Search Results (99)

The increasing number of acetabular revision total hip arthroplasties requires the evaluation of alternative materials in addition to established standards using a defined animal experimental defect that replicates the human acetabular revision situation as closely as possible. Defined bone defects in the load-bearing area of the acetabulum were augmented with various materials in an ovine periacetabular defect model (Group 1: NanoBone^® (artificial hydroxyapatite-silicate composite; Artoss GmbH, Germany); Group 2: autologous sheep cancellous bone; Group 3: Tutoplast^® (processed allogeneic sheep cancellous bone; Tutogen Medical GmbH, Germany)) and bridged with an acetabular reinforcement ring of the Ganz type. Eight months after implantation, a μ-CT examination (n = 8 animals per group) was performed. A μ-CT analysis of the contralateral acetabula (n = 8, randomly selected from all three groups) served as the control group. In a defined volume of interest (VOI), bone volume (BV), mineral volume (MV), and bone substitute volume (BSV), as well as the bone surface (BS) relative to the total volume (TV) and the surface-to-volume ratio (BS/BV), were determined. To assess the bony microarchitecture, trabecular thickness (Tb.Th), trabecular separation (Tb.Sp), and trabecular number (Tb.N), as well as connectivity density (Conn.D), the degree of anisotropy (DA), and the structure model index (SMI), were evaluated. The highest BV was observed for NanoBone^® (Group 1), which also showed the highest proportion of residual bone substitute material in the defect. This resulted in a significant increase in BV/TV with a significant decrease in BS/BV. The assessment of the microstructure for Groups 2 and 3 compared to Group 1 showed a clear approximation of Tb.Th, Tb.Sp, Tb.N, and Conn.D to the microstructure of the control group. The SMI showed a significant decrease in Group 1. All materials demonstrated their suitability by supporting biological defect reconstruction. NanoBone^® showed the highest rate of new bone formation; however, the microarchitecture indicated more advanced bone remodeling and an approximate restoration of the trabecular structure for both autologous and allogeneic Tutoplast^® cancellous bone when using the impaction bone grafting technique. Full article

Sparse matrix–vector multiplication (SpMV) plays a significant role in the computational costs of many scientific applications such as 2D/3D robotics, power network problems, and computer vision. Numerous implementations using different sparse matrix formats have been introduced to optimize this kernel on CPUs and GPUs. However, due to the sparsity patterns of matrices and the diverse configurations of hardware, accurately modeling the performance of SpMV remains a complex challenge. SpMV computation is often a time-consuming process because of its sparse matrix structure. To address this, we propose a machine learning-based tool, namely Elegante+, that predicts optimal scheduling policies by analyzing matrix structures. This approach eliminates the need for repetitive trial and error, minimizes errors, and finds the best solution of the SpMV kernel, which enables users to make informed decisions about scheduling policies that maximize computational efficiency. For this purpose, we collected 1000+ sparse matrices from the SuiteSparse matrix market collection and converted them into the compressed sparse row (CSR) format, and SpMV computation was performed by extracting 14 key sparse matrix features. After creating a comprehensive dataset, we trained various machine learning models to predict the optimal scheduling policy, significantly enhancing the computational efficiency and reducing the overhead in high-performance computing environments. Our proposed tool, Elegante+ (XGB with all SpMV features), achieved the highest cross-validation score of 79% and performed five times faster than the default scheduling policy during SpMV in a high-performance computing (HPC) environment. Full article

The projected global energy demand for 2050 drives the imperative search for alternative and environmentally friendly energy sources. An emerging and promising alternative is microbial fuel cells assisted with microalgae. This research evaluated the potential of Chlorella sp. biomass in electricity production using microbial fuel cells (MFCs) with a single chamber and activated carbon and zinc electrodes at the laboratory scale over 20 days of operation. Maximum values of voltage (1271 ± 2.52 mV), current (4.77 ± 0.02 mA), power density (247.514 mW/cm²), current density (0.551 mA/cm²), and internal resistance (200.83 ± 0.327 Ω) were obtained. The biomass-maintained pH values of 7.32 ± 0.03–7.74 ± 0.02 and peaks of electrical conductivity of 2450 ± 17.1 µS/cm and oxidation-reduction potential of 952 ± 20 mV were reached. Meanwhile, cell density and absorbance increased to average values of 2.2933 × 10⁷ ± 1.15 × 10⁶ cells/mL and 3.471 ± 0.195 absorbance units (AU), respectively. Scanning electron microscopy micrographs allowed the observation of filamentous structures of the formed biofilm attached to carbon particles, and energy-dispersive X-ray spectroscopy spectra of the anodes determined the predominance of oxygen, carbon, silicon, aluminum, and iron. Finally, this research demonstrates the great potential of Chlorella sp. biomass for sustainable bioelectricity generation in MFCs. Full article

The depletion of the ozone layer and climate change have increased exposure to ultraviolet (UV) radiation, driving the search for natural photoprotective agents. Marine macroalgae, particularly Gracilaria sp. (Rhodophyta) and Sargassum polyceratium (Ochrophyta), are rich in UV-absorbing bioactives, such as mycosporine-like amino acids (MAAs) and fucoxanthin, offering natural alternatives to synthetic sunscreens. This study aimed to develop and optimize a nanoemulsion incorporating both algal extracts, with MAAs and fucoxanthin strategically distributed in the aqueous and oil phases, respectively, to enhance synergistic broad-spectrum UV protection. MAAs were quantified in Gracilaria sp. using UHPLC-DAD, revealing 8.03 mg/g dry weight, primarily composed of shinorine and porphyra-334. Fucoxanthin was identified in S. polyceratium at 0.98 mg/g dry weight. A Box–Behnken design (BBD) was employed to optimize the nanoemulsion, targeting minimal droplet size and optimal ζ potential. The resulting formulation achieved a droplet size less than 100 nm and a ζ potential less than −25.0 mV. In vitro spectrophotometric analysis demonstrated significant photoprotective potential. The nanoemulsion containing only 375 ppm of algal extracts exhibited a UVA ratio of 1.25 and a critical wavelength of 379 nm, meeting the criteria for broad-spectrum protection and outperforming the commercial natural filter Helioguard^®365. These results confirm the efficacy of combining red and brown algae extracts in a nanoemulsion platform to deliver sustainable, low-dose photoprotection. This work presents, for the first time, the incorporation of red and brown algae extracts into a single nanoemulsion system, representing a novel strategy to maximize the combined photoprotective potential of MAAs and fucoxanthin. Ultimately, this investigation contributes to the growing field of marine-derived sunscreens and supports the advancement of “blue beauty” innovations aligned with eco-conscious formulation principles. Full article

As the world moves toward a low-carbon future, a key challenge is improving buildings’ energy performance while maintaining occupant thermal comfort. Emerging digital tools such as the Internet of Things (IoT) and Building Information Modeling (BIM) offer significant potential, enabling precise monitoring and control of building systems. However, integrating these technologies into a unified Digital Twin (DT) framework remains underexplored, particularly in relation to thermal comfort. Additionally, real-world case studies are limited. This paper presents a DT-based system that combines BIM and IoT sensors to monitor and control indoor comfort in real time through an easy-to-use web platform. By using BIM spatial and geometric data along with real-time data from sensors, the system visualizes thermal comfort using a simplified Predicted Mean Vote (sPMV) index. Furthermore, it also uses a hybrid machine learning model that combines Facebook Prophet and Long Short-Term Memory (LSTM) to predict the future indoor environmental parameters. The framework enables Model Predictive Control (MPC) while providing building managers with a scalable tool to collect, analyze, visualize, and optimize thermal comfort data in real time. Full article

Producing hydrogen by water electrolysis has attracted significant attention as a potential renewable energy solution. In this work, a catalyst with reduced graphene oxide (rGO) loaded on IrO₂/TiO₂ (called rGO/IrO₂/TiO₂) was designed for the catalytic oxygen evolution reaction (OER). The catalyst was synthesized by coating graphene oxide onto a pretreated IrO₂/TiO₂ precursor, followed by thermal treatment at 450 °C to achieve reduction and the adhesion of graphene to the substrate. The graphene support retained its intact sp² carbon framework with minor oxygen-containing functional groups, which enhanced electrical conductivity and hydrophilicity. Benefiting from the synergistic effect of an rGO, IrO₂, and TiO₂ matrix, the rGO/IrO₂/TiO₂ catalyst only needed overpotentials of 240 mV and 320 mV to reach 10 mA cm⁻² and 100 mA cm⁻² in the OER, along with excellent stability over 50 h. Its morphology and crystalline structure were characterized by SEM and XRD spectroscopy, and its electrochemical performance was tested by LSV analysis, EIS impedance spectrum, and double-layer capacitance (C_dl) measurements. This work introduces an innovative and eco-friendly strategy for constructing a high-performance, functionalized Ir-based catalyst. Full article

Given the growing interest in the functional properties of nanocellulosic forms, bacterial cellulose nanocrystals (BCNCs) have gained attention as sustainable, high-performance materials for diverse applications. Although recent research has addressed the use of agro-industrial waste for BCNCs production, limited attention has been given to residual crude glycerol, a widespread byproduct of the biodiesel industry. Therefore, this work aimed to synthesize and thoroughly characterize BCNCs from bacterial nanocellulose (BNC) obtained through the metabolism of crude glycerol via the novel bacterial strain Ancylobacter sp. STN1A. The influence of sulfuric acid (H₂SO₄) hydrolysis time on BCNCs´ morphology and physicochemical properties was evaluated. Severe hydrolysis conditions yielded shorter, narrower nanocrystals (0.91 μm × 40 nm; L/D = 22.8) with increased crystallinity (63%) and high colloidal stability (−40.17 ± 0.68 mV), as well as slightly reduced thermal stability. In contrast, milder conditions produced longer BCNCs (1.13 μm × 42 nm; L/D = 26.9) with similarly high zeta potential (−44.13 ± 0.73 mV), while maintaining the thermal and crystalline features of the starting BNC. These findings demonstrate the potential to tailor BCNCs´ properties through controlled hydrolysis and support the viability of producing versatile nanocellulosic materials from residual byproducts, contributing to both cost-effective production and environmental sustainability. Full article

This study aims to optimize the parameters for the ultrasound-assisted extraction of cellulose nanocrystals (CNCs) from scented pandan leaf waste and to enhance the properties of edible films reinforced with CNC. The CNC extraction conditions were optimized using response surface methodology (central composite design) by varying two independent variables, including amplitude (25.86% to 54.14%) and ultrasonication time (11.89 min to 33.11 min). The optimal extraction conditions were 50% amplitude and 30 min ultrasonication, providing CNCs with the highest extraction yield (29.85%), the smallest crystallite size (5.85 nm), and the highest crystallinity index (59.32%). The extracted CNCs showed favorable physicochemical properties, including a zeta potential of −33.95 mV, an average particle diameter of 91.81 nm, and a polydispersity index of 0.26. Moreover, sweet potato starch (SPS)-based films incorporating various CNC concentrations (0, 2, 4, 6, and 8%) were fabricated. Increasing CNC concentrations improved key film properties, including thickness, moisture content, water vapor permeability, tensile strength, light transmittance, and color. Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), and scanning electron microscopy (SEM) analyses confirmed hydrogen bonding, crystallinity, and uniform CNC distribution within the film as CNC content increased. These findings highlight ultrasound-assisted extraction as an efficient method for producing high-quality CNCs from pandan leaf waste, offering sustainable nanofillers to enhance biodegradable edible films. Full article

Saltwater intrusion (SWI) in coastal aquifers poses a significant threat to freshwater resources, exacerbated by climate change and rising sea levels. This study investigates SWI dynamics using laboratory experiments, geophysical monitoring with the self-potential (SP) method, and numerical simulations to assess the impact of varying salt concentrations (7 g/L and 35 g/L) on intrusion rates and electrochemical responses. Laboratory experiments were conducted in a custom-designed sandbox model, with SP data collected in real time using a 192-electrode system. Numerical simulations were performed to replicate experimental conditions and validate the model’s predictions. Results show that salt concentration significantly influences intrusion rates and SP responses. In low-salinity systems (7 g/L), SP values increased gradually from 0 mV to 20 mV, with a slow intrusion rate of 0.034 m/h. In contrast, moderate-salinity systems (35 g/L) exhibited rapid SP changes (0 mV to 5 mV) and a faster intrusion rate of 0.1 m/h. Sharp SP anomalies near the intrusion source, with values dropping from 10 mV to −40 mV, were observed in low-salinity systems, highlighting localized charge imbalances. The model’s performance was evaluated using relative RMSE, showing a good fit in Experiment (1) (RMSE = 5.00%) and acceptable results for Experiment (2) (RMSE = 23.45%). These findings demonstrate the potential of the SP method for real-time monitoring of SWI and provide insights for improving management strategies in coastal aquifers. Full article

Carbon-based electrocatalysts decorated with Pt and Ni nanoparticles were introduced herein to increase the efficiency of the water splitting process and thus reduce the price of the produced green hydrogen. The materials were prepared by innovative direct carbonization of ionic liquids containing the corresponding metal, thereby eliminating the need for additional solutions and templates. The structural integrity of the materials was validated through X-ray diffraction analysis and Fourier-transform infrared spectroscopy. The electrochemical performance of these materials in catalyzing hydrogen (HER) and oxygen (OER) evolution reactions was evaluated using voltammetry and electrochemical impedance spectroscopy, uncovering distinct behaviors and highlighting the role of ionic liquid in tailoring materials’ properties and performance. Specifically, the presence of Ni was observed to enhance the catalytic performance towards the HERs due to the interaction of Ni nanoparticles and a higher amount of sp²-hybridized carbon present. In contrast, incorporating Pt into the carbon matrix was found to augment the catalytic activity for OERs with a Tafel slope of 129 mV dec⁻¹ and a current density of 10 mA cm⁻² reached at a potential of 1.67 V. Moreover, chronoamperometric measurements evidenced materials’ steady performance under both HER and OER conditions. These findings of good activity and stability showed that the introduced approach of synthesis of carbon electrocatalysts decorated with heteroatoms by direct carbonization of ionic liquids holds great promise for the synthesis of efficient and affordable electrocatalysts for green hydrogen production. Full article

Has the mean-variance framework become obsolete? In this paper, we replace traditional variance–covariance methods of portfolio optimisation with relative Tsallis entropy and mutual information measures. Its goal is to enhance risk management and diversification in complicated finance ecosystems. We utilize the S&P 500 and Bitwise 10 cryptocurrency indices’ daily returns (2019–2024 data) and conduct our analysis to the year 2020 under extreme shocks. Many models were trained with different configurations, like mean-variance (MV), mean-entropy (ME), and mean-mutual information (MI) traders and their corresponding variants, using Sharpe’s ratio, Jensen’s alpha, and entropy value of risk (EVAR). The findings indicate that entropic models outperform conventional models in terms of diversification and, especially, extreme risk management. Because the appropriate normalization conditions often fail to be satisfied, we can informally see that after a recalibration of the effective frontier, we obtain from EVAR an accumulated resilience aspect to these rare events while also observing the great potential of entropy-based models to replicate non-linear dependencies between assets. The results show that models combining entropy and mutual information optimise the gain–loss ratio (GLR), providing stable diversification and improved risk management, while maximising returns in complex and volatile market environments. Full article

Cancer ranks among the top causes of illness and death globally. Nanotechnology holds considerable promise for enhancing the effectiveness of therapeutic and diagnostic approaches in cancer treatment. Our study presents a promising strategy for applying thiocompound nanomedicine in cancer therapy. Our first study aimed to investigate the biological properties of a new compound thiodiosgenin (TDG)—a new derivative of diosgenin—a natural compound with known antioxidant and anticancer properties. Our current second study aimed to compare the therapeutic efficacy of a new diosgenin—functionalized gold nanoparticles—with its precursor on prostate cancer (DU-145) cell lines. Moreover, the safety of the new thio-derivative and new conjugates was tested against the human epithelial line PNT-2. New advanced analytical techniques were developed for the characterization of nanomaterials using methods such as SP-ICP-MS, UV-Vis, TEM, NMR, FT-IR ELS, and TGA. Our synthetic approach was based, on the one hand, on the ligand exchange of citrates to thiodiosgenin (TDG) on gold nanoparticles, and on the other hand, on the attachment of DG through an ester bond to the linker, which was 3-mercaptopropionic acid (MPA) on gold nanoparticles. Initial in vitro studies indicate that TDG shows greater cytotoxic effects on cancer cells but poses risks to normal prostate epithelial cells (PNT-2). It was demonstrated that all the conjugates produced exhibited significant cytotoxic effects against cancer cells while being less harmful to normal prostate epithelial cells (PNT-2) compared to TDG itself. All the obtained conjugates showed antitumor properties; however, for targeted transport, the system referred to as AuNPs-MPAm1-DG is promising, due to the size of the nanoparticles of 53 nm, zeta potential of -30 mV, and loading content of 27.6%. New methods for synthesizing conjugates with diosgenin were developed and optimized for medical applications. Advanced new analytical methodologies were developed to characterize new conjugates, particularly the use of SP-ICP-MS, to solve existing differences in the shape and morphology of the surface of new conjugates. Full article

Walnut canker is a common disease in the Xinjiang Uygur autonomous region of China, which is caused by Cytospora chrysosperma. To date, there is no effective control measure for this disease. Infection with mycoviruses has been widely proven to reduce the virulence of plant pathogenic fungi, with some mycoviruses even serving as potential biological control agents for plant diseases. In this study, mycoviruses associated with 31 strains of C. chrysosperma from Xinjiang Uygur autonomous region were identified by metatranscriptomic sequencing. Seven new mycoviruses were identified by BLAST and RT-PCR analysis, which were Botrytis cinerea partitivirus 5 (BcPV5), Gammapartitivirus sp-XJ1 (GVsp-XJ1), Botoulivirus sp-XJ2 (BVsp-XJ2), Luoyang Fusar tick virus 2 (LfTV2), Leptosphaeria biglobosa narnavirus 17 (LbNV17), Sclerotinia sclerotiorum narnavirus 6 (SsNV6), and Cytospora ribis mitovirus (CrMV3). Among these, BcPV5, GVsp-XJ1, BVsp-XJ2, CrMV3, and LfTV2 were found to co-infect C. chrysosperma strain WS-11 and significantly reduce both the colony growth rate and virulence of the host. After co-culturing the virus-free WS-FV strain with WS-11, the colony growth rate and virulence of the derivative strain were also decreased. These results provide potential biocontrol resources for the control of walnut canker. Full article

This study investigated the biosynthesis, statistical optimization, characterization, and biocontrol activity of silver nanoparticles (AgNPs) produced by newly isolated Trichoderma sp. The Trichoderma asperellum strain TA-3N was identified based on the ITS gene sequence, together with its phenotypic characteristics (GenBank accession number: OM321439). The color change from light yellow to brown after the incubation period indicates AgNPs biosynthesis. The UV spectrum revealed a single peak with the maximum absorption at 453 nm, indicating that T. asperellum produces AgNPs effectively. A Rotatable Central Composite Design (RCCD) was used to optimize the biosynthesis of AgNPs using the aqueous mycelial-free filtrate of T. asperellum. The optimal conditions for maximum AgNPs biosynthesis (156.02 µg/mL) were predicted theoretically using the desirability function tool and verified experimentally. The highest biosynthetic produced AgNPs by T. asperellum reached 160.3 µg/mL using AgNO₃ concentration of 2 mM/mL, initial pH level of 6, incubation time of 60 h, and biomass weight of 6 g/100 mL water. SEM and TEM imaging revealed uniform spherical shape particles that varied in size between 8.17 and 17.74 nm. The synthesized AgNPs have a Zeta potential value of −9.51 mV. FTIR analysis provided insights into the surface composition of AgNPs, identifying various functional groups such as N–H, -OH, C-H, C=O, and the amide I bond in proteins. Cytotoxicity and genotoxicity assays demonstrated that AgNPs in combination with T. asperellum can mitigate the toxic effects of Fusarium oxysporum on barley. This intervention markedly enhanced cell division rates and decreased chromosomal irregularities. The results indicate that AgNPs synthesized by T. asperellum show the potential as an eco-friendly and efficient method for controlling plant diseases. Further studies are necessary to investigate their possible use in the agricultural sector. Full article

This paper proposes a simple, environmentally friendly, and efficient procedure for preparing natural water samples for the voltammetric determination of trace amounts of Se(IV). The method is based on premixing a sample with Amberlite XAD-7 resin at 50 °C. The composition of the 10 mL solution consists of the sample to be analysed, 0.1 mol L⁻¹ of acetate buffer at pH = 4.0, and 0.5 g of Amberlite XAD-7. After 2 min of stirring, a voltammetric measurement is carried out using a fixed bismuth microelectrode using the following potentials: −2.5 V for 2 s and −0.55 V for 30 s. The voltammetry is recorded by varying the potential from −400 mV to −1000 mV. An undisturbed Se(IV) signal is obtained in the presence of 10 mg L⁻¹ of Triton X-100, 5 mg L⁻¹ of SDS, 10 mg L⁻¹ of CTAB, 5 mg L⁻¹ of Rhamnolipid, 5 mg L⁻¹ of HA, 10 mg L⁻¹ of FA, and 2 mg L⁻¹ of NOM. The validity of the developed procedure is checked by analysing the certified reference materials SPS-SW1 (surface water) and TM-25.5 (Lake Ontario water) additionally enriched with surfactants and humic substances. Full article