Production of electricity using hydro-kinetic tidal turbines has many challenges that must to be overcome to ensure reliable, economic and practical solutions. Energy from flowing water is converted by a system comprising: the turbine rotor blades, a gearbox, an electrical generator, control systems, power electronics, export cables, and a connection to the electricity grid. To date these have often been modelled using simulations of independent systems, lacking bi-directional, real-time, coupling. This approach leads to critical effects being missed. Turbulence in the flow, results in large velocity fluctuations around the blades, causing rapid variation in the shaft torque and generator speed, and consequently in the voltage seen by the power electronics and consequently the export power quality. The resulting poor quality power may be unacceptable to the grid. Conversely, grid frequency and voltage changes can also cause the generator speed to change, resulting in changes to the shaft speed and torque and consequently changes to the lift and drag forces acting on the blades. Clearly, fully integrated, bi-directional, models are needed. Here we present two fully coupled models which use different approaches to model the hydrodynamics of rotor blades. The first model uses Blade Element Momentum Theory (BEMT), resulting in an efficient tool for turbine designers. The second model also uses BEMT combines this with an actuator line model of the blades coupled to an unsteady computational fluid dynamics (CFD) simulation. This simulation, implemented in OpenFOAM, uses an energy balance to compute the shaft speed. Both the BEMT and CFD models are coupled to an Open Modellica model of the electro-mechanical system. Both models have been used to simulate the performance of a 1.2m diameter, scale model, of a three bladed horizontal axis tidal turbine tested in the University of Edinburgh FloWave Ocean Energy Research Facility. The turbulent flow around the blades and the mechanical-electrical variables during the stable period of operation are analysed. Time series and tabulated average values of mechanical thrust, power, torque, and rotational speed as well as electrical variables of generator power, electromagnetic torque, voltage and current are presented for the coupled system simulation. The relationship between the mechanical and electrical variables and the results from both tidal turbine approaches are discussed. Our comparison shows that while the BEMT model provides an effective design tool (leading to slightly more conservative designs), the CFD/BEMT simulations provide more accurate predictions of the blade loads which can be especially important in assessing fatigue on the blades (though at an increased computational cost).

Coronavirus disease 2019 (COVID-19) has detrimental multi-system consequences. Symptoms may appear during the acute phase of infection, but literature on long-term recovery of young adults after mild-to-moderate infection is lacking. Heart rate variability (HRV) allows observation of autonomic nervous system (ANS) modulation post SARS-CoV-2 infection. Additionally, physical activity (PA) helps improve ANS modulation, where investigation of PA influence on ANS recovery is vital to reduce risk and severity of symptoms. Clinicians may use this research to aid development of non-medication interventions. At baseline, 18 control (CT) and 20 post-COVID-19 (PCOV) participants were observed where general amnamnesis was performed, followed by HRV and PA assessment. 10 CT and 7 PCOV subjects returned for follow-up (FU) evaluation 6 weeks after complete immunization (2 doses) and assessments were repeated. Over the follow-up period, decrease in sympathetic (SNS) activity (mean heart rate: p=0.0024, CI=-24.67- -3.26; SNS index: p=0.0068, CI=-2.50- -0.32) and increase in parasympathetic (PNS) activity (mean RR:p=0.0097, CI=33.72-225.51; PNS index: p=0.0091, CI=-0.20-1.47) were observed. At follow-up, HRV was not different between groups (p>0.05). Additionally, no differences were observed in PA between moments and groups. This study provides evidence of ANS recovery after SARS-CoV-2 insult in young adults over a follow-up period, independent of changes in PA.

This enables the chip to regulate the voice recognition function of the gadget, leading to a more natural and human-like process. Integrating this technique into the English language voice recognition system can greatly improve its precision in identifying the speech of a particular person. This research seeks to investigate and create an automatic error detection technique for an embedded speech instruction recognition system for English using artificial intelligence. The study commences with a conventional introduction to artificial intelligence, thereafter delving into a comprehensive investigation of the speech recognition algorithm. The MATLAB programme is used to determine the accurate number of words recognised by the system and its accuracy rate. The embedded teaching recognition system for English is then tested in different contexts to assess its performance. Several tests are performed to compare and analyse the results, which indicate that the integrated English voice recognition system achieves an accuracy rate of over 90% and has a low error rate in a calm environment. In a bustling environment with numerous auditory stimuli, the accurate recognition rate typically exceeds 60%.

Prolylcarboxypeptidase (PRCP, PCP, Lysosomal Pro-X-carboxypeptidase, Angiotensinase C) controls angiotensin - and kinin- induced cell signaling. Elevation of PRCP appear to be activated in chronic inflammatory diseases (cardiovascular disease (CVD), diabetes) in proportion to severity. Vascular endothelial cell senescence and mitochondrial dysfunction have consistently been shown in models of CVD in aging. The cellular senescence, a driver of age-related dysfunction, can differentially alter the expression of lysosomal enzymes due to lysosomal membrane permeability. There is a lack of data demostrating the effect of age-related dysfunction on the expression and function of PRCP. To explore the changes in PRCP, PRCP-dependent prekallikrein (PK) pathway was charcterized in early – and late-passage human pulmonary artery endothelial cells (HPAECs). Detailed kinetic analysis of cells treated with high molecular weight kininogen (HK), a precursor of bradykinin (BK), and PK revealed a mechansim by which senescent HPAECs activate the generation of kallikrein upon the assembly of the HK-PK complex on HPAECs in parallel with an upregulation of PRCP and endothelial nitric oxide (NO) synthase (eNOS) and NO formation. The NO production and expression of both PRCP and eNOS increased in early-passage HPAECs while decreased in late-passage HPAECs. Low activity of PRCP in late passage HPAECs was associated with rapid decreased telomerase reverse transcriptase mRNA levels. We also found that, with an increase in the passage number of HPAECs, reduced PRCP altered respiration rate. These results indicated that aging dysregulates PRCP protein expression, and further studies will shed light into the complexity of PRCP-dependent signling pathway in aging.

The integration of renewable energy and hybrid energy storage system (HESS) into electrified railways to build electric railway smart microgrid system (ERSMS) is beneficial for reducing fossil fuel consumption and minimizing energy waste. However, the fluctuations of renewable energy generation and traction load challenge the energy management effectiveness for such a complex system. In this work, an energy management strategy is proposed which firstly decomposes the renewable energy into low-frequency and high-frequency components by an integrated empirical mode decomposition (IEMD). Then, a two-stage energy distribution approach is utilized to appropriately distribute the energy flow among the ERSMS. Finally, the feasibility and effectiveness of the proposed solution are validated through case study.

This paper presents a new methodology to evaluate the performance of an electric vehicle hybrid power system consisting of a fuel cell and a supercapacitor. The study compares the results with those obtained for a battery-electric vehicle. The methodology extends to three driving modes, ECO, NORMAL, and SPORT, corresponding to conservative, moderate, and aggressive acceleration, and three driving conditions, low, medium, and high energy demand. We develop a simulation process to evaluate the energy consumption and the energy rate of a specific electric vehicle used as a prototype for the study. The methodology applies to a driving route that includes acceleration, deceleration, braking, and constant speed segments reproducing standard driving conditions in urban journeys. The proposed method considers combined driving modes, ECO, NORMAL, and SPORT, in each acceleration process, with variable fractions, 0% to 100%, for each mode. This methodology optimizes the simulation results as it fits the current driving way in urban environments. The simulation results show an average reduction in energy consumption of 37% and 27.1% in vehicle weight, contributing to lower energy use. The study concludes that using a hybrid power system, fuel cell/supercapacitor, instead of a battery in electric vehicles is beneficial, especially in journeys with frequent acceleration processes.

The Eliezer and Gray physical interpretation of the Ermakov-Lewis invariant is applied as a guiding principle for the derivation of the special relativistic analog of the Ermakov-Milne-Pinney equation and associated first integral. The special relativistic extension of the Ray-Reid system and invariant is obtained. General properties of the relativistic Ermakov-Milne-Pinney are analyzed. The conservative case of the relativistic Ermakov-Milne-Pinney equation is described in terms of a pseudo-potential, reducing the problem to an effective Newtonian form. The non-relativistic limit is considered as well. A relativistic nonlinear superposition law for relativistic Ermakov systems is identified. The generalized Ermakov-Milne-Pinney equation has additional nonlinearities, due to the relativistic effects.

To date, Cartesian (x, y, z) coordinate system (CCS) has been the default approach to geometrically specify atomic spatial positions in protein structures since the launch of Protein Data Bank (PDB) in 1971. To this end, this paper proposes a local spherical coordinate system (SCS) approach as an alternative to the default approach and a previously reported global SCS approach. The local SCS approach here requires only two parameters (θ and φ), instead of x, y and z as required by the default CCS approach. Essentially, CCS and SCS are like the two sides of one coin, i.e., geometric coordinate system for three-dimensional position specification. Therefore, this paper furthermore argues that it is time to flip the coin over, and have a look at the other side of the coin, e.g., the local SCS approach, which possesses an intrinsically lower degree of descriptional complexity than that of the default CCS approach, and constitutes a potentially useful alternative perspective for all protein structural research field.

A practical method is presented to estimate rare earth elements (REE) concentrations in magmatic vapour phase (MVP) in equilibrium with water-saturated granitic melts based on empirical fluid-melt partition coefficients of REE (k_P^REE). The values of k_P^REEcan be calculated from a set of new polynomial equations linking to the chlorine molality (m_Cl^v) of the MVP associated with granitic melts, which are established via a statistical analysis on the existing experimental dataset. These equations may be applied to the entire pressure range (0.1 to 10.0 kb) within the continental crust, suggesting that light REEs behave differently in magmatic fluids, i.e. either being fluid compatible with higher m_Cl^v or fluid incompatible with lower m_Cl^v values. In contrast, heavy REEs are exclusively fluid incompatible and partition favourably into granitic melts. Consequently, magmatic fluids tend to be rich in LREE relative to HREE, leading to REE fractionation during the evolution of magmatic hydrothermal systems. Maximum k_P^REEvalue for each element is predicted and presented in a REE distribution diagram constrained by the threshold of m_Cl^v. REE contents of the granitic melt is approximated by whole-rock analysis, so that REE concentrations in the associated MVP would be estimated from the value of k_P^REE given chemical equilibrium retains. Two examples are provided respectively, to show the use of this method as a REE tracer to fingerprint the source of ore-fluids responsible for the Lake George intrusion-related Au-Sb deposit in New Brunswick (Canada), and for the Bakircay Cu-Au (-Mo) porphyry systems in northern Turkey.

This article deals with the denoising of signals from sensors (current and voltage) in a photovoltaic conversion chain using wavelet theory. The idea is to reduce the noise as much as possible without distorting or losing the original signal information. To see the reliability of this proposed method, a comparative study between our proposed method (WDD) and the classic low-pass filter method was presented. The contribution in this work is the improvement of the DC-DC boost converter via the use of wavelet theory, however, that’s why we set two objectives: the first is to obtain reliable control of the DC-DC boost converter via the proposed WDD and the second to increase the overall system efficiency. The experimental results show a very great improvement in the quality of the signals of the proposed method compared to the classic method of filtering by low-pass filter.

This study develops a vitamin C controlled-release system trackable via color changes as a function of vitamin C release. The system is composed of coaxial microfibers prepared via coaxial electrospinning, with a core of poly(ethylene oxide) (PEO) incorporating vitamin C, and a shell composed of polycaprolactone (PCL) containing polydiacetylene (PDA) as the color-changing material. The shell thickness was controlled by adjusting the amount of PCL ejected during electrospinning, allowing the regulation of the release rate of vitamin C. When vitamin C added to PEO penetrated the PCL layer, the color of PDA changed from blue to red, indicating a color change. The results of this study can be applied to devices that require immediate detection of vitamin C release levels.

Knowledge is not merely the characteristic of certain pieces of information being deemed true and justifiable, but rather a process. Within an axiomatic system, the set of information that reaches the status of knowledge forms a universe that provides an interpretation of the reality one aims to describe. Language exchanges information through communication and the process of justification (exchange of information), if it consistently justifies a particular piece of information, it elevates it to knowledge. In this paper, we provide a framework for knowledge within an axiomatic model where we define the fundamental elements of communication and grammar. As a result, the structure dictates that knowledge, to be considered as such, must be investigateable by anyone who utilizes it in its entirety, both in form and content. Ultimately, the development of knowledge processing, referred to as \emph{knowmatics}, represents a clear evolution of the computer science that processes information (subset of knowledge).

This study aims to assess the operational capabilities of disaster and emergency management re-sources (DEMRs), which are pivotal in mitigating risks and minimizing losses amid the increas-ing frequency of disasters. The research constructs an effective operational capability evaluation system for DEMRs, encompassing four key aspects: resource planning, organizational manage-ment capability, resource support capability, and information processing capability. It focuses on identifying the factors that influence the effective operational capability of DEMRs in China and Korea, comparing and analyzing the relative importance and priority of each evaluation domain and indicator within these countries to enhance DEMRs' operational effectiveness. The method-ology involves calculating and ranking the weight of the four domains, with findings indicating that organizational management capability is most significant in China, whereas resource sup-port capability is prioritized in Korea. A comparative analysis of the local weight of indicators within each domain revealed the largest discrepancy between China and Korea in the infor-mation processing capability domain. The study concludes by calculating global weights, identi-fying fast response capability and resource allocation capability as the most impactful factors on DEMRs' operational capability, highlighting their critical role in disaster and emergency man-agement.

The article presents several innovative systems developed through student laboratory projects, including two autonomous vehicles, a four-legged walking robot, an active ankle-foot orthosis, a ball on beam balancing mechanism, a ball on plate system, and a manipulator arm—all powered by pneumatic artificial muscles (PAMs). Fluidic muscles offer significant potential in various mechatronic systems, robots, and manipulators due to their flexible, lightweight nature and compliance. Their ability to produce smooth and adaptable motions is particularly beneficial in applications requiring natural and human-like movement, such as rehabilitation and assistive devices. Although PAMs powered control systems face challenges with nonlinear phenomena, their biologically inspired design holds promise for future applications across various industries. These may include innovative applicability in industrial, automotive, and aerospace sectors, as well as use in sports, medical aids, entertainment, and animatronics. Incorporating self-made laboratory systems actuated by PAMs into control systems education offers a comprehensive learning opportunity that combines theoretical concepts with hands-on experience. This approach develops the necessary skills of future engineers, expanding their understanding of technical principles and preparing them for future challenges in engineering practice.

The design complexity of the new generation of civil aero-engines results in higher demands on engines’ components, higher component temperature, higher heat generation, and, finally, critical thermal management issues. This paper will propose a methodological approach to create physics-based models for heat loads developed by sources as well as a systematic sensitivity analysis to identify the effects of design parameters on the thermal behaviour of civil aero-engines. The ranges and levels of heat loads generated by heat sources (e.g., accessory gearbox, bearing, pumps, etc.) and heat absorption capacity of heat sinks (e.g., engine fuel, oil, and air) are discussed systematically. The practical research challenges for thermal management system design and development for the new and next generation of turbofan engines will then be addressed through a sensitivity analysis of the heat load values as well as the heat sinks flow rates. The potential solutions for thermal performance enhancements of propulsion systems will be proposed and discussed accordingly.

Leptospira, which are known to be important disease-causing agents transmitted between animals and humans, results in significant illness and, in some cases, significant death in human populations. This study aims to examine the genomic structure of Leptospira interrogans serovar Copenhageni strain FDAARGOS_203 to identify the specific genetic factors that contribute to antimicrobial resistance (AMR) and defense against phages. The genome, consisting of two contigs totaling 4,630,574 base pairs, underwent thorough examination for protein-coding sequences, transfer RNA genes, and ribosomal RNA genes. A total of twenty-two antibiotic resistance genes that specifically target essential cellular processes such as cell wall synthesis, DNA replication, and protein synthesis have been identified. Significant among these were gidB, GdpD, and PgsA, each involved in separate aspects of antibiotic resistance. In addition, the investigation explored the defense mechanisms of bacteriophages, revealing the presence of defense islands that contain a range of anti-phage systems, including RM_Type_IV, PrrC, Borvo, CAS_Class1-Subtype-IC, and CAS_Class1-Subtype-IB. This comprehensive genomic analysis enhances our understanding of the molecular mechanisms that determine Leptospira's ability to adapt to various environments. The identified genetic factors linked to AMR and defense against phages not only enhance our scientific comprehension but also provide a basis for focused interventions to reduce the impact of leptospirosis.

One of the important issues being explored in Industry 4.0 is a collaborative mobile robots. This collaboration requires precise navigation systems, especially indoor navigation systems where GNSS (Global Navigation Satellite System) cannot be used. To enable precise localization of robots, different variations of navigation systems are being developed, mainly based on trilateration and triangulation methods. Triangulation systems are distinguished by the fact that they allow precise determination of an object’s orientation, which is important for mobile robots. An important feature of positioning systems is the frequency of position updates based on measurements. For most systems it is 10-20 Hz. In our work, we propose a high-speed 50 Hz positioning system based on the triangulation method with infrared transmitters and receivers. In addition, our system is completely static, i.e. it has no moving/rotating measurement sensors, which makes it more resistant to disturbances (caused by vibrations, wear and tear of components, etc.). In this paper we describe the principle of the system as well as its design. Finally, we present tests of the built system, which show centimeter positioning accuracy with a position update frequency of 50 Hz.

Everyone should therefore consistently get access to enough and safe water. The operation of the existing distribution network as well as the proper optimization and implementation of the new distribution systems are required for a sufficient and safe water supply. In Sekota town sufficient amount of water was not reached to the beneficiaries due to shortage of water at the source. The primary goal of this study was to evaluate the performance and optimize the existing Sekota water supply distribution system using Bentley Water GEMS.The system's hydraulic modeling is carried out by considering as a continuous supply system, and the evaluation procedure used the extended period simulation approach after calibration was done. Calibration is used to ensure the performance of the model using the observed pressure values. The output of the existing system shows pressure is very high means above the maximum pressure and velocity is very low at peak hour demand. The results of velocity and pressure before optimization have negative effect on the performance of the system. The number of pipes and junctions their velocities and pressures which were in admissible ranges are 15 and 42 pipes for velocities and zero and 59 junctions for pressure before and after optimization were evaluated respectively.

In an increasingly complex world there is a real, urgent need for methodologies to enable engineers to model complex sociotechnical systems, as these now seem to describe the majority of systems in use today. This is of course exacerbated by the increasing involvement and augmentation with “black box” AI contributions. Hollnagel produced a methodology, (FRAM) which did allow the analyst in-sights into these systems’ behaviour, but the model-based system engineering applications demand numbers and a quantitative ap-proach. In the last 10 years, this original approach developed to model systems as sets of interactive, interdependent “functions”, (abstracted from agent or component details), has been further developed to the point where it can take the basic data and structures from the current component focussed system engineering “models”, and can pull it all together into dynamic models, (as opposed to static, fixed System Theoretic Process Accimaps), from which analysts can discern how they really work in practice, and predict the emergent behaviours characteristic of complex systems. This paper describes how the FRAM methodology has now been extended to provide these extra, essential attributes. It also describes its implementation using an open-source software, freely available for use and verification on the GitHub site.

There are different ways to analyse energy absorbance (EA) in the human auditory system. In previous research, we developed a complete finite element model (FEM) of the human auditory system. In this mentioned work, the external auditory canal (EAC), middle ear, and inner ear (spiral cochlea, vestibule, and semi-circular canals) were modelled based on human temporal bone histological sections. Multiple acoustic, structure and fluid-coupled analyses were conducted using the FEM to perform harmonic analyses in the 0.1–10 kHz range. Once the FEM had been validated with published experimental data, the FEM numerical results were used to calculate the EA or energy reflected (ER) by the tympanic membrane. This EA was also measured in clinical audiology tests which were used as a diagnostic parameter. A mathematical approach was developed to calculate the EA and ER, with numerical and experimental results showing adequate correlation up to 1 kHz. Another published FEM had adapted its boundary conditions to replicate experimental results. Here, we recalculated those numerical results by applying the natural boundary conditions of human hearing and found that the results almost totally agreed with our FEM. This boundary problem is frequent and problematic in experimental hearing test protocols: the more invasive they are, the more the results are affected. One of the main objectives of using FEMs is to explore how the experimental test conditions influence the results. Further work will still be required to uncover the relationship between the middle ear structure and EA to clarify how to best use FEMs. Moreover, the FEM boundary conditions must be more representative in future work to ensure their adequate interpretation.

The Woka-Cuona rift zone, situated in the easternmost portion of southern Tibet, displays complex geological conditions. It consists of three distinct grabens or half grabens, spanning the Himalayan and Gangdese terranes from south to north. Examining the distribution patterns and genetic mechanism of the geothermal system in the Woka-Cuona rift zone holds significant guidance for studying the genetic mechanisms of geothermal systems and the production and utilization of ge-othermal resources in the rift zones of southern Tibet. Based on the geological conditions of the study area, the mechanism of rift formation and the distribution characteristics of geothermal water in the three distinct grabens were analyzed through data collection, ground surveys, geochemical analysis, and isotope analysis. Alongside topographic, drainage, and structural features, the Woka-Cuona rift zone was subdivided into four zones from north to south - Woka, Qiongduojiang, northern Cuona, and southern Cuona grabens. Additionally, the study investigated the geochemical char-acteristics, recharge sources, and water-rock interactions of geothermal water in different zones, providing a scientific foundation for subsequent geothermal energy production.

Microfluidic systems offer precise control over physiological, biochemical, and mechanical stimuli in cell culture, allowing in vitro emulation of tissue or tumor microenvironments. This study aims to advance our understanding of tumor biology and contribute to personalized therapy development. Overcoming challenges in cell culture, including cell density and microfluidic device properties, is essential for this purpose. We designed a microfluidic system to facilitate the interaction of diverse cell lineages, incorporating human brain microvascular endothelial cells (HBEC5i), glioblastoma multiforme cells (U87MG), and astrocytes (ScienceCells 1800). Post-fabrication, we assessed the system's functionality and systematically evaluated cell inoculation conditions. Photographic acquisitions comprehensively captured cell culture and their interactions. The device successfully enabled assessment of cellular proliferation, invasion, and migration, supporting the growth of monolayers and tumor organoids. Importantly, each channel demonstrated independence in study processes while allowing cellular intercommunication, both physically and biochemically. In conclusion, the functional microfluidic device facilitated the study of cell migration, tumor invasion, and organoid growth, faithfully replicating biological features observed in a tumor microenvironment. This research contributes to advancing our understanding of tumor biology for the development of personalized therapies.

This policy paper explores various strategies that would facilitate transitioning the traditional Jordanian electrical grid to a secure smart grid. It includes comprehensive recommendations from academia and industry for the regulatory and governmental sector in Jordan to achieve specific roadmap objectives. As Jordan is heavily dependent on fossil fuels, This policy paper also provides recommendations for incorporating more renewables into its energy mix, thereby facilitating a sustainable future. The proposed policies will emphasise the creation of an enabling environment where innovation, research, and development initiatives flourish, thereby promoting private sector engagement.

Water microbial contamination is a serious issue that poses a risk to both animal and human health. 120 water samples collected from main water source and drinkers from a poultry farm. Different bacterial pathogens were isolated from water sources. Escherichia (E.) coli, Pseudomonas (P.) aureoginosa, (Salmonella) S. Typhimurim, Aeromonas (A.) hydrophila at different percentages. Variable degree of bacterial resistance to some commercial disinfectants commonly used to disinfect water system (iodine, terminator and H2O2). Nanoparticles were used to control bacteria in water. About the safety investigation for the prepared nanomaterials, the work results demonstrated that zinc oxide (ZnO) nanoparticles (NPs) exhibit the highest safety profile among the manufactured materials. The median fatal dose (LD50) for ZnO NPs was determined to be 3709 mg/kg body weight. In comparison, the LD50 values for zeolites and nanocomposites were 3251 mg/kg and 2658 mg/kg, respectively. Therapeutic dosages were estimated based on the LD50. Zeolite NPs, ZnO NPs and ZnO/zeolite NPs showing promising results in control of those bacteria. It was concluded that the escalating resistance of bacteria to disinfectants have led to a need to find alternative such as nanoparticles that proved promising results in control of pathogens, particularly it showed a safe effect on laboratory animals.

Bacteria in the gut microbiome play an intrinsic part in immune activation, intestinal permeability, enteric reflex, and entero-endocrine signaling. Gut microbiota communicates with the central nervous system (CNS) through the production of bile acids, short-chain fatty acids (SCFAs), glutamate (Glu), γ-aminobutyric acid (GABA), dopamine (DA), norepinephrine (NE), serotonin (5-HT) and histamine. A vast number of signals generated in the gastrointestinal tract (GIT) reaches the brain via afferent fibers of the vagus nerve (VN). Signals from the CNS are returned to entero-epithelial cells (EES) via efferent VN fibers and communicate with 100 to 500 million neurons in the submucosa and myenteric plexus of the gut wall, which is referred to as the enteric nervous system (ENS). Intercommunications between the gut and CNS regulate mood, cognitive behavior, and neuropsychiatric disorders such as autism, depression, and schizophrenia. The modulation, development, and renewal of nerves in the ENS, and changes in the gut microbiome alter the synthesis and degradation of neurotransmitters, which ultimately influence our mental health. The more we decipher the gut microbiome and understand its effect on neurotransmission, the closer we may get to the developing of novel therapeutic and psychobiotic compounds to improve cognitive functions and prevent mental disorders. In this review, the intricate control of entero-endocrine signaling and immune responses that keep the gut microbiome in a balanced state, and the influence that changing gut bacteria have on neuropsychiatric disorders are discussed.

The ZX Spectrum was a popular 8-bit home computer by Sinclair Research in the 80s. Even though some of these computers may still work, the audio tapes, the TV with an analog tuner and the micro-switch joystick, used with the original ZX Spectrum, nowadays are outdated and hard to find in good working order or replicate. Since many other old closed systems are also very difficult to update to support modern peripherals, there is a necessity to provide a methodology to adapt such systems to support new peripherals while being compatible with existing software. The work proposed in this paper is focused on recreating a ZX Spectrum+/48k computer and interface it with modern peripherals on an FPGA. This is accomplished by adding a co-processor to assist with the control of the new peripherals which would either require to complex architectural changes to the original system and in the end it would perform poorly due to the low performance of the Z80 CPU. This work distances from previous ones on emulating a ZX Spectrum since it focuses on the use of different upgraded peripherals and the use of a NIOS II soft-processor as a co-processor to manage the SD Card accesses. A demonstration of the proposed modernized architecture was made by successfully running a diagnostics ROM and playing original ZX Spectrum games from an SD card for game with a PS/2 keyboard and a pair of joysticks.

In this paper, it is shown that the bivariate beta statistical manifold of the first kind with three parameters has a gradient system Hamiltonian and is completely integrable. It is shown that this system admits a Lax pair representation. The question here is how to construct a gradient system and show that it is completely integrable while determining the integrable curves on the three-parameter bivariate beta manifold of the first kind admitting a potential function?To do this, we prove the existence of the potential on the manifold using ovidiu in Ovidiu, then using Amari's theorems in Amari, we show that this coordinate system admits a dual coordinate system. This will allow us to determine the Riemannian metric on the variety and to construct the gradient system. We linearise this system using Nakamura's method. We prove that it is Hamiltonian and completely integrable using the theorem in \cite{mama-proceeding}. It is shown that the Bivariate Beta of the first kind with three parameters, is an exponential function. The gradient system is linearizable. It is proven that the associate gradient system is Hamiltonian with $ \mathcal{H} $ which is in involution and satisfying $d\mathcal{H}=0.$ Therefore, the gradient system obtained is a sub-dynamical system of a $4$-dimensional system and is a completely integrable system. We show that the gradient system on the statistical model has the following Lax pair representation: $ \dot{L}= \left[L, N\right] $ where $L$ is a symmetric matrix and $N$ is the diagonal matrix. The gradient system defined by the Bivariate Beta family of the first kind with three parameters odd-dimensional manifold is a completely integrable Hamiltonian system.

Synchronization is a prerequisite for the stability of electrical energy, which is the cornerstone of a functioning society. Identifying whether generators are synchronized or not has been attracting immense research interest. Utilizing synchronized stability boundaries can strongly simplify stability discrimination. However, fundamental issues such as determining accurate stability boundaries remain challenging. In this study, an accurate synchronized stability boundary equation that is independent of the system and disturbances is presented, and it is applicable to an arbitrarily coupled grid. The special structure induced by spontaneous synchronization appears to be only near the stability boundary. The results of this study show that: the synchronous stability boundary is an intrinsic property of the system, independent of its structure and parameters. Synchronization on the network may be independent of the network. These conclusions will challenge the traditional perception of synchronization on networks, and the synchronization stability of the grid can be analyzed in a uniform way.

The COVID-19 pandemic has emphasized the crucial role of ventilation systems in mitigating cross-infections, especially in infectious disease hospitals. This study introduces a dual-design operation ventilation system that can operate under two sets of ventilation conditions for normal and epidemic times. A challenge is optimizing duct diameters for required airflow while maintaining hydraulic balance. We design a genetic algorithm with adaptive penalty factor, the velocity constraint and the improved crossover and mutation probability. The improved genetic algorithm is suitable for ventilation system networks, which can find a better air duct diameters combination to improve the hydraulic balance rate, and reduce the usage of air valves, resulting in efficient hydraulic balancing commissioning. Compared with the traditional genetic algorithm, it has a faster search speed and a better global search ability, which is effective for the optimal design of ventilation system networks.

The plant water status is crucial for growth and production, but the current climate change scenario makes it challenging to match the water plant demand. Blueberry is an economically important crop and plays an acknowledged role in human health due to its antioxidant compounds. This research aimed to determine whether exogenous methyl jasmonate application improves the antioxidant defense mechanisms for protecting the photosynthetic performance in blueberry plants under the stress condition of water deficit. A greenhouse experiment was carried out under a 16-h light period; 20ºC; and 60-80% relative humidity for 2 weeks before treatment application of methyl jasmonate (MeJA) to blueberry plants (Vaccinium corymbosum, Brigitta cultivar). The following treatments were maintained for 7-days: (i) 80% field capacity (NoWD); (ii) 80% field capacity plus MeJA application (NoWD + MeJA); (iii) 20% field capacity (WD); and (iv) 20% field capacity plus MeJA application (WD + MeJA). The MeJA was sprayed as an aqueous solution of 10 µM MeJA (Sigma-Aldrich) over the plant's foliar system. At the end of the assay; blueberry leaves were analyzed for the relative water content; specific leaf area; lipid peroxidation; total antioxidant activity; total phenols; total anthocyanins; anthocyanidin compounds and photosynthetic performance. Brigitta cultivar showed a significant decrease in the oxidative stress at leaf levels; with an increase in antioxidant activity; phenolic compounds; total anthocyanins; delphinidin; petunidin; antheraxanthin; zeaxanthin; and an improvement in photosynthetic performance parameters. Blueberry Brigitta cultivar was shown to be susceptible to WD decreased mainly photosynthesis. However; the MeJA application on leaves induced metabolic changes; through an increase of antioxidant strategy within the plant to counteract the negative effects of WD; protecting the photosynthetic apparatus; which allows the Brigitta cultivar to withstand the period of WD.

Purpose: Glue inhalation is a common unconventional substance of abuse and it contains neurotoxic and volatile solvents. We examined the toxicity profile and CNS activities of glue inhalation in Wistar rats.Methods: Acute toxicity was investigated using graded concentrations of 0.5, 1, and 2 mL of glue inhalation (n=3/group) for 4 hours in phase one followed by concentrations of 5, 10, and 20 mL of glue (n=1/group) for 4 hours in phase two. These animals were then observed for signs of toxicity and/or mortality for 24hours. The sub-acute toxicity was studied using 24 male Wistar rats at graded concentrations of Air, 2, 4 and 8mL glue (n=6/group) for 28 days. Blood samples were collected for biochemical and haematological evaluations, and vital organs (lung, liver, kidney, heart, brain, and eye) were used for histological analysis. Behavioural studies were carried out using Elevated Plus Maze, Hole Board Test, Open Field Test, Tail Suspension Test and Forced Swim Test. Dependence and abstinence effect were also evaluated. Results: The Lethal Dose (LD₅₀) of the inhalational glue was 14.14 ml. Glue significantly increased liver function parameters like TB, DB, ALP, ALT, TP, electrolyte levels (K⁺ and HCO₃) but reduced cholesterol level in exposed rats. Glue inhalation had significant anxiolytic and depressant effects on the rats at concentrations of 4mL and 8mL. Histological analysis revealed liver and lung tissue abnormalities and subconjunctival inflammation in eye tissue at 8mL. Conclusion: The study therefore suggests that glue inhalation has anxiolytic and depressant effects in Wistar rats.

This study is focused on an optimal sizing method based on genetic algorithms (GA) in order to design a high-performance photovoltaic system that would be installed in the Alioune Diop University of Bambey, Senegal. The multi-objective optimization allowed us to find a better trade- off between the Total Life Cycle cost (TLCC) and the Loss of Power Supply Probability (LPSP). The goal is to minimize the TLCC while maintaining a good satisfactory of the system with a desired LPSP, under certain constraints. The expressions of the TLCC and the LPSP are established according to the total photovoltaic energy and the battery capacity. The toolbox of Matlab software is used to implement the optimization problem with twelve blocks of the site and its different corresponding loads. The obtained results have led to a several combinations of the photovoltaic and battery capacities of which the best one is selected based on the lowest LPSP, that guaranteed a better load coverage during the night. The results of this proposed method are compared with intuitive method that has been firstly applied. For the block with the lowest load demand, the proposed optimization model leads to a reduction a reduction of 70% and 48% in the storage capacity and the TLCC respectively for a LPSP of 0.007 %.

The inherent non-smoothness of vibroimpact system leads to complex behaviors as well as strong sensitive dependence on parameter changes. Unfortunately, uncertainties and errors in system parameters are inevitable in mechanical engineering. Therefore, the investigations of dynamical behaviors for vibroimpact systems with stochastic parameters are highly essential. The present study aims to analyze the dynamical characteristics of the three-degree-of-freedom vibroimpact system with an uncertain parameter by means of the Chebyshev polynomial approximation method. Specifically, the vibroimpact system model considered is one with unilateral constraint. Firstly, the three-degree-of-freedom vibroimpact system with an uncertain parameter is transformed into an equivalent deterministic form by the Chebyshev orthogonal approximation. Then, the ensemble means responses of the stochastic vibroimpact system are derived. Numerical simulations are performed to verify the effectiveness of the approximation method. Furthermore, the periodic and chaos motions under different system parameters are investigated, and the bifurcations of the vibroimpact system are analyzed by the Poincaré map. The results demonstrate that both the restitution coefficient and the random factor can induce the appearance of the periodic bifurcation. It is worth noting that the bifurcations fundamentally differ between the stochastic and deterministic systems. The former has a bifurcation interval, while the latter occurs at a critical point.

The article is devoted to the issues of assessing the impact of changes in the delay value in the feed direction, what determines the regenerative nature of self-excitation of the cutting system, on the dynamics of metal processing on metal-cutting machines. It is this interconnected model of the cutting system that allows to identify the main dynamic effects that occur in the cutting system, including the effect of vibrations regeneration when cutting along the track. The article also has a section dedicated to the experiment on a real metalworking machine, on which vibrations of the top of the cutting wedge of the tool were measured and based on these data, a real calculation of the delay time and the magnitude of the change in the area of the cut layer was carried out, due to variations in the real feed. The conducted studies have shown that in addition to the vibrations of the cutting tool in the direction of feeding, the vibration activity of the tool in the direction of cutting plays an essential role in ensuring the regenerative effect. The delay time constant of the operator is formed, which determines the real value of the feed during cutting.

This work deals with the synthesis of bare and curcumin (CUR)-loaded chitosan (CS)-based macroparticles by ionic gelation using sodium hydroxide (NaOH) or sodium tripolyphosphate (TPP) as cross-linking agents. The resulting spherical-shaped macroparticles were studied using various characterization techniques, Scanning Electron Microscopy (SEM), Fourier Transformed Infrared Spectroscopy (FTIR), Thermogravimetric Analysis (TGA), and Differential Scanning Calorimetry (DSC). The release of CUR from the CS-based particles with respect to time was analyzed, and the encapsulation efficiency and degree of swelling were studied. All formulations showed excellent CUR trapping efficiency, exceeding 90%. In particular, the TPP-crosslinked macrobeads released 34 wt% of the charged CUR within minutes, while the remaining 66 wt% was released slowly due to the biodegradation of CS. The results indicate that the correct choice of gelling agent and its concentration leads to spherical particles capable of encapsulating CUR and releasing it in a wide range of kinetics depending on the specific application.

The general desire of the world's population is to eat as healthily as possible, an aspect that has a direct impact on the technological complex aimed at animals raising (proper breeding systems, microclimate factors with implications for the welfare of animals, etc.), as well as on the quality of the finished products that will enter the food supply. Therefore, the authors set out to study how the growth system influences the health status of rainbow trout raised in different systems. The observed experimental factors did not undergo significant changes. However, differences were generated by the applied growth system. For the amount of glucose in the blood, no statistically significant differences were identified between the groups. In contrast, comparison of the amount of glycogen led to obtaining very distinctly significant statistical fluctuations (the mean for P-si was 2.314±0.638 and for P-i 1.980±0.822). Growth hormone varied between 0.504±0.46 in the case of P-si and 0.694±0.22 ng/ml for P-i. The values obtained for cortisol showed a significant influence of stress factors on the studied trout. The general conclusion of the present study is that various technological factors influence the health status of livestock.

A comprehensive review on symmetry and conditional symmetry is made from the core conception of symmetry and conditional symmetry. For a dynamical system, the structure of symmetry means its robustness against the polarity change of some of the system variables. Symmetric systems typically show symmetrical dynamics and even when the symmetry is broken, symmetric pairs of coexisting attractors are born annotating the symmetry in another way. The polarity balance can be recovered by the combinations of the polarity reverse of system variables, and furthermore, it can also be restored by the offset boosting of some of the system variables if the variables lead to the polarity reverse from their functions. In this case, conditional symmetry is constructed giving a chance for a dynamical system outputting coexisting attractors. Symmetric strange attractors typically represent the flexible polarity reverse of some of the system variables, which brings more alternatives of chaotic signal and more convenience for chaos application. Symmetric and conditionally symmetric coexisting attractors can also be found in memristive systems and circuits. Therefore, symmetric chaotic system and those of conditional symmetry provide sufficient system options for chao-based applications.

ABSTRACT: The idea of a Common Mucosal Immune system (CMS) is 50 years old. Its relevance to immune protection at mucosal sites and its potential to modulate the impact of vaccination-induced protection against infection of the airway, has been poorly understood. The consequent failure of current SARS-CoV-2 vaccination to satisfy expectations with respect to prevention of infection, viral transmission, duration of protection and pattern of clinical protection, led to public health and medical decisions now under review. This review summarises knowledge of the CMS in man, including the powerful role it plays in immune protection and lessons with respect to what can and can not be achieved by systemic and mucosal vaccination for prevention of airway infection. The powerful impact in both health and disease of optimising delivery of immune protection using selected isolates from the respiratory microbiome, is demonstrated through review of randomised controlled trials (RCT’s) in subjects with chronic airway disease, and in otherwise healthy individuals with risk factors, in whom the idea of mucosal immune resilience is introduced.

Heart is composed of muscle cells called cardiomyocytes, including a specialized population, named pacemaker cells, that form the Cardiac Conduction System (CCS), responsible for generating the action potential dictating heart contractions. Failure of the CCS system leads to cardiac arrhythmias requiring complicated therapies and often surgical implantation of electrical pacemakers. However, recent research focusses on development of novel therapies using biological pacemakers aiming to substitute electrical devices. While most signalling pathways and transcription factors involved in the development of the pacemaker cells are known, the upstream regulatory networks need to be predicted through computer-based databases, mathematical modelling as well as functional testing of the regulatory elements in vivo, indicating the need for further research. Here we summarise the current knowledge about the vertebrate myocardial CCS system and development of the pacemaker cells and emphasise areas of future research to clarify the regulation of muscle pacemaker cells and ease development of biological therapies.

Phase change materials (PCMs) have emerged as promising solutions for latent heat thermal energy storage (LHTES) systems, offering considerable potential for storing energy derived from renewable sources across various engineering applications. The present study focused on optimization of solar cooling system by integrating LHTES with different PCM tank configuration. TRNSYS simulation software was selected for the study and collected experimental data from laboratory system prototype was used for system validation. The results indicate that the use of PCM led to a noteworthy decrease of 6.2% in auxiliary energy consumption. Furthermore, the duration during which the heat carrier temperature flow exceeded 90°C from the storage tank to the auxiliary heater was extended by 27.8% when PCM was utilized, compared to its absence. The use of PCM in LHTES is more effective under variable weather conditions. On the day when changes in weather conditions were observed, around 98% of the cooling load was provided by produced sun energy. The results of the research can be used to optimize the solar cooling system, which will help reduce the environmental impact of cooling systems running on non-renewable fuels.

This chapter aims to construct a relatively complete, universal, and highly reliable road surface state monitoring and perception system through the research of the A1 contact road reconstruction project of an international airport (hereinafter referred to as the “airport”). The system design is based on on-the-spot investigation, theoretical analysis, and engineering practice, using vibrating string type and resistive strain sensors as sensing means, real-time high-frequency signal acquisition technology as the guide, 4G router for wireless communication technology as the media, and storage technology for monitoring system based on server storage terminals. In combination with engineering background, aircraft motion state, main landing gear configuration, sensor selection and evaluation, and other major factors, the actual monitoring information needs of the plane are fully taken into account, as well as the difference in sensor information types, and the system design is carried out by stratification and classification.

More people around the world now have obesity than suffer from starvation thanks to our modern food system. Agriculture was transformed over the 20^th century by a variety of technological advancements that relied heavily on fossil fuels. In the United States of America, government policies and economic incentives led to surplus production of cheap inputs to processed food industries that produced a wide variety of heavily marketed, convenient, rewarding, timesaving, and relatively inexpensive ultra-processed foods. The energy available in the United States food supply increased much more than population needs, albeit with large inequities in food distribution and nutrition security. While most of the rise in per capita food availability during the late 20^th and early 21^st centuries in the United States resulted in increased food waste, a variety of mechanisms have been proposed by which changes in the increasingly ultra-processed food environment resulted in excess energy intake disproportionately in people genetically susceptible to obesity. As populations continue to grow, substantial investments in coordinated nutrition and agricultural research are needed to transform our current food system to one that relies less on fossil fuels, preserves biodiversity, ensures environmental health, and provides equitable access to affordable, safe, and nutritious food that reduces the prevalence of chronic diseases like obesity.

In this work, we propose a self-supervised multi-agent system that meets the online learning of clustering tasks for video behavior recognition spatio-temporal tasks. Encoding visual behavioral actions as discrete temporal sequence(DTS). Real-time clustering recognition task in a multi-agent system for continuous model building, training, and correction. Finally, we implemented a fully decentralized multi-agent system and completed its feasibility verification in a surveillance video application scenario on vehicle path clustering.

Smart mechatronics system in agriculture can be traced back to the mid-1980s, when research into automated fruit harvesting systems began in Japan, Europe, and the United States. Since then, impressive advances have been made smart mechatronics systems. Furthermore, smart mechatronics systems are promising areas, as results, we were intrigued to learn more about them. Consequently, the purpose of this study was to examine the smart mechatronic systems that have been applied to agricultural areas so far, with inspiration from smart mechatronic system in other sectors. To get an overview of the current state of the art, benefits and drawbacks of the smart mechatronics systems, various approaches were investigated. Moreover, smart mechatronic modules, and various networks applied in agriculture processing were examined. Finally, we were explored how the data retrieved using the one-way analysis of variance related to each other. The result showed that there were strong related keywords for different journals. The virtually limited use of sophisticated mechatronics in the agricultural industry, and at the same time, the low production rate, the demand for food security has fallen dramatically. Therefore, the application of smart mechatronics system in agricultural sectors would be taken into consideration in order to overcome these issues.

The choice of parameters for laser beams used in the treatment of musculoskeletal diseases is of great importance. First, to reach high penetration depths into biological tissue and, secondly, to achieve the required effects on a molecular level. The penetration depth depends on the wavelength since there are multiple light-absorbing and scattering molecules in tissue with different absorption spectra. The present study is the first comparing the penetration depth of 1064 nm laser light with light of a smaller wavelength (905 nm) using high-fidelity laser measurement technology. Penetration depths in two types of tissue (porcine skin and bovine muscle) were investigated. The transmittance of 1064 nm light through both tissue types was consistently higher than of 905 nm light. The largest differences (up to 5.9%) were seen in the upper 10 mm of tissue, while the difference vanished with increasing tissue thickness. The higher penetration was most likely due to a combination of lower absorption in hemoglobin and less scattering at larger wavelengths, and not due to absorption in melanin. Overall, differences in penetration depth were comparably small and high peak power and short pulse lengths of laser light seem to be more important to efficiently treat deep musculoskeletal diseases.

A progressive and chronic neurological condition called MSA (Multiple System Atrophy) is characterized clinically by varying degrees of dysautonomia, cerebellar ataxia, and parkinsonism. The concept of mitochondrial dysregulation in MSA is one perspective in handling this neurodegenerative disease. Damage to functional mitochondria is driven by the presence of ɑ-Synuclein-induced mitochondrial localization. The goal of MSA treatment up until now has been to reduce symptoms. One of the innovations in the treatment of MSA could be the novel idea based on mitochondrial reprogramming pathways. Mitochondrial reprogramming can be done in various ways in which the use of hydrogen, magnesium and low-dose hydrogen peroxide.

Soil erosion is one of the biggest problems in the agricultural sector that can affect ecosystems and human societies. A field of 50 slope was selected to study the runoff, soil and nutrients’ loss as well as crop productivity in different treatments (conventional tillage (CT) vs. no-tillage (NT), plant vs. no plant cover, contour cultivation (CC) vs. perpendicular to the contour cultivation, (PC) under natural rainfall. The experiment was conducted in central Greece in two cultivation periods. In autumn, the field was cultivated with intercropping Triticosecale and Pisum sativum and in spring with Sunflower. The total rainfall was 141.4 mm in the 1st year and 311 mm in the 2nd. We found that runoff in the treatment of no tillage with contour cultivation was 85% lower in both years compared to the no tillage-no plant control. Therefore, the contour cultivation-no tillage treatment had a positively effect in decreasing phosphorus and potassium concentrations lost from soil: indeed, there was a decrease by 55% and 62% in P and K, respectively, in the NT compared to the CC treatments. We conclude that the NT-CC treatment with plant cover was the most effective in reducing water runoff, soil nutrients’ loss and increasing yield.

Morinda citrifolia (noni) fruit juice has the potential to influence immune system function. This review discusses results from several human and animal studies that provide insight into the potential mechanisms of action by which noni juice exerts its immunomodulatory effects. Increased natural killer cell activity is a likely a major contributor to the improved health outcomes and increased survival times described in case reports and as observed in LLC and S180 tumor bearing mice. Increased interferon-gamma (IFN-γ) production is also an important mechanism of action through which noni improves immune function. IFN-γ promotes natural killer cell activity and phagocytosis, activities both seen in human and bovine studies as well as in rodents. Noni promotes regulatory cytokine expression, such as IL-2 which stimulates CD4+ T cell differentiation. Noni juice appears to influence this process via kinase 1/2 (ERK1/2) protein kinase B (Akt) and nuclear factor-kappa-beta signaling. As oxidative status is known to influence immune function, this review also discusses the notable antioxidant properties of noni juice that have been demonstrated in human trials.

6G is already being planned and will employ much higher frequencies, leading to a revolutionary era in communication between people as well as things. It is well known that weather, especially rain, can cause increased attenuation of signal transmission for higher frequencies. The standard methods for evaluating the effect of rain on symbol error rate are based on long-term averaging. These methods are an inaccurate, which results with an inefficient system design. This is critical regarding bandwidth scarcity and energy consumption and requires a more significant margin of effort to cope with the imprecision. Recently we have developed a new and more precise method for calculating communication system performance in case of rain, using the probability density function of rain rate. For high rain rate (above 10mm/hr), for a typical set of parameters, our method shows the symbol error rate in this range to be higher by orders of magnitude than that found by ITU standard methods. Our model also indicates that sensing and measuring the rain rate probability is important in order to provide the required bit error rate to the users. To the best knowledge of the authors, this novel analysis is unique. It can constitute a more effi-cient performance metric for the new era of 6G communication and prevent disruption due to incorrect system design. Keywords: atmospheric propagation, communication system performance, attenuation, com-munication

In today’s Web 2.0 era, online social media has become an integral part of our lives. In the course of the information revolution, the form of information has undergone a radical change, from simple text information to today’s integrated video, image, text and audio, and there has also been a great change in the way of dissemination and access, as people nowadays do not just rely on traditional media to passively receive information, but more actively and selectively obtain information from social media. Therefore, it has become a great challenge for us to effectively utilize these massive and integrated multi-modal media information to form an effective system of retrieval, browsing, analysis and usage. Unlike movies and traditional long-form video content, micro-videos are usually short in length, between a few seconds and tens of seconds, which allows users to quickly browse different contents and make full use of the fragmented time in their lives, while users can also share their micro-videos to their friends or the public, forming a unique social way. Video contains rich multimodal information, and fusing information from multiple modalities in a video recommendation task can improve the accuracy of the video recommendation task.According to the micro-video recommendation task, a new combinatorial network model is proposed to combine the discrete features of each modality into the overall features of various modalities through the network, and then fuse the various modal features to obtain the overall video features, which will be used for recommendation. In order to verify the effectiveness of the algorithm proposed in this paper, experiments are conducted in the public dataset, and it is shown the effectiveness of our model.

This study identified high-risk locations (hotspots), using geographic information systems (GIS) and spatial analysis. Five years of accident data (2013-2017) for the Lokoja-Abuja-Kaduna highway in Nigeria were used. Accident concentration analysis was carried out using the mean center analysis and Kernel density estimation method. These locations were further verified using Moran’s I Statistics (Spatial Autocorrelation) to determine their clustering with statistical significance. Fishnet polygon and Network spatial weight matrix approaches of Getis-Ord Gi* statistic for hotspot analysis were used for the hotspot analysis. Hotspots exist for 2013, 2014, and 2017 with a significance level between 95% - 99%. However, no hotspots exist for 2014 and 2015 since the pattern is random. The spatial autocorrelation analysis of the overall accident locations with a z-score = 0.0575, p-value = 0.9542, and Moran's I statistic = -0.0089 showed that the distribution of accidents on the study route is random. Thus, preventive measures for hotspot locations should be based on a yearly hotspot analysis. The average daily traffic values of 31,270 and 16,303 were obtained for the Northbound and Southbound directions of the Abaji-Abuja section. The results show that hotspot locations with high confidence levels are at points where there are geometric features.

Blockchain and Machine Learning gives the best solutions together in performing various tasks in the Smart Health care system. With these two new emerging technologies, that have materialized in the last decade. In this paper, we proposed secure, transparent and intelligent methods in the Internate of medical things industry using Machine learning models and blockchain technology to enhance security level and train our models to improve diagnostic, prevention, treatment of the patient, patient rights, patient autonomy and equality in the health care system.

Long-term changes in nanoparticles of copper-silver bimetallic systems on natural clinoptilolite obtained by ion exchange of Cu2+ and Ag+, and then reduced at different temperatures, have been studied. Even after storage under ambient conditions, XRD and UV-Vis diffuse reflectance spectra indicate the presence of nanospecies of reduced copper and silver. Scanning Electron Microscopy of aged bimetallic samples, reduced at the highest temperature (450oC) and the primary samples for their preparation, also aged, showed the presence of silver nanoparticles with a size of about 100 nm. They are formed in the initial ion-exchanged sample (without reduction) due to the degradation of Ag+ ions. The nanoparticles in the reduced sample are larger; in both samples they are evenly distributed over the surface. The presence of silver affects the stability and the mechanism of decomposition/oxidation of reduced copper nanospecies, and this stability is higher in bimetallic systems. The decomposition pattern of recently reduced species includes the formation of smaller nanoparticles and few-atomic clusters. This can occur, preceding the complete oxidation of Cu to ions. Quasi-colloidal silver, which is present in fresh bimetallic samples reduced at lower temperatures, transforms after aging into Ag8 clusters, which indicates the stability of these nanospecies on natural clinoptilolite.

An increasing amount of evidence indicates the critical role of the cutaneous nervous system in the initiation and maintenance of psoriatic skin lesions by neurogenic inflammation. However, molecular mechanisms affecting cutaneous neurons are largely uncharacterized. Therefore, we reanalyzed a psoriatic RNA sequencing dataset from published transcriptome experiments of nearly 300 individuals. Using the Ingenuity Pathway Analysis software, we associated several hundreds of differentially expressed transcripts (DETs) to nervous system development and functions. Since neuronal projections were previously reported to be affected in psoriasis, we performed an in-depth analysis of neurite formation-related processed. Our in silico analysis suggests that SEMA-PLXN and ROBO-DCC-UNC5 regulating axonal growth and repulsion are differentially affected in non-lesional and lesional skin samples. We identified opposing expressional alterations in secreted ligands for axonal guidance signaling (RTN4/NOGOA, NTNs, SEMAs, SLITs) and non-conventional axon guidance regulating ligands, including WNT5A and their receptors, modulating axon formation. These differences in neuritogenesis may explain the abnormal cutaneous nerve filament formation described in psoriatic skin. The processes also influence T cell activation and infiltration, thus highlighting an additional angle of the crosstalk between the cutaneous nervous system and the immune responses in psoriasis pathogenesis, in addition to the known neurogenic pro-inflammatory mediators.

The objectives of this paper are to analyze the urban growth and urbanization phenomenon in Algeria. Two processes that originated respectively by the expansion of existing urban areas and the process of urbanization that took place between 1954 and 2008, a period marked by significant economic, social and political changes in Algerian society. Our analysis was mainly based on the Algerian general census of population and habitat (2008) and on the application of rank-size distribution of cities according to Zipf’s rule. This study revealed that in Algeria, the urban system is particularly marked by the dramatic expansion of small cities. Indeed, the development of small towns, through the transition from rural to urban and the residential loosening of large cities have influenced the trend towards the balance of the urban system in Algeria. Results revealed also how the "primatial" city is undergoing profound economic and social changes at the national level. These changes are most often imposed from the top as part of land-use planning policy. This study provides some insights into the demographic dynamics of cities and the evolution of urban hierarchies in Algeria, through the comparison of the different rank-size distributions of Algerian cities in space and time. Our results suggest that land-use planning strategies are the only policies capable of influencing the future of the Algerian urban system.

Radio communication system in an underground mine is one of the very essential systems for the underground mine. It is required that the radio communication system must be reliable from the starting to construct the underground mine to the closure of the mine. However, underground mine radio communication systems reliability is required to be tested on an active radio communication system in a real environment. In the study was suggested a new research methodology that is studied reliability using dynamic system modeling on Vensim software instead of traditional method to study the reliability of radio communication systems calculating large-scale differential equations. In other words, we suggest a new research methodology. The Motorola Dimetra (TETRA) radio communication system's availability readiness information was used to simulate the reliability of the underground mine radio communication system probability of reliability using Vensim software for system dynamic modeling.Also, the factors that affect the reliability of underground mining radio communication systems was studied. The study was determined factors that affect the underground mine radio communication system from the following risks. The study was in the examples of the Oyu Tolgoi underground mine. The factors that affect the reliable operation of the underground mine radio communication system were determined using the failure statistics of TETRA radio communication system in the Oyu Tolgoi mine in 2015-2018.

Sphingolipids are lipids derived from an 18-carbons unsaturated amino alcohol, the sphingosine. Ceramide, sphingomyelins, sphingosine-1-phosphates, gangliosides and globosides, are part of this group of lipids that participate in important cellular roles such as structural part of plasmatic and organelle membranes maintaining their function and integrity, cell signaling response, cell growth, cell cycle, cell death, inflammation, cell migration and differentiation, autophagy, angiogenesis, immune system. The metabolism of these lipids involves a broad and complex network of reactions that convert one lipid into others through different specialized enzymes. Impairment of sphingolipids metabolism has been associated with several disorders, from several lysosomal storage diseases, known as sphingolipidoses, to polygenic diseases such as diabetes and Parkinson and Alzheimer diseases. Sphingolipids are mainly located in central nervous system, and their abundance and distribution depend on brain development state and cell type. Although several studies have expanded the knowledge about sphingolipids function both in health and disease, it is still necessary to continue their study to understand the cellular implications of novel sphingolipids. These studies will also contribute to the diagnosis and treatment of diseases in which these molecules are part of their pathophysiology. In this review, we summarize the main sphingolipid characteristics and current knowledge about the synthesis, catabolism, regulatory pathways, participation in action potential and ionic channels, among other relevant functions.

We propose a novel electrochemical system to form precipitation patterns of Cu-Fe-based Prussian blue analogues (Cu-Fe PBA) in agarose gels, using an applied voltage to produce reactant ions. The spatiotemporal evolution, spatial distribution, and crystallite morphologies of the precipitates were investigated by visual inspection, Fe Kα intensity distribution measurements, and optical and scanning electron microscope observations. The precipitation patterns and their evolution depended on the applied voltage. Multicolored periodic precipitation bands were stochastically formed under cyclic alternating voltage (4 V for 1 h and then 1 V for 4 h per cycle). The distances between adjacent bands were randomly distributed (0.30 ± 0.25 mm). The sizes and shapes of the crystallites generated in the gel were position-dependent. Almost cubic but fairly irregular crystallites (0.1–0.8 μm) were formed in the periodic bands, whereas definitely cube-shaped crystallites (1–3 μm) appeared close to the anode. These cube-like reddish-brown crystallites were assigned to Cu-FeII PBA. In some periodic bands, plate-like blue crystallites (assigned to Cu(OH)2) were also present. Future issues for applications of the observed periodic banding were discussed.

This paper addresses a wildlife monitoring problem using a team of UAVs for efficient monitoring of wildlife. The state-of-the-art technology using UAVs has been an increasingly popular tool to monitor wildlife compared to the traditional methods such as satellite imagery-based sensing or GPS trackers. However, there still exist unsolved problems as to how the UAVs need to cover a spacious domain to detect animals as many as possible. In this paper, we propose the optimal transport-based wildlife monitoring strategy for a multi-UAV system, to prioritize monitoring areas while incorporating complementary information such as GPS trackers and satellite-based sensing. Through the proposed scheme, the UAVs can explore the large-size domain effectively and collaboratively with a given priority. The time-varying nature of wildlife due to their movements is modeled as a stochastic process, which is included in the proposed work to reflect the spatio-temporal evolution of their position estimation. In this way, the proposed monitoring plan can lead to efficient wildlife monitoring with a high detection rate. Various simulation results including statistical data are provided to validate the proposed work.

Proposed article deals with analyses on trends of problem-solving robotic applications in manu-facturing, especially in transportations and manipulations. Intelligent agent-based manufacturing systems with robotic agents are observed. Intelligent core of such units must be able to propose the plan of problem-solving in form of strategy. The logical model of adaptive strategies planning for intelligent robotic system is described in form of predicates with presentation of data processing on base of set theory descriptions. Dynamic structure of workspace and possible change of goals are considered as reasons for functional strategies adaptation. Proposed formal descriptions are sup-ported by model of mobile robotic platform, acting in warehouse.

After the occurrence of a hydrogen fluoride leakage accident that triggered massive losses in Gumi, South Korea in 2012, the government and companies have been interested in installing mitigation systems to minimize the loss of a leakage accident. What lacks in previous researches studying mitigation systems is an evaluation of how much a mitigation system can reduce the impact of accidents. Therefore, modeling-based simulations of mitigation systems should be urgently developed to analysis of the performance of a mitigation system. This study aims to design a mitigation system to handle a leakage accident of a storage tank and determine its design specifications through the use of modeling. The basic concept is that when leakage occurs, leakage material in a dike is drained to a remote impoundment installed under the ground, while the material in the storage vessel is transferred to a reserve tank by a pump at the same time. To evaluate the efficacy of this system. hydrogen fluoride and benzene storage vessels are tested. The simulation results indicate that the proposed mitigation system can contribute to the reduction in the dispersion area for the materials as well as a large reduction in the leakage material.

Cancer-associated fibroblasts (CAF) form the basis of tumor microenvironment and possess immunomodulatory functions by interacting with other cells surrounding tumor, including T lymphocytes, macrophages, dendritic cells and natural killer cells. Ionizing radiation is a broadly-used method in radiotherapy to target tumors. In mammalian cells, ionizing radiation induces various types of DNA damages and DNA damage response. Being unspecific, radiotherapy affects all the cells in tumor microenvironment, including the tumor itself, CAFs and immune cells. CAFs are extremely radio-resistant and do not initiate apoptosis even at high doses of radiation. However, following radiation, CAFs become senescent and produce a distinct combination of immunoregulatory molecules. Radiosensitivity of immune cells varies depending on the cell type due to inefficient DNA repair in, for example, monocytes and granulocytes. In this minireview, we are summarizing recent findings on the interaction between CAF, ionizing radiation and immune cells in the tumor microenvironment.

This paper describes the development of a controller that enables trajectory control and vibration control. The controller performance was verified the using a 3D 2-link, flexible manipulator. On trajectory control using inverse kinematics, it was confirmed that the deflection due to its own weight deteriorated the track following performance. The vibration component of the resonance frequency of the flexible manipulator was generated, and the tip position accuracy is deteriorated. Using the results of control experiments based on the inverse kinematics, the system is identified and then created an inverse system for simultaneous control of trajectory control and vibration control. The target trajectories were the three joint angles. Finally, it was demonstrated through experiments on actual manipulator, that the system could sufficiently follow the ideal trajectory and suppress link vibrations.

In the field of machine learning, cluster analysis has always been a very important technology for determining useful or implicit characteristics in the data. However, the current mainstream cluster analysis algorithms require comprehensive analysis of the overall data to obtain the best parameters in the algorithm. As a result, handling large-scale datasets would be difficult. This research proposes a distributed related clustering mechanism for Unsupervised Learning, which assumes that if adjacent data are similar, a group can be formed by relating to more data points. Therefore, when processing data, large-scale datasets can be distributed to multiple computers, and the correlation of any two datasets in each computer can be calculated simultaneously. Later, results are processed through aggregation and filtering before assembled into groups. This method would greatly reduce the pre-processing and execution time of the dataset; in practical application, it only needs to focus on how the relevance of the data is designed. In addition, the experimental results show the accuracy, applicability, and ease of use of this method.

The immune system is a dynamic network of cells and cytokines are the major mediators of immune responses which combat pathogens. Based on the cytokine production, effector T cells differentiate into subsets known as Th1, Th2, Th17 or Treg (T regulatory). This system serves as a barrier to intracellular pathogens, bacterial infections and stimulates the production of reactive oxygen species (ROS), reactive nitrogen intermediates (RNI) and nitric oxide (NO), which diffuses across membranes and engulfs intracellular pathogens. Oxidative stress occurs when ROS, reactive nitrogen species (RNS) production and antioxidant defences become imbalanced. Oxidative stress generated by infected cells produces a substantial amount of free radicals which enables killing of intracellular pathogens. Intracellular pathogens are exposed to endogenous ROS as part of normal aerobic respiration, also aexogenous ROS and RNS are generated by the host immune system in response to infection. Nanoparticles which are designed for drug delivery are capable of trapping the desired drug in the particles which protects the drug from enzymatic degradation in a biological system. The small (subcellular) size of nanoparticles enables higher intracellular uptake of the drug which results in the reduction of the concentration of free drugs reducing their toxic effect. Research on the modulation of immune response and oxidative stress using nanoparticles used to encapsulate drugs has yet to be explored fully. In this review we illustrate the immune activation and generation of oxidative stress properties which are mediated by nanoparticle encapsulated drug delivery systems which can make the therapy more effective in case of diseases caused by intracellular pathogens.

Electronic invoicing has become mandatory for Italian companies since January 2019. Invoices are structured in a predefined xml template where the information reported can be easily extracted and analyzed. The main aim of this paper is to exploit the information structured in electronic invoices to build an intelligent system which can facilitate accountants work. More precisely, this contribution shows how it is possible to automate part of the accounting process: all sent or received invoices of a company are classified into specific codes which represent the economic nature of the the financial transactions. In order to classify data contained in the invoices a machine learning multiclass classification problem is proposed using as input variables the information of the invoices to predict two different target variables, account codes and the VAT codes, which composes a general ledger entry. Different approaches are compared in terms of prediction accuracy. The best performance is achieved considering the hierarchical structure of the account codes.

This paper presents an OSA patient interactive monitoring system based on the Internet of Things (IoT) framework. This system allows OSA patients to get timely rescue when they are sleepy outside. Because the Beidou position marker has an interactive function, it can reduce the anxiety of the patient while waiting for the rescue. At the same time, if a friend helps the OSA patients to call the doctor, the friend can also report the patient's condition in time. This system uses the popular IoT framework. At the bottom is the data acquisition layer, which uses wearable sensors to collect vital signs from patients, with a focus on ECG and SpO2 signals. The middle layer is the network layer that transmits the collected physiological signals to the Beidou indicator using the Bluetooth Low Energy (BLE) protocol. The top layer is the application layer, and the application layer uses the mature rescue interactive platform of Beidou. Since the GPS indicator has not included the communication satellite, So it has no SMS function. OSA patients can only passively wait for a rescue. Moreover, due to the lack of satellites in Asia and the insufficient density of the ground-enhanced system, the positioning error of OSA patients is large. The Beidou system developed by China itself, the main coverage of the satellite is in Asia, and is equipped with a high-density ground-based augmentation system. Therefore, the Beidou model improves the positioning accuracy and is equipped with a special communication satellite, which increases the short message interaction function. Therefore, patients can report disease progression in time while waiting for a rescue. After our simulation test, the effectiveness of the OSA patient rescue monitoring system based on the Internet of Things framework and the positioning accuracy of OSA patients have been greatly improved. Especially when OSA patients work outdoors, the cell phone base station signal coverage is relatively weak. The satellite signal is well covered, plus the SMS function of the Beidou indicator. Therefore, the system can be used to provide timely patient progress and provide data support for the medical rescue team to provide a more accurate rescue plan. After a comparative trial, the rescue rate of OSA patients using the detection device of this system was increased by 15 percentage points compared with the rescue rate using only GPS satellite phones.

We seek to elucidate an aspirational vision for the food system and explore whether the characteristics of such a system inadvertently set unattainable standards for rural, low wealth communities. We apply discourse analysis to the following qualitative datasets: (1) interviews with food experts and advocates, (2) scholarly and grey literature, (3) industry websites, and (4) email exchanges between food advocates. The analysis revealed eight aspirational food system discourses: Production, Distribution, and Infrastructure; Healthy, Organic, Local Food; Behavioral Health and Education; Sustainability; Finance and Investment; Huger Relief; Demand Side Preferences; Romanticized, Community Led Transformations. Study findings reveal that of eight discourses only three encompass the experiences of rural, low wealth residents. This aspirational food system may result in the disempowerment of the needs of rural, low wealth groups; a perpetuation of the failure of groups who will be unable to reach the aspirational food vision; silencing of discourses that might question those that play a role in the inequitable distribution of income while sanctioning discourses that focus on personal or community solutions; and the absence of other policy-based solutions that address issues located within the food system. Further research is needed to inform policies and programs to mitigate food insecurity in rural, low wealth populations.

Visual imagery, i.e., the mental experience of an object occurring in the absence of external visual stimulus, might encompass diverse content according to different observers. Further, subjectively experienced time is encoded in the later entorhinal cortex. Starting from these two observations, and considering Einstein’s account of spacetime, we show how, in terms of special relativity, the content of visual imagery is not stationary and fixed, rather depends on the standpoint of the observer. We elucidate how the subjective definition of time (perceived by our mind as static) might give rise to modifications in the length of the imagined object which are experimentally assessable and quantifiable. In particular, based on recent neuroscientific literature, we show how changes in our mental time windows are able to squeeze the visual content of mental imagery.

In this research paper we describe the development phase of a low-cost LoRa IoT solution applied to a kindergarten school with three years results. A set of sensors solution was developed in a LoRa communication board, battery powered, providing a simplified setup process. These sensors were used in order to measure temperature, humidity, luminosity, air quality and presence. Also, energy monitor solutions were integrated. The acquired data is transmitted and analysed for knowledge extraction, identifying savings and other related KPIs. From data, automatic saving actions were performed towards heating and cooling systems, lighting and a set of if-then actions were developed for automatic cost-saving actions, based on infrared signals to heating/cooling systems using some procedure of external command devices. This approach avoids the usage of proprietary vendor solutions in a flexible approach that can easily be deployed to any building facility. This is an important achievement since most of the building consumption is based on heating and cooling systems. In a three years test of the solution, the total energy consumption savings surpassed 20%

Facing with errors of a product after machining was a big title in this field. That will affect to product’s quality with unpredictable situation when products is in use for some particular application such as in medical facilities. Improving the precision of machine tools by exploring temperature on multiple points and measuring differential locations of the spindle is going to be executed in this study. A temperature measurement tool and a software running on Windows platform have been developed and combining with Non-bar system in order to support analyzing the temperature rising with the changes of length of the spindle to find the compensation solution based on eccentricity and length distortion. In this study, the whole tests have done on UX300 five – axis CNC machine tools for this investigation and the errors after applying compensation function have reduced 70% at least, with respect to the errors after machining without using compensation function.

The fact that Thailand’s energy policy has set a new renewable energy target of 30% of total final energy consumption by 2036. It also has the potential of solar energy and community demands in remote areas. However, most of the renewable energy technology will still be able to achieve renewable energy goals, similar to the case of the national policy that promotes Solar Home System (SHS) in remote areas, lack of good handling. Therefore, achieving the goal of the renewable energy policy should be in position using the right strategy. This article presents the result of a case study in the Akha upland community, northern Thailand, where we used the mixing method and factor analysis to analyze strategies for SHS related criteria. The key scopes and challenge included bottom-up planning concepts and subsidies from expert persons, while contributions to factors have an impact on developing sustainable SHS, include the creating approval of SHS technologies, developing of SHS management, promoting of SHS technologies, and supporting of SHS policies, respectively. Mainly, social factors provide positive effects, which thus influence the sustainable development of process SHS in terms of the creation of approval. Furthermore, there should be managed appropriately for each community, for the positive imagery of solar power.

Biogenic emissions affect the urban air quality as they are ozone and SOA precursors and should be taken into account when applying photochemical pollution models. The present study presents an estimation of the magnitude of Non-Methane Volatile Organic Compounds emissions (NMVOCs) emitted by vegetation over Greece. The methodology is based on computation performed with the aid of a Geographic Information System (GIS) and theoretical equations in order to develop an emission inventory on a 6x6 spatial resolution, in a temporal resolution of 1hr covering one year (2016). For this purpose, a variety of input data was used: improved satellite land-use data, land-use specific emission potentials, foliar biomass densities, temperature and solar radiation data. Hourly, daily and annual isoprene, monoterpenes and other volatile organic compounds (OVOCs) were estimated. In the area under study, the annual biogenic emissions were estimated up to 472 kt, consisting of 46.6% isoprene, 28% monoterpenes and 25.4% OVOCs. Results delineate an annual cycle with increasing values from March to April, while maximum emissions were observed from May to September, followed by a decrease from October to January.

This paper deals with the analytical modeling and control of rectilinear snake robots. During recent times snake robots have created much interest among researchers. The rectilinear pattern gait is one of the four biological snake locomotion modes. Rectilinear snakes have been widely used in rescue operations especially in rough terrains especially in narrow spaces where human intervention is not easy. Computational analysis of rectilinear motion is done using MATLAB.

The sustainability of ecotourism is the backbone of tourism development of a country. Ecotourism can contribute to both conservation and development in which involves dynamic relationship between tourism, biodiversity and communities, facilitate by great management. The purpose of this study is to analyze the dimensions of the socio-economic and environmental impacts of ecotourism in communities surrounding the Tasik Kenyir in Terengganu, Malaysia. This study provides a framework for the development and evaluation of ecotourism. The framework will determine if the relationships between indicators are positively correlated which will result in positive contribution to the other by using System Dynamic. Socio-cultural and economic data will be collected through interviews and group discussions in selected communities in Tasik Kenyir. Data on wildlife will be extracted from secondary data from Kenyir Research Institute, Universiti Malaysia Terengganu. The data analysis will explore the socio-cultural and economic differences between and within different communities due to ecotourism development, the contribution of ecotourism to conservation activities, local support for conservation and ecotourism as well as the influence of tourist activities on the distribution of wildlife species in Tasik Kenyir. This study aims to contribute toward understanding the natural resource community-ecotourism inter-relationship and help to bridge the knowledge gap that hinders biodiversity conservation initiatives. The findings will be used as a base for further development of ecotourism and will recommend alternative management options where necessary for the study area.

Neurotrophins play a principal role in neuronal survival and differentiation during development, but also in the maintenance of appropriate adult neuronal circuits and phenotypes. In the oculomotor system, we have demonstrated that neurotrophins are key regulators of developing and adult neuronal properties, but with peculiarities depending on each neurotrophin. For instance, the administration of NGF, BDNF or NT-3 protects neonatal extraocular motoneurons from cell death after axotomy, but only NGF and BDNF prevent the downregulation in ChAT. In the adult, in vivo recordings of axotomized extraocular motoneurons have demonstrated that the delivery of NGF, BDNF or NT-3 recovers different components of the firing discharge activity of these cells, with some particularities in the case of NGF. All neurotrophins have also synaptotrophic activity, although to different degrees. Accordingly, neurotrophins can restore the axotomy-induced alterations acting selectively on different properties of the motoneuron. In this review we summarize these evidences and discuss them in the context of other motor systems.

Household waste is the primary source of environmental pollution due to global population growth compared to other sources of waste. This research aims to develop a smart and integrated household waste management system framework. The resulting framework not only focuses on dimensions of information technology but also links it with other integrated dimensions. This research attempts to conduct a Systematic Literature Review (SLR) using the Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) protocol to produce a smart and integrated household waste management framework. The framework's design is carried out by identifying the type of household waste management process based on the Integrated Sustainable Waste Management (ISWM) framework, dimensions that support smart household waste management, and stakeholders involved. The SLR results, namely dimensions and subdimensions that support the framework of a smart and integrated household waste management system, were validated by a resource person from the Indonesian Ministry of Environment and Forestry. The smart and integrated household waste management framework that has been developed in this research contains five main dimensions: Information Technology, Operational Infrastructure, Governance, Economy, and Social-culture. This framework also addresses stakeholder engagement to support smart household waste management systems and identifies waste management processes based on the ISWM framework. This research uses the PRISMA technique to provide a framework for smart and integrated household waste management systems in the initial stage. The proposed framework has been validated and can be further developed as a smart and integrated household waste management system. This research also contributes to the involvement of various dimensions identified to deal with waste problems.

This work aims to study and analyze a hybrid power system for electric vehicles consisting of a dual low and high-rate lithium battery block and a fuel cell. In this configuration, the high-rate lithium battery powers the electric vehicle in high power demand processes like acceleration mode or on an uphill road; the low-rate battery operates at a low output power range, servicing the auxiliary systems and low power loads and the fuel cell supplies energy at intermediate power demand conditions, normal driving mode, constant velocity, or flat and downhill terrain. The dual power system improves global efficiency since every power unit operates optimally depending on driving conditions. Power sharing optimizes the lithium battery performance and fuel cell capacity, minimizing the size and weight of each energy system and enlarging the driving range. A comparative study between different lithium battery configurations and fuel cell shows an efficiency improvement of 31.4% for the hybrid dual battery block and fuel cell operating in low, high, and intermediate output power ranges, respectively. The study bases on a simulation process recreating current driving conditions for electric cars in urban, peripheral, and intercity routes. An alternative solution consisting of a hybrid system, fuel cell and a high rate lithium battery produces a 29 % power gain.

The basis of modern teeth whitening systems is the use of a whitening gel, usually containing hydrogen peroxide or carbamide peroxide. The purpose of our study was to evaluate the effect of chemical and modified office teeth whitening systems on the mineral metabolism of oral fluid and to determine a safer method. The study covered 81 patients aged 22 to 35 years of both sexes with teeth color A2 and darker on the Vita Classic scale. Determination of the concentration of calcium and phosphates in the oral fluid was carried out on a spectrophotometer using ready-made Human kits. Chemical tooth whitening was performed using a gel based on 40% hydrogen peroxide. After the procedure, remineralization therapy with enamel-sealing liquid was performed for 14 days. The obtained results indicate that the most pronounced changes in the content of calcium (+74.4%, p <0.001) and рhosphates (phosphorus) (-23.07%, p <0.001) were observed when using a chemical bleaching system. After the teeth whitening procedure using a modified technique, less pronounced changes in the concentrations of calcium (+29.07, p <0.001) and phosphorus (-14%, p <0.001) were observed. The use of remineralizing agents led to a faster recovery of the initial levels of calcium and phosphates in the oral fluid. Both bleaching systems caused similar changes in the chemical composition of the oral fluid.

The TeNDER project aims to improve the Quality of Life (QoL) of chronic patients through an integrated care ecosystem. This study evaluates the Health Recommender System (HRS) developed for the project, which offers personalized recommendations based on data collected from a set of monitoring devices. The list of notifications covered different areas of daily-life such as physical activity, nutrition, and sleep. We conducted this case of study to evaluate the effectiveness and usability of the HRS in providing accurate and relevant recommendations to users. Evaluation process consisted on survey administration for QoL assessment, and the satisfaction and usability of the HRS. The four-week pilot study involved several patients and caregivers, and demonstrated that the HRS was perceived as user-friendly, consistent, and helpful, with a positive impact on patients’ QoL. However, the study highlights the need for improvement in terms of personalization of recommendations.

We present a finite element model updating technique for soil-structure system identification of the Millikan Library building using the seismic data recorded during the 2002 Yorba Linda earthquake. A detailed finite element (FE) model of the Millikan Library building is developed in OpenSees and updated using a sequential Bayesian estimation approach for joint parameter and input identification. A two-step system identification approach is devised. First, the fixed-base structural model is updated to estimate the structural model parameters (including effective elastic modulus of structural components, distributed floor mass, and Rayleigh damping parameters) and some uncertain components of the foundation-level motion. Then, the identified structural model is used for soil-structure model updating wherein the Rayleigh damping parameters, the stiffness and viscosity of the soil subsystem (modeled using a substructure approach), and the foundation input motions (FIMs) are estimated. The identified model parameters are compared with state-of-practice recommendations. While a specific application is made for the Millikan Library, the present work offers a framework for integrating large-scale FE models with measurement data for model inversion. By utilizing this framework for different civil structures and earthquake records, key structural model parameters can be estimated from the real-world recorded data, which can subsequently be used for assessing and improving, as necessary, state-of-the-art seismic analysis and structural modeling techniques. This paper presents an effort towards using real-world measurements for large-scale FE model updating in the soil and structure, uniform soil time domain for joint parameter and input estimation, and thus paves the way for future applications in system identification, health monitoring and diagnosis of civil structures.

Migraine is a primary headache disorder characterized by unilateral throbbing, pulsing headache, which lasts for hours to days, and the pain can interfere with daily activities. It exhibits various symptoms, such as nausea, vomiting, sensitivity to light, sound, and odors and physical activity consistently contributes to worsening pain. Despite the intensive research, little is still known about the pathomechanism of migraine. It is widely accepted that migraine involves activation and sensitization of the trigeminovascular system. It leads to the release of several pro-inflammatory neuropeptides and neurotransmitters and causes a cascade of inflammatory tissue responses including vasodilation, plasma extravasation secondary to capillary leakage, edema, and mast cell degranulation. Convincing evidence obtained in rodent models suggests that neurogenic inflammation is assumed to contribute to the development of a migraine attack. Chemical stimulation of the dura mater triggers activation and sensitization of the trigeminal system and causes numerous molecular and behavioral changes; therefore, this is a relevant animal model of acute migraine. This review article discusses the emerging evidence supporting the involvement of neurogenic inflammation and neuropeptides in the pathophysiology of migraine, presenting the most recent advances in preclinical research and the novel therapeutic approaches to the disease.

Integrated photovoltaic-fuel cell (IPVFC) systems, amongst other integrated energy generation methodologies are renewable and clean energy technologies that have received diverse research and development attentions over the last few decades due to their potential applications in a hydrogen economy. This article systematically updates the state-of-the-art of IPVFC systems and provides critical insights into the research and development gaps needed to be filled/addressed to advance these systems towards full commercialisation. The design methodologies, renewable energy-based microgrid and off-grid applications, energy management strategies, optimisations and the prospects as self-sustaining power source were covered. IPVFC systems could play an important role in the upcoming hydrogen economy since they depend on solar hydrogen which has almost zero emissions during operation. Highlighted herein are the progresses as well as the technical challenges requiring research efforts to solve to realise numerous potential applications of IPVFC systems such as in unmanned aerial vehicles, hybrid electric vehicles, agricultural applications, telecommunications, desalination, synthesis of ammonia, boats, buildings, and distributed microgrid applications.

The accurate prediction of the solar Diffuse Fraction (DF), sometimes called the Diffuse Ratio, is an important topic for solar energy research. In the present study, the current state of Diffuse Irradiance research is discussed and then three robust, Machine Learning (ML) models, are examined using a large dataset (almost 8 years) of hourly readings from Almeria, Spain. The ML models used herein, are a hybrid Adaptive Network-based Fuzzy Inference System (ANFIS), a single Multi-Layer Perceptron (MLP) and a hybrid Multi-Layer Perceptron-Grey Wolf Optimizer (MLP-GWO). These models were evaluated for their predictive precision, using various Solar and Diffuse Fraction (DF) irradiance data, from Spain. The results were then evaluated using two frequently used evaluation criteria, the Mean Absolute Error (MAE) and the Root Mean Square Error (RMSE). The results showed that the MLP-GWO model, followed by the ANFIS model, provided a higher performance, in both the training and the testing procedures.

This paper presents a method to detect and classify the high impedance fault that occur in the medium voltage distribution network using discrete wavelet transform (DWT) and adaptive neuro-fuzzy inference system (ANFIS). The network is designed using Matlab software and various faults such as high impedance, symmetrical and unsymmetrical fault have been applied to study the effectiveness of the proposed ANFIS classifier method. This is achieved by training the ANFIS classifier using the features (standard deviation values) extracted from the three phase fault current signal by DWT technique for various cases of fault with different values of fault resistance in the system. The success and discrimination rate obtained for identifying and classifying the high impedance fault from the proffered method is 100% whereas the values are 66.7% and 85% respectively for conventional fuzzy based approach. The results indicate that the proposed method is more efficient to identify and discriminate the high impedance fault accurately from other power system faults in the system.

Oil has become the object of global exploits and fierce competition among the major world powers as it is a key strategic non-renewable resource. Transnational petroleum investment is therefore an important mechanism available to countries and international corporations to control oil resources even though there are numerous inherent uncertainties and risks. A new risk assessment index system is proposed in this paper based on use of the Delphi expert scoring system and fuzzy comprehensive evaluation that aims to minimize the potential risks inherent to multinational petroleum investment. This approach encapsulates political, legal, socioeconomic, and infrastructural factors to develop a technical method that can be used for transnational petroleum investment risk assessment. An evaluation of oil investment risk within a case study area is also presented; results provide reference data that can be applied by national and international oil companies to mitigate risks of transnational oil investment.

Autonomous and cooperative vehicle systems represent a key priority in the automotive realm. Networked driving simulation can be utilized as a safe, cost-effective experimental replica of real traffic environments in order to support and accelerate the development of such systems. In networked driving simulation, different independent systems collaborate to achieve a common task: multi-driver traffic scenario simulation. Yet distinct system complexity levels are necessary to fulfill the requirements of various application scenarios, such as development of vehicle systems, analysis of driving behavior, and training of drivers. With myriad alternatives of available systems and components, developers of networked driving simulation are typically confronted with high design complexity. There are no systematic approaches to date for the design of networked driving simulation in accordance with the specific requirements of the concerned application scenarios. This paper presents a novel design method for networked driving simulation. The method consists mainly of a procedure model that is accompanied by a configuration software. The procedure model includes the necessary phases for the systematic design of application-oriented platforms for networked driving simulation. The configuration software embeds supportive decision-making processes that enable developers to apply the design method and easily create different system models. The design method was validated by generating system models and developing platforms of networked driving simulation for three different application scenarios.

The scarcity and pollution of freshwater are extremely crucial issues today and the expansion of water reuse have been considered as an option to reduce its impact. This study aims to assess the efficiency of an integrated greywater treatment system and hydroponic lettuce production as a part of a green wall structure and to evaluate the health risk associated with the production and consumption of lettuce through quantitative microbial risk assessment (QMRA) and chemical health risk assessment. The study was conducted based on the unique configuration of source separation system; on-site greywater treatment system; green wall structure as a polishing step; and hydroponic lettuce production in the green wall structure. The final effluent from the system was used to grow three lettuce varieties by adding urine as a nutrient solution. Both water samples and plant biomass were collected and tested for E. coli and heavy metals contamination. The system has gained a cumulative 5.1 log10 reduction of E. coli in the final effluent and no E. coli found in the plant biomass. QMRA results indicated that the system attained the health-based targets, 10–6 DALYs per person per year. Similarly, health risk index (HRI) and targeted hazard quotient (THQ) results did not exceed the permissible level, thus the chemical health risk concern was insignificant.

With the trend of public infrastructure becoming more sustainable, large multi-purpose sports venues (LMPSVs) have become one of the world's most complex architectural projects and one of the landmark buildings of an international city. LMPSVs will lead the world in sustainable design, construction and operational innovations, and play a crucial role in raising awareness of sustainability around the world. System Thinking (ST), System Dynamics (SD) and Sustainable System Development (SSD) theories are three interrelated concepts that together form a methodological framework for solving complex system problems and driving strategies. The purpose of this study is to examine how LMPSVs can implement environmental, social, governance, and innovation (ESGI) enterprise transformation strategy (ETS) based on a sustainable systems development (SSD) framework. In view of the current global environmental challenges and social responsibility requirements, the motivation of this study is to provide an integrated transformation pathway for LMPSVs to achieve the goal of sustainable development and to contribute to the field of related disciplines. The methodology of this research adopts a combination of literature review and case study analysis, and the theoretical basis is mainly drawn from cutting-edge research in the fields of sustainable development, corporate social responsibility (CSR) and environmental management. Then, by analyzing successful transformation cases in China, we extract data and information to explore the application and effectiveness of these strategies in practice. The results of the study show that by implementing ESGI-based transformation strategy, LMPSVs can not only make significant progress in terms of environmental protection, social responsibility, and governance structure, but also drive long-term corporate growth and competitiveness through innovation. Specifically, these results are realized in terms of increased efficiency in energy use, improved waste management, community involvement and increased stakeholder satisfaction. The study concludes by emphasizing that the SSD-based ESGI Transformation Strategic framework provides a sustainable pathway for LMPSVs. In the future, the extension of this transformation strategy will help a wider range of industry sectors to achieve sustainable development goals, and has wide application potential and far-reaching social significance.

Electric power systems are experiencing relevant changes involving the growing penetration of distributed generation and energy storage systems, the introduction of electric vehicles, the management of responsive loads, the proposals for new energy markets and so on. Such evolution is pushing for a paradigm shift: the management must move from traditional planning and manual intervention to full “smartization” of medium and low voltage networks. Peculiarities and criticalities of future power distribution networks originate from the complexity of the system that includes both the physical aspects of electric networks and the cyber aspects, like data elaboration, feature extraction, communication, supervision and control; only fully integrated advanced monitoring systems can foster this transition towards network automation. The design and development of such future networks require distinct kinds of expertise in the industrial and information engineering fields. In this context, this paper provides a comprehensive review of current challenges and multidisciplinary interactions in the development of smart distribution networks.

At 100% penetration, intermittent renewable energy causes outages. To flatten the leaping supply and demand curves of renewable energy, an energy storage medium and carrier are required. The Hydrogen energy stotrage system (HydESS), which combines a proton exchange membrane (PEM)-based water electrolysis (WE) system and a fuel cell (FC), has the quickest response time, the longest duration, and the greatest storage capacity. HOMER tools for techno-economic analysis are used to evaluate the HydESS hybrid system. Kyiv, Ukraine, is appealing due to its spatial-temporal wind speed, solar irradiance, and energy security. With an LCOE of $0.245 kWh−1 and 9.3% fuel cell power output, the most feasible solution is onshore wind turbine-coupled PEMFC HydESS. As a result 1,000-kW wind power, 250-kW PEMFC, 250-kW PEMWE, and 441-kW BESS are optimized to serve a 3,900 kWh day academic residence load. When compared to a diesel generator and a BESS, the hybrid HydESS reduces CO2 emissions by 4,132 tons over a 25-year period. The LCOE of a hybrid HydESS system is determined by the SOFC lifetime rather than the PEMFC's 2% difference between 40,000 and 50,000 h with the same rated power. This study recommends accelerating PEMFC development with fluctuation-endurable materials and design.

In this article the problem of detection and isolation (FDI) in wheeled mobile robot is 1 treated. first of all we consider a master-slave robot system in which the master robot has to follow a 2 desired trajectory given by a well-determined control law, then the slave is controlled by the master. 3 However in real environment there is no ideality because faults can appear in the master or slave 4 or even the both and affect the system and may lead to unacceptable results so to ensure a well 5 functioning an extended kalman filter is tuned to diagnosis eventual faults and to generate residuals 6 in order to detect and isolate them. The performance of an estimator based on an EKF is simulated 7 based MATLAB Simulink simulations.

The process of building microgrids on top of existing passive distribution networks warrants a multi-criteria analysis. Besides the calculation of investment outlays needed for the modernization of distribution networks, such an analysis covers an assessment of the technological and economic effects of building microgrids. The resulting effects depend on the topology and configuration of distribution networks, specific microgrid features, the choice of current type for the entire microgrid or its individual parts, the ways of connecting distributed energy resources (DER), the availability and condition of information and communications technology (ICT) infrastructure, and other factors. Complete input data allow one to design an optimal microgrid configuration, but the main technological and economic effects are determined by the algorithms of operation and the parameters setting of the automatic control system (ACS) and the protection system. Known approaches to designing microgrids focus on addressing basic tasks while minimizing investment required for their implementation. The above is fully justified when constructing new microgrids, but building microgrids on top of existing distribution networks, given the uniqueness of their topology and configuration, does not allow the use of standardized solutions. The development of approaches to the design of microgrids under such constraints, with minimized investment for the modernization of existing distribution networks, is an urgent task. The use of different types of current for microgrid segments determines the choice of particular ACS and protection system, which depends on the availability of information and communications technology infrastructure. This article contributes a review of approaches to designing AC and AC-DC microgrids to maximize their technological and economic effects. We review techniques for analyzing existing distribution networks aimed at choosing the type of current for the entire microgrid or its individual parts, the optimal connection points of microgrids to distribution networks, the mix and capacity of DERs, with such choices informed by the condition of switching devices and information and communications technology infrastructure. The article presents the results of the analysis of approaches to choosing the optimal configuration of microgrids, microgrid ACS and protection system, with an evaluation of the technological and economic effects subject to minimization of investment for the modernization of existing distribution networks.

The PLM concept implies the use of heterogeneous information resources at different stages of the product life cycle, the joint work of which allows you to effectively solve the problems of product quality and various costs. According to the principle of isomorphism of regularities of complex systems, an effective PLM system must have these regularities. Unfortunately, this principle is not often fundamental when designing PLM systems. The purpose of the work is to show, using a simple example, the principles of development, operation and use of an educational multi-agent PLM system, the main purpose of which is to study and research these regularities in the life cycle of a special threaded connection. The multi-agent approach to the development of a PLM system provides the necessary prerequisites for the emergence of system-wide regularities in it. The parallel work of agents is implemented using the actor model and the Ray Python-package. Agents for the logical inference of knowledge base facts, CAD/FEA/CAM/SCADA agents, agents for optimization by various methods, and other agents have been developed. Open source software was used to develop the system. Each agent has relatively simple behavior, implemented by its rule function, and can interact with other agents. The system can work in interactive mode with the user or in automatic mode according to a simple algorithm: the rule functions of all agents are executed until at least one of them returns a value other than None. Examples of the operation of the system are given and such system-wide regularities as emergence, historicity and self-organization are demonstrated in it.

This paper develops a methodology to control the navigation of an autonomous ship robot from an initial state to a final. To solve the problem the following approach is used: The ship robot system is modelled as a control system of six ordinary differential equations involving six state variables and three control variables. After having computed the system Hamiltonian, the feasible controls for optimality are derived from the normal equations of optimality as functions of the state and costate variables. Such controls are substituted into the state and the costate equations and give a combined control-free state-costate system of ordinary differential equations which is solved numerically by using a developed Matlab computer program. Associated computational simulations are designed and provided to show the reliability of the approach.

It is not easy to dynamically analyze thermal bridges that require multidimensional analysis in building energy simulations, which are mostly one-dimensional platforms. To solve this problem, many studies have been conducted and, recently, a study was conducted to model the thermal bridge based on the data by approaching this in a similar way to steady-state analysis, showing high accuracy. This was an early-stage study, which is only applicable when the indoor temperature is constant. By extending this study, a thermal bridge model that can be applied even when the indoor temperature changes over time is proposed and validated. Since the governing equation, the heat diffusion equation, is linear, the key idea is to create and apply two thermal bridge transfer function models by expressing the heat flow entering the room as a linear combination of the transfer function for indoor temperature and the transfer function for outdoor temperature. For the proposed thermal bridge model, the NRMSE of the model itself showed a high accuracy of 99.9%, and in the verification through annual simulation using the model, the NRMSE showed an accuracy of 88.8%.

A two-link model of exoskeleton with variable-length links for supporting the lower limbs of the human musculoskeletal system is proposed in the article. The researched model differs from the existing ones by the variable-length links, and by the angle calculation method. While in the existing models, the angles are calculated from the regular direction – from vertical, or from horizontal, - in the proposed research they are calculated between the links. As for practical exoskeleton implementation, the proposed method of angle calculation is appropriate to the actual working conditions of the electrical motors with the reduction gears installed in the hinges, which change the angles between the links. The mathematical model in the form of the system of Lagrange differential equations of the second kind is obtained. The obtained mathematical model is examined for existence and uniqueness of the Cauchy solution. The kinematic trajectory of the link motion has been synthesized. The controlling actions required for its implementation have been found.

Heart Rate Monitors (HRMs) are an indispensable tool for controlling training parameters of healthy athletes. They became a source of information about stress heart rhythm disturbances, recognized as unexpected increases in heart rate (HR), which can be life-threatening for athletes. Most HRMs do not recognize the type of arrhythmia, confusing them with artifacts. The aim of the study was to assess the usefulness of ECG recording functions by sports HRMs among endurance athletes, coaches, and physicians in comparison with other basic and hypothetical functions. We conducted 3 surveys among endurance athletes (76 runners, 14 cyclists, and 10 triathletes), as well as 10 coaches and 10 sports doctors to obtain information on how important ECG recording is, and what functions of HRMs should be improved to meet their expectations in the future. The respondents were asked questions regarding use and hypothetical functions, as well as preference for HRM type (optical/strap). For athletes, the 4 most important functions were distance traveled, pace, instant heart rate, and information about reaching the oxygen threshold. ECG recording was the 8th and 9th most important for momentary and continuous, respectively. Coaches opined more importance to ECG recording. Doctors placed ECG recording as most important. All participants preferred optical HRMs to strap HRMs. Research on the improvement and implementation of HRM functions shows slightly different preferences of athletes compared to coaches and doctors. Suspected arrhythmia increases the value of the HRM’s ability to record ECGs during training by athletes and coaches. For doctors, this is the most desirable feature in any situation. Considering the expectations of all groups continuous ECG recording during training will significantly improve the safety of athletes.

The planning and decision-making for a distributed energy supply concept in complex actor structures like in districts calls for the approach to be highly structured. Here, a strategy with strong use of energetic simulations is developed, the core elements are presented and research gaps are identified. The exemplary implementation is shown using the case study of a new district on the former Oldenburg airbase in northwestern Germany. The process is divided into four consecutive phases, which are carried out with different stakeholder participation and use of different simulation tools. Based on a common objective, a superstructure of the applicable technologies is developed. Detailed planning is then carried out with the help of a multi-objective optimal sizing algorithm and Monte Carlo based risk assessment. The process ends with the operating phase, which is to guarantee a further optimal and dynamic mode of operation. The main objective of this publication is present the core elements of the planning processes and decision-making framework based on the case study and to find and identify research gaps that will have to be addressed in the future.

Increasing demand for electricity and modernization of power systems within competitive markets induce power systems to operate close to their stability limits. Therefore, a power system continuous monitoring and control by using voltage stability indices are known exigence. This is the first-ever effort, examined more than 40 voltage stability indices thorough an exhaustive study based in on their formulation, application, performance, and assessment measures. Which is conducted based on a logical and chronological order considering the most recent worldwide applied voltage stability indices. However, the generalizability of such an immense diversity of these indices in term of multivariable objectives subjects to a certain limitation to summate into a deciphered outcome. Despite all these obstacles, this study systematically reviews available indices in the literature within the past three decades to set out an integrated knowledge with an insight up-to-date exposition. That followed with a comparative analysis in term of their similarity, functionality, applicability, formulation, merit, demerit, and overall performances. Also, a broad categorization of voltage stability indices is addressed. This study with an immediate implication in practice as an exhaustive roadmap can be counted a planning and operation reference in the context of voltage stability for students, researchers, scholars, and practitioners.