Appl. Sci., Volume 9, Issue 22 (November-2 2019) – 255 articles

System modeling is a main task in several research fields. The development of numerical models is of crucial importance at the present because of its wide use in the applications of the generically named machine learning technology, including different kinds of neural networks, random field models, and kernel-based methodologies. However, some problems involving the reliability of their predictions are common to their use in the real world. Octahedric regression is a kernel averaged methodology developed by the authors that tries to simplify the entire process from raw data acquisition to model generation. A discussion about the treatment and prevention of overfitting is presented and, as a result, models are obtained that allow for the measurement of this effect. In this paper, this methodology is applied to the problem of estimating the energetic needs of different buildings according to their principal characteristics, a problem that has importance in architecture and civil and environmental engineering due to increasing concerns about energetic efficiency and ecological footprint. Full article

Boron and oxygen-doped Cr–Al–Ti–N coatings were deposited by closed field unbalanced magnetron sputtering (CFUBMS) of TiB target manufactured by self-propagating high-temperature synthesis, and Ti, Cr, and Al targets. To evaluate the influence of doping elements, as-deposited coatings were studied by glow discharge optical emission spectroscopy (GDOES), SEM, XRD, and optical profilometry. Mechanical properties were measured by nanoindentation and tribological, abrasive and electrochemical testing. The introduction of boron suppresses columnar growth and leads to structural refinement and a decrease of coating’s surface roughness. The addition of 2.3 at.% boron results in the highest mechanical properties: hardness H = 15 GPa, stable friction coefficient f = 0.65, and specific wear Vw = 7.5 × 10⁻⁶ mm³N⁻¹m⁻¹. To make the coating more visually appealing, oxygen was introduced in the chamber near the end of the deposition cycle. Upper Cr–Al–Ti–B–O–N layers were studied in terms of their composition and coloration, and the developed two-layer decorative coatings were deposited on cast metallic art pieces. Full article

Black carbon (BC) is an important component of particulate matter (PM) in urban environments. BC is typically emitted from gas and diesel engines, coal-fired power plants, and other sources that burn fossil fuel. In contrast to PM, BC measurements are not always available on a large scale due to the operational cost and complexity of the instrumentation. Therefore, it is advantageous to develop a mathematical model for estimating the quantity of BC in the air, termed a BC proxy, to enable widening of spatial air pollution mapping. This article presents the development of BC proxies based on a Bayesian framework using measurements of PM concentrations and size distributions from 10 to 10,000 nm from a recent mobile air pollution study across several areas of Jordan. Bayesian methods using informative priors can naturally prevent over-fitting in the modelling process and the methods generate a confidence interval around the prediction, thus the estimated BC concentration can be directly quantified and assessed. In particular, two types of models are developed based on their transparency and interpretability, referred to as white-box and black-box models. The proposed methods are tested on extensive data sets obtained from the measurement campaign in Jordan. In this study, black-box models perform slightly better due to their model complexity. Nevertheless, the results demonstrate that the performance of both models does not differ significantly. In practice, white-box models are relatively more convenient to be deployed, the methods are well understood by scientists, and the models can be used to better understand key relationships. Full article

Residual stress is the main cause of flatness defects in sheet metal and the basic method to improve the shape quality of the sheet is to reduce and eliminate the residual stress by multi-roll levelling. The curvature coupling between repeated sheet bendings in multi-roll levelling greatly affects the accuracy of the analysis of the residual stress evolution, which is rarely considered in current research. Aiming to address this problem, a method for eliminating residual stress by multi-roll levelling based on curvature coupling is discussed in this article. An evaluation criterion and an analysis model are proposed to investigate the evolution of the residual stress in multi-roll levelling considering the curvature coupling between bendings. The effects of the intermesh of the work rolls and the plastic deformation of the sheet on the residual stress are also discussed. The results show that multi-roll levelling will cause rolling residual stress while reducing the initial residual stress of the sheet and the larger plastic deformation caused by the intermesh of the work rolls at the entry is beneficial for the complete elimination of the initial residual stress, but the rolling residual stress will increase at the same time. Therefore, the total residual stress of the sheet after levelling depends on the appropriate levelling parameters. Full article

The rapid development of the number of wireless broadband devices requires that the induced uplink exposure be addressed during the design of the future wireless networks, in addition to the downlink exposure due to the transmission of the base stations. In this paper, the positions and power levels of massive MIMO-LTE (Multiple Input Multiple Output-Long Term Evolution) base stations are optimized towards low power consumption, low downlink and uplink electromagnetic exposure and maximal user coverage. A suburban area in Ghent, Belgium has been considered. The results show that the higher the number of BS antenna elements, the fewer number of BSs the massive MIMO network requires. This leads to a decrease of the downlink exposure (−12% for the electric field and −32% for the downlink dose) and an increase of the uplink exposure (+70% for the uplink dose), whereas both downlink and uplink exposure increase with the number of simultaneous served users (+174% for the electric field and +22% for the uplink SAR). The optimal massive MIMO network presenting the better trade-off between the power consumption, the total dose and the user coverage has been obtained with 37 64-antenna BSs. Moreover, the level of the downlink electromagnetic exposure (electric field) of the massive MIMO network is 5 times lower than the 4G reference scenario. Full article

This paper analyzes trends in renewable-energy-sources (RES), power converters, and control strategies, as well as battery energy storage and the relevant issues in battery charging and monitoring, with reference to a new and improved energy grid. An alternative micro-grid architecture that overcomes the lack of flexibility of the classic energy grid is then described. By mixing DC and AC sources, the hybrid micro-grid proposes an alternative architecture where the use of bi-directional electric vehicle chargers creates a micro-grid that directly interconnects all the partner nodes with bi-directional energy flows. The micro-grid nodes are the main grid, the RES and the energy storage systems, both, on-board the vehicle and inside the micro-grid structure. This model is further sustained by the new products emerging in the market, since new solar inverters are appearing, where a local energy storage for the RES is available. Therefore, the power flow from/towards the RES becomes bi-directional with improved flexibility and efficiency. Full article

This paper describes an innovative virtual laboratory for students of Hydraulic Engineering at an Italian university that shows water discharge measurement techniques applied in open-channel flows. Such new technology, which supports traditional practical classes, has the potential to increase students’ motivation and improve their skills, as well as simultaneously reducing the costs, time, and possible dangers that continuous field experiments would involve. Thanks to this immersive and interactive experience that is carried out indoors, students learn to move around a fluvial environment, as well as work more safely and with reduced risks of accidents. Besides, the virtual lab can boost learners’ interest by combining education with pleasure and making knowledge more fun. Collaboration with a group of students enrolled in the Master’s degree course of the Civil and Environmental Engineering program at Basilicata University at the early stages of developing the educational tool led to improvements in its performance and features. Also, a preliminary testing procedure carried out on a student sample, verified the achievement of the students’ learning objectives in terms of knowledge and skills. Such analysis indicated that students took more active role in the teaching/learning process and they showed greater interest in the topic dealt with through the new technology compared to the involvement of students observed during traditional lessons in previous years. The architecture and operational modes of the virtual laboratory as well as the results of the preliminary analysis are discussed. Full article

In the marine environment, biofilm formation is an important lifestyle for microorganisms. A biofilm is comprised of cells embedded in an extracellular matrix that holds them close together and keeps the biofilm attached to the colonized surface. This predominant lifestyle and its main regulation pathway, namely quorum-sensing (QS), have been shown to induce specific bioactive metabolites. In this study, we investigated the biofilm formation by two marine bacteria belonging to the Vibrio species to discover potentially innovative bioactive compounds. We proposed a protocol to isolate biofilm extracts, to analyze their biochemical composition, and to compare them to planktonic cell extracts. Cells were grown attached to a plastic surface; extracts were prepared in water, NaOH, or in ethyl acetate and analyzed. Extracellular matrix components featured carbohydrates, proteins, lipids, and low amount of DNA. Carbohydrates appeared to be the main constituent of biofilm but also of the planktonic cell supernatant. Moreover, antimicrobial and QS-signaling activities were evidenced in extracts. Full article

End-plate surface distance is important for length value dissemination in the field of metrology. For the measurement of distance of two surfaces, the positioning method is the key for realizing high precision. A practical method with nanometer positioning precision is introduced in consideration of the complexity of positioning laser sources of the traditional methods and new methods. The surface positioning is realized by the combination of laser interference and white light interference. In order to verify the method, a 0.1 mm height step is made, and an experiment system based on the method is established. The principle and the basic theory of the method are analyzed, and the measures to enhance the repeatability from optical and mechanical factors and signal processing methods are presented. The experimental result shows that the surface positioning repeatability is in the order of 10 nm. The measurement uncertainty evaluation shows that the standard uncertainty is 21 nm for a 0.1 mm step. It is concluded that the method is suitable to be applied to the length measurement standard of the lab. Full article

In this work, the vibration behavior of a 4-cylinder, 4-stroke, petrol engine was simulated by leveraging on the Finite Element Method (FEM). A reduced modelling strategy based on the component mode synthesis (CMS) was adopted to reduce the size of the full FEM model of the engine. Frequency response function (FRF) analyses were used to identify the resonant frequencies and corresponding modes of the different FEM models, and the obtained results were compared with experimental data to get the model validation. Subsequently, modal-based frequency forced response analyses were performed to consider the loads acting during the real operating conditions of the engine. Finally, the impact on vibrations at the mounts, produced by an additional bracket connecting the engine block and gearbox, was also investigated. Both the full and reduced FEM model demonstrated and reproduced with high accuracy the vibration response at the engine mounts, providing a satisfactory agreement with the vibrations measured experimentally. The reduced modelling strategy required significantly shorter runtimes, which decreased from 24 h for the full FEM model to nearly 2 h for the reduced model. Full article

Electrocardiographic (ECG) signal is essential to diagnose and analyse cardiac disease. However, ECG signals are susceptible to be contaminated with various noises, which affect the application value of ECG signals. In this paper, we propose an ECG signal de-noising method using wavelet energy and a sub-band smoothing filter. Unlike the traditional wavelet threshold de-noising method, which carries out threshold processing for all wavelet coefficients, the wavelet coefficients that require threshold de-noising are selected according to the wavelet energy and other wavelet coefficients remain unchanged in the proposed method. Moreover, The sub-band smoothing filter is adopted to further de-noise the ECG signal and improve the ECG signal quality. The ECG signals of the standard MIT-BIH database are adopted to verify the proposed method using MATLAB software. The performance of the proposed approach is assessed using Signal-To-Noise ratio (SNR), Mean Square Error (MSE) and percent root mean square difference (PRD). The experimental results illustrate that the proposed method can effectively remove noise from the noisy ECG signals in comparison to the existing methods. Full article

Reliable detection of the media-adventitia border (MAB) and the lumen-intima border (LIB) in intravascular ultrasound (IVUS) images remains a challenging task that is of high clinical interest. In this paper, we propose a superpixel-wise fuzzy clustering technique modified by edges, followed by level set evolution (SFCME-LSE), for automatic border extraction in 40 MHz IVUS images. The contributions are three-fold. First, the usage of superpixels suppresses the influence of speckle noise in ultrasound images on the clustering results. Second, we propose a region of interest (ROI) assignment scheme to prevent the segmentation from being distracted by pathological structures and artifacts. Finally, the contour is converged towards the target boundary through LSE with an appropriately improved edge indicator. Quantitative evaluations on two IVUS datasets by the Jaccard measure (JM), the percentage of area difference (PAD), and the Hausdorff distance (HD) demonstrate the effectiveness of the proposed SFCME-LSE method. SFCME-LSE achieves the minimal HD of 1.20 ± 0.66 mm and 1.18 ± 0.70 mm for the MAB and LIB, respectively, among several state-of-the-art methods on a publicly available dataset. Full article

Although blockchain technology was first introduced through Bitcoin, extending its usage to non-financial applications, such as managing academic records, is a new mission for recent research to balance the needs for increasing data privacy and the regular interaction among students and universities. In this paper, a design for a blockchain-based system, namely UniChain, for managing Electronic Academic Records (EARs) is proposed. UniChain is designed to improve the current management systems as it provides interoperable, secure, and effective access to EARs by students, universities, and other third parties, while keeping the students’ privacy. UniChain employs timed-based smart contracts for governing transactions and controlling access to EARs. It adopts advanced encryption techniques for providing further security. This work proposes a new incentive mechanism that leverages the degree of universities regarding their efforts on maintaining academic records and creating new blocks. Extensive experiments were conducted to evaluate the UniChain performance, and the results indicate the efficiency of the proposal in handling a large dataset at low latency. Full article

(1) Background: We previously demonstrated that customary regression protocols for curvature in geometrical space all derive from a generalized model of complex allometry combining scaling parameters expressing as continuous functions of covariate. Results highlighted the relevance of addressing suitable complexity in enhancing the accuracy of allometric surrogates of plant biomass units. Nevertheless, examination was circumscribed to particular characterizations of the generalized model. Here we address the general identification problem. (2) Methods: We first suggest a log-scales protocol composing a mixture of linear models weighted by exponential powers. Alternatively, adopting an operating regime-based modeling slant we offer mixture regression or Takagi–Sugeno–Kang arrangements. This last approach allows polyphasic identification in direct scales. A derived index measures the extent on what complexity in arithmetic space drives curvature in arithmetical space. (3) Results: Fits on real and simulated data produced proxies of outstanding reproducibility strength indistinctly of data scales. (4) Conclusions: Presented analytical constructs are expected to grant efficient allometric projection of plant biomass units and also for the general settings of allometric examination. A traditional perspective deems log-transformation and allometry inseparable. Recent views assert that this leads to biased results. The present examination suggests this controversy can be resolved by addressing adequately the complexity of geometrical space protocols. Full article

In this paper, the important topic of cooperative searches for multi-dynamic targets in unknown sea areas by unmanned aerial vehicles (UAVs) is studied based on a reinforcement learning (RL) algorithm. A novel multi-UAV sea area search map is established, in which models of the environment, UAV dynamics, target dynamics, and sensor detection are involved. Then, the search map is updated and extended using the concept of the territory awareness information map. Finally, according to the search efficiency function, a reward and punishment function is designed, and an RL method is used to generate a multi-UAV cooperative search path online. The simulation results show that the proposed algorithm could effectively perform the search task in the sea area with no prior information. Full article

Movies have become one of the major sources of entertainment in the current era, which are based on diverse ideas. Action movies have received the most attention in last few years, which contain violent scenes, because it is one of the undesirable features for some individuals that is used to create charm and fantasy. However, these violent scenes have had a negative impact on kids, and they are not comfortable even for mature age people. The best way to stop under aged people from watching violent scenes in movies is to eliminate these scenes. In this paper, we proposed a violence detection scheme for movies that is comprised of three steps. First, the entire movie is segmented into shots, and then a representative frame from each shot is selected based on the level of saliency. Next, these selected frames are passed from a light-weight deep learning model, which is fine-tuned using a transfer learning approach to classify violence and non-violence shots in a movie. Finally, all the non-violence scenes are merged in a sequence to generate a violence-free movie that can be watched by children and as well violence paranoid people. The proposed model is evaluated on three violence benchmark datasets, and it is experimentally proved that the proposed scheme provides a fast and accurate detection of violent scenes in movies compared to the state-of-the-art methods. Full article

Today, patients generate a massive amount of health records through electronic health records (EHRs). Extracting usable knowledge of patients’ pathological conditions or diagnoses is essential for the reasoning process in rule-based systems to support the process of clinical decision making. Association rule mining is capable of discovering hidden interesting knowledge and relations among attributes in datasets, including medical datasets, yet is more likely to produce many anomalous rules (i.e., subsumption and circular redundancy) depends on the predefined threshold, which lead to logical errors and affects the reasoning process of rule-based systems. Therefore, the challenge is to develop a method to extract concise rule bases and improve the coverage of non-anomalous rule bases, i.e., one that not only reduces anomalous rules but also finds the most comprehensive rules from the dataset. In this study, we generated non-anomalous association rules (NAARs) from a cerebrovascular examination dataset through several steps: obtaining a frequent closed itemset, generating association rule bases, subsumption checking, and circularity checking, to fit production rules (PRs) in rule-based systems. Toward the end, the rule inferencing part was performed by PROLOG to obtain possible conclusions toward a specific query given by a user. The experiment shows that compared with the traditional method, the proposed method eliminated a significant number of anomalous rules while improving computational time. Full article

A new method based on reverse-phase HPLC combined with photodiode array (PDA) was developed to quantify the release of trans-resveratrol (tRES) from solid lipid nanoparticles (SLN). The mobile phase was composed of 75:0:25 (V/V) water/methanol/acetonitrile at 0–3.5 min, 32.5:30.0:37.5 (V/V) water/methanol/acetonitrile at 3.6–5.8 min, and 75:0:25 (V/V) water/methanol/acetonitrile at 5.9–10 min. The flow rate was set at 1.0 mL/min, and tRES was detected at the wavelength of 306.6 nm. A concentration range of 1–100 µg/mL was used to obtain the linear calibration curve. SLN were produced by ultrasound technique to load 0.1% (wt/wt) of tRES, and the in vitro release of the drug was run in modified Franz diffusion cells. The mean recovery of tRES was found to be 96.84 ± 0.32%. The intra-assay and inter-assay coefficients of variation were less than 5%. The proposed method was applied to in vitro permeability studies, and the Weibull model was found to be the one that best fits the tRES release, which is characterized by a simultaneous lipid chain relaxation and erosion during drug release. Full article

This paper presents a tutoring system which uses three different granularities for helping students to classify animals from bone fragments in zooarchaeology. The 3406 bone remains, which have 64 attributes, were obtained from the excavation of the Middle Palaeolithic site of El Salt (Alicante, Spain). The coarse granularity performs a five-class prediction, the medium a twelve-class prediction, and the fine a fifteen-class prediction. In the coarse granularity, the results show that the first 10 most relevant attributes for classification are width, bone, thickness, length, bone fragment, anatomical group, long bone circumference, X, Y, and Z. Based on those results, a user-friendly interface of the tutor has been built in order to train archaeology students to classify new remains using the coarse granularity. A pilot has been performed in the 2019 excavation season in Abric del Pastor (Alicante, Spain), where the automatic tutoring system was used by students to classify 51 new remains. The pilot experience demonstrated the usefulness of the tutoring system both for students when facing their first classification activities and also for seniors since the tutoring system gives them valuable clues for helping in difficult classification problems. Full article

The uncertainty in parameter estimation arises from structural systems’ input and output measured errors and from structural model errors. An experimental verification of the shuffled complex evolution metropolis algorithm (SCEM-UA) for identifying the optimal parameters of structural systems and estimating their uncertainty is presented. First, the estimation framework is theoretically developed. The SCEM-UA algorithm is employed to search through feasible parameters’ space and to infer the posterior distribution of the parameters automatically. The resulting posterior parameter distribution then provides the most likely estimation of parameter sets that produces the best model performance. The algorithm is subsequently validated through both numerical simulation and shaking table experiment for estimating the parameters of structural systems considering the uncertainty of available information. Finally, the proposed algorithm is extended to identify the uncertain physical parameters of a nonlinear structural system with a particle mass tuned damper (PTMD). The results demonstrate that the proposed algorithm can effectively estimate parameters with uncertainty for nonlinear structural systems, and it has a stronger anti-noise capability. Notably, the SCEM-UA method not only shows better global optimization capability compared with other heuristic optimization methods, but it also has the ability to simultaneously estimate the uncertainties associated with the posterior distributions of the structural parameters within a single optimization run. Full article

The application of Autonomous Underwater Vehicle (AUV) is expanding rapidly, which drives the urgent need of its autonomy improvement. Motion control system is one of the keys to improve the control and decision-making ability of AUVs. In this paper, a saturation based nonlinear fractional-order PD (FOPD) controller is proposed for AUV motion control. The proposed controller is can achieve better dynamic performance as well as robustness compared with traditional PID type controller. It also has the advantages of simple structure, easy adjustment and easy implementation. The stability of the AUV motion control system with the proposed controller is analyzed through Lyapunov method. Moreover, the controlled performance can also be adjusted to satisfy different control requirements. The outperformed dynamic control performance of AUV yaw and depth systems with the proposed controller is shown by the set-point regulation and trajectory tracking simulation examples. Full article

Large-diameter multi-bucket foundation is well suited for offshore wind turbines at deeper water than 20 m. Air floating transportation is one of the key technologies for the cost-effective development of bucket foundation. To predict the dynamic behavior of large-diameter tripod bucket foundation (LDTBF) supported by an air cushion and a water plug inside every bucket in waves, three 1/25-scale physical model tests with different bucket spacing were conducted in waves; detailed prototype foundation models were established using a hydrodynamic software MOSES with a draft of 4.0 m, 4.5 m, and 5.0 m and with a water depth of 10.0 m, 11.25 m, and 12.5 m. The numerical and experimental results are consistent for heaving motion, while exhibiting favorable agreement for pitching motion. The results show that the resonant periods for heaving motion increased with increasing draft and water depth. The maximum amplitude for heaving motion first decreased and then increased with the increase of water depth and spacing between the buckets. The maximum amplitude for pitching motion first decreased and then increased with increasing water depth but decreased with increasing spacing between the buckets. The wider the spacing between the bucket foundations, the larger the heave response amplitude operators (RAOs). Simply improving the pitch RAOs by increasing the spacing between bucket foundations is limited and negatively affects motion performance during the transportation of LDTBF. Full article

We investigate the optical absorption and scattering properties of four different kinds of seawater as the quantum channel. The models of discrete-modulated continuous-variable quantum key distribution (CV-QKD) in free-space seawater channel are briefly described, and the performance of the four-state protocol and the eight-state protocol in asymptotic and finite-size cases is analyzed in detail. Simulation results illustrate that the more complex is the seawater composition, the worse is the performance of the protocol. For different types of seawater channels, we can improve the performance of the protocol by selecting different optimal modulation variances and controlling the extra noise on the channel. Besides, we can find that the performance of the eight-state protocol is better than that of the four-state protocol, and there is little difference between homodyne detection and heterodyne detection. Although the secret key rate of the protocol that we propose is still relatively low and the maximum transmission distance is only a few hundred meters, the research on CV-QKD over the seawater channel is of great significance, which provides a new idea for the construction of global secure communication network. Full article

In this study, the temperature distribution of the Methane-Air premixed flame was measured. In order to enhance the measurement accuracy of the CT-TDLAS (Computed tomography-tunable diode laser absorption spectroscopy), the SMART (simultaneous multiplicative algebraic reconstruction technique) algorithm has been adopted. Further, the SLOS (summation of line of sight) and the CSLOS (corrective summation of line of sight) methods have been adopted to increase measurement accuracies. It has been verified that the relative error for the temperatures measured by the thermocouples and calculated by the CT-TDLAS was about 10%. Full article

In this research, we investigated using unmanned aerial vehicle (UAV) photographic technology to prevent the further expansion of unauthorized construction and thereby reduce postdisaster losses. First, UAV dynamic aerial photography was used to obtain dynamic digital surface model (DSM) data and elevation changes of 2–8 m as the initial sieve target. Then, two periods of dynamic orthophoto images were superimposed for human–computer interaction interpretation, so we could quickly distinguish buildings undergoing expansion, new construction, or demolition. At the same time, mobile geographic information system (GIS) software was used to survey the field, and the information gathered was developed to support unauthorized construction detection. Finally, aerial images, interpretation results, and ground survey information were integrated and released on WebGIS to build a regulatory platform that can achieve accurate management and effectively prevent violations. Full article

This paper introduces the concept of targeted field investigation on the reliability of earth-retaining structures in an active state, which is implemented in a random finite element method (RFEM) framework. The open source RFEM software REARTH2D was used and modified suitably in order to accommodate the purposes of the present research. Soil properties are modeled as random fields, and measurements are modeled by sampling from different points of the field domain. Failure is considered to have occurred when the “actual” resultant earth pressure force on the retaining wall (calculated using the friction angle random field) is greater than the respective “predicted” force (calculated using an homogenous friction angle field characterized by the mean of the values sampled from the respective random field). Two sampling strategies are investigated, namely, sampling from a single point and sampling from a domain, through an extensive parametric analysis. As shown, the statistical uncertainty related to soil properties may be significant and can only be minimized by performing targeted field investigation. Among the main findings is that the optimal sampling location in the active state is immediately adjacent to the wall face. In addition, it is advisable that the entire wall height be considered in sampling. Finally, it was observed that the benefit from a targeted field investigation is much greater as compared to the benefit gained using characteristic values in a Load and Resistance Factor Design framework. Full article

In the present study, we report a highly effective electrochemical sensor for detecting 2,4-dinitrotoluene (2,4-DNT). The amperometric determination of 2,4-DNT was carried out using a gold electrode modified with zinc–metal organic framework-8 and silver quantum dot (Zn-MOF-8@AgQDs) composite. The synthesized nanomaterials were characterized by using transmission electron microscopy (TEM), Fourier transform infrared spectroscopy (FTIR) and X-ray powder diffraction (XRD). The synthesized nanocomposite proved to be efficient in electro-catalysis thereby reducing the 2,4-DNT. The unique combination present in Zn-MOF-8@AgQDs composite offered an excellent conductivity and large surface area enabling the fabrication of a highly sensitive (−0.238 µA µM⁻¹ cm⁻²), selective, rapid and stable 2,4-DNT sensor. The dynamic linear range and limit of detection (LOD) was about 0.0002 µM to 0.9 µM and 0.041 µM, respectively. A 2,4-DNT reduction was also observed during the linear sweep voltammetry (LSV) experiments with reduction peaks at −0.49 V and −0.68 V. This is an unprecedented report with metal organic framework (MOF) composite for sensing 2,4-DNT. In addition, the presence of other species such as thiourea, urea, ammonia, glucose, and ascorbic acid displayed no interference in the modified electrode suggesting its practicability in various environmental applications. Full article

The article presents the results of experimental and theoretical works aimed at determining the distribution of heat emitted by an obstacle lighting lamp. These kind of lamps are commonly applied as a warning for air traffic vehicles. There is a need for lighting devices with various intensities, whose application depends on the location and operating conditions. The overall aim of the author’s work is to develop a computer model that would enable us to conduct research aimed at determining the optimal parameters of lamp operation without the need to build many physical models. Measurements of heat emitted by a currently manufactured lamp were made, and based on these, a numerical model of the lamp operating under laboratory conditions was developed. The considered lamp has two heat sources, one of which is light-emitting diodes (LEDs), while the other heat source consists of stabilizers and other elements of the lamp power supply system. After positive experimental verification of the numerical model, theoretical analyses of heat emission under various meteorological conditions were carried out, while the values of ambient temperature and airflow velocity were changed; then, the influence of these parameters on the temperature distribution on the surface of the lamp was determined. Full article

Examining the indoor air environment of public venues, especially populated supermarkets such as Co-Ops in Kuwait, is crucial to ensure that these venues are safe from indoor environmental deficits such as sick building syndrome (SBS). The aim of this study was to characterize the quality of the indoor air environment of the Co-Ops supermarkets in Kuwait based on investigation of CO₂, CO, NO₂, H₂S, TVOCs, and NMHC. On-site measurements were conducted to evaluate these parameters in three locations at the selected Co-Ops, and the perceived air quality (PAQ) was determined to quantify the air’s pollutants as perceived by humans. Moreover, the indoor air quality index (AQI) was constructed for the selected locations, and the ANOVA test was used to analyze the association between the observed concentrations among these environmental parameters. At least in one spot at each Co-Op, the tested environmental parameters exceeded the threshold limit set by the environmental agencies. The PAQ for Co-Op1, 2, and 3 are 1.25, 1.00, and 0.75 respectively. CO₂ was significantly found in an association with CO, H₂S, and TVOCs, and its indoor-outdoor concentrations were significantly correlated with R² values ranges from 0.40 to 0.86 depending on the tested location. Full article

In this paper, we introduce a novel system for physics-based vehicle simulation from input trajectory. The proposed system approximates the physical movements of a real vehicle using a proportional derivative (PD) servo which estimates proper torques for wheels and controls a vehicle’s acceleration based on the conditions of the given trajectory. To avoid expensive simulation calculation, the input trajectory is segmented and compared to the optimized trajectories stored in a path library. Based on the similarity of the curve shape between the input and simulated trajectories, an iterative search method is introduced to generate a physically derivable trajectory for convincing simulation results. For an interaction with other objects in the virtual environment, the surface of the vehicle is subdivided into several parts and deformed individually from external forces. As demonstrated in the experimental results, the proposed system can create diverse traffic scenes with multiple vehicles in a fully automated way. Full article