bluuebunny/crossref_metadata_2025 huggingface dataset:
Geographical–Historical Analysis of the Herbarium Specimens Representing the Economically Important Family Amaranthaceae (Chenopodiaceae-Amaranthaceae Clade) Collected in 1821–2022 and Preserved in the Herbarium of the Jagiellonian University in Krakow
Authors: Stadnicka-Futoma Agata , Nobis Marcin
Published: June 2024

Herbaria constitute a form of documentation, store and secure comparative material, as well as constitute an extra original gene bank. They are an invaluable database among others for the biological, ethnobotanical and agricultural sciences. The digitization of herbarium collections significantly facilitates access to archival materials; however, searching them is still time-consuming. Therefore, our work aims to analyze the herbarium collection of 8801 sheets for specimens representing the economically important family Amaranthaceae (Chenopodiaceae-Amaranthaceae clade) deposited the oldest herbarium in Poland, the herbarium of the Jagiellonian University (KRA). These specimens have been collected from almost all the continents in dozens of countries for over 200 years. The analyses conducted, including the taxonomic coverage, geographical characteristics and origin, temporal coverage and utility importance of representative species, present the discussed resources in a more accessible way and may become a more attractive form for scientists potentially interested in more advanced research work.
Immune-Mediated Ocular Surface Disease in Diabetes Mellitus—Clinical Perspectives and Treatment: A Narrative Review
Authors: Ghenciu Laura Andreea , Hațegan Ovidiu Alin , Bolintineanu Sorin Lucian , Dănilă Alexandra-Ioana , Faur Alexandra Corina , Prodan-Bărbulescu Cătălin , Stoicescu Emil Robert , Iacob Roxana , Șișu Alina Maria
Published: June 2024

Diabetes mellitus (DM) is a chronic metabolic disorder marked by hyperglycemia due to defects in insulin secretion, action, or both, with a global prevalence that has tripled in recent decades. This condition poses significant public health challenges, affecting individuals, healthcare systems, and economies worldwide. Among its numerous complications, ocular surface disease (OSD) is a significant concern, yet understanding its pathophysiology, diagnosis, and management remains challenging. This review aims to explore the epidemiology, pathophysiology, clinical manifestations, diagnostic approaches, and management strategies of diabetes-related OSD. The ocular surface, including the cornea, conjunctiva, and associated structures, is vital for maintaining eye health, with the lacrimal functional unit (LFU) playing a crucial role in tear film regulation. In DM, changes in glycosaminoglycan metabolism, collagen synthesis, oxygen consumption, and LFU dysfunction contribute to ocular complications. Persistent hyperglycemia leads to the expression of cytokines, chemokines, and cell adhesion molecules, resulting in neuropathy, tear film abnormalities, and epithelial lesions. Recent advances in molecular research and therapeutic modalities, such as gene and stem cell therapies, show promise for managing diabetic ocular complications. Future research should focus on pathogenetically oriented therapies for diabetic neuropathy and keratopathy, transitioning from animal models to clinical trials to improve patient outcomes.
Sodium Houttuyfonate Prevents Seizures and Neuronal Cell Loss by Maintaining Glutamatergic System Stability in Male Rats with Kainic Acid-Induced Seizures
Authors: Chang Yi , Chen Yi-Jun , Wang Su-Jane
Published: June 2024

The present study evaluated the antiseizure and neuroprotective effects of sodium houttuyfonate (SH), a derivative of Houttuynia cordata Thunb. (H. cordata), in a kainic acid (KA)- induced seizure rat model and its underlying mechanism. Sprague Dawley rats were administered normal saline, SH (50 or 100 mg/kg), or carbamazepine (300 mg/kg) by oral gavage for seven consecutive days before the intraperitoneal administration of KA (15 mg/kg). SH showed antiseizure effects at a dose of 100 mg/kg; it prolonged seizure latency and decreased seizure scores. SH also significantly decreased neuronal loss in the hippocampi of KA-treated rats, which was associated with the prevention of glutamate level increase, the upregulation of glutamate reuptake-associated proteins (excitatory amino acid transporters 1–3), glutamate metabolism enzyme glutamine synthetase, the downregulation of the glutamate synthesis enzyme glutaminase, and significant alterations in the expression of AMPA (α-amino-3-hydroxy-5-methyl-4-isoxazole-propionic acid receptor) and NMDA (N-methyl-D-aspartic acid receptor) receptor subunits in the hippocampus. Furthermore, the effects of SH were similar to those of the antiseizure drug carbamazepine. Therefore, the results of the present study suggest that SH has antiseizure effects on KA-induced seizures, possibly through the prevention of glutamatergic alterations. Our findings suggest that SH is a potential alternative treatment that may prevent seizures by preserving the normal glutamatergic system.
Unraveling the Cardiac Matrix: From Diabetes to Heart Failure, Exploring Pathways and Potential Medications
Authors: Tudurachi Bogdan-Sorin , Anghel Larisa , Tudurachi Andreea , Sascău Radu Andy , Zanfirescu Răzvan-Liviu , Stătescu Cristian
Published: June 2024

Myocardial infarction (MI) often leads to heart failure (HF) through acute or chronic maladaptive remodeling processes. This establishes coronary artery disease (CAD) and HF as significant contributors to cardiovascular illness and death. Therefore, treatment strategies for patients with CAD primarily focus on preventing MI and lessening the impact of HF after an MI event. Myocardial fibrosis, characterized by abnormal extracellular matrix (ECM) deposition, is central to cardiac remodeling. Understanding these processes is key to identifying new treatment targets. Recent studies highlight SGLT2 inhibitors (SGLT2i) and GLP-1 receptor agonists (GLP1-RAs) as favorable options in managing type 2 diabetes due to their low hypoglycemic risk and cardiovascular benefits. This review explores inflammation’s role in cardiac fibrosis and evaluates emerging anti-diabetic medications’ effectiveness, such as SGLT2i, GLP1-RAs, and dipeptidyl peptidase-4 inhibitors (DPP4i), in preventing fibrosis in patients with diabetes post-acute MI. Recent studies were analyzed to identify effective medications in reducing fibrosis risk in these patients. By addressing these areas, we can advance our understanding of the potential benefits of anti-diabetic medications in reducing cardiac fibrosis post-MI and improve patient outcomes in individuals with diabetes at risk of HF.
Expression of HOXB7 in the Lung of Patients with Idiopathic Pulmonary Fibrosis: A Proof-of-Concept Study
Authors: Samarelli Anna Valeria , Tonelli Roberto , Raineri Giulia , Mastrolia Ilenia , Costantini Matteo , Fabbiani Luca , Catani Virginia , Petrachi Tiziana , Bruzzi Giulia , Andrisani Dario , Gozzi Filippo , Marchioni Alessandro , Masciale Valentina , Aramini Beatrice , Ruggieri Valentina , Grisendi Giulia , Dominici Massimo , Cerri Stefania , Clini Enrico
Published: June 2024

Background: The molecular pathways involved in the onset and progression of idiopathic pulmonary fibrosis (IPF) still need to be fully clarified as some are shared with lung cancer development. HOXB7, a member of the homeobox (Hox) gene family, has been found involved in various cancers. Methods: Immunohistochemical (IHC) analysis was run on lung tissue samples from surgical lung biopsy (SLB) of 19 patients with IPF, retrospectively selected from the IPF database of the University Hospital of Modena. HOXB7 expression was analyzed and compared with that of five patients with no evidence of pulmonary fibrosis as controls. Results: The semi-quantitative analysis of IHC showed that HOXB7 protein expression was higher in IPF patients compared to controls (difference between means = 6.2 ± 2.37, p = 0.0157). Further, HOXB7 expression was higher in IPF patients with a higher extent of fibrosis (50–75%)—measured with high-resolution computer tomography—compared to those with a lower extent (0–25%) (difference between means = 25.74 ± 6.72, p = 0.004). Conclusions: The expression of HOXB7 is higher in the lung of IPF patients compared to controls, and was represented in different cellular compartments within the lung niche. Further investigations are needed to clarify its role in the pathogenesis and progression of IPF.
Effect of Trough Incidence Angle on the Aerodynamic Characteristics of a Biomimetic Leading-Edge Protuberanced (LEP) Wing at Various Turbulence Intensities
Authors: Arunvinthan Shanmugam , Gouri Ponnusamy , Divysha Saravanan , Devadharshini RK , Nithya Sree Rajan
Published: June 2024

A series of wind tunnel tests were performed to investigate the effect of turbulent inflows on the aerodynamic characteristics of variously modified trough incident leading-edge-protuberanced (LEP) wing configurations at various turbulence intensities. A self-developed passive grid made of parallel arrays of round bars was placed at different locations of the wind tunnel to generate desired turbulence intensity. The aerodynamic forces acting over the trough incidence LEP wing configuration where obtained from surface pressure measurements made over the wing at different turbulence intensities using an MPS4264 Scanivalve simultaneous pressure scanner corresponding to a sampling frequency of 700 Hz. All the test models were tested at a wide range of angles of attack ranging between 0°≤α≤90° at turbulence intensities varying between 5.90% ≤ TI ≤ 10.54%. Results revealed that the time-averaged mean coefficient of lift (CL) increased with the increase in the turbulence intensity associated with smooth stall characteristics rendering the modified LEP test models advantageous. Furthermore, based on the surface pressure coefficients, the underlying dynamics behind the stall delay tendency were discussed. Additionally, attempts were made to statistically quantify the aerodynamic forces using standard deviation at both the pre-stall and the post-stall angles.
CoNiTe2 Nanomaterials as an Efficient Non-Enzymatic Electrochemical Sensing Platform for Detecting Dopamine
Authors: Wang Zhi-Yuan , Shen Chi-Hung , Yang Shih-Hao , Chang Han-Wei , Tsai Yu-Chen
Published: June 2024

Dopamine (DA) is an important catecholamine neurotransmitter in the mammalian central nervous system that affects many physiological functions. Hence, a highly sensitive and selective sensing platform is necessary for quantification of DA in the human body. In this study, ternary transition metal tellurides of CoNiTe2 were successfully synthesized using the hydrothermal method. The proposed CoNiTe2 nanomaterials were dispersed well in Nafion to form a well-dispersed suspension and, when dropped on a glassy carbon electrode (GCE) as the working electrode (CoNiTe2/Nafion/GCE) for electrochemical non-enzymatic DA sensing, displayed excellent electrocatalytic activity for dopamine electrooxidation. The morphology and physical/chemical properties of CoNiTe2 nanomaterials were characterized using field emission scanning electron microscopy (FESEM), transmission electron microscopy (TEM), X-ray diffraction (XRD), and X-ray photoelectron spectroscopy (XPS). In order to obtain the best electrochemical response to DA from the fabricated CoNiTe2/Nafion/GCE, the experimental conditions of electrochemical sensing, including the CoNiTe2 loading amounts and pH values of the phosphate buffer solution (PBS), were explored to achieve the best electrochemical sensing performance. Under optimal conditions (2 mg of CoNiTe2 and pH 6.0 of PBS), the fabricated CoNiTe2/Nafion/GCE showed excellent electrocatalytic activity of DA electrooxidation. The CoNiTe2/Nafion/GCE sensing platform demonstrated excellent electrochemical performance owing to the optimal structural and electronic characteristics originating from the synergistic interactions of bimetallic Co and Ni, the low electronegativity of Te atoms, and the unique morphology of the CoNiTe2 nanorod. It exhibited a wide linear range from 0.05 to 100 μM, a high sensitivity of 1.2880 µA µM−1 cm−2, and a low limit of detection of 0.0380 µM, as well as acceptable selectivity for DA sensing. Therefore, the proposed CoNiTe2/Nafion/GCE could be considered a promising electrode material for electrochemical non-enzymatic DA sensing.
Bryophytes Collection of the University of Brasilia Herbarium, Brazil
Authors: Camelo Mel , Faria Allan , Cemin Daniela , Câmara Paulo , Carvalho-Silva Micheline
Published: June 2024

The UB Herbarium, located in the Department of Botany at the University of Brasilia (Brasilia, Brazil), was established in 1963. It is the third-largest herbarium in Brazil, housing approximately 277,000 samples. This study presents a quantitative description of the bryophytes collection at the UB Herbarium, which is the second-largest bryophytes collection in Brazil. It contains 31,099 samples, including specimens from all continents and 79 countries, with a focus on specimens from Brazil, Papua New Guinea, Malaysia, the United States, Chile, Indonesia, South Africa, Ireland, Argentina, and Sweden, as well as various islands and archipelagos. The collection has grown significantly since its creation in 1963, when it initially held 869 specimens; it now contains 31,099 specimens, which is a 59.3% increase. The herbarium holds 95 types of bryophytes. These results were gathered from consultations in the UB Herbarium online database and compiled into an Excel spreadsheet. These findings highlight the importance of our collection, making it a valuable resource for students and researchers interested in exploring and studying a diverse array of specimens.
EUAVDet: An Efficient and Lightweight Object Detector for UAV Aerial Images with an Edge-Based Computing Platform
Authors: Wu Wanneng , Liu Ao , Hu Jianwen , Mo Yan , Xiang Shao , Duan Puhong , Liang Qiaokang
Published: June 2024

Crafting an edge-based real-time object detector for unmanned aerial vehicle (UAV) aerial images is challenging because of the limited computational resources and the small size of detected objects. Existing lightweight object detectors often prioritize speed over detecting extremely small targets. To better balance this trade-off, this paper proposes an efficient and low-complexity object detector for edge computing platforms deployed on UAVs, termed EUAVDet (Edge-based UAV Object Detector). Specifically, an efficient feature downsampling module and a novel multi-kernel aggregation block are first introduced into the backbone network to retain more feature details and capture richer spatial information. Subsequently, an improved feature pyramid network with a faster ghost module is incorporated into the neck network to fuse multi-scale features with fewer parameters. Experimental evaluations on the VisDrone, SeaDronesSeeV2, and UAVDT datasets demonstrate the effectiveness and plug-and-play capability of our proposed modules. Compared with the state-of-the-art YOLOv8 detector, the proposed EUAVDet achieves better performance in nearly all the metrics, including parameters, FLOPs, mAP, and FPS. The smallest version of EUAVDet (EUAVDet-n) contains only 1.34 M parameters and achieves over 20 fps on the Jetson Nano. Our algorithm strikes a better balance between detection accuracy and inference speed, making it suitable for edge-based UAV applications.
Digital Silk Roads: Leveraging the Metaverse for Cultural Tourism within the Belt and Road Initiative Framework
Authors: Dayoub Bashar , Yang Peifeng , Omran Sarah , Zhang Qiuyi , Dayoub Alaa
Published: June 2024

The advent of the Metaverse, a convergence of virtual and physical realities, presents unprecedented opportunities for promoting cultural tourism along the historic Silk Roads within the Belt and Road Initiative (BRI) framework. However, this emerging technology’s potential remains largely unexplored in the context of cultural heritage preservation and its promotion. The aim of this study is to address this gap by empirically examining how the Metaverse can be harnessed to improve tourists’ experiences, support sustainable tourism development, and promote cultural exchange along the Silk Roads. In this study, we employed a mixed-methods approach grounded in attribution theory, using both surveys and semi-structured interviews with Silk Road tourists who had been exposed to Metaverse applications. To investigate the relationships between Metaverse features, tourists’ attributions, satisfaction, and behavioral intentions, we used structural equation modeling and thematic analysis. The findings revealed that perceived immersion, avatar identification, and cultural authenticity significantly influenced tourists’ internal, stable, and controllable attributions. Interviews further highlighted the Metaverse’s potential to promote accessibility, interpretation, and engagement with Silk Road heritage, while also raising sociocultural and ethical considerations. This paper also showcases the development of Metaverse digital twin prototypes for several iconic Silk Road cities to demonstrate the potential for participatory virtual environments to promote cultural heritage preservation, accessibility, and sustainable tourism. The study’s findings contribute to the theoretical understanding of Metaverse tourism and the application of attribution theory, offering practical insight for the responsible and effective harnessing of this transformative technology. This research provides actionable recommendations for policymakers, destination managers, and technology providers to optimize the Metaverse’s potential for cultural tourism along the Silk Roads. This has great potential in promoting the BRI’s connectivity and cooperation objectives. This paper lays the foundation for future research and responsible innovation at the intersection of emerging technologies, cultural heritage, and sustainable tourism development.
Self-Supervised and Supervised Image Enhancement Networks with Time-Shift Module
Authors: Tuncal Kubra , Sekeroglu Boran , Abiyev Rahib
Published: June 2024

Enhancing image quality provides more interpretability for both human beings and machines. Traditional image enhancement techniques work well for specific uses, but they struggle with images taken in extreme conditions, such as varied distortions, noise, and contrast deformations. Deep-learning-based methods produce superior quality in enhancing images since they are capable of learning the spatial characteristics within the images. However, deeper models increase the computational costs and require additional modules for particular problems. In this paper, we propose self-supervised and supervised image enhancement models based on the time-shift image enhancement method (TS-IEM). We embedded the TS-IEM into a four-layer CNN model and reconstructed the reference images for the self-supervised model. The reconstructed images are also used in the supervised model as an additional layer to improve the learning process and obtain better-quality images. Comprehensive experiments and qualitative and quantitative analysis are performed using three benchmark datasets of different application domains. The results showed that the self-supervised model could provide reasonable results for the datasets without reference images. On the other hand, the supervised model outperformed the state-of-the-art methods in quantitative analysis by producing well-enhanced images for different tasks.
Sample Voltage Dead-Beat Control Based on Differentiative Voltage Prediction and Switching-Cycle Extension for DC-DC Converters
Authors: Li Qidong , Zhang Desheng , Zhu Liying , Zhang Wenjia , Min Run , Zhang Qiao , Tong Qiaoling
Published: June 2024

In this paper, a sample voltage dead-beat control based on differentiative voltage prediction (DVP) and switching-cycle extension (SCE) is presented to achieve optimal transient response for DC-DC converters under discontinuous conduction mode (DCM) operation. Firstly, to improve load transient response, a DVP method is proposed to estimate the load. With the estimated load, the controller realizes load current feedforward and thus improves the transient response with a wide load range. Secondly, an SCE strategy is proposed to enlarge the output current range and output voltage slew rate, both of which have limited value under conventional digital pulse width modulation (DPWM). When the output current reaches the limited value, the proposed strategy increases the switching cycle to enlarge the current range without losing DCM operation. Finally, combining DVP with SCE, the converter not only achieves optimal response in large signal transients, but also doubles the load range in DCM operation.
The Role of Clean Coal Technologies in the Development of Renewable Energy Sources
Authors: Rybak Aurelia , Rybak Aleksandra , Joostberens Jarosław
Published: June 2024

The article presents research on the synergistic impact of clean coal technologies and renewable energy sources on the energy mix in Poland. The main causes of problems that inhibit the development of renewable energy sources and ways to eliminate them are presented. A factor that may undermine the development of renewable energy potential is access to critical raw materials such as rare earth elements. Clean coal technologies will make it possible to survive the transition period for coal-based energy mixes. The CCT solution described in this article will enable the acquisition of rare earth elements necessary for the development of renewable energy sources. The ability to meet the demand for REEs based on elements recovered from fly ash is examined. For this purpose, an analysis of wind electricity production capacities was carried out and a forecast until 2030 was created. A program was written using machine learning and the Gompretz sigmoid model. Based on the forecast, the level of demand for REEs was determined and compared with the supply obtained from fly ash. The authors propose an alternative source of REEs and analyze the relationship between demand and supply of this source.
The Bright Side of Uncertainty: The Impact of Climate Policy Uncertainty on Urban Green Total Factor Energy Efficiency
Authors: Gao Da , Zhou Xiaotian , Liu Xiaowei
Published: June 2024

Climate change has a significant impact on human economic and social life, and climate issues have rapidly emerged as a global hot topic. Using data from prefecture-level cities in China from 2005 to 2020 as a sample, this study explores the relationship between climate policy uncertainty (CPU) and urban green total factor energy efficiency (GTFEE). The results show that, first, the CPU can significantly improve urban GTFEE, and results are reconfirmed after various robustness tests. Second, the CPU promotes urban GTFEE by improving public environmental concerns and optimizing the energy consumption structure. Third, the promotion role of CPU in urban GTFEE is particularly significant in resource-based cities and economically developed cities. The results of this study provide a theoretical basis and practical enlightenment for the government to formulate forward-looking climate policies and promote the transformation of green development in cities.
The Drivers of Renewable Energy: A Global Empirical Analysis of Developed and Developing Countries
Authors: Hunt Lester C. , Kipouros Paraskevas , Lamprakis Zafeirios
Published: June 2024

The need for renewable energy is regarded as a major component in the move towards achieving sustainable development. Using a large sample of 177 countries over the period 1990 to 2020, this research explores the impact of the most significant drivers of renewable energy. Findings from this work contribute to the literature by identifying the most significant drivers of renewable energy deployment and their different responses in developed and developing economies. Empirical results suggest that GDP, oil price, access to electricity, and CO2 and methane emissions are significant determinants of renewables both as a share in energy consumption and as a share in electricity production. Additionally, trade is found to be a significant driver for the share of renewables in total energy consumption but not for the share of renewables in the electricity production model. Finally, our findings indicate that the factors influencing the development of renewables vary significantly between developed and developing countries, necessitating distinct approaches for each group of countries. These results can play a significant role from a policy perspective in designing and implementing specific policies to increase renewable energy deployment.
Torque Vectoring Control as an Energy-Efficient Alternative to Vehicle Suspensions Tuning
Authors: Asperti Michele , Vignati Michele , Sabbioni Edoardo
Published: June 2024

With a shift in the automotive industry’s focus towards sustainability and energy efficiency, optimizing vehicle handling dynamics has been put on a secondary level. Moreover, there is a growing trend towards comfort-oriented design, conversely to the vehicle-handling one. Nevertheless, recent advancements such as the integration of multiple independently controlled electric motors on a vehicle is enabling torque vectoring, which offers a promising opportunity for reconciling these conflicting objectives. This paper proposes a novel approach for jointly improving vehicle handling and energy efficiency performance. Indeed, through advanced simulation techniques, the effects of various suspension configurations are explored to strike a balance between cornering performance and energy consumption. Then, a torque vectoring controller is designed in combination with a meticulous tuning of the suspension setup. This innovative approach of considering the active control design together with the suspensions’ setup allows to obtain superior performances. Indeed, the desired vehicle cornering capabilities can be achieved while also guaranteeing a significantly more efficient vehicle in straight-line running, which covers most of the usual road driving time.
Validating Meteosat Second Generation and Himawari-8 Derived Solar Irradiance against Ground Measurements: Solarad AI’s Approach
Authors: Meher Jitendra Kumar , Rizvi Syed Haider Abbas , Choudhary Bhramar , Choudhary Ravi , Thakre Yash , Kumar Ritesh , Singh Vikram
Published: June 2024

This study assesses the efficacy of the Heliosat-2 algorithm for estimating solar radiation, comparing its outputs against ground measurements across seven distinct countries: the Netherlands, Spain, Japan, Namibia, South Africa, Saudi Arabia, and India. To achieve this, the study utilizes two distinct satellite data sources—Himawari-8 for Japan and Metosat Second Generation-MSG for the rest of the countries—and spanning the time between January 2022 and April 2024. A robust methodology for determining albedo parameters specific to Heliosat-2 was developed. During cloudy days, the estimates provided by Heliosat-2 generally exceeded the ground measurements in all of the countries. Conversely, on clear days, there was a tendency for underestimation, as indicated by the median values of the mean bias (MB) across most of the countries. The Heliosat-2 model slightly underestimates daily radiation values, with a median MB ranging from −27.5 to +10.2 W·m−2. Notably, the median root mean square error (RMSE) on clear days is significantly lower, with values ranging from 24.8 to 108.7 W·m−2, compared to cloudy days, for which RMSE values lie between 75.3 and 180.2 W·m−2. In terms of R2 values, both satellites show strong correlations between the estimated and actual values, with a median value consistently above 0.86 on a monthly scale and over 92% of daily data points falling within ±2 standard deviations.
Protective Effects of Long Double-Stranded RNA with Different CpG Motifs against Miamiensis avidus and Viral Hemorrhagic Septicemia Virus (VHSV) Infections in Olive Flounder (Paralichthys olivaceus)
Authors: Choi Hee-Jae , Choi Da-Yeon , Park Jung-Jin , Jung Hye Jin , Kim Bo-Seong , Hong Sung-Chul , Kim Jun-Hwan , Kang Yue Jai
Published: June 2024

The South Korean aquaculture industry has incurred considerable production losses due to various infectious diseases. Artificially synthesized polyinosinic–polycytidylic acid (poly I:C), structurally similar to double-stranded RNA (dsRNA) and cytidine–phosphate–guanosine oligodeoxynucleotides, can enhance immune responses and protect against diseases. Here, we investigated dsRNA molecules with different cytidine–phosphate–guanosine (CpG) motifs (dsRNA-CpGMix) as fused agents to treat Miamiensis avidus and viral hemorrhagic septicemia virus (VHSV) infection in olive flounders. We further investigated the efficacy of specific sequence motifs in dsRNA in modulating immunostimulatory effects. Fish treated with poly I:C or dsRNA-CpGMix exhibited higher survival rates than the control group. Olive flounder leukocytes stimulated with poly I:C or dsRNA-CpGMix showed increased scuticocidal activity in the presence of inactivated immune sera. dsRNA with CpG motif sequences induced higher resistance against M. avidus and VHSV infections than dsRNA without CpG motif sequences, and the dsRNA-CpGMix group showed upregulated ISG15 or Mx compared to the dsRNA-GFP group. Thus, dsRNA containing CpG motifs can be used as effective immunostimulants to enhance resistance against viral and parasitic diseases in olive flounder. The specific sequences of the CpG motifs in dsRNA may be important for enhancing immune responses and resistance against M. avidus and VHSV infections in olive flounders.
Procyanidin B1 and Coumaric Acid from Highland Barley Alleviated High-Fat-Diet-Induced Hyperlipidemia by Regulating PPARα-Mediated Hepatic Lipid Metabolism and Gut Microbiota in Diabetic C57BL/6J Mice
Authors: Liu Zehua , Liu Jianshen , Tang Ruoxin , Zhang Zhaowan , Tian Shuangqi
Published: June 2024

A whole-grain highland barley (WHB) diet has been recognized to exhibit the potential for alleviating hyperlipidemia, which is mainly characterized by lipids accumulation in the serum and liver. Previously, procyanidin B1 (PB) and coumaric acid (CA) from WHB were found to alleviate serum lipid accumulation in impaired glucose tolerance mice, while the effect on modulating the hepatic lipid metabolism remains unknown. In this study, the results showed the supplementation of PB and CA activated the expression of peroxisome proliferator-activated receptor α (PPARα) and the target genes of cholesterol 7-α hydroxylase (CYP7A1) and carnitine palmitoyl transferase I (Cpt1) in the liver cells of high-fat-diet (HFD)-induced diabetic C57BL/6J mice, resulting in decreases in the serum total cholesterol (TC), triglyceride (TG), and low-density lipoprotein (LDL-C) contents, and an increase in the high-density lipoprotein (HDL-C) content. High-throughput sequencing of 16S rRNA indicated that supplementation with PB and CA ameliorated the gut microbiota dysbiosis, which was associated with a reduction in the relative abundance of Ruminococcaceae and an increase in the relative abundance of Lactobacillus, Desulfovibrio, and Akkermansia. Spearman’s correlation analysis revealed that these genera were closely related to obesity-related indices. In summary, the activation of PPARα expression by PB and CA from WHB was important for the alleviation of hyperlipidemia and the structural adjustment of the gut microbiota.
Unlocking the Potential of Insect-Based Proteins: Sustainable Solutions for Global Food Security and Nutrition
Authors: Lisboa Hugo M. , Nascimento Amanda , Arruda Amélia , Sarinho Ana , Lima Janaina , Batista Leonardo , Dantas Maria Fátima , Andrade Rogério
Published: June 2024

The present review highlights the potential of insect-based proteins to address the growing need for sustainable and secure food systems. The key findings suggest that edible insects offer a viable and environmentally friendly alternative to traditional livestock, requiring significantly less land, water, and feed while emitting lower levels of greenhouse gases. Insect farming can also reduce waste and recycle nutrients, supporting circular economy models. Nutritionally, insects provide high-quality protein, essential amino acids, and beneficial fats, making them valuable to human diets. Despite these benefits, this review emphasizes the need for comprehensive regulatory frameworks to ensure food safety, manage potential allergenicity, and mitigate contamination risks from pathogens and environmental toxins. Additionally, developing innovative processing technologies can enhance the palatability and marketability of insect-based products, promoting consumer acceptance. This review concludes that with appropriate regulatory support and technological advancements, insect-based proteins have the potential to significantly contribute to global food security and sustainability efforts.
GC-MS Combined with Proteomic Analysis of Volatile Compounds and Formation Mechanisms in Green Teas with Different Aroma Types
Authors: Niu Xiaojun , Ao Cun , Yu Jizhong , Zhao Yun , Huang Haitao
Published: June 2024

Aroma is one of the key factors for evaluating the quality of green tea. A tender aroma (NX) and floral-like aroma (HX) are two types of high-quality aroma of green tea. In this work, the different aroma types of baked green tea were classified by sensory evaluation. Then, seven tea samples with a typical tender or floral-like aroma were selected for further volatile component analysis by GC-MS. A total of 43 aroma compounds were identified in two different aroma types of baked green tea samples. The PCA showed that linalool, geraniol, 3-hexenyl butyrate, and 3-hexenyl hexanoate were the major volatiles contributing to the HX. On the other hand, most of the alcohol volatiles, such as 1-octanol, 1-octen-3-ol, 1-dodecanol, 1-hexadecanol, phenylethyl alcohol, benzyl alcohol, aldehydes and some hydrocarbons contributed more to the NX. In addition, the chemical composition analysis showed that the content of free amino acids was higher in NX green tea samples, while the content of catechins was relatively higher in HX tea samples. A proteomic analysis revealed that most of the enzymes involved in VPBs pathways, such as phenylalanine ammonialyase, peroxidase, and shikimate-O-hydroxycinnamoyl transferase, were more abundant in NX than in HX tea samples. These results laid a foundation for the aroma formation mechanism of different aroma types of baked green tea and provided some theoretical guidance for the breeding of specific aroma varieties.
Assessment of Different Levels of Blackcurrant Juice and Furcellaran on the Quality of Fermented Whey-Based Beverages Using Rheological and Mechanical Vibration Damping Techniques
Authors: Rejdlová Anita , Vašina Martin , Lorencová Eva , Hružík Lumír , Salek Richardos Nikolaos
Published: June 2024

In the current study, fermented whey-based beverage models with different levels of blackcurrant juice (0; 10; 20; 100% (w/w)) and furcellaran (0.25% and 0.50% (w/w)) were produced and evaluated. Physicochemical, rheological, mechanical vibration damping, and sensory analyses were performed. During fermentation (48 h), the values of pH, density, and total soluble solids decreased. On the other hand, the ethanol content during fermentation increased up to a final content in the range of 0.92–4.86% (v/v). The addition of furcellaran was effective in terms of sediment content decrease to a level of 0.25% (w/w). In general, the samples exhibited non-Newtonian pseudoplastic behaviour. The sensory analysis revealed that the sample with a composition of 20% (w/w) blackcurrant juice and 0.50% (w/w) furcellaran received the highest score.
Exploring Novel Soliton Solutions to the Time-Fractional Coupled Drinfel’d–Sokolov–Wilson Equation in Industrial Engineering Using Two Efficient Techniques
Authors: Hossain Md Nur , Miah M. Mamun , Alosaimi Moataz , Alsharif Faisal , Kanan Mohammad
Published: June 2024

The time-fractional coupled Drinfel’d–Sokolov–Wilson (DSW) equation is pivotal in soliton theory, especially for water wave mechanics. Its precise description of soliton phenomena in dispersive water waves makes it widely applicable in fluid dynamics and related fields like tsunami prediction, mathematical physics, and plasma physics. In this study, we present novel soliton solutions for the DSW equation, which significantly enhance the accuracy of describing soliton phenomena. To achieve these results, we employed two distinct methods to derive the solutions: the Sardar subequation method, which works with one variable, and the Ω′Ω, 1Ω method which utilizes two variables. These approaches supply significant improvements in efficiency, accuracy, and the ability to explore a broader spectrum of soliton solutions compared to traditional computational methods. By using these techniques, we construct a wide range of wave structures, including rational, trigonometric, and hyperbolic functions. Rigorous validation with Mathematica software 13.1 ensures precision, while dynamic visual representations illustrate soliton solutions with diverse patterns such as dark solitons, multiple dark solitons, singular solitons, multiple singular solitons, kink solitons, bright solitons, and bell-shaped patterns. These findings highlight the effectiveness of these methods in discovering new soliton solutions and supplying deeper insights into the DSW model’s behavior. The novel soliton solutions obtained in this study significantly enhance our understanding of the DSW equation’s underlying dynamics and offer potential applications across various scientific fields.
HitSim: An Efficient Algorithm for Single-Source and Top-k SimRank Computation
Authors: Bai Jing , Zhou Junfeng , Chen Shuotong , Du Ming , Chen Ziyang , Min Mengtao
Published: June 2024

SimRank is a widely used metric for evaluating vertex similarity based on graph topology, with diverse applications such as large-scale graph mining and natural language processing. The objective of the single-source and top-k SimRank query problem is to retrieve the kvertices with the largest SimRank to the source vertex. However, existing algorithms suffer from inefficiency as they require computing SimRank for all vertices to retrieve the top-k results. To address this issue, we propose an algorithm named HitSimthat utilizes a branch and bound strategy for the single-source and top-k query. HitSim initially partitions vertices into distinct sets based on their shortest-meeting lengths to the source vertex. Subsequently, it computes an upper bound of SimRank for each set. If the upper bound of a set is no larger than the minimum value of the current top-k results, HitSim efficiently batch-prunes the unpromising vertices within the set. However, in scenarios where the graph becomes dense, certain sets with large upper bounds may contain numerous vertices with small SimRank, leading to redundant overhead when processing these vertices. To address this issue, we propose an optimized algorithm named HitSim-OPT that computes the upper bound of SimRank for each vertex instead of each set, resulting in a fine-grained and efficient pruning process. The experimental results conducted on six real-world datasets demonstrate the performance of our algorithms in efficiently addressing the single-source and top-k query problem.
Leveraging Machine Learning to Analyze Semantic User Interactions in Visual Analytics
Authors: Jeong Dong Hyun , Jeong Bong Keun , Ji Soo Yeon
Published: June 2024

In the field of visualization, understanding users’ analytical reasoning is important for evaluating the effectiveness of visualization applications. Several studies have been conducted to capture and analyze user interactions to comprehend this reasoning process. However, few have successfully linked these interactions to users’ reasoning processes. This paper introduces an approach that addresses the limitation by correlating semantic user interactions with analysis decisions using an interactive wire transaction analysis system and a visual state transition matrix, both designed as visual analytics applications. The system enables interactive analysis for evaluating financial fraud in wire transactions. It also allows mapping captured user interactions and analytical decisions back onto the visualization to reveal their decision differences. The visual state transition matrix further aids in understanding users’ analytical flows, revealing their decision-making processes. Classification machine learning algorithms are applied to evaluate the effectiveness of our approach in understanding users’ analytical reasoning process by connecting the captured semantic user interactions to their decisions (i.e., suspicious, not suspicious, and inconclusive) on wire transactions. With the algorithms, an average of 72% accuracy is determined to classify the semantic user interactions. For classifying individual decisions, the average accuracy is 70%. Notably, the accuracy for classifying ‘inconclusive’ decisions is 83%. Overall, the proposed approach improves the understanding of users’ analytical decisions and provides a robust method for evaluating user interactions in visualization tools.
Drosophila melanogaster Limostatin and Its Human Ortholog Promote West Nile Virus Infection
Authors: Mead Ezra B. , Lee Miyoung , Trammell Chasity E. , Goodman Alan G.
Published: June 2024

The arbovirus West Nile virus (WNV) is a danger to global health. Spread primarily by mosquitoes, WNV causes about 2000 cases per year in the United States. The natural mosquito immune response controls viral replication so that the host survives but can still transmit the virus. Using the genetically malleable Drosophila melanogaster model, we previously dissected innate immune pathways used to control WNV infection. Specifically, we showed that insulin/IGF-1 signaling (IIS) activates a JAK/STAT-mediated immune response that reduces WNV. However, how factors that regulate IIS in insects control infection has not been identified. D. melanogaster Limostatin (Lst) encodes a peptide hormone that suppresses insulin secretion. Its mammalian ortholog, Neuromedin U (NMU), is a peptide that regulates the production and secretion of insulin from pancreatic beta cells. In this study, we used D. melanogaster and human cell culture models to investigate the roles of these insulin regulators in immune signaling. We found that D. melanogaster Lst mutants, which have elevated insulin-like peptide expression, are less susceptible to WNV infection. Increased levels of insulin-like peptides in these flies result in upregulated JAK/STAT activity, leading to protection from infection. Treatment of human cells with the insulin regulator NMU results in increased WNV replication. Further investigation of methods to target Lst in mosquitoes or NMU in mammals can improve vector control methods and may lead to improved therapeutics for human and animal infection.
Spotted Lanternflies Respond to Natural Pheromone Lures for Mate-Finding and Oviposition
Authors: Cooperband Miriam F. , Murman Kelly M.
Published: June 2024

Using semiochemicals collected from spotted lanternflies Lycorma delicatula (Hemiptera: Fulgoridae) (SLF) and deployed in the field with circle traps, we demonstrated that SLF responded to SLF pheromones: in particular, this was the case for males while seeking mates and for females while ovipositing. The attractants consisted of SLF body extract emitted from diffuser lures and SLF honeydew on burlap ribbons, collected from heavily infested locations. Traps with attractants were deployed in field sites with very light SLF infestations to avoid competing signals of pre-existing aggregations. The number of SLF equivalents emitted by each diffuser per trapping period was used in a dose–response analysis. Three trees per block received either (1) a control hexane lure and a clean ribbon, (2) a lure containing SLF extract and a clean ribbon, or (3) a lure containing SLF extract and a honeydew-laden ribbon. Ten blocks were sampled three times per week for twelve weeks. We found a significant positive dose–response by males to SLF body extract only in the presence of SLF honeydew, indicating a synergistic effect between honeydew volatiles and body volatiles. This dose–response occurred for five weeks after mating started, after which males no longer responded. Subsequently, females had a significant positive dose–response to SLF extract only in the presence of honeydew when oviposition was their primary activity, continuing for two weeks, suggesting that females may use pheromones to aggregate for oviposition. The extract in the absence of honeydew did not result in a positive dose–response, nor did the hexane control. These findings suggest that SLF respond synergistically to the combination of pheromones present in both SLF honeydew and SLF bodies. Thus, combining key components from both sources may aid the development of semiochemical lures for SLF.
Earlier Menarche in Greek Girls Born by Caesarean Section: A Case–Control Study
Authors: Tsinopoulou Vasiliki Rengina , Kotanidou Eleni P. , Athanasiadis Nikolaos , Bacopoulou Flora , Stefanaki Charikleia , Fidani Liana , Galli-Tsinopoulou Assimina , Christoforidis Athanasios
Published: June 2024

Objectives: The purpose of this study was to report on the menarcheal age in girls of Greek origin and assess its potential associations with their demographic and perinatal data, as well as their maternal menarcheal age. Methods: In this case–control study, adolescent girls were recruited between September 2021 and September 2022 from two Pediatric Endocrinology Units, Aristotle University of Thessaloniki, Greece. Eligible participants included Greek girls up to the age of 18 years, with menarche and the absence of chronic disease or chronic medication use. Participants were divided into two groups, the early menarche group and the control group (menarche before or after 11 years of age, respectively). Data included participants’ maternal menarcheal age, their chronological age, place of residence, anthropometric data (at recruitment) and perinatal data (birth order, gestational age, type of delivery, birth weight/length). Results: A total of 100 girls aged 7–17 years (mean age ± SD 12.51 ± 2.59 years) were included in this study. The mean ± SD menarcheal age of the total sample was 11.47 ± 1.55 years (median 11.20 years; range 7.50–16.25 years); 43% had early menarche (median menarcheal age 10.50 years; range 7.50–10.91 years), and 57% had menarche after age 11 (median menarcheal age 12.08 years; range 11.00–16.25 years). The caesarean section rate was significantly (p < 0.001) higher in girls with early menarche (83.7%) than controls, whereas other variables did not differ significantly between groups. Conclusions: This Greek sample demonstrated a relatively young age at menarche with a significant proportion of girls with early menarche; in the latter group, the rate of caesarian sections was significantly higher than controls.
Artificial Intelligence in Coronary Artery Calcium Scoring
Authors: Aromiwura Afolasayo A. , Kalra Dinesh K.
Published: June 2024

Cardiovascular disease (CVD), particularly coronary heart disease (CHD), is the leading cause of death in the US, with a high economic impact. Coronary artery calcium (CAC) is a known marker for CHD and a useful tool for estimating the risk of atherosclerotic cardiovascular disease (ASCVD). Although CACS is recommended for informing the decision to initiate statin therapy, the current standard requires a dedicated CT protocol, which is time-intensive and contributes to radiation exposure. Non-dedicated CT protocols can be taken advantage of to visualize calcium and reduce overall cost and radiation exposure; however, they mainly provide visual estimates of coronary calcium and have disadvantages such as motion artifacts. Artificial intelligence is a growing field involving software that independently performs human-level tasks, and is well suited for improving CACS efficiency and repurposing non-dedicated CT for calcium scoring. We present a review of the current studies on automated CACS across various CT protocols and discuss consideration points in clinical application and some barriers to implementation.