bluuebunny/crossref_metadata_2025 huggingface dataset:
Predictive Analysis of Corrosion Dynamics in Prestressed Concrete Exposed to Chloride Environments
Authors: Pierott Rodrigo Moulin Ribeiro , Garcia Sergio , Kropf Diogo , Figueiredo Karoline , da Costa Bruno Barzellay Ferreira , Amario Mayara , Najjar Mohammad K. , Haddad Assed
Published: August 2024

This study investigates the corrosion behavior of 5 mm diameter prestressed wires in concrete beams under chloride attack, a prevalent issue for coastal infrastructure. The study simulated aggressive chloride environments to understand their impact on structural integrity and service life. Utilizing a combination of advanced digital image correlation (DIC) techniques and a novel machine learning-based predictive model, the research provides a nuanced analysis of the interplay between stress levels, corrosion rates, and concrete strength. Empirical findings reveal a significant correlation between increased prestress levels and accelerated corrosion, indicating a crucial consideration for the design and maintenance of prestressed concrete structures. Notably, this study found that beams with a 95% prestress level exhibited a corrosion rate of 0.64 mm/year, significantly higher than the 0.37 mm/year for non-prestressed beams. The predictive model’s accuracy was validated with a mean squared error of 0.517 and an R2 value of 0.905, offering a valuable tool for quantifying the impact of corrosion. Therefore, the predictive model is a valuable tool for quantifying the impact of corrosion, enhancing the ability to assess and improve the durability of such infrastructure. This study’s insights highlight the necessity for a balanced approach to design and regular monitoring, especially in chloride-rich environments. By helping to develop more resilient construction practices and contributing to sustainable development goals, this study can significantly impact the safety and service life of coastal bridges and structures, aligning with global efforts to create more sustainable and durable infrastructure.
Compositional and Fabrication Cycle Optimization of Ceria-Zirconia-Supported Mo-Based Catalysts for NH3-SCR NOx Reduction
Authors: Spiridigliozzi Luca , Monfreda Viviana , Esposito Serena , Tammaro Olimpia , Blangetti Nicola , Deorsola Fabio Alessandro , Dell’Agli Gianfranco
Published: August 2024

The reduction of nitrogen oxides (NOx), critical pollutants from stationary to mobile sources, mainly relies on the selective catalytic reduction (NH3-SCR) method, employing ammonia to reduce NOx into nitrogen and water. However, conventional catalysts, while effective, pose both environmental and operational challenges. This study investigates ceria-zirconia-supported molybdenum-based catalysts, exploring the effects of zirconium doping and different catalyst synthesis techniques, i.e., co-precipitation and impregnation. The catalytic performance of the differently prepared samples was significantly influenced by the molybdenum incorporation method and the zirconium content within the ceria-zirconia support. Co-precipitation at higher temperatures resulted in catalysts with better structural attributes but slightly lower catalytic activity compared to those prepared via impregnation. Optimal NOx reduction (close to 100%) was observed at a 15 mol% zirconium doping level when using the impregnation method.
Performance of Artificial Diets for Zelus renardii (Hemiptera: Reduviidae) Rearing
Authors: Picciotti Ugo , Valverde-Urrea Miguel , Sefa Valdete , Ragni Marco , Garganese Francesca , Porcelli Francesco
Published: August 2024

Mass production is a prerequisite for using natural enemies in integrated pest management and organic farming. Natural enemies in agroecosystems include predators that prey on insects, which they can subdue while maintaining adequate pest population densities. The Leafhopper Assassin Bug (LAB), Zelus renardii, can be a natural enemy in agroecosystems, selecting its prey for size and mobility. Some of LAB’s prey include Philaenus spumarius (L.), Bactrocera oleae (Rossi), Drosophila suzukii (Matsumura), and Macrohomotoma gladiata Kuwayama, suggesting this reduviid for biocontrol agent in various contexts. We reared LABs for two subsequent broods offering living prey and artificial diets. Our data show that the rearing of Z. renardii is feasible with oligidic, meridic, and holidic artificial formulations. Four artificial diets allowed the complete post-embryonic development of LABs in captivity for two successive generations. The accumulated degree-days (ADDs) accurately predict the growth of LABs based on heat accumulation, estimating that up to three generations could grow per year in captivity at the experimented T°C.
Enhancing Prediction Accuracy of Vessel Arrival Times Using Machine Learning
Authors: Evmides Nicos , Aslam Sheraz , Ramez Tzioyntmprian T. , Michaelides Michalis P. , Herodotou Herodotos
Published: August 2024

Marine transportation accounts for approximately 90% of the total trade managed in international logistics and plays a vital role in many companies’ supply chains. However, en-route factors like weather conditions or piracy incidents often delay scheduled arrivals at destination ports, leading to downstream inefficiencies. Due to the maritime industry’s digital transformation, smart ports and vessels generate vast amounts of data, creating an opportunity to use the latest technologies, like machine and deep learning (ML/DL), to support terminals in their operations. This study proposes a data-driven solution for accurately predicting vessel arrival times using ML/DL techniques, including Deep Neural Networks, K-Nearest Neighbors, Decision Trees, Random Forest, and Extreme Gradient Boosting. This study collects real-world AIS data in the Eastern Mediterranean Sea from a network of public and private AIS base stations. The most relevant features are selected for training and evaluating the six ML/DL models. A comprehensive comparison is also performed against the estimated arrival time provided by shipping agents, a simple calculation-based approach, and four other ML/DL models proposed recently in the literature. The evaluation has revealed that Random Forest achieves the highest performance with an MAE of 99.9 min, closely followed by XGBoost, having an MAE of 105.0 min.
A Consolidated Linearised Progressive Flooding Simulation Method for Onboard Decision Support
Authors: Braidotti Luca , Prpić-Oršić Jasna , Bertagna Serena , Bucci Vittorio
Published: August 2024

In pursuing quick and precise progressive flooding simulations for decision-making support, the linearised method has emerged and undergone refinement in recent years, becoming a reliable tool, especially for onboard decision support. This study consolidates and enhances the modelling approach based on a system of differential-algebraic equations capable of accommodating compartments filled with floodwater. The system can be linearised to permit analytical solutions, facilitating the utilization of larger time increments compared to conventional solvers for differential equations. Performance enhancements are achieved through the implementation of an adaptive time-step mechanism during the integration process. Furthermore, here, a correction coefficient for opening areas is introduced to enable the accurate modelling of free outflow scenarios, thereby mitigating issues associated with the assumption of deeply submerged openings used in governing equations. Experimental validation is conducted to compare the method’s efficacy against recent model-scale tests, specifically emphasising the improvements stemming from the correction for free outflow.
Numerical Simulation of Bionic Underwater Vehicle Morphology Drag Optimisation and Flow Field Noise Analysis
Authors: Huang Xiaoshuang , Han Dongxing , Zhang Ying , Chen Xinjun , Liu Bilin , Kong Xianghong , Jiang Shuxia
Published: August 2024

The study of aquatic organisms’ ectomorphology is important to understanding the mechanisms of efficient swimming and drag reduction in fish. The drag reduction mechanism in fish remains unknown yet is needed for optimising the efficiency of bionic fish. It is thus crucial to conduct drag tests and analyses. In this paper, an optimal dolphin morphological model is constructed taking the beakless porpoise as the research object. A numerical simulation of the dolphin body model is carried out for different combinations of pitch angle and speed adopting computational fluid dynamics, and the flow field noise of the dolphin body model is solved for different speeds using the FW-H equation. When the dolphin model is oriented horizontally, the differential pressure drag accounts for approximately 20–25% of the total drag as airspeed increases. As both the pitch angle and airspeed increase, the differential pressure drag and friction drag decrease with increasing airspeed. Moreover, the acoustic energy is mainly concentrated at low frequencies for both the dolphin and Bluefin-21 models. The dolphin body model has better noise performance than the Bluefin-21 model at the same speed. The optimisation of the external morphology of the bionic underwater submarine and the analysis of the shape drag are thus important for revealing the drag reduction mechanism, reducing noise in the flow field and provide guidance for research on bionic fish.
The Volcanic Rocks and Hydrocarbon Accumulation in the Offshore Indus Basin, Pakistan
Authors: Sun Jing , Liang Jie , Gong Jianming , Liao Jing , Zhao Qingfang , Zhao Chen
Published: August 2024

To analyze the impact of volcanic rocks in the Offshore Indus Basin on hydrocarbon reservoir formation, seismic data interpretation, seismic data inversion, and sea–land correlation analysis were carried out. The results show that, longitudinally, volcanic rocks are mainly distributed at the top of the Cretaceous system or at the bottom of the Paleocene, and carbonate rock platforms or reefs of the Paleocene–Eocene are usually developed on them. On the plane, volcanic rocks are mainly distributed on the Saurashtra High in the southeastern part of the basin. In terms of thickness, the volcanic rocks revealed by drilling in Karachi nearshore are about 70 m thick. We conducted sparse spike inversion for acoustic impedance in the volcanic rock area. The results show that the thickness of the Deccan volcanic rocks in the study area is between 250 and 750 m which is thinning from southeast to northwest. Based on sea–land comparison and comprehensive research, the distribution of volcanic rocks in the Indian Fan Offshore Basin played a constructive role in the Mesozoic oil and gas accumulation in the Indus offshore. Therefore, in the Indian Fan Offshore Basin, attention should be paid to finding Mesozoic self-generated and self-stored hydrocarbon reservoirs and Cenozoic lower-generated and upper-stored hydrocarbon reservoirs.
Effect of Earnings Management on Earnings Quality and Sustainability: Evidence from Gulf Cooperation Council Distressed and Non-Distressed Companies
Authors: Aljifri Khaled , Elrazaz Tariq
Published: August 2024

This study evaluates the effect of earnings management on earnings quality and sustainability in the GCC region, particularly in distressed and non-distressed companies. Studies on earnings quality and sustainability have mostly concentrated on developed markets, with little attention paid to emerging markets like the GCC region. This research is the first to examine how manipulating earnings impacts the quality and sustainability of earnings in distressed and non-distressed companies. This study utilized a unique dataset that represents the GCC region, which has a specific socio-cultural context. We collected data from 839 publicly listed companies in the GCC region between 2011 and 2022 using DataStream®, WorldScope (WS), and Refinitiv Eikon. To test our hypotheses and ensure accuracy, we used three types of regressions (the fixed effects model, OLS, and 2SLS) and conducted robustness and endogeneity tests. The results of this study indicate that accruals-based earnings management has a negative impact on earnings quality for distressed and non-distressed firms but a positive effect on earnings sustainability for both types of companies. The results of this study also find variations in earnings management practices across industries. These findings provide valuable guidance for auditors, investors, and other stakeholders to evaluate the earnings quality and sustainability of distressed and non-distressed companies, benefiting the GCC economy and similar economies.
Exploring Calendar Anomalies and Volatility Dynamics in Cryptocurrencies: A Comparative Analysis of Day-of-the-Week Effects before and during the COVID-19 Pandemic
Authors: Sahu Sonal , Ramírez Alejandro Fonseca , Kim Jong-Min
Published: August 2024

This study investigates calendar anomalies and their impact on returns and volatility patterns in the cryptocurrency market, focusing on day-of-the-week effects before and during the COVID-19 pandemic. Using advanced statistical models from the GARCH family, we analyze the returns of Binance USD, Bitcoin, Binance Coin, Cardano, Dogecoin, Ethereum, Solana, Tether, USD Coin, and Ripple. Our findings reveal significant shifts in volatility dynamics and day-of-the-week effects on returns, challenging the notion of market efficiency. Notably, Bitcoin and Solana began exhibiting day-of-the-week effects during the pandemic, whereas Cardano and Dogecoin did not. During the pandemic, Binance USD, Ethereum, Tether, USD Coin, and Ripple showed multiple days with significant day-of-the-week effects. Notably, positive returns were generally observed on Sundays, whereas a shift to negative returns on Mondays was evident during the COVID-19 period. These patterns suggest that exploitable anomalies persist despite the market’s continuous operation and increasing maturity. The presence of a long-term memory in volatility highlights the need for robust trading strategies. Our research provides valuable insights for investors, traders, regulators, and policymakers, aiding in the development of effective trading strategies, risk management practices, and regulatory policies in the evolving cryptocurrency market.
Nostalgic Geotourism as a New Form of Landscape Presentation: An Application to the Carphatian Mountains
Authors: Tometzová Dana , Jesenský Miloš , Molokáč Mário , Kornecká Enikő
Published: August 2024

In recent years, there has been a surge in interest towards innovative methods of landscape presentation across various tourism sectors, including natural heritage. Geotourism exemplifies this trend, emerging as a distinct form of tourism primarily centered on inanimate elements of nature, accentuating the aesthetic value of landscapes. Presently, geotourism serves as a platform for showcasing landscape along with its historical narrative, contemporary attributes, and, inherently, its evolutionary trajectory. This paper delves into novel avenues within geotourism, introducing the concept of nostalgic geotourism. This concept involves the portrayal of geological heritage through the lens of historical inquiry. The authors employ a multidimensional analysis to forge a robust theoretical framework underpinning the emergence of this unconventional form of tourism dedicated to landscape presentation. Additionally, the paper furnishes a case study conducted in the High Tatras region, featuring a 19th-century guided tour (lecture) on non-living nature. Through this illustration, the theoretical construct of nostalgic geotourism is applied to the locale. This heralds a fresh dimension of tourism reminiscent of traditional nostalgia-based tourism, with a pronounced cultural focus. The innovative concept fosters an increased interest in exploring geological heritage and natural landscapes, while emphasizing their sentimental value.
Soil Quality Assessment and Influencing Factors of Different Land Use Types in Red Bed Desertification Regions: A Case Study of Nanxiong, China
Authors: Si Fengxia , Chen Binghui , Wang Bojun , Li Wenjun , Zhu Chunlin , Fu Jiafang , Yu Bo , Xu Guoliang
Published: August 2024

Soil environmental issues in the red bed region are increasingly conspicuous, underscoring the critical importance of assessing soil quality for the region’s sustainable development and ecosystem security. This study examines six distinct land use types of soils—agricultural land (AL), woodland (WL), shrubland (SL), grassland (GL), bare rock land (BRL), and red bed erosion land (REL)—in the Nanxiong Basin of northern Guangdong Province. This area typifies red bed desertification in South China. Principal component analysis (PCA) was employed to establish a minimum data set (MDS) for calculating the soil quality index (SQI), evaluating soil quality, analyzing influencing factors, and providing suggestions for ecological restoration in desertification areas. The study findings indicate that a minimal data set comprising soil organic matter (SOM), pH, available phosphorus (AP), exchangeable calcium (Ca2+), and available copper (A-Cu) is most suitable for evaluating soil quality in the red bed desertification areas of the humid region in South China. Additionally, we emphasize that exchangeable salt ions and available trace elements should be pivotal considerations in assessing soil quality within desertification areas. Regarding comprehensive soil quality indicators across various land use types, the red bed erosion soils exhibited the lowest quality, followed by those in bare rock areas and forest land. Within the minimal data set, Ca2+ and pH contributed the most to overall soil quality, underscoring the significance of parent rock mineral composition in the red bed desertification areas. Moreover, the combined effects of SOM, A-Cu, and AP on soil quality indicate that anthropogenic land management and use, including fertilization methods and vegetation types, are crucial factors influencing soil quality. Our research holds significant implications for the scientific assessment, application, and enhancement of soil quality in desertification areas.
Study on Wetland Evolution and Landscape Pattern Changes in the Shaanxi Section of the Loess Plateau in the Past 40 Years
Authors: Xue Zhaona , Wang Yiyong , Huang Rong , Yao Linjia
Published: August 2024

The Shaanxi section is the central region of the Loess Plateau. Its unique wetland environment plays an indispensable role in regional ecological environment security. Clarifying the characteristics of wetland changes in the region is an important prerequisite for wetland management and protection. This study, based on the remote sensing data of the Shaanxi section of the Loess Plateau, analyzed the changes in the wetland area and type transfer in this region in 1980, 1990, 2000, 2010 and 2020 using the wetland dynamic degree model, the Markov transfer matrix, the landscape pattern index, and centroid analysis. The results showed that, from 1980 to 2020, the total wetland area and natural wetland area in the Shaanxi section of the Loess Plateau continued to shrink, decreasing by 79.35 km2 and 80.50 km2, respectively, while the artificial wetland area increased by 1.14 km2. Among the regions, Xi’an experienced the most significant reduction, with a total decrease of 83.04 km2 over 40 years, followed by Xianyang City, where the wetland area decreased by 6.50 km2. In contrast, the wetland areas of Yulin City, Weinan City, Yan’an City, Baoji City and Tongchuan City increased slightly. From 1980 to 2020, the change in the wetland types in the Shaanxi section of the Loess Plateau was mainly characterized by transfers between beach lands and river canals. River canals are the primary type of wetland in this region. The degree of fragmentation is the highest in reservoir potholes, while marshes have the largest clumpiness index. Over the same period, the centroid of the wetlands in the Shaanxi section of the Loess Plateau moved from south to north as a whole, although, between 1990 and 2000, the centroid position remained relatively stable. These results provide a theoretical basis and data support for wetland monitoring and protection in the Shaanxi section of the Loess Plateau and also provide a reference for the protection and sustainable development of other inland wetland resources in arid and semi-arid regions.
Association between Outlying Values in Body Condition Indices in Small Mammals and Their Habitats
Authors: Balčiauskas Linas , Balčiauskienė Laima
Published: August 2024

Habitat type and habitat change are very important factors in the body condition of small mammals that inhabit them. The response can be positive, increasing, or the opposite, decreasing body condition. We analyzed outliers of the body condition indices (BCIs) of 12 species trapped in nine different habitats during 1980–2023 in Lithuania, a mid-latitude country. Mixed and fragmented habitats, as well as commensal habitats, could be considered the least suitable for small mammals, based on the highest proportions of underfit and low proportions of best-fit individuals. On the contrary, meadows and disturbed habitats (landfills and cormorant colonies) had the highest proportions of best-fit individuals, while the proportion of under-fit individuals was much lower than expected. We found outliers in the BCI in all species, except for the under-fit harvest mice (Micromys minutus), and in all habitats, though not numerous. The presence of the highest BCI in yellow-necked mice (Apodemus flavicollis) and bank voles (Clethrionomys glareolus) in the disturbed habitats studied and in house mice (Mus musculus) in commensal habitats may be related to the resources provided by these habitats. Our results demonstrate the feasibility of using retrospective small mammal morphometric data to analyze their relationship with habitat.
RETRACTED: Ahmad (2021). Protecting the Rights of Minorities under International Law and Implications of COVID-19: An Overview of the Indian Context. Laws 10: 17
Authors: Ahmad Nehaluddin
Published: August 2024

Laws retracts the article “Protecting the Rights of Minorities under International Law and Implications of COVID-19: An Overview of the Indian Context” (Ahmad 2021), cited above [...]
PolyDexFrame: Deep Reinforcement Learning-Based Pick-and-Place of Objects in Clutter
Authors: Imtiaz Muhammad Babar , Qiao Yuansong , Lee Brian
Published: August 2024

This research study represents a polydexterous deep reinforcement learning-based pick-and-place framework for industrial clutter scenarios. In the proposed framework, the agent tends to learn the pick-and-place of regularly and irregularly shaped objects in clutter by using the sequential combination of prehensile and non-prehensile robotic manipulations involving different robotic grippers in a completely self-supervised manner. The problem was tackled as a reinforcement learning problem; after the Markov decision process (MDP) was designed, the off-policy model-free Q-learning algorithm was deployed using deep Q-networks as a Q-function approximator. Four distinct robotic manipulations, i.e., grasp from the prehensile manipulation category and inward slide, outward slide, and suction grip from the non-prehensile manipulation category were considered as actions. The Q-function comprised four fully convolutional networks (FCN) corresponding to each action based on memory-efficient DenseNet-121 variants outputting pixel-wise maps of action-values jointly trained via the pixel-wise parametrization technique. Rewards were awarded according to the status of the action performed, and backpropagation was conducted accordingly for the FCN generating the maximum Q-value. The results showed that the agent learned the sequential combination of the polydexterous prehensile and non-prehensile manipulations, where the non-prehensile manipulations increased the possibility of prehensile manipulations. We achieved promising results in comparison to the baselines, differently designed variants, and density-based testing clutter.
Task-Importance-Oriented Task Selection and Allocation Scheme for Mobile Crowdsensing
Authors: Chang Sha , Wu Yahui , Deng Su , Ma Wubin , Zhou Haohao
Published: August 2024

In Mobile Crowdsensing (MCS), sensing tasks have different impacts and contributions to the whole system or specific targets, so the importance of the tasks is different. Since resources for performing tasks are usually limited, prioritizing the allocation of resources to more important tasks can ensure that key data or information can be collected promptly and accurately, thus improving overall efficiency and performance. Therefore, it is very important to consider the importance of tasks in the task selection and allocation of MCS. In this paper, a task queue is established, the importance of tasks, the ability of participants to perform tasks, and the stability of the task queue are considered, and a novel task selection and allocation scheme (TSAS) in the MCS system is designed. This scheme introduces the Lyapunov optimization method, which can be used to dynamically keep the task queue stable, balance the execution ability of participants and the system load, and perform more important tasks in different system states, even when the participants are limited. In addition, the Double Deep Q-Network (DDQN) method is introduced to improve on the traditional solution of the Lyapunov optimization problem, so this scheme has a certain predictive ability and foresight on the impact of future system states. This paper also proposes action-masking and iterative training methods for the MCS system, which can accelerate the training process of the neural network in the DDQN and improve the training effect. Experiments show that the TSAS based on the Lyapunov optimization method and DDQN performs better than other algorithms, considering the long-term stability of the queue, the number and importance of tasks to be executed, and the congestion degree of tasks.
EVFL: Towards Efficient Verifiable Federated Learning via Parameter Reuse and Adaptive Sparsification
Authors: Wu Jianping , Wu Chunming , Chen Chaochao , Jin Jiahe , Zhou Chuan
Published: August 2024

Federated learning (FL) demonstrates significant potential in Industrial Internet of Things (IIoT) settings, as it allows multiple institutions to jointly construct a shared learning model by exchanging model parameters or gradient updates without the need to transmit raw data. However, FL faces risks related to data poisoning and model poisoning. To address these issues, we propose an efficient verifiable federated learning (EVFL) method, which integrates adaptive gradient sparsification (AdaGS), Boneh–Lynn–Shacham (BLS) signatures, and fully homomorphic encryption (FHE). The combination of BLS signatures and the AdaGS algorithm is used to build a secure aggregation protocol. These protocols verify the integrity of parameters uploaded by industrial agents and the consistency of the server’s aggregation results. Simulation experiments demonstrate that the AdaGS algorithm significantly reduces verification overhead through parameter sparsification and reuse. Our proposed algorithm achieves better verification efficiency compared to existing solutions.
DiFastBit: Transaction Differentiation Scheme to Avoid Double-Spending for Fast Bitcoin Payments
Authors: Melo David , Pomares-Hernández Saúl Eduardo , Rodríguez-Henríquez Lil María , Pérez-Sansalvador Julio César
Published: August 2024

Bitcoin is a payment system that generates a decentralized digital currency without ensuring temporal constraints in its transactions; therefore, it is vulnerable to double-spending attacks. Karame has proposed a formalization for a successful double-spending attack based on meeting three requirements. This focuses on fast payment scenarios where the product is delivered immediately after the payment is announced in the mempool, without waiting for transaction confirmation. This scenario is key in Bitcoin to increase the probability of a successful double-spending attack. Different approaches have been proposed to mitigate these attacks by addressing one or more of Karame’s three requirements. These include the following: flooding every transaction without restrictions, introducing listeners/observers, avoiding isolation by blocking incoming connections, penalizing malicious users by revealing their identity, and using machine learning and bio-inspired techniques. However, to our knowledge, no proposal deterministically avoids double-spending attacks in fast payment scenarios. In this paper, we introduce DiFastBit: a distributed transaction differentiation scheme that shields Bitcoin from double-spending attacks in fast payment scenarios. To achieve this, we modeled Bitcoin from a distributed perspective of events and processes, reformulated Karame’s requirements based on Lamport’s happened-before relation (HBR), and introduced a new theorem that consolidates the reformulated requirements and establishes the necessary conditions for a successful attack on fast Bitcoin payments. Finally, we introduce the specifications for DiFastBit, formally prove its correctness, and analyze DiFastBit’s confirmation time.
Investigating Oscillatory Behavior in Third-Order Neutral Differential Equations with Canonical Operators
Authors: Alsharidi Abdulaziz Khalid , Muhib Ali
Published: August 2024

In this study, we aim to set new criteria regarding the asymptotic behavior of the neutral differential equation of the third order. These criteria are designed to ensure that this equation is oscillatory using comparisons with first-order differential equations and Riccati substitution. The results we obtained improve some of the results found in the literature. Some examples are provided to illustrate the applicability of our results and compare them with results found in some previous studies.
Trend in Infective Endocarditis in Bulgaria: Characteristics and Outcome, 17-Years, Single Center Experience
Authors: Dobreva-Yatseva Bistra , Nikolov Fedya , Raycheva Ralitsa , Uchikov Petar , Tokmakova Mariya
Published: August 2024

Background: Infective endocarditis (IE) remains a difficult disease to diagnose and treat, with a persistently high mortality rate. There is a lack of recent data on IE in Bulgaria over the last decades. Methods: This study is retrospective, single-centered, and includes 270 patients diagnosed with IE for the period 2005–2021. We compared two periods, 2005–2015 (n = 119) and 2016–2021 (n = 151), to find the characteristics changes. Results: The study included 177 (65.5%) male patients. In the second period, there is a significant increase in age from 62 (44–73) to 67 (53–75), (p = 0.023); in the Charlson comorbidities index (CCI) from 3 (1–4) to 4 (2–6), (p = 0.000); in cases with chronic kidney diseases (CKDs) from 15 (12.6%) to 55 (36.9%), (p = 0.001); coronary arterial diseases (CADs) from 20 (16.85%) to 44 (29.1%), (p = 0.018); and atrial fibrillation (AF) from 13 (10.9%) to 36 (23.8%), (p = 0.006). Ejection fraction decreased significantly in the second period from 63 (56–70) to 59 (51–66), (p = 0.000). Almost half of the patients 123 (45.6%) had no known predisposing cardiac condition, and 125 (46.3%) had an unknown port of entry. IE was community-acquired in 174 (64.4%), healthcare-associated in 72 (26.7%), and injection-drug-use-related IE in 24 (8.9%). The study population included 183 (67.8%) native valve IE, 85 (31.5%) prosthetic IE, and 2 (0.74%) intracardiac-device-related IE. The hemocultures were positive in 159 (59.6%), and the most frequent pathogenic agent was staphylococci—89 (33.3%) (Staphylococcus aureus—44 (16.5%) and coagulase negative staphylococci—45 (16.8%)). Only 54 (20%) of patients underwent early surgery. The all-cause 30-day mortality rate was 67 (24.8%). There is no significant difference between the two periods in terms of the characteristics listed above. Conclusions: The profile of IE in Bulgaria has changed with increasing age and comorbidity, changing predisposing cardiac conditions, and entry door. The most common pathogen was the Staphylococcus spp. The 30-day mortality rate remains high.
Long-Term Prevalence of Fungal Keratitis at a Swiss Tertiary Eye Clinic
Authors: Bajka Anahita , Said Sadiq , Quiblier Chantal , Schulthess Bettina , Reinhold Ilana , Barthelmes Daniel , Zweifel Sandrine Anne , Blaser Frank
Published: August 2024

Fungal keratitis is a rare yet severe infection of the cornea. Fungal species distribution depends on the climate and socioeconomic status and can show regional variation. This retrospective single-center study was conducted at a tertiary eye care center and the collaborating Institute of Medical Microbiology in Switzerland. On investigating all fungal-positive corneal scrapings and contact lens assessments of patients with keratitis from January 2012 to December 2023, 206 patients were identified, of which 113 (54.9%) were female. The median age was 38 (IQR 29.8, [18–93]), and 154 (74.8%) applied contact lenses. The most commonly found pathogen was Candida spp., followed by Fusarium spp. Molds were 1.8 times more common than yeasts. Linear regression showed no significant increase or decrease in the infection rate over time (p = 0.5). In addition, 10 patients (4.9%) were found to have coinfections with Acanthamoeba, 11 (5.3%) with HSV-1, none with HSV-2, and 4 (1.9%) with VZV. This study provides a long-term overview of fungal-positive corneal scrapings and contact lens specimens of patients with fungal keratitis. Based on our results, coinfections with Acanthamoeba, HSV, and VZV are frequent, especially in patients wearing contact lenses. Thus, wearing contact lenses may facilitate coinfection in fungal keratitis.
Effects of Deep Tillage on Wheat Regarding Soil Fertility and Rhizosphere Microbial Community
Authors: Sui Junkang , Wang Chenyu , Ren Changqing , Hou Feifan , Zhang Yuxuan , Shang Xueting , Zhao Qiqi , Hua Xuewen , Liu Xunli , Zhang Hengjia
Published: August 2024

Wheat production is intrinsically linked to global food security. However, wheat cultivation is constrained by the progressive degradation of soil conditions resulting from the continuous application of fertilizers. This study aimed to examine the effects of deep tillage on rhizosphere soil microbial communities and their potential role in improving soil quality, given that the specific mechanisms driving these observed benefits remain unclear. Soil fertility in this research was evaluated through the analysis of various soil parameters, including total nitrogen, total phosphorus, total potassium, available phosphorus, and available potassium, among others. The high-throughput sequencing technique was utilized to examine the rhizosphere microbial community associated with deep tillage wheat. The findings indicated that deep tillage cultivation of wheat led to reduced fertility levels in the 0–20 cm soil layer in comparison with non-deep tillage cultivation. A sequencing analysis indicated that Acidobacteria and Proteobacteria are the dominant bacterial phyla, with Proteobacteria being significantly more abundant in the deep tillage group. The dominant fungal phyla identified were Ascomycota, Mortierellomycota, and Basidiomycota. Among bacterial genera, Arthrobacter, Bacillus, and Nocardioides were predominant, with Arthrobacter showing a significantly higher presence in the deep tillage group. The predominant fungal genera included Mortierella, Alternaria, Schizothecium, and Cladosporium. Deep tillage cultivation has the potential to enhance soil quality and boost crop productivity through the modulation of soil microbial community structure.
Genomic Analysis of a Novel Torradovirus “Rehmannia Torradovirus Virus”: Two Distinct Variants Infecting Rehmannia glutinosa
Authors: Qin Yanhong , Lu Shuhao , Wen Yi , Li Shaojian , Gao Suxia , Zhang Desheng , Li Xuemeng , Yang Jin , Gu Li , Li Mingjie , Wang Fei , Lu Chuantao
Published: August 2024

Rehmannia glutinosa, a crucial medicinal plant native to China, is extensively cultivated across East Asia. We used high-throughput sequencing to identify viruses infecting R. glutinosa with mosaic, leaf yellowing, and necrotic symptoms. A novel Torradovirus, which we tentatively named “Rehmannia torradovirus virus” (ReTV), was identified. The complete sequences were obtained through reverse-transcription polymerase chain reaction (RT-PCR), 5′ and 3′ rapid amplification of cDNA ends, and Sanger sequencing. The amino acid sequence alignment between the ReTV-52 isolate and known Torradovirus species in the Pro-Pol and coat protein regions were 51.3–73.3% and 37.1–68.1%, respectively. Meanwhile, the amino acid sequence alignment between the ReTV-8 isolate and known Torradovirus species in the Pro-Pol and coat protein regions were 52.7–72.8% and 36.8–67.5%, respectively. The sequence analysis classified ten ReTV strains into two variants. The ReTV-52 genome has two RNA segments of 6939 and 4569 nucleotides, while that of ReTV-8 consists of two RNA segments containing 6889 and 4662 nucleotides. Sequence comparisons and phylogenetic analysis showed ReTV strains clustered within the Torradovirus, exhibiting the closet relation to the squash chlorotic leaf spot virus. The RT-PCR results showed a 100% ReTV detection rate in all 60 R. glutinosa samples. Therefore, ReTV should be classified as a novel Torradovirus species. ReTV is potentially dangerous to R. glutinosa, and necessitating monitoring this virus in the field.
Synthetic or Natural (Bio-Based) Hydroxyapatite? A Systematic Comparison between Biomimetic Nanostructured Coatings Produced by Ionized Jet Deposition
Authors: Montesissa Matteo , Sassoni Enrico , Boi Marco , Borciani Giorgia , Boanini Elisa , Graziani Gabriela
Published: August 2024

Calcium phosphate (CaP)-based materials are largely explored in orthopedics, to increase osseointegration of the prostheses and specifically in spine surgery, to permit better fusion. To address these aims, nanostructured biogenic apatite coatings are emerging, since they better mimic the characteristics of the host tissue, thus potentially being better candidates compared to their synthetic counterpart. Here, we compare hydroxyapatite (HA) nanostructured coatings, obtained by ionized jet deposition, starting from synthetic and natural sources. The starting materials and the corresponding films are characterized and compared from a compositional and morphological point of view, then their stability is studied after post-treatment annealing. Although all the films are formed by globular aggregates and show morphological features at different scales (from nano to micro), significant differences are found in composition between the synthetic and naturally derived HA in terms of magnesium and sodium content, carbonate substitution and Ca/P ratio, while differences between the coatings obtained by the different natural HA sources are minor. In addition, the shape of the aggregates is also target-dependent. All coatings have a good stability after over 14 days of immersion in medium, with natural apatite coatings showing a better behavior, as no cracking and detachments are observed during immersion. Based on these results, both synthetic and naturally derived apatitic materials appear promising for applications in spine surgery, with coatings from natural sources possessing physiochemical properties more similar to the mineral phase of the human bone tissue.
Human Serum Albumin Protein Corona in Prussian Blue Nanoparticles
Authors: Colombi Chiara , Dacarro Giacomo , Diaz Fernandez Yuri Antonio , Taglietti Angelo , Pallavicini Piersandro , Doveri Lavinia
Published: August 2024

Prussian Blue nanoparticles (PBnps) are now popular in nanomedicine thanks to the FDA approval of PB. Despite the numerous papers suggesting or describing the in vivo use of PBnps, no studies have been carried out on the formation of a protein corona on the PBnp surface and its stabilizing role. In this paper, we studied qualitatively and quantitatively the corona formed by the most abundant protein of blood, human serum albumin (HSA). Cubic PBnps (41 nm side), prepared in citric acid solution at PB concentration 5 × 10−4 M, readily form a protein corona by redissolving ultracentrifuged PBnp pellets in HSA solutions, with CHSA ranging from 0.025 to 7.0 mg/mL. The basic decomposition of PBnp@HSA was studied in phosphate buffer at the physiological pH value of 7.4. Increased stability with respect to uncoated PBnps was observed at all concentrations, but a minimum CHSA value of 3.0 mg/mL was determined to obtain stability identical to that observed at serum-like HSA concentrations (35–50 mg/mL). Using a modified Lowry protocol, the quantity of firmly bound HSA in the protein corona (hard corona) was determined for all the CHSA used in the PBnp@HSA synthesis, finding increasing quantities with increasing CHSA. In particular, an HSA/PBnp number in the 1500–2300 range was found for CHSA 3.0–7.0 mg/mL, largely exceeding the 180 HSA/PBnp value calculated for an HSA monolayer on a PBnp. Finally, the stabilization brought by the HSA corona allowed us to carry out pH-spectrophotometric titrations on PBnp@HSA in the 3.5-9-0 pH range, revealing a pKa value of 6.68 for the water molecules bound to the Fe3+ centers on the PBnp surface, whose deprotonation is responsible for the blue-shift of the PBnp band from 706 nm (acidic solution) to 685 nm (basic solution).
Geometry-Tuned Optical Absorption Spectra of the Coupled Quantum Dot–Double Quantum Ring Structure
Authors: Bejan Doina , Stan Cristina
Published: August 2024

We investigate the energy spectra and optical absorption of a 3D quantum dot–double quantum ring structure of GaAs/Al0.3Ga0.7As with adjustable geometrical parameters. In the effective mass approximation, we perform 3D numerical computations using as height profile a superposition of three Gaussian functions. Independent variations of height and width of the dot and of the rings and also of the dot–rings distance determine particular responses, useful in practical applications. We consider that a suitable manipulation of the geometrical parameters of this type of quantum coupling offer a variety of responses and, more important, the possibility of a fine adjusting in energy spectra and in the opportunity of choosing definite absorption domains, properties required for the improvement of the performances of optoelectronic devices.
Nifedipine Improves the Ketogenic Diet Effect on Insulin-Resistance-Induced Cognitive Dysfunction in Rats
Authors: Abdel-Kareem Nancy M. , Elshazly Shimaa M. , Abd El Fattah May A. , Aldahish Afaf A. , Zaitone Sawsan A. , Ali Sahar K. , Abd El-Haleim Enas A.
Published: August 2024

Insulin resistance, induced by high fructose consumption, affects cognitive function negatively. Nifedipine may be suggested for neurological disorders. This study aimed to assess the effect of nifedipine with either a normal diet (ND) or a ketogenic diet (KD) in cognitive dysfunction. Male Wistar rats received 10% fructose in drinking water for 8 weeks to induce insulin resistance. Rats received nifedipine (5.2 mg/kg/day; p.o.) later with ND or KD for an additional five weeks. One and two-way ANOVAs were used in analyzing the data. Reversion to the ND improved insulin resistance and lipid profile, besides brain-derived neurotrophic factor (BDNF), glycogen synthase kinase-3 beta (GSK3β), and insulin-degrading enzyme (IDE) levels. Rats fed KD alone and those that received nifedipine with KD did not show similar improvement in the previously mentioned parameters as the ND group. However, nifedipine-ND rats showed improvement in cognitive behavior and insulin resistance. Treatment with nifedipine-KD ameliorated GSK3β, amyloid β (Aβ), and tau protein levels. As the nifedipine-KD combination succeeded in diminishing the accumulated Aβ and tau protein, KD may be used for a while due to its side effects, then nifedipine treatment could be continued with an ND. This conclusion is based on the finding that this combination mitigated insulin resistance with the associated improved behavior.
The Association between Statin Use and Reduced Migraine Likelihood: A Comprehensive Analysis of Migraine Subtypes and Statin Types in a Nationwide Korean Cohort
Authors: Kang Ho Suk , Kim Joo-Hee , Kim Ji Hee , Bang Woo Jin , Yoo Dae Myoung , Lee Na-Eun , Han Kyeong Min , Kim Nan Young , Choi Hyo Geun , Min Kyueng-Whan , Kwon Mi Jung
Published: August 2024

Despite growing interest in the preventive effects of statins, as lipid-lowering agents, on migraine attacks, comprehensive nationwide studies comparing migraine likelihood between statin users and controls are lacking. Our nested case–control study within the Korean National Health Insurance Service-Health Screening Cohort (2002–2019) investigated this association using 38,957 migraine patients and 155,828 controls, considering migraine subtypes (with/without aura) and statin types (lipophilic vs. hydrophilic). Using propensity score matching and adjusting for confounders, statin use was linked to reduced migraine likelihood overall (odds ratio (OR) 0.93), particularly for migraines with aura (OR 0.75) and without aura (OR 0.94). Lipophilic statins were effective for both subtypes, while hydrophilic statins mainly reduced the likelihood of migraines without aura. Subgroup analyses showed consistent benefits across demographics, but varied effectiveness based on weight, smoking, alcohol use, hemoglobin levels, and dyslipidemia history. In summary, this nationwide cohort study suggests that statin use may reduce migraine likelihood among Korean adults across diverse demographics and clinical profiles, but varied effectiveness based on certain lifestyle and comorbidity factors underscores the importance of considering individual patient profiles when assessing the potential benefits of statin therapy for migraine prevention.
Development of Orodispersible Tablets with Solid Dispersions of Fenofibrate and Co-Processed Mesoporous Silica for Improved Dissolution
Authors: Baumgartner Ana , Planinšek Odon
Published: August 2024

Poor water solubility is an important challenge in the development of oral patient-friendly solid dosage forms. This study aimed to prepare orodispersible tablets with solid dispersions of a poorly water-soluble drug fenofibrate and a co-processed excipient consisting of mesoporous silica and isomalt. This co-processed excipient, developed in a previous study, exhibited improved flow and compression properties compared to pure silica while maintaining a high specific surface area for drug adsorption. Rotary evaporation was used to formulate solid dispersions with different amounts of fenofibrate, which were evaluated for solid state properties and drug release. The solid dispersion with 30% fenofibrate showed no signs of crystallinity and had a significantly improved dissolution rate, making it the optimal sample for formulation or orodispersible tablets. The aim was to produce tablets with minimal amounts of additional excipients while achieving a drug release profile similar to the uncompressed solid dispersion. The compressed formulations met the requirements for orodispersible tablets in terms of disintegration time, and the drug release from best formulation approximated the profile of uncompressed solid dispersion. Future research should focus on reducing the disintegration time and tablet size to enhance patient acceptability further.