Search Results (194)

Background: DNA evidence can play a critical role during the investigation of illicit drugs cases. A key challenge, however, is in determining whether DNA profiles recovered on the evidence items, such as drug packages, arise from direct handling or indirect transfer. Methods: In this respect, we simulated common drug offense scenarios where illicit drugs were discovered inside vehicular or household settings that can be linked to the suspect. DNA transfer was evaluated based on two hypothetical propositions: (1) the individual’s DNA was directly deposited onto the mock drug packages through handling, or alternatively (2) DNA persisting on a particular surface had transferred onto the packages. For the direct transfer scenario, 15 participants were requested to pack the mock drug packages using their bare hands. For the indirect transfer scenario, DNA-free mock drug packages were placed at various locations in 15 vehicles and 15 bedrooms for different time intervals. Following each scenario, DNA samples were collected from multiple areas of the mock drug packages. DNA transfer was assessed based on quantification and profiling results, which were subsequently evaluated within a Bayesian network-based framework. Results: Higher DNA transfer frequencies onto the mock drug packages were observed in the direct-handling experiment compared to those from indirect transfer, suggesting that DNA transfer occurs to a higher degree from active contact. In direct-handling scenarios, the amount of DNA recovered from the handles of the carrier bags was much higher than that from the exterior bodies, indicating preferential DNA deposition at the contact areas. Conversely, the results from indirect transfer scenarios showed similar recovered DNA amounts between the handles and the exterior bodies of the carrier bags, with minimal transfer to the interior surfaces. These findings indicate that the likelihood of recovering DNA from specific areas of evidence items can be linked to the particular activities and transfer mechanisms involved. Conclusions: The findings of this study expand the empirical knowledge of DNA transfer processes across diverse forensic contexts. Full article

Background: The increasing prevalence of antibiotic-resistant Mycoplasma genitalium poses a significant challenge to global public health, necessitating the exploration of alternative therapeutic strategies, including vaccine development. Methods: In this study, we employed an immuno-informatics-based reverse vaccinology approach augmented with artificial intelligence-driven tools, to identify and characterize potential B-cell and T-cell epitopes from the hypothetical proteins (HPs) retrieved from the genome of the MG_G37T strain, a previously uncharacterized yet promising vaccine target. Using multiple softwares, a systematic pipeline was utilized to assess the sub-cellular localization, antigenicity, and allergenicity of the selected proteins. Results: Sub-cellular localization analysis identified the presence of several outer membrane and extracellular proteins in the genome of MG_G37T, indicating their surface association and accessibility to immune surveillance. Antigenicity and allergenicity prediction tools led to the identification of two top-scoring hypothetical proteins (fig|2097.71.peg.1 (UniProt ID: P22747) and fig|2097.70.peg.33 (UniProt ID: Q57081)) that demonstrated strong antigenic potential, non-allergenic properties, and suitability as vaccine candidates. Epitope mapping and structural modeling analyses further validated the immunogenic potential of these epitopes, highlighting their ability to interact with host immune components effectively. Comparative analyses with mouse allelic regions indicated the potential translational relevance of these predicted epitopes for preclinical studies. Conclusions: In particular, this study highlights the potential of these two hypothetical proteins as a promising vaccine candidate and provides a strong reason for experimental validation towards the design and development of effective vaccines to combat M. genitalium infections in the era of antimicrobial resistance. Full article

Cybersecurity has become a critical concern in the automotive sector, where the increasing connectivity and complexity of modern vehicles—particularly in the context of autonomous driving—have significantly expanded the attack surface. In response to these challenges, this paper presents the Welcome To The Machine (WTTM) framework, developed to support proactive and structured cyber risk management throughout the entire vehicle lifecycle. Specifically tailored to the automotive domain, the framework encompasses four core actions: detection, analysis, response, and remediation. A central element of WTTM is the WTTM Questionnaire, designed to assess the organizational cybersecurity maturity of automotive manufacturers and suppliers. The questionnaire addresses six key areas: Governance, Risk Management, Concept and Design, Security Requirements, Validation and Testing, and Supply Chain. This paper focuses on the development and validation of WTTM-Q. Statistical validation was performed using responses from 43 participants, demonstrating high internal consistency (Cronbach’s alpha > 0.70) and strong construct validity (CFI = 0.94, RMSEA = 0.061). A supervised classifier (XGBoost), trained on 115 hypothetical response configurations, was employed to predict a priori risk classes, achieving 78% accuracy and a ROC AUC of 0.84. The WTTM framework, supported by a Vehicle Security Operations Center, provides a scalable, standards-aligned solution for enhancing cybersecurity in the automotive industry. Full article

Shiga toxin-producing Escherichia coli (STEC) are genetically diverse foodborne pathogens of major global public health concerns. Serogroup-level identification is critical for effective surveillance and outbreak control; however, it is often challenged by STEC’s genome plasticity and frequent recombination. In this study, we employed a standardized pangenomic pipeline integrating Roary ILP Bacterial Core Annotation Pipeline (RIBAP) and Panaroo to analyze 160 complete, high-quality STEC genomes representing eight major serogroups at a 95% sequence identity threshold. Candidate serogroup-specific markers were identified using gene presence/absence profiles from RIBAP and Panaroo. Our analysis revealed several high-confidence markers, including metabolic genes (dgcE, fcl_2, dmsA, hisC) and surface polysaccharide-related genes (capD, rfbX, wzzB). Comparative pangenomic evaluation showed that RIBAP predicted a larger pangenome size than Panaroo. Additionally, some genomes from the O104:H1, O145:H28, and O45:H2 serotypes clustered outside their expected clades, indicating sporadic serotype misplacements in phylogenetic reconstructions. Functional annotation suggested that most candidate markers are involved in critical processes such as glucose metabolism, lipopolysaccharide biosynthesis, and cell surface assembly. Notably, approximately 22.9% of the identified proteins were annotated as hypothetical. Overall, this study highlights the utility of pangenomic analysis for potential identification of clinically relevant STEC serogroups markers and phylogenetic interpretation. We also note that pangenome analysis could guide the development of more accurate diagnostic and surveillance tools. Full article

Laminosioptes cysticola (Vizioli, 1870), a tissue-dwelling mite responsible for nodular acariasis in birds, was identified from two hens reared in a rural backyard flock in Umbria, Italy. Adult mites were found in the subcutaneous tissue and on the serosal surface of various internal organs. Larval and first- and second-stage nymphal forms were observed beneath the skin and near the trachea and esophageal serosa. By comparing the existing literature with that reported in the present study, we propose a hypothetical reconstruction of the parasite’s life cycle. It is postulated that the entry of L. cysticola occurs through the cervical skin, where adults mate and larviparous females give birth to larvae. These larvae migrate into the loose connective tissues surrounding the trachea and esophagus, where they develop into nymphs. The immature forms then progress along the esophagus and trachea to reach the thoracic and abdominal cavities, colonizing the serosal surfaces of visceral organs. It remains unclear whether, or how, the mites return to the subcutaneous tissues to complete their maturation. Senescent specimens degenerate within the subcutis, where they are encased by a granulomatous inflammatory reaction that leads to the formation of characteristic calcified nodules. Full article

Trichomonas vaginalis, a prevalent sexually transmitted protozoan parasite, is associated with adverse birth outcomes, increased risk of HIV and other sexually transmitted infections, infertility, and cervical cancer. Despite its widespread impact, trichomoniasis remains underdiagnosed and underreported globally. Trichomonas vaginalis virus (TVV), a double-stranded RNA (dsRNA) virus infecting T. vaginalis, could impact T. vaginalis pathogenicity. We provide an overview of TVV, including its genomic structure, transmission, impact on protein expression, role in 5-nitroimidazole drug susceptibility, and clinical significance. TVV is a ~5 kbp dsRNA virus enclosed within a viral capsid closely associated with the Golgi complex and plasma membrane of infected parasites. Hypothetical mechanisms of TVV transmission have been proposed. TVV affects protein expression in T. vaginalis, including cysteine proteases and surface antigens, thus impacting its virulence and ability to evade the immune system. Additionally, TVV may influence the sensitivity of T. vaginalis to treatment; clinical isolates of T. vaginalis not harboring TVV are more likely to be resistant to metronidazole. Clinically, TVV-positive T. vaginalis infections have been associated with a range in severity of genital signs and symptoms. Further research into interactions between T. vaginalis and TVV is essential in improving diagnosis, treatment, and the development of targeted interventions. Full article

Concerning building acoustics, the impact of sound propagation in the building structure can be considered one of the most relevant problems. Floating floors are an efficient solution, composed of a rigid walking surface above a resilient material. Functioning as a spring, the resilient layer must have adequate damping properties and compressive strength against permanent and imposed loads to guarantee its performance over time. In this context, this study aims to completely evaluate the impact sound reduction of composite lightweight floating floors formed by ceramic tiles and recycled rubber mats when subjected to prolonged loads, from material characterization to their application in a hypothetical scenario. This study was based on the dynamic stiffness (ISO 9052-1) and compressive creep (ISO 16534) of the resilient layer and the physical characterization of the ceramic tiles, predicting the present and future (15 years) impact sound reductions and their application in a hypothetical room, considering direct and indirect transmissions paths (ISO 12354-2). The results showed that the lightweight floating floor compositions lost their damping capability to a degree that can reduce their weighted reduction in the impact sound pressure level by up to 2 dB over prolonged periods (15 years). Howsoever, the compositions had considerable initial impact sound insulation capability and adequate performance maintenance over time. Full article

Since 2011, pelagic sargassum blooms (S. fluitans and S. natans) have impacted coastal communities, aquaculture, tourism, and biodiversity across the Tropical Atlantic region. Whilst the initial event is generally attributed to an anomalous North Atlantic Oscillation (2009–2010), the drivers of sargassum movement and proliferation remain unclear. This research gap is particularly evident in West Africa, where annual and seasonal sargassum variability is under-researched, and a lack of consensus exists on seasonal and annual trends. This paper addresses these gaps by (1) providing a first attempt at characterising the seasonal and annual trends of sargassum biomass in the Eastern Tropical Atlantic, through using satellite imagery to create a time-series for 2011–2022; and (2) exploring the hypothetical drivers of movement and proliferation of sargassum for this area, through assessing its co-variation with potential drivers including atmospheric, oceanic, and policy, establishing a historical timeline of events. The time-series analysis reveals an annual biomass peak in September and a second peak between March and May. The exploration of potential drivers reveals that alongside sea surface temperature there are multiple factors that could be influencing sargassum biomass, and that further research is necessary to clarify primary and secondary drivers. The results contribute to understanding drivers, impacts, and predictions of sargassum blooms in the Eastern Tropical Atlantic. We anticipate that our findings will enable sargassum-affected areas to better anticipate the size and timing of sargassum events in West Africa and offer researchers a new perspective on possible drivers of proliferation within the wider Tropical Atlantic region. Full article

The paper considers one of the possible statements of inverse problems in gravimetric and magnetometric remote sensing, proposes a new approach to its solution and formulates algorithms that implement this approach. The problem under consideration consists of finding hypothetical sources of the corresponding potential fields at a given depth based on these fields measured on the Earth’s surface. The problem is reduced to solving systems of linear algebraic equations (SLAE) with ill-conditioned matrices. The proposed approach to the numerical solution is based on improving the condition number of the SLAE’s matrix. A numerical algorithm implementing the proposed approach that is applicable to the stable solution of degenerate and ill-conditioned SLAEs with an approximately given right-hand side is formulated in general form. The algorithm uses the SVD decomposition of the SLAE’s matrix and constructs a new matrix close to the original one with a better (smaller) condition number. An approximate solution to the original SLAE is calculated using the pseudoinverse of the new matrix. The results of a theoretical study of the algorithm are presented and the main properties of the new matrix are given. In particular, the reduction of its condition number is estimated. Several implementations of this algorithm are considered, in particular, the MPMI method, which is based on the use of so-called minimal pseudoinverse matrices. For the model problem, the advantage of the MPMI method over a number of other common methods is shown. The MPMI method is applied to solve the considered problems of gravity exploration and magnetic exploration both in the separate solution of these inverse problems and in their joint solution when processing geophysical data for the Kathu region, in the Northern Cape area of South Africa. Full article

Wind energy is a vital renewable resource with substantial economic and environmental benefits, yet its spatial variability poses significant optimization challenges. This study advances wind farm layout optimization by employing a systematic genetic algorithm (GA) tuning approach using the design of experiments (DOE) method. Specifically, a full factorial 2² DOE was utilized to optimize crossover and mutation coefficients, enhancing convergence speed and overall algorithm performance. The methodology was applied to a hypothetical wind farm with unidirectional wind flow and spatial constraints, using a fitness function that incorporates wake effects and maximizes energy production. The results demonstrated a 4.50% increase in power generation and a 4.87% improvement in fitness value compared to prior studies. Additionally, the optimized GA parameters enabled the placement of additional turbines, enhancing site utilization while maintaining cost-effectiveness. ANOVA and response surface analysis confirmed the significant interaction effects between GA parameters, highlighting the importance of systematic tuning over conventional trial-and-error approaches. This study establishes a foundation for real-world applications, including smart grid integration and adaptive renewable energy systems, by providing a robust, data-driven framework for wind farm optimization. The findings reinforce the crucial role of systematic parameter tuning in improving wind farm efficiency, energy output, and economic feasibility. Full article

While fluvial features are plentiful on Mars and offer valuable insights into past surface conditions, the climatic conditions inferred from these valleys, like precipitation and surface runoff discharges, remain the subject of debate. Model-based estimations have already been applied to several Martian valleys, but exploration of the related numerical estimations has been limited. This work applies an improved precipitation-based, steady-state erosion/accumulation model to a Martian valley and compares it to a terrestrial Mars analogue dessert catchment area. The simulations are based on a previously observed precipitation event and estimate the fluvial-related hydrological parameters, like flow depth, velocity, and erosion/accumulation processes in two different but morphologically similar watersheds. Moderate differences were observed in the erosion/accumulation results (0.13/−0.06 kg/m²/s for Zafit (Earth) and 0.01/−0.007 for Tinto B (Mars)). The difference is probably related to the lower areal ratio of surface on Mars where the shield factor is enough to trigger sediment movement, while in the Zafit basin, there is a larger area of undulating surface. The model could be applied to the whole surface of Mars. Using grain size estimation from the global THEMIS dataset, the grain size value artificially increased above that observed, and decreased hypothetic target rock density tests demonstrated that the model works according to theoretical expectations and is useful for further development. The findings of this work indicate the necessity of further testing of similar models on Mars and a better general analysis of the background geomorphological understanding of surface evolution regarding slope angles. Full article

In this work, WO₃/TiO₂ core–shell (C-S) nanowires (NWs) were successfully synthesized by the coaxial electrospinning method and subsequent high-temperature calcination treatment. After some microscopic structural characterizations, although the prepared WO₃–TiO₂ and TiO₂–WO₃ C-S NWs displayed quite different surface morphologies, both of the shell coatings were uniform and their typical shell thicknesses were extremely close, with mean values of 22 and 20 nm, respectively. In gas sensing tests, WO₃/TiO₂ C-S NWs exhibited good selectivity towards triethylamine (TEA) without significant interfering gases. Compared with bare WO₃ and TiO₂ NWs, WO₃/TiO₂ C-S NWs showed better gas sensing performance. Specifically, the optimal operating temperature and response of TiO₂–WO₃ C-S NWs to 100 ppm TEA were 130 °C and 106, which were reduced by 70 °C and increased by 5.73 times compared to bare WO₃, respectively. Obviously, the C-S nanostructures contributed to improving the gas sensing performance of materials towards TEA. Finally, some hypothetical sensing mechanisms were proposed, which were expected to have important reference significance for the design of target products applied to TEA sensing. Full article

This purely theoretical study considers two new geometric state-space properties of the classical linear time-optimal control problem with one input and real non-positive eigenvalues of the system, with constraints only on the control input and without constraints on the state-space variables, following from Pontryagin’s maximum principle. These properties complement the well-known facts from the maximum principle about the number of switchings of the control function and the character of the optimal phase trajectories of the system leading it to the state-space origin. They lay the foundation of a new method for synthesizing the time-optimal control without the need to describe the switching hyper-surfaces. The new technique is demonstrated on two examples. The so-called “axes initialization” and the synthesis technique are illustrated on the double integrator system in its entirety. The second one is on a hypothetical seventh-order system. Full article

With the recent proliferation of electric vehicles, there is increasing attention on drive motors that are powerful and efficient, with a higher power density. To meet such high power density requirements, the cooling technology used for drive motors is particularly important. To further optimize the cooling effects, the use of direct oil-cooling technology for drive motors is gaining more attention, especially regarding the requirements for electric vehicle electric oil pumps (EOPs) in motor cooling. In such high-temperature environments, it is also necessary for the EOP to maintain its performance under high temperatures. This research explores the feasibility of using high-temperature-resistant ferrite magnets in the rotors of EOPs. For a 150 W EOP motor with the same stator size, three different rotor configurations are proposed: a surface permanent magnet (SPM) rotor, an interior permanent magnet (IPM) rotor, and a spoke-type IPM rotor. While the rotor sizes are the same, to maximize the power density while meeting the rotor’s mechanical strength requirements, the different rotor configurations make the most use of ferrite magnets (weighing 58 g, 51.8 g, and 46.3 g, respectively). Finite element analysis (FEA) was used to compare the performance of these models with that of the basic rotor design, considering factors such as the no-load back electromotive force, no-load voltage harmonics (<10%), cogging torque (<0.1 Nm), load torque, motor loss, and efficiency (>80%). Additionally, a comprehensive analysis of the system efficiency and energy loss was conducted based on hypothetical electric vehicle traction motor parameters. Finally, by manufacturing a prototype motor and conducting experiments, the effectiveness and superiority of the finite element method (FEM) design results were confirmed. Full article

We explore a new approach for the parsimonious, generalizable, efficient, and potentially automatable characterization of spectral diversity of sparse targets in spectroscopic imagery. The approach focuses on pixels which are not well modeled by linear subpixel mixing of the Substrate, Vegetation and Dark (S, V, and D) endmember spectra which dominate spectral variance for most of Earth’s land surface. We illustrate the approach using AVIRIS-3 imagery of anthropogenic surfaces (primarily hydrocarbon extraction infrastructure) embedded in a background of Arctic tundra near Prudhoe Bay, Alaska. Computational experiments further explore sensitivity to spatial and spectral resolution. Analysis involves two stages: first, computing the mixture residual of a generalized linear spectral mixture model; and second, nonlinear dimensionality reduction via manifold learning. Anthropogenic targets and lakeshore sediments are successfully isolated from the Arctic tundra background. Dependence on spatial resolution is observed, with substantial degradation of manifold topology as images are blurred from 5 m native ground sampling distance to simulated 30 m ground projected instantaneous field of view of a hypothetical spaceborne sensor. Degrading spectral resolution to mimicking the Sentinel-2A MultiSpectral Imager (MSI) also results in loss of information but is less severe than spatial blurring. These results inform spectroscopic characterization of sparse targets using spectroscopic images of varying spatial and spectral resolution. Full article