First, a brief overview is provided on humanoid robots, and also models for the dynamic behavior are discussed. As base for these models these two methods Denavit-Hartenberg and Newton-Euler are used. Main aim of this work is to investigate the stability of a biped robot developed from IHRT. There is currently the low base of robot - consisting of feet, legs, hips and upper part of robots body. This structure currently has ten degrees of freedom.

Fluid flow in human body is generally known to influence a variety of cellular behaviors. Different nanoparticle properties as well as cell type, interaction with other cells and cellular environments also show significant effect on nanoparticle uptake and drug efficacy. The aim of this study was to evaluate the effect of shear stress on cellular behaviors of biocompatible and biodegradable nanoparticles to cancer cells (A549 cell lines) in a biomimetic microfluidic system. We prepared a gelatin-oleic conjugate (GOC) as an amphiphilic biomaterial to prepare self-assembled gelatin-oleic nanoparticles (GON). Coumarin-6 and paclitaxel were used as the fluorescence marker and model drug, respectively, and were loaded into GONs by incubation (C-GONs; PTX-GONs). Additionally, we evaluated the cellular uptake of fluorescence labeled C-GONs and the drug efficacy of PTX-GONs. The cellular uptake of C-GONs by A549 cells in the absence of shear stress revealed that the mean fluorescence intensity was slightly decreased compared to that in the presence of shear stress. The results also indicated that negatively charged PTX-GONs had a lower cancer killing effect under dynamic conditions than that under static conditions. It also suggested that fluidic shear stress did not significantly affect drug uptake and efficiency in case of PTX-GONs. The cellular interactions between nanoparticles and cells in drug delivery should be carefully examined according to the physicochemical properties of nanoparticles such as the type of materials, size and mainly surface charge in a biomimetic microfluidic condition.

The material undergoes high temperature and high strain rate deformation process during cutting process, may induce the dynamic recrystallization behavior and result the evolution of dynamic mechanical properties of the material to be machined. In this paper, the modified Johnson-Cook(J-C) model for Nickel based powder metallurgy superalloy considering dynamic recrystallization behavior in high strain rate and temperature is proposed. The dynamic mechanical properties of the material under different strain rates and temperature conditions are obtained by quasi-static compression test and split Hopkinson pressure bar (SHPB) test. The coefficients of the modified J-C model are obtained by linear regression method. The modified model is verified by comparison with experimental and model prediction results. The results show that the modified J-C model proposed in this paper can accurately describe the mechanical properties of nickel-based powder metallurgy superalloys at high temperature and high strain rate. Which provides help for studying the cutting mechanism and finite element simulation of nickel-based powder metallurgy superalloy.

Unsupported sleepers or void zones in ballasted tracks are one of the most recent and frequent track failures. The void failures have the property of intensive development that, without timely maintenance measures, can cause the appearance of cost-expensive local instabilities like subgrade damages. The reason of the intensive void development lies in the mechanics of the sleeper and ballast bed interaction. The particularity of the interaction is a dynamic impact that occur due to void closure. Additionally, void zones cause inhomogeneous ballast pressure distribution between the void zone and fully supported neighbour zones. The present paper is devoted studying the mechanism of the sleeper-ballast dynamic impact in the void zone. The results of experimental in-situ measurements of rail deflections showed the significant impact accelerations in the zone even for light-weight slow vehicles. A simple 3-beam numerical model of track and rolling stock interaction has shown the similar to the experimental measurements dynamic interaction. Moreover, the model shows that the sleeper accelerations are more than 3 times higher than the corresponding wheel accelerations and the impact point appear before the wheel enters the impact point. The analysis of ballast loadings shows the specific impact behaviour in combination with the quasistatic part that is different for void and neighbour zones, which are characterised with high ballast pre-stressed conditions. The analysis of void sizes influence demonstrate that the impact loadings, wheel and sleeper maximal accelerations appear at certain void depth after which the values decrease. The ballast quasistatic loading analysis indicates more than twice increase of the ballast loading in neighbour zones for long voids and almost full quasistatic unloading for short length voids. However, the used imitation model cannot explain the nature of the dynamic impact. The mechanism of the void impact is clearly explained by the analytic solution using a simple clamped beam. A simplified analytical expression of the void impact velocity shows that it is linearly related to the wheel speed and loading. The comparison to the numerically simulated impact velocities shows a good agreement and the existence of the void depth with the maximal impact. An estimation of the long-term influences for the cases of normal sleeper loading, high ballast pre-stress and quasistatic loading in the neighbour zones and high impact inside the void are performed.

The BH 25 railway bridge, located in Indonesia, consists of three spans: 9.5 m (span-1 girder type), 21.9 m (span-2 truss type), and 9.6 m (span-3 girder type). Despite the initial plan for camber, it was not achieved, leading to the installation of temporary support on span-2. To assess the level of damage and determine the necessary steps, static and dynamic tests were conducted using a CC206 locomotive. The maximum deflection was recorded at -4.60 mm for span-1, -11.30 mm for span-2, and -3.42 mm for span-3. The dominant frequency in the vertical direction of span-2 was found to be 14.65 Hz. Due to the inability to achieve the planned camber and the subsequent removal of temporary support, external prestressing will be implemented, resulting in a camber of 11.82 mm. This change in prestressing also affects the dominant frequency of span-2, which becomes 17.07 Hz.

Piezoelectric cantilever harvesters have a large power output at their natural frequency, but in some applications the frequency of ambient vibrations is different from the harvester’s frequency and/or ambient vibrations are periodic with some harmonic components. To cope with these operating conditions harvesters with integrated trimming devices (ITDs) are proposed. Some prototypes are developed with the aid of an analytical model and tested with an impulsive method. Results show that a small trimming device can lower the main resonance frequency of a piezoelectric harvester of the same extent as a larger tip mass and moreover generates at high frequency a second resonance peak. A multi-physics numerical FE model is developed for predicting the generated power and for performing stress-strain analysis of harvesters with ITDs. The numerical model is validated on the basis of experimental results. Several configurations of ITDs are conceived and studied. Numerical results show that harvesters with ITDs are able to generate relevant power at two frequencies owing to the particular shape of the modes of vibration. The stress in the harvesters with ITDs is smaller than the stress in the harvester with a tip mass trimmed to the same frequency.

Ensuring safe and continuous autonomous navigation in long-term mobile robot applications is still challenging. To ensure a reliable representation of the current environment without the need for periodic re-mapping, updating the map is recommended. However, in case of incorrect estimation of robot pose, updating the map can lead to errors that prevent the robot localisation and jeopardize map accuracy. In this paper, we propose a safe LIDAR-based occupancy grid map updating algorithm for dynamic environments taking into account the uncertainties in the estimation of the robot’s pose. The proposed approach allows robust long-term operations as it can recover the robot’s pose, even when it gets lost, to continue the map update process providing a coherent map. Moreover, the approach is robust also to temporary changes in the map due to the presence of dynamic obstacles such as humans and other robots. Results highlighting map quality, localisation performance, and pose recovery, both in simulation and experiments, are reported.

Hexakis(2-alkoxy-1,5-phenyleneimine) macrocycles were synthesized using a simple one−pot procedure through by precipitation−driven cyclization. The acetal−protected AB−type monomers, 2-alkoxy-5-aminobenzaldehyde diethyl acetals, underwent polycondensation in water or acid−containing tetrahydrofuran. The precipitation−driven cyclization based on imine dynamic covalent chemistry and π−stacked columnar aggregation played a decisive role in the one−pot synthesis. The progress of the reaction was analyzed by MALDI−TOF mass spectrometry. The macrocycles with alkoxy chains were soluble in specific organic solvents such as chloroform, allowing their structures to be analyzed by NMR. The shape−anisotropic, nearly planar, and persistent macrocycles aggregated into columnar assemblies in polymerization solvents, driven by aromatic π−stacking. The octyloxylated macrocycle OcO−Cm6 exhibited an enantiotropic columnar liquid crystal−like mesophase between 165°C and 197°C. In the SEM image of (S)-(−)-3,7-dimethyloctyloxylated macrocycle (−)BCO-Cm6, columnar substances with a diameter of 100−200 nm were observed. The polymerization solution for 2-(2-methoxyethoxy)ethoxy)ethoxylated macrocycle (TEGO−Cm6) gelled and showed thixotropic properties by forming a hydrogen bond network.

Previous studies generally reckon that the full converter-base wind power generation (FCWG) is a ’decoupled’ power source from the grid, which hardly participates in electromechanical oscillations. However, it is found recently that strong interaction could be induced which might incur severe resonance incidents in electromechanical dynamic timescale. In this paper, the participation of FCWG in electromechanical dynamics is extensively investigated, and particularly, an unusual transition of electromechanical oscillation mode (EOM) is uncovered for the first time. The detailed mathematical models of open-loop and closed-loop power systems are firstly established, and modal analysis is employed to quantify the FCWG participation in electromechanical dynamics, with two new mode identification criteria, i.e., FCWG dynamics correlation ratio (FDCR) and quasi-electromechanical loop correlation ratio (QELCR). On this basis, the impact of different wind penetration levels and controller parameter settings on the participation of FCWG is investigated. It is revealed that if an FOM has a similar oscillation frequency to the system EOMs, there is a high possibility to induce strong interactions between FCWG dynamics and system electromechanical dynamics of the external power systems. In this circumstance, an interesting phenomenon may occur that an EOM may be dominated by FCWG dynamics, and hence is transformed into a quasi-EOM, which actively involves the participation of FCWG quasi-electromechanical state variables.

Abrasive Water Jet Machining (AWJM) is a non-conventional machining process that, unlike other methods, is deemed superior because of its applicability, versatility, and no heat-affected zones in the target material. The main objective of this paper was to develop a cheap, practical model for a low-pressure water jet cutting machine and provide some empirical test data for cutting delicate materials. Proper design calculations were performed and are included for both the water jet machine and the two-axis numerical control. Finite Element Analysis results validate the structural integrity of beams and columns in AWJM. Computational Fluid Dynamic analysis of the nozzle shows good agreement with the theoretical calculations regarding the pressure and velocity of the water-abrasive mixture exiting the nozzle. Modal analysis in ANSYS was done to mitigate potential failure due to resonance induced by vibrations. Limited testing on various thicknesses of polystyrene foam ranging from 1-5 mm thickness and rubber sheet of 1 mm thickness showed that even low pressure of 25-30 bar was sufficient to produce a kerf without any burr. However, extensive testing to report optimized parameters like nozzle transverse speed, standoff distance, abrasive flow rate, etc for working at low-pressure ranges is still a consideration for future investigation.

Since the outbreak of 2019 novel coronavirus (2019-nCoV) at the hardest-hit city of Wuhan, the fast-moving spread has killed over three hundred people and infected more than ten thousands in China¹. There are more than one hundred cases outside of China, affecting a dozen of countries globally². The genome sequence of 2019-nCoV has been reported and fast diagnostic kits, effective treatment as well as preventive vaccines are rapidly being developed³. Initial fast-growing confirmed cases triggered lock-down of Wuhan as well as nearby cities in Hubei Province. Mathematical models have been proposed by scientists around the world to project the numbers of infected cases in the coming days ^4,5. However, major factors such as transportation and cultural customs have not been weighed enough. Our model is not set out for precise prediction of the number of infected cases, rather, it is meant for a glance of the dynamics under a public epidemic emergency situation and of different contributing factors. We hope that our model and simulation would provide more insights and perspective information to public health authorities around the globe for better informed prevention and containment solution.

Rainfall runoff modeling has been a subject of interest for decades due to a need to understand a catchment system for management, for example regarding extreme event occurrences such as flooding. Tropical catchments are particularly prone to the hazards of extreme precipitation and the internal drivers of change in the system, such as deforestation and land use change. A model framework of dynamic TOPMODEL, DECIPHeR v1 - considering the flexibility, modularity and portability - and Generalized Likelihood Uncertainty Estimation (GLUE) method are both used in this study. They reveal model performance for the streamflow simulation in a tropical catchment, i.e. the Kelantan River in Malaysia, that is prone to flooding and experiences high rates of land use change. 32 years' continuous simulation at a daily time scale simulation along with uncertainty analysis resulted in a Nash Sutcliffe Efficiency (NSE) score of 0.42 from the highest ranked parameter set, while 25.35% of the measurement falls within the uncertainty boundary based on a behavioral threshold NSE 0.3. The performance and behavior of the model in the continuous simulation suggests a limited ability of the model to represent the system, particularly along the low flow regime. In contrast, the simulation of eight peak flow events achieves moderate to good fit, with the four peak flow events simulation returning an NSE > 0.5. Nonetheless, the parameter scatterplot from both the continuous simulation and analyses of peak flow events indicate unidentifiability of all model parameters. This may be attributable to the catchment modelling scale. The results demand further investigation regarding the heterogeneity of parameters and calibration at multiple scales.

For better export marketing strategies (EMS), companies mobilize their internal resources, which are managerial commitment, firm experience, and product uniqueness. However, Small businesses with constrained resources cannot be well explained with this view. So, more research on how small business come up with EMS have been called for. To explain how resource-restricted firms which rely heavely on entrepreneur, this study adopted the concept of dynamic managerial capabilities (DMCs) and resource versatility to better explain small business exports. We analyzed small businesses in Mongolia with qualitative research methods, including interviews with entrepreneurs and support organizations, site visits, and group discussions. We suggest international dynamic marketing capabilities (IDMCs), which are entrepreneurial orientation, networking capability, and versatile dynamic capability for small business. Theoretical and managerial implications are discussed.

The article presents the method of identification of dynamic models for different flight states of a rotary-wing UAV. Experimental flights were conducted to obtain data necessary for the identification process. Such models can later be implemented in simulations to represent the behavior of real-life objects. Simulation of UAV swarms is the first stage of developing a swarm system, where prototyping with physical models is problematic. Therefore, obtaining accurate models is crucial for the simulation process to be reliable. Also, verification of obtained models was performed to make sure that they were identified correctly. In particular, the presented method was proven effective and successfully used in some applications.

We have developed a self-consistent model for predicting velocity of 1/2[111] screw dislocation in binary iron--carbon alloys gliding by a high-temperature Peierls mechanism. The methodology of modelling includes: (i) Kinetic Monte-Carlo (kMC) simulation of carbon segregation in dislocation core and determination the total carbon occupancy of the core binding sites; (ii) Determination of kink-pair formation enthalpy of a screw dislocation in iron---carbon alloy; (iii) KMC simulation of carbon drag and determination of maximal dislocation velocity at which the atmosphere of carbon atoms can follow a moving screw dislocation; (iv) Self consistent calculation of average velocity of screw dislocation in binary iron--carbon alloys gliding by a high-temperature kink-pair mechanism under constant strain rate. We conduct a quantitative analysis of the conditions of stress and temperature at which screw dislocation glide in iron--carbon alloy is accomplished by a high-temperature kink-pair mechanism. We estimate the dislocation's velocity at which screw dislocation brakes away from the carbon cloud and thermally-activated smooth dislocation propagation is interrupted by sporadic bursts controlled by athermal dislocation activity.

In this study, in order to develop the composition ceramics for the application of ultrasonic transducer device for temporomandibular joint disorder pain relief and facial skin massage, Pb0.88(La0.6Sm 0.4)0.08(Mn 1/3 Sb 2/3)0.02 Ti 0.98 O3 ceramics were manufactured using CuO as sintering aids, and their piezoelectric ,and resonant properties were investigated. At the specimen sintered at 1200 [℃], the excellent values of piezoelectric properties appeared, respectively: the dielectric constant (εr) of 202, piezoelectric constant (d33) of 56[pC/N], first and third overtone electromechanical coupling factor kt of 0.548, kt3 of 0.219, and then first and third overtone mechanical quality factor Qmt1 of 345, Qmt3 of 292 were suitable for the device application such as ultrasonic transducer, respectively. When the length of one side was 7.7 mm, first and third overtone electromechanical coupling factor kt1 of 0.555, kt3 of, 0.196, and then first ,third overtone mechanical quality factor Qmt1 of 381, Qmt3 of 393 , and the first dynamic ratio(D.R) and third overtone dynamic ratio(D.R) of 63.7(dB),and 37.7(dB) were suitable for the device application such as ultrasonic transducer ,respectively .

Japanese encephalitis virus (JEV) causes acute viral encephalitis in humans and reproductive disorders in pigs. JEV emerged during the 1870s in Japan and since that time, JEV has been transmitted exclusively throughout Asia, according to known reporting and sequencing records. A recent JEV outbreak occurred in Australia which affected commercial piggeries across different temperate southern Australian states and caused confirmed infections in humans. A total of 47 human cases and seven deaths were reported. The recent evolving situation of JEV needs to be reported due to its continuous circulation in endemic regions and spread to non-endemics areas. Here, we reconstructed the phylogeny and population dynamics of JEV using recent JEV isolates for the future perception of disease spread. Phylogenetic analysis shows the most recent common ancestor occurred about 3120 years ago (YA) (95% Highest posterior density [HPD], 2680 to 3715). Our results of the Bayesian skyline plot (BSP) demonstrates that JEV demography lacks fluctuations for the last two decades, but it shows that JEV genetic diversity has increased during the last ten years. This indicates the potential JEV replication in the reservoir host, which is helping it to maintain its genetic diversity, and to continue its dispersal into non-endemic areas. The continuous spread in Asia and recent detection from Australia further support these findings. Therefore, an enhanced surveillance system is needed along with precautionary measures such as regular vaccination and mosquito control to avoid future JEV outbreaks.

Contactless charging is evolving fast in many domains and applications such as the electrical vehicles (EV). The principle consists of transferring energy between two systems without having any electrical connection between them. This power transfer can be realized by emitting a magnetic field for Inductive Power Transfer (IPT). In the automotive domain, the application of contactless charging to supply power to the vehicle while driving is one of the solutions envisaged to solve the limited autonomy range of EV and reduced its cost but the system must comply with existing standards (e.g., allocated frequency range and radiated electromagnetic emissions), as summarized in this paper.

This experimental research presents an easier model for fitting experimental results that can be simulate the dynamical behaviour of a single degree freedom system, SDFS, subjected in a forced vibration in a shaking table. The fractional damping using a Kelvin-Voigt fractional derivative rheological model, KVFRdm, to represent a fractional oscillator and compare with the experimental model.

Addressing sustainable mobility in urban areas has become a priority in today’s society, given the growing population and increasing vehicular flow in these areas. Intelligent Transportation Systems have emerged as innovative and effective technological solutions to address these challenges. Research in this area has become crucial, as it contributes not only to improve mobility in urban areas, but also to positively impact the quality of life of its inhabitants. To address this, a dynamic clustering methodology for vehicular trajectory data is proposed which can provide an accurate representation of the traffic state. Data was collected for the city of San Francisco, a dynamic clustering algorithm was applied and then an indicator was applied to identify areas with traffic congestion. Several experiments were also conducted with different parameterizations of the forgetting factor of the clustering algorithm. The results showed in terms of precision that the dynamic clustering methodology achieved high match rates compared to the congestion indicator applied to static cells.

Decision making is a complex process involving various parts of the brain which are active during different times. It is challenging to measure externally the exact instance when any given region becomes active during the decision-making process. Here we try to extract and visualize the dynamic functional brain activation information from the observed fMRI data. We propose the use of a regularized deconvolution model to simultaneously map various activation regions within the brain and track how different activation regions changes with time. Thus, providing both spatial and temporal brain activation information. The activation information can then be further analyzed as per need and requirements. The proposed technique was validated using simulated data and then applied to a simple decision-making task for identification of various brain regions involved in different stages of decision making. The visualization aspect of the algorithm allows us to actually see the flow of activation (and deactivation) in form of a motion picture. The dynamic estimate may aid in understanding the causality of activation between various brain regions in a better way.

Semantic segmentation of remote sensing urban scene imagery is a pixel-wise prediction, which is applied to identify the land-cover or land-use category. However, semantic segmentation demands huge computation cost. In order to reduce the huge computation cost, a common method is to introduce transformer and CNN hybrid method to have a good trade-off between accuracy and computation cost. However, recent CNN-transformer hybrid methods often capture local-global context and cross-window interaction information simultaneously. Then they introduce the local-global context to fuse the local feature, which repeat fuse the local and global feature and result in the additional computation cost. And previous methods often ignore to filter the local and global feature. To fix the problem, we design a lightweight decoder-EDDformer, which is Efficient Global Value Transformer with Dynamic Gatefusion module. Efficient global value transformer only response for extracting global feature. Dynamic Gatefusion module filter the local and global semantic feature and fuse them to capture the local-global context in one time. Extensive experiments reveal that our method not only runs faster but also achieves higher accuracy compared with other state-of-the-art lightweight models.

Cable-Driven Parallel Robots (CDPRs) are a special kind of parallel manipulator which use cables to control the position and orientation of the mobile platform or end-effector. The usage of cables instead of rigid links offer some advantages over their conventional rigid counterparts. As cables can only pull, but not push, the number of cables (n) required to command the end-effector is always n+1. This configuration is known as fully-constrained and it is the most extended configuration for CDPRs. Although CDPRs have many advantages, such as their ability to cover large working areas, one of their main problems is that their working area (workspace) is limited in comparison to its frame area (planar case), or frame volume (spatial case), due to the minimum and maximum allowed tensions. Depending of these tensions values the workspace can be notoriously decreased. In order to tackle this problem, lots of works focus on solving kinematics or dynamics problems for cable sagging, i.e., they take into account sagging when modelling the robot kinematic and include these poses inside the usable robot workspace. Taking into account phenomenons like this increases the mathematical complexity of the problem, and much more complex techniques are required. On the other hand, the lack of workspace problem can be tackled by adding active or passive elements to the robot design. In this sense, this paper proposes two mechanical modifications: to add passive carriages to the robot frame and to use a single cable loop to command the end-effector position and orientation. This work presents the kinematic, static and dynamic models of the novel design and shows the gain of workspace for a planar case while taking into account different parameters of the robot.

The study considers building a dynamic model of profit maximization for the car-sharing system and its verification on the example of implementing such a system in Astana (Republic of Kazakhstan). The region, bounded by the administrative boundaries of Astana, was divided into subregions by covering the region with regular hexagons placed side by side. A dataset was built with information on 1168 trips to Astana from January to March 2023. The Kepler visualization service constructed maps of the beginning and end of trips in the region and a map of trips binding to the hexagonal grid cells. Each cell of the grid corresponds to a specific sub-region, for which the quantitative parameters necessary for solving the profit maximization problem in the car-sharing system are calculated. Stations with cars will be placed in the cells of the grid, which will be available to car-sharing service customers. Based on the collected data, a dynamic (four periods per day) and static profit maximization model in the car-sharing system was built. Modeling was carried out based on the built models in the example of Astana. It was established that using a dynamic model of profit maximization in the car-sharing system increases the profit by 3.7%.

Objectives: To investigate the value of early lactate dynamic monitoring index in predicting prognosis of patients with sepsis and septic shock. Methods: We performed our test on 50 patients. Out of 50 patients, 28 are male, and 22 are female. Prospectively studied pediatric patients with septic shock were performed. Vital signs, Lactate clearance, were obtained at presentation 6 h, 12 h, 24 h over the first 48 h of hospitalization. The therapy received, outcome parameters of mortality and duration of hospitalization were recorded. Results: The statistical data and comparative analysis showed that an average of 16.88 days after admission, 5 patients have died, 17 patients are poorly prognosis leaves the hospital, and the remaining 28 are recovered and discharged. The primary outcome variable of mean 16 days hospitalization mortality rate was 10%. Poor prognosis 34% and fully recovery 56 % were observed. In this retrospective cohort study, a lactate level of more than 2.5mmol/L was the best threshold to predict 28-day mortality among severe sepsis and septic shock patients. In our research, we found mean LC 6 h 3.08mmol/L, and after 48 h mean it is 1.79mmol/L. Significant LC 6 h found, which is 8.08mmol/L in the death group patient where 48 h mmol/L shows significant high. Poor prognosis also presents a clinical increase of lactate level high in the LC 6 h analysis, which is 3.32mmol/L. Recovered patients showed a significant improvement after administering treatment depending on the patient organ involvement and good decrease of lactate reports achieved, which is 1.20mmol/L, where admission reports show it was 1.91mmol/L in LC 6 h. Mean Heart rate 94/51mmhg, pulse 119, temperature 39℃, respiratory rate 32.26, and urine output 456 ml recorded during our study. Death patient shows a remarkable detonation of those reports but has a significant clinical report with the recovered patients. Conclusion: The early lactate dynamic monitoring index has a high value in predicting sepsis and septic shock patients' prognosis, thus worth popularizing.

Leishmaniasis is a group of neglected infectious, non-contagious diseases caused by parasites of the Leishmania genus which affects millions of people worldwide. The drugs available for its treatment, especially in cases of visceral leishmaniasis, are old, outdated, have serious side effects and in many cases are ineffective due to the emergence of resistant strains. In this context, the search for new candidates for more effective and safer drugs which can become new therapeutic alternatives is a constant need. In this work, 10 new chalcones were synthesized in high yields through Claisen-Schmidt condensation and were evaluated in vitro against Leishmania infantum promastigotes and amastigotes. CP04 and CP06 compounds were the most promising, respectively showing IC50 values = 13.64 ± 0.25 and 11.19 ± 0.22 against promastigotes, and IC50 = 18.92 ± 0.05 and 22.42 ± 0.05 against amastigotes. The compounds did not show cytotoxicity in erythrocytes, showing selectivity indexes greater than 74 and 90. Molecular docking studies carried out under the sterol 14-alpha demethylase (CYP-51) (PDB: 3L4D) and trypanothione reductase (PDB: 5EBK) enzymes from L. infantum evidenced the great affinity of the CP04 molecule for these targets, showing Moldock score values of -94.0758 and -50.5692 KJ/mol-1, with these values being much lower than the co-crystallized ligand energies. Molecular dynamics simulations demonstrated great stability of CP04 in its targets, thus indicating a real interaction possibility. Our findings confirm the potential that chalcones have as candidates for anti-leishmania drugs, and suggest that the CP04 compound may become a promising drug candidate to design and develop novel chalcone-based analogs for leishmaniosis therapy.

Large water bodies such as the Laurentian Great Lakes have significant influences on local and regional climate through their unique physical features. Due to the coarse spatial resolution of general circulation models (GCMs), the Great Lakes are geometrically ignored in most GCMs. Thus, the dynamical downscaling technique serves as a necessary and feasible solution to bridge the gap. The Weather Research and Forecasting model (WRF) with an updated lake scheme is employed to downscale from a GCM, GFDL-CM3. The WRF-Lake’s performance is evaluated against observations, the GCM, as well as 23 other GCMs. Results show that the coupled air-lake model, with a fine spatial resolution and realistic lake bathymetries, reproduced a more reasonable spatiotemporal climatology than GCMs, as well as the lake-induced characteristics that were missed in GCMs. With lakes present, the seasonal variability of air temperature was reduced in WRF-Lake relative to GFDL-CM3, especially in summer. A reduced air temperature trend, about 4.5 °C/100 year in the 21st century, was projected in WRF-Lake. The seasonal evolutions of lake surface temperature and lake ice coverage were well captured by the lake model. The lake surface temperature was projected to be warming by 3.5-4 °C and the lake ice diminishing by 58.9% - 86%. Those results brought by the WRF-Lake model suggest that a fine resolution of the topography and the incorporation of the lake-atmosphere interactions are crucial to improve the understanding of the climate and climate change in the Great Lakes region.

A proxy war, between a coalition of countries, BLUE and a country, RED, is considered. RED wants to increase the size of the RED territory. BLUE wants to involve more regions in trade and other types of cooperation. GREEN is a small and independent nation that wants to become a member of BLUE. RED attacks GREEN and tries to invade. BLUE decides to give optimal arms support to GREEN. This support can help GREEN in the war against RED and simultaneously reduce the military power of RED, which is valuable to BLUE, also outside this proxy war, since RED may confront BLUE also in other regions. The optimal control problem of dynamic arms support, from the BLUE perspective, is defined in general form. The objective function is a weighted sum of the present value of the free GREEN territory and the present value to BLUE of the net loss of military resources in the RED army. The net loss of RED at a particular point in time is a function of the location of the front line and the size of the mobile GREEN forces behind the RED line. First, it is assumed that the expected net loss is proportional to the force ratio behind the red front line. It is proved that the net loss function is a strictly concave quadratic function of x, the location of the front line. It is also proved that the unique maximum of the net loss function occurs at the same front location, also if the net loss function is proportional to the strength ratio behind the RED lines, raised to any strictly positive exponent. From the BLUE perspective, there is an optimal position of the front. This position is a function of the weights in the objective function and all other parameters. Optimal control theory is used to determine the optimal dynamic BLUE strategy, conditional on a RED strategy, which is observed by BLUE military intelligence. The optimal arms support strategy for BLUE is to initially send a large volume of arms support to GREEN, to rapidly move the front to the optimal position. Then, the support should be almost constant during most of the war, keeping the war front location stationary. In the final part of the conflict, when RED will have almost no military resources left and tries to retire from the GREEN territory, BLUE should strongly increase the arms support and make sure that GREEN rapidly can regain the complete territory and end the war

Fuel consumption, subsequent emissions and safe operation of class 8 vehicles are of prime importance in recent days. It is imperative that the vehicle operates in its true optimal operating region given a variety of constraints such as road grade, load, gear shifts, Battery State of charge (for hybrid vehicles), etc. In this paper a research study is conducted to evaluate the fuel economy and subsequent emission benefits when applying predictive control to a mild hybrid line haul truck. The problem is solved using a combination of dynamic programming with back tracking and model predictive control. The specific fuel saving features that are studied in this work are dynamic cruise control, gear shifts, vehicle coasting and torque management. These features are evaluated predictively as compared to a reactive behavior. The predictive behavior of these features are a function of road grade. The result and analysis shows significant improvement in fuel savings along with NOx benefits. Out of the control features dynamic cruise (predictive) control and dynamic coasting showed the most benefits while predictive gear shifts and torque management (by power splitting between battery and engine) for this architecture did not show fuel benefits but provided other benefits in terms of powertrain efficiency.

Websites and applications use personalisation services to profile their users, collect their patterns and activities and eventually use this data to provide tailored suggestions. User preferences and social interactions are therefore aggregated and analysed. Every time a user publishes a new post or creates a link with another entity, either another user, or some on-line resource, new information is added to the user profile. Exposing private data does not only reveal information about single users' preferences, increasing their privacy risk, but can expose more about their network that single actors intended. This mechanism is self-evident on \emph{social networks} where users receive suggestions based on their friends' activity. We propose an information theoretic approach to measure the differential update of the anonymity risk for time-varying user profiles. This expresses how privacy is affected when new content is posted and how much third party services get to know about the users when a new activity is shared. We use real Facebook data to show how our model can be applied on a real world scenario.

In this paper is shown the dynamic modeling and design of a passivity based controller for the RV-3SB robot. Firstly, the dynamic modeling of the of the Mitsubishi Rv-3SB robot is done by the Euler-Lagrange formulation in order to obtain a decoupled dynamic model considering the actuators orientation besides the position of this analyzed robot. It is important to remark that the dynamic model of the RV-3SB robot is done based in the kinematic model obtention in which is developed by the implementation of screw theory. Then the passivity based controller is obtained by separating the end effector variables and the actuator variables by making an appropriate coordinate transformation. The passivity based controller is obtained by selecting an appropriate storage function and by the Lyapunov theory the passivity based control law is obtained in order to drive the error variaable, which is the difference between the measured end effector position variable and the end effector desired position variable. The passivity based controller makes that the error variable reach the origin in finite time taking into consideration the dissipation properties of the proposed controller in order to stabilizes the desired end effector position. A numerical simulation experiement is performed in order to validate the theoretical results obtained in this research study. It is verified by numerical experimentation that the proposed control strategy is efficient and effective in order to drive the error variable to the origin in comparison with other modified techniques found in the literature. Finally, the appropriate discussion and conclusion of this research study are provided.

This report discusses the application of approximate dynamic programming (ADP) and Krylov subspace methods in solving sequential decision-making problems in machine learning. ADP is used when dealing with large state spaces or when the exact dynamics are unknown. The paper explores various ADP methods such as temporal difference learning and least-squares policy evaluation. The authors also focus on the use of Krylov subspace methods for solving the Bellman equation in ADP. The report provides insights into linear approximation, stochastic algorithms, and the Arnoldi algorithm for orthonormal basis. Overall, the paper highlights the theoretical foundation provided by ADP and its connection with Krylov subspace methods, shedding light on their application in computer science.

The study of values at European and global level has gained momentum along with the theory of values launched by Schwartz. Values are dormant, hidden, unobservable and impossible to measure directly. They exist somewhere within the human being, manifested by different attitudes, depending on their degree of generality. The paradigm of basic human values implies shared universal values that are encountered in cultures all over the world. The theory of values designed by Schwartz has refined the pool of 19 basic individual values representing principles in individuals and group, further describing the dynamic relationships among them. This study presents practical evidence of the dynamics between individual values, the dynamics theorized by Schwartz in 2012. Following the development of an online questionnaire made up of 46 items with online responses options on a Lickert scale from 1 to 6, where 1 represents less important and 6 represent very important, 220 young people from Western Romania voluntarily responded. By testing the hypothesis assuming the dynamic relationship between the two values through multiple regression analysis, the results demonstrate that in Model 1, which involves a linear relationship, health explains 42% of the variance in security with a F =161,215 significant at p <.01. In Model 2, which involves a curvilinear relationship, health explains 50% of the variance in security version with a F = 35,336 significant at p <.01. The incremental prediction optimization of 8% added by including the squared security accounts for the curve in the regression line, indicating the existence of a curvilinear relationship between security and health. The dynamic relationship demonstrates that upper limit and lower limit aspects of security, significantly influence the health value in a negative way. Normal levels of security trigger a high level of prioritization of health value. The implications of this type of relationship are discussed in explaining the value phenomenon at individual level. The study shows limits due to the selected sample, focusing exclusively on young people with higher education from the Western region of Romania. This sample was the target group of "The National Identity of Romanian Youth" project which designed this research.

A Smart Home is characterized by the presence of a huge number of small, low power devices, along with more classical devices. According to the Internet of Things (IoT) paradigm, all of them are expected to be always connected to the Internet in order to provide enhanced services. In this scenario, an attacker can undermine both the network security and the user’s security/privacy. Traditional security measures are not sufficient, because they are too difficult to setup and are either too weak to effectively protect the user or too limiting for the new services effectiveness. The paper suggests to dynamically adapt the security level of the smart home network according to the user perceived risk level what we have called network sentiment analysis. The security level is not fixed, established by a central system (usually by the Internet Service Provider) but can be changed with the users cooperation. The security of the smart home network is improved by a distributed firewalling and Intrusion Detection Systems both to the smart home side as to the Internet Service Provider side. These two parts must cooperate and integrate their actions for reacting dynamically to new and ongoing threats. Moreover, the level of network sentiment detected can be propagate to nearby home networks (e.g. the smart home networks of the apartments inside a building) to increase/decrease their level of security, thus creating a true in-line Intrusion Prevention System (IPS). The paper also presents a test bed for Smart Home to detect and counteract to different attacks against the IoT devices,,Wi-Fi and Ethernet connections .

This paper studies a model of dynamic compensation and capital structure with managerial traits. We show that Optimistic manager perceives equity as more undervalued than debt, while, confident manager perceives debt as more undervalued than equity. Managerial risk aversion mitigates manager’s bias. The risk aversion of the optimistic manager has a convex effect on the optimal coupon. There exists the level of risk aversion eliminating the bias on the leverage. The managerial optimist has an ambiguous effect on the owner’s bankruptcy level. The risk aversion has a convex effect on the owner’s bankruptcy level. The optimistic/confident manager underestimates the credit spread. The risk aversion has convex effect on the credit spread. In contrast to rational manager, the optimistic/confident manger has higher level of effort. The risk aversion has a negative effect on the effort.

The effects of psychological pressure on perceiving the height of a jump bar just before starting a high jump run was investigated. University students (N = 14) training for a high jump event performed 15 trials (3 practice, 6 pressure, and 6 non-pressure) in counterbalanced order in their daily practice environment. The height of the bar was judged as significantly higher on pressure trials compared to non-pressure trials. A regression analysis indicated that participants who reported increased subjective perceived pressure tended to judge the bar to be higher. There was no significant difference between pressure and non-pressure trials for the performance index, defined as the success rate. This study provides the first evidence that environmental perceptions prior to executing a motor task under pressure may make performance of the task appear to be more difficult.

Environmental decentralization (ED), or the allocation of environmental protection affairs and responsibilities among various administrative authorities, affects the effectiveness of environmental regulation in promoting green total factor productivity (GTFP). Based on panel data of 30 Chinese provinces from 2001 to 2015, this paper employs dynamic panel models to test the effects of environmental regulations (environmental protection investment, ENV; pollutant discharge fees, PDF) on GTFP, with or without being influenced by ED. Without the impact of ED, GTFP is significantly inhibited by ENV while significantly promoted by PDF. Considering the impact of ED, with the strengthening of ED, the negative effects of ENV on GTFP is significant; contrarily, the positive effects of PDF on GTFP is significant; improving provincial ED adds negative effects of ENV, while reduces the positive effects of PDF; increasing prefectural ED reduces negative effects of ENV; expanding county-level ED adds the positive effects of PDF. Therefore, to boost GTFP growth, prefectural environmental protection authorities should have more autonomy in ENV, while the county-level should have more autonomy in PDF.

Oleanolic acid (OA) being the ubiquitous compound in the plant kingdom is studied for both the neuroprotective and neurotoxic properties. The mechanism of acetylcholinesterase (AChE) inhibitory potential of OA is investigated using the molecular dynamic simulations (MD) and docking as well as membrane-like and in vitro tests. There are also applied SH-SY5Y human neuroblastoma cells as well as in vivo on the zebrafish tests. The inhibitory potential towards the AChE enzyme is examined using the TLC-bioautography assay (the IC50 value is 9.22 μM). The CH- interactions between the central fragment of the ligand molecule and the aromatic cluster created by the His440, Phe288, Phe290, Phe330, Phe331, Tyr121, Tyr334, Trp84 and Trp279 side chains are observed. The in vitro tests carried out on the SH-SY5Y cells indicates that the viability rate is reduced to 71.5%, 61%, and 43% at the concentrations of 100 µg/mL, 300 µg/mL, and 1000 µg/mL, respectively after 48 hours of incubation whereas cytotoxicity against the tested cell line with the IC50 value is 714.32 ± 32.40 µg/mL. The in vivo tests on the zebrafish prove that there is no difference between the control and experimental groups as regards the mortality rate and morphology (P>0.05).

Power and energy efficiency are among the most crucial requirements in high-performance and other computing platforms. This work examines through extensive experimentation methods and procedures suitable for assessing the power and energy efficiency of fundamental hardware building blocks inside a typical high-performance CPU, focusing on the dynamic branch predictor (DBP). The investigation relies on the Running Average Power Limit (RAPL) interface from Intel, a software tool for credibly reporting the power and energy based on instrumentation inside the CPU. We use well-known microbenchmarks under various run conditions to explore potential pitfalls and to develop precautions to raise the precision of the measurements obtained from RAPL for more reliable power estimation. The authors discuss the factors that affect measurements and share the difficulties encountered and the lessons learned.

Dynamic Realistic Failure Process Analysis (DRFPA) is a numerical software based on FEM it is firstly validated by comparing with the experimental test. Such validation is carried out under two consistent concrete specimens under uniaxial compression. After validation, DRFPA is used to study the influence of two parallel pre-existing crack inclination angles on the fracture of concrete under dynamic loads. The evolution of wing cracks and secondary cracks is investigated by observing the initiation, coalescence, and propagation of them. Meanwhile, the relationship between failure mode and inclination angles is discussed via analyzing the acoustic emission events. Finally, it is concluded the relationship between inclination angles of pre-cracks and performance/stability of concrete structure.

As a special class of “green” elastomers, thermoplastic vulcanizates (TPVs) have been widely used in industries due to the combination of the excellent resilience of conventional elastomers and the easy recyclability of thermoplastics. Here, the morphology evolution of TPVs based on polyamide 6/ethylene-propylene-diene rubber (PA6/EPDM) blends was investigated by varying the content of the curing agent, phenolic resin (PF). With the incorporation of 6 wt% PF, the gel content of the EPDM phase reaches a high value of 49.6wt% and a typical sea-island structure is formed with EPDM domain in a micro-nano size. The dynamic rheology behaviors of TPVs showed that with the curing degree of EPDM phase increasing, a denser network of EPDM particles is formed in PA6 matrix. Also, a lower crystal degree and crystal peak temperature are observed, indicating that the presence of a growth restriction of PA6 crystal plate induced by a thinner plastic layer between the adjacent EPDM particles. However, the crystal form of PA6 is not changed with the increasing curing degree of the EPDM phase. This study provides an effective strategy to realize a new kind of TPVs, which can be easily introduced into industrial applications.

Oncogenic protein E6 from Human Papilloma Virus 16 (HPV-16) mediates the degradation of Membrane-associated guanylate kinase with inverted domain structure-1 (MAGI-1), throughout the interaction of its protein binding motif (PBM) with the Discs-large homologous regions 1 (PDZ1) domain of MAG1-1. Generic variation in the E6 gene that translates to changes in the protein’s amino acidic sequence modifies the interaction of E6 with the cellular protein MAGI-1. MAGI-1 is a scaffolding protein found at tight junctions of epithelial cells, where it interacts with a variety of proteins regulating signaling pathways. MAGI-1 is a multidomain protein containing two WW (rsp-domain-9), one guanylate kinase-like, and six PDZ domains. PDZ domains played an important role in the function of MAGI-1 and served as targets for several viral proteins including the HPV-16 E6. The aim of this work was to evaluate, with an in silico approach, employing molecular dynamics simulation and protein-protein docking, the interaction of the intragenic variants E-G350 (L83V), E-C188/G350 (E29Q/L83V), E-A176/G350 (D25N/L83V), E6-AAa (Q14H/H78Y/83V) y E6-AAc (Q14H/I27RH78Y/L83V) and E6-reference of HPV-16 with MAGI-1. We found that variants E-G350, E-C188/G350, E-A176/G350, AAa and AAc increase their affinity to our two models of MAGI-1 compared to E6-reference.

This work investigates the influence of strain rate on the stress/strain behaviour of Scalmalloy. This material is an aluminium-scandium-magnesium alloy, specifically developed for additive manufacturing. The bulk yield stress of the material processed by Selective Laser Melting is approximately 340 MPa which can be increased by heat-treating to approximately 530 MPa. These numbers, combined with the low mass density of 2.7 g/cm3, make Scalmalloy an interesting candidate for lightweight crash-absorbing structures. As this application is inherently dynamic, it is of interest to study the loading rate sensitivity, which is difficult to predict: Al-Sc alloys exhibit classic strain rate sensitivity with an increased yield stress at elevated strain rates. However, Al-Mg alloys are known to show the contrary effect, they exhibit less strength as strain rate is increased. To answer the question how these effects combine, we study the dynamic behaviour at four different strain rates ranging from 10−3 /s to 1000 /s using servo-hydraulic and Split-Hopkinson testing methods. The resulting data is analysed in terms of strain rate sensitivity of tensile strength and failure strain. A constitutive model based on a simplified Johnson-Cook approach is employed to simulate the tensile tests and provides good agreement with the experimental observations.

Digital twins are the foundation of autonomous off-road vehicles. Dynamic reduction methods are one of several ways to develop digital twins for off-road vehicles. The article commences with a comprehensive overview of the most widely used dynamic reduction methods and then introduces performance metrics for assessing their efficacies in the context of digital twins. The paper additionally includes a detailed mathematical derivation of the state-space representation for reduced-order finite element models. The state-space representation of the reduced finite element models facilitates their export to problem-solving environments for dynamic analysis. The state-space models are eventually solved utilizing the built-in libraries of numerical solvers in textual and graphical programming platforms. In addition, the article identifies the set of solvers that best suit the simulation of virtual models for off-road vehicles. This article also includes an evaluation of the simulation results of digital models with modes ranging from 0 to 30 Hz. In addition, the article demonstrates the lower bound of the frequency range necessary and sufficient to be retained in off-road vehicle virtual models. Finally, the paper presents the simulation outcomes for digital models of commercial off-road vehicles with custom-built control, electrical, and control systems.

5G heterogeneous network overlaid by millimeter-wave (mmWave) access employs mmWave meshed backhauling as a promising cost-efficient backhaul architecture. Due to the nature of mobile traffic distribution in practice which is both time-variant and spatially non-uniform, dynamic construction of mmWave meshed backhaul is prerequisite to support the varying traffic distribution. Focusing on such scenario of outdoor dynamic crowd (ODC), this paper proposes a novel method to control mmWave meshed backhaul for efficient operation of mmWave overlay 5G HetNet through Software-Defined Network (SDN) technology. Our algorithm is featured by two functionalities, i.e., backhauling route multiplexing for overloaded mmWave small cell base stations (SC-BSs) and mmWave SC-BSs’ ON/OFF status switching for underloaded spot. In this paper, the effectiveness of the proposed meshed network is confirmed by both numerical analyses and experimental results. Simulations are conducted over a practical user distribution modeled from measured data in realistic environments. Numerical results show that the proposed algorithm can cope with the locally intensive traffic and reduce energy consumption. Furthermore, a WiGig (Wireless Gigabit Alliance certified) device based testbed is developed for Proof-of-Concept (PoC) and preliminary measurement results confirm the proposed dynamic formation of the meshed network’s efficiency.

The technique of superposition of motions in the space of Lagrange variables is described, which allows us to obtain the equations of combined motion by replacing the Lagrange variables of superimposed (external) motion with Euler variables of nested (internal) motion. The components of velocity and acceleration in the combined motion obtained as a result of differentiating the equations of motion in time coincide with the results of vector addition of the velocities and accelerations of the particles involved in the superimposed motions at each moment of time. Examples of motion and superposition descriptions for absolutely solid and deformable bodies with equations for the main kinematic characteristics of motion, including for robot manipulators with three independent drives, pressing with torsion, bending with tension, and cross– helical rolling, are given. For example, given the fragment of calculation of forces in the kinematic pairs shown the advantages of the description of motion in Lagrangian form for the dynamic analysis of lever mechanisms, allows to determine the required external exposure when performing the energy conservation law at any time in any part of the mechanism.

The purpose of this paper is to provide empirical evidence to water policy-makers and the evaluation of the application of economic instruments such as price and other factors affecting demand, they contribute to improved decision-making around water management in the Biosphere Reserve El Vizcaino, Mexico. It was estimated a dynamic function with average price specification and other price perception specification. The findings show that consumers react to average price perceived and not the marginal price; long-run price elasticity is higher than short-run and both elasticities are inelastic. Elasticities inelastic with rising prices generate high incomes to improve water planning, supply quality and expand service coverage. The results suggest that the level of knowledge of users on the price is key to take into account restructuring rates in a scenario where the consumer has asymmetric information and themselves achieve goals of economic efficiency, social equity and environmental sustainability.

This paper presents a robust method based on graph topology to find the topologically correct and consistent subset of inter-robot relative pose measurements for multi-robot map fusion. However, the absence of good prior gives a severe challenge to distinguish the inliers and outliers, and wrong loop closures can seriously corrupt the fused global map. Existing works mainly rely on the consistency of spatial dimension to select inter-robot measurements, which does not always hold. In this paper, we propose a fast inter-robot loop closure selection method that integrates the consistency and topology relationship of measurements, which both conform to the continuity characteristics of similar scenes and spatiotemporal consistency. The traditional high-dimensional consistency matrix is decomposed into the sub-matrix blocks corresponding to the overlapping trajectory area. Building on this logic, a clustering method involving topology correctness of inter-robot loop closures is introduced to split the entire measurement set into multiple clusters. We define the weight function to find the maximum cardinality subset with topologically correct and consistent, then convert the weight function to a maximum clique problem in the graph and solve it. We evaluate the performance of our method in a simulation and in a real-world experiment. Compared to state-of-the-art methods, the results show that our method can achieve competitive performance in accuracy while reducing computation time by 75%.

Comparison between hydraulic and hydrologic computational methods is conducted in this study, regarding prismatic open channels under unsteady subcritical flow conditions. One-dimensional unsteady flow continuity and momentum equations are solved using explicit and implicit finite difference schemes for a symmetrical trapezoidal cross section, where the flow discharge and depth are the dependent variables. The results have been compared to those derived from Muskingum-Cunge hydraulic/hydrologic method as well as the commercial software HEC-RAS. The results from explicit and implicit code compare well to those from commercial software and hydraulic/hydrologic methods for long prismatic channels, thus directing the hydraulic engineer to quick preliminary design of prismatic open channels for unsteady flow with satisfactory accuracy.

Based on the fractional order of nonlinear system for love model with a periodic function as an external force, analyzed the characteristics of the chaotic dynamic in this study. The relationship between the chaotic dynamic of the fractional-love model with the external force and the fractional-order system was analyzed when the parameters are fixed. Further, we also studied the relationship between the chaotic systemic dynamic and the parameters when the fractional-order system is fixed. The results show that when the parameters are fixed, the fractional-order system exhibited segmented chaotic states for the different fractional orders of the system. When fixed the fractional-order system, the system exhibited the periodic and chaotic states as parameter changes.

This paper presents a limited scope dynamic probabilistic risk assessment (D-PRA) on the survivability of commercial of the shelf (COTS) drones tasked with surveilling areas with varying radiation levels after a nuclear accident. The D-PRA is based on a discrete-dynamic event tree (D-DET) approach, which couples with the OpenEPL error propagation framework to model sequences leading to Loss of Mission (LOM) scenarios due to component failures in the drone’s navigation system. Radiation effects are simulated by calculating the total ionizing dose (TID) against the permissible limit per component, and errors are propagated within the electronic hardware and software blocks to quantify navigation system availability per radiation zone. The proposed methods are integrated into the traditional event tree/fault tree approach and the most vulnerable components are radiation-hardened (RAD-HARD) to the extent specified by a predefined mission success criterion. The results demonstrate the usefulness of the proposed approach in performing trade studies for incorporating COTS components into RAD-HARD drone designs.

This paper presents the results of investigations of the effects of hot deformation parameters in compression investigation on the austenite grain size in HSLA steel (0.16% C, 0.037% Nb, 0.004% Ti, 0.0098% N). The axisymmetric compression investigations were performed on cylindrical investigation specimens of d=1.2 using the Gleeble 3800 simulator. The strain rate=1s^-1÷15.9s^-1 and strain degree ε=1.2. Before deformation, the research specimens were austenitized at TA = 1100 ÷ 1250 °C. Metallographic observations of the primary austenite grains were conducted with an optical microscope, while the structure of dynamically recrystallized austenite, inherited by martensite, was examined by EBSD technique using a scanning electron microscope. Based on the analysis of investigation results, it was found that the size of dynamically recrystallized austenite grains in HSLA steel were clearly affected by hot compression parameters. In contrast, no significant impact of austenitising temperature on their size was found.

Human behaviour was tipped as the mainstay in the control of further SARS-CoV-2 (COVID-19) spread especially after the lifting of restrictions by many countries. Countries in which restrictions were lifted soon after the first wave, had subsequent waves of the COVID-19 infections and it remains to be seen whether there will be more waves. In this paper, we formulate a deterministic model for COVID-19 incorporating dynamic non-pharmaceutical interventions, dubbed social dynamics. The model steady states are determined and their stability analysed. Numerical simulations are carried out to determine the pack of various parameters that influence the social dynamics. In South Africa, the first wave was the only wave in which the only interventions rested solely on human behavior. The model is thus fitted to COVID-19 data on the first wave in South Africa. The results presented in this paper have implications on the trajectory of the pandemic in the presence of changing social processes.

Porous metals possess low bulk density, large specific strength, high stiffness and special thermal, electromagnetic and acoustic conductivity, so that porous metals are widely used in filtration and separation, flame retardant explosion-proof, biomedical application, etc. Compared with its corresponding dense metal, the presence of porous structures also leads to different corrosive performances of porous metal. So, some researches have utilized weight loss method, electrochemical impedance to evaluate porous metals’ corrosion behavior; however, the influence of pore structure on metal corrosion is still controversial, and present methods used for analyses of porous metals’ corrosion are statistical averages of the corrosion behavior of the entire porous material, which cannot accurately reflect the corrosion behavior inside the pore structure. Herein, we prepare porous copper samples with 0, 24, 72, 96 pores using mechanical process, and employ scanning kelvin probe combined with electrochemical polarization curve and impedance spectroscopy to test the corrosion performance of the porous copper in static and dynamic NaCl solution. The relevant results indicate that in static solution, the corrosion resistance of samples gradually increases with the rise of the number of pores. By contrast, the sample with 24 pores exhibits more susceptible to corrosion than the sample without pore.

Ubiquitin-specific protease 14 (USP14) is a member of the Deubiquitinating enzymes (DUBs) involved in disrupting the regulation of the ubiquitin-proteasome system, responsible for the degradation of impaired and misfolded proteins which is an essential mechanism in eukaryotic cells. The involvement of USP14 in cancer progression and neurodegenerative disorders has been reported. Thereof USP14 is a prime therapeutic target; hence, designing efficacious inhibitors of USP14 is central in curbing these conditions. Herein, we relied on structural bioinformatics methods incorporating molecular docking, Molecular Mechanics Generalized Born Surface Area (MM-GBSA), Molecular dynamics simulation (MD simulation) and ADME to identify potential allosteric USP14 inhibitors. A library of over 733 compounds from the PubChem repository with >90% match to the IU1 chemical structure was screened in a multi-step framework to attain prospective drug-like inhibitors. Two potential lead compounds (CID 43013232 and CID 112370349) were shown to record better binding affinity compared to IU1, but with subtle difference to IU1-47, a 10-fold potent compound when compared to IU1. The stability of the lead molecules complexed with USP14 was studied via MD simulations. The molecules were found to be stable within the binding site throughout the 50ns simulation time. Moreover, the protein-ligand interactions across the simulation run time suggest Phe331, Tyr476, and Gln197 as crucial residues for USP14 inhibition. Furthermore, in silico pharmacological evaluation revealed the lead compounds as pharmacological sound molecules. Overall, the methods deployed in this study revealed two novel candidates that may show selective inhibitory activity against USP14, which could be exploited to produce potent and harmless USP14 inhibitors.

Neuromuscular disorders cause progressive muscular weakness, which limits upper extremity mobility and performance during activities of daily life. A dynamic arm support can improve mobility and quality of life. However, their use is often discontinued over time for unclear reasons. This study aimed to evaluate whether users of dynamic arm supports demonstrate and perceive quantifiable mobility benefits over a period of two months. Nine users of dynamic arm supports were included in this observational study. They had different neuromuscular disorders and collectively used four different arm supports. They were observed for three consecutive weeks during which they were equipped with a multi-sensor network of accelerometers to assess the actual use of the arm support and they were asked to provide self-reports on the perceived benefits of the devices. Benefits were experienced mainly during anti-gravity activities and the measured use did not change over time. The self-reports provided contextual information in domains such as participation to social life, in addition to the sensor system. However self-reports overestimated the actual use by up to three-fold compared to the accelerometer measures. A combination of objective and subjective methods is recommended for meaningful and quantifiable mobility benefits during activities of daily life.

Stress relaxation tests in cantilever bending were performed on the C7025 and C7035 alloys at 298K and 393K，respectively. The effect of stress-relief treatments on stress relaxation properties was investigated. The structural changes associated with the stress relaxation process were examined using transmission electron microscope. The stress relaxation curve fits well to empirical formula σ*=[Kˊln(t+α₀)+C]^-n for stress relaxation. The curves can be split into two stages. The stress relax quickly in the first stage, slows down in the second stage, and tends to be a certain limit value after a long time. The curve and microstructure reveals that the C7035 alloy has a lower rate of stress relaxation and a higher anti-stress relaxation capacity than the C7025. The first reason is that the movement of vacancies required by spinodal decomposition is inhibited, and the quantity of cobalt -containing vacancies decreases dramatically in the C7035 alloy. The other reason is that the precipitated phases became uniformly diffused in the C7035 alloy. The precipitate phase uniformly distributes in the grain boundaries and the matrix, during the relaxed condition, and thus the dislocations moving is blocked by the precipitates.

Positive invariant set is an important concept of dynamic systems. The purpose of this paper is to study the sufficient and necessary conditions that the set of ellipsoids and the Lorenz cone are positive invariant sets of discrete time systems. By means of nonlinear programming and induced norm, the problem of positive invariance is formulated as an optimization problem, and the equivalent dual form optimization is also presented using the dual optimization method. Our results provide more alternative methods for determining the positive invariance of quadratic form convex sets from the point of view of optimization and dual optimization. The effectiveness of this method is demonstrated by numerical examples.

The fault diagnosis of the gearbox is primarily based on the analysis of the harmonic response. However, the generation mechanism of the harmonic response of the gear pair is still not distinctly explained in a healthy gearbox. Therefore, this paper is dedicated to establishing a dynamic model of the gearbox for this issue. In this model, the contact force of the bearing and the meshing stiffness of the gear pair are determined by the Hertz theory and the potential energy method, then the shaft motion is used as the connection to establish the coupling relationship between the gear pair and the bearing. After this dynamic model is confirmed by experiments and existing models, the coupling relationship inside the gearbox and the harmonic response of the gear pair are studied using this model. The result demonstrates that a closed control loop is formed due to the vibration transmission between the gear pair, the bearing and the shaft, and there is a strong coupled vibration between the gear pair and the bearing in the gearbox. Due to the generation of the center distance error, misalignment angle and disorganized meshing process of the gear pair, the meshing stiffness is altered, which excites the harmonic response of the gear pair. When the speed of the gearbox is increased, although the vibration amplitude of the gearbox is increased, the system predominantly vibrates at the fundamental frequency, and the harmonic of the gear pair is also shifted to the low frequency band.

The damage evolution rules of coal under true triaxial combined static-dynamic loads are important to understand and reveal the mechanism of rockburst in coal mines. The numerical simulation was carried out using FLAC3D to explore the coupling effect of static and dynamic stress, especially the influence of dynamic load parameters. The results show that the increase of dynamic load amplitude not only makes the plastic zone grow exponentially and shorten the damage development time, but also decreases the residual strength of the coal sample, which leads to a much more violent of the dynamic failure. The stress wave can propagate more stable in the coal sample with the increase of dynamic load frequency and the development time of the plastic zone also show synchronous fluctuating features, and when the frequency is like the intrinsic frequency of the coal sample, the dynamic load has a significant stimulate effect. The static and dynamic loads have different damage effect to the coal sample under true triaxial stress path, the weight decreases in order of the minimum principal stress, the maximum principal, the amplitude of the dynamic load and at last the dynamic stress frequency by the entropy weight method analysis.

Liquid and gas are distinct in their extent of dynamic atomic correlations; in gas atoms are almost uncorrelated whereas they are strongly correlated in liquid. This distinction applies also to electronic systems. Fermi liquids are actually gas-like, whereas strongly correlated electrons are liquid-like. Doped Mott insulators share characteristics with supercooled liquids. Such distinctions have important implications on superconductivity. We discuss the evolution of dynamic atomic correlations in liquid with temperature, and a possible effect of dynamic correlations on the high-temperature superconductivity in the cuprates.

Considering the dynamic stall effects in engineering calculations is essential for correcting the aerodynamic loads acting on wind turbines, both during power production and stand-still cases, and impacts significantly the turbine aeroelastic stability. The employed dynamic stall model needs to be accurate and robust for a wide range of airfoils and range of angle of attack. The present studies are intended to demonstrate the performance of a recently implemented "IAG dynamic stall" model in a wind turbine design tool Bladed. The model is transformed from the indicial type of formulation into a state-space representation. The new model is validated against measurement data and other dynamic stall models in Bladed for various flow conditions and airfoils. It is demonstrated that the new model is able to reproduce the measured dynamic polar accurately without airfoil specific parameter calibration and has a superior performance compared to other models in Bladed.

Biofuels and biochemicals play significant roles in the transition towards a fossil-free society. However, large-scale biorefineries are not yet cost-competitive with their fossil-fuel counterparts, and it is important to identify biorefinery concepts with high economic performance. For evaluating early-stage biorefinery concepts, one needs to consider not only the technical performance and process costs but also the economic performance of the full supply chain and the impacts on feedstock and product markets. This article presents and demonstrates a conceptual interdisciplinary framework that can constitute the basis for evaluations of the full supply-chain performance of biorefinery concepts. This framework considers the competition for biomass across sectors, assumes exogenous end-use product demand, and incorporates various geographical and technical constraints. The framework is demonstrated empirically through a case study of a sawmill-integrated biorefinery producing liquefied biomethane from forestry and forest industry residues. The case study results illustrate that acknowledging biomass market effects in the supply chain evaluation implies changes in both biomass prices and the allocation of biomass across sectors. The proposed framework should facilitate the identification of biorefinery concepts with a high economic performance which are robust to feedstock price changes caused by the increase in biomass demand.

Based on the recorded watershed characteristics, the future conditions on the basin system can be predicted using a different method. In this study, dynamic land-use change and its impacts on the streamflow for the Dabus watershed were predicted using ANN-CA based method. The model performance for accurate prediction of the future land-use change on the Dabus River watershed has been checked by validation of the simulated value with the actual value, hence the overall kappa value (k) = 0.83 for the simulated 2016-LULC validated with actual 2016-LULC. Then, 2026-LULC was predicted based on the 2004 and 2009-LULC. The streamflow for the case of 2004 and 2009-LULC has been simulated using the SWAT model. The value of NSE = 0.87 and 0.90 was attained during validation of simulated streamflow for 2004 and 2009-LULC data cases, respectively. The agreement of simulated value of streamflow with the observed data is indicated as R2 = 0.91 and 0.96 for 2004-LULC and 2009-LULC. The effects of the dynamic land-use change on streamflow for the predicted land use(2026-LULC) catchment were evaluated by T-test analysis. Hence, T-stat =0.04 and -0.002 in the case of simulated streamflow used 2004-LULC and 2009-LULC, respectively compared with simulated value using 2026-LULC.

Mini-bioreactor systems enabling automatized operation of numerous parallel cultivations have been used to accelerate and optimize bioprocess development. As implementation of fed-batch conditions, multiple options of process control and sample analysis are possible, these systems represent valuable screening tools for large-scale production. However, the dynamic behavior of cultivations has not yet been considered regarding data evaluation and decision making during high-throughput screening in mini-bioreactors. In this study, the characterization of Saccharomyces cerevisiae AH22 secreting recombinant endopolygalacturonase is performed in 48 parallel fed-batch cultivations regarding 16 experimental conditions. Automated parallel process control, frequent sampling and analysis were implemented. Data-driven multivariate methods were developed to allow for fast, automated decision making as well as online predictive data analysis regarding endopolygalacturonase production. Using dynamic process information, a cultivation with abnormal behavior could be detected by principal component analysis as well as two clusters of similarly behaving cultivations, later classified according to the feeding rate. By decision tree analysis, cultivation conditions leading to an optimal recombinant product formation could be identified automatically. The developed method is easily adaptable and suitable for automatized process development reducing the experimental times and costs.

Dynamic visualizations have been developed to exchange information that transforms over time across a broad range of professional and academic contexts. However, these visual tools may impose substantial demands on the learner’s cognitive resources that are very limited in current knowledge. Cognitive load theory has been used to improve learning from dynamic visualizations by providing certain design techniques to manage learner cognitive load without adding any oral/written explanations. This systematic review examined a series of experimental studies assessing the roles of these design techniques in learning tactical scenes of play through dynamic visualizations. Electronic databases PubMed and Google Scholar were used to search relevant articles. Eleven studies were eventually included for the systematic review based on the eligibility criteria. The present review revealed that adapting design techniques to the level of learners’ expertise, type of depicted knowledge, and level of content complexity is a crucial part of effective learning.

Injuries to the ligaments of the knee are extremely common among athletes who participate in high-risk sports, or any sport that requires frequent cutting motions, jumping, or contact. In order to determine the best way to heal these injuries, it is important to understand not just the pathology of the injury, but also the biomechanical factors that are affected, including stability and steadiness. While many studies have been done to examine the stability of healthy knees, there is little to no existing literature on stability of knees afflicted by injury. In order to surpass this obstacle, static steadiness and dynamic stability data was collected using the Lockhart Monitor phone application and Xsens accelerometers, respectively, both before and after completion of a course of physical therapy in a patient with a grade 2 medial collateral ligament (MCL) tear. These results were then used to determine the degree to which the prescribed physical therapy protocol was effective in healing the MCL, which can be useful for tweaking the individual protocol for future conservative treatment and management of the injury.

Emergence of multi drug resistant (MDR) and extensively drug resistant (XDR) Mycobacterium tuberculosis poses a serious threat to TB control as the available treatment options are less effective in these cases. Therefore, new strategies are required for identification of new drugs and drug targets. The M. tuberculosis dihydrodipicolinate synthase is a putative drug target with no potent inhibitor. Here in this study, we have used a comprehensive computational approach to identify small molecule inhibitors and validated them in vitro. As similar structures tend to have similar functions, therefore 3 approaches, namely, (a) known inhibitor-based approach, (b) substrate analogues, (c) product analogues were used for compound screening from various chemical libraries. The fourth approach we have taken is fragment library screening.In vitro studies revealed that β-hydroxypyruvic acid tartronic acid are inhibitors of Mtb-rDapA with maximum inhibition 48% and 51% at 500µM concentrations respectively. We have also observed that β-hydroxypyruvic acid is a time dependent inhibitor of Mtb-rDapA. Further, thermal shift assays showed that β-hydroxypyruvic acid interacts with Mtb-rDapA and the thermal stability of Mtb-rDapA shifted by 3˚C. Among the product analogues of Mtb-DapA, dipicolinic acid showed to bind to Mtb-rDapB shifting thermal stability of Mtb-rDapB by 0.5˚C in binding. Additionally, we have designed a new approach by combining substrate and product analogues to achieve better inhibitions. In vitro assays validated that this combination approach increased maximum inhibition up to 100%. We envision that these compounds would serve as potent leads for tuberculosis drug discovery.

The utilization of primary school buildings is multifaceted, primarily due to the high occupancy density, varying thermal preferences among occupants, diverse indoor activities (such as walking, sports, and conversation), and a constant flow of individuals entering and exiting the building. This results in frequent opening and closing of external windows and doors and fluctuations in internal heat gain. Consequently, frequent interactions between the indoor and outdoor microenvironments lead to energy losses. This study conducts a comprehensive literature review on building energy loss stemming from occupant behavior and the interactions between indoor and outdoor microenvironments. Furthermore, it proposes a dynamic real-time monitoring system based on a computer data capture and visualization platform foundation for building energy loss. The research methods include data crawling, data association rule mining, and data association analysis. The research findings yield a universally applicable and informative building energy-saving design theory based on extensive data analysis. Additionally, the system presents information on occupants' behavior and the microclimate data of indoor and outdoor environments on a computer screen, facilitating human-machine communication and enabling timely adjustments to design strategies for new buildings and operation and maintenance strategies for existing buildings.

The modeling of tilting-pad journal and thrust bearings presents a level of complexity beyond that of bearings of fixed-arc geometry, particularly with regard to dynamic influences. With tilting-pad bearings, the theory surrounding the fluid film must be complemented with representative modeling of the pad dynamics. What has been recognized in recent decades has been the significance of the pad support, in particular the flexibility of the pivot region of the pad. The typical model for including the stiffness of the pivot has been based on Hertzian contact theory. Some researchers have been noting that the Hertzian theory does not permit sufficient flexibility in the pivot region. It is suggested that the contact mechanics at the pivot would be better represented as a pairing of rough surfaces. The modeling used here is based on a statistical asperity micro-contact theory for rough-surface line contact that has been extended to include contact stiffness. This model has been applied to the determination of the effective dynamic properties of tilting-pad bearings. The results show that pivot stiffness can be as low as one-third the stiffness determined by Hertzian theory. Comparison to published experimental results confirms the significance of the rough-surface modeling, particularly for the line contacts associated with rocker-back tilting pads.

Abstract: The Inconel 625 is a nickel-based alloy has been widely used in the high-temperature application. The Inconel 625 exhibits unstable plastic flow at elevated temperature characterized by serrated yielding, known as Portevin-Le Chatelier effect. The aim of this work is to evaluate the mechanical properties at high temperatures of the Inconel 625. The tensile tests were performed in the temperature range of room temperature until 1000 °C and strain rate of 2x10^-4 to 2x10^-3 s^-1. The creep tests were performed in the temperature range of 600-700 °C, in the stress range of 500-600 MPa in a constant load mode. The surface fracture was observed by optical and scanning electron microscopy. Serrated stress-strain behavior was observed in the curves obtained at 200 to 700 °C, which was associated with the dynamic strain aging effect. The yield strength and the elongation values show an anomalous behavior as a function of the test temperature. An intergranular cracking was observed specimen tensile tested at 500 °C that can be attributed to the decohesion of the carbides along the grain boundaries. The fracture surface of the specimen tensile tested at 700 °C showed the predominance of transgranular cracking with tear dimples with a parabolic shape.

Trajectory Optimization (TO) is the sequence of processes that are considered in order to produce the best path that mends the overall performance or reduces the consumption of the resources where the restriction system remains maintained. In this survey, an inclusive review of the latest advancements in modeling and optimization of trajectory generation in robotic applications will be discussed broadly. In recent times, numerous studies have employed optimal control techniques involving direct and indirect methods in order to convert the authentic Trajectory Optimization problem into a constrained parameter optimization problem. Moreover, a huge variety of optimization algorithms such as Genetic Algorithms (GA), Simulated Annealing (SA), Sequential Quadratic Programming (SQP), and Particle Swarm Optimization (PSO) are used aiming to find the optimal solutions for trajectory planning. It is observable that, minimizing the jerk, energy consumption, and execution time among the most widely used design objectives, on the other hand, the robot’s joints configurations and the motor torques are the most used design variables. This paper aims to review the fundamental techniques and their coincident robotic applications in the field of trajectory optimization aiming to afford some steering for related researchers.

This paper utilizes dynamic panel threshold technology to conduct a nonlinear test on the direct effect between environmental regulation and economic fluctuations and the effect of industrial structure upgrading by taking 35 industrial sectors in China from 2003 to 2016 . The research has found that there is an inverted "U" relationship between environmental regulation and economic fluctuations, with the enhancement of environmental regulations, the economic fluctuation increases first and then decreases. The cross-terms of environmental regulation and industrial structure rationalization or industrial structure upgrading are significantly negative, which indicates that the enhancement of environmental regulation is conducive to promoting industrial structure upgrading and reducing the economic fluctuations. While the rationalization factors of industrial structure and advanced industrial structure are significantly negative, indicating that both forms of industrial structure upgrading are conducive to reducing the economic fluctuations. Environmental regulation has technical innovation thresholds for industrial structure upgrading and economic fluctuations, but there are no human capital or FDI thresholds. In the rationalization model of industrial structure, there is a nonlinear "U" relationship between environmental regulation and economic fluctuations when the proportion of scientific research expenditure is more than 1.35%. With the enhancement of environmental regulation, the economic fluctuation reduces first and then increases, and the corresponding inflection point value is 2.398% of the environmental regulation level. At the same time, the environmental regulation can indirectly reduce economic fluctuations by pushing down the industrial structure upgrades. In the advanced model of industrial structure, there is a “U” relationship between environmental regulation and economic fluctuation when the proportion of scientific research expenditure is greater than 1.26%. With continuous enhancement of environmental regulation, the economic fluctuation reduces first and then increases. The corresponding inflection point value is 1.78% of the environmental regulation level, and environmental regulation can indirectly reduce economic fluctuations by promoting the industrial structure at the same time.

One of the most important problems of geotechnical engineering is the design of pile foundations. Piles are generally designed for vertical and horizontal static loads. However, it is important to design piles against dynamic loads in regions with high seismicity. This study verified a centrifuge experiment obtained from the literature with a finite element program. With the kinematic interaction analyses made for this purpose, the effect of parameters such as layered soil, groundwater, pile stiffness, and earthquake acceleration were investigated numerically. According to the results obtained, it was understood that the earthquake magnitude is the most important parameter in kinematic interaction analyses. In addition, in layered soil conditions, the fact that 75% of the pile length is in the weak soil creates the most unfavorable situation. It has been observed that pile stiffness and groundwater level also have certain effects on the kinematic interaction.

With the increasingly stringent airworthiness standards, the noise generated during the rotorcraft flight is gradually attracting people’s attention. It widely operated helicopters at low altitudes because of their maneuverability. The way to reduce the noise caused by the complex airflow of the helicopter rotor system has progressively become a hot topic for researchers. Using a hybrid acoustic analysis method, this paper investigates the improvement of the noise and thrust of the helicopter’s tail rotor through the tail rotor structural parameters. For the basic model, the turbulence simulation is performed using an incompressible detached eddy simulation (DES) method, and the Lighthill acoustic analog equation is calculated using the finite element method (FEM). We verified the accuracy of the method through wind tunnel tests. We chose a series of structural parameters for sound simulation and fluid simulation calculations. The results indicate that the modified tail rotor noise reduced by 16.5 dBA and the total thrust increased by 19.9% from the prototype model. This work can enhance the duct tail rotor design to improve aerodynamic and aeroacoustic performance.

Wireless Sensor Network is an emerging technology and the collaboration of wireless sensors becomes one of the active research areas to utilize sensor data. Various sensors collaborate to recognize the changes of a target environment, to identify, if occurs, any radical change. For the accuracy improvement, the calibration of sensors has been discussed, and sensor data analytics are becoming popular in research and development. However, they are not satisfactorily efficient for the situations where sensor devices are dynamically moving, abruptly appearing or disappearing. If the abrupt appearance of sensors is a zero-day attack and the disappearance of sensors is an ill-functioning comrade, then sensor data analytics of untrusted sensors will result in an indecisive artifact. The pre-defined sensor requirements or meta-data based sensors verification is not adaptive to identify dynamically moving sensors. This paper describes a deep-learning approach to verify the trustworthiness of sensors by considering the sensor data only, without having to use meta-data about sensors or to request consultation from a cloud server. The contribution of this paper includes 1) quality preservation of sensor data for mining analytics and 2) authenticity verification of dynamically moving sensors with no external consultation.

Magnetorheological (MR) fluids have been known to react to magnetic fields of sufficient magnitudes. While in the presence of the field the material develops a yield stress. The tunable property has made it attractive in e.g. semi-active damper applications in vibration control domain in particular. Within the context of a given application the fluids can be exploited in at least one of the fundamental operating modes of which the so-called gradient pinch mode has been least explored. Contrary to the other operating modes, the MR fluid volume in the flow channel is exposed to a non-uniform magnetic field in such a way that the Venturi-like contraction is developed in a flow channel solely by means of a solidified material in the regions near the walls rather than mechanically driven changes of the channel’s geometry. The pinch mode rheology of the material has made it a potential candidate in developing on a new category of MR valves. By convention, a pinch mode valve features a single flow channel with poles over which non-uniform magnetic field is induced. In this study the authors examine ways of extending the dynamic range of pinch mode valves by employing a number of such arrangements (stages) in series. To accomplish this, the authors developed a prototype of a multi-stage (three-stage) valve, and then compared its performance against that of a single-stage valve across a wide range of hydraulic and magnetic stimuli. To summarize, improvements in the pinch mode valve dynamic range are evident, however, at the same time it is hampered by the presence of serial air gaps in the flow channel.

Human civilizations are under enormous threats due to the outbreak of novel coronavirus (COVID-19) originated from Wuhan, China. The asymptomatic carriers are the potential spreads of this novel virus. Since, guaranteed antiviral treatments have not been available in the market so far, it is really challenging to fight against this contagious disease. To save the living mankind, it is urgent to know more about how the virus transmits itself from one to another quite rapidly and how we can predict future infections. Scientists and Researchers are working hard in investigating to understand its high infection rate and transmission process. One possible way to know is to use our existing COVID-19 infection data and prepare a useful model to predict the future trend. Mathematical modelling is very useful to understand the basic principle of COVID-19 transmission and provide necessary guidelines for future prediction. Here, we have reviewed 9 distinct commonly used models based on Mathematical implementations for COVID-19 transmission and dig into the deep head to head comparison of each model. Finally, we have discussed interesting key behaviour of each model, relevant upcoming important issues, challenges and future directions.

The sudden pervasive of severe acute respiratory syndrome Covid-19 has been leading the universe into a prominent crisis. It has influenced each zone, for example, industrial area, horticultural zone, Public transportation, economic zone, and so on. So as to see how Covid-19 affected the globe, we conducted an investigation characterizing the effects of the pandemic over the world using Machine Learning (ML) method. Prediction is a typical data science exercise that helps the administration with function planning, objective setting, and anomaly detection. We propose an additive regression model with interpretable parameters that can be naturally balanced by experts with domain intuition about the time series. We focus on global data beginning from 22^nd January 2020, till 26^th April 2020 and performed dynamic map visualization of Covid-19 expansion globally by date wise and predicting the spread of virus on all countries and continents. The major advantages of this work include accurate analysis of country-wise as well as province/state-wise confirmed cases, recovered cases, deaths, prediction of pandemic viral attack and how far it is expanding globally.

Dynamic measurement error correction is an effective method to improve the sensor precision. Dynamic measurement error prediction is an important part of error correction, support vector machine (SVM) is often used to predicting the dynamic measurement error of sensors. Traditionally, the parameters of SVM were always set by manual, which can not ensure the model’s performance. In this paper, a method of SVM based on an improved particle swarm optimization (NAPSO) is proposed to predict the dynamic measurement error of sensors. Natural selection and Simulated annealing are added in PSO to raise the ability to avoid local optimum. To verify the performance of NAPSO-SVM, three types of algorithms are selected to optimize the SVM’s parameters, they are the particle swarm optimization algorithm (PSO), the improved PSO optimization algorithm (NAPSO), and the glowworm swarm optimization (GSO). The dynamic measurement error data of two sensors are applied as the test data. The root mean squared error and mean absoluter percentage error are employed to evaluate the prediction models’ performances. The experiment results show that the NAPSO-SVM has a better prediction precision and a less prediction errors among the three algorithms, and it is an effective method in predicting dynamic measurement errors of sensors.

Autonomous mobile robots are essential to the industry, and human-robot interactions are becoming more common nowadays. These interactions require that the robots navigate scenarios with static and dynamic obstacles in a safely manner, avoiding collisions. This paper presents a physical implementation of a method for dynamic obstacle avoidance using a Long Short-Term Memory (LSTM) neural network that obtains information from the mobile robot’s LiDAR for it to be capable of navigating through scenarios with static and dynamic obstacles while avoiding collisions and reaching its goal. The model is implemented using a TurtleBot3 mobile robot within an OptiTrack Motion Capture (MoCap) system for obtaining its position at any given time. The user operates the robot through these scenarios, recording its LiDAR readings, target point, position inside the MoCap system, and its linear and angular velocities, all of which serve as the input for the LSTM network. The model is trained on data from multiple user-operated trajectories across five different scenarios, outputting the linear and angular velocities for the mobile robot. Physical experiments prove that the model is successful in allowing the mobile robot to reach the target point in each scenario while avoiding the dynamic obstacle, with a validation accuracy of 98.02%.

Physical rehabilitation aims to help people recover their mobility and strength after an injury or illness. One way to evaluate progress in rehabilitation is through isokinetic prototype tests that describe the dynamic characteristics of an isokinetic leg extension device for rehabilitation and control action. These tests use an isokinetic system to assess muscle strength and performance in a patient during isometric or isokinetic contraction. An experimental prototype allows the performance of the device to be evaluated in a controlled environment prior to use by the patient. In order to achieve physical recovery from musculoskeletal injuries in the lower limbs and achieve the reintegration of the affected subject into society as an independent and autonomous individual in their daily activities, a control model is presented that introduces a medical isokinetic rehabilitation protocol, where the element that allows carrying out such protocol consists of a magnetic particle brake whose control action is strongly influenced by the dynamics of the system when in contact with the end user, specifically the patient's legs in the stretch from the knee to the ankle. The results of these tests are valuable for health professionals seeking to measure their patient’s progress during the rehabilitation process and determine when it is safe and appropriate to advance in their treatment.

Calibration of flow devices is important in several areas of pharmaceutical, flow chemistry and microfluidic applications where dosage of process liquids or accurate measurement of the flow rate is important. The process-oriented liquid itself might influence the performance of the flow device and the simultaneous determination of the dynamic viscosity under flow conditions might be a valuable information for the process parameters. To offer the simultaneous calibration of the dynamic viscosity of the process-oriented liquid at the corresponding flowrate, METAS has built a pipe viscometer for the traceable in-line measurement of the dynamic viscosity in the current flow facilities for low flow rates from 1 L/min to 150 mL/min and pressure drops up to 10 bar. The traceability of all the measuring quantities as well as the geometrical dimensions of the micro tube guarantee the traceability of the pipe viscometer to SI units. The most challenging part is the traceable determination of the inner diameter of the micro tube. This can be achieved by measuring the pressure drop as a function of flow rate with the pipe viscometer and applying the law of Hagen-Poiseuille with a traceable dynamic viscosity of a reference liquid (water) or perform the measurements with the micro-CT at METAS, which determines the inner diameter by x-ray diffraction. The validation of the stated measurement uncertainty of the pipe viscometer has been performed by means of calibration of the dynamic viscosity of several reference liquids with traceable density and kinematic viscosity. The setup of the facility, the traceability as well as the uncertainty calculation of the pipe viscometer for the in-line measurement of the dynamic viscosity are discussed in this paper.

In this article, the research team has systematically developed a method to model the kinematics and dynamics of a 3-wheeled robot subjected to external disturbances and sideways wheel sliding. These models will be used to design control laws that compensate for wheel slippage, model uncertainties, and external disturbances. These are control algorithms developed based on Dynamic Surface Control (DSC). Adaptive trajectory tracking DSC algorithm using fuzzy logic system (AFDSC) and radial neural network (RBFNN) with fuzzy logic system to overcome the disadvantages of DSC and expand the application domain for wheeled Mobile Robots (WMR). However, this Adaptive Fuzzy Neural Network Dynamic Surface Control (AFNNDSC) adaptive controller ensures the closed system is stable and follows the preset trajectory in the presence of wheel slippage model uncertainty and is affected by significant amplitude disturbances. The stability and convergence of the closed-loop system are guaranteed based on the Lyapunov analysis. The AFNNDSC adaptive controller is evaluated by simulation on MATLAB/Simulink software and in a steady state. The maximum position error on the right wheel and left wheel is 0.000572 (m) and 0.000523 (m), and the angular velocity tracking error in the right and left wheels of the control method is 0.000394 (rad/s). The experimental results show the correctness of the theoretical analysis, the effectiveness of the proposed controller, and the possibility of practical application.

Because of the large number of parameters that interact in their function, determining dynamic regime parameters as well as the mode of function of amplifying stages is an extremely complex problem. This paper describes a LabVIEW application for studying the functioning of an ampli-fier in various connections. The user selects the generator's parameters, the type of connection and its parameters, as well as the electric charge characteristics. The application can determine both the stage characteristics and the Bode characteristics. The amplifier's stability zone, as well as its gain and phase, are determined based on these characteristics. An important advantage of this application is that the design of the amplifier stage can be made starting from some param-eters that the amplifier can establish, from which the values of components can be determined. In order to validate the simulation results using the LabVIEW application, a specialized program Multisim was used, as well as experimental measurements using the Electronics Explorer Board. Both Multisim and Electronics Explorer Board can determine Bode characteristics. In both simu-lations and experimental amplifiers, the same schemes with the same transistor was used. The application can be used for educational purposes as well as to design the amplifier's stage to achieve specific parameters.

Understanding and evaluating urban investment environment is essential for effectively improving the efficiency of resource allocation between cities and promoting overall development of the regional economy. This paper takes 15 node cities on maritime Silk Road covered by the “Belt and Road” as the research object, establishes a dynamic evaluation index system for investment environment, and uses projection pursuit cluster to analyze and evaluate the investment environment of the cities. It is found that the investment environment potential of a city is directly related to the level of social development, economic development, and the degree of opening to the outside world. It is recommended that node cities should seize the important opportunity of the construction of the Maritime Silk Road, introduce world-wide human, financial and material resources to promote regional resources allocation and flow, and continuously improve and upgrade the investment environment quality.

The present work highlights some of the dynamic couplings observed in a series of tests performed in a wave basin with a scaled-model of a FOWT with semi-submersible substructure. The model was moored by means of a conventional chain catenary system and an actively controlled fan was used for emulating the thrust loads during the tests. A set of wave tests comprising regular and irregular waves was done for different wave angles and wind velocities. The experimental records illustrate the main coupling effects involved and how they affect the FOWT motions in waves, especially when the floater presents a non-negligible tilt angle.. In addition, an analysis of the frequency-domain dynamic model was made in order to evaluate its ability to capture these effects properly. The influence of different modes of fan response, floater trim angles (changeable with ballast compensation) and variations of the mooring stiffness with the offsets were investigated in the analysis. Results attest that significant changes in the FOWT responses may indeed arise from coupling effects, thus indicating that caution must be taken when simplifying the hydrodynamic frequency-domain models often used as a basis for the simulation of FOWTs in waves and in in optimization procedures for the design of the floater and mooring lines.

Al-6%Mg-Sc-Zr alloys with the total ratio of Sc + Zr = 0.32 wt.% make up the target of this research. The content of scandium and zirconium varied with an increment of 0.02%. The alloys were produced by induction casting. Their ultrafine-grained (UFG) microstructure was formed with Equal Channel Angular Pressing (ECAP). Such cast alloys have a homogeneous macrostructure formed by small equiaxed grains in the central part of the ingot and columnar crystals along the edges of the cross section. After ECAP, the average grain size in the alloy specimens is 0.5–1 µm. The average grain size does not depend on the ratio of Sc and Zr in these alloys. Superplasticity tests were performed at temperatures ranging from 300 to 500 °C and at a strain rate varying between 3.3·10-3 and 3.3·10-1 s-1. UFG Al-6%Mg-0.20%Sc-0.12%Zr and Al-6%Mg-0.18%Sc-0.14%Zr alloys exhibit the highest superplasticity. It was suggested that changes in Sc:Zr ratio affect spatial distribution and composition of the following precipitating particles: Al3Sc, Al3Zr, Al3(ScxZr1-x). An increase in Zr concentration is shown to reduce the susceptibility of UFG alloys to cavitation fracture.

The Oil reservoirs with low permeability account for a large proportion in the world, they surpass half of the total number of the oil reservoirs in China, it is important to exploit this kind of reservoir effectively. The exploitive results of these reservoir using normal water flooding methods are very poor because of the thine pores, bad connections and so on. However, these problems can be well solved by applying gas injection techniques. In this paper, the effects on the recovery effects exerted by the injection parameters such as the oxygen content in the injected air, the injection speed etc. were studied by several experiments using independently designed equipments aiming at one low permeable sandstone reservoir in China. Several conclusions were made from the experiment results: the best recovery effects can be achieved by injecting the oxygen reduced air with 8% of oxygen at the speed of 0.3ml/min (7.41×10-4PV/min) using the methods of injecting the air slugs and the foaming agent slugs alternately; the best oxidation time of the oil was 168 hours and the final oil recovery could be enhanced by 26.5% in this method. It was also showed by the experiments that the larger the permeability ratio is, the larger the recovery factor will be increased. At last, several equations about relationships between the EOR and the air injection parameters were revealed according to the results of the experiments which may offer some references to the LTO process mechanisms study in the similar oil reservoir.

In the last years, more and more studies highlight the advantages of complementing traditional master classes with additional activities that improve students´ learning experience. This combination of teaching techniques is specially advised in the field of structural engineering, where intuition of the structural response it is of vital importance to understand the studied concepts. This paper deals with the introduction of a new (and more encouraging) educational tool to introduce intuitively students in the dynamic response of structures excited with an educational shaking table. Most of the educational structural health monitoring systems use sensors to determine the dynamic response of the structure. The proposed tool is based on a radically different approach, as it is based on low-cost image-recognition techniques. In fact, it only requires the use an amateur camera, a black background and a computer. In this study, the effects of both the camera location and the image quality are also evaluated. Finally, to validate the applicability of the proposed methodology, the dynamic response of small-scale buildings with different typologies is analyzed. In addition, a series of surveys were conducted in order to evaluate the activity based on student´s satisfaction and the actual acquisition and strengthening of knowledge.

The dynamic and surface manipulation of the M13 bacteriophage meeting application demands enable a pathway to design efficient applications with high selectivity and responsivity rate. Herein, we report the role of the M13 bacteriophage thin film layer deposited on an optical nanostructure involving gold nanoparticles/SiO2/Si and its influence on optical and geometrical properties. The thickness of the M13 phage layer was either controlled by varying the concentration or humidity exposure levels, and optical studies were conducted. We designed a standard and dynamic model based upon three-dimensional finite-difference time-domain (3D FDTD) simulations distinguishing the necessity of each model under variable conditions. As seen from the experiments, the origin of respective peak wavelength positions is addressed in detail with the help of simulations. The importance of the dynamic model was noted when humidity-based experiments were conducted. Inexpensive, multi-wavelength optical characteristics from a single structure, reproducibility, and reversible properties are significant advantages of involving M13 bacteriophage. We believe this work will provide fundamental insight into understanding and interpreting the geometrical and optical properties of the nanostructures involving M13 bacteriophage.

A new approach is presented for dynamic modeling of chemical and isotopic evolution of C1-3 during the hydrocarbon generation process. Based on systematic data obtained from published papers for pyrolysis of various hydrocarbon sources(type I kerogen/source rock, type II kerogen/source rock, type III kerogen/source rock, crude oil, asphalt, etc), the empirical evolution framework of chemical and isotopic composition of C1-3 during the hydrocarbon generation process was built. Although the empirical framework was built only by fitting large amount of pyrolysis data, the chemical and isotopic composition of C1-3 derived from the pyrolysis experiments all follow the evolution laws, convincing us that it is applicable to the thermal evolution process of various hydrocarbon sources. Based on the simplified formula of the isotopic composition of mixed natural gas at different maturities (δ13Cmixed) δ13Cmixed=(X〖*n〗_iA 〖*δ〗^13 C_iA+Y〖*n〗_iB 〖*δ〗^13 C_iB)/(X〖*n〗_iA+Y〖*n〗_iB ), it can be derived that the cumulative isotopic composition of alkane generated in certain maturity interval can be expressed by the integral of the product of instantaneous isotopic composition and instantaneous yield at certain maturity point, and then divided by the cumulative yield of alkane generated in corresponding maturity interval. Thus, the cumulative isotopic composition(A(X)), cumulative yield(B(X)), instantaneous isotope(C(X)),and instantaneous yield(D(x)) in the dynamic model comply with the following formula during the maturity interval of (X0-X) A(X)=(∫_(X_0)^X▒〖C(X)*D(X)dx〗)/(B(X)), where A(X) and B(X) can be obtained by fitting of pyrolysis data, and D(x) can also be obtained from the derivation of B(X). The dynamic model was applied on the pyrolysis data of Pingliang Shale to illustrate the quantitative evolution of cumulative yield ,instantaneous yield, cumulative isotope and instantaneous isotope of C1-3 with increasing maturity.The dynamic model can quantify the yield of methane, ethane and propane as well as δ13C1, δ13C2 and δ13C3 respectively during the hydrocarbon generation process, which is of great significance to evaluate the natural gas resources of hydrocarbon source rock with different maturity and to identify the origin and evolutionary process of hydrocarbons by chemical and isotopic data. Moreover, this model provides an approach to study the dynamic evolution of isotope series of C1-3 (including reversed isotopic series), which is hopeful to reveal the mechanism responsible for isotopic reversal when combined with post-generation studies.

Asphalt binder is a temperature sensitive material, whose performance is greatly affected by the climate change of the environment. Improper selection of asphalt will cause a lot of damage and affect the durability of the road. The establishment of asphalt pavement performance zoning in Xinjiang, a vast area with great temperature difference, will provide reference for the selection of asphalt suitability, the refinement of pavement design and the sustainable development of road engineering. In this study, 11 years of temperature data in Xinjiang region were collected and analyzed, and 98% reliability of pavement design temperature was used to draw a performance grading map of asphalt pavement in Xinjiang region based on ArcGIS platform. Finally, Xinjiang region was divided into 9 performance zones. At the same time, the performance grade (PG) of five kinds of asphalt binders in Karamay were explored. The result shows that there is little difference in continuous PG span between different matrix asphalt binders, the lower penetration grade, the better high temperature performance, the worse low temperature performance. After adding SBS modifier, the continuous PG span can be higher than the matrix asphalt in 20 ℃. All these provide the basis for reasonable selection of asphalt binders in different areas of Xinjiang.

Bladder cancer is one of the most common malignant diseases in the urinary system and a highly aggressive neoplasm. The prognosis is not favourable usually and its evolution for particular patients is very difficult to find out. In this paper we propose a dynamic mathematical model that describes the bladder tumor growth and the immune response evolution. This model is customized for a single patient, determining appropriate model parameter values via model calibration. Due to the uncertainty of the tumor evolution, using the calibrated model parameters, we predict the tumor size and the immune response evolution over the next few months assuming three different scenarios: favourable, neutral and unfavourable. In the former, the cancer disappears; in the second a 5mm tumor is expected around the middle of August 2018; in the worst scenario, a 5mm tumor is expected around the end of May 2018. The patient has been cited around June 15th, 2018, to check the tumor size, if it exists.

This paper studied the dynamic characteristics of the deployment process of the replaceable interface mast and the vibration generated at the end of the mast. The interface is discretized by the absolute nodal coordinate thin shell element with gradient reduction, and the three-dimensional motion of the reconfigurable rigid body module is described by the natural coordinate method. The dynamic equations of the interface and the reconfigurable module without external constraints are established by the principle of virtual work. Finally, the dynamic models of each part are assembled into the dynamic model of the mast system deployment process through the system constraint equation. According to the established dynamic model of the mast system deployment process, the dynamic behavior changes of the replaceable interface mast are analyzed. At the same time, the differences in the deployment behavior of the replaceable interface mast under different system configuration schemes, flexible interface geometric parameters, and different driving laws are studied and compared. It provides guidance for the scheme configuration of the mast system, the structural design of the interface, and the deployment motion planning of the mast. According to the physical prototype and the assembly of the mast system model, the deployment process of the replaceable interface mast is experimentally analyzed. It shows that the established dynamic model of the mast system can correctly analyze the dynamic characteristics of the deployment behavior of the replaceable interface mast, which provides a reference for the design and behavior analysis of the mast system.

Resource pricing in cloud computing has become one of the main challenges for cloud providers. The challenge is determining a fair and appropriate price to satisfy users and resource providers. To determine a fair price, it is necessary to consider the conditions and needs of both parties: provider and user. This research tries to provide a pricing mechanism for cloud computing based on game theory. The proposed mechanism takes into account three factors including fault possibility, interaction between virtual machines, and energy consumption to reach a fair price. In the proposed game, the provider decides on the price of the virtual machine which can be offered to the user on each physical machine and the user decides between the virtual machines offered to run its application. The whole game is implemented as a function of the resource broker component. The proposed mechanism is simulated and evaluated using the CloudSim simulator. Its performance is compared with several previous recent mechanisms. According to the results, the proposed mechanism has been able to determine a more reasonable price for the user and the provider which increases the overall profitability of the cloud system.

Ransomware constitutes a distinctive category of pernicious software that sequesters a user's digital assets by encryption, holding them hostage until a sum is extorted from the victim. These incursions have escalated to become among the most prevalent and significant threats confronting both individuals and corporate entities. In combatting this virulent program, dynamic analysis has been established as the favored detection modality. Such analyses typically hinge on Windows API calls, the conduits through which programs requisition services from the operating system. Yet, the superfluous and unrelated Windows API calls interjected by adversaries into the execution stream of suspect binaries precipitate an excessively noisy behavioral sequence, which impairs the performance of counter-ransomware mechanisms. The research outlined herein introduces a novel non-signature-based detection paradigm that harnesses efficacious Windows API call sequences through supervised machine learning strategies. An innovative Enhanced Min Max (EmRmR) filter technique is proposed, aiming to purge noisy features and isolate the most indicative feature subset that encapsulates the ransomware's true behavior. The EmRmR method, diverging from the traditional Min Max approach, circumvents the superfluous calculations that are a hallmark of the conventional algorithms, thereby necessitating a reduced number of evaluations. Additionally, a refinement procedure has been integrated to contract the program's call trace volume by discarding those Windows API calls lacking a robust correlation with ransomware's pivotal behavior. Subsequent to rigorous experimental analyses and juxtaposition with extant behavior-based detection methodologies, the proposed strategy has demonstrated its efficacy in differentiating ransomware behavior, delivering high detection precision alongside a diminution in false-positive occurrences.

The first appearance of viruses can date back to the late last century. As an effective form of malware, viruses reside in the permanent storage of target hosts. Before a virus can execute, that must load into memory from the persistent storage included in the associated file. Due to the reliable destructive power of viruses, many mechanisms have been developed to defend computer systems against these hazardous threats. Antivirus software is one of the most famous and popular among these mechanisms. Most antivirus software uses static analysis (signature-based) technology on files stored in permanent storage, such as hard disks or USB flashes, to detect viruses hidden in files. Fileless malware was developed to enhance the survivability of malware by circumventing detection. Fileless malware only exists in the target hosts’ memory, not files. Antivirus software cannot even access the fileless malware code, much less analyze it, since it may be performed in memory directly without needing to load it from a disk. As a result, it is difficult for an antivirus engine to defend a system against fileless malware attacks. This paper proposes a kernel-based solution called Check-on-Execution (CoE) to detect fileless malware on a Linux system. When a program is going to execute a piece of code in a writable and executable memory area of a process, CoE suspends the code execution first. Coe retrieves the code from memory, packs the code with an ELF header to create an ELF file, and uses VirusTotal to check the file to prevent a Linux system from executing fileless malware. Experimental results show that CoE noticeably enhances the ability of a Linux system to defend itself again fileless malware. CoE is also suitable for protecting a system from shell code injection attacks, such as buffer and heap overflow attacks. It is capable of handling even packed malware. But in this paper, we only focus on fileless malware.

The traditional Simultaneous Localization and Mapping (SLAM) systems are based on the 1 strong static assumption, and their performance will degrade significantly due to the presence of 2 dynamic objects located in dynamic environments. To decrease the effects brought by the dynamic 3 objects, based on ORB-SLAM2 system framework, a novel dynamic semantic SLAM system called 4 MOR-SLAM is presented using mask repair method, which can accurately detect dynamic objects 5 and realize high-precision positioning and tracking of the system in dynamic indoor environments. 6 First, an instance segmentation module is added to the front end of ORB-SLAM2 to distinguish 7 dynamic and static objects in the environment and obtains a preliminary mask. Next, to overcome the 8 under-segmentation problem in instance segmentation, a new mask inpainting model is proposed to 9 ensure that the integrity of object masks, which repairs large objects and small objects in the image 10 with depth value fusion method and morphological method respectively. Then, a reliable basic matrix 11 can be obtained based on the above repaired mask. Finally, the potential dynamic feature points 12 in the environment are detected and removed through the reliable basic matrix, and the remaining 13 static feature points are input into the tracking module of the system to realize the high-precision 14 positioning and tracking in dynamic environments. The experiments on the public TUM dataset 15 show that, compared with ORB-SLAM2, the MOR-SLAM improves the absolute trajectory accuracy 16 by 95.55%. In addition, compared with DynaSLAM and DS-SLAM on the high-dynamic sequences 17 (fr3/w/rpy and fr3/w/static), the MOR-SLAM improves the absolute trajectory accuracy by 15.20% 18 and 59.71%, respectively

The purpose of this study was to compare Electromyographic (EMG) with Mechanomyo- 1 graphic (MMG) recordings during isometric conditions, and during a simulated load-lifting task. 2 Twenty-two males (age: 25.5 ± 5.3 years) first performed maximal voluntary contractions (MVC) and 3 submaximal isometric contractions of upper limb muscles at 25%, 50% and 75% MVC. Participants 4 then executed repetitions of a functional activity simulating a load-lifting task above shoulder level, 5 at 25%, 50% and 75% of their maximum activity (based on MVC). The low frequency part of the 6 accelerometer signal (< 5 Hz) was used to segment the 6 phases of the motion. EMG and MMG were 7 both recorded during the entire experimental procedure. Root mean square (RMS) and mean power 8 frequency (MPF) were selected as signal extraction features. During isometric contractions, EMG 9 and MMG exhibited similar repeatability scores. They also shared similar RMS vs force relationship, 10 with RMS increasing to 75% MVC and plateaued to 100%. MPF decreased with increasing force to 11 75% MVC. In dynamic condition, RMSMMG exhibited higher sensitivity to changes in load than 12 RMSEMG. These results confirm the feasibility of MMG measurements to be used during functional 13 activities outside the laboratory. It opens new perspectives for future applications in sports science, 14 ergonomics and human-machine interfaces conception.