Search Results (110)

Background: There is a growing need for highly accessible and simplified methods to track postural control in adults affected by neurodegenerative diseases. Therefore, the aim of this study was to assess the validity of smartphone-derived postural control analyses compared with traditional center-of-pressure (COP) measures in healthy adults and people with type 2 diabetes mellitus (T2DM). Methods: A total of 36 participants (21 controls, 15 T2DM) completed static postural testing during single- and double-leg stance, also with eyes open and eyes closed. Data from a smartphone attached to the lower back measured trunk acceleration (SP-ACC) concurrently with gold-standard center of pressure (COP). The root mean square (RMS) and movement velocity (MV) were extracted from both trunk acceleration and COP data. The effect of balance condition and groups were statistically evaluated using non-parametric statistical tests. Results: SP-ACC and COP metrics showed progressive sway increases with task difficulty in both groups (all p < 0.001). RMS-ACC demonstrated moderate-to-strong correlations with RMS-COP across conditions (r = 0.55–0.90). Compared with controls, the T2DM group exhibited significantly higher RMS-ACC in DLS-EC and SLS-EO (both p < 0.01) and higher MV-ACC in DLS-EO, SLS-EO, and SLS-EC (p = 0.04–<0.001), reflecting impaired postural control. Conclusions: Smartphone-based IMU assessments showed good agreement with COP analysis and detected condition-specific balance deficits in T2DM. These findings support smartphone-based IMU metrics as a promising tool for accessible and scalable balance screening in diabetes care. Full article

Silver nanoparticles were biosynthesized using the culture supernatant of Staphylococcus sp. YRA, a strain isolated from Colombian mining sediments. Synthesis was optimized at 1 mM AgNO₃, pH 7, 40 °C and 7 μg/mL extract, producing spherical, protein-capped AgNPs with primary sizes in the tens-of-nanometers range (~35–90 nm by SEM), while DLS indicated larger hydrodynamic diameters (~250–320 nm) consistent with aggregation in suspension (ζ-potential −16.6 mV). These nanoparticles remained stable over 6 months. Characterization by UV–Vis, SEM, AFM, EDS and FTIR confirmed extracellular protein-mediated reduction and capping. The AgNPs showed antibacterial activity against multidrug-resistant clinical isolates (Staphylococcus aureus, Escherichia coli, Klebsiella pneumoniae, Salmonella bongori, Enterococcus spp.), with inhibition zones of 8–16 mm at 400–1000 μg/mL. Biofilm formation was reduced by >50% at 700 μg/mL in both Gram-positive and Gram-negative strains. In Phaseolus vulgaris (P. vulgaris), low concentrations (5–100 μg/mL) increased growth and chlorophyll content, while 500 μg/mL caused moderate inhibition. FTIR analysis identified amide and thiol groups from bacterial enzymes as capping agents. These results suggest Staphylococcus sp. YRA as a bacterial platform for AgNPs production with antibiofilm activity against MDR pathogens and acceptable phytotoxicity profile for potential applications. Full article

The complementarity of plant proteins from various sources could achieve higher nutritional value to satisfy the requirement of replacing animal proteins. Therefore, it is very important to seek efficient and convenient approaches to fabricate highly soluble protein composites. In this study, macadamia protein–soybean protein (SP-MP′) composites were fabricated by alkaline-thermal treating at different ratios of 1:0.5, 1:1, and 1:2; then, the nitrogen solubility index, particle characteristics, and structure and emulsifying properties of SP-MP′ composites were investigated. The nitrogen solubility indexes of SP-MP′ composites were higher than 80%, and less small insoluble aggregates were observed by scanning electron microscopy. SP-MP′ composites exhibited high ζ-potential values, which were higher than −50 mV. Sodium dodecyl sulfate–polyacrylamide gel electrophoresis (SDS-PAGE) analysis found that both subunits of individually alkaline-thermal-treated macadamia protein (MP′) and soybean protein (SP′) were presented in SP-MP′ composites. The results of fluorescence, sulfhydryl group, and secondary structure illustrated that the SP interacted with MP to form SP-MP′ composites by the co-folding of proteins during neutralization. Compared to the individual proteins, SP-MP′ composites exhibited stronger emulsification ability and stability indexes (EAI and ESI) as the proportion of MP increased, and the EAI and ESI of SP-MP_1:2′ were 21.53 m²/g and 146.7%, respectively. Meanwhile, emulsions prepared by SP-MP′ composites displayed more uniform oil droplet distributions. The findings suggested that highly soluble SP-MP′ composites with stronger emulsification abilities were successfully fabricated, which have great potential as ingredients to manufacture nutritional plant protein beverages. Full article

Siderophores are low-molecular-weight chelating agents secreted by microorganisms under iron-limiting conditions, playing a crucial role in metal bioavailability and microbial survival. In this study, siderophores produced by Glutamicibacter sp. strain Al-Teq-24-F2, isolated from plant-associated samples, were characterized through a combination of spectroscopic and analytical methods. ESI-MS analysis of the crude extract revealed several abundant ions between 175 and 800 m/z, suggesting a mixture of secondary metabolites. After chromatographic purification, FT-IR and NMR analyses indicated the presence of amide, hydroxyl, and carboxylate functional groups. Integrating these data allowed for the proposal of a siderophore structure with a molecular weight of 438.25 Da. Thermogravimetric analysis showed thermal stability below 115 °C. During Fe (III) complexation, the zeta potential shifted from −21.15 mV to +42 mV, confirming strong interaction between the ligand and the metal. UV–Vis and fluorescence spectroscopy displayed characteristic bathochromic and hypochromic shifts, together with pronounced fluorescence quenching upon iron binding. These findings provide new insight into the structural and physicochemical properties of siderophores produced by Glutamicibacter sp. and highlight their potential applications in biosensing and metal chelation processes. Full article

Ultra-bandgap semiconductor material, β-gallium oxide (β-Ga₂O₃), has great potential for fabricating the next generation of high-temperature, high-voltage power devices due to its superior material properties and cost competitiveness. In addition, β-Ga₂O₃ has the advantages of high-quality, large-size, low-cost, and controllable doping, which can be realized by the melt method. It has a wide bandgap of 4.7–4.9 eV, a large breakdown field strength of 8 MV/cm, and a Baliga figure of merit (BFOM) as high as 3000, which is approximately 10 and 4 times that of SiC and GaN, respectively. These properties enable β-Ga₂O₃ to be strongly competitive in power diodes and metal-oxide-semiconductor field-effect transistor (MOSFET) applications. Most of the current research is focused on electrical characteristics of those devices, including breakdown voltage (V_BR), specific on-resistance (R_ON,SP), power figure of merit (PFOM), etc. Considering the rapid development of β-Ga₂O₃ diode technology, this review mainly introduces the research progress of different structures of β-Ga₂O₃ power diodes, including vertical and lateral structures with various advanced techniques. A detailed analysis of Ga₂O₃-based high-voltage power diodes is presented. This review will help our theoretical understanding of β-Ga₂O₃ power diodes as well as the development trends of β-Ga₂O₃ power application schemes. Full article

Coal spontaneous combustion in arid regions poses severe threats to both ecological security and resource sustainability. Focusing on the detection challenges in Fire Zone No. 1 of the Miaoergou Coalfield, Xinjiang, this study proposes an Integrated Geophysical Collaborative Detection Framework that combines high-precision magnetic surveys, spontaneous potential (SP) measurements, and transient electromagnetic (TEM) methods. This innovative framework effectively overcomes the limitations of traditional single-method detection approaches, enabling the precise delineation of fire zone boundaries and the accurate characterization of spatial dynamics of coal fires. The key findings of the study are as follows: (1) High-magnetic anomalies (with a maximum ΔT of 1886.3 nT) exhibit a strong correlation with magnetite-enriched burnt rocks and dense fracture networks (density > 15 fractures/m), with a correlation coefficient (R²) of 0.89; (2) Negative SP anomalies (with a minimum SP of −38.17 mV) can effectively reflect redox interfaces and water-saturated zones (moisture content > 18%), forming a “positive–negative–positive” annular spatial structure where the boundary gradient exceeds 3 mV/m; (3) TEM measurements identify high-resistivity anomalies (resistivity ρ = 260–320 Ω·m), which correspond to non-waterlogged goaf collapse areas. Spatial integration analysis of the three sets of geophysical data shows an anomaly overlap rate of over 85%, and this result is further validated by borehole data with an error margin of less than 10%. This study demonstrates that multi-parameter geophysical coupling can effectively characterize the thermo-hydro-chemical processes associated with coal fires, thereby providing critical technical support for the accurate identification of fire boundaries and the implementation of disaster mitigation measures in arid regions. Full article

Sparse matrix–vector multiplication (SpMV) is a fundamental kernel in high-performance computing (HPC) whose efficiency depends heavily on the storage format across central processing unit (CPU) and graphics processing unit (GPU) platforms. Conventional supervised approaches often use execution time as training labels, but our experiments on 1786 matrices reveal two issues: labels are unstable across runs due to execution-time variability, and single-label assignment overlooks cases where multiple formats perform similarly well. We propose a dynamic labeling strategy that assigns a single label when the fastest format shows clear superiority, and multiple labels when performance differences are small, thereby reducing label noise. We further extend feature analysis to multi-dimensional structural descriptors and apply clustering to refine label distributions and enhance prediction robustness. Experiments demonstrate 99.2% accuracy in hardware (CPU/GPU) selection and up to 98.95% accuracy in format prediction, with up to 10% robustness gains over traditional methods. Under cost-aware, end-to-end evaluation that accounts for feature extraction, prediction, conversion, and kernel execution, CPUs achieve speedups up to 3.15× and GPUs up to 1.94× over a CSR baseline. Cross-round evaluations confirm stability and generalization, providing a reliable path toward automated, cross-platform SpMV optimization. Full article

Efficient biomass harvesting remains one of the primary barriers to the commercial feasibility of large-scale microalgal production. This study investigates the effect of different culture media on the surface physicochemical properties of Tetradesmus sp., with emphasis on their role in natural aggregation. Cultures were grown for 30 days under controlled light and temperature conditions using Blue Green 11 (BG11), Tris–acetate–phosphate (TAP), and deionized water supplemented with Bayfolan^® fertilizer. Surface hydrophobicity was assessed through microbial adhesion to solvents (MATS) and contact angle analysis, electrokinetic properties were evaluated by zeta potential measurements, and cell surface chemistry was characterized by attenuated total reflectance (ATR) sampling methodology for Fourier Transform Infrared (FTIR) spectroscopy. Across all treatments, Tetradesmus sp. exhibited inherent hydrophobicity, but Bayfolan^® supplementation yielded the highest contact angle (49.0 ± 0.9°) and the least negative free energy of interaction (ΔGsws = −26.36 mJ·m⁻²), indicating a stronger tendency toward self-aggregation. Zeta potential values remained consistently negative (−10 to −14 mV), with no significant variation among media, suggesting that hydrophobic interactions rather than electrostatic forces govern aggregation. ATR-FTIR spectra confirmed the presence of lipids, proteins, and carbohydrates, with changes in peak intensities reflecting metabolic adjustments to media composition. These results demonstrate that low-cost Bayfolan^® supplementation enhances surface hydrophobicity and aggregation, providing a sustainable strategy to facilitate biomass recovery and reduce harvesting costs in microalgal biorefineries. Full article

Sparse Matrix–Vector Multiplication (SpMV) is a critical computational kernel in high-performance computing (HPC) and artificial intelligence (AI). However, its irregular memory access patterns lead to frequent cache misses on multi-level cache hierarchies, significantly degrading performance. Scratchpad memory (SPM), a software-managed, low-latency on-chip memory, offers improved data locality and control, making it a promising alternative for irregular workloads. To enhance SpMV performance, we propose a vectorized execution framework targeting SPM-augmented processors. Recognizing the limitations of traditional formats for vectorization, we introduce Sorted-Row-Block ELL (SRB-ELL), a new matrix storage format derived from ELLPACK (ELL). SRB-ELL stores only non-zero elements, partitions the matrix into row blocks, and sorts them by block size to improve load balance and SIMD efficiency. We implement and evaluate SRB-ELL on a custom processor architecture with integrated SPM using the gem5 simulator. Experimental results show that, compared to vectorized CSR-based SpMV, the SRB-ELL design achieves up to 1.48× speedup and an average of 1.19×. Full article

Submicron particles (SPs), with diameters less than 1.0 μm, are a serious health risk, and urban meteorology variables (MVs), impacted by human activity, can support their sustainability. This study, in a city immersed in a basin geomorphology, is carried out during the summer period of high temperatures and variable relative humidity. An area of high urban density was selected, with the presence of high-rise buildings, urban canyons that favor heat islands, low forestation, intense vehicular traffic, and extreme conditions for MVs. Hourly measurements, in the form of time series, record the number of SPs (for diameters of 0.3, 0.5, and 1.0 μm) along with MVs (temperature (T), relative humidity (RH), and wind speed magnitude (WS)). The objective is to verify whether MVs (RH, T) promote the sustainability of SPs. For this purpose, Spearman’s analysis and a heavy-tailed probability function were used. The central tendency probability, a Gaussian distribution, was discarded since its probability does not discriminate extreme events. Spearman’s analysis yielded significant p-values and correlations between PM₁₀, PM_5.0, PM_2.5, and SPs. However, this was not the case between MVs and SPs. By applying a heavy-tailed probability analysis to extreme events, the results show that MVs such as T and RH act in ways that can favor the accumulation and persistence of SP concentrations. This tendency could have been exacerbated during the measurement period by heat waves and a geographical environment under the influence of a prolonged drought resulting from climate change and global warming. Full article

Background: The aims of this paper are to examine the impact of the COVID-19 pandemic on the non-rational use of antibiotics and potential alterations in the antibiotic resistance profiles of multi-drug resistant (MDR) isolates of Klebsiella pneumoniae (KPN), Pseudomonas aeruginosa (PAE), and Acinetobacter baumannii (ABA). Material and Methods: This study was conducted at the tertiary University Hospital “Dr Dragisa Misovic-Dedinje” (Belgrade, Serbia) and was divided into three periods: pre-pandemic (1.4.2019–31.3.2020, period I), COVID-19 pandemic (1.4.2020–31.3.2021, period II), and COVID-19 pandemic-second phase (1.4.2021–31.3.2022, period III). Cultures were taken from each patient with clinically suspected infection (symptoms, biochemical markers of infection). All departments of the hospital were included in this study. Based on the source, all microbiological specimens were divided into 1° blood, 2° respiratory tract (tracheal aspirate, bronchoalveolar lavage fluid, throat, sputum), 3° central-line catheter, 4° urine, 5° urinary catheter, 6° skin and soft tissue, and 6° other (peritoneal fluid, drainage sample, bioptate, bile, incisions, fistulas, and abscesses). After the isolation of bacterial strains from the samples, an antibiotic sensitivity test was performed for each individual isolate with the automated Vitek^® 2 COMPACT. Antibiotic consumption testing was performed by the WHO guideline equations (ATC/DDD). Results: A total of 2196 strains of KPN, PAE, and ABA from 41,144 hospitalized patients were isolated (23.6% of the number of total isolates). The number of ABA isolates statistically increased (p = 0.021), while the number of PAE isolates statistically decreased (p = 0.003) during the pandemic. An increase in the percentage of MDR strains was observed for KPN (p = 0.028) and PAE (p = 0.027). There has been an increase in the antibiotic resistance of KPN for piperacillin–tazobactam, the third and fourth generations of cephalosporins (ceftriaxone, ceftazidime, and cefepime), all carbapanems (imipenem, meropenem, and ertapenem), and levofloxacin; of PAE for imipenem; and of ABA for amikacin. Total antibiotic consumption increased (from 755 DBD to 1300 DBD, +72%), especially in the watch and reserve group of antibiotics. The highest increases were noted for vancomycin, levofloxacin, azithromycin, and meropenem. MV positively correlated with the increased occurrence of MDR KPN (r = 0.35, p = 0.009) and MDR PAE (r = 0.43, p = 0.009) but not for MDR ABA (r = 0.09, p = 0.614). There has been a statistically significant increase in the Candida sp. isolates, but the prevalence of Clostridium difficile infection remained unchanged. Conclusions: The COVID-19 pandemic has influenced the increase in total and MDR strains of KPN, ABA, and PAE and worsened their antibiotic resistance profiles. An increase in the consumption of both total and specific antibiotics was observed, mostly of fluoroquinolones and carbapenems. A positive correlation between the number of patients on MV and an increase in MDR KPN and MDR PAE strains was noted. It is necessary to adopt and demand the implementation of appropriate antimicrobial stewardship interventions to decrease the resistance of intrahospital pathogens to antibiotics. Full article

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