Hasil untuk "Engineering"

Ivica Kladarić, Stjepan Golubić, Danko Ćorić et al.

The article examines the effect of different types of two-layer nanostructured coatings (cVIc and nACVIc) deposited on three types of steel substrates, 45S20, C45E, and 42CrMo4, to determine the resistance to adhesive wear of the substrate/coating system. The samples underwent different heat treatments, including normalising, quenching, and quenching and tempering, followed by PVD (physical vapour deposition) treatment at temperatures of 450 °C (cVIc) and 460 °C (nACVIc). The thickness of the cVIc layers for all three steels ranged from 0.9 to 3.4 μm, while the thickness of the nACVIc layers on all steels was slightly greater, ranging from 1.9 to 3.1 μm. Tribological tests were conducted using the pin-on-disc method, and the results were statistically analysed. Results indicate that steel grade, heat treatment, and PVD coating significantly affect adhesive wear resistance, with the type of PVD coating showing the strongest influence. For all three steels, quenched and uncoated samples exhibited the lowest adhesion wear index values. Normalised and quenched with or without tempering steels coated with cVIc layer exhibit higher resistance to adhesive wear due to better adhesion of the layer compared to the nACVIc coating.

Renato Pereira, José Muralha, Luís Lamas

Este artigo explora a aplicação de métodos probabilísticos na análise da fiabilidade e no dimensionamento do reforço de taludes rochosos sujeitos a mecanismos de rotura planar. O estudo incide no caso de um maciço rochoso intersetado por uma família de descontinuidades paralela à face do talude. O volume com potencial de instabilização é idealizado como um modelo de blocos, para o qual se desenvolve uma formulação em sistemas de componentes. Como termo de comparação, analisa-se igualmente um modelo simplificado que considera o mesmo volume como um bloco único. Os resultados evidenciam a influência da inclinação do plano de deslizamento. Verifica-se que o modelo constituído por múltiplos blocos conduz a índices de fiabilidade inferiores. Contudo, a sua utilização para o dimensionamento probabilístico do reforço tem vantagens apenas para inclinações baixas do plano de deslizamento. A análise sugere ainda que o modelo de blocos múltiplos pode ser adequadamente representado por um modelo simplificado de dois blocos.

Ashraf abdallah, Bara' Al-MISTAREHI, Amir SHTAYAT

Agriculture is a vital component of Egypt's economy; therefore, using Digital Elevation Models (DEMs) in agricultural planning in Egypt has significant benefits regarding water management, site appropriateness assessment, flood risk mitigation, and infrastructure construction. It is also essential for planners to make more informed decisions, optimize resource allocation, and support sustainable farming practices. This research paper investigates the accuracy of obtaining DEM data from four free global models (STRM30, ALOS30, COP30, and TanDEM-X90). The global DEM data has been compared to an actual GNSS-RTK DEM data surveyed onsite for two agricultural block areas in Aswan, the southern Government of Egypt. The two blocks are a part of a national project. For Block I and II, the RMSE of the Model STRM30 was 2.92 m and 3.59 m, respectively, indicating a poorer solution. Regarding accuracy, the ALOS30 model ranks third, reporting an RMSE of 2.58 m for block II and 3.30 m for block I. COP30 has an RMSE value of 1.06 m for blocks I and II and.91 m overall. TanDEM-X90 is the most accurate model in this investigation; block I provided an RMSE of 0.90 m with an SD of 0.58 m (SD95% = 0.38 m). After removing the anomalies, the model's stated RMSE for block II was 0.34 m, with an SD value of 0.62 m and 1.03 m. According to the classification using machine learning algorithms, with an accuracy of 84.7% for block I and 85% for block II, TanDEM-X90 is the best solution.

Majid Riaz, Pedro Guerra, Raffaele Gravina

This paper introduces an innovative EEG sensor-based computational framework that establishes a pioneering nexus between personality trait quantification and neural dynamics, leveraging biosignal processing of brainwave activity to elucidate their intrinsic influence on cognitive health and oscillatory brain rhythms. By employing electroencephalography (EEG) recordings from 21 participants undergoing the Trier Social Stress Test (TSST), we propose a machine learning (ML)-driven methodology to decode the Big Five personality traits—Extraversion (Ex), Agreeableness (A), Neuroticism (N), Conscientiousness (C), and Openness (O)—using classification algorithms such as support vector machine (SVM) and multilayer perceptron (MLP) applied to 64-electrode EEG sensor data. A novel multiphase neurocognitive analysis across the TSST stages (baseline, mental arithmetic, job interview, and recovery) systematically evaluates the bidirectional relationship between personality traits and stress-induced neural responses. The proposed framework reveals significant negative correlations between frontal–temporal theta–beta ratio (TBR) and self-reported Extraversion, Conscientiousness, and Openness, indicating faster stress recovery and higher cognitive resilience in individuals with elevated trait scores. The binary classification model achieves high accuracy (88.1% Ex, 94.7% A, 84.2% N, 81.5% C, and 93.4% O), surpassing the current benchmarks in personality neuroscience. These findings empirically validate the close alignment between personality constructs and neural oscillatory patterns, highlighting the potential of EEG-based sensing and machine-learning analytics for personalized mental-health monitoring and human-centric AI systems attuned to individual neurocognitive profiles.

Nuiyen Aussanee, Khumin Vinta, Wichai Siriwan

Cadmium contamination found in paddy fields in the Maesot District of Tak Province, Thailand. This area was remediated using 50mg/L of ZVI. The study aimed to isolate and identify soil bacteria in the soil and rice roots and to investigate ZVI’s effect on the isolated bacterial cells. The results indicated no significant difference in soil bacteria content before and after remediation at the 95% confidence level. Twelve isolates of nitrogen-fixing bacteria were obtained. Those isolates could grow at high concentrations of 300 mg/L of ZVI. RH17 had a high tolerance for TSA with 300 mg/L of ZVI at only 10 CFU/ml. The effects of ZVI at 150 mg/L on RH17 cells, a small amount of ZVI was observed adhering to the cells’ surface and forming giant cells, while at 300 mg/L of ZVI, caused a reduction in growth by 81.0%. The nifH gene of RH17 was related to Rhizobium sp. strain 5-1-2. The results demonstrated the cadmium remediation process with 50mg/L of ZVI did not affect the cell count of soil bacteria in the paddy field. However, at 150 mg/L or higher, ZVI damaged the isolated Rhizobium sp. cell membrane. So, the remediation using ZVI must consider the appropriate concentration.

Li Ji, Huayong Zhang, Huayong Zhang et al.

Warming is a key factor influencing the function of the structure and function of phytoplankton communities. However, the impacts of temperature on phytoplankton resource use efficiency (RUE) in mountain rivers remain poorly understood. Here, the spatiotemporal patterns of phytoplankton community structure (biomass, community composition, and diversity), function (RUE), and the main environmental factors in a high-latitude mountainous stream were investigated to assess how temperature affects the phytoplankton RUE. The results showed that phytoplankton species richness, biomass, and RUE all increased with rising temperature, with species richness significantly higher. There was a shift in the phytoplankton community from dominated by Cyanophyta at lower temperatures to dominated by Cryptophyta at higher temperatures. Phytoplankton RUE was significantly positively correlated to species richness, but no significant relationship was observed between RUE and Pielou’s evenness. Furthermore, redundancy analysis and Mantel tests revealed that water temperature, nutrient (TP, and NH4+-N) and physicochemical variable (flow velocity, and dissolved oxygen) explained 40.40% of the overall variation in phytoplankton RUE. Phytoplankton RUE exhibited stronger responses to environmental variables than phytoplankton biomass or diversity. The results highlighted that temperature directly affected phytoplankton community composition and enhanced RUE by altering environmental conditions and biodiversity. Temperature plays a crucial role in shaping the structure and function of phytoplankton communities in rivers. Our results contribute to the deep understanding of the mechanisms by which temperature influences RUE providing a basis for the sustainable management and conservation of aquatic ecosystems and watersheds.

Phat T. Nguyen, Duy C. Huynh, Loc D. Ho et al.

Amidst the rapid global expansion of smart grids, ensuring the safety and reliability of power transmission systems has become paramount. Insulators are critical components of high-voltage transmission lines, providing both electrical insulation and mechanical support. However, their exposure to electrical, mechanical, and environmental stressors renders them vulnerable point within the system. Defective insulators are a major cause of failures in power transmission systems. Consequently, the early and accurate detection of these defects is pivotal for maintaining the integrity and reliability of the power grid. To address this challenge, this study proposes InsDD-YOLO, a novel object detection architecture enhanced from the YOLOv13 framework. The model incorporates a suite of strategic enhancements, including an improved DSConv (IDSConv) module for robust feature extraction, a streamlined Neck architecture augmented with a feature stream from a shallower layer (B2) to improve small-target detection, and a direct Head connection mechanism to maximize the preservation of fine-grained details. Experimental results demonstrate that InsDD-YOLO achieves superior performance, reaching an mAP0.5 of 90.1% and an mAP<inline-formula> <tex-math notation="LaTeX">${}_{0.5:0.95}$ </tex-math></inline-formula> of 46.4%, outperforming the baseline YOLOv13 model by a significant 5.0% in mAP0.5. With an inference time of just 5.4 ms, the proposed model not only establishes a new benchmark for accuracy but also demonstrates an effective trade-off between performance and speed, underscoring its significant potential for deployment in real-time, automated power grid monitoring systems.

Rory Ward, Dan Bigioi, Shubhajit Basak et al.

While current research predominantly focuses on image-based colorization, the domain of video-based colorization remains relatively unexplored. Many existing video colorization techniques operate frame-by-frame, often overlooking the critical aspect of temporal coherence between successive frames. This approach can result in inconsistencies across frames, leading to undesirable effects like flickering or abrupt color transitions between frames. To address these challenges, we combine the generative capabilities of a fine-tuned latent diffusion model with an autoregressive conditioning mechanism to ensure temporal consistency in automatic speaker video colorization. We demonstrate strong improvements on established quality metrics compared to existing methods, namely, PSNR, SSIM, FID, FVD, NIQE and BRISQUE. Specifically, we achieve an 18% improvement in performance when FVD is employed as the evaluation metric. Furthermore, we performed a subjective study, where users preferred LatentColorization to the existing state-of-the-art DeOldify 80% of the time. Our dataset combines conventional datasets and videos from television/movies. A short demonstration of our results can be seen in some example videos available at <uri>https://youtu.be/vDbzsZdFuxM</uri>.

Jehad Al Dallal, Bader Alkhazi

The cohesion of an object-oriented class refers to the relatedness of its methods and attributes. Constructors, destructors, and access methods are special types of methods featuring unique characteristics that can artificially affect class cohesion quantification. Methods within a class can also directly or transitively invoke each other, representing another cohesion aspect not considered by most existing cohesion measures. The impact of considering special methods (SPs) and transitive relations (TRs) in cohesion measurement on the abilities of the measures to predict inheritance reusability has yet to be investigated. In this paper, we empirically explored this effect. We applied a statistical technique to test the significance of the cohesion value changes across seven scenarios of ignoring or considering SPs and TRs. In addition, we applied a machine learning-based technique to build inheritance reusability prediction models using each of the considered measures and scenarios, evaluated the classification performance of the prediction models, and statistically compared the inheritance reusability prediction results. The results show that for most of the considered measures, the ignorance/consideration of SPs and TRs changed the cohesion values and the corresponding prediction significantly. Based on the study findings, when building inheritance reusability prediction models, software engineers are advised to 1) combine cohesion with other quality factors; 2) exclude the TRs from cohesion quantification; and 3) decide whether to consider or ignore SPs in cohesion quantification based on the selected measure(s) to be used in the prediction model, as this decision differs from one measure to another.

Shengyan Wang, Huijia Dai, Qingling Tang et al.

Pichia pastoris is one of the most commonly used hosts for producing heterologous proteins, whereas production levels vary depending on the protein of interest and are also regulated by regulatory factors. We conducted RNA-seq by expressing the reporter EGFP and observed significant upregulation of certain subunits (Sec61p, Sbh1p, Sss1p, Sec66p and Sec72p) of the Sec complex in the high-expression recombinant GS115 stains. The overexpression of these genes may increase the expression levels of heterogeneous proteins. In this study, the endogenous promoters of the Sec complex subunits Sbh1p, Sss1p, Sec66p and Sec72p were isolated and verified their activity using the Lac-Z reporter gene. Sss1, Sbh1, Sec66 and Sec72 were overexpressed under the control of their own promoters in Pichia pastoris, respectively. The overexpression of Sss1, Sbh1, Sec66 and Sec72 in cells was confirmed by fluorescent microscope and Western blot analysis. The α-amylase was employed to evaluate the effect of overexpression of the Sec subunits on the heterologous protein expression. The results demonstrated that the α-amylase activity increased by 16%, 58%, 16% and 17% in the strains overexpressing Sss1, Sbh1, Sec66 and Sec72, respectively. Engineering the protein translocation pathway can be an alternative to enhance heterogeneous proteins in Pichia pastoris expression system.

Panuluh Albertus Hariwangsa, Morozumi Takuya

We study the hierarchy between MT , vL, and vR, the relevant energy scales of the Minimal Universal Seesaw Model (MUSM), where the two lightest quark families remain massless at tree level. We also predict the heavy top quark mass, mt′ . We do some numerical analysis using recent experimental data. Our numerical analysis demonstrates that MT is sensitive to the values of the Yukawa couplings. The heavy top quark mass (mt′ ) is predicted to be within the range from 1.4 TeV to 7.2 TeV for vR = 10 TeV.

Jinichi Sakaguchi, Keisuke Nakayama, Katsuaki Komai et al.

Carbon capture and storage due to photosynthesis activities has been proposed as a carbon sink to mitigate climate change. To enhance such mitigation, previous studies have shown that freshwater lakes should be included in the carbon sink, since they may capture as much carbon as coastal areas. In eutrophic freshwater lakes, there is uncertainty about whether the equilibrium equation can estimate the partial pressure of carbon dioxide (pCO2), owing to the presence of photosynthesis due to phytoplankton, and pH measurement error in freshwater fluid. Thus, this study investigated the applicability of the equilibrium equation and revealed the need to modify it. The modified equilibrium equation was successfully applied to reproduce pCO2 based on total alkalinity and pH through field observations. In addition, pCO2 at the water surface was lower than the atmospheric partial pressure of carbon dioxide due to photosynthesis by phytoplankton during strong stratification. The stratification effect on low pCO2 was verified by using the Net Ecosystem Production (NEP) model, and a submerged freshwater plants such as Potamogeton malaianus were found to have high potential for dissolved inorganic carbon (DIC) sequestration in a freshwater lake. These results should provide a starting point toward more sophisticated methods to investigate the effect of freshwater carbon on DIC uptake in freshwater stratified eutrophic lakes.

Shuai Wang, Zongbao Zhang, Chao Wang

Abstract The mining of open pit mines is widespread in China, and there are many cases of landslide accidents. Therefore, the problem of slope stability is highlighted. The stability of the slope is a factor that directly affects the mining efficiency and the safety of the entire mining process. According to the statistics, there is a 15 percent chance of finding landslide risk in China’s large-scale mines. And due to the expansion of the mining scale of the enterprise, the problem of slope stability has become increasingly obvious, which has become a major subject in the study of open-pit mine engineering. In order to better predict the slope stability coefficient, this study takes a mine in China as a case to deeply discuss the accuracy of different algorithms in the stability calculation, and then uses a deep learning algorithm to study the stability under rainfall conditions. The change of the coefficient and the change of the stability coefficient before and after the slope treatment are experimentally studied with the displacement of the monitoring point. The result shows that the safety coefficient calculated by the algorithm in this paper is about 7% lower than that of the traditional algorithm. In the slope stability analysis before treatment, the safety factor calculated by the algorithm in this paper is 1.086, and the algorithm in this paper is closer to reality. In the stability analysis of the slope after treatment, the safety factor calculated by the algorithm in this paper is 1.227, and the stability factor meets the requirements of the specification. It also shows that the deep learning algorithm effectively improves the efficiency of the slope stability factor prediction and improves security during project development.

Iwa Pramudya, Deny Andesta, Hidayat Hidayat

Work accidents have the ability to cause the formation of every work activity. Aspects of work accidents can be caused by machines or aspects of worker negligence. The comfort of workers is highly dependent on the situation and the industrial area. One of the markers that need to be observed is occupational safety and health. So that the industry applies the K3 listed on PT Swadaya Graha which is currently still in a non-HIRARC condition as a basis for mitigation. The HIRARC procedure finds a procedure that starts to ensure the activity after which the source of the hazard is identified, risk assessment, and control over that exists and has the aim of remembering the level of risk associated with a place. From that case, the author thinks it is necessary to carry out an OHS risk assessment using the HIRARC procedure by carrying out research that aims to find out how to analyze the capabilities of hazards that can be carried out and their control on a cnc lathe machine at PT Swadaya Graha . The procedure used is the HIRARC (Hazard Identification Risk Assessment and Risk control) approach. The results of this research are that there are 5 work disaster hazard capabilities in the Ministry of CNC BUBUT. After that this research shows there is no. 1. extreme type of hazard. risk, and 1 high risk and 3 medium risk. The most common hazard abilities occur because of the lack of PPE and the undisciplined workers and not exploring work SOPs. Therefore, it is necessary to try socialization and continue to emphasize through daily safety briefings and safety signs.

Hamza Abu Owida, Jamal I. Al-Nabulsi, Feras Alnaimat et al.

Tissue engineering is a relatively new area of research that combines medical, biological, and engineering fundamentals to create tissue-engineered constructs that regenerate, preserve, or slightly increase the functions of tissues. To create mature tissue, the extracellular matrix should be imitated by engineered structures, allow for oxygen and nutrient transmission, and release toxins during tissue repair. Numerous recent studies have been devoted to developing three-dimensional nanostructures for tissue engineering. One of the most effective of these methods is electrospinning. Numerous nanofibrous scaffolds have been constructed over the last few decades for tissue repair and restoration. The current review gives an overview of attempts to construct nanofibrous meshes as tissue-engineered scaffolds for various tissues such as bone, cartilage, cardiovascular, and skin tissues. Also, the current article addresses the recent improvements and difficulties in tissue regeneration using electrospinning.

Tusar Kanti Roy

Donghwan Song, Adrian Matias Chung Baek, Jageon Koo et al.

Over the past decades, additive manufacturing has rapidly advanced due to its advantages in enabling diverse material usage and complex design production. Nevertheless, the technology has limitations in terms of quality, as printed products are sometimes different from their desired designs or are inconsistent due to defects. Warping deformation, a defect involving layer shrinkage induced by the thermal residual stress generated during manufacturing processes, is a major factor in lowering the quality and raising the cost of printed products. This study utilized a variety of thermal time series data and the K-nearest neighbors (KNN) algorithm with dynamic time warping (DTW) to detect and predict the warping deformation in the printed parts using fused deposition modeling (FDM) printers. Multivariate thermal time series data extracted from thermocouples were trained using DTW-based KNN to classify warping deformation. The results showed that the proposed approach can predict warping deformation with an accuracy of over 80% by only using thermal time series data corresponding to 20% of the whole printing process. Additionally, the classification accuracy exhibited the promising potential of the proposed approach in warping prediction and in actual manufacturing processes, so the additional time and cost resulting from defective processes can be reduced.

S. H. Pervak, Ya. L. Zinher, Yu. F. Adamenko et al.

Мікросмужкові фільтри широко застосовують в радіоелектронних системах. Фільтри нижніх частот конструюють на основі квазізосереджених індуктивностей та ємностей. Квазізосереджену ємність виконують як мікросмужкову секцію із широким сигнальним провідником або як розімкнутий шлейф, з’єднаний з основною лінією. Традиційні конструкції таких ємностей двовимірні (2D) у вигляді відрізків мікросмужкової лінії. Запропоновані авторами тривимірні (3D) квазізосереджені елементи мають в 1,5…4 рази більші значення реактивних параметрів. Розімкнутий 3D-шлейф являє собою глухий металізований отвір у діелектричній основі, з’єднаний з основною лінією. У статті розглянуто конструктивні відмінності 2D та 3D ємнісних шлейфів. 3D-шлейф як порівняти з 2D-шлейфом має суттєво кращі параметри: його хвильовий імпеданс менший в 1,4…3,5 рази, а ємність більша в 1,6…4,1 рази. Оскільки для фільтра необхідні задані значення ємності, площа 3D-шлейфа відповідно менша. 3D-моделюванням проаналізовано особливості залежностей електричних параметрів 3D-шлейфа від його конструктивних параметрів. Показано, що частота режекції шлейфа дорівнює частоті резонанса шлейфа з паразитною індуктивністю, зумовленою шлейфним Т-з’єднанням. У разі традиційних розмірів контакта шлейфа та основної лінії ця індуктивність від’ємна, що призводить до збільшення значення частоти режекції і, відповідно, погіршення крутості амплітудно-частотних характеристик шлейфа та фільтра. Для зменшення паразитної індуктивності запропоновано конструктивне рішення у вигляді контактного майданчика між лінією та шлейфом. Досліджено залежності цієї індуктивності від конструктивних параметрів шлейфа та майданчика. Оптимізація розмірів контактного майданчика дозволяє оптимізувати значення індуктивності з умови необхідної крутості амплітудно-частотної характеристики. Запропоновано одновимірну модель 3D-шлейфа, що характеризує його еквівалентними хвильовим імпедансом та відносною діелектричною проникністю. Ця модель може використовуватися як модель першого наближення під час проектування та дослідження мікросмужкових фільтрів на основі ємнісних 3D-шлейфів.

Walter Fuertes, Francisco Reyes, Paúl Valladares et al.

Cyber-attacks have increased in severity and complexity. That requires, that the CERT/CSIRT research and develops new security tools. Therefore, our study focuses on the design of an integral model based on Business Intelligence (BI), which provides reactive and proactive services in a CSIRT, in order to alert and reduce any suspicious or malicious activity on information systems and data networks. To achieve this purpose, a solution has been assembled, that generates information stores, being compiled from a continuous network transmission of several internal and external sources of an organization. However, it contemplates a data warehouse, which is focused like a correlator of logs, being formed by the information of feeds with diverse formats. Furthermore, it analyzed attack detection and port scanning, obtained from sensors such as Snort and Passive Vulnerability Scanner, which are stored in a database, where the logs have been generated by the systems. With such inputs, we designed and implemented BI systems using the phases of the Ralph Kimball methodology, ETL and OLAP processes. In addition, a software application has been implemented using the SCRUM methodology, which allowed to link the obtained logs to the BI system for visualization in dynamic dashboards, with the purpose of generating early alerts and constructing complex queries using the user interface through objects structures. The results demonstrate, that this solution has generated early warnings based on the level of criticality and level of sensitivity of malware and vulnerabilities as well as monitoring efficiency, increasing the level of security of member institutions.

L. Gil, L. Jiménez, A. C. Castro et al.

La aleación de aluminio 7075-T6 es una aleación estructural ampliamente utilizada para aplicaciones aeronáuticas, debido a su alta relación entre resistencia mecánica y peso. Dependiendo de las condiciones ambientales, algunos mecanismos de corrosion tales como intergranular, exfoliacion, picadura y crevice se ha encontrado que ocurren en estructuras de aviones de aleaciones de aluminio. Un avance siginificativo para mejorar el comportamiento de esta aleación es la aplicación de recubrimientos autocatalíticos de Ni-P, los cuales confieren una excelente resistencia a la corrosión acoplado con una reducción del desgaste erosivo y un aumento de la dureza. El propósito de este trabajo fue investigar el efecto de la aplicación de un recubrimiento de Ni-P sobre la resistencia a la corrosión de una aleación de aluminio 7075-T6. Los resultados obtenidos indican que la aplicación del recubrimiento de Ni-P disminuye la susceptibilidad a la picadura y hace a la aleación de aluminio 7075 T6, prácticamente inmune al ataque por corrosion expoliación.