Extraction techniques of important bioactive molecules from the major concern of Seafood byproducts are getting emphasis for better valorization. Employing green extraction technologies for efficient and quality production of these bioactive molecules is also strictly required. Hence, understanding the extraction process parameters to effectively design an applicable optimization strategy could make this real. In this review, statistical optimization strategies applied for the extraction process parameters of bioactive molecules from Seafood byproducts are focused. The type of experimental designs, and techniques applied to criticize and validate the effects of independent variables on the extraction output was addressed. Dominant parameters studied were enzyme/substrate ratio, pH, time, temperature and power of extraction instruments. The yield of bioactive compounds, chitin and chitosan, proteins and peptides, enzymes and carotenoids (Astaxanthins) were the most studied responses. Efficiency and/or economic and quality considerations and their selected optimization strategies that favour the production of potential bioactive molecules were also reviewed.

The acquisition of vegetation coverage information is crucial for crop field management, and utilizing visible light spectrum vegetation indices to extract vegetation coverage information is a commonly used method. However, most visible light spectrum vegetation indices do not fully consider the relationships between the red, green, and blue bands during their construction, making it difficult to ensure accurate extraction of coverage information throughout the crop's entire growth cycle. To rapidly and accurately obtain potato vegetation coverage information, drones were used in this study to obtain high-resolution digital orthoimages of potato growth stages. Based on the differences in the grayscale values of potato plants, soil, shadows, and drip irrigation belts, this study presents a combination index of blue and green bands (BGCI) and a combination index of red and green bands (RGCI). The vegetation index intersection method was used with 10 vegetation information indices to extract vegetation coverage, and the differences in extraction accuracy were compared with those of the maximum entropy method and bimodal histogram method. Based on the high-precision fraction vegetation coverage (FVC) extraction results, the Pearson correlation coefficient method and random forest feature selection were used to screen 10 vegetation and 24 texture features, and the top 6 vegetation indices most strongly correlated with the FVC were selected for potato growth stage FVC estimation and accuracy verification. A high-precision potato vegetation coverage estimation model was successfully established. This study revealed that during the potato tuber formation and expansion stages, the BGCI combined with the vegetation index intersection method achieved the highest vegetation coverage extraction accuracy, with overall accuracies of 99.61% and 98.84%, respectively. The RGCI combined with the vegetation index intersection method achieved the highest accuracy, 98.63%, during the maturation stage. For the potato vegetation coverage estimation models, the model based on the BGCI achieved the highest estimation accuracy (R2=0.9116, RMSE=5.7903), and the RGCI also achieved good accuracy in terms of vegetation coverage estimation (R2=0.8987, RMSE=5.8633). In the generality verification of the models, the R2 values of the FVC estimation models based on the BGCI and RGCI were both greater than 0.94. A potato vegetation coverage estimation model was constructed based on two new vegetation information indices, demonstrating good accuracy and universality.

A novel approach to optimizing turbomachinery performance is presented in this chapter, which integrates Computational Fluid Dynamics (CFD) simulations, an artificial neural network (ANN) with a modified Non-dominated Sorting Genetic Algorithm II (NSGA-II). Using this enhanced algorithm, substantial performance improvements can be achieved through geometric optimization. The effectiveness of this method is demonstrated in two case studies: an inducer for a centrifugal pump and a Savonius wind turbine. The inducer is designed to maximize head coefficient, hydraulic efficiency, and net positive suction head by optimizing factors such as inlet and outlet blade angles. The optimization process employs the Group Method of Data Handling (GMDH) for objective function modeling, followed by Pareto front plotting and TOPSIS for identifying trade-off optimal points. Results indicate significant improvements in head coefficient, hydraulic efficiency, and NPSHR by 14.3%, 0.3%, and 30.2%, respectively. Twist angle, aspect ratio, and overlap ratio are also optimized for wind turbine blades. The power coefficient is enhanced by 5.32%, the torque coefficient by 13.74%, and the rotational speed by 0.071% through multi-objective optimization. As a result of this approach, efficiency improves, and valuable insights into the optimal design principles for turbomachinery components are also gained.

This paper presents a biologically inspired flocking-based aggregation behaviour of a swarm of mobile robots. Aggregation behaviour is essential to many swarm systems, such as swarm robotics systems, in order to accomplish complex tasks that are impossible for a single agent. We developed a robot controller using Reynolds’ flocking rules to coordinate the movements of multiple e-puck robots during the aggregation process. To improve aggregation behaviour among these robots and address the scalability issues in current flocking-based aggregation approaches, we used a K-means algorithm to identify clusters of agents. Using the developed controller, we simulated the aggregation behaviour among the swarm of robots. Five experiments were conducted using Webots simulation software. The performance of the developed system was evaluated under a variety of environments and conditions, such as various obstacles, agent failure, different numbers of robots and arena sizes. The results of the experiments demonstrated that the proposed algorithm is robust and scalable. Moreover, we compared our proposed algorithm with another implementation of the flocking-based self-organizing aggregation behaviour based on Reynolds’ rules in a swarm of e-puck robots. Our algorithms outperformed this method in terms of cohesion performance and aggregation completion time.

Ti-Al based alloys, particularly TiAl and Ti3Al two-phase alloys, have garnered significant attention as potential replacements for various high-temperature structural materials due to their exceptional properties, including low density, oxidation resistance, and high strength at elevated temperatures. Despite these advantages, experimental studies on the microstructure evolution of Ti-Al based alloys under complex conditions remain challenging to observe and characterize. This review article examines the current research on molecular dynamics (MD) simulations of Ti-Al based alloys, focusing on two-phase Ti-Al alloys, Ti-Al amorphous alloys, Ti-Al composite materials, and the welding and multi-layer/film applications of Ti-Al alloys. The review highlights the unique capabilities of MD simulations in predicting the behavior of Ti-Al based alloys and addresses existing scientific challenges. Furthermore, the article discusses future research directions and development prospects in this field.

The paper explores the features of numerical simulation to analyze the dynamic behavior of drives controlled by pulse-width modulators. Modern motor control systems widely use pulse width modulation. Effective numerical modeling of such systems has specific features because the models employed are continuous-event and have hybrid behavior due to the presence of nonlinear links with discontinuities of the first kind. Therefore, it is essential to have special integration methods with variable steps, which should be factored in when developing the model. The paper shows how these problems are solved when modeling an electric drive with a DC motor in the SimInTech software.

This literature review investigates the importance of simulation and measurement techniques in the development of transmission lines and antennas, which are crucial to the reliability and efficiency of communication system. It emphasizes the necessity of exact measurement and computational approaches for simulating complicated electromagnetic process, which help to optimize designs before physical prototypes are built. The review examines a variety of research articles that offer innovative solutions to improving accuracy in antenna design, scalability and cost challenges in antenna measurements, and crosstalk measurement methods. It also explores how these methodologies affect antenna design parameters such as gain, bandwidth, and radiation patterns, emphasizing the importance of correct modeling to ensure the performance of transmission lines and antennas in modern communication system. The review serves as a valuable reference for guiding future research and technological advancements in these fields.

The majority of existing numerical simulations of the effect of bridge piers on water movement are based on a limited number of bridge piers at a laboratory scale. Furthermore, some 2D numerical simulations for actual bridge projects have deficiencies, including the use of overly large mesh sizes and an inadequate treatment of bridge piers. In this study, we compare three methods of structural mesh encryption, suspension mesh, and nonstructural mesh based on Delft3D, and apply the optimization scheme to a real bridge project. It is demonstrated that optimal results can be achieved by utilising a grid size comparable to the pier diameter (Dp) in the region away from the piers. In the vicinity of the piers, the grid cell size should be no larger than 1/9 Dp. The suspended grid technique (DD Boundary) can yield results consistent with those obtained using a full-area high-resolution grid, provided that the total number of grids can be reduced and the computational time is considerably reduced. In this study, the unstructured mesh (Deflt3D Flexible Mesh) scheme was unable to capture the oscillations of the wake flow behind the bridge piers. However, the application of the optimized scheme in bridge engineering has demonstrated its practical value. The findings of this study on mesh resolution and suspension mesh scheme can be applied to the Delft3D software and are also useful for other numerical simulation work.

To address the requirements of sonar imaging, such as high receiving sensitivity, wide bandwidth, wide receiving angle, an AlN PMUT with an optimized ratio of 0.6 for the piezoelectric layer diameter to backside cavity diameter is proposed in this paper. A sample AlN PMUT is designed and fabricated with SOI substrate-based bulk MEMS process. The characterization test result of the sample demonstrates a -6 dB bandwidth of approximately 500 kHz and a measured receiving sensitivity per unit area of at 1.37 V/μPa/mm2, which significantly surpasses the performance of previously reported PMUTs. The -6 dB horizontal angles of the AlN PMUT at 300 kHz and 500 kHz are measured 68.30° and 54.24°, respectively. To achieve an accurate prediction of its characteristics when being packaged and assembled in a receive array, numerical simulations with the consideration of film stress are conducted. The numerical result shows a maximum deviation of ±7% in the underwater receiving sensitivity across the frequency range of 200 kHz to 1000 kHz and a deviation of about 0.33% in the peak of underwater receiving sensitivity comparing to the experimental data. By such good agreement, the simulation method reveals its capability of providing theoretical foundation for enhancing the uniformity of the AlN PMUTs in future studies.

This paper introduces a low-tech capacitive micromachined ultrasonic transducer (CMUT) designed with low environmental footprint materials. The fabrication process involves a copper plate as the fixed bottom electrode, a polymer-based adhesive as a dielectric material, and an aluminum foil as the top electrode.Finite element simulations include studies of displacement, mechanical stresses, and eigenfrequency. Experimental measurements validate the device's electromechanical behavior, showing an eigenfrequency of 88.6 kHz and a displacement of 22 pm. The low-tech CMUT demonstrates potential for applications such as ultrasonic actuation and energy harvesting, offering simplicity, biocompatibility, and low environmental impact. While not directly ready for applications, these transducers provide hands-on experience with technology similar to high-performance silicon-based implementations. These low-tech MUTs are perfect practical case studies for teaching purposes, combining simulation and experimental validation.

This paper concentrates on computing the efficiency of heliostat field systems. By conducting a comprehensive analysis of the mathematical model for optical efficiency, we have effectively simplified the complex three-dimensional illumination problem of heliostat fields into a two-dimensional issue. Our work primarily investigates the calculation methods for the average optical efficiency and output power of heliostat. Traditionally, calculating shadow and blocking efficiency, key factors affecting the optical performance of mirror fields, has posed a significant technical challenge. Through innovative improvements to the Monte Carlo simulation technique, this study has successfully reduced the spatial dimensionality of the problem. We employed a series of novel coordinate transformations to simulate light tracing on a two-dimensional plane, thereby efficiently calculating the efficiency of shadows and obstructions. Not only have we solved the computational challenges of shadow and obstruction efficiency, but our unique algorithm design also allows us to precisely obtain the overall average optical efficiency of the heliostat field while enhancing computational efficiency.

The two-parameter distribution introduced by Kumaraswamy (1980) is a very flexible alternative to the Beta distribution with the same (0,1) support. Originally proposed in the field of hydrology, it has subsequently received a good deal of positive attention in both the theoretical and applied statistics literatures. Interestingly, the problem of testing formally for the appropriateness of the Kumaraswamy distribution appears to have received little or no attention to date. To fill this gap, in this paper we apply the “biased transformation” methodology proposed by Raschke (2009) to several standard goodness-of-fit tests based on the empirical distribution function. A simulation study reveals that these (modified) tests perform well in the context of the Kumaraswamy distribution, in terms of both low size distortion, and respectable power. In particular, the “biased transformation” Anderson-Darling test dominates the other tests that are considered.

This paper offers a theoretical and experimental examination of the concurrent production of electricity and heat using photovoltaic thermal (PV/T) technology. The efficiency performance of the PV/T system is meticulously analyzed using MATLAB/Simulink software environments. Notably, the proposed PV/T system shows reliable performance, and its validity is confirmed through experimental validation on a test stand with a single PV/T panel positioned at a 45-degree angle to the horizontal and a 0-degree azimuth angle.

Shear dynamics simulation under extreme pressure was used to optimise the composition of ester-based lubricant base oil and extreme pressure additives. As a result, the ester-based lubricant in the weak-gel drilling fluid achieves reduction and increases the efficiency in drilling construction, and the field operation efficiency improves. The results of base oil lubrication simulation show that three base oils, namely, methyl oleate, ethyl oleate and butyl oleate, can be stably adsorbed on the surface layer of the shear surface. Methyl oleate has the lowest system temperature after shear stabilisation and has a high load-bearing capacity. The shear stress of methyl oleate decreases by changing the initial shear temperature and speed. It increases by 6.36 MPa when the speed increases from 10 m/s to 30 m/s. At this time, the shear stress of butyl oleate increases by 10.11 MPa. The results of the four-ball friction experiments show that the radius of the abrasion spot of methyl oleate is 179.83 μm, which is smaller than that of the other two base oils. Moreover, the friction coefficient of methyl oleate is 0.0018, which is approximately 1/3 of that of butyl oleate. Methyl oleate has better lubrication efficiency. The shear simulation results are consistent with the experimental results. The simulation can be used for the molecular design of lubricant materials. The oleic acid amide–containing amine group and the glyceride oleic–containing hydroxyl group were selected as the extreme pressure functional components for shear simulation. Results show that the shear stress of oleic acid amide is much lower than that of oleic acid glyceride when the initial shear temperature and speed change. The extreme pressure lubrication component–containing amine group is better than the extreme pressure lubrication material–containing hydroxyl group. The effects of different oleamide contents in the two-component mixtures on the lubricating properties were investigated through shear simulation, with methyl oleate as the base oil and oleamide as the extreme pressure functional component. The simulation results show that the lubricant has the optimal shear stress when 10% oleamide is added to the lubricant. The base properties of the lubricant were tested using a mixture of 90% methyl oleate and 10% oleamide, formulated as a lubricant. Results show that the friction coefficient can be reduced to 0.03 when 0.5% of the lubricant is added to the base mud. Moreover, the lubricant film formed shows high strength. Then, 1% lubricant was added to the weak-gel drilling fluid to evaluate the effect of the lubricant on the gel structure of the drilling fluid. Results show that adding lubricant does not affect the rheological properties of the drilling fluid. The gel structure of the system also remains stable even after 7 days of continuous ageing. The results of the field experiments in Hua3-01 well show that adding 1% ester-based lubricant to the field drilling fluid reduces the drilling friction by 33%. Thus, the efficiency of directional side drilling can be effectively improved, complicated accidents, such as poor starting and stopping of drilling and stuck jamming, can be avoided, and the goals of reducing quantity and increasing efficiency can be completed.

Rectenna is the key component in radio-frequency circuits for receiving and converting electromagnetic waves into direct current. However, it is very challenging for the conventional semiconductor diode switches to rectify high-frequency signals for 6G telecommunication (>100 GHz), medical detection (>THz) and rectenna solar cells (optical frequencies). Such a major challenge can be resolved by replacing the conventional semiconductor diodes with tunneling diodes as the rectenna switches. In this work, metal-insulator-metal (MIM) tunneling diodes based on 2D insulating materials were designed, and their performance was evaluated using a comprehensive simulation approach which includes density-function-theory simulation of 2D insulator materials, modeling of the electrical characteristics of tunneling diodes, and circuit simulation for rectifiers. It is found that novel 2D insulators such as monolayer TiO2 can be obtained by oxidizing sulfur-metal layered materials. The MIM diodes based on such insulators exhibit fast tunneling and excellent current rectifying properties. Such tunneling diodes effectively convert the received high-frequency electromagnetic waves into direct current.

To accurately predict the matching relationships between the various components and the engine performance in the whole aero-engine environment, this study introduces a two-dimensional throughflow simulation method for the whole aero-engine. This method is based on individual throughflow solvers for the turbo-machinery and the combustor. It establishes a throughflow simulation model for the whole engine by integrating with the compressor-turbine co-operating equations and boundary conditions. The turbo-machinery throughflow solver employs a circumferentially averaged form of the time-dependent Navier-Stokes equations (N-S) as the governing equation. The combustor solver uses the Reynolds Average Navier-Stokes (RANS) method to solve flow and chemical reaction processes by constructing turbulence, combustion, and radiation models. The accuracy of the component solver is validated using Pratt & Whitney’s three-stage axial compressor (P&W3S1) and General Electric’s high-pressure turbine (GE-EEE HPT), and the predicted results are consistent with the experimental data. Finally, the developed throughflow method is applied to simulate the throttling characteristics of the WZ-X turboshaft engine. The results predicted by the throughflow program are consistent with the GasTurb calculations, including the trends of shaft power delivered, specific fuel consumption (SFC), inlet airflow, and total pressure ratio of the compressor. The developed method to perform throughflow simulation of the whole aero-engine eliminates the dependence on a general component map. It can quickly obtain the meridian flow field parameters and overall engine characteristics, which is expected to guide the design and modification of the engine in the future.

The authors of the article analyze the existing methods and models of technological preparation of machine-building industries. The structure of a three-level simulation model with network-centric control, the structures of individual elements of the simulation model and the process of simulation modeling are described. The criteria for choosing a rational option for the processing technological route have been determined. During the research, a simulation program was implemented in C++. It allows you to select the optimal scenario for the operation of a production site based on two criteria: time and cost. The volume of implementation is about 2x103 lines of code. A diagram of the modeling algorithm for the implemented program, a description of the classes and their interactions are given in the article. The developed simulation model was tested at a machine-building enterprise using the example of the “Pusher” part, manufactured under single-unit production condi-tions. The technological equipment used for the manufacture of this part was formed in the form of input data of the simulation model. The results of simulation modeling for the selected part are described. For each variant of the technological processing route, the values of variable costs and the duration of the production cycle were determined.

It is a critical issue to allocate redundancy to critical smart grid infrastructure for disaster recovery planning. In this study, we present a framework to combine statistical prediction methods and optimization models for the optimal redundancy allocation problem. First, we develop statistical simulation methods to identify critical nodes of very large-scale smart grid infrastructure based on the topological features of embedding networks, and then present a linear integer programming model based on generalized assignment problem (GAP) for redundancy allocation of critical nodes in smart grid infrastructure. The model is specifically implemented in the context of smart grid infrastructure. The findings demonstrate that the combined approach of statistical simulation and optimization effectively addresses the size limitations inherent in a sole optimization approach. Notably, the optimal solutions for redundancy allocation in very large grid systems highlight that the cost of redundancy is only a fraction of the economic losses incurred due to weather-related outages.

The pneumatic muscle is an actuator well known for its inherited compliance. In the last years, there have been a lot of applications of these actuators, mainly oriented toward medical devices. However, there are few papers that use muscle as a model associated with mechanical structures. These actuators are difficult to control because their stiffness depends on the applied pressure, determining a non-linear behavior. This article presents a model, created in Matlab, considering the muscle as a kinematic structure. The model is simulated as an individual structure and a PID controller is applied to test the response. Then, these results are validated by experimental tests done in the laboratory on different types of muscles. Comparison results validate the accuracy of the model.

Swirling coal flames are encountered in swirl burners of boiler furnaces and cyclone coal combustors, and were studied using large-eddy simulation (LES) in reported references. However, the structures of swirling coal flames remain to be further studied. In the present paper LES of swirling coal flames is conducted for two combustors using two gas combustion models. The statistical simulation results are accessed by experiments and the instantaneous simulation results are used to analyze the specific features of flame structures of four cases. It is seen that different inlet flow conditions and different secondary-air flow rate lead to different flame structures

Additive manufactured interlocking structures often face challenges in achieving suitable joinability due to thermal deformation. This issue becomes particularly interesting when fabricating structures that require high density but not fully connected layers, such as soft-magnetic materials. This study focuses on systematical investigation of the deformation as a function of finger thickness and building direction in model interlocking structure. In the perpendicular direction to the build plate, the distortions of joint part were significantly reduced due to lower thermal stress. In addition, the effect of laser power and scan speed on interlocking structure are systematically discussed. Additionally, through stress and thermal simulations of additive manufacturing process, it was confirmed that the compensated model can enhance the joinability of interlocking structures. These findings contribute to the development of optimal design for additive manufactured parts of soft magnetic materials such as stators in electric motor components, which needs insulations and density.

The 3D reconstruction of vermiculite-based sealing material was carried out based on CT scanning experiments and Avizo software. The precision and representation of the reconstructed digital core were tested by calculating the pore structure parameters and comparing them with the experimental results of mercury compression. Avizo is a perfect interface with Fluent software to perform micro-scale seepage simulation to explore the distribution of pressure and velocity fields during fluid transport. In this paper, a new approach is proposed to study the penetration leakage of non-metallic gaskets by using equivalent pore networks.

This paper presents a parametric study of the multistorey hydro-powered pump, known as "Bunyip," which has demonstrated significant potential in contributing to rural regions. The study aims to understand the underlying physics of the system and enhance its hydraulic performance. A transient three-dimensional model using the commercial Computational Fluid Dynamics (CFD) tool Ansys-Fluent is utilized to gain insights into the fundamental flow mechanics, operational efficiency, standard capacity, and relative delivery. The investigation involves an initial assessment of performance for three Bunyip devices based on manufacturing data. Parametric analysis is conducted, and a parametric dataset is generated through meticulous application and numerical modelling. The CFD results are validated against experimental data. Three design configurations are considered, and 58 sets of varied input parameters are examined. The best design configuration is evaluated against five cases of conventional hydro-power pump systems. The results indicate that a smaller diameter of the pressure chamber and a higher supply head lead to higher pressure, achieving a target head of 3 m with 15% efficiency and a flowrate of 11.82 l/min.

Voice spoofing attempts to break into a specific automatic speaker verification (ASV) system by forging the user’s voice, and can be used through methods, such as text-to-speech (TTS), voice conversion (VC), and replay attacks. Recently, deep learning-based voice spoofing countermeasures have been developed. however, the problem with replay is that it is difficult to construct a large number of datasets because it requires a physical recording process. To overcome these problems, this study proposes a pre-training framework based on multi-order acoustic simulation for replay voice spoofing detection. Multi-order acoustic simulation utilizes existing clean signal and room impulse response (RIR) datasets to generate audios, which simulate the various acoustic configurations of the original and replayed audios. The acoustic configuration refers to factors, such as the microphone type, reverberation, time delay, and noise that may occur between a speaker and microphone during the recording process. We assume that a deep learning model trained on an audio that simulates the various acoustic configurations of the original and replayed audios can classify the acoustic configurations of the original and replay audios well. To validate this, we performed pre-training to classify the audio generated by the multi-order acoustic simulation into 3 classes: clean signal, audio simulating the acoustic configuration of the original audio, and audio simulating the acoustic configuration of the replay audio. We also set the weights of the pre-training model to the initial weights of the replay voice spoofing detection model using the existing replay voice spoofing dataset and then performed fine-tuning. To validate the effectiveness of the proposed method, we evaluated the performance of the conventional method without pre-training and proposed method using an objective metric, i.e., the accuracy. As a result, the conventional method achieved 92.94% accuracy and proposed method achieved 98.16% accuracy.

In the end, this paper analyzed the economy from the investment in plant construction, raw material collection, product production and product sales. The resulting products include pyrolytic carbon, pyrolytic oil, pyrolysis gas. The results showed that when the treatment scale was 1 ton h−1, the pyrolysis plants with three loading modes will always be in a state of loss during the 20-year running time. When the processing scale was 9 ton h−1, the pyrolysis plant can be profitable in the first year. In the sensitivity analysis, the influence of three pyrolysis products on the total return on investment was explored. The results showed that the price change of pyrolysis oil has the greatest influence on the total return on investment (Total ROI) under the three loading methods, The price change of pyrolysis gas has minimal impact on the Total ROI. This study provides basic data and basis for the commercialization of coal-biomass co-pyrolysis technology and investment in plant construction.

In recent years discrete element method (DEM) has gradually been applied to the traditional fluidization simulation of fine particles in micro fluidized bed (MFB). The application of DEM in simulating fast fluidization of fine particles in MFB has not yet received attention. This article presents a drag model that relies on the surrounding environment of particles, namely particle circumstance-dependent drag modle or PCDD model. Fast fluidization in MFB of fine particles is simulated using DEM based on the PCDD model. It is found that the gas-solid two-phase flow in MFB meets the common law of fast fluidization in circulating fluidized bed (CFB) to a certain extent, and also presents a special law that is significantly different from that in CFB. Simulations indicate that the local structure in MFB exhibits particle aggregation which is a natural property of fast fluidized, forming a structure where continuous dilute phase and dispersed concentrated phase coexist. The formation and fragmentation of particle clusters in different local regions of the bed have time synchronization. There exists strong effect of solid back-mixing in MFB, leading to relatively low outlet solid flux. The gas back-mixing effect is, however, not so distinct. The axial porosity shows a monotonically increasing distribution with the bed height, but does not strictly follow the single exponential distribution. The solid volume fraction at the bottom of the bed is significantly lower than the correlated value in CFB. The axial heterogeneous distribution of the cross-sectional average porosity in the lower half of the bed is also weakened. The radial porosity shows a distribution pattern of higher in the central region and lower in the sidewall region. Compared with the correlation results in CFB, the porosity near the central region in MFB is relatively low, while the porosity near the sidewall region is relatively high. The geometric size of the container, especially the radial size, is much smaller than that of a CFB. The relative area of contact between the MFB wall and particles is larger, and the wall friction factor becomes more significant. This may be the main reason for the time synchronization of particle agglomeration, severe particle back-mixing, low outlet solid flux, monotonically increasing axial porosity and weak core-annular structure of radial porosity.

In recent years, Machine Learning (ML) has become a buzzword in the petroleum industry with numerous applications which guide engineers in better decision-making. The most powerful tool that most production development decisions rely on is reservoir simulation with applications in numerous modeling procedures, such as individual simulation runs, history matching and production forecast and optimization. However, all these applications lead to considerable computational time and computer resources associated costs, rendering reservoir simulators as not fast and robust enough, thus introducing the need for more time-efficient and smart tools, like ML models which are able to adapt and provide fast and competent results that mimic the simulator’s performance within an acceptable error margin. The first part of the present study (Part I) offers a detailed review of ML techniques in the petroleum industry, specifically in subsurface reservoir simulation, for the cases of individual simulation runs and history matching, whereas the ML-based Production Forecast Optimization applications will be presented in Part II. This review can assist engineers as a complete source for applied ML techniques since, with the generation of large-scale data in everyday activities, ML is becoming a necessity for future and more efficient applications.

Wind energy is a rapidly expanding renewable energy technique. Wind farm developers need to understand the interaction between wind farms and the atmospheric flow over complex terrain. Large-eddy simulations provide valuable data for gaining further insight into the impact of rough topography on wind-farm performance. In this research, we investigate the influence of spatial heterogeneity on wind turbine performance. We conducted numerical simulations of a 12×5 wind-turbine array on various rough topographies. First, we evaluated our LES method through mesh convergence analysis, using mean vertical profiles, vertical friction velocity, and resolved and subgrid-scale kinetic energy. Next, we analyze the effects of surface roughness and dispersive stresses on the performance of fully developed large wind farms. Our results demonstrate that the ground roughness element’s flow resistance boosts large wind-farm power production by almost 68% in fully aerodynamic rough surface compared to flat terrain. Dispersive stress analysis revealed that the primary degree of spatial heterogeneity in the wind farm is in the streamwise direction, which is the “wake-occupied” region, and the relative contribution of dispersive shear stress is almost 45% to the overall drag. We also observed that the power performance of the wind farm in complex terrain outperforms the drag. Our study has implications for improving the design of wind turbines and wind farms in complex terrain to increase their efficiency and energy output.

The implementation of grey and green infrastructure is an effective mean to address urban flooding and nonpoint source pollution, but due to the complexity of the process and the diver-sity of benefits, there is a lack of measurement for their comprehensive benefits. Adopting a typ-ical university in Beijing as an example, this paper simulated the multidimensional benefits of the water quantity, water quality, and ecology of grey and green facility renovation by coupling the storm water management model (SWMM) and InfoWorks Integrated Catchment Manage-ment (ICM). Monetization methods and economical means were employed to characterize the comprehensive benefits. The results showed that grey and green infrastructure retrofitting re-duces the number of severe overflow nodes in the study area by 54.35%, the total overflow vol-ume by 22.17%, and the nonpoint source pollution level by approximately 80% under the heavy rain scenario and 60% under the rainstorm scenario. The annual benefits of grey and green infra-structure renovation reached ¥765,600/year, of this amount, ¥83,100/year is from hydrological regulation, ¥454,100/year is from nonpoint source pollution reduction, and ¥228,300/year is from ecological improvement. The benefits of green facilities were higher than those of grey facilities, and the combined benefits were negatively correlated with the rainfall level, with a total bene-fit–cost ratio of 1.19. The results provide methodological and data support for grey and green in-frastructure retrofitting within the context of sponge cities.

The ultrasonic vibration assisted pressing process can improve the fluidity, the uneven distribution of density and particle size of WC-Co powder. However, the microscopic mechanism of ultrasonic vibration on the powder remains unclear. In this paper, WC and Co particles are simulated by three-dimensional spherical models of two particle sizes with the aide of the secondary development of Python. At the same time, the forming process of powder at mesoscale is simulated in the virtue of the finite element analysis software ABAQUS. The influence of vibration amplitude on the fluidity, the filling density and the stress distribution of WC-Co powder is investigated when the ultrasonic vibration is applied to the conventional pressing process. From simulation results, the ultrasonic vibration amplitude has great influences on the density of the compact. With the increase of the ultrasonic amplitude, the compact density also increases gradually. At the initial stage of the compaction, the particles move violently under the action of ultrasonic vibration, the fluidity is obviously enhanced, the arch bridge effect between particles is destroyed, the fine particles quickly fill the pores between the large particles, which increase the density, and the residual stress in the billet decreases after the compaction. From the experimental results, the size distribution of the billet is more uniform, the elastic aftereffect is reduced, the dimensional instability is improved, and the density curves obtained by experiment and simulation are within a reasonable error range.

Since the discovery of graphene, due to its excellent optical, thermal, mechanical and electrical properties, it has a broad application prospect in energy, materials, biomedicine, electromagnetism and other fields. A great quantity of researches on the physical mechanism of graphene has been applied to engineering in electromagnetism and optics. To study the properties of graphene, different kinds of numerical methods have been developed for simulating the electromagnetic field effects of graphene, and equivalent boundary conditions have been employed to replace graphene in the computational domain. In this work, the numerical methods with equivalent boundary conditions are reviewed, and some examples are provided to illustrate their applicability.

When there is uncertainty in the value of parameters of the input random components of a stochastic simulation model, two-level nested simulation algorithms are used to estimate the expectation of performance variables of interest. In the outer level of the algorithm (n) observations are generated for the parameters, and in the inner level (m) observations of the simulation model are generated with the value of parameters fixed at the value generated in the outer level. In this article, we consider the case in which the observations at both levels of the algorithm are independent, showing how the variance of the observations can be decomposed into the sum of a parametric variance and a stochastic variance. Next, we derive central limit theorems that allow us to compute asymptotic confidence intervals to assess the accuracy of the simulation-based estimators for the point forecast and the variance components. Under this framework, we derive analytical expressions for the point forecast and the variance components of a Bayesian model to forecast sporadic demand; and we use these expressions to illustrate the validity of our theoretical results by performing simulation experiments using this forecast model.

Air conditioners are indispensable necessities in daily life and industrial production. However, the heat generation of their internal core power components can limit their performance release. In this work, we explore the application of thermoelectric coolers (TECs) in the field of power device heat dissipation through finite element simulation. First, we geometrically modeled the structure and typical operating conditions of core power devices in air conditioners. We compared the temperature fields in air cooling and TEC active cooling modes for high power consumption power devices in a 319 K operating environment. The simulation results show that in the single air cooling mode, the maximum temperature of the 173.8 W power device reaches 394.4 K and the average temperature reaches 373.9 K, which exceeds its rated operating temperature of 368.1 K. However, after adding TEC, the maximum temperature of the power device drops to 331.8 K at an operating current of 7.5 A and the average temperature of the device is 326.5 K. It indicates that TEC active cooling has a significant effect on the temperature control of the power device. At the same time, we also studied the effect of TEC working current on the temperature control effect of power devices. For TEC, there is a minimum working current of 5 A; when it is less than 5 A, TEC has no cooling effect; the cooling effect of TEC increases with an increase in working current. When the TEC working current is 10 A, the average temperature of the power device can be reduced to 292.9 K. This study has made a meaningful exploration of the application of TEC in chip temperature control and heat dissipation, providing a new solution for chip thermal management and accurate temperature control.

Accurate analysis of continuous-wave electron spin resonance (cw ESR) spectra of biological or organic free-radicals and paramagnetic metal complexes is key to understand their structure-function relationships and electrochemical properties. Current method of analysis based on simulations often fail to extract the spectral information accurately. In addition, such analyses are highly sensitive to spectral resolution and artifacts, users’ defined input parameters and spectral complexity. We introduce a simulation-independent spectral analysis approach that enables broader application of ESR. We use a wavelet packet transform-based method for extracting g values and hyperfine (A) constants directly from cw ESR spectra. We show that our method overcomes the challenges associated with simulation-based methods for analyzing poorly / partially resolved and unresolved spectra, which is a common in most cases. The accuracy and consistency of the method are demonstrated on a series of experimental spectra of organic radicals and copper-nitrogen complexes. We showed that for a two-component system, the method identifies their individual spectral features even at a relative concentration of 5% for the minor component.

To sustain and advance the development of our laboratory, it is imperative for the laboratory 1 personnel to consistently deliver high-quality products and services that meet customer expectations. 2 The progress of productivity and the pace of technological advancements result in constant evolution 3 of measurement procedures, analytical techniques, and overall work methods. Our research within 4 the Neutron Activation Analysis (NAA) laboratory is aimed at contributing to the establishment of 5 quality assurance that complies with the ISO 17025 standard. As such, the laboratory implements 6 quality-oriented approaches to foster a culture of continuous improvement in its detector operations 7 and enhance customer satisfaction.

Humanity’s path to avoiding extinction is a daunting and inevitable challenge which proves difficult to solve, partially due to the lack of data and evidence surrounding the concept. We aim to address this confusion by addressing the most dangerous threats to humanity, in hopes of providing a direction to approach this problem. Using a probabilistic mode, we observed the effects of nuclear war, climate change, asteroid impacts, artificial intelligence and pandemics, which are the most harmful disasters in terms of their extent of destruction on the length of human survival. We consider the starting point of the predicted average number of survival years as the present calendar year. Nuclear war, when sampling from an artificial normal distribution, results in an average human survival time of 60 years into the future starting from the present, before a civilization-ending disaster. While climate change results in an average human survival time of 193 years, the simulation based on impact from asteroids results in an average of 1754 years. Since the risks from asteroid impacts could be considered in the far future, it can be concluded that nuclear war, climate change, and pandemics are presently the most prominent threats to humanity. Additionally, the danger from superiority of artificial intelligence over humans, although abstract in its sense, is a factor of careful study and could also have wide ranging implications, impeding man’s advancements towards becoming a more advanced civilization.

Groundwater degradation is a global problem linked to irrigation agriculture and aggravated by climate change. In drylands, where aquifer recharge is low, irrigation has emerged as an engine of economic growth. This problem falls under the paradigm of desertification, as it fits the definition of this complex problem in that the degradation of drylands is due to climatic variations and inappropriate human activities. Land Degradation Neutrality (LDN), the response of the United Nations Convention to Combat Desertification to the lack of progress in tackling desertification, is integrated into Sustainable Development Goal 15.3 and provides the adequate framework for implementing effective solutions. LDN prioritizes prevention strategies, and early warning systems coupled to integrated simulation models is a sound approach. We analyze the dynamics of a coastal aquifer in southern Spain, a “desertification landscape” according to the Spanish National Action Plan to Combat Desertification. For this purpose, we have (i) adapted a generic desertification model that considers socio-ecological systems as a particular case of predator-prey systems; and (ii) coupled to this model a risk analysis to calculate the probabilities of groundwater salinization under the current scenario of water resources use, driven by the expansion of greenhouse agriculture supported by external water transfer. The risk of desertification is close to 100%: groundwater salinity is 40 dS m-1 (well above tomato tolerance, 3.5 dS m-1), and 2.4 Mm3 yr–1 water transfer is needed to support the 631 ha of greenhouses. This worrying result suggests that complimentary solutions should be promoted to deactivate the ongoing process of desertification. Among them, we propose reclaimed water, diversifying the economy, or promoting crops adapted to aridity. This simulation framework shows how to explore the future of a socio-ecosystem under current scenarios and others that consider climate change, the energy crisis, or the impact of alternative solutions.

This paper considers the principles of building a circuit model of film resistor cutting. The conductive resistive medium is defined with the component equations and the topology of the circuit model. A method of estimating the electric parameters of a resistor operating in the system with a measuring voltage source is shown. An equation system for the node voltages is defined, and the resistive layer parameters are analyzed as the circuit model structure changes during the cutting process.

The combination of interstitial hyperthermia treatment (IHT) with high dose rate brachytherapy (HDR-BT) for prostate cancer treatment and has the potential to improve clinical outcome, since it highly enhances the efficiency of cell kill, especially when applied simultaneously. Therefore, we have developed the ThermoBrachy applicators. To effectively apply optimal targeted IHT, treatment planning is considered essential. However, treatment planning in IHT is rarely applied since it is regarded difficult to accurately calculate the deposited energy in the tissue in a short enough time for clinical practice. In this study, we investigated various time-efficient methods for fast computation of the electromagnetic (EM) energy deposition resulting from the ThermoBrachy applicators. Initially, we investigated the use of an electro-quasistatic solver. Next, we extended our investigation to the application of geometric simplifications. Furthermore, we investigated the validity of the superpositioning principle, which can enable adaptive treatment plan optimization without the need for continuous recomputation of the EM field. Finally, we evaluated the accuracy of the methods by comparing them to the golden standard Finite-Difference Time-Domain calculation method using gamma-index analysis. The simplifications considerably reduced the computation time needed, improving from >12 h to a few seconds. All investigated methods showed excellent agreement with the golden standard by showing a >99% passing rate with 1%/0.5 mm Dose Difference and Distance-to-Agreement criteria. These results allow the proposed electromagnetic simulation method to be used for fast and accurate adaptive treatment planning.

Double suction centrifugal pump installed along the Yellow River faces the serious sediment erosion due to the high sediment content which cause the poor operation efficiency of pump unit. The particle motion characteristics and erosion characteristics in the pump under different flow rates and different particle concentrations were numerically simulated based on the particle track model of solid-liquid two-phase flow. The results show that the flow rate has a significant effect on the particle tracks and the erosion caused by the particles in the impeller. The total erosion rate is positively correlated with the flow rate, and increases with the increase of flow rate. The vortex and secondary flow in the impeller have obvious influence on the particle trajectory, which increases the particle concentration at the trailing edge of the pressure surface and intensifies the impact erosion in this area. The particles carried by the vortex intensifies the local erosion. The particle concentration mainly affects the erosion rate, but has little effect on the erosion position. The in-fluence of flow rate on the pump erosion is greater than that of the particle properties. These results provide a reference for optimization of the design of anti-erosion blades of the double-suction pump and regulation-operation of pumping station.

There is a case about a system comprising two queues of M/M(a)/1/K with a due date with FCFS service policy in each queue. Using the methods of simulation and mathematical analysis, the solution diagrams were illustrated for the fixed due date Ɵ=1 second at the phase of due date up to the commencement of the service, limited capacity K₁=5 and K₂=4, for both scenarios of different service management rate resulted. For the analytical solution, first, a SAN model from the system was created in the Mobius tool. For simulation, a java discrete systems simulation code was used. Adjustment of the initial values, selection of the scenarios for service rate, the number of the consumers in the simulation, etc. were all carried out in the simulation code.

In this paper, the computational fluid dynamics (CFD) method has been used to simulate the gas flow and the catalytic hydrogenation process of the C-2 hydrogenation adiabatic reactor in a practical ethylene production unit of a chemical plant. The laminar finite-rate model was used for the chemical reaction model. The standard two-equation model was used for the turbulence model. The exponent-function kinetic model was used for the reaction dynamics model. The simulation results were in good agreement with the actual industrial data obtained from the C-2 hydrogenation reactor, and the distributions of reaction parameters such as temperature and component concentrations in the reactor were further analyzed. Based on the validated CFD models, the structure and operating conditions of the reactor, as well as hydrogen load distribution ratios, are simulated for comparing the comprehensive performance metrics of ethylene selectivity and acetylene conversion rate; as a result, we can obtain the optimal temperature of 312 K, the optimal hydrogen/acetylene ratio of 0.10 as well as the optimal hydrogen load distribution ratio of 4:4:2, and the diameter/height ratio exerts a marginal effect on the selectivity, conversion rate and harmonic mean of the reactor.

Nanoparticle (NP) transport is increasingly relevant to subsurface engineering applications such as aquifer characterization, fracture electromagnetic imaging and environmental remediation. An efficient field-scale simulation framework is critical for predicting NP performance and designing subsurface applications. In this work, for the first time, a streamline-based model is presented to simulate NP transport in field-scale subsurface systems. It considers a series of behaviors exhibited by engineered nanoparticles (NPs), including time-triggered encapsulation, retention, formation damage effects and variable nanofluid viscosity. The key methods employed by the algorithm are streamline-based simulation (SLS) and an operator-splitting (OS) technique for modeling NP transport. SLS has proven to be efficient for solving transport in large and heterogeneous systems, where the pressure and velocity fields are firstly solved on underlying grids using finite-difference (FD) methods. After tracing streamlines, one-dimensional (1D) NP transport is solved independently along each streamline. The adoption of OS enhances flexibility for the entire solution procedure by allowing different numerical schemes to solve different governing equations efficiently and accurately. For the NP transport model, an explicit FD scheme is used to solve the advection term, an implicit FD scheme is used for the diffusion term and an adaptive numerical integration is used to solve the retention terms. The model is implemented in an in-house streamline-based code, which is verified against analytical solutions, a commercial FD reservoir simulator (ECLIPSE) and an academic FD colloid transport code (MNMs). For a 1D homogeneous case, the effluent breakthrough curves (BTC) produced by the in-house simulator are in good agreement with the analytical solution and MNMs, respectively. For a two-dimensional (2D) heterogeneous case, the BTC and concentration pattern of the in-house simulator all match well with the solution produced by commercial simulator. Simulations on a synthetic three-dimensional (3D) nanocapsule application engineering design case, are performed to investigate the effect of fluid and NP properties on the displacement pattern of an existing subsurface fluid.

Automotive aerodynamics comprises of the study of aerodynamics of road vehicles. Its main goals are reducing drag, minimizing noise emission, improving fuel economy, preventing undesired lift forces and minimizing other causes of aerodynamic instability at high speeds. The Ahmed body has the form of a highly simplified car, consisting of a blunt nose with rounded edges fixed onto a box-like middle section and a rear end that has an upper slanted surface, the angle of which can be varied. It retains vital features of real vehicles in order to study the flow fields around it and the related turbulence models which characterizes the actual flow at elevated Reynolds number. In the present study, the aerodynamic behavior of this body is investigated numerically by the aid of commercial CFD tool: Ansys Fluent. The results of the simulation are validated with available experimental data and results of the simulations from other literatures. The numerical data were obtained for a fixed free stream velocity of 25 m/s at the inlet. The simulations were performed at a fixed slant angle of 25 degree and zero yaw angle. The present study focuses on how local refinement of mesh inside the concerned body and the outside, helps affect the results and for which grid dependency test is the primary objective of this paper. The present study also helps demonstrate how the drag of the body behaves, which is mainly the effect of pressure drag force generated at the rear portion of the body. The study also focuses on important properties like the velocity magnitude at different locations for different meshing cases, and to capture the flow pattern in the front or near the wake region. The study can be further helpful to future researchers in determining resistance, fuel efficiency etc. helping designers to optimize in specialized areas for better efficiency.

This publicly available simulation analysis compares baseline construction options versus sustainable options and evaluates both break-even costs as well as environmental effects. The simulation (https://rminator.shinyapps.io/sustain4/) provides users with comparative estimates based upon existing research on costs. This is the first simulation of its type that quantifies multiple sustainable construction options, associated break-even points, and environmental considerations for public use. Results estimate that a 100% solar solution for the baseline 3,000 square foot / 279 square meter house with 2 occupants results in a break-even of 9 years. The simulation includes options for rainwater harvesting or wells, Icynene foam, engineered lumber, Energy Star windows and doors, low flow water fixtures, aerobic / non-aerobic waste treatment or municipal services, and many other options. This is the first simulation of its type to provide publicly available sustainable construction analysis based on research, and it illustrates that sustainable construction might be both green for the environment and green for the pocketbook.

Flour yield determined the profitability of flour mill, but the intrinsic variability of the grain makes it very complex to analysis and estimate wheat grain flour yield. Simulation for flour yield attributes offer considerable advantages in flour mill, if reliable predictions of flour yield can be provided, because the wheat grain characteristics can be tested before milling. If this is possible, the characteristics thus observed could be quantified more reliably and objectively by Structural Equation Modelling (SEM). SEM was used to look for the most important wheat grain characteristics on flour yield, and then these wheat grain characteristics were used to simulate flour yield. Furthermore, the regressive equation was verified by the field experiment. The coefficient of variation of grain characteristics was low and distributed rather closely. The results of SEM showed that test weight had the most significantly effects on flour yield, followed by the hardness index. Test weight and hardness index could excellently estimate flour yield by multiplicative effect of test weight and hardness index, and which could determine 68% of the variation in flour yield. The simulation result can not only predict flour yield, but also look for the important grain characteristics for the flour yield.

The main purpose of this research is to use “DMAIC” and “DMADV” framework of six sigma to reduce cost of projects, increase yields, improve performance and reduce defects. This study conclude that the sigma level of cement bag production in four production lines is “4.7 DPMO” values of 710 and the possibility of defects per unit of 11 possibilities this situation was handled by using six sigma. Any business or industry run only to satisfy customer and increase their profits, this can be attained as development of quality product..For the ranking of newly established universities the certification of those institutes is very important and also a critical process. For this process we used Lean six sigma approach that can identify the wastes that affect this process.Six sigma can be applied to any work field such as education, power optimization and other types of industries Six sigma “DMAIC” approach is also used for the testing of EDA tools that occurs due to the complex coding or configurations, flows and platforms they support. To improve the process quality of SDLC it’s necessary to remove the defects of system in advance along with thorough valuation of size and it also makes project accordant with real time environment

Several factors influence traffic congestion and overall traffic dynamics. Simulation modeling has been utilized to understand the traffic performance parameters during traffic congestions. This paper focuses on driver behavior of route selection by differentiating three distinguishable decisions, which are shortest distance routing, shortest time routing and less crowded road routing. This research generated 864 different scenarios to capture various traffic dynamics under collective driving behavior of route selection. Factors such as vehicle arrival rate, behaviors at system boundary and traffic light phasing were considered. The simulation results revealed that shortest time routing scenario offered the best solution considering all forms of interactions among the factors. Overall, this routing behavior reduces traffic wait time and total time (by 69.5% and 65.72%) compared to shortest distance routing.

As the energy efficiency demands for future buildings become increasingly stringent, preliminary assessments of energy consumption are mandatory. These are possible only through numerical simulations, whose reliability crucially depends on boundary conditions. We therefore investigate their role in numerical estimates for the usage of geothermal energy, performing annual simulations of transient heat transfer for a building employing a geothermal heat pump plant and energy piles. Starting from actual measurements, we solve the heat equations in 2D and 3D using COMSOL Multiphysics and IDA-ICE, and discover a negligible impact of the multiregional ground surface boundary conditions. Moreover, we verify that the thermal mass of the soil medium induces a small vertical temperature gradient on the piles surface. We also find a roughly constant temperature on each horizontal cross-section, with nearly identical values if the average temperature is integrated over the full plane or evaluated at one single point. Calculating the yearly heating need for an entire building we then show that the chosen upper boundary condition affects the energy balance dramatically. Using directly the pipes’ outlet temperature induces a 54% overestimation of the heat flux, while the exact ground surface temperature above the piles reduces the error to 0.03%.

Micro-pollutants such as 17β-Estradiol (E2) have been detected in different water resources and their negative effects on the environment and organisms have been observed. Aptamers are established as a possible detection tool, but the underlying ligand binding is largely unexplored. In this study, a previously described 35-mer E2-specific aptamer was used to analyse the binding characteristics between E2 and the aptamer with a MD simulation in an aqueous medium. Because there is no 3D structure information available for this aptamer, it was modeled using coarse-grained modeling method. The E2 ligand was positioned inside a potential binding area of the predicted aptamer structure, the complex was used for an 25 ns MD simulation, and the interactions were examined for each time step. We identified E2-specific bases within the interior loop of the aptamer and also demonstrated the influence of frequently underestimated water-mediated hydrogen bonds. The study contributes to the understanding of the behavior of ligands binding with aptamer structure in an aqueous solution. The developed workflow allows generating and examining further appealing ligand-aptamer complexes.

Recent advances in sensor and platform technologies such as satellite systems, unmanned aerial vehicles (UAV), manned aerial platforms, and ground-based sensor networks have resulted in massive volumes of data is produced and collected about the earth. Processing, managing, and analyzing these data is one of the main challenges in 3D synthetic representation used in modeling and simulation (M&S) of the natural environment. M&S devices, such as flight simulators, traditionally require a variety of different databases to provide a synthetic representation of the world. M&S often requires integration of data from a variety of sources stored in different formats. Thus, for simulation of a complex synthetic environment, such as a 3D terrain model, tackling interoperability among its components (geospatial data, natural and man-made objects, dynamic and static models) is a critical challenge. Conventional approaches used local proprietary data models and formats. These approaches often lacked interoperability and created silos of content within the simulation community. Therefore, open geospatial standards are increasingly perceived as a means to promote interoperability and reusability for 3D M&S. In this paper, the Open Geospatial Consortium (OGC) CDB Standard is introduced. “CDB” originally refers to Common DataBase which is currently considered as a name with no abbreviation in the OGC community. The OGC CDB is an international standard for structuring, modeling, and storing geospatial information required in high performance modeling and simulation applications. CDB defines the core conceptual models, use cases, requirements, and specifications for employing geospatial data in 3D M&S. The main features of the OGC CDB Standard are described as run-time performance, full plug-and-play interoperable geospatial data store, usefulness in 3D and dynamic simulation environment, ability to integrate proprietary and open-source data formats. Furthermore, compatibility with the OGC standards baseline reduces the complexity of discovering, transforming, and streaming geospatial data into the synthetic environment and makes them more widely acceptable to major geospatial data/software producers. This paper includes an overview of OGC CDB version 1.0 which defines a conceptual model and file structure for the storage, access, and modification of a multi-resolution 3D synthetic environment data store. Finally, this paper presents a perspective of future versions of the OGC CDB and what the steps are for humanizing the OGC CDB standard with the other OGC/ISO standards baseline.

(1) Background: Breast cancer is the leading malignancy worldwide and in Ghana it has a poor overall survival. However, approximately 50% of cases are early stage disease and with advances in breast cancer treatment and improvement in survival, quality of life (QOL) becomes as im-portant as treatment of the disease. (2) Methodology: This was a cross-sectional study of survivors who had breast conserving surgery (BCS), mastectomy only (M) and mastectomy with breast re-construction (BRS) from 2016 to 2020 at a tertiary hospital in Ghana, comparatively assessing their QOL using EORTC QLQ C-30 and EORTC QLQ BR-23. (3) Results: The study participants had an overall Global Health Status (GHS) median score of 83.3 [IQR: 66.7-91.7] with no significant differences between the surgery types. The BRS group had a statistically significant lower median scores for the Functional scale (82.8 and 51.0) and the highest scores for the Symptomatic scale (15.7 and 16.5). Body image was significantly lowest for the BRS group 83.3 [68.8-91.7] and highest 100 [91.7-100] for the BCS group (p < 0.001). (4) Conclusion: There is a need to develop support systems tailored at improving the QOL of breast cancer survivors taking into consideration the type of surgery performed.

During speciation-with-gene-flow, a transition from single-locus to multi-locus processes can occur, as strong coupling of multiple loci creates a barrier to gene flow. Testing predictions about such transitions with empirical data requires building upon past theoretical work and the continued development of quantitative approaches. We simulated genomes under different evolutionary scenarios of gene flow and divergent selection, extending previous work with the additions of neutral sites and coupling statistics, allowing us to investigate if and how selected and neutral sites differ in the conditions they require for transitions during speciation. As the per-locus strength of selection grew and/or migration decreased, it became easier for selected sites to show divergence – and thus to rise in linkage disequilibrium (LD) with each other as a statistical consequence – farther in advance of the conditions under which neutral sites could diverge. Indeed, even very low rates of gene flow were sufficient to prevent differentiation at neutral sites. However, once strong enough, coupling among selected sites eventually reduced gene flow at neutral sites as well. To explore whether similar transitions might be detectable in empirical data, we used published genome resequencing data from three taxa of Heliconius butterflies. We found that allele-frequency outliers and F ST outliers exhibited stronger patterns of LD than the genomic background, as expected. The statistical characteristics of LD – likely indicative of the strength of coupling of barrier loci – varied between chromosomes and taxonomic comparisons. Broad qualitative agreement between the patterns we observed in the empirical data and our simulations suggests that selection drives rapid genome-wide transitions to multi-locus coupling, illustrating how divergence and gene flow interact along the speciation continuum.

This study presents a novel Fe-CNs-P/S carbon composite material, synthesized by doping elements P and S into NH2-MIL-101 (Fe) using carbonization method. The material's application in sustainable water treatment was evaluated, focusing on its effectiveness in activating persulfate for pollutant degradation. The research thoroughly investigates the synthesis process, structural characteristics, and performance in degrading pollutants. Results indicate that Fe-CNs-P/S-5 with 50% P and S co-doping is higher than that of other samples, where the degradation rate of TC in 30min is as high as 98.11% under the optimum conditions, that is temperature at 25 ℃, 0.05 g/L of catalyst concentration, and 0.2 g/L of PMS concentration. The composite material demonstrates robust versatility and stability, maintaining high degradation efficiency across multiple organic pollutants, with no significant reduction in catalytic performance after four cycles. Furthermore, the free radical quenching experiments displays that the singlet oxygen 1O2 is the main active species. It is demonstrated that the doping of P and S play a role in the enhancement of PMS activation over the Fe-CNs-P/S catalyst. This material demonstrates remarkable efficacy in treating a range of organic contaminants and exhibits excellent reusability, presenting a promising approach for enhancing sustainability in water treatment applications.

The open burning of sugarcane residue is commonly used as a low-cost and fast method during pre-harvest and post-harvest periods. However, this practice releases various pollutants, including dioxins. This study aims to predict polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs, or dioxins) emissions using the Grey Model (GM (1,1)) and to map the annual flux spatial distribution at the provincial level from 2023 to 2028. Using the activity rate of dry crop residue from national agencies and literature, and following the guidelines set by the United Nations Environment Programme (UNEP), an annual emission inventory was developed at the provincial level. The distribution of emissions from 2016 to 2022 was then mapped. The average PCDD/Fs emission values exhibit significant variation among the provinces, averaging 309 pg TEQ/year. Spatially, in line sugarcane production, South Sumatra and East Jawa consistently show high emissions, often exceeding 400 pg/m². Emissions based on the UNEP emission factor tend to be higher compared to other factors, due to its generic nature and lack of regional specificity. The emission predictions using the Grey Model GM (1,1) indicate that North Sumatra is expected to experience a steady increase in PCDD/Fs emissions, whereas South Sumatra and Lampung are projected to see a slight decline. This forecast assumes there will be any changes in regional intervention strategies. Most regions in Jawa Island show a gradual increase in emissions, except for East Jawa, which is predicted to have a slight decline from 416 pg/year in 2023 to 397 pg/year in 2028. Additionally, regions like Gorontalo and parts of East Jawa are projected to remain "hotspots" with consistently high emissions, suggesting the need for targeted interventions. Future studies should consider developing monthly emissions profiles to account for local agricultural practices and seasonal conditions. The emission data generated in this study, which includes both spatial and temporal distributions, is valuable for air quality modeling studies. Utilizing this data can help assess the impact of current and future emissions on ambient air quality.

We present a novel method for online measurement of multi-point opening distances of midpalatal suture during rapid palatal expansion (RPE) using fiber optic Fabry-Perot (F-P) sensors. The sensor consists of an optical fiber with a cut flat end face and an optical reflector, which are implanted into the palatal base structure of an expander and is capable of measuring the precise distance between two optical reflective surfaces. As a demonstration, a 3D printed skull model containing the maxilla and zygomaticomaxillary complex (ZMC) was produced and a miniscrew-assisted rapid palatal expander (MARPE) with two guide rods was used to generate the midpalatal suture expansion. The reflected spectrums of the sensors were used to dynamically extract cavity length information for full process monitoring of expansion. The dynamic opening of the midpalatal suture during the gradual activation of the expander was measured, and a displacement resolution of 2.5 μm was demonstrated. The angle of expansion was derived and the results suggested that the midpalatal suture was opened with a slightly V type expansion of 0.03 rad at the first loading and subsequently expanded in parallel. This finding might be useful for understanding the mechanical mechanisms that lead to different types of expansion. The use of a fiber-optic sensor for mounting the rapid palatal expander facilitates biomechanical studies and experimental and clinical evaluation of the effects of RPE.

The aim of this work was to investigate a new, simple one-pot combustion synthesis technique for creating sulphur-based CuS/ZnS p-n heterojunction nanocomposite photocatalysts. The study examined the photocatalytic activity and reusability of these nanocomposites in removing rhodamine B (RhB) dye under visible light irradiation. Various methods of characterisation were employed to determine the properties of the materials, including particle morphology, crystalline phases and bandgap energy. The intrinsic reaction parameters, such as catalyst loading, pH level of the solution, and initial pollutant concentration, were varied to establish the optimal photo-degradation conditions. The results showed that a binary CuS/ZnS catalyst with a 10 gL-1 loading, at pH 5, degraded 97% of 5 ppm RhB dye after 270 minutes of visible light irradiation. Addition-ally, this composite catalyst exhibited excellent chemical stability and reusability, achieving 83% RhB dye removal after five recycling runs. Scavenger tests identified the photogenerated holes (h+) and superoxide free radicals (•O2) as the primary reactive species responsible for degradation. This study provides valuable insight into the design of highly efficient nanomaterials for removing organopollutants in wastewater, and a possible reaction mechanism is proposed.

This study assessed the periodic fluctuations among microbial biomass Carbon (C), Nitrogen (N) and Phosphorus (P), and the consequences of variations in altitude and abiotic factors on the soil microbial biomass (C, N and P) in a temperate mixed-oak pine forest of Central Himalaya. This research was directed at three forest stands along an altitudinal gradient. Samples were collected in triplicates, seasonally from each selected site and microbial C, N and P were determined through the fumigation extraction method. Microbial biomass C, N and P decreased significantly (P<0.01, correlation coefficient -0.985, -0.963, -0.948, respectively) with increasing altitude, while the rainy season showed the highest values, and winter season revealed the least values. Microbial biomass C, N and P showed positive correlation with silt particles, water holding capacity, bulk density, porosity, soil moisture, organic C, total N and P, and negative correlations with sand particles and soil pH. The microbial biomass C showed strong associations with soil microbial N (r=0.80, P<0.01) and P (r=0.89, P<0.01) contents, while the soil microbial biomass N and P also showed strong positive correlation (r=0.92, P< 0.01). Soil microbial biomass was greatly influenced by the altitude and abiotic variables whereas, weakly by temporal variation. The microbial C: N ratio indicated that fertility of soil is influenced by the species assemblage. Our findings suggest that high microbial biomass and low C: N ratio during rainy season could be considered as a strategy to conserve nutrients by temperate mixed-oak pine forest ecosystem.

Because of the need to replace the current clinical artemisinins in artemisinin combination therapies, we are evaluating fitness of amino-artemisinins for this purpose. These include the thiomorpholine derivative artemiside obtained in one scalable synthetic step from dihydroartemisinin (DHA) and the derived sulfone artemisone. We have recently shown that artemiside undergoes facile metabolism via the sulfoxide artemisox into artemisone and thence into the unsaturated metabolite M1; DHA is not a metabolite. Artemisox and M1 are now found to be approximately equipotent with artemiside and artemisone in vitro against asexual P. falciparum (Pf) blood stage parasites (IC50 1.5 – 2.6 nM). Against Pf NF54 blood stage gametocytes, artemisox is potently active (IC50 18.9 nM early-stage, 2.7 nM late-stage). Comparative drug metabolism and pharmacokinetic (DMPK) properties were assessed via po and iv administration of artemiside, artemisox and artemisone in a murine model. Following oral administration, the composite Cmax value of artemiside plus its metabolites artemisox and artemisone formed in vivo is some 2.6-fold higher than that attained following administration of artemisone alone. Given that efficacy of short half-life rapidly-acting antimalarial drugs such as the artemisinins is associated with Cmax, it is apparent that artemiside will be more active than artemisone in vivo, due to additive effects of the metabolites. As is evident from earlier data, artemiside indeed possesses appreciably greater efficacy in vivo against murine malaria. Overall, the higher exposure levels of active drug following administration of artemiside coupled with its synthetic accessibility indicate it is much the preferred drug for incorporation into rational new artemisinin combination therapies.

This work reports the role of structure and composition on the determination of the performances of p-type SnOx TFTs deposited by rf magnetron sputtering at room temperature, followed by a post-annealed step up to 200 °C at different oxygen partial pressures (Opp), between 0% and 20%, but where the p-type conduction was only observed between 2.8–3.8%. The role of structure and composition were evaluated by XRD and Mössbauer spectroscopic studies. The study allows to identify the best phases/compositions and thicknesses (around 12 nm) to be used that lead to the production of TFTs with a bottom gate configuration, on glasses coated with conductive Indium Tin Oxide, followed by Aluminium Titanium Oxide dielectric layer with saturation mobility of 4.6 cm²V⁻¹s⁻¹ and on-off ratio above 7 × 10⁴, operating at the enhancement mode with a saturation voltage of −10 V.

Nitrogen (N) and sulfur (S) are essential macro-elements crucial for the proper development, productivity, nutrient uptake, and the building blocks of protein biosynthesis. The plant's N-metabolism is also influenced by S, and its deficiency can lead to a decline in the consumption of N from fertilizers. The objective of this research was to assess the impacts Temporal N and S applications on the nutrient uptake, productivity, use efficiencies and micronutrients content status in soybean seeds. The field trial in randomized complete block design carried out, experiment comprised fourteen treatments with varying N and S quantities. N and S were applied through starter and temporal applications in different combinations. The findings indicated that temporal application of individually N and S fertilization as 25 kg ha-1 as starter and 25 kg ha-1 as temporal applications at R2 stage enhanced the highest nutrient uptake, seeds and stalks yields. The use efficiencies, as well as the Zinc (Zn) and iron (Fe) uptake by seeds, showed an increase with the temporal application of both nutrients compared to the control. Furthermore, soil Zn and Fe contents were also enhanced with the temporal applications of nitrogen and sulfur fertilization. As a result, it could be decided that the nitrogen and sulfur temporal applications not only enhanced nutrient uptake, productivity and use efficiencies but also improved the micronutrient uptake by soybean. Furthermore, this practice contributed to an improvement in soil Zn and Fe content.

Various attempts to amplify an AQP11 cDNA from tissues of the spiny dogfish (Squalus acanthias) were made. Two pairs of deoxy-inosine-containing degenerate primers were designed based on conserved amino acid sequences from an AQP11 alignment. These primers yielded some faint bands from gill cDNA that were sequenced. Blast searches with the sequences showed they were not AQP11. An elasmobranch AQP11 nucleotide sequence alignment was produced to identify conserved regions to make further degenerate primers. One primer pair produced a short 148bp fragment showing particularly strong expression in gill and intestine. It was sequenced and represented a piece of the AQP11 gene. However, as the fragment may have resulted from contaminating genomic DNA (in total RNA used to make cDNA), 5’ and 3’ RACE was performed to amplify the two ends of the putative cDNA. 5’ and 3’ RACE amplifications depend on the presence of a 5’ cap nucleotide and a poly A tail respectively on the putative AQP11 mRNA. Hence successful amplification was only possible from cDNA and not genomic DNA. Nested RACE amplifications were performed using gill and intestinal RACE cDNA but none of the DNA fragments were AQP11. Consequently, the spiny dogfish AQP11 gene may represent a pseudogene.

Open-source devices are nowadays used in a vast number of research fields like medicine, education, agriculture, and sports among others. In this work, an open-source, portable, low cost pH logger, appropriate for in situ meas-urements was designed and developed to assist in experiments on agricultural produce manufacturing. Τhe device was calibrated manually using pH buffers for values of 4.01 and 7.01. Then it was tested by manually measuring pH from the juice of citrus fruits. A waterproof temperature sensor was added to the device for temperature compen-sation when measuring pH. A formal method comparison process between the open-source device and a Hanna HI9024 Waterproof pH Meter was designed to assess their agreement. We derived indices of agreement and graph-ical assessment tools using mixed-effects models. Advantages and disadvantages for interpreting agreement through the proposed procedure are discussed. In our illustration, indices reported mediocre agreement and the subsequent similarity analysis revealed a fixed bias of 0.22 pH units. After recalibration, agreement between the devices im-proved to excellent levels. The process can be followed in general to avoid misleading or over-simplistic results of studies reporting solely correlation coefficients for formal comparison purposes.

Natural fibers have attracted increasing interest as an alternative to produce environmentally friendly and sustainable materials. Particularly, hemp fibers have revealed to be widely used in various industrial applications due to their extremely unique properties. However, hemp can generate a large amount of agro-waste, and results in an attractive source of biopolymers for the development of low-cost materials in alternative to the raw materials and conventional petroleum-based plastics. In addition, deep eutectic solvents (DESs), a new type of truly green solvents, have been tested to remove gums, lignin, and other non-cellulosic components from hemp fibers. Reusing these components dissolved into the DESs to fabricate new materials directly by electrospinning is a very attractive but still unexplored endeavor. Thus, this innovative research to venture new upcycling pathways is focused on the fabrication of composite nanofibers by electrospinning of a gel-based blend of Poly(vinyl alcohol) (PVA) and hemp agro-waste (HW) dissolved into choline chloride (ChCl) : Glycerol (1:2) and ChCl : Urea (1:2) DES mixtures. The results obtained revealed that the produced nanofibers displayed uniform appearance with diameters ranging from 257.72 ± 65.63 nm to 380.78 ± 133.98 nm. In addition, the mechanical properties of the electro-spun composite nanofibers produced from the gel-based blends of HW dissolved in DESs and PVA (HW-DESs_PVA) were found to be superior, resulting in an enhanced tensile strength and Young’s modulus. Furthermore, the incorporation of HW into the nanofibers was able to provide bioactive antioxidant and antibacterial properties. Overall, this study demonstrated a promising, more sustainable, and eco-friendly way to produce electrospun composite nanofibers using HW in a circular economy perspective.

We report the first correction by Prime editing of a mutation in the RYR1 gene, paving the way to gene therapies for RYR1-related myopathies. The RYR1 gene codes for a calcium channel named Ryanodine receptor 1, which is expressed in skeletal muscle fibers. The failure of this channel causes muscle weakness in patients, which degenerates into motor disabilities. Currently, there are no effective treatments for these diseases, which are mainly caused by point mutations. Prime editing allows the modification of precise nucleotides in the DNA. Our results showed a 59% correction rate of the T4709M mutation in the RYR1 gene in human myoblasts by RNA delivery of the Prime editing components. It is to be noted that the T4709M is recessive, and thus, persons having a heterozygous mutation are healthy. These results are the first demonstration that it is possible to correct mutations in the RYR1 gene.

Abstract: This paper outlines the methodology and results for a two species finite volume scalar computational drug transport model developed for simulating the mass transport of Poly(lactic-co-glycolic acid (PLGA) ) from a half-embedded single strut implanted in a coronary arterial vessel wall. The mathematical drug transport model incorporates the convection-diffusion equation in scalar form (dimensionless) with a two species (free-drug and bound-drug) mass transport setup including reversible equilibrium reaction source terms for the free and bound-drug states to account for the pharmaco-kinetic reactions in the arterial wall. The relative reaction rates of the added source terms control the interconversion of drug between the free and bound-drug states. The model is solved by a 2-D finite-volume method for discretizing and solving the free and bound drug transport equations with anisotropic vascular drug diffusivities. This model is an improvement over our previously developed model using the finite-difference method. A dimensionless characteristic scaling pre-analysis was conducted a priori to evaluate the significance of implementing the reaction source terms in the transport equations. This paper reports the findings of an investigation of the interstitial flow profile into the arterial wall and the free and bound drug diffusion profiles with a parametric study of varying polymer drug concentration (low and high), tortuosity, porosity, and Peclet and DamKöhler numbers over the course of 400 hours (16.67 days). The results also reveal how a single species drug delivery model that neglects both a reversible binding reaction source term and the porosity and tortuosity of the arterial wall cannot accurately predict the distribution of both the free and bound drug.

There is a long standing ‘two times problem’ in that a satisfactory reconciliation between the time of physics and that of psychology has not been realized. A partial solution to the past/present/future phenomenon has been successfully given by the Hartle information gathering and processing system (IGUS) view. That model IGUS robot is enhanced here for the entire ‘two times problem’ to deal with not only the temporal experiences of the flow of time but also those of manifest time. A dualistic robot is proposed which has a veridical system of temporal experiences that are compatible with various spacetime cosmologies. It also has an illusory system of corresponding temporal experiences. This dualistic IGUS robot was made possible by discovering temporal experience within the brain that correspond to those of physics. The dualistic theory suggests that the veridical system, as a result of evolution, begets the illusory system to enhance behavioral adaptation. Thus, there is just one fundamental physical time which the brain does, indeed, possess and then enhances with illusory counterparts. Therefore, there should no longer be a need to reify illusory temporal experiences as modern spacetime cosmologies tend to do. Physical time already resides within human time.

Late pear cultivars, such as ‘Conference’, can be stored for a long period, with their storability depending on storage conditions. A three-year study (2011-2013) compared the impact of half-year storage using four technologies – normal atmosphere, normal atmosphere + 1-methylcyclopropene (1-MCP), controlled atmosphere, controlled atmosphere + 1-MCP – on the quality parameters of ‘Conference’ pears, such as mass loss, firmness, total soluble solids, acidity, antioxidant capacity, and the incidence of diseases and disorders. Additionally, the study analysed different storage conditions in terms of profitability, based on the market prices for pears in the seasons during which the pears were stored. The storage conditions had a very strong influence on the fruit quality parameters, and was found to affect most visibly the mass loss and the incidence of postharvest diseases and disorders. The storage of ‘Conference’ pears for 180 days in normal atmosphere is not economically viable, even if the fruit is subjected to 1-MCP treatment.

Databases are by far the most valuable asset of companies. Since the need was seen not only to count but also to have some type of record of elements such as crops, animals, money, properties and that this record could be consulted and modified according to the situation, that is where the first database was born. , and after that, these databases cannot be disorganized, they also need to be managed and administered under established standards that facilitate their understanding and management not only by their creators but by the other people who subsequently administer them. Databases and database management systems have an interesting evolutionary history that deserves to be analyzed and this is the objective of this document, where it is sought to understand. Along with databases and their management systems, data mining or Data mining arises that in order not to extend ourselves so much, it is the job of finding common patterns in various data sources and in what way they can be used to predict situations or results of various circumstances; We also focus on the other topic that we will present, Oracle data mining, which roughly is to merge data mining with Oracle, which makes it a powerful tool for obtaining information and predicting results based on statistics.In this article we will study and analyze the ideas, concepts and basic examples that make up SGBD and Data Mining and, we will try to go deeper into this topic, the use of decision techniques such as advanced statistical algorithms. We also present a fictitious example of the application of these techniques: predicting which products can be sold based on their relationship with others. we will give a brief explanation of association rules, data mining cycle and the types of learning and the evolution that data mining has had.

In this work the existence and nonexistence of stationary radial solutions to the elliptic partial differential equation arising in the molecular beam epitaxy are studied. Since we are interested in radial solutions we arrive at the following fourth-order differential equation

Diagnosis and prognosis of failures for aircrafts’ integrity are some of the most important regular functionalities in complex and safety-critical aircraft structures. Further, development of failure diagnostic tools such as Non-Destructive Testing (NDT) techniques, in particular, for aircraft composite materials, has been seen as a subject of intensive research over the last decades. The need for diagnostic and prognostic tools for composite materials in aircraft applications rises and draws increasing attention. Yet, there is still an ongoing need for developing new failure diagnostic tools to respond to the rapid industrial development and complex machine design. Such tools will ease the early detection and isolation of developing defects and the prediction of damages propagation; thus allowing for early implementation of preventive maintenance and serve as a countermeasure to the potential of catastrophic failure. In this paper, following a short introductory summary and definitions, this paper provides a brief literature review of recent research on failure diagnosis of composite materials with an emphasis on the use of NDT techniques in aerospace industry. In addition to this, within a some of significant NDT application extents, prognosis of composites is also briefly discussed.

Apolipoprotein B mRNA-editing enzyme catalytic polypeptide-like (APOBEC) proteins are a diverse and evolutionarily conserved family of cytidine deaminases that provide a variety of functions from tissue-specific gene expression and immunoglobulin diversity to control of viruses and retrotransposons. APOBEC family expansion has been documented among mammalian species, suggesting a powerful selection for their activity. Enzymes with a duplicated zinc-binding domain often have catalytically active and inactive domains, yet both have antiviral function. Although APOBEC antiviral function was discovered through hypermutation of HIV-1 genomes lacking an active Vif protein, much evidence indicates that APOBECs also inhibit virus replication through mechanisms other than mutagenesis. Multiple steps of the viral replication cycle may be affected, although nucleic acid replication is a primary target. Packaging of APOBECs into virions was first noted with HIV-1, yet is not a prerequisite for viral inhibition. APOBEC antagonism may occur in viral producer and recipient cells. Signatures of APOBEC activity include G-to-A and C-to-T mutations in a particular sequence context. The importance of APOBEC activity for viral inhibition is reflected in the identification of numerous viral factors, including Vif, which are dedicated to antagonism of these deaminases. Such viral antagonists often are only partially successful, leading to selection for viral variants.

Multiple preventive vaccines are being developed to counter the COVID-19 pandemic. The leading candidates have now been evaluated in non-human primates (NHPs) and human Phase 1 and/or Phase 2 clinical trials. Several vaccines have already advanced into Phase 3 efficacy trials, while others will do so before the end of 2020. Here, we summarize what is known of the antibody and T-cell immunogenicity of these vaccines in NHPs and humans. To the extent possible, we compare how the vaccines have performed, taking into account the use of different assays to assess immunogenicity and inconsistencies in how the resulting data are presented. We also summarize the outcome of SARS-CoV-2 challenge experiments in immunized macaques, while noting variations in the protocols used, including but not limited to the virus challenge doses.

We construct admissible circulant Laplacian matrix functions as generators for strictly increasing random walks on the integer line. These Laplacian matrix functions refer to a certain class of Bernstein functions. The approach has connections with biased walks on digraphs. Within this framework, we introduce a space-time generalization of the Poisson process as a strictly increasing walk with discrete Mittag-Leffler jumps subordinated to a (continuous-time) fractional Poisson process. We call this process ‘space-time Mittag-Leffler process’. We derive explicit formulae for the state probabilities which solve a Cauchy problem with a Kolmogorov-Feller (forward) difference-differential equation of general fractional type. We analyze a “well-scaled” diffusion limit and obtain a Cauchy problem with a space-time convolution equation involving Mittag-Leffler densities. We deduce in this limit the ‘state density kernel’ solving this Cauchy problem. It turns out that the diffusion limit exhibits connections to Prabhakar general fractional calculus. We also analyze in this way a generalization of the space-time fractional Mittag-Leffler process. The approach of construction of good Laplacian generator functions has a large potential in applications of space-time generalizations of the Poisson process and in the field of continuous-time random walks on digraphs.

Spherical harmonic (SH) interpolation is a commonly used method to spatially up-sample sparse Head Related Transfer Function (HRTF) datasets to denser HRTF datasets. However, depending on the number of sparse HRTF measurements and SH order, this process can introduce distortions in high frequency representation of the HRTFs. This paper investigates whether it is possible to restore some of the distorted high frequency HRTF components using machine learning algorithms. A combination of Convolutional Auto-Encoder (CAE) and Denoising Auto-Encoder (DAE) models is proposed to restore the high frequency distortion in SH interpolated HRTFs. Results are evaluated using both Perceptual Spectral Difference (PSD) and localisation prediction models, both of which demonstrate significant improvement after the restoration process.

Mutations in the calcium channel gene Transient Receptor Potential cation channel subfamily V member 4 (TRPV4) cause autosomal dominant skeletal dysplasia, with phenotypes ranging from mild to perinatal lethality. A recent report detailed murine thrombocytosis in the absence of functional TRPV4, but no prior reports have described platelet count abnormalities in the context of human TRPV4 disease. Here, we report a case of prolonged thrombocytosis in the context of TRPV4-associated metatropic dysplasia that was lethal in the infantile period.

Mealybugs cause economic loss to vineyards through physical damage, fouling fruit and leaves with honeydew, and the transmission of viruses. Planococcus ficus is one of several mealybug species in vineyards, and one that causes economic damage over a relatively large global range. To develop novel management tools, host resistance to P. ficus, which has not previously been identified for any grape cultivars, was studied. Ten grape lines (species, cultivars, and rootstocks) were evaluated for P. ficus resistance across two separate potted plant assays. Significant differences were detected among cultivars and rootstocks in the recorded number of P. ficus juveniles, adults and egg sacs. Cabernet Sauvignon and Chardonnay were two of the most susceptible grape cultivars for mealybug population growth, whereas rootstocks IAC 572, 10-17A and RS-3 all demonstrated some level of resistance. Southern fire ant (Solenopsis xyloni) was positively associated with mealybug populations, but did not have a negative effect on the observed presence of other arthropod species including potential predators.

ICEpMERPH, the first integrative conjugative element [ICE] of the SXT/R391 family isolated in the United Kingdom and Europe was analyzed to determine the nature of its adaptive functions, its genetic structure and homology to related elements normally found in pathogenic Vibrio or Proteus species. Whole Genome Sequencing of Escherichia coli isolate KH802 [which contains the ICE pMERPH] was carried out using Illumina sequencing technology. ICEpMERPH has a size of 110 Kb and has 112 putative open reading frames [ORFs], the “Hotspot regions” of the element were found to contain putative restriction digestion systems, insertion sequences and heavy metal resistance genes that encode resistance to mercury, as previously reported but also surprisingly to arsenate. A novel arsenate resistance system was identified in Hotspot 4 of the element, and unrelated to other SXT/R391 elements. This arsenate resistance system is potentially linked to two genes, orf 69, encoding an organoarsenical efflux MFS transporter-like protein related to ArsJ and orf70, encoding an NAD-dependent glyceraldehyde-3-phosphate dehydrogenase. Phenotypic analysis using isogenic strains of AB1157 with and without the ICE revealed resistance to low levels of arsenate in the range 15-25 mM. This novel, low level resistance may have an important adaptive function in polluted environments, which often contain low levels of arsenate contamination. Bioinformatic analysis on the novel determinant and the phylogeny of ICEpMERPH is presented.

There are frequently interactions between active folds and major rivers (mean annual water discharges > 70 m³s^-1). The major river may incise across the fold, to produce a water gap across the fold, or a bevelling (or lateral planation) of the top of the fold. Alternatively, the major river may be defeated to produce a diversion of the river around the fold, with wind gaps forming across the fold in some cases, or ponding of the river behind the fold. Why a river incises or diverts is often unclear, though influential characteristics and processes have been identified. A new scheme for investigating fold-river interactions has been devised, involving a short description of the major river, climate, and structural geology, and 13 characteristics of river and fold geomorphology: 1) Channel width at location of fold axis, w, 2) Channel-belt width at location of fold axis, cbw, 3) Floodplain width at location of fold axis, fpw, 4) Channel sinuosity, Sc, 5) Braiding index, BI, 6) General river course direction, RCD, 7) Distance from fold core to location of river crossing, C-RC, 8) Distance from fold core to river basin margin, C-BM, 9) Width of geological structure at location of river crossing, Wgs, 10) Estimate of erosion resistance of surface sediments/rocks and deeper sediments/rocks in fold, ERs, ERd, 11) Channel water surface slope at location of fold axis, s, 12) Average channel migration rate, Rm, 13) Estimate of fold total uplift rate, TUR. The first 10 geomorphological characteristics should be readily determinable for nearly all major rivers using widely available satellite imagery and fine scale geological maps. The last 3 characteristics should be determinable for most major rivers where other data sources are available. This study demonstrates the methodology of this scheme, using the example of the major rivers Karun and Dez interacting with active folds in the foreland basin tectonic setting of lowland south-west Iran. For the rivers Karun and Dez (mean annual water discharges 575 m³s^-1 and 230 m³s^-1, respectively), it was found that geomorphological characteristics Nos. 2, 3 and 7 had statistically significant differences (p-value ≤ 0.05) between the categories of river incision across a fold and river diversion around a fold. For river incision, at the fold axis, channel-belt width was always < 2.7 km, and floodplain width was generally (80 % of cases) < 5.7 km; whereas for river diversion, at the projection of the fold axis, these two characteristics had a wide range of values. For river incision, the distance from the fold core to the location where the river channel crossed the fold axis, was generally (80 % of cases) ≤ 8.5 km; whereas for river diversion, this distance was always > 22 km. Since it is highly likely that different characteristics will be important for other major rivers interacting with other folds, it is recommended that this scheme is now used to investigate a variety of major rivers from across the globe. By comparing the same parameters for different major rivers, a better understanding of fold-river interactions should be achieved.

This study investigated the effects of two plyometric training protocols on sprint and change of direction (COD) performance in elite hockey players. A parallel-group randomized controlled trial design was used and seventeen elite male and female field hockey players were randomly allocated into either low-to-high (L-H, n = 8) or high-to-low (H-L, n = 9) training groups. Each group performed separate variations of the drop jump exercise twice weekly for six weeks, with an emphasis on either jump height (L-H) or drop height (H-L). Performance variables assessed included sprint times over 10 m and 20 m, as well as 505 time. A two-way repeated measures analysis of variance was performed and Cohen’s d effect sizes were calculated. The H-L group displayed significant small ES improvement from baseline to post-training in the 10 m sprint (1.893 ± 0.08 s pre vs 1.851 ± 0.06 s post) (ES = −0.44) (P = <0.05). Small but not statistically significant differences between groups were observed for 10 m and 20 m sprint performance, and no significant differences were observed within or between groups for 505 time. These findings highlight the difficulty in substantially enhancing speed and COD ability in highly trained athletic populations through the addition of a low volume, short duration plyometric training protocol.

This brief review highlights some current issues in Galactic stellar nucleosynthesis, and some recent laboratory studies by the Wisconsin atomic physics group that have direct application to stellar spectroscopy, in order to advance our understanding of the chemical evolution of our Galaxy. The relevant publication history of the lab studies are summarized, and investigations into the abundances of neutron-capture and iron-peak elements in low metallicity stars are described. Finally, new initatives in near-infrared spectroscopy are briefly explored.

There is need to accurately design pipelines to transport the expected increase of CO₂ captured from industrial processes after the signing of the Paris Climate Agreement in 2016. This paper reviews several aspects of CO₂ pipeline design with emphasis on pressure drop and models for the calculation of pipeline diameter. Two categories of pipeline equations were identified. The first category is independent of pipeline length and has two different equations. This category is used to specify adequate pipeline diameter for the volume of fluid transported. The optimum economic pipe diameter equation (Eq. 17) with nearly uniform resultant velocity values at different flow rates performed better than the standard velocity flow equation (Eq. 20). The second category has four different equations and is used to calculate pipeline pressure drop or pipeline distance for the installation of booster stations after specifying minimum and maximum pipeline pressures. The hydraulic equation is preferred because it gave better resultant velocity values and the closest diameter value obtained using Aspen HYSYS (V.10) simulation. The effect of impurities on the pressure behaviour and optimal pipeline diameter and pressure loss due to acceleration were ignored in the development of the models. Further work is ongoing to incorporate these effects into the models.

Forest fire is a major ecological disaster, which has economic, social and environmental impacts on humans and also causes the loss of biodiversity. Forest officials issue the warnings to the public on the basis of fire danger index classes. There is no fire danger index for the country India due to the sparsely distributed meteorological stations. Previous studies suggest that Static Fire Danger Index (SFDI) as well as Dynamic Fire Danger Index (DFDI) have been derived from the satellite datasets. In this study, we have made an attempt to integrate both the Static and Dynamic fire danger indices and also used the Near Real Time (NRT) data sets that can be available for download through NASA FTP server after one hour of the satellite overpass. In this study, DFDI has been calculated from the MODIS Terra NRT Land Surface Temperature (MOD11_L2) and MODIS TERRA NRT surface reflectance MOD09. Finally, The Forest Fire Danger Index (FFDI) has been developed from the static and dynamic fire danger indices by the additive model and the overall accuracy was around 81.27%. Thus, the FFDI has been useful to predict the fire danger accurately and can be useful anywhere, where the meteorological stations are un-available.

Climate variability and change has been found to be one of the factors that affect economies leading to food insecurity in various parts of the world. Kenya is no exception. This study looks at how climate variability has contributed to food insecurity in Kisii County, Kenya. The objectives of this study is therefore to, (i) to examine the rainfall and temperature trends in Kisii County for a period of approximately 30 years, (ii) to examine the effect of climate variability on food production and (iii) to assess the perception of local farmers on weather and climate information, (iv) to evaluate the coping strategies adopted at to bridge the gap on food deficit at different household level and (v) to assess the nutritional status of children and the elderly. The study was conducted in two sub-counties of Kisii County; Marani and Bomachoge Chache. The data used was mainly rainfall and temperature data from meteorological stations and sample data gathered from selected groups. The study population comprised of children between 6 months and 59 months, household heads, elderly people and agricultural officers. Purposive sampling was used to select agricultural officers while multistage sampling was used to select respondents at household level. Data was collected by use of a pre-tested questionnaire. The MUAC tape was used to collect nutritional status of children while BMI data was obtained from elderly people. Mann Kendall statistic was used to determine whether the trend of rainfall and temperature observed is significant while Chi-square test was used to determine whether the coping strategies observed varied significantly at household level. From the analysis, rainfall has not shown any significant change in Kisii County while temperature trend has been significantly increasing over the years at 95% confidence level. This could explain the observed reduction in river levels. Analysis of crop production and price trends of major food crops in Kisii County showed a decreasing trend of food production leading to increase in price over the years. This meant that farmers could not produce enough to take them to the next harvesting season making farmers to adopt different coping strategies at household level which differed significantly according to Chi-Square test. Malnutrition status of both elderly people above 59 years and children between 6-59 months were similar with 23% of both children/elderly being severely malnourished/malnourished. This study has only looked at climatic factors such as rainfall and temperature. Other aspects such as depth of underground water, ph level of soil and the effects of land fragmentation also need to be looked at. This study is important to both farmers in choosing the right crop to plant, and policy makers and planners in formulating the best mitigation and intervention strategies for Kisii County food insecurity problem. This will further contribute to national efforts towards achievement of vision 2030.

This study compared two object-oriented land use change detection methods—detection after classification (DAC) and classification after detection (CAD) —based on a digital elevation model, slope data, and multi-temporal Landsat images (TM image for 2000 and ETM image for 2010). We noted that the overall accuracy of the DAC (86.42%) was much higher than that of the CAD (71.71%). However, a slight difference between the accuracies of the two methods exists for deciduous broadleaf forest, evergreen coniferous forest, mixed wood, upland, paddy, reserved land, and settlement. Owing to substantial spectrum differences, these land use types can be extracted using spectral indexes. The accuracy of DAC was much higher than that of CAD for industrial land, traffic land, green shrub, reservoir, lake, river, and channel, all of which share similar spectrums. The discrepancy was mainly because DAC can completely utilize various forms of information apart from spectrum information during a two-stage classification. In addition, the change-area boundary was not limited at first, but was adjustable in the process of classification. DAC can overcome smoothing effects to a great extent using multi-scale segmentations and multi-characters in detection. Although DAC yielded better results, it was more time-consuming (28 days) because it uses a two-stage classification approach. Conversely, CAD consumed less time (15 days). Thus, a hybrid of the two methods is recommended for application in land use change detection.

Objectives: We compared housing and the eating habits of Roma. Contemporary findings (2013) were compared with those from the first monothematic work on Roma (1775) depicting their housing and eating habits. Methods: Data come from a journal (1775) and from semi-structured interviews (2013) with more than 70 Roma women and men who live segregated in excluded settlements at the edges of villages or scattered among the majority. Data were collected in two villages and one district town in the Tatra region, where data from the 1775 measurements originate. We used classical sociological theory and new ethnography to interpret the obtained data. Results: The main findings showed differences between specific social classes then and now regarding housing as well as eating habits, related to both conditions among Roma in the Tatra. The national Roma foods gója or marikľa are traditional foods of Slovak ancestors living in poverty in the country. The houses of Roma do not greatly differ from those of the majority. Conclusions: We conclude that life strategies of the citizens of poor settlements now are similar to two centuries ago, typical for the culture of poverty in various countries of the world even after the centuries.

Analyzing the impacts of urban landscape patterns on the thermal environment has become one of the key research areas in addressing urban heat islands (UHI) and improving the living environment. A case study was carried out in Fuzhou, Fujian Province of China, to quantify the spatial patterns of urban landscape and land surface temperature (LST) in different development areas. The contribution of the thermal environment and the factors influencing the heterogeneity of LST were analyzed and discussed. In this study, bi-temporal Landsat imagery was selected to calculate LST, percent impervious surface area (ISA), and fractional vegetation cover (FVC). The urban area was further divided into three concentric urban zones, ranging from the city center to the urban periphery, based on urban development densities. The spatial pattern of LST and its variance were analyzed and compared between different zones and different dates. The thermal environment contribution of different zones was also quantified to indicate the change in urban landscape pattern resulting from urban expansion in different zones. Furthermore, Geodetector was used to explore the single factors and interaction factors controlling the spatial patterns of LST in each zone. The results showed that (ⅰ) Urban expansion primarily increased in zone 2 and zone 3, and the areal proportion of high and sub-high LST areas increased from 56.11% and 21.08% to 62.03% and 32.49% in zone 2 and zone 3, respectively, from 2004 to 2021; (ⅱ) The heat effect contribution of zones 2 and 3 reached from 75.16% in 2004 to 89.40% in 2021, indicating that the increase of ISA with >LSTmean was more pronounced in zone 3 and zone 2 during the period; (ⅲ) The driving factors of LST spatial distribution were regionally different because of the different landscape patterns, and the explanatory power for the heterogeneity of LST in zone 1 was weaker than that in zone 2 and zone 3 in the study area; (ⅳ) The interaction of different factors had a higher explanatory power on the spatial distribution of LST than a single factor in each zone because the distributions of land cover types are heterogeneous in urban area. The results of the study can be used to improve urban planning for urban ecology and UHI mitigation.

This paper investigates the relationship between public spaces and quality of life (QoL) for older adults, aiming to identify knowledge gaps within the context of population ageing and urbanization. Recognizing the growing importance of sustainable urban development, the research explores how cities can foster active ageing and improve QoL through accessible and inclusive public spaces. A scoping literature review identifies five key QoL domains for older adults: autonomy, meaningful activities, positive social relationships, leisure opportunities, and health. The review highlights areas requiring further investigation, including the interplay between environmental design and social connections, intergenerational perspectives on public space liveliness, the influence of context on QoL and the built environment, and the value of qualitative research in this field. By contributing to the understanding of QoL in relation to public spaces through the lens of Person-Environment fit theory, this study aims to inform urban design, landscape architecture, and policymaking in the creation of age-friendly communities with inclusive public spaces.

The bi- or multi-nucleated Reed-Sternberg cell (RS) is the diagnostic cornerstone of EBV-positive and EBV-negative classical Hodgkin lymphoma (cHL). cHL is a germinal center (GC) derived B-cell disease. Hodgkin cells (H) are the mononuclear precursors of RS. An experimental model has to fulfill three conditions to qualify as common pathogenic denominator: i) to be of germinal center-derived B-cell origin, ii) to be EBV-negative to avoid EBV latency III expression, and iii) to support permanent LMP1 expression upon induction. These conditions are unified in the EBV-, Diffuse Large B-Cell Lymphoma (DLBCL) cell line BJAB-tTA-LMP1. 3D reconstuctive nanotechnology revealed spatial, quantititive and qualitative disturbance of telomere/shelterin interactions in mononuclear H-like cells, further progression during transition to RS-like cells, including progressive complexity of the karytotype with every mitotic cycle, due to BBF (breakage/bridge/fusion) events. The findings of this model were confirmed on diagnostic patient samples and correlate with clincal outcome. Moreover, in vitro signficant disturbance of the lamin AC/telomere interaction progressively occured. In summary, our research over the past three decades identifed cHL as the first lymphoid maligancy driven by a disturbed telomere/shelterin/lamin AC interaction, generating the diagnostic RS. Our findings may act as trailblazer for tailored therapies in refractory cHL.

This paper gives a brief insight of project requirements for “Wireline” method of Horizontal Directional Drilling (HDD). In any drilling project, it is extremely important to know the precise location of existing lines, know the precise location of the advancing drill bit and know the precise location of the newly installed line. The wireline method is mainly used to accurately steer during medium (Midi-HDD), and large (Maxi-HDD). Today, there are two methods of HDD wireline steering: magnetic and gyro. The magnetic steering tool uses a surface tracking system to verify the tool’s precise underground position. Sensors located within the down-hole provide constant updates of Inclination, Azimuth and Tool Face orientation to the surface via a wireline. The data is processed utilizing computers from the surface and specialized Steering software to provide information on depth, course length and distance off the predetermined azimuth. In addition to a great steering method, HDD projects require the presence of well-trained and experienced steering technicians. Those people are specifically trained to operate the machinery, and it would be counterproductive to work with such great equipment without the help of the correct operators. In conclusion, the wireline method of HDD has a unique capability to track the location of the cutterhead and steer it during the drilling process. The result is a greater capability in placing the necessary utilities in difficult underground conditions.

Optimizing warehouse operations and leveraging data insights are driving forces behind the rise of automation. This research explores the development of the SWIF warehouse management system (WMS) using the Agile methodology, a departure from traditional software development approaches. Agile’s iterative and step-by-step approach facilitated a streamlined development process. It allowed for quick adjustments based on evolving needs and feedback from stakeholders. This resulted in a substantial decrease in development time and a noticeable improvement in the final product’s quality. The study emphasizes the positive effect of Agile on teamwork and customer satisfaction. Developers reported enhanced communication and collaboration, leading to a stronger sense of ownership and engagement. Customers expressed greater satisfaction with the features and functionalities delivered in stages. The successful implementation of Agile in SWIF’s development showcases its effectiveness in managing complex and ever-changing software development projects. The study encourages the adoption of Agile methodology for similar projects to boost responsiveness, quality, and overall project success.

Edge computing helps radio-supported mobile systems to process computing tasks on the side of servers. The proximity to an edge computing node avoids excessive latencies, which benefits the calculation of real-time algorithms. Special computing needs arise because mobile systems are often so limited in weight and energy that they cannot carry powerful on-board computers. We propose the use of FPGA-based co-processors (FPGA: Field Programmable Gate Array) to handle computations in an edge node. The calculation of the Fast Fourier Transformation (FFT) will be presented as an example of a co-processor. The use of FPGA-based co-processors poses a particular challenge when a mobile system leaves its radio cell, and the computing context must be transferred to another edge node. The article first addresses specific edge computing requirements, such as case-by-case reconfiguration of computing hardware and the handover mechanism from one edge node to another. Using the example of an FPGA-based FFT co-processor, we describe its development, which was carried out under the condition that mobile clients can request different co-processors and that they can also change the edge node when changing the radio cell. The latter requires passing the co-processor context. For the FPGA, this means that the co-processor is part of a partially reconfigurable environment and must support the handover mechanisms in hardware. At the end we indicate the need for FPGA resources and compare this with alternative solutions.

This paper introduces the exponential time differencing (ETD) technique as a numerical method to solve efficiently American vulnerable options pricing. We address several challenges, including removing cross-derivative terms through appropriate transformations, treating early-exercise opportunities using the penalty method, and substituting fixed boundary conditions with corresponding one-sided finite differences. The proposed method is shown to be both accurate and efficient through numerical experiments, which also compare the results with existing methods and analyse the numerical stability and convergence rate.

This paper explores the multifaceted impact of biofilms, bacterial communities enveloped in extracellular polymeric substance (EPS). Biofilms play a dual role, acting as environmental champions and health threats. They interact with heavy metals, either causing pollution or aiding environmental remediation. Beneficial biofilms generate electricity and repair concrete cracks, offering sustainable solutions. Conversely, they contribute to infections, posing health risks. The study emphasizes the need for in-depth research, utilizing bibliographic methods to analyze global biofilm research. By identifying keywords, core countries, and pivotal organizations, the paper informs future investigations, offering insights into biofilm research evolution and practical applications.

In the last two decades, plant taxonomy has bloomed, following the development of a novel technique, namely DNA Barcoding. DNA barcodes are standardized sequences, ideally unique, coding or non-coding, either from the genome of the organism or from its organelles, that are used to identify/classify an organismal group; in short the method includes amplification of the DNA barcode, sequencing and comparison with a reference database containing the relevant sequences from different species. In plants, the use a universal DNA barcode, such as COI which is used in animals, has not been achieved so far. Several DNA barcodes from single loci as well as combinations of barcodes have been successfully used in various settings; additionally, as next generation sequencing becomes affordable, very long sequences- super barcodes, such as the chloroplast genome are being used successfully especially to distinguish between close species. In this review we summarize the work done on DNA barcoding in plants and discuss different approaches used so far.

Background The falsification of food products is a practice that has always been with mankind. Initially, it stemmed from the need to satisfy basic needs, and then from the desire for profit, at the expense of the health and sometimes the lives of consumers. Today, food safety issues are becoming a priority in consumers' daily lives. It is estimated that one in four food products is falsified. Man has lost the ability to naturally identify healthy food. He has therefore begun to prioritise the speed and ease of its preparation at the expense, often of health. The techniques currently available for detecting falsification are inaccessible to the ordinary consumer. The technique proposed by the authors is the beginning of a publicly available method for detecting falsification. Scope and approach Currently, instrumental or sensory methods are used to assess the authenticity, and therefore identification, of foods. The former are expensive and time-consuming and the latter are unobjective. The authors proposed a method using ultrasound with parameters that are neutral to the material to be tested. The technique allows results to be obtained in times measured in microseconds without destroying the material under test, saving costs. Three differently weighted groups of beers were used for the study. These were industrial, regional and domestic beers. Main findings and conclusions The results of the study indicate that the ultrasonic method is useful for the non-destructive identification of industrial and regional beers, which are produced using different technologies and differ in composition. The method analysed was not suitable for separating homebrew beers from other types of beer.

This article presents a novel sustainable business management technique, emphasizing description and estimation over the outdated profit metric. Due to the intricacies and challenges of implementing the 2019 capital management method based on capital valuation (implemented in 2020–2022), a simpler approach became essential. While it is plausible for organizations to implement capital management based on their valuation, undertaking it with no outside help presents a challenge. The new descriptive method is fundamentally distinct in that detailed monetary valuations of capitals are omitted in favor of description and estimation. This paper establishes the groundwork for applying the new approach in several stages and introduces three new management indicators—the overall accomplishment of management goals index (evaluating management efficacy), the capital level index, and the adjustment (compliance) index—replacing the profit metric. Noteworthy advantages include separating the assessment of management outcomes from the organization's condition, including human and social capital into efficiency evaluations, and removing the profit indicator for management purposes, which prevents resource waste and enhances company efficiency and effectiveness.

By developing the previously proposed method of combining continuum mechanics with Einstein Field Equations, it has been shown that the classic relativistic description, curvilinear description, and quantum description of the physical system may be reconciled using the proposed Alena Tensor. For a system with an electromagnetic field, the Lagrangian density equal to the invariant of the electromagnetic field was obtained, vanishing four-divergence of canonical four-momentum appears to be consequence of the Poyinting theorem, and explicit form of one of gauges of the electromagnetic four-potential was introduced. The proposed method allows for further development with additional fields.

During the creation and integration of a health care system based on medical knowledge graphs, it is necessary to review and select the vocabularies and definitions that best fit the information requirements of the system being developed. This implies the reuse of medical knowledge graphs; however, full importation of knowledge graphs is not a tractable solution in terms of memory requirements. In this paper we present a modularization-based method for knowledge graph reuse. A case study of graph reuse is presented by transforming the original model into a lighter one.

This paper presents a new method for approximating the classical arcsine function. The proposed approximating methodology is simpler in its approach than other classical approaches and undeniably innovative. It is based on matrix representation besides the basic interpolation to approximate the inverse trigonometric function. It provides an efficient model which allows for reliable and precise calculations. The results are as per our knowledge unseen results in the previous literature.