC) and soil and plant analysis development (SPAD), were inverted using machine learning models based on multi-source image features at the plot scale. The results indicated that the RGB image quality from the M3M outperformed that of the M2P, while the MS image quality was marginally superior to that of the P4M. Nevertheless, these advantages in pixel-scale data quality did not improve inversion accuracy for crop parameters at the plot scale. Spectral features (SFs) derived from the P4M-based MS sensor demonstrated significant advantages in AGB inversion (R2 = 0.86, rRMSE = 27.47%), while SFs derived from the M2P-based RGB camera exhibited the best performance in SPAD inversion (R2 = 0.60, rRMSE = 7.67%). Additionally, combining spectral and textural features derived from the P4M-based MS sensor yielded the highest accuracy in PNC inversion (R2 = 0.82, rRMSE = 14.62%). This study clarified the data quality of three prevalent UAV mounted sensor systems in PA and their influence on parameter inversion potential, offering guidance for selecting appropriate sensors and monitoring key crop growth parameters.
Designing Channel Attention Fully Convolutional Networks with Neural Architecture Search for Customer Socio-Demographic Information Identification Using Smart Meter Data
Authors: Luo Zhirui , Li Qingqing , Qi Ruobin , Zheng Jun
Published: January 2025

Background: Accurately identifying the socio-demographic information of customers is crucial for utilities. It enables them to efficiently deliver personalized energy services and manage distribution networks. In recent years, machine learning-based data-driven methods have gained popularity compared to traditional survey-based approaches, owing to their time and cost efficiency, as well as the availability of a large amount of high-frequency smart meter data. Methods: In this paper, we propose a new method that harnesses the power of neural architecture search to automatically design deep neural network architectures tailored for identifying various socio-demographic information of customers using smart meter data. We designed a search space based on a novel channel attention fully convolutional network architecture. Furthermore, we developed a search algorithm based on Bayesian optimization to effectively explore the space and identify high-performing architectures. Results: The performance of the proposed method was evaluated and compared with a set of machine learning and deep learning baseline methods using a smart meter dataset widely used in this research area. Our results show that the deep neural network architectures designed automatically by our proposed method significantly outperform all baseline methods in addressing the socio-demographic questions investigated in our study.
Protease and Bacillus coagulans Supplementation in a Low-Protein Diet Improves Broiler Growth, Promotes Amino Acid Transport Gene Activity, Strengthens Intestinal Barriers, and Alters the Cecal Microbial Composition
Authors: Niu Junlong , Qiao Yingying , Yang Xiaopeng , Chen Xiaoshuang , Li Hongfei , Guo Yongpeng , Zhang Wei , Wang Zhixiang
Published: January 2025

Low-protein (LPRO) diets can effectively reduce feed costs and decrease environmental pollution, making them an important pathway to enhance the sustainability of livestock production. However, they may have adverse effects on the growth performance of broiler chickens, which has limited their widespread application. This study aims to explore the impact of adding protease (PRO) to LPRO diets on the growth performance of broiler chickens, especially under conditions with or without the presence of Bacillus coagulans (BC), in order to provide theoretical support for the scientific application and promotion of LPRO feeds. We selected 432 one-day-old broiler chickens and divided them into four treatment groups, which were fed with the control (CON) diet, the LPRO diet, the PRO diet (LPRO diet with added protease), and the PAB diet (PRO diet with added BC). The LPRO group demonstrated decreased growth performance while both PRO and PAB diets resulted in a significant increase (p < 0.05). Both PRO and PAB diets significantly enhanced the expression of amino acid transport genes and tight junction genes (p < 0.05) and optimized the composition of the intestinal microbiota. Overall, LPRO diets have a detrimental effect on the growth of broiler chickens, while the PRO and PAB diets effectively counteract these negative effects by improving protein digestion, amino acid absorption, and intestinal health.
Current Enzooticity of Dirofilaria immitis and Angiostrongylus vasorum in Central and Southern Italy
Authors: Traversa Donato , Morelli Simone , Di Cesare Angela , Astuti Chiara , Barlaam Alessandra , Colombo Mariasole , Veronesi Fabrizia , Paoletti Barbara , Iorio Raffaella , Maggi Raffaella , Passarelli Alessandra , Pede Alessia , Rossi Linda , Diaferia Manuela
Published: January 2025

Dirofilaria immitis and Angiostrongylus vasorum are major parasitic nematodes of dogs. Many environmental and phenological changes have recently modified their geographic patterns in many countries; thus, this study has updated the distribution of D. immitis and A. vasorum in dog populations of selected regions of Central and Southern Italy. Also, collateral data on other endoparasites affecting the study population have been collected. Blood and fecal samples collected from 2000 dogs were tested using Knott’s test and copromicroscopy (i.e., Baermann’s and fecal flotation tests), respectively. Binomial logistic regression was performed to evaluate statistically significant associations between positivity for D. immitis and/or A. vasorum and potential risk factors. Overall, 35 (1.7%) and 62 (3.1%) dogs were positive for microfilariae of D. immitis and first stage larvae (L1) of A. vasorum, respectively, while 3 (0.1%) were co-infected by both nematodes. Microfilariae of Dirofilaria repens were found in 148 (7.4%) dogs, while at the flotation, eggs of Ancylostomatidae, Trichuris vulpis, and ascarids were found in the feces of 323 (16.5%), 249 (12.4%), and 172 (8.6%), dogs, respectively. Overall, 217 (10.8%) and 44 (2.2%) dogs were positive for eggs of Capillaria aerophila and Capillaria boehmi. The presence of cardiorespiratory clinical signs or non-specific signs, history of travel, and an age of >4 years old were significantly associated with positivity for D. immitis, while A. vasorum was significantly recorded in dogs with cardiorespiratory signs, or with a history of mollusk ingestion or permanent outdoor housing. These results confirm that D. immitis is enzootic in the investigated regions of Central and Southern Italy, even where it was rare/undetected until recently. Indeed, although some dogs positive for D. immitis had a history of travel in enzootic areas, the majority of them were never moved, indicating that they acquired the parasite in the region where they live. Additionally, A. vasorum is stably enzootic in the study areas, as also are other extraintestinal nematodes (i.e., D. repens and C. aerophila) that are more frequently detected today than in the past. A high level of vigilance and routine parasitological screening are necessary, considering the high prevalence of intestinal parasites in owned dogs that are also co-infected by respiratory parasites. The implementation of chemoprevention against D. immitis in dogs living in the examined area should be encouraged.
Integrating Metabolomics and Genomics to Uncover the Impact of Fermented Total Mixed Ration on Heifer Growth Performance Through Host-Dependent Metabolic Pathways
Authors: Hu Zhenzhen , Zuo Minyu , Ding Shixuan , Zhong Yifan , Xue Mingyuan , Zheng Huichao
Published: January 2025

With the increasing demand for enhancing livestock production performance and optimizing feed efficiency, this study aimed to investigate the effects of fermented total mixed ration (FTMR) containing different proportions of rice straw and sheath and leaves of Zizania latifolia on systemic nutrient metabolism and oxidative metabolism under host genetic regulation and on growth performance of heifers. A total of 157 heifers aged 7–8 months were selected, and their hair was collected for whole-genome sequencing. They were randomly assigned into four groups of 18 to 21 cattle each and fed FTMR containing varying levels of rice straw (21% in LSF, 28% in MSF, 35% in HSF) or 31% sheath and leaves of Zizania latifolia (ZF) for a two-month period. At the end of trial, blood and urine samples were collected to measure biochemical indexes and metabolomics. The results showed that high rice straw content and ZF diets could increase blood glucose and non-protein nitrogen in heifers, that is, blood glucose and urea nitrogen levels in HSF and ZF groups were higher than those in LSF and MSF groups (p < 0.05). Meanwhile, the two diets could improve the antioxidant level of heifers. Urine metabolomics analysis between the groups identified three differential metabolic pathways, including 11 metabolites. Among them, l-homoserine and o-acetylserine had significant SNPs associated with them, which promoted glutathione metabolism. Although there was no significant effect of diet on heifers’ average daily gain (ADG) in body weight (p > 0.05), there was substantial inter-individual variation in metabolites among all animals, as further correlation analyses illustrated. Twenty-eight metabolites were significantly associated with ADG (R > 0.3, p < 0.05). Four of them were identified as biomarkers, primarily regulating energy metabolism and oxidative balance. In conclusion, feeding HSF and ZF FTMR enhances glutathione metabolism and antioxidant capacity in heifers, positioning key metabolites as candidates for ADG markers. This integrative omics approach underscores the potential for enhancing livestock productivity and promoting sustainable agricultural practices.
Towards a Digital Transformation Hyper-Framework: The Essential Design Principles and Components of the Initial Prototype
Authors: Perisic Ana , Perisic Branko
Published: January 2025

To cope with the complexity, the digital transformation of cyber-physical and socio-technology systems demands the utilization of heterogeneous tailorable development environments with dynamic configuring ability and transparent integration of independently developed dedicated frameworks. The essential design principles and component-based architecting of the initial prototype of the digital transformation hyper-framework represent this research target. These principles are derived from the broad scope analysis of digital transformation projects, methods, and tools and are glued to the proposed virtual twin hyper-document. The critical analysis of the digital transformation domain influenced the formulation of five research hypotheses that frame digital transformation of digital transformation, as the second goal of this research article. Armed with a meta-modeling layer, the incremental development of hybrid architecture instances focuses on meta-models and their transformations into functional, interpretable environments. The applicability aspects of the formulated hypothesis are verified throughout the architecture, meta-configuration, and handling of information resources as the essential segments of the initial version of the proposed evolution prototype. The detailed illustration of the horizontal and vertical interoperability of the proposed framework is illustrated by the Life Cycle Modeling component framework that creatively integrates the System, Software, and Operation Engineering aspects of the proposed hyper-framework. The proposed prototype capabilities are discussed in the context of the contemporary digital transformation ecosystem. Specification and development of the additional component frameworks, in compliance with specified generative mechanisms, directing further refinements of the proposed hyper-framework.
Weigh-in-Motion Method Based on Modular Sensor System and Axle Recognition with Neural Networks
Authors: Liu Xiaoyong , Yang Zhiyong , Shi Bowen
Published: January 2025

Weigh-in-motion systems can measure the number of axles to obtain a vehicle’s type and upper limit of weight, which, combined with the weight measured by the system, can be used for highway toll collection and overload management. This paper proposes a new modular system based on multi-sensor fusion and neural network axle recognition to address issues concerning the high failure rate of axle recognition devices and low weighing accuracy. We use a modular system consisting of multiple weighing platforms, enabling whole-vehicle-load weighing with multiple vehicles traveling through platforms. In addition, we propose a sequential generation model based on a Transformer and Gated Recurrent Unit to calculate the weighing signal generated by the weighing sensors, and then obtain the number of axles and the gross vehicle weight. Finally, the axle recognition algorithm and modular systems are tested in multiple scenarios. The accuracy of the axle recognition is 99.51% and 99.84% in the test set and the toll station, respectively. The weighing error of the modular system in the test field is less than 0.5%, and 99.18% of vehicles had an error of less than 5% at the toll station. The modular system has the advantages of high accuracy, consistent performance, and high traffic efficiency.
Improving Text Recognition Accuracy for Serbian Legal Documents Using BERT
Authors: Bogdanović Miloš , Frtunić Gligorijević Milena , Kocić Jelena , Stoimenov Leonid
Published: January 2025

Producing a new high-quality text corpus is a big challenge due to the required complexity and labor expenses. High-quality datasets, considered a prerequisite for many supervised machine learning algorithms, are often only available in very limited quantities. This in turn limits the capabilities of many advanced technologies when used in a specific field of research and development. This is also the case for the Serbian language, which is considered low-resourced in digitized language resources. In this paper, we address this issue for the Serbian language through a novel approach for generating high-quality text corpora by improving text recognition accuracy for scanned documents belonging to Serbian legal heritage. Our approach integrates three different components to provide high-quality results: a BERT-based large language model built specifically for Serbian legal texts, a high-quality open-source optical character recognition (OCR) model, and a word-level similarity measure for Serbian Cyrillic developed for this research and used for generating necessary correction suggestions. This approach was evaluated manually using scanned legal documents sampled from three different epochs between the years 1970 and 2002 with more than 14,500 test cases. We demonstrate that our approach can correct up to 88% of terms inaccurately extracted by the OCR model in the case of Serbian legal texts.
A Novel Acoustic Ventilation Barrier Based on the Block-Shaped Space-Coiling Metamaterial
Authors: Wu Qiaoyun , Xu Zhe , Xu Zhifeng , Ding Lan , Zhao Chunfeng
Published: January 2025

Newly emerged acoustic barriers provide effective solutions for noise reductions of varied kinds in which acoustic barriers made of Fano resonance-based space-coiling metamaterial are reported to have promising application prospects for their broadband noise reduction ability and good ventilation performance. However, current Fano resonance-based acoustic ventilation barriers are hard to practically apply since most of them are difficult to manufacture or install. To this end, this research proposes a novel acoustic ventilation barrier based on block-shaped space-coiling metamaterial, which is not only as functional as other acoustic ventilation barriers but also easy to manufacture and install. To obtain a more in-depth understanding of the noise reduction effect, the influence of the design parameters on transmission loss is numerically studied. Additionally, we conduct both numerical and experimental studies on the transmission loss and the ventilation performance of a full-scale meta-unit. Furthermore, through the corresponding optimization process, the proposed acoustic ventilation barrier can have transmission loss consistently above 10 dB across the frequency range of 495~1063 Hz. Lastly, a composite ventilation acoustic barrier obtained by stacking two layers of different proposed metamaterials is presented, which achieves multiband noise reduction performance across the ultra-broad frequency range of 479~1758 Hz.
Pattern-Based Test Suite Reduction Method for Smart Contracts
Authors: Górski Tomasz
Published: January 2025

Testing in the software development process is one of the crucial disciplines. The immutability of deployed smart contracts makes tests particularly important in their design and implementation. The objective is to minimize the costs of smart contract testing by reducing the number of test cases. The article presents the test suite reduction method for smart contracts, which exploits the knowledge of their design manner. In particular, the design of a mechanism for evaluating the list of verification rules controlling the execution of transactions was used. The proposed method defines a minimum set of test cases for smart contracts designed according to a specific design pattern. The test case reduction level was shown using analytical formulas enclosed in the paper. Compared to full coverage, the method reduces over 96% of test cases for a smart contract with at least eight verification rules. The performance tests were conducted and the analysis of the results was enclosed as well. Both the smart contract evaluation time and the test suite execution time are less than 0.01 of a millisecond. Besides, the method reduces the number of test data for smart contracts by over 79%. Therefore, the method can be especially useful in continuous software integration and delivery.
Ad Hoc Data Foraging in a Life Sciences Community Ecosystem Using SoDa
Authors: Naha Kallol , Jamil Hasan M.
Published: January 2025

Biologists often set out to find relevant data in an ever-changing landscape of interesting databases. While leading journals publish descriptions of databases, they are usually not recent and do not frequently update the list that discards defunct or poor-quality databases. These indices usually include databases that are proactively requested to be included by their authors. The challenge for individual biologists, then, is to discover, explore, and select databases of interest from a large unorganized collection and effectively use them in their analysis without too large of an investment. The advocation of the FAIR data principle to improve searching, finding, accessing, and inter-operating among these diverse information sources in order to increase usability is proving to be a difficult proposition and consequently, a large number of data sources are not FAIR-compliant. Since linked open data do not guarantee FAIRness, biologists are now left to individually search for information in open networks. In this paper, we propose SoDa, for intelligent data foraging on the internet by biologists. SoDa helps biologists to discover resources based on analysis requirements and generate resource access plans, as well as storing cleaned data and knowledge for community use. SoDa includes a natural language-powered resource discovery tool, a tool to retrieve data from remote databases, organize and store collected data, query stored data, and seek help from the community when things do not work as anticipated. A secondary search index is also supported for community members to find archived information in a convenient way to enable its reuse. The features supported in SoDa endows biologists with data integration capabilities over arbitrary linked open databases and construct powerful computational pipelines using them, capabilities that are not supported in most contemporary biological workflow systems, such as Taverna or Galaxy.
Strategic Resource Planning for Sustainable Biogas Integration in Hybrid Renewable Energy Systems
Authors: Motevakel Pooriya , Roldán-Blay Carlos , Roldán-Porta Carlos , Escrivá-Escrivá Guillermo , Dasí-Crespo Daniel
Published: January 2025

In response to the growing demand for sustainable energy and the environmental impacts of fossil fuels, renewable sources like biomass have become crucial, especially in regions rich in agricultural and animal waste. This study focuses on a real-life project in Aras de los Olmos, Spain, where solar, wind, and biogas from biomass serve as primary energy sources, supplemented by a hydro-based storage system to stabilize supply. Central to the research is optimizing biomass inflow to the biogas reactor—the primary controllable variable—to effectively manage the supply chain, maximize energy output, and minimize logistical costs. The study addresses practical challenges by utilizing real data on demand, truck capacities, and costs and employing robust optimization tools like Gurobi. It demonstrates how optimized biomass flow can secure energy needs during high demand or when other renewables are unavailable. Integrating technical and economic aspects, it offers a comprehensive and practical model for sustainable and economically viable energy production in rural communities. It provides a foundational framework for future renewable energy and optimized energy storage system studies.
Hake Fish Preservation Using Plant-Based Impregnated Polylactic Acid Food Films as Active Packaging
Authors: Sánchez-García Fini , Machado Noelia D. , Tirado-Fernández María , Cejudo-Bastante Cristina , Roldán Ana M. , Mantell-Serrano Casimiro , Casas-Cardoso Lourdes
Published: January 2025

Global fish consumption has steadily increased; however, fishery products are difficult to preserve. Active packaging has emerged as an alternative to improve its conservation. In this work, fresh hake fillets were packaged in commercial polylactic acid films impregnated with olive leaf extract using supercritical CO2. The impregnation was performed at 35 °C and 400 bar for 1 h. The ABTS assay was used to determine the antioxidant activity, and migration tests were performed using food simulants A and D2 for 10 days at 5 °C. The fresh fillets were packaged in impregnated and control films and stored for 12 days at 4 °C. The microbiological, physical (drip loss, aw, pH, and color) and chemical parameters (total volatile base and trimethylamine) were analyzed. The impregnated films presented a 706 μg extract mg−1 polymer, showing a 2-fold extract release using food simulant D2 than simulant A. After hake storage using impregnated films, reduced microbial count, and drip loss, maintaining the pH stability was obtained. The color turned yellowish and no detectable olfactory presence of the extract was noted. The chemical parameters were similar in both types of films. The proposed biodegradable packaging with olive by-products preserves moisture and controls microbial growth, representing an eco-friendly alternative.
A Multi-Output Ensemble Learning Approach for Multi-Day Ahead Index Price Forecasting
Authors: Sahoo Kartik , Thakur Manoj
Published: January 2025

The stock market index future price forecasting is one of the imperative financial time series problems. Accurately estimated future closing prices can play important role in making trading decisions and investment plannings. This work proposes a new multi-output ensemble framework that integrates the hybrid systems generated through importance score based feature weighted learning models through a continuous multi-colony ant colony optimization technique (MACO-LD) for multi-day ahead index future price forecasting. Importance scores are obtained through four different importance score generation strategies (F-test, Relief, Random Forest, and Grey correlation). Multi-output variants of three baseline learning algorithms are brought in to address multi-day ahead forecasting. This study uses three learning algorithms namely multi-output least square support vector regression (MO-LSSVR), multi-output proximal support vector regression (MO-PSVR) and multi-output ε-twin support vector regression (MO-ε-TSVR) as the baseline methods for the feature weighted hybrid models. For the purpose of forecasting the future price of an index, a comprehensive collection of technical indicators has been taken into consideration as the input features. The proposed study is tested over eight index futures to explore the forecasting performance of individual hybrid predictors obtained after incorporating importance scores over baseline methods. Finally, multi-colony ant colony optimization algorithm is employed to construct the ensemble results from the feature weighted hybrid models along with baseline algorithms. The experimental results for all the eight index futures established that the proposed ensemble of importance score based feature weighted models exhibits superior performance in index future price forecasting compared to the baseline methods and that of importance score based hybrid methods.
SqueezeMaskNet: Real-Time Mask-Wearing Recognition for Edge Devices
Authors: Benitez-Garcia Gibran , Prudente-Tixteco Lidia , Olivares-Mercado Jesus , Takahashi Hiroki
Published: January 2025

This paper presents SqueezeMaskNet, a lightweight convolutional neural network designed for real-time recognition of proper and improper mask usage. The model classifies four categories: masks worn correctly, masks covering only the mouth, masks not covering, and no mask. SqueezeMaskNet integrates seamlessly with existing face detection systems, removing the need for retraining. We propose using Fire modules for efficiency, along with attention mechanisms like efficient channel attention (ECA) and squeeze-and-excitation (SE) blocks for improved feature refinement. SqueezeMaskNet achieved 96.7% accuracy on the challenging FineFM test set and ran at 297 FPS on a GPU and up to 96 FPS on edge devices like a Jetson Orin NX. We also introduced ImproperTFM, a subset of real-world images focusing on improper mask usage, which enhanced the model accuracy when combined with FineFM data. Comparative experiments demonstrated SqueezeMaskNet’s superior performance, efficiency, and adaptability compared to MobileNet and EfficientNet, making it a practical solution for mask-wearing recognition across various devices and settings.
Peripheral Blood DNA Methylation Changes in Response to Centella asiatica Treatment in Aged Mice
Authors: Monestime Olivia , Davis Brett A. , Layman Cora , Wheeler Kandace J. , Hack Wyatt , Zweig Jonathan A. , Soumyanath Amala , Carbone Lucia , Gray Nora E.
Published: January 2025

Alterations in epigenetic modifications, like DNA methylation, in peripheral blood could serve as a useful, minimally invasive biomarker of the effects of anti-aging interventions. This study explores this potential with a water extract of the botanical Centella asiatica (CAW). Eighteen-month-old mice were treated with CAW in their drinking water for 5 weeks alongside vehicle-treated eighteen-month-old C57BL6 mice. Reduced representation bisulfite sequencing (RRBS) was used to identify genome-wide differential methylation in the blood of CAW-treated aged mice compared to vehicle-treated aged mice. Our results showed a distinct enrichment of differentially methylated regions (DMRs) nearby genes involved in biological processes relevant to aging (i.e., antioxidant response, metabolic regulation, cellular metabolism). A distinct difference was observed between males and females in both the number of methylation sites and the state of methylation. Moreover, genes nearby or overlapping DMRs were found to be enriched for biological processes related to previously described cellular effects of CAW in the mouse brain (i.e., antioxidant response, metabolic regulation, calcium regulation, and circadian rhythm). Together, our data suggest that the peripheral blood methylation signature of CAW in the blood could be a useful, and readily accessible, biomarker of CAW’s effects in aging.
Tetrahydrobiopterin in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: A Friend or Foe?
Authors: Rahman A. F. M. Towheedur , Benko Anna , Bulbule Sarojini , Gottschalk Carl Gunnar , Arnold Leggy A. , Roy Avik
Published: January 2025

Myalgic Encephalomyelitis or Chronic Fatigue Syndrome (ME/CFS) is a chronic multisystem disease characterized by severe muscle fatigue, pain, dizziness, and brain fog. The two most common symptoms are post-exertional malaise (PEM) and orthostatic intolerance (OI). ME/CFS patients with OI (ME+OI) suffer from dizziness or faintness due to a sudden drop in blood pressure while maintaining an upright posture. Clinical research has demonstrated that patients with OI display severe cardiovascular abnormalities resulting in reduced effective blood flow in the cerebral blood vessels. However, despite intense investigation, it is not known why the effective cerebral blood flow is reduced in OI patients. Based on our recent findings, we observed that tetrahydrobiopterin (BH4) metabolism was highly dysregulated in ME+OI patients. In the current review article, we attempted to summarize our recent findings on BH4 metabolism to shed light on the molecular mechanisms of OI.
Assessment of Developmental Prosopagnosia in an Individual with Tourette Syndrome and Attention Deficit Hyperactivity Disorder: A Case Report
Authors: Emhjellen Petter Espeseth , Starrfelt Randi , Raudeberg Rune , Hassel Bjørnar
Published: January 2025

Background/Objectives: Prosopagnosia is the inability to recognize people by their faces. Developmental prosopagnosia is the hereditary or congenital variant of the condition. The aim of this study was to demonstrate the assessment of developmental prosopagnosia in a clinical context, using a combination of commercially available clinical assessment tools and experimental tools described in the research literature. Methods: We conducted a comprehensive neuropsychological assessment of a man with Tourette syndrome and attention deficit hyperactivity disorder (ADHD). The patient (ON) had experienced difficulties with face identity recognition throughout his life but believed they were caused by a lack of interest in others. Results: The neuropsychological assessment revealed varying degrees of difficulties primarily related to executive functions, attention, reaction time, and memory processes, as expected in a person with Tourette’s syndrome and ADHD. In addition, ON reported severe problems with face recognition on a prosopagnosia questionnaire and demonstrated severely impaired performance on tests of face memory and face perception commonly used to diagnose prosopagnosia. Interestingly, he reported familial face recognition problems on the maternal side of the family, while tics and ADHD symptoms occurred on the paternal side. This suggests that, in this case, the conditions were likely inherited through different genetic pathways. Conclusions: Proper assessment of face recognition problems, which includes a broad spectrum of clinical assessment tools, could help patients develop awareness and acceptance of themselves and their difficulties, and could serve as a basis for the development of clinical interventions. While ON’s DP, Tourette syndrome, and ADHD may have distinct genetic origins, impairment in face identity recognition has been observed across several neurodevelopmental conditions and is likely more common than currently thought.
Analysis of the Temporal and Spatial Patterns of Residential Prices in Qingdao and Its Driving Factors
Authors: Wang Yanjun , Feng Yin , Han Kun , Zheng Zishu , Dai Peng
Published: January 2025

As an important indicator of the level of urban economic development and the quality of the residents’ lives, housing prices are affected by various factors, such as the spatial distribution of the housing market, the housing characteristics of neighborhoods, and the location conditions. This paper summarizes the spatial distribution of housing prices in Qingdao using GIS, analyzing spatial distribution characteristics, and combines these with the Geographically Weighted Regression (GWR) model to explore the influence of various factors, such as community attributes, location, transportation, and peripheral facilities on residential prices. The results show that from 2003 to 2023, residential housing prices in Qingdao exhibited a significant, continuous upward trend, with rapid growth in the early period and more stable growth in the later period; the spatial structure of residential prices evolved from a “single core” in Shinan District to a “double core + fan” structure involving both Shinan and Laoshan Districts, eventually forming a “double core + fan + mosaic” spatial layout; the green environment, congestion, leisure facilities, service management, and other community factors not only reflect the economic strengths and lifestyles of the residents, but also serve as key drivers of residential price differentiation.
An Updated Systematic Review and Network Meta-Analysis of First-Line Triplet vs. Doublet Therapies for Metastatic Hormone-Sensitive Prostate Cancer
Authors: Matsukawa Akihiro , Litterio Giulio , Cormio Angelo , Miszczyk Marcin , Kardoust Parizi Mehdi , Fazekas Tamás , Tsuboi Ichiro , Mancon Stefano , Schulz Robert J. , Laukhtina Ekaterina , Rajwa Paweł , Mori Keiichiro , Chlosta Piotr , Marchioni Michele , Schips Luigi , Miki Jun , Kimura Takahiro , Shariat Shahrokh F. , Yanagisawa Takafumi
Published: January 2025

Purpose: The addition of androgen receptor pathway inhibitors (ARPIs) to androgen deprivation therapy (ADT), with or without docetaxel (Doc), is currently recommended for metastatic, hormone-sensitive prostate cancer (mHSPC). Recently, the ARANOTE trial evaluated the efficacy and safety of Darolutamide + ADT in this setting. We aimed to update a network meta-analysis (NMA) of these combination therapies. Methods: We conducted a systematic search for RCTs on systemic therapies for mHSPC using MEDLINE, Embase, and the Web of Science Core Collection in September 2024. An NMA utilizing random-effects models was performed to compare progression-free survival (PFS), overall survival (OS), and adverse event (AE) incidence (PROSPERO: CRD42024591458). Results: A total of 12 RCTs (n = 11,954) were included in our NMAs. Triplet therapies were associated with significant improvements in PFS compared to ARPI-based doublet therapies (hazard ratio [HR]: 0.74; 95% confidence interval [CI]: 0.59–0.93; p = 0.01), but the difference did not reach the conventional levels of statistical significance for OS (HR: 0.82; 95% CI: 0.67–1.01; p = 0.059). In a subset analysis, compared to ARPI-based doublet therapies, triplet therapies showed a significant improvement in PFS in patients with high-volume disease (HR: 0.64; 95% CI: 0.47–0.88; p < 0.01), whereas no significant improvement was observed in those with low-volume disease (HR: 0.86; 95% CI: 0.45–1.67; p = 0.7). No significant difference in grade ≥ 3 AEs was observed between triplet therapies and ARPI-based doublet therapies. The main limitations include patient heterogeneity and limited follow-up in some studies. Conclusions: Triplet therapies can improve the oncologic outcomes of patients with mHSPC compared to ARPI-based doublet therapies, without significantly increasing severe AEs. These findings warrant further confirmation in a head-to-head trial powered for overall survival.
Psoas Muscle Index as an Independent Predictor of Survival in Patients with Hepatocellular Carcinoma Receiving Systemic Targeted Therapy
Authors: Imai Kenji , Takai Koji , Aiba Masashi , Unome Shinji , Miwa Takao , Hanai Tatsunori , Sakai Hiroyasu , Shirakami Yohei , Suetsugu Atsushi , Shimizu Masahito
Published: January 2025

Background: This study aimed to investigate the usefulness of the psoas muscle index (PMI) as an independent predictor of survival after systemic targeted therapy initiation in patients with hepatocellular carcinoma (HCC). Method: In total, 214 patients with HCC who underwent systemic targeted therapy at the Gifu University Hospital were enrolled. The correlation between the PMI and the skeletal muscle index (SMI) was assessed using Pearson’s correlation coefficient (PCC). The Cox proportional hazards model was employed to determine whether the PMI, along with the α-fetoprotein (AFP) level and the ALBI score, influenced survival; these variables were considered time-dependent covariates. The optimal PMI cut-off value that yielded the most significant differences in survival was determined using maximally selected statistics. Results: The PMI was significantly correlated with the SMI (PCC = 0.38 and p < 0.001 for women; PCC = 0.62 and p < 0.001 for men). The PMI independently influenced survival (hazard ratio: 0.852; 95% confidence interval: 0.755–0.962; and p < 0.001), along with established prognostic factors such as the AFP and the ALBI score. The optimal PMI cut-off values that yielded the most significant differences in survival were 2.86 cm2/m2 for women and 3.55 cm2/m2 for men, and these values significantly stratified patient outcomes for both sexes (p < 0.001). Conclusions: The PMI serves as a reliable surrogate for the SMI in assessing skeletal muscle mass and predicting survival.
Early Versus Delayed Androgen Deprivation Therapy for Biochemical Recurrence After Local Curative Treatment in Non-Metastatic Hormone-Sensitive Prostate Cancer: A Systematic Review of the Literature
Authors: Karim Muneeb Uddin , Tisseverasinghe Steven , Cartes Rodrigo , Martinez Constanza , Bahoric Boris , Niazi Tamim
Published: January 2025

Background: The ideal timing of androgen deprivation therapy (ADT) for patients with biochemical recurrence (BCR) of prostate cancer (PCa) remains controversial due to its side effects and uncertain impact on survival outcomes. Methods: We performed a review of the current literature by comprehensively searching the PubMed, Embase, and Cochrane databases to determine the optimal timing of ADT initiation after biochemical recurrence. We selected 26 studies including systematic reviews, randomized controlled trials (RCTs), and retrospective studies, while also reviewing practice guidelines. Results: Not all patients with BCR cancer experience clinical or radiological progression. While early ADT may delay progression, evidence of its effect on PCa-specific mortality remains inconclusive. The PSA thresholds for initiating ADT vary, complicating decision-making. Key predictors of progression include a short PSA doubling time (PSADT), a high Gleason score (GS), and a brief interval to BCR of PCa post-radiotherapy (RT). Combining ADT with androgen receptor pathway inhibitors (ARPIs) has been shown to improve metastasis-free survival in high-risk patients. Conclusion: The ideal timing of ADT initiation in BCR PCa remains uncertain. Early ADT can help control the progression, but its effect on PCa-specific mortality is unclear. Stratifying patients by their risk factors, such as their PSADT, GS, and time to BCR can guide individualized treatment. In high-risk patients, delaying ADT should be avoided, while combining ADT with an androgen receptor pathway inhibitor (ARPI) may further improve outcomes.
Consequences of Surface Composition and Aggregation Conditions of Ag Nanoparticles on Surface-Enhanced Raman Scattering (SERS) of Pesticides
Authors: Oliveira Marcelo José dos Santos , Ruiz Gilia Cristine Marques , Rubira Rafael Jesus Gonçalves , Sanchez-Cortes Santiago , Constantino Carlos José Leopoldo , Furini Leonardo Negri
Published: January 2025

Surface-enhanced Raman scattering (SERS) is highly dependent on the adsorption of target molecules onto metallic surfaces, such as colloidal metallic nanoparticles. The selection of suitable substrates is crucial for optimizing SERS performance. Herein, we investigated the dependence of two pesticide SERS signals, thiabendazole (TBZ) and carbendazim (MBC), on both Ag nanoparticles (reduced by hydroxylamine—AgH or citrate—AgCT) and the aggregation conditions induced by adding different salts (NaCl, KCl or KNO3). In addition to SERS experiments, in order to assess the induced aggregation of the Ag nanoparticles, UV-Vis absorption spectroscopy, dynamic light scattering (DLS) and zeta potential were employed. For AgH, the use of salts did not yield the greatest effect in the presence of TBZ, as only with the pesticide was it possible to achieve the highest aggregation and greater intensity of the SERS signal. In contrast, with the MBC pesticide, the KNO3 salt promoted the greatest aggregation state and was crucial for obtaining the most amplified SERS signal. The thicker coating layer of AgCT prevented the adsorption of both pesticides on the surface of the nanoparticles, which was achievable using salts containing Cl− ions. Additionally, to obtain the SERS signal of MBC with AgCT, besides the presence of chlorinated salts, other adjustments were necessary, such as changing both the pH of the medium (from pH 5.8 to pH 8, for which MBC is in its neutral form) and the laser lines (from 785 to 514.5 nm). These findings demonstrated that although the pesticide molecules belong to the same chemical functional group, their detection was strongly influenced by the surface of the silver nanoparticles and the salts added. This highlights the specific nuances in detection depending on the method of Ag synthesis and the nature of the aggregating agents used.
Applicability of Hydrogen Fuel for a Cruise Ship
Authors: Mäkelä Maarit , Niemi Seppo , Nuortila Carolin , Nyystilä Lauri
Published: January 2025

Cruise ships function as a means of transport while simultaneously accommodating thousands of guests, providing a holiday experience with various entertainment options. This translates to high energy requirements for propulsion and hotel operations, typically covered by the combustion of fossil fuels. The operation of cruise vessels with fossil fuels contributes to carbon dioxide and also local harmful emissions in ports when shore power connections are not available. To enable cleaner and sustainable cruising, alternative technologies and fuels must be adopted. The present study evaluated the applicability of hydrogen fuel in combustion engines in a Meraviglia-class cruise ship. The fuel consumption of the ship was based on a real operation in Europe. This study examined how fuel energy in the form of LH2 could be stored on the ship for a European cruise route and concludes that 3700 m3 of storage space would be needed to accommodate the liquid hydrogen. The mass of the LH2 would only be one-third of that of fossil fuels, but the weight of the LH2 tanks would most likely increase the total weight of the hydrogen storage. Additional new technologies and combined power production could significantly reduce the amount of LH2 to be stored.
Improved Uniformity Properties and Corrosion Resistance of Zinc–Nickel Composite Coating Enhanced by Nano-SiO2
Authors: Chang Sujie , Wang Yuanhao , Wang Jianpeng , Hao Zerui , Yang Yang , Wang Yi , Wang Xinyi , Cao Fan , Shi Lei
Published: January 2025

In this study, pre-treated low-carbon steel substrates were electroplated with Zinc–Nickel (ZN) alloy composite coatings enhanced by the incorporation of nano-silicon dioxide (SiO2) particles in an alkaline solution. ZN deposits with varying concentrations of nano-SiO2—specifically, 1, 2, 3, 5, and 10 wt%—were achieved by adjusting the ratio between the nano-SiO2 and ZN alloy electroplating solutions. The influence of the nano-SiO2 content on both the quality of the coating and its corrosion behavior was investigated in detail. Scanning electron microscopy (SEM), energy-dispersive spectroscopy (EDS), and an atomic force microscope (AFM) were utilized to assess the surface, cross-section structure, elemental composition, and thickness of the coatings. Notably, the addition of nano-SiO2 improved the microstructure of the coating, leading to a reduction in grain size as well as enhancements in uniformity and density while revealing that co-deposition reached an optimal concentration at 3 wt% nano-SiO2. The corrosion behavior of coated specimens was evaluated through electrochemical impedance spectroscopy (EIS) and polarization techniques within a 3.5 wt% NaCl solution serving as a corrosive medium. Specifically, for typical prepared coatings, the corrosion current density decreased from 1.410 × 10−4 A·cm−2 to 5.762 × 10−6 A·cm−2, which is a remarkable reduction by one to two orders of magnitude relative to the SiO2-free coatings mentioned previously. These findings provide a straightforward approach for selecting 3 wt% nano-SiO2 as an effective additive in ZN composite coatings.