bluuebunny/crossref_metadata_2025 huggingface dataset:
Fast, Simple, and Sensitive Voltammetric Measurements of Acyclovir in Real Samples via Boron-Doped Diamond Electrode
Authors: Gorylewski Damian , Tyszczuk-Rotko Katarzyna , Wójciak Magdalena , Sowa Ireneusz
Published: September 2024

The voltammetric acyclovir (ACV) trace-level determination procedure has been introduced. This is the first time that a commercially available boron-doped diamond electrode (BDDE) coupled with differential-pulse voltammetry (DPV) has been used for this purpose. The commercially available BDDE is characterized by a short response time, low background current, and very good analytical parameters of ACV determination. Ultimately, DPV measurements using the BDDE in 0.075 mol L−1 PBS with a pH of 7.2 under optimized conditions achieved the lowest detection limit (LOD = 0.0299 nmol L−1) reported in the literature for voltammetric procedures. Moreover, it is highly resistant to the presence of various interfering agents and has been used to analyze pharmaceutical and municipal wastewater samples. The obtained results are consistent with measurements made using chromatographic reference methods.
Research on Fault Diagnosis Method with Adaptive Artificial Gorilla Troops Optimization Optimized Variational Mode Decomposition and Support Vector Machine Parameters
Authors: Fang Ting , Ma Long , Zhang Hongkai
Published: September 2024

To address the issue of intelligent optimization algorithms being prone to local optima, resulting in insufficient feature extraction and low fault-type recognition rates when optimizing Variational Mode Decomposition and Support Vector Machine parameters, this paper proposes a fault diagnosis method based on an improved Artificial Gorilla Troops Optimization algorithm. The Artificial Gorilla Troops Optimization algorithm was enhanced using Logistic chaotic mapping, a linear decreasing weight factor, the global exploration strategy of the Osprey Optimization Algorithm, and the Levy flight strategy, improving its ability to escape local optima, adaptability, and convergence accuracy. This algorithm was used to optimize the parameters of Variational Mode Decomposition and Support Vector Machine for fault diagnosis. Experiments on fault diagnosis with two datasets of different sample sizes showed that the proposed method achieved a diagnostic accuracy of no less than 98% for samples of varying sizes, with stable and reliable results.
Analytical Modeling and Experimental Validation of the Coefficient of Friction in AlSi10Mg-SiC Composites
Authors: Iftikhar Saba , Kolev Mihail , Kolev Dimitar
Published: September 2024

Recognizing the lightweight nature and superior tribological properties of Al-based metal matrix composites, this study introduces a novel analytical model based on polynomial approximations, offering new insights into the mechanisms of dry friction in AlSi10Mg-SiC composite materials. Key findings highlight a significant reduction in the coefficient of friction (COF) and oscillation amplitudes in SiC-reinforced composites, indicating superior tribological performance compared to their unreinforced counterparts. This behavior is attributed to the effective distribution of SiC particles within the aluminum matrix, which mitigates the stick–slip motion commonly observed under dry sliding conditions. Importantly, the model using polynomial approximations is noted for its simplicity and ease of implementation in practice. The study’s conclusions not only underscore the benefits of SiC reinforcement in enhancing wear resistance but also contribute to the broader field of materials science by providing a robust framework for the predictive modeling of COF in various composite systems.
Design and Testing of a Fully Automatic Aquatic Plant Combing Machine for Crab Farming
Authors: Yuan Shijie , Xu Jintao , Yuan Hao , Ku Jinsheng , Liu Zexin
Published: September 2024

To meet the requirements of the crab growth environment regarding aquatic plant density and improve the efficiency of aquatic plant clearing, this paper shows the development process of a fully automatic aquatic plant combing machine for crab farming. It proposed the use of torsion spring hooks to replace traditional cutting blades to break tangled aquatic plants, reducing the length of aquatic plants in dense areas and thus controlling the density of aquatic plants in crab ponds. Through theoretical analysis and calculation of the torsion spring hooks, it was ensured that they could meet the design requirements, and transient dynamic simulation tests were conducted based on ANSYS. Finally, experimental verification was carried out. The performance test results of the torsion spring hooks showed that the torsion force generated within a certain torsion angle range could break the aquatic plant, and obstacles could be avoided through self-deformation. The water performance test results showed that the average clearing efficiency of the whole machine for aquatic plants was 4.92 mu/h, the missed clearing rate of aquatic plants was 0.44%, and the crab injury rate was 0.028%. The design of this machine can provide a reference for the development of aquatic plant harvesters for crab farming.
A Novel Integration of Data-Driven Rule Generation and Computational Argumentation for Enhanced Explainable AI
Authors: Rizzo Lucas , Verda Damiano , Berretta Serena , Longo Luca
Published: September 2024

Explainable Artificial Intelligence (XAI) is a research area that clarifies AI decision-making processes to build user trust and promote responsible AI. Hence, a key scientific challenge in XAI is the development of methods that generate transparent and interpretable explanations while maintaining scalability and effectiveness in complex scenarios. Rule-based methods in XAI generate rules that can potentially explain AI inferences, yet they can also become convoluted in large scenarios, hindering their readability and scalability. Moreover, they often lack contrastive explanations, leaving users uncertain why specific predictions are preferred. To address this scientific problem, we explore the integration of computational argumentation—a sub-field of AI that models reasoning processes through defeasibility—into rule-based XAI systems. Computational argumentation enables arguments modelled from rules to be retracted based on new evidence. This makes it a promising approach to enhancing rule-based methods for creating more explainable AI systems. Nonetheless, research on their integration remains limited despite the appealing properties of rule-based systems and computational argumentation. Therefore, this study also addresses the applied challenge of implementing such an integration within practical AI tools. The study employs the Logic Learning Machine (LLM), a specific rule-extraction technique, and presents a modular design that integrates input rules into a structured argumentation framework using state-of-the-art computational argumentation methods. Experiments conducted on binary classification problems using various datasets from the UCI Machine Learning Repository demonstrate the effectiveness of this integration. The LLM technique excelled in producing a manageable number of if-then rules with a small number of premises while maintaining high inferential capacity for all datasets. In turn, argument-based models achieved comparable results to those derived directly from if-then rules, leveraging a concise set of rules and excelling in explainability. In summary, this paper introduces a novel approach for efficiently and automatically generating arguments and their interactions from data, addressing both scientific and applied challenges in advancing the application and deployment of argumentation systems in XAI.
Enhancing Predictive Models for On-Street Parking Occupancy: Integrating Adaptive GCN and GRU with Household Categories and POI Factors
Authors: Zhao Xiaohang , Zhang Mingyuan
Published: September 2024

Accurate predictions of parking occupancy are vital for navigation and autonomous transport systems. This research introduces a deep learning mode, AGCRU, which integrates Adaptive Graph Convolutional Networks (GCNs) with Gated Recurrent Units (GRUs) for predicting on-street parking occupancy. By leveraging real-world data from Melbourne, the proposed model utilizes on-street parking sensors to capture both temporal and spatial dynamics of parking behaviors. The AGCRU model is enhanced with the inclusion of Points of Interest (POIs) and housing data to refine its predictive accuracy based on spatial relationships and parking habits. Notably, the model demonstrates a mean absolute error (MAE) of 0.0156 at 15 min, 0.0330 at 30 min, and 0.0558 at 60 min; root mean square error (RMSE) values are 0.0244, 0.0665, and 0.1003 for these intervals, respectively. The mean absolute percentage error (MAPE) for these intervals is 1.5561%, 3.3071%, and 5.5810%. These metrics, considerably lower than those from traditional and competing models, indicate the high efficiency and accuracy of the AGCRU model in an urban setting. This demonstrates the model as a tool for enhancing urban parking management and planning strategies.
A New Predictive Method for Classification Tasks in Machine Learning: Multi-Class Multi-Label Logistic Model Tree (MMLMT)
Authors: Ghasemkhani Bita , Balbal Kadriye Filiz , Birant Derya
Published: September 2024

This paper introduces a novel classification method for multi-class multi-label datasets, named multi-class multi-label logistic model tree (MMLMT). Our approach supports multi-label learning to predict multiple class labels simultaneously, thereby enhancing the model’s capacity to capture complex relationships within the data. The primary goal is to improve the accuracy of classification tasks involving multiple classes and labels. MMLMT integrates the logistic regression (LR) and decision tree (DT) algorithms, yielding interpretable models with high predictive performance. By combining the strengths of LR and DT, our method offers a flexible and powerful framework for handling multi-class multi-label data. Extensive experiments demonstrated the effectiveness of MMLMT across a range of well-known datasets with an average accuracy of 85.90%. Furthermore, our method achieved an average of 9.87% improvement compared to the results of state-of-the-art studies in the literature. These results highlight MMLMT’s potential as a valuable approach to multi-label learning.
Comparative Analysis of Space Vector Pulse-Width Modulation Techniques of Three-Phase Inverter to Minimize Common Mode Voltage and/or Switching Losses
Authors: Tawfiq Kotb B. , Sergeant Peter , Mansour Arafa S.
Published: September 2024

Inverter-based systems encounter significant challenges in mitigating common-mode voltage (CMV) and minimizing inverter losses. Despite various space vector pulse-width modulation (SVPWM) techniques proposed to address these issues, a comprehensive comparative analysis has been lacking. This paper addresses this gap through an experimental and simulation-based evaluation of nine SVPWM techniques. A new discontinuous SVPWM technique, DSVPWM-K4, is introduced, which involves reversing the use of the two zero vectors in DSVPWM-K3. DSVPWM-K3 delivers superior performance in terms of CMV reduction, total harmonic distortion (THD), and inverter losses across all modulation indices (MI = 1, 0.75, 0.5, and 0.25), making it the most effective overall. Although DSVPWM-K4 is a novel approach, it ranks second in effectiveness. The RSPWM technique achieves the lowest CMV with a zero peak-to-peak value but is most effective at lower modulation indices (0.25 and 0.5) due to higher harmonic distortion at higher modulation indices. AZSPWM performs optimally at higher modulation indices, providing a 66.66% reduction in CMV compared to continuous SVPWM and significantly lower THD compared to RSPWM. In contrast, NSPWM exhibits nearly double the THD compared to continuous SVPWM.
Optimal Financing Strategy in a Dual-Channel Supply Chain with Agricultural Product
Authors: Deng Liurui , Yu Xiwei
Published: September 2024

This study models a two-stage agricultural supply chain consisting of a financially constrained manufacturer of agricultural products and a financially stable retailer. We examine two supply chain structures: traditional and dual channel. Our analysis centers on the effects of consumer green preferences, consumer sensitivity to the freshness of agricultural products, and substitution rate between green and non-green agricultural products on the profitability of supply chain members. The purpose of this work is to study the optimal financing strategy for companies producing both regular and organic products simultaneously. We analyze optimal financing strategies for the manufacturer using three models: bank financing, internal debt financing, and internal equity financing. Our results indicate that in both traditional and dual-channel supply chains, increased consumer green preferences or greater sensitivity to the freshness of agricultural products improve supply chain profitability, while a higher substitution rate between green and non-green products reduces profits. Additionally, the manufacturer prefers internal debt financing when consumer environmental awareness is low. Conversely, as consumer environmental awareness increases, internal equity financing becomes more profitable. These findings offer valuable insights for agricultural product manufacturers facing financial constraints, assisting them in selecting the most appropriate financing model.
A Sustainable Supply Chain Model with Variable Production Rate and Remanufacturing for Imperfect Production Inventory System under Learning in Fuzzy Environment
Authors: Alsaedi Basim S. O.
Published: September 2024

In the present paper, a sustainable supply chain model is investigated with a variable production rate and remanufacturing for the production of defective items under the effect of learning fuzzy theory, where the lower and upper variations in fuzzy demand rate are affected by learning parameters and backorders are also allowed. Our proposed model reveals a springy manufacturing inventory organization that makes various types of items, and imperfect items can be created through the method of manufacturing things in a fuzzy environment. When the screening process is completed, defective items are remanufactured immediately, and a limited financial plan and space limitations are assumed concerning the product assembly. We minimized the total fuzzy inventory cost with different distributions (beta, triangular, double triangular, uniform, and χ2 (chi−square)) concerning the production rate, lot size, and backorder under learning in a fuzzy environment where the costs of screening, manufacturing, carrying, carbon emissions, backorders, and remanufacturing are included. The Kuhn–Tucker optimization technique is applied to solve non-linear equations that are based on some distributions. Numerical examples, sensitivity analysis, managerial insights and observations, limitations, future work, and applications are provided for the validation of our proposed model, and the industrial scope of this proposed work is included.
Dual Transformation of Auxiliary Variables by Using Outliers in Stratified Random Sampling
Authors: Alomair Mohammed Ahmed , Daraz Umer
Published: September 2024

To estimate the finite population variance of the study variable, this paper proposes an improved class of efficient estimators using different transformations. When both the minimum and maximum values of the auxiliary variable are known and the ranks of the auxiliary variable are associated with the study variable, these estimators are particularly useful. Therefore, the precision of the estimators can be effectively improved through the utilization of these rankings. We examine the properties of the proposed class of estimators, including bias and mean squared error (MSE), using a first-order approximation through a stratified random sampling method. To determine the performances and validate the findings mathematically, a simulation study is carried out. Based on the results, the proposed class of estimators performs better in terms of the mean squared error (MSE) and percent relative efficiency (PRE) as compared to other estimators in all scenarios. Furthermore, in order to prove that the performances of the improved class of estimators are better than those of the existing estimators, three data sets are examined in the application section.
A Chemical Toolbox to Unveil Synthetic Nature-Inspired Antifouling (NIAF) Compounds
Authors: Neves Ana Rita , Godinho Sara , Gonçalves Catarina , Gomes Ana Sara , Almeida Joana R. , Pinto Madalena , Sousa Emília , Correia-da-Silva Marta
Published: September 2024

The current scenario of antifouling (AF) strategies to prevent the natural process of marine biofouling is based in the use of antifouling paints containing different active ingredients, believed to be harmful to the marine environment. Compounds called booster biocides are being used with copper as an alternative to the traditionally used tributyltin (TBT); however, some of them were recently found to accumulate in coastal waters at levels that are deleterious for marine organisms. More ecological alternatives were pursued, some of them based on the marine organism mechanisms’ production of specialized metabolites with AF activity. However, despite the investment in research on AF natural products and their synthetic analogues, many studies showed that natural AF alternatives do not perform as well as the traditional metal-based ones. In the search for AF agents with better performance and to understand which molecular motifs were responsible for the AF activity of natural compounds, synthetic analogues were produced and investigated for structure–AF activity relationship studies. This review is a comprehensive compilation of AF compounds synthesized in the last two decades with highlights on the data concerning their structure–activity relationship, providing a chemical toolbox for researchers to develop efficient nature-inspired AF agents.
Augmenting Reality in Spinal Surgery: A Narrative Review of Augmented Reality Applications in Pedicle Screw Instrumentation
Authors: Xiao Sheng-Xian , Wu Wen-Tien , Yu Tzai-Chiu , Chen Ing-Ho , Yeh Kuang-Ting
Published: September 2024

Background and Objectives: The advent of augmented reality (AR) in spinal surgery represents a key technological evolution, enhancing precision and safety in procedures such as pedicle screw instrumentation. This review assesses the current applications, benefits, and challenges of AR technology in spinal surgery, focusing on its effects on surgical accuracy and patient outcomes. Materials and Methods: A comprehensive review of the literature published between January 2023 and December 2024 was conducted, focusing on AR and navigational technologies in spinal surgery. Key outcomes such as accuracy, efficiency, and complications were emphasized. Results: Thirteen studies were included, highlighting substantial improvements in surgical accuracy, efficiency, and safety with AR and navigational systems. AR technology was found to significantly reduce the learning curve for spinal surgeons, improve procedural efficiency, and potentially reduce surgical complications. The challenges identified include high system costs, the complexity of training requirements, the integration with existing workflows, and limited clinical evidence. Conclusions: AR technology holds promise for advancements in spinal surgery, particularly in improving the accuracy and safety of pedicle screw instrumentation. Despite existing challenges such as cost, training needs, and regulatory hurdles, AR has the potential to transform spinal surgical practices. Ongoing research, technological refinements, and the development of implementation strategies are essential to fully leverage AR’s capabilities in enhancing patient care.
Risk Factors for Postoperative Donor Site Complications in Radial Forearm Free Flaps
Authors: Hong Seungeun
Published: September 2024

Background and Objectives: The radial forearm free flap (RFFF) is the most commonly used flap for head and neck reconstruction. However, complications at the donor site are its major drawbacks. We aimed to identify the patient comorbidities and factors that predict donor site complications after RFFF. Materials and Methods: A retrospective chart review of consecutive patients who underwent RFFF reconstruction for head and neck cancer between 2015 and 2022 was performed. Demographic variables, clinical processes, and postoperative complications were assessed. All variables were analyzed using univariate and multivariate analyses. Results: Sixty-seven patients underwent RFFF reconstruction, and all received a split-thickness skin graft at the donor site. Twenty-five patients experienced delayed skin graft healing, whereas nine experienced sensory changes at the donor site. Hypertension and age had statistically significant negative effects on wound healing. The incidence of hand swelling was related to graft size, and the occurrence of paresthesia was significantly higher in diabetic patients and significantly lower in those with acellular dermal matrix (ADM). Conclusions: Patients with hypertension had a higher risk of prolonged wound healing after RFFF than their normotensive patients. Clinicians should pay particular attention to wound healing strategies in patients with hypertension. Additionally, better neuropathy care is recommended to achieve sensory recovery after RFFF in patients with diabetes. Using a skin graft with ADM could be a method to alleviate neurological symptoms.
Guillain-Barrè Syndrome—Retrospective Analysis of Data from a Cohort of Patients Referred to a Tertiary Care Pediatric Neuromuscular Center from 2000 to 2017: Electrophysiological Findings, Outcomes, and a Brief Literature Review
Authors: Cavirani Benedetta , Baga Margherita , Cesaroni Carlo Alberto , Rizzi Susanna , Spagnoli Carlotta , Frattini Daniele , Della Giustina Elvio , Pisani Francesco , Fusco Carlo
Published: September 2024

Background and Objectives: Guillain-Barré syndrome (GBS) is the most frequent cause of acute flaccid paresis in children. The aim of this study was to describe the clinical and electrophysiological findings and outcomes of children with GBS diagnosed in our unit. Moreover, the literature on pediatric GBS cases from the past 5 years was reviewed. In this retrospective study, we reported data on 12 patients (9 male and 3 female patients; mean age: 5 y, 4 mo; range: 9 mo–11 y) clinically diagnosed at the Child Neurology Unit of the AUSL-IRCCS of Reggio Emilia, Italy, between 2000 and 2017 and a brief analysis/comparison with data from the literature. Materials and Methods: Data were collected from medical charts. Results: In our cohort, male patients were more frequent than female ones (9 vs. 3), and upper respiratory tract infection (n = 8, 66.7%) was the most frequent triggering factor. The main clinical symptoms on admission were distal lower limbs’ weakness with gait difficulties (83.3%), pain (50%), upper limbs’ weakness (50%), and dysphagia for liquids (25%). Peripheral neurophysiological studies revealed acute inflammatory demyelinating polyradiculoneuropathy (AIDP) in 66.6% of the children, acute motor and sensory axonal neuropathy (AMSAN) in 25%, and acute motor axonal neuropathy (AMAN) in 8.3%. Ten individuals (83.3%) received timely treatment with intravenous immunoglobulins (IVIG), and, out of these ten patients, 58% received concomitant treatment with IV methylprednisolone because of a progressive disease course. Complete remission was observed in the majority of individuals (91.6%) within 6 months of symptom onset. Conclusions: Different subtypes of GBS can affect children; however, the outcome is usually positive. Early treatment appears to be important for a favorable outcome.
DFT Insights into the Physical Properties of Layered LiMnSe2 and LiMnTe2 Compounds
Authors: Benmakhlouf Abdennour , Faid Fares , Ghermoul Nedjmeddine , Özdoğan Kemal , Helaimia Taoufik , Bouhemadou Abdelmadjid , Galanakis Iosif
Published: September 2024

Using state-of-the-art first-principles electronic-band-structure calculations alongside density functional theory, we investigated the structural, elastic, electronic, and magnetic properties of LiMnZ2 (Z = Se, Te) compounds with a trigonal structure. Initially, we determined the equilibrium lattice structure and atomic positions, which aligned well with experimental values. Ferromagnetism was shown to be more favorable than the non-magnetic state. The elastic constants, cohesive energies, and formation energies indicated that the studied compounds were mechanically stable in the experimentally determined trigonal lattice. The analysis of spin-polarized band structures and density of states revealed that both LiMnZ2 compounds exhibited perfect half-metallic characters. The total spin magnetic moment per formula unit adhered to the Slater–Pauling rule, being exactly 4 μΒ, mainly concentrated at the Mn atoms due to the strong spin polarization of the Mn d orbitals. We anticipate that our results will prompt further experimental and computational studies for the application of these layered materials in practical devices.
Practical Approaches for Determining the Structural Resolution Capability of X-ray Computed Tomography Measurement Tasks
Authors: Busch Matthias , Hausotte Tino
Published: September 2024

The structural resolution describes the ability of a measuring device to detect small structures on the surface of a component or test specimen by means of a quantitative value. However, the structural resolution in the computer tomograph depends on the object and must therefore be determined separately for each measurement task. The previous approaches to structural resolution determination are only related to test specimens. In this paper, less discrete approaches based on a circular pattern are presented, which can be integrated into the measured component. A voxel-based methodology as well as two surface-based methodologies are described. The investigation results regarding the effect of the component position on the structural resolution are obtained on the basis of real CT measurements. A comparison is also completed with the well-known hourglass method. The results show that the resolution depends on the object being measured, with similar values being obtained for the same object using different methods.
Study of the Characteristics of Ba0.6Sr0.4Ti1-xMnxO3-Film Resistance Random Access Memory Devices
Authors: Chen Kai-Huang , Cheng Chien-Min , Kao Ming-Cheng , Kao Yun-Han , Lin Shen-Feng
Published: September 2024

In this study, Ba0.6Sr0.4Ti1-xMnxO3 ceramics were fabricated by a novel ball milling technique followed by spin-coating to produce thin-film resistive memories. Measurements were made using field emission scanning electron microscopes, atomic force microscopes, X-ray diffractometers, and precision power meters to observe, analyze, and calculate surface microstructures, roughness, crystalline phases, half-height widths, and memory characteristics. Firstly, the effect of different sintering methods with different substitution ratios of Mn4+ for Ti4+ was studied. The surface microstructural changes of the films prepared by the one-time sintering method were compared with those of the solid-state reaction method, and the effects of substituting a small amount of Ti4+ with Mn4+ on the physical properties were analyzed. Finally, the optimal parameters obtained in the first part of the experiment were used for the fabrication of the thin-film resistive memory devices. The voltage and current characteristics, continuous operation times, conduction mechanisms, activation energies, and hopping distances of two types of thin-film resistive memory devices, BST and BSTM, were measured and studied under different compliance currents.
Wettability Behaviour of Metal Surfaces after Sequential Nanosecond and Picosecond Laser Texturing
Authors: Tang Yin , Fang Zheng , Fei Yang , Wang Shuai , Perrie Walter , Edwardson Stuart , Dearden Geoff
Published: September 2024

This study examines the wettability behaviour of 304 stainless steel (304SS) and Ti-6Al-4V (Ti64) surfaces after sequential nanosecond (ns) and picosecond (ps) laser texturing; in particular, how the multi-scale surface structures created influence the lifecycle of surface hydrophobicity. The effect of different post-process treatments is also examined. Surfaces were analysed using Scanning Electron Microscopy (SEM), a white light interferometer optical profiler, and Energy Dispersive X-ray (EDX) spectroscopy. Wettability was assessed through sessile drop contact angle (CA) measurements, conducted at regular intervals over periods of up to 12 months, while EDX scans monitored elemental chemical changes. The results show that sequential (ns + ps) laser processing produced multi-scale surface texture with laser-induced periodic surface structures (LIPSS). Compared to the ns laser case, the (ns + ps) laser processed surfaces transitioned more rapidly to a hydrophobic state and maintained this property for much longer, especially when the single post-process treatment was ultrasonic cleaning. Some interesting features in CA development over these extended timescales are revealed. For 304SS, hydrophobicity was reached in 1–2 days, with the CA then remaining in the range of 120 to 140° for up to 180 days; whereas the ns laser-processed surfaces took longer to reach hydrophobicity and only maintained the condition for up to 30 days. Similar results were found for the case of Ti64. The findings show that such multi-scale structured metal surfaces can offer relatively stable hydrophobic properties, the lifetime of which can be extended significantly through the appropriate selection of laser process parameters and post-process treatment. The addition of LIPSS appears to help extend the longevity of the hydrophobic property. In seeking to identify other factors influencing wettability, from our EDX results, we observed a significant and steady rate of increase in the carbon content at the surface over the study period.
pH Nonlinearly Dominates Soil Bacterial Community Assembly along an Altitudinal Gradient in Oak-Dominant Forests
Authors: Lin Litao , Li Guixiang , Yu Huiyi , Ma Keming
Published: September 2024

Soil bacteria, the predominant microbiota in soil, are subject to the law of minimum and the law of tolerance, but the assembly patterns of soil bacteria in response to environmental factors remain far from clear. Here, we took advantage of an altitudinal gradient (1020–1770 asl) in oak-dominant forests and assessed whether soil bacteria linearly or nonlinearly respond to environmental properties through the changes in the community diversity and composition. We found that soil bacteria decreased with increasing altitude in terms of the species richness and phylogenetic structure, while they were unchanged with increasing altitude in terms of community composition. The species richness was nonlinearly affected by the soil pH (19.9%), C:N ratio (14.3%), SOC (11.4%), and silt + clay content (9.9%). Specifically, the species richness peaked at a pH of 5.5–6.5, and an SOC of 25–50 g kg−1, and it showed abrupt decreases and increases at a C:N ratio of 14.5 and a silt + clay content of 70%. The community composition was significantly affected by the soil pH (28.2%), then by the SOC (3.6%), available phosphorus (1.0%), and silt + clay content (0.5%), and it showed less turnovers at a pH of 6.0, SOC of 50 g kg−1, and available phosphorus > 3.0 g kg−1. These findings imply that environmental filtering processes nonlinearly shape bacterial communities.
The Role of the Gut Microbiota in Complications among Hemodialysis Patients
Authors: Du Junxia , Zhao Xiaolin , Ding Xiaonan , Han Qiuxia , Duan Yingjie , Ren Qinqin , Wang Haoran , Song Chenwen , Wang Xiaochen , Zhang Dong , Zhu Hanyu
Published: September 2024

The composition of the gut microbiota varies among end-stage renal disease (ESRD) patients on the basis of their mode of renal replacement therapy (RRT), with notably more pronounced dysbiosis occurring in those undergoing hemodialysis (HD). Interventions such as dialysis catheters, unstable hemodynamics, strict dietary restrictions, and pharmacotherapy significantly alter the intestinal microenvironment, thus disrupting the gut microbiota composition in HD patients. The gut microbiota may influence HD-related complications, including cardiovascular disease (CVD), infections, anemia, and malnutrition, through mechanisms such as bacterial translocation, immune regulation, and the production of gut microbial metabolites, thereby affecting both the quality of life and the prognosis of patients. This review focuses on alterations in the gut microbiota and its metabolites in HD patients. Additionally, understanding the impact of the gut microbiota on the complications of HD could provide insights into the development of novel treatment strategies to prevent or alleviate complications in HD patients.
Petrogenesis of an Episyenite from Iwagi Islet, Southwest Japan: Unique Li–Na Metasomatism during the Turonian
Authors: Imaoka Teruyoshi , Akita Sachiho , Ishikawa Tsuyoshi , Tani Kenichiro , Kimura Jun-Ichi , Chang Qing , Nagashima Mariko
Published: September 2024

A unique Li–Na metasomatic rock from Iwagi Islet in Southwest (SW) Japan is an episyenite that contains new Li-rich minerals, including sugilite, katayamalite, murakamiite, and ferro-ferri-holmquistite. We present petrographical, mineralogical, and geochronological data for the protoliths and episyenite. We classified the metasomatic rocks based on the mineral assemblages, from the protolith biotite granite to albitized granite, quartz albitite, hedenbergite albitite, aegirine albitite, sugilite albitite, and katayamalite albitite. The protolith of hedenbergite albitites may have been metasomatic granite that has been subjected to calcic skarnization. Albitites are formed related to fractures and shear zones that focused the fluid flow and metasomatism. Extensive albitization and formation of abundant Li minerals requires involvement of external Li-Na-Cl-rich fluids, which might be related to deep high-temperature Arima-like brines derived from dehydration of the subducted oceanic slab. Formation of the albitites began with quartz dissolution and vug formation, and record interface-coupled dissolution–reprecipitation processes in an open system. The 40Ar/39Ar age of 91.5 ± 0.3 Ma determined for the katayamalite is slightly younger than the protolith zircon U–Pb age of 93.5 ± 1.7 Ma (Turonian), reasonably explaining the timing of Li–Na metasomatism after the petrogenesis of host granites.
The Role of Organic Matter and Hydrocarbons in the Genesis of the Pb-Zn-Fe (Ba-Sr) Ore Deposits in the Diapirs Zone, Northern Tunisia
Authors: Rddad Larbi , Jemmali Nejib , Jaballah Samar
Published: September 2024

Extensional tectonics along NE-trending faults, coupled with diapirism, created paleo-highs and subsiding basins, providing the structural framework for subsequent mineralization processes. The preservation of organic matter within the Fahdene and Bahloul Cretaceous formations during the Anoxic Oceanic Events (AOE-1 and AOQ-2) facilitated the extraction of metals from seawater. The association of metals with organic matter, Fe-Mg oxides, and pyrite is revealed by principal component analysis (PCA). The subsequent maturation of organic matter generated hydrocarbons, with thermal cracking leading to the incorporation of organo-metallic ligands into mobile hydrocarbons. Oilfield brines form as a byproduct of this catagenesis. The metal-rich hydrocarbons and basinal brines invaded SO4−2-rich fluids from Triassic evaporites, resulting in the precipitation of sulfates (barite and celestite) and the bacteriogenic (BSR) and/or thermal (TSR) reduction of sulfate to reduced sulfur, which combined with metals to form sulfide ores. This study examines the role of hydrocarbons in the genesis of ore deposits within the diapiric zone, drawing upon a synthesis of literature and geological data. It highlights the interplay between basinal evolution, the organic matter-rich Cretaceous formations (Fahdene and Bahloul), diapiric paleo-highs, and the Alpine orogeny, which are identified as crucial factors in ore genesis in the diapiric zone.
The Effect of Chronic Treatment with the Inhibitor of Phosphodiesterase 5 (PDE5), Sildenafil, in Combination with L-DOPA on Asymmetric Behavior and Monoamine Catabolism in the Striatum and Substantia Nigra of Unilaterally 6-OHDA-Lesioned Rats
Authors: Lorenc-Koci Elżbieta , Kamińska Kinga , Lenda Tomasz , Konieczny Jolanta
Published: September 2024

The use of phosphodiesterase inhibitors in the treatment of Parkinson’s disease is currently widely discussed. The study aimed to investigate the impact of acute and chronic treatment with the phosphodiesterase 5 inhibitor, sildenafil, at low and moderate doses of 2 mg/kg and 6 mg/kg, and L-DOPA (12.5 mg/kg), alone or in combination, on asymmetric behavior and dopamine (DA) and serotonin metabolism in the striatum and substantia nigra of unilaterally 6-OHDA-lesioned rats. Acute administration of sildenafil at both tested doses jointly with L-DOPA significantly increased the number of contralateral rotations during a 2 h measurement compared to L-DOPA alone. The effect of a lower dose of sildenafil combined with L-DOPA was much greater in the second hour of measurement. However, the acute combined administration of a higher dose of sildenafil with L-DOPA resulted in an immediate and much stronger increase in the number of contralateral rotations compared to L-DOPA alone, already visible in the first hour of measurement. Interestingly, the chronic combined administration of 2 mg/kg of sildenafil and L-DOPA significantly reduced the number of contralateral rotations, especially during the first hour of measurement, compared to the long-term treatment with L-DOPA alone. Such an effect was not observed after the long-term combined treatment of a higher dose of sildenafil and L-DOPA compared to L-DOPA alone. The concentration of DA in the ipsilateral striatum and substantia nigra after the last combined chronic dose of sildenafil (2 or 6 mg/kg) and L-DOPA (12.5 mg/kg) was significantly higher than after L-DOPA alone. In spite of much stronger increases in the DA concentration in the ipsilateral striatum and substantia nigra, the number of contralateral rotations was reduced in the group of rats treated with the combination of 2 mg/kg sildenafil and L-DOPA compared to the group receiving L-DOPA alone. Moreover, the combined treatment with a low dose of sildenafil and L-DOPA had an opposite effect on DA catabolism, as assessed by DOPAC/DA and HVA/DA indexes, and these indexes were reduced in the ipsilateral striatum but increased in the contralateral striatum and substantia nigra compared to the treatment with L-DOPA alone. The results of the present study show that the addition of a low dose of a PDE5 inhibitor to the standard L-DOPA therapy differently modulates rotational behavior, the tissue DA concentration and its catabolism in the striatum and substantia nigra.
Metabolic and Pharmacokinetic Profiling Studies of N, N-Dimethylaniline-Heliamine in Rats by UHPLC-Q-Orbitrap MS/MS
Authors: Xi Ruqi , Abdulla Rahima , Sherzod Jurakulov , Ivanovna Vinogradova Valentina , Habasi Maidina , Liu Yongqiang
Published: September 2024

Cardiovascular disease is the first cause of death worldwide and kills more people each year than any other cause of death. N, N-dimethylaniline-heliamine (DH), a synthetic tetrahydroisoquinoline alkaloid, has shown notable antiarrhythmic activity. However, the metabolic processes and pharmacokinetic characteristics of DH in rats have not been studied. This study aims to identify its metabolites, as well as develop and validate a rapid and efficient bioanalytical method for quantifying DH in rat plasma over a wide range of concentrations. Its metabolites were characterized in silico, in vitro, and in vivo. A series of 16 metabolites were identified, of which 12 were phase I metabolites and 4 were phase II metabolites. A low probability of DH binding to DNA, protein, and glutathione is predicted by the in silico model. The main metabolic processes of DH were demethylation, dehydrogenation, glucuronidation, and sulfation. Concentration–time profiles were generated by analyzing the plasma, and the outcomes were analyzed via non-compartmental analysis to identify the pharmacokinetic parameters. Among the detected parameters were the volume of distribution, estimated at 126,728.09 ± 56,867.09 mL/kg, clearance at 30,148.65 ± 15,354.27 mL/h/kg, and absolute oral bioavailability at 16.11%. The plasma distribution volume of DH was substantially higher than the overall plasma volume of rats, which suggests that DH has a specific tissue distribution in rats. This study suggests that DH is appropriately bioavailable and excreted via a variety of routes and has low toxicity.
Photovoltage-Driven Photoconductor Based on Horizontal p-n-p Junction
Authors: Han Feng , Mi Guanyu , Luo Ying , Lv Jian
Published: September 2024

The photoconductive gain theory demonstrates that the photoconductive gain is related to the ratio of carrier lifetime to carrier transit time. Theoretically, to achieve higher gain, one can either prolong the carrier lifetime or select materials with high mobility to shorten the transit time. However, the former slows the response speed of the device, while the latter increases the dark current and degrades device sensitivity. To address this challenge, a horizontal p-n-p junction-based photoconductor is proposed in this work. This device utilizes the n-region as the charge transport channel, with the charge transport direction perpendicular to the p-n-p junction. This design offers two advantages: (i) the channel is depleted by the space charge layer generated by the p and n regions, enabling the device to maintain a low dark current. (ii) The photovoltage generated in the p-n junction upon light absorption can compress the space charge layer and expand the conductive path in the n-region, enabling the device to achieve high gain and responsivity without relying on long carrier lifetimes. By adopting this device structure design, a balance between responsivity, dark current, and response speed is achieved, offering a new approach to designing high-performance photodetectors based on both traditional materials and emerging nanomaterials.
Comparison In Vitro Study on the Interface between Skin and Bone Cell Cultures and Microporous Titanium Samples Manufactured with 3D Printing Technology Versus Sintered Samples
Authors: Shevtsov Maxim , Pitkin Emil , Combs Stephanie E. , Meulen Greg Van Der , Preucil Chris , Pitkin Mark
Published: September 2024

Percutaneous implants osseointegrated into the residuum of a person with limb amputation need to provide mechanical stability and protection against infections. Although significant progress has been made in the biointegration of percutaneous implants, the problem of forming a reliable natural barrier at the level of the surface of the implant and the skin and bone tissues remains unresolved. The use of a microporous implant structure incorporated into the Skin and Bone Integrated Pylon (SBIP) should address the issue by allowing soft and bone tissues to grow directly into the implant structure itself, which, in turn, should form a reliable barrier to infections and support strong osseointegration. To evaluate biological interactions between dermal fibroblasts and MC3T3-E1 osteoblasts in vitro, small titanium discs (with varying pore sizes and volume fractions to achieve deep porosity) were fabricated via 3D printing and sintering. The cell viability MTT assay demonstrated low cytotoxicity for cells co-cultured in the pores of the 3D-printed and sintered Ti samples during the 14-day follow-up period. A subsequent Quantitative Real-Time Polymerase Chain Reaction (RT-PCR) analysis of the relative gene expression of biomarkers that are associated with cell adhesion (α2, α5, αV, and β1 integrins) and extracellular matrix components (fibronectin, vitronectin, type I collagen) demonstrated that micropore sizes ranging from 200 to 500 µm of the 3D printed and sintered Ti discs were favorable for dermal fibroblast adhesion. For example, for representative 3D-printed Ti sample S6 at 72 h the values were 4.71 ± 0.08 (α2 integrin), 4.96 ± 0.08 (α5 integrin), 4.71 ± 0.08 (αV integrin), and 1.87 ± 0.12 (β1 integrin). In contrast, Ti discs with pore sizes ranging from 400 to 800 µm demonstrated the best results (in terms of marker expression related to osteogenic differentiation, including osteopontin, osteonectin, osteocalcin, TGF-β1, and SMAD4) for MC3T3-E1 cells. For example, for the representative 3D sample S4 on day 14, the marker levels were 11.19 ± 0.77 (osteopontin), 7.15 ± 0.29 (osteonectin), and 6.08 ± 0.12 (osteocalcin), while for sintered samples the levels of markers constituted 5.85 ± 0.4 (osteopontin), 4.45 ± 0.36 (osteonectin), and 4.46 ± 0.3 (osteocalcin). In conclusion, the data obtained show the high biointegrative properties of porous titanium structures, while the ability to implement several pore options in one structure using 3D printing makes it possible to create personalized implants for the best one-time integration with both skin and bone tissues.
Preparation and Characterization of Amide-Containing Polyimide Films with Enhanced Tribopositivity for Triboelectric Nanogenerators to Harvest Energy at Elevated Temperatures
Authors: Pan Zhen , Yuan Shunqi , Zhang Yan , Ren Xi , He Zhibin , Wang Zhenzhong , Han Shujun , Qi Yuexin , Yu Haifeng , Liu Jingang
Published: September 2024

As triboelectric nanogenerator (TENG) technology continue to evolve, its application in harsh environments has increasingly captivated the interest of researchers. However, the current research on heat-resistant triboelectric materials remains predominantly focused on the development of tribo-negative materials, with scant attention given to their equally crucial tribo-positive counterparts. In this study, the tribo-positive polyimide (PI) material with enhanced tribo-positivity is developed by integrating amide groups with electron-donating effects into the molecular chain. Furthermore, the TENG devices based on this series of tribo-positive PI materials have demonstrated an open-circuit voltage (VOC) of 242 V, a short-circuit current (ISC) of 8.13 μA, and a transferred charge (QSC) of 117 nC. Notably, these devices also demonstrate the capability to efficiently generate electricity even under elevated temperature conditions. This work not only proposes a potential molecular design strategy for developing high-performance tribo-positive PI materials applicable in TENGs, but also markedly propels the advancement of robust energy-harvesting devices engineered for operation at elevated temperatures.
Assessment of Supplementation with Different Biomolecules in the Prevention and Treatment of COVID-19
Authors: González-Acedo Anabel , Manzano-Moreno Francisco Javier , García-Recio Enrique , Ruiz Concepción , Luna-Bertos Elvira de , Costela-Ruiz Víctor Javier
Published: September 2024

Consequences of the disease produced by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have led to an urgent search for preventive and therapeutic strategies. Besides drug treatments, proposals have been made for supplementation with biomolecules possessing immunomodulatory and antioxidant properties. The objective of this study was to review published evidence on the clinical usefulness of supplementation with vitamin D, antioxidant vitamins (vitamin A, vitamin E, and vitamin C), melatonin, lactoferrin and natural products found in food (curcumin, luteolin, ginger, allicin, magnesium and zinc) as supplements in SARS-CoV-2 infection. In general, supplementation of conventional treatments with these biomolecules has been found to improve the clinical symptoms and severity of the coronavirus disease (COVID-19), with some indications of a preventive effect. In conclusion, these compounds may assist in preventing and/or improving the symptoms of COVID-19. Nevertheless, only limited evidence is available, and findings have been inconsistent. Further investigations are needed to verify the therapeutic potential of these supplements.