Search Results (7,195)

Effective network intrusion detection using anomaly scores from unsupervised machine learning models depends on the performance of the models. Although unsupervised models do not require labels during the training and testing phases, the assessment of their performance metrics during the evaluation phase still requires comparing anomaly scores against labels. In real-world scenarios, the absence of labels in massive network datasets makes it infeasible to calculate performance metrics. Therefore, it is valuable to develop an algorithm that calculates robust performance metrics without using labels. In this paper, we propose a novel algorithm, Expectation Maximization-Area Under the Curve (EM-AUC), to derive the Area Under the ROC Curve (AUC-ROC) and the Area Under the Precision-Recall Curve (AUC-PR) by treating the unavailable labels as missing data and replacing them through their posterior probabilities. This algorithm was applied to two network intrusion datasets, yielding robust results. To the best of our knowledge, this is the first time AUC-ROC and AUC-PR, derived without labels, have been used to evaluate network intrusion detection systems. The EM-AUC algorithm enables model training, testing, and performance evaluation to proceed without comprehensive labels, offering a cost-effective and scalable solution for selecting the most effective models for network intrusion detection. Full article

Transition metal oxides, distinguished by their high theoretical specific capacitance values, inexpensive cost, and low toxicity, have been extensively utilized as electrode materials for high-performance supercapacitors. Nevertheless, their conductivity is generally insufficient to facilitate rapid electron transport at high rates. Therefore, research on bimetallic oxide electrode materials has become a hot spot, especially in the field of micro-supercapacitors (MSC). Hence, this study presents the preparation of bimetallic oxide electrode materials via electro-spark machining (EM), which is efficient, convenient, green and non-polluting, as well as customizable. The fabricated copper-molybdenum bimetallic oxide (MoCuO_x) device showed good electrochemical performance under the electrode system. It provided a high areal capacity of 50.2 mF cm⁻² (scan rate: 2 mV s⁻¹) with outstanding cycling retention of 94.9% even after 2000 cycles. This work opens a new window for fabricating bimetallic oxide materials in an efficient, environmental and customizable way for various electronics applications. Full article

Terraces are an important form of surface modification, and their spatial distribution data are of utmost importance for ensuring food and water security. However, the extraction of terrace patches faces challenges due to the complexity of the terrain and limitations in remote sensing (RS) data. Therefore, there is an urgent need for advanced technology models that can accurately extract terraces. High-resolution RS data allows for detailed characterization of terraces by capturing more precise surface features. Moreover, leveraging deep learning (DL) models with local adaptive improvements can further enhance the accuracy of interpretation by exploring latent information. In this study, we employed five models: ResU-Net, U-Net++, RVTransUNet, XDeepLabV3+, and ResPSPNet as DL models to extract fine patch terraces from GF-2 images. We then integrated morphological, textural, and spectral features to optimize the extraction process by addressing issues related to low adhesion and edge segmentation performance. The model structure and loss function were adjusted accordingly to achieve high-quality terrace mapping results. Finally, we utilized multi-source RS data along with terrain elements for correction and optimization to generate a 1 m resolution terrace distribution map in the Zuli River Basin (TDZRB). Evaluation results after correction demonstrate that our approach achieved an OA, F1-Score, and MIoU of 96.67%, 93.94%, and 89.37%, respectively. The total area of terraces in the Zuli River Basin was calculated at 2557 ± 117.96 km² using EM with our model methodology; this accounts for approximately 41.74% ± 1.93% of the cultivated land area within the Zuli River Basin. Therefore, obtaining accurate information on patch terrace distribution serves as essential foundational data for terrace ecosystem research and government decision-making. Full article

The applicability of Hybrid Energy Storage Systems (HESSs) has been shown in multiple application fields, such as Charging Stations (CSs), grid services, and microgrids. HESSs consist of an integration of two or more single Energy Storage Systems (ESSs) to combine the benefits of each ESS and improve the overall system performance. In this work, we propose a novel power management controller called the Hybrid Controller for the efficient HESS’s charging and discharging, considering the State of Charge (SoC) of the HESS and the dynamic supply and load. The Hybrid Controller optimises the use of the HESS, i.e., minimises the amount of energy drawn from and discharged to the grid, thus utilising and prioritising the provided Photovoltaic (PV) power. The performance of our proposal was assessed via simulation using various evaluation metrics, i.e., Autarky, charge/discharge cycle, and Self-Consumption (SC), where we defined 24 scenarios in different locations in Germany. Full article

Recent advances in cryo-electron microscopy (cryo-EM) have facilitated the high-resolution structural determination of macromolecular complexes in their native states, providing valuable insights into their dynamic behaviors. However, insufficient understanding or experience with the cryo-EM image processing parameters can result in the loss of biological meaning. In this paper, we investigate the dihydrolipoyl acetyltransferase (E2) inner core complex of the pyruvate dehydrogenase complex (PDC) and reconstruct the 3D maps using five different symmetry parameters. The results demonstrate that the reconstructions yield structurally identical 3D models even at a near-atomic structure. This finding underscores a crucial message for researchers engaging in single-particle analysis (SPA) with relatively user-friendly and convenient image processing software. This approach helps reduce the risk of missing critical biological details, such as the dynamic properties of macromolecules. Full article

Background: The tiller number is a key agronomic trait for increasing the yield potential of wheat (Triticum aestivum L.). A number of quantitative trait loci (QTLs) and key genes controlling tillering have been identified, but the regulatory mechanisms remain unclear. Methods: In this study, we utilized the dwarf-monoculm mutant (dmc) obtained from the ethyl methane sulfonate (EMS)-treated wheat cultivar Guomai 301. The F₂ populations were constructed using the dmc mutant crossed to multiple tiller parents. The F₂ populations were surveyed for tillering traits at the critical fertility stage for genetic analyses. The extreme-tillering-phenotype plants from the F₂ population were used to construct mixing pools that were analyzed by a wheat 55K SNP array. The tillering genes of dmc were mapped using the wheat 55K SNP array combined with transcriptomic data. Results: The results showed that the genetic phenotype of dmc is controlled by two dominant genes. The tillering genes of dmc were mapped on the 60–100 Mb region of chromosome 5B and the 135–160 Mb region of chromosome 7A. A total of sixteen candidate genes associated with the tillering trait of dmc were identified. Two candidate genes, TraesCS5B02G058800 and TraesCS7A02G184200, were predicted to be involved in indole acetic acid (IAA) response and transport, which were considered as potential regulatory genes. Conclusions: This study elucidated the genetic basis of the dmc mutant and provided two valuable reference genes for studying the development and regulatory mechanisms of wheat tillering. Full article

Background: The World Health Organization (WHO) estimates that 180,000 patients die from burns every year, which is considered a serious public health issue. Patients with burns require immediate pre-hospital care and transport to specialized treatment facilities. The aim of this study was to outline the profile of the burn patient from the perspective of the Polish Medical Air Rescue (PMAR), as well as to analyze the medical procedures being implemented. Methods: The study includes 2154 interventions by air emergency medical teams (AEMS) which provided aid for burn patients. The analysis covered the period from 2018 to 2022, including nationwide data made available from the IT systems of the PMAR. Statistical design was used, allowing for correlations of variables, at a significance level of p < 0.05. Results: Patients’ ages ranged from 1 month to 96 years (mean 35.05; SD ± 26.88). Adult patients (n = 1409; 65.41%) constituted the vast majority. The number of interventions to children below 1-year-old was noticeable (n = 394; 18.29%). Men were the most likely to suffer burns, up to three times more often than women (n = 1574, 73.07% vs. n = 570, 26.46%. T29—burns to multiple body areas (n = 890)—and T21—burns to the trunk (n = 255)—were most frequently reported as diagnoses according to the ICD-10 classification. A statistically significant association was found between age group and ICD-10 diagnosis (p < 0.001). The vast majority of patients were transported from the scene directly to Burn Treatment Centers (n = 1373; 63.74%). Treatment of pain by helicopter emergency medical services (HEMS) crews appeared to be effective (p < 0.001), and other interventions consisted of administering medications—ketamine (23.72%), rocuronium bromide (15.78%), propofol (14.02%)—and procedures such as sedation (30.87%), as well as intubation (13.42%) and mechanical ventilation (13.23%). Conclusions: The burn patient profile indicates men with a mean age of 35 years. Nevertheless, HEMS crews often carry out missions to infants and newborns. The most common diagnosis was extensive body burns. In 63.74% of the missions, patients were transported to the Burn Treatment Center. The HEMS crews implement effective pharmacological analgesia, and handle rescue medications and procedures to stabilize the patient’s condition. Full article

Commonly found landmines, such as the TM-62M, MON-100, and PDM-1, in the recent Russia–Ukraine war confirm the continued use of metals in munitions. Traditional demining techniques, primarily relying on handheld metal detectors and Ground Penetrating Radar (GPR) systems, remain state of the art for subsurface detection. However, manual demining with handheld metal detectors can be slow and pose significant risks to operators. Drone-based metal detection techniques offer promising solutions for rapid and effective landmine detection, but their reliability and accuracy remain a concern, as even a single missed detection can be life-threatening. This study evaluates the potential of an airborne metal detection system as an alternative to traditional handheld detectors. A comparative analysis of three distinct metal detectors for landmine detection is presented: the EM61Lite, a sensitive airborne metal detection system (tested in a pseudo-drone-based scenario); the CTX 3030, a traditional handheld all-metal detector; and the ML 3S, a traditional handheld ferrous-only detector. The comparison focuses on the number of metallic targets each detector identifies in a controlled test field containing inert landmines and UXOs. Our findings highlight the strengths and limitations of airborne metal detection systems like the EM61Lite and emphasize the need for advanced processing techniques to facilitate their practical deployment. We demonstrate how our experimental normalization technique effectively identifies additional anomalies in airborne metal detector data, providing insights for improved detection methodologies. Full article

We show that analyzing archived and future multibeam backscatter and bathymetry data, in tandem with regional environmental parameters, can help to identify polymetallic nodule fields in the world’s oceans. Extensive archived multibeam transit data through remote areas of the world’s oceans are available for data mining. New multibeam data will be made available through the Seabed 2030 Project. Uniformity of along- and across-track backscatter, backscatter intensity, angular response, water depth, nearby ground-truth data, local slope, sedimentation rate, and seafloor age provide thresholds for discriminating areas that are permissive to nodule presence. A case study of this methodology is presented, using archived multibeam data from a remote section of the South Pacific along the Foundation Seamounts between the Selkirk paleomicroplate and East Pacific Rise, that were collected during the 1997 Foundation–Hotline expedition on R/V Atalante. The 12 kHz Simrad EM12D multibeam data and the other forementioned data strongly suggest that a previously unknown nodule occurrence exists along the expedition transit. We also compare the utility of three different backscatter products to demonstrate that scans of printed backscatter maps can be a useful substitute for digital backscatter mosaics calculated using primary multibeam data files. We show that this expeditious analysis of legacy multibeam data could characterize benthic habitat types efficiently in remote deep-ocean areas, prior to more time-consuming and expensive video and sample acquisition surveys. Additionally, utilizing software other than specialty sonar processing programs during this research allows an exploration of how multibeam data products could be interrogated by a broader range of scientists and data users. Future mapping, video, and sampling cruises in this area would test our prediction and investigate how far it might extend to the north and south. Full article

Magnetic and electromagnetic techniques have a long history of application in mineral exploration to detect deposits and their surroundings. Their implementation over the last fifteen years has been affected by strong variations in the mining market in parallel with important technological developments. During this period, both methods were the subject of numerous documented case studies all over the globe, which is a sign of popularity and longevity of these techniques. Through a review of case histories from the main geophysical journals, we analyze the principal usage of these methods when applied to mineral exploration, while the majority of documented cases originate from North America, Asia, and Australia. There are more case studies describing the use of the magnetic method and we attribute this popularity to direct and indirect use of this method for mineral exploration. In particular, there is an increasing number of magnetic surveys conducted with drones. Combining magnetic and electromagnetic techniques is also common. The number of magnetic and EM technique case histories range by descending order from gold, porphyry copper, polymetallic, massive sulfides, uranium, Ni-Cu-PGE, iron ore, kimberlite, and iron-oxide copper-gold, with a number of single continent-specific applications. Full article

Saquinavir is a drug used as an HIV treatment, with recent reports of new uses. It has poor aqueous solubility and very low oral bioavailability. However, when prepared in a eutectic mixture with the natural bioenhancer, piperine, it demonstrated improvements in these drawbacks. Therefore, considering that EMs can be easily produced and scaled-up, it could potentially be used in new pharmaceutical formulations. For this purpose, an analytical method capable of quantifying SQV in the presence of PIP is required for quality control purposes. In this context, UV–Vis equipment is simpler to use and cheaper than HPLC, and it is commonly available in most laboratories. Therefore, a derivative spectrophotometry method at 245 nm was developed and validated to quantify SQV. The method showed good linearity from 0.5 to 100.0 mg/L, with a limit of detection and limit of quantification of 0.331 mg/L and 0.468 mg/L, respectively. Furthermore, it was precise, accurate, and demonstrated good specificity up to a 1:4.3 SQV:PIP ratio. Consequently, the results demonstrate that the method can be employed for SQV quantification in the presence of PIP as an economical and simple technique. This contribution could be the basis for a quality control technique for these types of products. Full article

Satellite-derived observations of ocean colour provide continuous data on chlorophyll-a concentration (Chl-a) at global scales but are limited to the ocean’s surface. So far, biogeochemical models have been the only means of generating continuous vertically resolved Chl-a profiles on a regular grid. MULTIOBS is a multi-observations oceanographic dataset that provides depth-resolved biological data based on merged satellite- and Argo-derived in situ hydrological data. This product is distributed by the European Union’s Copernicus Marine Service and offers global multiyear, gridded Chl-a profiles within the ocean’s productive zone at a weekly temporal resolution. MULTIOBS addresses the scarcity of observation-based vertically resolved Chl-a datasets, particularly in less sampled regions like the Eastern Mediterranean Sea (EMS). Here, we conduct an independent evaluation of the MULTIOBS dataset in the oligotrophic waters of the EMS using in situ Chl-a profiles. Our analysis shows that this product accurately and precisely retrieves Chl-a across depths, with a slight 1% overestimation and an observed 1.5-fold average deviation between in situ data and MULTIOBS estimates. The deep chlorophyll maximum (DCM) is adequately estimated by MULTIOBS both in terms of positioning (root mean square error, RMSE = 13 m) and in terms of Chl-a (RMSE = 0.09 mg m⁻³). The product accurately reproduces the seasonal variability of Chl-a and it performs reasonably well in reflecting its interannual variability across various depths within the productive layer (0–120 m) of the EMS. We conclude that MULTIOBS is a valuable dataset providing vertically resolved Chl-a data, enabling a holistic understanding of euphotic zone-integrated Chl-a with an unprecedented spatiotemporal resolution spanning 25 years, which is essential for elucidating long-term trends and variability in oceanic primary productivity. Full article

This paper presents a conceptual framework aimed at integrating Digital Twins and cyber-physical production systems into the energy management of manufacturing facilities. To address the challenges of rising energy costs and environmental impacts, this framework combines digital modeling and customized energy management for direct manufacturing operations. Through a review of the existing literature, essential components such as physical models, a data platform, an energy optimization platform, and various interfaces are identified. Key requirements are defined in terms of functionality, performance, reliability, safety, and additional factors. The proposed framework includes the physical system, data platform, energy management system, and interfaces for both operators and external parties. The goal of this framework is to set the basis for allowing manufacturers to reduce energy consumption and costs during the lifecycle of assets more effectively, thereby improving energy efficiency in smart manufacturing. The study highlights opportunities for further research, such as real-world applications and sophisticated optimization methods. The advancement of Digital Twin technologies holds significant potential for creating more sustainable factories. Full article

Phase noise is a consequence of the instability inherent in the operation of oscillators, making it impossible to entirely eliminate. For low-cost internet of things (IoT) devices, this type of noise can be particularly pronounced, posing a challenge in providing high-quality localization services. To tackle this issue, this paper introduces an improved localization algorithm that includes phase noise compensation. The proposed algorithm enhances the direction of arrival (DoA) estimation for each base station by employing the EM–MUSIC method, subsequently forming a non-convex optimization problem based on the mean square error (MSE) of the estimated DoA results. Finally, a closed-form solution is derived through rational assumptions and approximations. Results show that this algorithm effectively minimizes localization errors and achieves accuracy levels within the sub-meter range. Full article

For inertial platforms with unknown model parameters and internal information, traditional model-free controllers fail to resist external vibrations solely based on the platform gyroscope, deteriorating the performance of inertial platforms. Therefore, we apply the light gradient boosting machine (LightGBM) to identify an end-to-end platform model, followed by proposing a data-driven MPC scheme to improve the control performance. Furthermore, an expectation maximization (EM) method is designed to solve the optimization problems with non-differentiable identification models, which are challenges for the traditional gradient descent-based optimizer. In addition, an adaptive compensation strategy is designed for generalizing the data-driven control scheme to different external vibrations. Finally, experimental results demonstrate the feasibility, efficacy, and generalization ability of the proposed method. Full article