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Found 6273 publications
Effect of Spirulina platensis on the content values of wheat bread
Publication Name: Scientific Reports
Publication Date: 2026-12-01
Volume: 16
Issue: 1
Page Range: Unknown
Description:
Due to their nutritional composition, algae are promising ingredients in the development of new foods. The aim of our work was to prepare bread containing Spirulina platensis (new name Arthrospira platensis) in different percentages (0.5, 1.0, 2.5%) within the framework of the MSZ 6369/8-1988 standard, and to determine its content (dry matter, ash, fat, protein/nitrogen, fiber content, carbohydrate content, and polyoxide, color), as well as its texture and color. Furthermore, we assessed consumer opinions through a sensory evaluation. We found that increasing the width and shape fraction while decreasing the height. The results showed that the antioxidant and polyphenols properties of Spirulina-enriched breads increased. The protein, nitrogen, fibre content increased and carbohydrate, energy value properties of Spirulina-enriched breads decreased with increasing concentration of algae. Spirulina powder increased the greenness of the bread and decreased the lightness of the crumb. The hardness, cohesiveness and springiness increased with the addition of Spirulina to bread, while the gumminess and chewiness values became lower compared to the control. Consumer acceptability results showed that the addition of Spirulina at a concentration of 2.5% significantly reduced overall acceptance. Our results indicated that Spirulina cyanobacteria, can be a suitable raw material for making bread, also from the point of view of healthier and sustainable nutrition.
Open Access: Yes
Evaluating blockchain-based waste management investments in smart cities using a multi-criteria decision support framework
Publication Name: Scientific Reports
Publication Date: 2026-12-01
Volume: 16
Issue: 1
Page Range: Unknown
Description:
With growing urbanization, there are increasing demands on waste management systems that can be performed in an environmentally friendly way as well as efficiently. Current approaches to managing waste often have issues with efficiency, transparency, and engaging with the public. Blockchain technology has been identified as one potential solution to these problems because it offers several benefits including decentralization, security, and transparency. The selection of the best blockchain-based waste management (BBWM) system is very difficult due to the many different evaluation criteria that may conflict with each other. Therefore this research uses a multi-criteria decision making (MCDM) approach using CIMAS (Criteria Importance Assessment), for determining weights based upon subjective input, and LOPCOW (Logarithmic Percentage Change-Driven Objective Weighing), for determining weights based upon objective data within the MCDM framework. To rank alternatives effectively, an Alternative Ranking Order Method Accounting for Two-Step Normalization (AROMAN) technique is applied, ensuring a precise evaluation process. The use of T-Spherical Fuzzy Sets (T-SFS) captures all three (membership, non-membership, hesitation degree) and is used to address the variability that exists when making an expert judgment. Some of the key factors include; Technological Feasibility, Operational Costs, Scalability, Data Security, Regulatory Compliance, Environmental Impact. Based on the evaluation criteria, it appears that the Blockchain Enabled Waste Tracking System is the most appropriate alternative due to its high potential for Transparency, Regulatory Compliance and Fraud Prevention. In addition, this research will provide Policymakers, Urban Planners and Investors with a methodical way of making Data Driven Decisions on BBWM Investments.
Open Access: Yes
The effect of mixed fatigue on knee biomechanics and muscle activation during sidestep cutting in elite soccer players
Publication Name: BMC Sports Science Medicine and Rehabilitation
Publication Date: 2026-12-01
Volume: 18
Issue: 1
Page Range: Unknown
Description:
Background: Football is one of the most popular sports in the world, and it is also a sport with a high rate of injury. The study aims to investigate the effects of physical and mental mixed fatigue (PMF) on knee biomechanics during sidestep cutting maneuvers in elite male soccer players, thereby assessing the potential mechanisms underlying non-contact knee injuries. Methods: Thirty-six elite male soccer players were recruited (age: 21.61 ± 1.22 years; body mass: 75.16 ± 6.34 kg; height: 175.8 ± 3.53 cm; shoe size: 41–44 EUR). Following a targeted fatigue induction protocol, key lower limb biomechanical data were acquired during anticipated sidestep cutting maneuvers both pre- and post-PMF. Statistical analyses were performed utilizing paired sample t-tests and one-dimensional Statistical Parametric Mapping (SPM1d). Results: Following PMF, knee valgus increased at initial contact (P = 0.022). Kinetic analysis, supported by SPM1d, revealed a marked transition from an extensor-dominant to a flexor-dominant pattern in sagittal knee moments (P = 0.007), alongside elevated knee valgus moments (P = 0.039). Neuromuscularly, quadriceps and lateral gastrocnemius activation (iEMG/RMS) significantly decreased, whereas compensatory increases were observed in the hamstrings and medial gastrocnemius (all P < 0.001). Conclusion: While PMF preserved most kinematics, the statistically significant increase in knee valgus, though small in magnitude, suggests an impaired frontal-plane control that may elevate Anterior Cruciate Ligament (ACL) strain. The shift from quadriceps to hamstring dominance reflects a compensatory neuromuscular strategy. These findings emphasize the importance of incorporating cognitive load into injury-prevention programs and monitoring mental fatigue to reduce non-contact knee injury risks.
Open Access: Yes
Ensemble deep learning approach for traffic video analytics in edge computing
Publication Name: Scientific Reports
Publication Date: 2026-12-01
Volume: 16
Issue: 1
Page Range: Unknown
Description:
Video analytics is the new era of computer vision in identifying and classifying objects. Traffic surveillance videos can be analysed to using computer vision to comprehend the road traffic. Monitoring the real-time road traffic is essential to control them. Computer vision helps in identifying the vehicles on the road, but the present techniques either perform the video analysis on the cloud platform or the edge platform. The former introduces more delay in processing while controlling is needed in real-time, the latter is not accurate in estimating the current road traffic. YOLO algorithms are the most notable ones for efficient real-time object detection. To make such object detections feasible in lightweight environments, its tinier version called Tiny YOLO is used. Edge computing is the efficient framework to have its computation done on the edge of the physical layer without the need to move data into the cloud to reduce latency. A novel hybrid model of vehicle detection and classification using Tiny YOLO and YOLOR is constructed at the edge layer. This hybrid model processes the video frames at a higher rate and produces the traffic estimate. The numerical traffic volume is sent to Ensemble Learning in Traffic Video Analytics (ELITVA) which uses F-RNN to make decisions in reducing the traffic flow seamlessly. The experimental results performed on drone dataset captured at road signals show an increase in precision by 13.8%, accuracy by 4.8%, recall by 17.4%, F1 score by 19.9%, and frame rate processing by 12.8% compared to other existing traffic surveillance systems and efficient controlling of road traffic.
Open Access: Yes
Modelling optimal investment planning for household photovoltaic and battery systems under dynamic electricity market conditions
Publication Name: Discover Sustainability
Publication Date: 2026-12-01
Volume: 7
Issue: 1
Page Range: Unknown
Description:
Capacity sizing and calculating cost savings for residential households in a rapidly evolving energy market, influenced by fluctuating electricity prices and changing government incentives, is a highly complex problem. The key challenges stem from multiple interacting factors, including retail electricity prices, the desired payback period, household size, applicable electricity schemes, and the capacity factor of the photovoltaic (PV) system. The nominal power output of the solar energy system is constrained by both the specifications and the number of installed inverters and PV panels. As solar generation is intermittent and non-dispatchable, it is inherently weather-dependent and often unable to align with the dynamic fluctuations in household electricity consumption. From a financial modelling perspective, the length of the accounting period directly determines the time resolution of the model, influencing both the accuracy of cash flow estimation and investment decision-making. The proposed two-level investment planning model is based on the process network synthesis approach. At the upper level of the process model, solar generation technologies, including inverters and solar panels, are technically and economically assessed. At the lower level, which represents the load consumption side, the periodical energy balances for production, storage, demand, and purchase are considered. In order to accurately evaluate the solar energy system, the model is developed with both a monthly framework and a detailed hourly framework. The time resolution allows the model to account for grid intake, electricity sold, and storage inventory conditions over the defined periods, ultimately providing the optimal sizing for a solar system equipped with battery storage. Case studies are conducted to investigate the effects of household size, extended payback periods, varying retail electricity prices, and grid reliability. These scenarios demonstrate the key parameters that significantly influence the economic feasibility and optimal sizing of the solar energy system, which are discussed in detail in this paper.
Open Access: Yes
Discovery of potential antiviral compounds and accelerating the therapeutic discovery against monkeypox virus
Publication Name: Scientific Reports
Publication Date: 2026-12-01
Volume: 16
Issue: 1
Page Range: Unknown
Description:
Monkeypox virus is a zoonotic virus of the genus Orthopox viruses. It can be transmitted through direct or indirect contact with animals or infected ones. Owing similarity of pathogenesis with smallpox, the same drugs can be used for both viruses, but they are not specific and only help to relieve the symptoms only. Therefore, the absence of antiviral treatment or licensed vaccine highlights an urgent need, especially due to its rapid prevalence. The study screened the library of compounds to retrieve drug-like molecules that can act against monkeypox virus. The highly virulent target gene B8R having uniport ID Q3I8J0 was chosen. Targeting B8R is substantial for global health and can align with SDG 3 and awareness of disease management. The B8R was modelled via Artificial intelligence (AI) AlphaFold method and then exposed to a library of compounds. Complementary interactions in the active site were shown by molecular docking. The Complex-1 had the greatest binding affinity (–8.4 kcal/mol), followed by Complex-2 (–8.1 kcal/mol) and Complex-3 (–7.7 kcal/mol). After 125 ns, Complex-1 reached equilibrium at 7.5 Å RMSD, according to MD simulations, exhibiting stable ligand retention and reliable interactions with crucial residues Gly135 and Lys136. Complex-3 shown intermediate protein stability (6 Å RMSD) but notable ligand fluctuation (48 Å RMSF), while Complex-2 displayed increased protein RMSD (8 Å RMSD) and delayed ligand stabilisation (16 Å RMSF). These results were corroborated by PCA analysis, which showed that Complex-1 exhibits coherent structural development whereas Complex-2 and Complex-3 show scattered and compact trajectories, respectively. Complex-1 promise for Mpox viral inhibition was highlighted by the fact that it was the most stable and dynamically favourable contender overall. The N-terminal follows the folding trend. The insilico analysis not only proposed a potent compound but also provides deep insight into the behavior of protein. The proposed potent compound against this zoonotic virus can be helpful to combat the monkeypox virus by subjecting it further towards experimental investigation.
Open Access: Yes
Role of centres in public transport networks
Publication Name: European Transport Studies
Publication Date: 2026-12-01
Volume: 3
Issue: Unknown
Page Range: Unknown
Description:
A well-functioning public transport network is the foundation of sustainable urban mobility. However, the term 'well working' is difficult to define and may be subjective. This paper introduces a network-analytical approach to show the correlation between usage, which reflects the quality of a public transport service, and the structure of its network. This approach is based on Barabási's definition of a scale-free network and physicists' observations of network structures. Ultimately, the paper will show that scale-free public transport networks are more efficient in terms of usage, as modelled by the modal split of the observed cities.
Open Access: Yes
Molecular characterisation of the invasive terrestrial nemertean Geonemertes pelaensis: long and complex mitogenome and presence of NUMTs
Publication Name: Scientific Reports
Publication Date: 2026-12-01
Volume: 16
Issue: 1
Page Range: Unknown
Description:
The complete mitochondrial genome of the invasive terrestrial nemertean Geonemertes pelaensis Semper, 1863 (Nemertea: Prosorhochmidae) was sequenced from two specimens collected in geographically distant French overseas territories—Martinique in the Caribbean and New Caledonia in the South-West Pacific. In both specimens, the mitogenome contained 13 protein-coding genes, two rRNA genes, and 21 tRNA genes, and was unusually large, approaching 32 kb. The two genomes differed by only four single nucleotide polymorphisms and one indel. A comparison with 22 cox1 sequences available in GenBank confirmed this high level of genetic conservation, suggesting a recent introduction from related source populations. The extraordinary length of the mitogenome was largely attributable to two extended regions comprising only tRNA genes and long intergenic sequences. These results were contrasted with data from an unpublished SRA sequencing project (SRS20559370) of an unlocalized specimen identified as G. pelaensis; its reconstructed mitogenome was only 18 kb in length (14 kb shorter) and showed extensive sequence divergence. Phylogenetic analyses placed this specimen as the sister lineage to G. pelaensis, highlighting the need for further investigation of this taxon. In the Martinique specimen, several NUMTs (nuclear mitochondrial pseudogenes) were also detected, which could complicate future studies relying solely on Sanger sequencing. Sequencing additionally revealed prey DNA from the gut contents of both worms: the New Caledonian specimen had consumed an unidentified noctuid moth, while the Martinique specimen had likely fed on the invasive cockroach Periplaneta australasiae (Fabricius, 1775), itself an introduced species.
Open Access: Yes
Antimicrobial use and Escherichia coli resistance patterns in Hungarian pig farms: a data-driven farm-level analysis
Publication Name: Scientific Reports
Publication Date: 2026-12-01
Volume: 16
Issue: 1
Page Range: Unknown
Description:
Antimicrobial resistance (AMR) poses a critical challenge to both human and veterinary medicine, with pig production recognized as one of the major contributor due to intensive antimicrobial usage (AMU). This study aimed to explore the relationship between AMU and AMR patterns of Escherichia coli isolated from commercial pig farms, using data-driven analytical methods. Farm-level records were harmonized with microbiological data from 203 isolates collected in December 2023 across four Hungarian farms. AMU was summarized over 3-, 6-, 9-, and 12-month retrospective windows and expressed in modified population-corrected units, while AMR was quantified as mean minimum inhibitory concentration (MIC) and AMR rate under epidemiological and clinical breakpoints. The results revealed substantial variation in AMU among farms, with amoxicillin predominating across timeframes. Farm-specific comparisons indicated that higher AMU may not always coincide with elevated resistance levels, and data analysis did not consistently identify a direct association between use and resistance at the individual farm level, which warrants further investigation in larger datasets. Correlation analyses identified strong intra-class relationships among β-lactams and fluoroquinolones, as well as a cross-class linking, suggesting concurrent selection pressures. Overall, the integration of AMU and AMR data demonstrated the feasibility of farm-level surveillance for AMR modelling and provides a foundation for future predictive systems to support antimicrobial stewardship in livestock production.
Open Access: Yes
