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This paper proposes adding waste plastics to asphalt. Using molecular dynamics to study the properties of modified asphalt after adding polyethylene (PE), and clarify its application direction according to its microscopic characteristics, in order to achieve the goals of resource recycling, environmental protection, improvement of asphalt performance and cost reduction. First, construct the molecular model of asphalt according to the four components of the asphalt molecule; construct the molecular model of PE according to the molecular formula of polyethylene; Secondly, by calculating the solubility parameters and interaction energy of asphalt and PE, the compatibility is judged. Finally, the results of the micromechanical simulations of the original and modified asphalt were compared with the test results of the rheological properties of the asphalt. The research results show that the compatibility between PE and asphalt is the best at 175°C, indicating that this temperature is the best modification temperature of asphalt; the addition of PE increases the order of asphalt molecules, and increases the mechanical modulus of asphalt and high temperature rheological properties. The combination of micro simulation and macro test makes the content of this paper more complete and provides theoretical value for the application of waste PE modified asphalt pavement. [ABSTRACT FROM AUTHOR]

This paper presents a thermal error model for a lathe CNC machine using temperature on moving parts, which is usually a difficult measurement. Different working conditions are performed to obtain temperature and thermal displacement of the machine. A multi-linear regression model is applied for modelling relationship between temperatures and thermal errors. Data of two constant working conditions are implemented to find out the fitting function. Through analysis, it shows that thermal errors for X- and Z-axes can be estimated based on only four temperature points (T2, T3, T10 and T12 for the X-axis and T4, T6, T7 and T11 for the Z-axis). Results reveal that using movable part temperature data (T12), the average and maximum error in the predicted thermal displacement of the X-axis can be reduced about 1/3 and 2/5 compared to without using T12, while the movable temperature point on Z-Screw (T8) has a tiny effect on the average and maximum error of predicted thermal displacement of the Z-axis. Results herein can provide useful information to develop a thermal compensation for the CNC lathe machine. [ABSTRACT FROM AUTHOR]

The inherent randomness in economic factors causes complex and irregular behaviour that affects financial system stability and economic growth. Such chaotic behaviour can make it difficult to synchronize financial systems. The chaotic finance system synchronization precision maintains financial stability and economic growth. In this paper, the controller design procedure assumes that the financial system is exposed to unknown bounded exogenous disturbances and model uncertainties. This research proposes a novel direct adaptive control strategy that achieves robust synchronization of two identical four-dimensional finance chaotic (FDFC) systems. The proposed controller establishes a faster, smoother synchronization error vector convergence to zero. The controller design procedure does not eliminate the closed-loop's nonlinear terms and is independent of the financial system parameters. These controller's attributes accomplish the closed-loop robust performance. Further, this controller uses real-time estimates of unknown model uncertainties and bounds to compensate for unknown exogenous disturbances. Computer simulation results and proofs of theoretical analysis based on the Lyapunov stability theory confirm that the proposed control technique compels the error vector trajectories to the origin in a short transient time with less active oscillations for all signals. The paper includes comparative computer simulations for verifying the theoretical findings. [ABSTRACT FROM AUTHOR]

Switching to low-global warming potential (GWP) propellants for pressurized metered dose inhalers (pMDIs) is crucial in current inhalation product development, as it is crucial to safeguard patient access. This paper provides both theoretical and experimental evidence to advance the understanding of the relative performance of pMDIs using traditional HFA propellants (HFA-134a, HFA-227ea) versus new low-GWP propellant (HFO-1234ze, HFO-1234yf, HFC-152a) across three stages of pMDI actuation: discharge of propellant from the spray orifice, atomization of the bulk liquid into droplets, and interaction with the surrounding environment. The acoustic profiles, which represent the propellant discharge from the spray orifice, revealed that the plume duration and audio amplitude were mostly influenced by the diameter of the orifice and to a lesser extent by propellant type. The initial propellant droplet size produced after atomization of the discharged bulk liquid was evaluated by measuring content equivalent diameters at different ethanol concentrations and spray orifice diameters. Through a 0.32 mm spray orifice, propellant-only pMDIs produced droplets in the 9.0–13.5 µm range, with HFC-152a yielding the largest droplets and HFO-1234yf the smallest, while all exhibited comparable dependence on ethanol concentration and spray orifice size. Modeling of moisture condensation on propellant droplets indicated that the amount of condensed water and droplet lifetime both depend strongly on ambient humidity and ethanol concentration and only weakly on the propellant type. Three suspension formulations in HFA-134a, HFO-1234ze, or HFC-152a, were tested under varying relative humidities to evaluate the impact of ambient humidity on the in vitro aerosol performance of suspension pMDIs. Copyright © 2024 American Association for Aerosol Research [ABSTRACT FROM AUTHOR]

In the subway system, a high concentration of iron particles can cause significant damage to human health, and magnetic filters that efficiently filter out iron particles have attracted considerable attention recently. Therefore, it is both urgent and important to study the influencing factors of magnetic filters for improving filtration efficiency and reducing resistance. In this paper, to establish a filtration model for magnetic filters, the flow field, magnetic field and particle tracking of magnetic filters are calculated in three steps. After the force analysis of particles, it can be concluded that the particle tracking module needs only to consider drag force, magnetic force and gravity. Based on the filtering model, a two-dimensional magnetic filter was simulated on a computer. and the factors affecting filtration efficiency and resistance were analyzed. It was found that an increase in magnetic field intensity and the diameter of the particle have a positive effect on the filtration efficiency of the magnetic filter, while the increase in airflow velocity and the distance between magnets has a negative effect. The increase in distance between magnets has a negative effect on the resistance of the magnetic filter. In particular, the distance between magnets and the strength of magnets are two of the most influential factors. Finally, two simple formulas concerning the relationship between filtration efficiency, resistance and influencing factors were revealed, by which filtration efficiency and resistance in practical magnetic filter design can be calculated. Copyright © 2023 American Association for Aerosol Research [ABSTRACT FROM AUTHOR]

Change Detection (CD) provides a research basis for environmental monitoring, urban expansion and reconstruction as well as disaster assessment, by identifying the changes of ground objects in different time periods. Traditional CD focused on the Binary Change Detection (BCD), focusing solely on the change and no-change regions. Due to the dynamic progress of earth observation satellite techniques, the spatial resolution of remote sensing images continues to increase, Multi-class Change Detection (MCD) which can reflect more detailed land change has become a hot research direction in the field of CD. Although many scholars have reviewed change detection at present, most of the work still focuses on BCD. This paper focuses on the recent progress in MCD, which includes five major aspects: challenges, datasets, methods, applications and future research direction. Specifically, the background of MCD is first introduced. Then, the major difficulties and challenges in MCD are discussed and delineated. The benchmark datasets for MCD are described, and the available open datasets are listed. Moreover, MCD is further divided into three categories and the specific techniques are described, respectively. Subsequently, the common applications of MCD are described. Finally, the relevant literature in the main journals of remote sensing in the past five years are analyzed and the development and future research direction of MCD are discussed. This review will help researchers understand this field and provide a reference for the subsequent development of MCD. Our collections of MCD benchmark datasets are available at: [ABSTRACT FROM AUTHOR]

The public sector's possibilities of using geospatial technologies are vast and can improve public management. In the Brazilian Federal Government, the use of geospatial technologies is unknown, nor is it known the main applications and public and private actors involved. This research proposes to analyze the geospatial technologies market in the Federal Government between the years 2011 and 2019 through public data of contracts. Through the individual analysis of 600 contracts, we concluded that R$ 804,747,626.99 were negotiated during the period. The contracts mainly involved Remote Sensing and Aerophotogrammetry (50%) and Geographic Information Systems (33%) solutions, applied primarily in the thematic areas of Oil & Gas (39%), Infrastructure (19%), and Environment & Natural Resources (10%). Fototerra was the leading company, providing R$ 155,553,107.03 in products and services. The foremost acquiring institution was the Ministry of Mines and Energy, contracting R$ 410 million, of which Petrobras acquired R$ 311 million. This paper showed how different federal institutions use Geography's technological bases to fulfill their missions, improve social well-being, and contribute to a more developed, less unequal, and fairer country. [ABSTRACT FROM AUTHOR]

As maritime activities increase globally, there is a greater dependency on technology in monitoring, control, and surveillance of vessel activity. One of the most prominent systems for monitoring vessel activity is the Automatic Identification System (AIS). An increase in both vessels fitted with AIS transponders and satellite and terrestrial AIS receivers has resulted in a significant increase in AIS messages received globally. This resultant rich spatial and temporal data source related to vessel activity provides analysts with the ability to perform enhanced vessel movement analytics, of which a pertinent example is the improvement of vessel location predictions. In this paper, we propose a novel strategy for predicting future locations of vessels making use of historic AIS data. The proposed method uses a Linear Regression Model (LRM) and utilizes historic AIS movement data in the form of a-priori generated spatial maps of the course over ground (LRMAC). The LRMAC is an accurate low complexity first-order method that is easy to implement operationally and shows promising results in areas where there is a consistency in the directionality of historic vessel movement. In areas where the historic directionality of vessel movement is diverse, such as areas close to harbors and ports, the LRMAC defaults to the LRM. The proposed LRMAC method is compared to the Single-Point Neighbor Search (SPNS), which is also a first-order method and has a similar level of computational complexity, and for the use case of predicting tanker and cargo vessel trajectories up to 8 hours into the future, the LRMAC showed improved results both in terms of prediction accuracy and execution time. [ABSTRACT FROM AUTHOR]

Addressing post-fire impacts largely depends on burn "severity." A singular severity classification that encompasses the holistic effects of fire on all ecosystem processes does not currently exist. Lumping vegetation burn severity and soil burn severity into one metric, or using them interchangeably, can induce large inaccuracies and uncertainties in the intended ecosystem response to forcing. Often, burn "severity" reflects fire impacts on vegetation, which can be measured through remote sensing. Vegetation burn severity is likely more apropos for ecological research, whereas soil burn severity is more relevant for hydrological analyses. This paper reviews different remotely sensed vegetation severity products currently (mis)used for hydrological modeling, provides examples of when vegetation burn severity may (not) match soil burn severity, and summarizes the potential synergistic future of remote sensing with in situ severity metrics. While the focus in this paper is on the western United States, the lessons and principles apply universally. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has accelerated acceptance of learning from other countries, especially for high-income countries to learn from low- and middle-income countries, a practice known as global learning. COVID-19’s rapid disease transmission underscored how connected the globe is as well as revealed stark health inequities which facilitated looking outside of one’s borders for solutions. The Global Learning for Health Equity (GL4HE) Network, supported by Robert Wood Johnson Foundation, held a 3-part webinar series in December 2021 to understand the current state of global learning and explore how global learning can advance health equity in the post-COVID-19 era. This paper reflects on these cutting-edge discussions about the current state of global learning, drawing upon the highlights, perspectives, and conclusions that emerged from these webinars. The paper also comments on best practices for global learning, including adapting for context, addressing biases, funding considerations, ensuring bidirectional partnerships, community engagement, and adopting a multidisciplinary approach. [ABSTRACT FROM AUTHOR]

The historical origins of the Tibet issue in Sino-Indian relations remain understudied. Most diplomatic histories on this subject focus on the highest levels of government, glossing over the immense role of domestic actors in shaping the Tibet question in the India-China relationship. This paper aims to address this gap by studying the domestic response to Dalai Lama's flight to India. Specifically, it analyses the domestic and international advocacy of the noted freedom fighter Jayaprakash Narayan. The paper highlights how Narayan's advocacy was critical in building global and public opinion on the Tibet question, culminating in the passage of Resolution 1723 at the United Nations. It argues that understanding his actions on Tibet is critical because of its negative impact on the Indian government's policy of preventing the issue from gaining international recognition – a gesture aimed at steadying the declining relationship with China. By hindering the government's efforts at damage control, the paper demonstrates how Jayaprakash Narayan's advocacy was a key factor explaining why Sino-Indian ties precipitously declined over the Tibet issue. [ABSTRACT FROM AUTHOR]

In a federal political system like India, the role of the federal units bordering the neighboring countries becomes crucial in foreign policy-making toward neighboring countries. It is expected that when similar political parties or coalition partners remain in power in both the center and the states, federal politics does not hinder policy-making toward neighboring countries. Moreover, foreign policy being a central subject, federal units any way reflect passive tendencies, especially in the case of governments with the same party affiliations. Both these simplifications are contested in this paper by citing instances of the role of West Bengal and Tripura, India's two federal units bordering the neighboring country of Bangladesh, at different historical junctures, in which similar political parties in the center and the state resulted in more friction than when different political parties were in office in matters of India's foreign policy-making toward Bangladesh. The paper argues that instead of federalization of foreign policy, where federal units have an influential role, this particular experience suggests an externalization of federalism, where an external variable (Bangladesh) influences internal federal dynamics to the extent that domestic electoral politics force the political parties of the two federal units to give importance to the neighboring country in taking positions on foreign policy-making. The immediate context of fifty years of the India-Bangladesh relationship and question about over-centralization during the latest phase of the National Democratic Alliance (NDA) regime in India push the authors to take up Bangladesh as a case to contest the given of Indian federalism in foreign policy making. [ABSTRACT FROM AUTHOR]

In this study, we investigate the influence of dislocation strengthening in the metastable parent phase on the deformation-induced martensitic transformation behavior of a face-centered cubic (fcc) Co20Cr20Fe34Mn20Ni6 high-entropy alloy. Annealed and hot-swaged specimens were prepared. In-situ neutron diffraction experiments captured an accelerated transformation kinetics in the hot-swaged specimen due to accumulated dislocations. The phase-specific macrostress development showed that the hexagonal close-packed $ \rvarepsilon $ ε -martensite predominantly accommodated the macroscopic plastic deformation of the annealed counterpart. Conversely, the matrix dislocation strengthening promoted cooperative plasticity of the $ \rgamma $ γ -matrix and the $ \rvarepsilon $ ε -martensitic phase, thus enhancing yield stress while preserving ductility. This paper firstly uncovers the role and significance of matrix dislocation strengthening on the mechanical behavior of metastable high-entropy alloys via in-situ neutron diffraction experiments. [ABSTRACT FROM AUTHOR]

Locally confined electrodeposition of precursors in liquid is one of the most effective approaches for additive manufacturing of metal microstructures. However, reported data were overwhelmingly obtained at the micrometer scale, whereas sub-microscale and nanoscale microstructures are of interest in electromagnetic or optical fields. In this paper, we propose a cold-constrained local electrodeposition (CCLE) technique to address the issue that locally confined electrodeposition of precursors in liquid is challenging in the fabrication of sub-microscale three-dimensional microstructures. Microstructure printing is conducted via locally confined electrodeposition by a pipette with a sub-microscale opening to deliver electrodeposition electrolyte in a supporting electrolyte. The electrolytes are cooled to 5 °C, which constrains the large-scale diffusion of the electrodeposition electrolyte and significantly reduces the electrodeposition area. It is found that the proposed CCLE technique can print sub-microscale (minimum size is low to 290 nm) structures, which have highly uniform deposits, smooth surfaces and high strength. [ABSTRACT FROM AUTHOR]

In present paper, a universal method for multi-objective parameter optimisation of additive manufacturing processes was proposed and successfully applied to laser-based directed energy deposition (DED) experiments with mixtures of H13 and M2 steel powders that were deposited on 4Cr5Mo2SiV1 hot work die steel. The DED experiments were designed and completed based on the response surface method with 13 groups of laser parameters. The microstructure of the deposited alloy steel was observed and its mechanical properties were tested. The deposited steel alloy achieved an ultimate tensile strength (UTS) of 1821 ± 30 MPa with a reasonable elongation of approximately 4.5%, and the bond strength specimens achieved a bond toughness of ~10.66% with a moderate UTS (1329 ± 28 MPa). A multi-objective optimisation method was proposed based on response surfaces which were established according to microstructural characteristics and mechanical properties data. It provided a basis for achieving high strength or high toughness DED-fabricated steel alloys. [ABSTRACT FROM AUTHOR]

Deposition path patterns play an important role in controlling residual stresses and deformation in direct energy deposition-arc (DED-arc) process. In this paper, the effects of various path patterns on the evolution of the temperature history, residual stress distribution, and substrate deformations are investigated through experiments and finite element analysis. The predicted results of temperature fields and substrate deformations are verified experimentally by the infrared thermal imager and the laser profile scanner, respectively. It is found that the path patterns have significant effects on the stress distribution in the first few layers, and the minimum substrate deformation is obtained by the zigzag path along the short edge of the block. The proposed finite element method and measuring method are confirmed to be effective and feasible, providing valuable insight into the residual stresses and deformations control in the DED-arc process. [ABSTRACT FROM AUTHOR]

It is well known that Additive Manufacturing (AM) is a slow process when compared to conventional manufacturing processes. To address this problem, this paper explores the concept of cooperative printing due to its ability to significantly increase the printing speed. It discusses current cooperative printing systems and proposes a new multi-arm configuration to address current limitations such as reduced cooperative printing area. The proposed configuration allows printing parts that are impossible to print or inefficiently printed by other configurations. Moreover, to improve efficiency and reduce printing time, new algorithms are proposed, including the Intermediate Point Method for collision avoidance. This method is three times more effective at preventing collisions compared to the current state-of-the-art algorithms and generates paths with lower travel durations. The proposed system was successfully tested in printing several single and multi-layer objects, showing a significant speed increase, surpassing the maximum printing time reduction reported in the literature. [ABSTRACT FROM AUTHOR]

Wire and Arc Additive Manufacturing (WAAM) with high efficiency and low-cost is an economical choice for the rapid fabrication of medium-to-large-sized metallic components and has attracted great attention from scholars and entrepreneurs in recent years. However, defects such as porosity, and humps, could occur occasionally after each layer of deposition on weld bead surfaces due to disturbances and process abnormities. Detection and quantitative evaluation of weld bead defects is crucial to ensure successful deposition and the quality of the entire component. In this paper, a novel defect detection and evaluation system was developed for WAAM utilizing machine vision technology. The system incorporated new defect detection algorithms based on analysing the 2D curvature of the weld bead height curve and the 3D curvature of the weld bead point cloud. Furthermore, a defect evaluation algorithm was developed based on reconstructing the normal weld bead contour using geometric features extracted from the accumulated point cloud. This system enables the automatic detection of weld bead morphology during the WAAM process, offering important information about the location, type, and volume of defects for effective interlayer repairs and enhanced part quality. [ABSTRACT FROM AUTHOR]

Laser powder bed fusion (LPBF) is increasingly prominent in essential fields such as aerospace. However, due to the characteristics of the manufacturing process and the high test cost, the performance of fabricated structures is inherently uncertain, leading to a challenging characterisation of their performance. This paper proposes a non-probabilistic convex modelling framework involving confirming uncertainties, processing data, and establishing a nonprobabilistic convex model, to quantitatively describe the uncertainties concerning the physical properties of structures fabricated by LPBF. Firstly, the non-probabilistic convex modelling framework is proposed and an efficient uncertainty quantification method is developed utilising the non-probabilistic convex model. Then, criteria are set up for evaluating the performance of the developed method, and computational efficiency and accuracy are illustrated via benchmark numerical examples. Last but not least, two types of representative structures, solid and lattice structures, are fabricated via the LPBF method. The physical properties are tested through tensile and compression experiments. By confirming the necessity of accounting for uncertainties with limited data, we employing the proposed framework to the real representative specimens fabricated via the LPBF method, demonstrating that the structures fabricated by LPBF have substantial uncertainty and the proposed framework is practical. [ABSTRACT FROM AUTHOR]

This paper presents the first digital geomorphometric atlas of Romania. It primarily includes existing international classifications of landforms, as well as land-surface variables (LSVs) derived from Forest and Buildings removed Copernicus Digital Elevation Model (FABDEM) at a resolution of 30 m. Besides the standard moving window of 3 x 3 (90 x 90 m), most LSVs were also derived in moving windows of 11 x 11 (330 x 330 m), and 27 x 27 (810 x 810 m), which represent the topographic grain values specific to the Romanian topography. Up to this point, the atlas contains 10 sets of landform classification data including the geomorphons and 24 sets of LSVs as follows: Slope, Aspect, Sin (Eastness), Cos (Northness), Profile Convexity, Plan Convexity, Longitudinal Curvature, Cross-Sectional Curvature, Minimum Profile Convexity and Multidirectional Hillshade. The data are available opensource for both interactive visualizations on the ArcGIS Online platform and for download on the Google Drive platform. [ABSTRACT FROM AUTHOR]

This paper presents a map of terrestrial glacial geomorphology of eleven surge-type and nonsurge- type glacier forefields in southwest and west Spitsbergen, Svalbard. Glacier forefields were mapped using a combination of field surveys and the use of an uncrewed airborne vehicle in September 2022 and satellite imagery captured in 2020, with mapping performed in ArcGIS Pro at a 1:5000 scale. Maps were constructed for glaciers in Van Kuelenfjorden and Van Mijenfjorden (southwest Spitsbergen), and in Isfjorden, Billefjorden a fjord branch of Isfjorden and St. Jonsfjorden (west Spitsbergen), to obtain a breadth of glacier types and features representative of glacial landsystems on Svalbard. The detailed landform inventory was divided into: (i) ice marginal, (ii) subglacial, (iii) glaciofluvial and glaciolacustrine, (iv) supraglacial and (v) other non-glacial and contemporary features. These detailed maps provide a geomorphological insight into the past and present characteristics of glaciers on Svalbard. [ABSTRACT FROM AUTHOR]

The paper provides a comprehensive overview of the transformation of the glacial isthmus between Sørkapp Land (southern peninsula) and the remainder of Spitsbergen from 1900 to 2023. The region distinguishes itself with notable environmental and landscape transformations since the early twentieth century, the post-Little Ice Age. These ongoing transformations are poised to swiftly convert the Sørkapp Land peninsula into an island, driven by the decline of the glacial isthmus connecting Sørkapp Land to the rest of Spitsbergen. [ABSTRACT FROM AUTHOR]

This paper accompanies the Maps of Geohazard features of the Cilento and the Calabro- Tyrrhenian continental margin in the southern Tyrrhenian Sea (Italy). The main geohazardrelated features were derived from extensive seafloor mapping through the collection of high-resolution multibeam data acquired during several oceanographic cruises. They encompass many fluids seepage features, fault scarps, landslides scars, gullies, channels, and canyons. Hazards related to coastal landslides and shelf-indenting canyons are very high in these sectors (especially in southern Calabria) due to active seismicity coupled with rapid uplift, high sedimentation rates and narrow or totally absent continental shelf, thus promoting a direct connection between steep slopes and coastal areas. In this setting, masswasting features can directly impact coastal or submarine infrastructures or indirectly create local tsunami waves, as observed in historical times. Moreover, this physiographic setting of the margin facilitates the transfer of marine litter toward deep-sea areas. [ABSTRACT FROM AUTHOR]

The MaGIC project (Marine Geohazard along the Italian Coasts) had the aim of mapping the geohazard in the Italian seas and resulted in numerous maps. In this paper, we present the maps: 'Maps of Geohazard features of the eastern Sardinian Margin'. The Eastern Sardinia margin has mainly a narrow shelf, which reaches a width of 20 km only to the north. At the base-of-slope, a series of intra-slope basins sits in the structural depressions formed during the opening of the Tyrrhenian back-arc system. Submerged, coastal depositional bodies are present in the Olbia area where the continental shelf is large. They most likely represent the remnants of coastal environments formed during the last rise in sea level. They can represent important geo-resources for application in the issue of coastal erosion management. They are also the site of ecosystems hosting a specific biodiversity, which need to be preserved. In the central and southern part of the mapped area, the shelf is very narrow with an average width of about 4 km. Here, many canyon heads are very close to the coastline. They develop through retrogadational processes. Particularly in those canyons, where the canyon heads reach the coast, sediment instability represents an important source of geohazards to the coastal regions. [ABSTRACT FROM AUTHOR]

The MaGIC project (Marine Geohazard along the Italian Coasts) had the aim of mapping the geohazard in the Italian seas and resulted in the production of numerous maps covering parts of the Italian Seas. In this paper, we present the maps: 'The submerged portions of the Aeolian volcanic islands and the north-eastern Sicilian margin', located in the south-eastern Tyrrhenian Sea. Both areas are affected by active geological processes, which represent important geohazards elements. Inthe submarine parts of the Stromboli volcanoremobilization of volcaniclastic deposits occur along the Sciara del Fuoco, where small-scale instabilities may represent a source of geohazard. Hydrothermal activity occurs on Enarete and Enaretino conical seamounts. The north-eastern Sicilian margin has a narrow continental shelf. Numerous canyon heads indent the shelf and, sometimes, reach close to the coast. Canyons have often a retrogradational trend and further eventual landward shift through sliding can iendangeri coastal or offshore infrastructures. Many of the canyons connect with leveed channels with widespread sediment instability. In the Gioia Basin, some of the channels connect to form the Stromboli slope Valley. Volcanic unrest or local and regional earthquakes are proven to have caused submarine landslides and tsunamis. [ABSTRACT FROM AUTHOR]

Protein S (PS) is a vital endogenous anticoagulant. It plays a crucial role in regulating coagulation by acting as a cofactor for the activated protein C (APC) and tissue factor pathway inhibitor (TFPI) pathways. Additionally, it possesses direct anticoagulant properties by impeding the intrinsic tenase and prothrombinase complexes. Protein S oversees the coagulation process in both the initiation and propagation stages through these roles. The significance of protein S in regulating blood clotting can be inferred from the significant correlation between deficits in protein S and an elevated susceptibility to venous thrombosis. This is likely because activated protein C and tissue factor pathway inhibitor exhibit low efficacy as anticoagulants when no cofactors exist. The precise biochemical mechanisms underlying the roles of protein S cofactors have yet to be fully elucidated. Nevertheless, recent scientific breakthroughs have significantly enhanced comprehension findings for these functions. The diagnosis of protein S deficiency, both from a technical and genetic standpoint, is still a subject of debate due to the complex structural characteristics of the condition. This paper will provide an indepth review of the molecular structure of protein S and its hemostatic effects. Furthermore, we shall address the insufficiency of protein S and its methods of diagnosis and treatment. [ABSTRACT FROM AUTHOR]

This paper proposes three different models for investigating the long-term performance of routine maintenance works using the discrete-time Markov model. The three models are called (M1, M2, and M3), which represent specific forms of the transition probability matrix. The (M1) model only incorporates the routine maintenance variables (Mi,i-1) under the assumption of only one-state upgrade. The (M2 and M3) models incorporate both routine maintenance variables (Mi,i-1), and major rehabilitation variables (Qi,1) under the assumption of upgrade to condition state (1). Two different modeling methods are proposed for pavement long-term performance prediction in the presence of maintenance and rehabilitation (M&R) variables. The first one is the project-level approach as applied to small pavement networks which assumes that all M&R works can be performed in a short-time period. The second one is the network-level approach which requires the M&R works to be spanned over the entire year as applied to large pavement networks. A model cost-effectiveness index is proposed to evaluate the long-term performance of potential M&R schedules under an unconstrained annual budget. In contrast, M&R variable cost-effectiveness indices are proposed as useful parameters for yielding optimal M&R schedules under a constrained annual budget. The sample results indicated the unrealistic performance of the (M1) model and the usefulness of the (M2 and M3) models in yielding reliable long-term M&R schedules. [ABSTRACT FROM AUTHOR]

This paper proposes a novel approach to utilizing open-source legal databases in academic education, especially in the fields of law and police investigations. Our framework provides a way to organize and analyze this data and extract reports that are associated with crime scenes, addressing the challenge of classifying unstructured legal documents by using text mining, natural language processing, and machine learning techniques. We developed a supervised machine learning model capable of accurately classifying court documents based on two classifiers: one identifies the documents containing crime scenes, and the other classifies them into five types of crimes. The experimental results were promising, as the random forest algorithm achieved an accuracy of 91.07% for the first classifier and support vector machines achieved an accuracy of 82.46% for the second classifier. What distinguishes our work is the creation of a crime dictionary that includes 70 crime tools and 151 related terms extracted from various forensic sources. It is considered relatively small, but it contributed to giving good classification results. The proposed crime dictionary can be generalized, developed, used in advanced searches, and integrated with police databases to improve crime scene analysis. Overall, the research highlights the use of court databases in police academic education and attempts to utilize them in a more effective manner. [ABSTRACT FROM AUTHOR]

Most manufactured electrical cables suffer from reductions in their physical, mechanical and electrical properties. These setbacks are mainly attributed to the improper control of wire tension during the cable manufacturing process. Hence, this paper systematically reviewed different control algorithms involved in controlling tension in moving webs, which include conventional control, advanced control, observer-based control, artificial intelligence-based control and hybrid control techniques. Thus, the review provided information about existing tension control techniques in moving webs, including their strengths and weaknesses. It was observed in this review that although a significant research effort has been made on web tension control systems, a thorough literature review is still lacking. It was concluded that controller optimisation using hybrid control algorithms is gaining popularity in web tension control due to their improved control response. Hence, its application in wire tension control can better help cable manufacturers improve the quality of manufactured cables. [ABSTRACT FROM AUTHOR]

The intense competition in the field of new shipbuilding business today requires shipyards to increase their productivity in terms of quality, cost, on-time delivery performance, and flexibility. Product-oriented Work Breakdown Structure (PWBS)-based steel ship production technology has played a vital role in the shipyard's success in competition. A block and modular assembly approach using the PWBS method was prepared to guide shipyards. This paper presents a study on the technology capability of four selected Indonesian medium-sized shipyards and one leading shipyard as the benchmark in using the PWBS method. The technology capability in shipbuilding is measured using the technometric assessment model by the United Nations Economic and Social Commission for Asia and the Pacific (UNESCAP), which consists of four indicators; technoware, humanware, infoware, and orgaware. The results show that the shipyards' Technology Coefficient Contribution (TCC) is between 0.5 and 0.7 (TCC maximum 1.0). This value indicates that the four shipyards in this case study are capable of building ships based on PWBS method. However, some aspects have to be improved to ensure the method is implemented properly, including: better design software that could prepare comprehensive production engineering documents, production lane with more automation, and more crane capacity. Of course, large additional investments must be supported by continuous orders for new ships with relatively the same type and size of ships, so that they are more productive and gradually able to compete in the global market. [ABSTRACT FROM AUTHOR]

This paper gives an investigation into the morphological analysis of boron carbide and the mechanical properties of the Jutton-Glass hybrid polymer nanocomposites. As reinforcements, hybrid nanoparticles comprising boron carbide and graphene nanoplatelets were used. For laying the composites, the vacuum bagging technique was used with the composition of hybrid nanomaterial taken as 0, 0.25 and 0.5 wt.% of Gr and B4C, and the samples were tested for mechanical properties as per ASTM standards. The samples prepared have been subjected to various tests, and the results are reported. Before the preparation of composites, the polymer was mixed with surface-modified nanomaterial and stability tests were conducted to assess uniform dispersion with the aid of UV spectroscopy, and the outcomes showed that the samples had been exceptionally uniform over some time. It is determined that the mechanical behavior of hybrid composites, which include B4C with Gr, shows better properties than base, B4C, and Gr. However, the multi-layered samples with graphene nanoplatelets also showcased encouraging mechanical properties like hardness and tensile strength. [ABSTRACT FROM AUTHOR]

This paper describes deep neural network (DNN) models based on hyperparameter optimization for the prediction of the compressive strength of concrete. The novelty of this research lies in the implementation of optimized hyperparameters to train the DNN models with the aim to enhance their predictive accuracy. Utilizing the Keras Tuner library, the most effective hyperparameters for the DNN models were identified. These models are then trained and evaluated using an experimental dataset of 1030 instances, encompassing nine quantitative variables that include various concrete mix ingredients and age. The target variable for all models is the compressive strength of concrete. The assessment of model performance, based on metrics like mean squared error (MSE) and R² values, was conducted on previously unseen test data. The optimal configuration for the hidden layers in the model was identified as five layers, containing 12, 16, 16, 40, and 26 neurons, respectively. The optimal learning rate for the model was 0.001. With this set of optimal hyperparameters, the best DNN model achieved an MSE of 28.76 and an R² value of 0.89 on the testing data. The results demonstrate a significant improvement in the DNN models' performance when trained with the optimized hyperparameters. In comparison to the regression model, the performance of the DNN models was significantly better. Adopting the predictive models developed in this research offers the potential for substantial cost and time savings by circumventing the need for labour-intensive and time-consuming laboratory tests. [ABSTRACT FROM AUTHOR]

In this paper, some exact solutions of the stochastic generalized nonlinear shallow water wave equation are investigated. This equation is important in fluid mechanics' fields since it can model the propagation of disturbances in water and other incompressible fluids. Opposite to what is usually considered in the literature, the two dispersion coefficients of the nonlinear terms are considered dependent random quantities as a more realistic case. The modified extended-tanh function (METF) method is combined with the random variable transformation (RVT) technique to get full probabilistic solutions of the problem via computing the probability density functions (PDFs) of the solution processes. Based on the probability density function, any statistical moment of the solution can be evaluated. Through two different applications for the input random variables (dispersion coefficients), my findings are applied efficiently. Finally, numerical results are presented graphically along the spatial dimension at a certain wave speed and time. The obtained results ratify that the proposed technique is efficient and powerful for obtaining analytical probabilistic solutions for the problem. [ABSTRACT FROM AUTHOR]

Studies reviewed in this paper show anomaly for temperature pertaining to streamflow and rainfall showing different trends, especially in Ethiopia to support the research findings and interpretation. There are many hydrological models, including 54 physically distributed, lumped, and conceptual hydrological models, of which 28 have been used in Ethiopian river basins. The models include the most adaptable and commonly used SWAT model applicable from small areas up to large basins. It is indeed a challenge to use a single hydrological model as the data rely on consistency, limitation-free, and exactly fitted output. The overall performance of individual physically-based, conceptual, and machine learning (ML) models varied at different watersheds. Reasonably, ML performs very well, up to 0.99 for R² and NSE and up to 0.001 for PBIAS. Inopportunely, using a single hydrological model has its limitations; ensemble multi-individual models, coupling or hybridization of physical or conceptual models with machine learning, combining evolutionary optimization algorithms with ML, and also comparisons of multi-single hydrological models, and selecting the best one are recommended options. No single hydrological model is indispensable and can be termed as better than the other for any watershed. Somewhat, ML outperforms SWAT but cannot be considered an absolute substitute. The size of the watershed, the number of data used, and the ratio between calibrations year to validation year do not have a clear correlation with the performance, particularly for the SWAT model accounted for in this review. Optimization algorithms explore multiple options and choosing the right one is a tedious task before a final decision is taken. [ABSTRACT FROM AUTHOR]

This paper investigates the effects of powder waste glass (PWG) at 10%, 15%, and 20 wt.% replacement of cement on the flow characteristic, setting time, compressive strength, water sorption, rate of the heat of hydration, cumulative heat of hydration; alkali-silica reaction (ASR), and microstructure characteristics of the resulting paste and mortar mixtures. A total of eight cementitious mixtures including two control mixtures have been investigated in this experimental program to evaluate the effect of PWG on the fresh and hardened state characteristics of paste and mortar mixtures. Test results show that the incorporation of PWG in the cementitious mixtures results in significant enhancement of their microstructure, increase in compressive strength, improvement in moisture barrier characteristics, and considerable reduction in the rate of the heat of hydration and cumulative heat of hydration. Up to 20 wt.% replacement of cement with fine PWG is seen to be innocuous from the standpoint of ASR. Furthermore, the use of PWG in paste results in delaying the initial and final setting times and increases the flow characteristic of the mortar mixture. [ABSTRACT FROM AUTHOR]

Deepfakes are a rapidly growing technological trend that is revolutionizing many digital processes, from media production to digital access. They offer various advantages for both users and creators alike. For example, they can provide entertainment value by allowing users to create humorous or satirical versions of existing media content without having to film new scenes. They can also automate production workflows by generating background characters or extras for movies. Additionally, deepfakes could be used in healthcare applications, such as virtual avatars for doctors who require assistance during consultations with patients located far from hospitals or clinics. However, deepfakes also pose a threat to society as they can be used for malicious purposes, including spreading false information or exploiting the likenesses of others for financial gain. To address these concerns, various types of regulations have been introduced across jurisdictions worldwide. These laws prohibit doctored audio recordings and visual materials aimed at influencing election outcomes. Some countries have even gone as far as requiring companies producing deepfake materials to identify themselves as such, to make audiences aware that what they are seeing may not always be authentic representations of events. In this paper, the author will discuss what deepfakes are, their potential benefits and risks, the various types of deepfakes that exist, and how the USA has attempted to regulate them. The author will also suggest some policy recommendations aimed at mitigating the risks associated with deepfakes while still preserving their creative potential. [ABSTRACT FROM AUTHOR]

To correctly evaluate the effects of treatments, conducting randomized controlled trials (RCTs) is a reasonable approach. However, because it is generally difficult to implement RCTs for all treatments, methods to estimate the treatment effects using observational data have been actively studied and used in various decision-making processes. Observational data accumulated in business activities and elsewhere contains the results of various previously implemented treatments, and correctly estimating the effects of any given treatment without separating the impacts of other treatments is challenging. Against this background, this paper proposes a method to estimate the effects of multiple treatments of various types while considering various causal relationships. Specifically, the proposal is a variational inference method that estimates the effect of multiple treatments using four latent factors estimated from observations, making assumptions that are independent of the type and number of treatments. The proposed method makes it possible to appropriately estimate the effects of measures even in situations with complex causal relationships. In addition, in situations where measures with continuous parameters are being implemented, it is possible to estimate the effects of measures that have not been implemented in the past by treating the content of the measures as a continuous variable. [ABSTRACT FROM AUTHOR]

A drastic decline in the number of students that are enrolled for Engineering is now being experienced in developed as well as developing countries. Learning is becoming boring as a generation brought up on technology is losing the ability to pay attention in traditional classes for a long stretch of time. This has led to the idea that other teaching methods do exist and can be applied in teaching/learning. This work leveraged the use of Digital Game-Based Learning (DGBL) in Engineering classrooms to develop a serious game named LogicHouse Version 1 (LogicHouse-V1 or LogicHouse for short). The game, is a web-based serious game prototype that targets selected topics in Digital Electronics course. This course is a core component of undergraduate curriculum in Electrical & Electronics Engineering, Computer Engineering, Information Technology, Communication Engineering, Computer Science and other related Science Technology Engineering and Mathematics (STEM) courses. LogicHouse involves a virtual broken house where the player has to play the various levels to fix the house and gain points along the way. This game was designed based on the Learning Mechanics-Game Mechanics (LM-GM) model and the Unified Modeling Language (UML). Furthermore, the design was implemented using Adobe Illustrator, Procreate, Unity Engine, C#, Microsoft Azure Playfab and deployed on itch.io. Preliminary evaluation results indicate that students are interested in the game and its application. Based on this, there is a prospect of improved performance in any course in which the game is implemented. [ABSTRACT FROM AUTHOR]

The non-centrifugal cane sugar (panela) subsector stands out in Colombia as one of the most important agro-businesses, with economic growth and projection for the export of its products. For its part, the application of the Lean-Kaizen philosophy has proven to be effective for organizations to achieve continuous improvement in quality and productivity. This paper exposes the implementation of the pillars of Kaizen for the improvement of the panela manufacturing process applied in an artisan mill (Trapiche) in the Santander region, Colombia. Through the case study methodological approach, a Trapiche was selected and its production process was studied in terms of waste, order and cleanliness, and standardization. The results evidenced the types of waste that occur throughout the panela production process, the current state of order and cleanliness, and the way in which the operations are carried out to obtain the finished product. With the implementation housekeeping program (5S) and the standardization of the operational procedures, the main waste, sources of dirt and the reduction of the time used for the manufacture of panela were eliminated. The Kaizen actions improved the order and cleanliness of the Trapiche by 63% and the panela manufacturing time by 10%, complying with product quality standards. [ABSTRACT FROM AUTHOR]

This paper investigates the effect of the SiC and triplex thermal aging treatment (TTAT) on the mechanical behavior of compound bars. The bars were fabricated by varying the SiC (2, 4 and 6wt. %) in Al6061. Initially, bars were tested for hardness and compression strength in homogenized conditions. It is observed that as SiC is increased in the matrix, mechanical properties have improved. The bars with composite cores exhibited better properties as compared to bars with composite casing. For the bar having a composite core, with 2 wt. % SiC, the compression strength was 530.70 MPa, for the 4 wt.% SiC core it was 589.35 MPa and for the 6 wt.% SiC it was 691.88 MPa. Failure was progressive, with noticeable signs of failure, and the load-bearing ability was found to be fairly stable up to nearly 218 kN. Later, the bar with a 6 wt. % SiC core was subjected to TTAT, and surface hardness, compression strength, and interfacial shear strength were found to have increased by 11.2, 3.2 and 11.11%, respectively. SiC are the hard particles; reinforcing them in a soft matrix induces strain in the lattice and thus enhances the hardness of the composite. During aging, the diffusion of alloy atoms is blocked by the generated dislocations present around the SiC particles. Hence, the bars with a higher quantity of SiC in the composite core can be used for high load-bearing structural applications due to their superior mechanical properties as an alternative to the simple composite bars with the same SiC quantity. [ABSTRACT FROM AUTHOR]

This paper gives the investigation of the mechanical properties of Jutton-Glass hybrid polymer nanocomposite with multi walled carbon nanotubes (MWCNTs) and graphene nanoplatelets (GNPs) as reinforcements. For preparing the composites, the vacuum bagging technique was used with the composition of hybrid nano-material taken as 0, 0.25, and 0.5 wt. % of Graphene nanoplatelets and MWCNTs and the samples were tested for mechanical properties as per ASTM standards. The samples prepared have been subjected to various testing, and the results are reported. Prior to the preparations of composites, the polymer was mixed with surface-modified nanomaterials and stability tests were conducted to assess uniform dispersion with the aid of UV-Vis spectroscopy, the outcomes showed that the samples were exceptionally uniform over a period. The hardness and tensile properties were evaluated, and it was found that surface-modified nanomaterials could improve the properties better compared to the use of pristine nanomaterials as reinforcements. It was found that 0.25% MWCNT and graphene nanoplatelets (GNPs) show more improved properties than 0.5% MWCNT and Graphene nanoplatelets. However, the composite samples with Graphene nanoplatelets also showcased encouraging mechanical properties like hardness and tensile strength. [ABSTRACT FROM AUTHOR]

Waste is considered a significant environmental issue in modern times thus the purpose of this paper is to compare the use of different waste materials in replacing aggregates in concrete. This study investigates the potential of incorporating plastic waste (PW), textile sludge (TS), and construction and demolition waste (CDW) into concrete as sustainable alternatives to traditional construction materials, by evaluating its mechanical, durability characteristics as well as the cost related to different process of the project. The study focuses on the use of PW and TS as a replacement for fine aggregate, and CDW as replacements for coarse aggregate. Thus, four concrete mixes incorporating PW and TS were prepared, using 0% 10%, 25%, 40% replacement levels. The compressive strength of concrete with 10% plastic waste as fine aggregate was 32.49 N/mm² showing higher results than that of TS. Furthermore, another four concrete mixes incorporating CDW were prepared, using 0%, 25%, 50%, 75% replacement levels. The compressive strength of concrete with 25% CDW was 30.90 N/mm² indicating an increase of 2% than the control block. The study concluded that the best strategy is to incorporate construction and demolition waste as a replacement for coarse aggregate in concrete. This is because it resulted in an increase in compressive strength as well as a decrease in cost. [ABSTRACT FROM AUTHOR]

The behavior of steel bolted connections is a complex structural problem which involves various factors such as material nonlinearity, large deformation and contact. The investigation of this behavior is one of challenging subjects in structural analyses. Unlike other structural modelling, the connections of bolted structures involve a large number of contacts, which are critical to the behavior of the joints. This paper focuses on investigating the behavior of a type of the external diaphragm which is used in rectangular hollow section column-to-beam bolted connections. The creation of a reliable finite element model is a primary aim of this research. The ABAQUS finite element package is used to simulate the experimental behavior, and three highly complex 3D finite element models are created, accounting for material nonlinearly, large deformation and contact behavior involved in the models. The connection models have been analyzed under some loading conditions up to failure. Comparisons with experimental data show that the models have high levels of accuracy, and these models may be used to gain an insight into important issues such as the connection tying force capacity of an external diaphragm, bolt and plate bearing behavior, and bolt shearing. [ABSTRACT FROM AUTHOR]

The m-polar fuzzy set (mFs) algorithm is a novel approach to solving multi-polar uncertainty problems. Combining other multi-criteria decision-making techniques can improve this algorithm in efficient ways. This work examines the ELimination Et Choice Translating Reality-I (ELECTRE-I) approach. The input data given to any MCDM technique will change the rank of alternatives based on the method of normalization used and the weight calculation method utilized for the criteria weight calculation purpose. Various normalization approaches and criteria weight methods are required to transform real data into normalized data for MCDM method implementation. This study uses a framework to implement the mFs ELECTRE-I algorithm to investigate the effect of AHP weight and Shannon's entropy weight (SEW) calculation combined with normalization strategies. In this paper, selecting nontraditional machining (NTM) processes is evaluated to assess the impact of the created framework on choices and rank performance analysis. The study results in linear sum and vector normalization are suitable normalization techniques with AHP as well as Shannon's entropy weight (SEW) criteria weight methodology with Spearman's rank correlation coefficients as 0.8333 and 0.9285, respectively, which shows consistency of the rank of alternatives with the results obtained by previous researchers. This study can be used to select suitable normalization and criteria weight methods for the m-polar fuzzy set ELECTRE-I algorithm while solving multi-criteria decision-making problems. The framework is intended to address various industrial problems with many criteria, including the selection of robots, non-traditional machining techniques, and various industrial challenges without considering their subgroups. [ABSTRACT FROM AUTHOR]

The objective of this study was to investigate the mechanism of soot formation in biodiesel by analyzing the combustion of individual components. The paper presents a numerical analysis of the effect of preheat temperatures on nucleation rates, coagulation rates, and soot volume fraction in methyl linolenate (MLe) co-flow flame. In this work, Moss-Brooke's soot model and a reduced kinetic mechanism containing 177 chemical species and 2904 chemical reactions were used to simulate the pyrolysis and combustion of MLe. A laminar jet flame with inlet velocities of 0.4 m/s was studied. The preheat temperature of the fuel was varied between 300 and 450 K. The burner walls were stationary and no-slip conditions were applied. The pressure outlet had Neumann boundary conditions and the tangential velocity was set to zero at the wall. It was established that an increase in fuel preheat temperatures causes an increase in nucleation rates and the amount of soot due to accelerated fuel pyrolysis, improved diffusion, acceleration from buoyancy, and earlier formation of PAHs. It was discovered that increasing the fuel preheat temperature had a greater impact on soot formation along the centerline than on the wing. [ABSTRACT FROM AUTHOR]

Power Electronics (PE) is pivotal in fostering renewable energy. However, focusing on usage efficiency shifts environmental impacts across its life cycle, leading to excessive resource extraction and waste accumulation. Integrating environmental impact indicators in PE development is crucial for informed design decisions. Nevertheless, the current literature lacks the provision of adequate understanding of the PE product development process for successful ecodesign in PE industry. To effectively tackle the industrial integration aspect of ecodesign that enable functional and system innovation, this study employs empirical research, combining literature analysis with in-depth interviews with PE designers. Requirements for an ecodesign support to integrate ecodesign practices into the Product Development Process (PDP) of PCB-based Power Electronic Components (PECs) is proposed in this paper based on the interview results. These specifications are delineating the necessary working and decision- making steps. Subsequently, a parameterized Functional Block-based Life Cycle Analysis (FB-LCA) model is proposed under the requirement. A five-step methodology is proposed to operationalise the implementation of the FB-LCA model, aiming to supporting the definition of functional structure, configuration of technical solutions and choice of hardware components by considering environmental impacts generated all along life cycle, from manufacturing, transport, use, circularity scenario, end-of-life .The case study of a PCB-based boost converter design is conducted in collaboration with a PE engineer to test the practical implementation of FB-LCA model. [ABSTRACT FROM AUTHOR]

The challenge of swift and reliable earthquake location prediction within earthquake early warning (EEW) systems underscore the need for innovative solutions. Existing methods provide predictions, yet there is a clear demand for enhanced accuracy and expediency in the process of resolving. The article intends in prediction of both magnitude of earthquakes and the affected areas in a specific region, focusing on California, United States, by leveraging historical data using neural networks (NNs). Neural networks outperform other algorithms such as XGBoost, linear regression, random forest, gradient boosting and support vector machine (SVM), in terms of high R² score and low score of MAE and also mean squared error (MSE). The derived results of R² score, MSE and MAE are 0.1607, 0.1615 and 0.2951, respectively. It seamlessly integrates geospatial visualization through Folium and GeoPandas. These tools enhance the predictive model's capabilities by generating dynamic maps enriched with markers, each representing the anticipated impact of earthquakes. The user interface facilitates interactive input, enabling users to input earthquake parameters for real-time predictions. The resultant map not only showcases the predicted impact zone but also provides valuable insights into the severity of seismic events. It stands as a testament to the synergy between machine learning and geospatial visualization, offering a holistic solution for earthquake prediction and geographical representation. [ABSTRACT FROM AUTHOR]

The construction industry faces challenges in evaluating success due to inconsistent methods and a lack of uniformity. Traditional evaluation methods often result in subjective and biased results. Professionals, stakeholders, and researchers disagree on assessment techniques. The paper aims to identify stakeholder-responsive evaluation criteria, establish an evaluation criteria model, develop a quantitative evaluation algorithm, and provide an evaluation process framework. This method and framework fill traditional evaluation gaps, reduce subjectivity and bias, enhance accuracy, simplify evaluation, and are suitable for project evaluation. Data was gathered from experts and project stakeholders through focus group discussions, interviews, archive documents, and site observations. First, identify criteria and subcriteria and develop a criteria-relation model that achieves fitness indices and passes validity and reliability tests. Next, quantitative evaluation weighted coefficients were determined, and an algorithm was developed. A quantitative evaluation of a case study revealed that project seven has very high success; projects three, six, eight, and nine have high success; project two has medium success; projects one, four, and five have low success; and there is no project with a very low success. Projects achieved average success rates of 86.42, 79.6, 66.5, 71.17, 83.63, 81.27, and 89.14% in quality, cost, time, safety, impact, satisfaction, and lesson learning, respectively. This study is novel and original due to its criteria structural equation model, quantitative evaluation algorithm with inclusive criteria index, and unique evaluation processes framework. This enhances evaluation science, providing new insights for stakeholders, professionals, academics, and policymakers, and enhancing stakeholder communication in future project success evaluations. [ABSTRACT FROM AUTHOR]

This paper aims to assess the level of awareness of safety precautions in the use of extension cords in Ho Municipality in Ghana. The relevance of this study is to provide an understanding of the awareness level of safety measures likely to lead to a significant reduction in incidents of domestic fire outbreaks when using an extension cord. A cross-sectional research was carried out in the Ho Municipality between February and April 2022. Six hundred and one (601) individuals were chosen from houses using a random selection method. A standardised questionnaire was used to gather data, and then entered and analysed using the Statistical Package for Social Science (SPSS) V.16. Descriptive statistics, Binary logistic regression analysis with a 0.05 p-value and the adjusted odds ratio (AOR) with a 95% confidence interval (CI), Relative Importance Index (RII), and the Sample T-test were used to examine the significance of connections. Among the participants, there is a low level of awareness of extension cord ratings and standard labels from autonomous testing facilities. The participants' knowledge of awareness was significantly related to gender; [0.722 (95% (CI): 1.476 - 2.869), p = 0.001 < (0.05)]. Again, most participants overload the extension cord during usage and practice poor safety measures that could result in a fire outbreak. The study suggests that users should purchase extension cords that have been endorsed by an autonomous testing laboratory and fully be educated on the safety procedures that will aid in safeguarding lives and property by both government and non-governmental agencies. [ABSTRACT FROM AUTHOR]