Search Results (20,286)

The emergence of new Anaplasma strains in the Mediterranean region poses a challenge for both veterinary medicine and public health, as it can lead to more complex diagnostic and treatment strategies. Species related to Anaplasma platys and A. phagocytophilum, two important tick-borne pathogens, have been reported in several Mediterranean countries. However, the data on their presence in Sardinia remain limited. This study aimed to identify theAnaplasmaspecies genetically related to zoonotic agents, such as A. phagocytophilum or A. platys, in Sardinian horses, cattle, and swine. Using various molecular approaches targeting the groEL and gltA genes, the results confirm the presence of Candidatus (Ca.) Anaplasma turritanum and reveal the emergence of Candidatus (Ca.) Anaplasma cinensis and an A. phagocytophilum-like strain, designated as A. phagocytophilum-like 2, in Sardinian horses and cattle. These findings underscore the importance of ongoing surveillance in Sardinia and similar Mediterranean regions, as well as the urgent need for enhanced diagnostic tools and preventive strategies. Given the zoonotic potential of these emerging strains, these findings emphasize the need for greater vigilance in both veterinary and human health sectors to mitigate the risks associated with tick-borne Anaplasma species transmission. Ongoing research and proactive measures are essential to reduce the public health burden and prevent the spread of these pathogens across animal and human populations. Full article

Detecting fraudulent behaviors in electricity consumption is a significant challenge for electric utility companies due to the lack of information and the complexity of both constructing patterns and distinguishing between regular and fraudulent consumers. This study proposes a methodology based on data analytics that, through the processing of information, generates lists of suspicious metering systems for fraud. The database provided by the electrical distribution company contains 266,298 records, of which 15,013 have observations for possible frauds. One of the challenges lies in managing the different variables in the training data and choosing appropriate evaluation metrics. To address this, a balanced database of 27,374 records was used, with an equitable division between fraud and non-fraud cases. The features used in the identification and construction of patterns for non-technical losses were crucial, although additional techniques could be applied to determine the most relevant variables. Following the process, several popular classification models were trained. Hyperparameter optimization was performed by using grid search, and the models were validated by using cross-validation techniques, finding that the ensemble methods Categorical Boosting (CGB), Light Gradient Boosting Machine (LGB) and Extreme Gradient Boosting (EGB) are the most suitable for identifying losses, achieving high performance and reasonable computational cost. The best performance was compared by measuring accuracy (Acc) and F1 score, which allows for the evaluation of various techniques and is a combination of two metrics: detection rate and precision. Although CGB achieved the best performance in terms of accuracy (Acc = 0.897) and F1 (0.894), it was slower than LGB, so it is considered the ideal classifier for the data provided by the electrical distribution company. This research study highlights the importance of the techniques used for fraud detection in electricity metering systems, although the results may vary depending on the characteristics of the training, the number of variables, and the available hardware resources. Full article

This study explores the in situ measurement of contact temperature in thermo-elastohydrodynamic lubrication (TEHL) within cylindrical roller thrust bearings (CRTBs) utilizing vapour-deposited resistive thin-film sensors. The sensors, optimized for compactness and high spatial resolution, were strategically embedded on the stationary bearing raceways near the outer, inner, and mean radius. This configuration enabled a precise measurement of temperature variations in both pure rolling and rolling–sliding regions of the CRTBs. The experimental results revealed a consistent decrease in temperature from the inner and outer radius zones towards the mean radius as the slip-to-roll ratio (SRR) decreased in these regions. Temperature profiles showed an early rise in the inlet zone attributed to thermal inlet shear. At higher speeds, a secondary temperature peak indicative of full-film lubrication was observed in the outlet zone immediately following the Hertzian contact. The study further shows the influence of surface pressure, shear rates, sliding friction, and circumferential speed on contact temperature dynamics, offering insights into their complex interplay. Additionally, viscosity variations due to different oil temperatures were found to critically affect the rate of temperature rise and the propensity for mixed friction phenomena. A higher viscosity resulted in an earlier onset of the temperature rise in the contact, while a lower viscosity and higher speeds promote mixed lubrication, leading to reduced contact film temperatures. These findings provide valuable insights into the behaviour of CRTB-lubricated contacts under various operating conditions and serve as crucial validation data for advanced TEHL computational models. Full article

Since vehicle attitude cannot be readily measured, this paper designs a state observer based on the information available on the CAN bus. The attitude angle estimated in this way is not only robust in practical applications but can also replace an IMU sensor for accurate remaining fuel range prediction under complex driving conditions. The primary innovation of this work is the development of an extended Kalman filter (EKF)-based estimation of the vehicle pitch attitude angle and its deployment in real-world vehicle systems. Firstly, a vehicle longitudinal model considering the suspension dynamics is established, followed by a model-based extended Kalman filter (EKF) design. Then, the EKF algorithm is verified by a co-simulation using Simulink and CarSim of typical working conditions. Numerical tests indicate the effectiveness of the EKF algorithm, with the estimation error being below 0.5°. Finally, the proposed EKF is engineered to range-extended NETA electrical vehicles and applied for reliable remaining fuel range prediction. The mass-production application proves that the EKF observer can respond to changes in body pitch motion stably and rapidly, and the estimated error is less than 1.5°. Full article

Outbreaks involving carbapenemase-producing enterobacteria (CPE) have become a common occurrence in healthcare settings. While clonal dissemination is firmly established as a cause for these outbreaks, horizontal gene transfers (HGTs) between different species of Enterobacterales found in clinical and environmental isolates are less so. To gather evidence backing up this hypothesis, a review covering the 2013–2024 period was performed. HGTs between different species of clinical and environmental Enterobacterales were identified in thirteen papers, half of those published within the last three years. A combination of short- and long-read whole genome sequencing (WGS) was predominantly used to identify mobile genetic elements and plasmids. The more frequently reported carbapenemases were KPCs, followed by NDMs and IMPs. Predictably, broad-host-range plasmids were responsible for over 50% of HGTs, with the IncA/C group being in the lead. Klebsiella pneumoniae and Enterobacter cloacae complexes were the most frequent species identified in clinical samples, while Citrobacter freundii dominated environmental ones. Drains and pipework frequently constituted CPE reservoirs in protracted outbreaks, alternating epidemic outbursts with silent phases. Including WGS in a systematic environmental surveillance would help in swiftly identifying those CPE reservoirs and possibly help better control plasmid outbursts by allowing the implementation of adequate infection prevention and control measures. Full article

To obtain a more comprehensive understanding of the specific properties of complex-shaped technical aerosols—such as partially sintered aggregates formed in combustion processes or structured particles resulting from complex synthesis processes—it is essential to measure more than a single equivalent size. This study examines a novel method for determining a two-dimensional distribution of two distinct particle properties within the size range from $50\mathrm{nm}$ to $1000\mathrm{nm}$: the Centrifugal Differential Mobility Analyzer (CDMA). The CDMA enables the simultaneous measurement of both mobility and Stokes equivalent diameters, providing a detailed two-dimensional particle property distribution. This, in turn, allows for the extraction of shape-related information, which is essential for characterizing particles in terms of their chemical composition, reactivity, and other physicochemical properties. This paper presents a detailed evaluation of a first CDMA prototype. First, CFD simulations of the flow field within the classifier are presented in order to assess and understand non-idealities arising from the exact geometry. Subsequently, the transfer function is evaluated by particle trajectory calculations based on the simulated flow field. It can be demonstrated that the simulated transfer functions agree quite well with transfer functions derived from streamlines of an ideal flow field, indicating that the non-idealities in the classifying region are almost negligible in their effect on the classification result. An experimental determination of the transfer function shows additional effects not covered by the previous simulations, like broadening by diffusion and losses due to diffusion and precipitation within the in- and outlet of the classifier. Finally, the determined transfer functions are used to determine the full two-dimensional distribution with regard to the mobility and Stokes equivalent diameter of real aerosols, like spherical particles and aggregates at different sintering stages, respectively. Full article

The pervasive use of social media platforms, such as X (formerly Twitter), has become a part of our daily lives, simultaneously increasing the threat of cyber attacks. To address this risk, numerous studies have explored methods to detect and predict cyber attacks by analyzing X data. This study specifically examines the application of AI techniques for predicting potential cyber threats on X. DeepNN consistently outperforms competing methods in terms of overall and average figure of merit. While character-level feature extraction methods are abundant, we contend that a semantic focus is more beneficial for this stage of the process. The findings indicate that current studies often lack comprehensive evaluations of critical aspects such as prediction scope, types of cybersecurity threats, feature extraction techniques, algorithm complexity, information summarization levels, scalability over time, and performance measurements. This review primarily focuses on identifying AI methods used to detect cyber threats on X and investigates existing gaps and trends in this area. Notably, over the past few years, limited review articles have been published on detecting cyber threats on X, especially those concentrating on recent journal articles rather than conference papers. Full article

Background/Objectives: The complex pathophysiology of painful cervical radiculopathy is only partially understood. Neuroimmune activation in the dorsal root ganglion and spinal cord is assumed to underlie the genesis of radicular pain. Molecular positron emission tomography (PET) using the radiotracer [¹¹C]DPA713, which targets the 18-kDa translocator protein (TSPO), offers the ability to quantify neuroinflammation in humans in vivo. The primary objectives of this study were to (1) assess whether uptake of [¹¹C]DPA713, a metric of neuroinflammation, is higher in the neuroforamina and spinal cord of patients with painful cervical radiculopathy compared with that in pain-free participants and (2) assess whether [¹¹C]DPA713 uptake is associated with clinical parameters, such as pain intensity. Methods: Dynamic 60 min [¹¹C]DPA713 PET/CT scans were acquired, and regions of interest were defined for neuroforamina and spinal cord. Resulting time-activity curves were fitted to a single-tissue compartment model using an image-derived input function, corrected for plasma-to-whole blood ratios and parent fractions, to obtain the volume of distribution (V_T) as the primary outcome measure. Secondary neuroinflammation metrics included 1T2k V_T without metabolite correction (1T2k_WB) and Logan V_T. Results: The results indicated elevated levels of 1T2k V_T at the neuroforamina (p < 0.04) but not at the spinal cord (p = 0.16). Neuroforamina and spinal cord 1T2k V_T lack associations with clinical parameters. Secondary neuroinflammatory metrics show associations with clinical parameters such as the likelihood of neuropathic pain. Conclusions: These findings enhance our understanding of painful cervical radiculopathy’s pathophysiology, emphasizing the neuroforamina levels of neuroinflammation as a potential therapeutic target. Full article

Although fiber–matrix interfacial strengths, which affect the mechanical properties of fiber-reinforced plastics (FRPs), are considered to be determined by complex factors, few studies have systematically evaluated the relationship between the matrix properties and the fiber–matrix interfacial shear strength. In this study, the properties of various thermoplastics were measured, and the matrix tightening stress that constricts the fiber was simulated using finite element method (FEM) analysis. The relationships between the fiber–matrix interfacial shear strength and the matrix properties were clarified. The mechanical properties of carbon fiber reinforced thermoplastic (CFRTP) laminates were also evaluated, and the relationships between the fiber–matrix interfacial shear strength and the mechanical properties of CFRTP laminates were examined. The fiber–matrix interfacial shear strength showed a positive correlation with the matrix tightening stress tightening the fiber in the radial direction, as well as with matrix density, tensile strength, modulus, and melting temperature, while a negative correlation was found with the coefficient of linear expansion of the matrix. A higher fiber–matrix interfacial shear strength can be achieved by using a matrix with higher density, even without direct evaluation of the fiber–matrix interfacial strength, as the fiber–matrix interfacial shear strength showed a strong positive correlation with matrix density. Furthermore, the mechanical properties of CFRTP laminates were enhanced when matrices with higher fiber–matrix interfacial shear strength were used. Full article

Solid-State Drives (SSDs) enabled the implementation of real-time cloud services, with a primary focus on high performance and high availability. SSD failure prediction can improve overall system availability by preventing data loss and service interruption. SSDs employ a built-in SMART (Self-Monitoring, Analysis, and Reporting Technology) system to predict failures when certain operating parameters exceed predefined thresholds. Such univariate SMART-based models can predict a limited set of drive failures. Research in SSD failure prediction is focused on multivariate models, which can exploit the complex interactions between SMART attributes that lead to drive failure in order to detect a much larger set of failures. This paper presents an anomaly detection model, based on the Mahalanobis distance measure, which is used for the failure prediction of SSD drives. The model is able to rank the features according to their influence on failure prediction by using a forward feature selection algorithm. The proposed model is tested on a publicly available Alibaba SSD dataset, where the six highest-ranked SMART features were identified. Using this subset of SMART features, our model was able to detect 64% of failures with 81% accuracy while keeping a high precision of 96%. Full article

The diaphragm wall plays an important role in the safe construction of foundation pits, and it is crucial to accurately monitor its deformation in real time. Traditional monitoring methods often face challenges in achieving distributed monitoring, and the cost of using fiber optic sensors for real-time and distributed monitoring can be prohibitively high. To improve the monitoring efficiency and accuracy of the deep deformation of the diaphragm wall, this paper proposes a hybrid monitoring method that combines ultra-weak fiber Bragg grating (UWFBG) technology and traditional FBG sensors. This distributed–discrete optical fiber monitoring approach allows for continuous, high-resolution data collection along the diaphragm wall while providing targeted, real-time measurements at critical locations. Fiber optic crack testing of concrete beam structures was carried out to verify the method of evaluating the health status of structures using distributed fiber optic data. An engineering case study was developed to validate the feasibility of this method. The results demonstrated that the hybrid approach effectively captures the overall deformation distribution of the diaphragm wall while enabling real-time monitoring of key areas, including the detection of crack initiation and propagation. The proposed method offers a significant advancement in deformation monitoring, providing enhanced accuracy, spatial coverage, and the ability to detect both macro-scale trends and micro-scale anomalies, which is particularly beneficial for complex underground structures. Full article

Residual stresses in multilayer thin coatings represent a complex multiscale phenomenon arising from the intricate interplay of multiple factors, including the number and thickness of layers, material properties of the layers and substrate, coefficient of thermal expansion (CTE) mismatch, deposition technique and growth mechanism, as well as process parameters and environmental conditions. A multiscale approach to residual stress measurement is essential for a comprehensive understanding of stress distribution in such systems. To investigate this, two AlGaN/GaN multilayer coatings with distinct layer architectures were deposited on sapphire substrates using metalorganic vapor phase epitaxy (MOVPE). High-resolution X-ray diffraction (HRXRD) was employed to confirm their epitaxial growth and structural characteristics. Focused ion beam (FIB) cross-sectioning and transmission electron microscopy (TEM) lamella preparation were performed to analyze the coating structure and determine layer thickness. Residual stresses within the multilayer coatings were evaluated using two complementary techniques: High-Resolution Scanning Transmission Electron Microscopy—Graphical Phase Analysis (HRSTEM-GPA) and Focused Ion Beam—Digital Image Correlation (FIB-DIC). HRSTEM-GPA enables atomic-resolution strain mapping, making it particularly suited for investigating interface-related stresses, while FIB-DIC facilitates microscale stress evaluation. The residual strain values obtained using the FIB-DIC and HRSTEM-GPA methods were −3.2 × 10⁻³ and −4.55 × 10⁻³, respectively. This study confirms that residual stress measurements at different spatial resolutions are both reliable and comparable at the required coating depths and locations, provided that a critical assessment of the characteristic scale of each method is performed. Full article

Integration with rural tourism is an important way to achieve the sustainable development of ecological farms. Existing literature on the integration of agriculture and tourism lacks discussion from the microscopic farm level, making it difficult to capture the complex mechanisms of the integration of ecological farms and rural tourism. This paper attempts to address this problem by exploring the driving factors of the integration of ecological farms and rural tourism. The research aim of this paper is to construct a theoretical framework for driving the integration of ecological farms and rural tourism. We first conducted research on farms in four ecological agriculture demonstration zones: Ziquejie in Loudi, Hunan Province; Heshi in Shilin, Yunnan Province; Rongjiang in Dali, Yunnan Province; and Youxiqiao Village in Hunan Province. We interviewed 64 stakeholders in ecotourism and used grounded theory methods to construct a model and propose hypotheses. On this basis, a measurement scale was designed, and data was collected from 1041 Chinese ecological farms (ecological farm operators) using a structured questionnaire. The partial least squares structural equation model (PLS-SEM) was used to model and analyze the data to test the constructed model. The study found that higher market demand, regional economic level, intrinsic development needs, intrinsic resource endowments, technical support, and resource integration can promote the integration of ecological farms and rural tourism. Market demand and intrinsic development needs constitute the generative force of agritourism integration, while resource integration and intrinsic resource endowments constitute the development force of agritourism integration, and technical support and the regional economic level constitute the supporting force of agritourism integration. Full article

Absorption of electromagnetic waves in a broadband frequency range with polarization insensitivity and wide incidence angles is greatly needed in modern technological applications. Many methods using metamaterials have been suggested to address this requirement; they can be complex multilayer structures or use external electronic components. In this paper, we present a plasmonic metasurface structure that was simply fabricated using the standard printed circuit board technique but provided a high absorption above 90%, also covering a broadband frequency range from 12.30 to 14.80 GHz. This plasmonic metasurface consisted of structural unit cells composed of multiple split rings connected by a copper bar. Analysis, simulation, and measurement results showed that the metasurface also showed polarization-insensitive properties and maintained an absorption above 90% at incident angles up to 45 degrees. The suggested plasmonic metasurface is a fundamental design that can also be used to design the absorber in different frequency ranges and is able to adapt well to being fabricated at various scales. Full article

This study investigates how the simultaneous development of multiple urban megaprojects creates synergistic effects in residential property markets, with significant implications for urban planning and policy. Through an enhanced hedonic pricing model incorporating inter-project interaction terms, the research quantifies both individual and collective impacts of concurrent developments on property values. Analysis of comprehensive transaction data (2016–2022) reveals complex patterns of complementary and competing effects between proximate megaprojects, demonstrating that their combined impact differs substantially from the sum of their individual effects. The findings highlight the critical importance of coordinated planning approaches that consider inter-project dynamics when designing urban regeneration strategies. This research provides the first empirical measurement of megaproject synergy effects, offering valuable insights for policymakers and investors in optimizing the economic outcomes of transformational flagship buildings. Full article