Rough Estimate Research Articles

Simultaneous Estimation of Vehicle Mass and Unknown Road Roughness Based on Adaptive Extended Kalman Filtering of Suspension Systems

This study presents a vehicle mass estimation system based on adaptive extended Kalman filtering with unknown input (AEKF-UI) estimation of vehicle suspension systems. The suggested real-time methodology is based on the explicit correlation between road roughness and suspension system. Because the road roughness input influences the suspension system, AEKF-UI with a forgetting factor is proposed to simultaneously estimate the time-varying parameter (vehicle mass) of vehicle suspension systems and road roughness using an unknown input estimator. However, a constant forgetting factor does not adaptively weigh the covariance of all the states, and optimal filtering cannot be ensured. To resolve this problem, we present an adaptive forgetting factor technique employed to track time-varying parameters and unknown inputs. Simulation studies demonstrate that the proposed algorithm can simultaneously estimate the vehicle mass variation and unknown road roughness input. The feasibility and effectiveness of the proposed estimation algorithm were verified through laboratory-level experiments.

Using a novel two-stage strategy to characterize the spatial distribution of associations between temperature and COVID-19: A case study in the continental United States

BackgroundNumerous studies have studied the association between daily average temperature (DAT) and daily COVID-19 confirmed cases, which show considerable heterogeneity, even opposite results, among different regions. Such heterogeneity suggests that characterizing the association on a large area scale would ignore the local variation, even obtain false results in some local regions. So, characterizing the spatial distribution of heterogeneous DAT-COVID-19 associations and exploring the causes plays an important role on making temperature-related region-specific intervention measures and early-warning systems. MethodsAiming to characterize the spatial distribution of associations between DAT and COVID-19 confirmed cases in the continental United States, we proposed a novel two-stage strategy. In the first stage, we used the common stratified distributed lag nonlinear model to obtain the rough state-specific associations. In the second stage, conditional autoregression was used to spatially smooth the rough estimations. Furtherly, based on the idea, two modified strategies were used to investigate the time-varying associations and the modification effects derived from the vaccination campaign. ResultsAround one-third of states exhibit no significant association between DAT and daily confirmed COVID-19 cases. Most of the remaining states present a low risk at low DAT and a high risk at high DAT, but several states present opposite associations. The average association curve presents a ‘S’ shape with positive association between −8 – 18 °C and keeping flat out of the range. An increased vaccination coverage rate will increase the risk when DAT < 12 °C, but slightly affect the risk when DAT > 12 °C. ConclusionA considerable spatial heterogeneity of DAT-COVID-19 associations exists in America and the average association curve presents a ‘S’ shape. The vaccination campaign significantly modifies the association when DAT is low, but only make a slight modification when DAT is high.

Non-invasive anaemia detection by examining palm pallor: A smartphone-based approach

Anaemia, caused due to lack of blood haemoglobin level, is one of the most common diseases that affects billions of people across the world. According to WHO statistics, India is one of the developing countries with highest prevalence of anaemia. Conventional invasive methods are cost-prohibitive and difficult to administer globally which essentially demands non-invasive, inexpensive and reliable solution. This work targets to combine state-of-the computational approaches with the idea of age-old practice of rough estimation of blood haemoglobin level by observing pallor in palm to develop a non-invasive anaemia detection system. The proposed system works with the basis of inducing changes in palm pallor with suitable pressure application and release, measuring the rate of change of colour and performing time-domain analysis thereof to correlate with blood haemoglobin concentration. The video of colour changes in palm induced through a customised device, is captured using smartphone camera and is processed and analysed through a set of image processing and analysis techniques. Estimated parameters are provided as input to the ensemble-based prediction models comprising of regression and multi-layer perceptron. The proposed system ensures a sensitivity of 93% with MSE and RMSE of 0.701 and 0.698, respectively, determined on palm pallor video samples of 131 participants.

Viscoelastic or viscoplastic glucose theory (VGT #82): An investigation of economics markers versus COVID pandemic markers during 9 quarters from Y2020Q1 to Y2022Q1 based on GH-method: math-physical medicine, especially the VGT energy tool (No. 672)

Beginning with paper No. 578 dated 1/8/2022, the author wrote a total of 80 medical research articles using the viscoelasticity and viscoplasticity theories (VGT) from physics and engineering disciplines on 80 different datasets of chosen medical subjects. These papers aim to explore some hidden biophysical behaviors and provide a quantitative understanding of inter-relationships between a selected medical symptom, i.e. biomarker, and multiple influential factors, “root causes or risk factors”. These hidden biophysical behaviors and possible inter-relationships existed among lifestyles, medical conditions, chronic diseases, and certain severe complications, such as heart attacks, stroke, cancers, dementia, or longevity. All of the chosen subjects with their datasets, multiple symptoms, and risk factors are “time-dependent” which means that all of the biomedical variables are changing from time to time. This is why he utilizes VGT tools from physics and engineering to conduct his medical research work. From 1979 to 1982, the author attended a university for his MBA degree with an emphasis on finance and marketing. He spent many years managing a successful high-tech business in Silicon Valley, where it focused on many economic key factors, such as GDP, inflation, stock market performance, etc. As a result, money, finance, and economics are not unfamiliar subjects to him. During his recent medical research work using the VGT tool, he suddenly realized that there is a similarity between the medical and economic systems. The economic variables (inputs and outputs) are comparable to medical variables he studied (causes and symptoms), e.g. waveforms, fluctuation, trends, etc. Both medical and economic variables have possessed “time-dependent” characteristics. The recent COVID-19 pandemic is a unique and severe experience in the world other than the Spanish flu that happened over 100 years ago. He wondered what kind of impact or inter-relationship existed during the pandemic outcome along with overall economic activities. Therefore, he selects the US gross domestic product (GDP) numbers as the output variable along with the US inflation rates (inflation) and the US COVID-19 death cases (COVID) as two input variables to conduct his math-physical medicine (MPM) analysis using the VGT tool. In summary, he conducted three related VGT studies in this article. The first is the GDP of economics versus the inflation rate and COVID death. The second is the inflation rate of economics versus pandemic death and infection from medicine. The third is COVID death from medicine versus COVID infection from medicine. Mathematically, these studies have similar methodologies (VGT) but with different outcome observations and interpretations. Initially, he Googled national data on economics and COVID. However, it should be mentioned that the COVID data are rough estimates directly from the published charts from the Center for Disease Control (CDC) and Johns Hopkins University. The COVID data are simplified with rounded numbers to thousands for death and millions for infection because the precise digits do not change the physical characteristics of VGT analysis results. Next, he searched and reviewed a few economics articles related to GDP, inflation, consumer price index (CPI), etc. Over the past 2+ years, due to his medical research interest, he was exposed to the news, many articles, and published research papers and clinical data regarding the COVID pandemic. This study is of particular interest to him since it links national economics with a severe infectious disease. This article is his first attempt to link COVID deaths with some important economic measurements, specifically GDP and inflation rate. The established theory of viscoelasticity and viscoplasticity (from the physics branch of science) should

Vibrational Model of Heat Conduction in a Fluid of Hard Spheres

Application of a vibrational model of heat transfer to a fluid made of hard spheres is discussed. The model was originally proposed to describe heat conduction in fluids with soft pairwise interactionsHere, it is shown that only minor modifications are required to apply the model in the opposite limit of hard sphere interactions. Good agreement with recent results from molecular dynamics simulation is documented in the moderately dense regime. Near the freezing point, however, the model overestimates the thermal conductivity coefficient (by ≃50%). The new approach is compared with other simple models for the thermal conductivity coefficients such as Bridgman’s expression and the Enskog formula. The value of the coefficient in the Bridgman’s expression, appropriate for the hard sphere fluid, is determined. A new expression for the dependence of the reduced thermal conductivity coefficient on the reduced excess entropy is proposed. The obtained results can be useful for rough estimates of the thermal conductivity coefficient of simple fluids with steep interactions when more accurate experimental results are not available.

Performance characterization of a traditional wood-fired pizza oven.

Neapolitan pizza, a renowned Italian food recognized as one of the traditional specialties guaranteed (TSG) by European Commission Regulation no. 97/2010, should be exclusively baked in wood-fired ovens for approximately 90 s. Despite its extensive use in restaurants and rotisserie shops all around the world, such equipment has been very poorly studied thus far. The aims of this study were to characterize the operation of a pilot-scale wood-fired pizza oven from its start-up phase to its baking operation and assess its thermal efficiency. To manage brick firing, the oven was lighted at a firewood feed rate (Qfw ) of 3 kg/h for just 1 h on the first day, 2 h on the second day, 4 h on the third day, and approximately 8 h on the fourth day. Independent of its lighting frequency, after 4-6 h, the oven vault or floor temperature approached an equilibrium value of 546 ± 53°C or 453 ± 32°C, respectively. The initial oven floor temperature gradient was linearly related to Qfw , while the maximum floor temperature tended to an asymptotic value of 629 ± 43°C at Qfw =9kg/h. The well-known water boiling test was adapted to assess the heat absorbed by a prefixed amount of water when the pizza oven was operating in pseudosteady-state conditions at Qfw =3kg/h. The thermal efficiency of this oven was 13 ± 4%, and this value was further confirmed by other baking tests with four different white and tomato pizza products. PRACTICAL APPLICATION: Although wood-fired pizza ovens are largely used all over the world, little is known about their transitory and pseudosteady-state regime performance. This study shows how to perform the start-up procedure of pilot-scale equipment and, independent of the operator's ability, how to achieve pseudosteady-state conditions using different firewood feed rates. Finally, its thermal efficiency was assessed by water heating and pizza baking tests, which allowed a rough estimation of firewood consumption.

Update on gut microbiota in gastrointestinal diseases.

The human gut is a complex microbial ecosystem comprising approximately 100 trillion microbes collectively known as the “gut microbiota”. At a rough estimate, the human gut microbiome contains almost 3.3 million genes, which are about 150 times more than the total human genes present in the human genome. The vast amount of genetic information produces various enzymes and physiologically active substances. Thus, the gut microbiota contributes to the maintenance of host health; however, when healthy microbial composition is perturbed, a condition termed “dysbiosis”, the altered gut microbiota can trigger the development of various gastrointestinal diseases. The gut microbiota has consequently become an extremely important research area in gastroenterology. It is also expected that the results of research into the gut microbiota will be applied to the prevention and treatment of human gastrointestinal diseases. A randomized controlled trial conducted by a Dutch research group in 2013 showed the positive effect of fecal microbiota transplantation (FMT) on recurrent Clostridioides difficile infection (CDI). These findings have led to the development of treatments targeting the gut microbiota, such as probiotics and FMT for inflammatory bowel diseases (IBD) and other diseases. This review focuses on the association of the gut microbiota with human gastrointestinal diseases, including CDI, IBD, and irritable bowel syndrome. We also summarize the therapeutic options for targeting the altered gut microbiota, such as probiotics and FMT.

Waste management in Iceland: Challenges and costs related to achieving the EU municipal solid waste targets

Waste management in Iceland has developed considerably in recent years. Before 1990, most of the waste was either burnt in open pits or landfilled. In the past, information about waste management in Iceland used to be almost exclusively published in reports and was primarily based on rough estimates. Currently, incinerators and landfilling sites are highly regulated and follow EU legislation. Additionally, reporting has gradually improved and is approaching EU standards, although improvement is still needed. In an international context, Iceland is far behind the other Nordic countries as well as the EU-27 countries in reducing landfill rates and enhancing energy recovery and recycling rates. According to the EU landfill directive, the total amount of municipal solid waste (MSW) landfilled must be below 10% by 2035; however, it is currently over 60%. Other targets are similarly far off, and it is unlikely that Iceland will meet those in time without immediate and significant changes in waste management. This article aims to evaluate MSW management in Iceland at the national and regional levels, its compliance with the EU’s targets for waste management and the associated costs inflicted on municipalities. Hence, annual accounts data were used when comparing regions and municipalities. It was found that there are significant differences in per capita waste management expenditure between municipalities with less than 1,000 inhabitants (€379) and ones with more than 10,000 inhabitants (€106). Without changes in proposed future waste management strategies, this gap will inevitably increase in the upcoming years.

Artificial neural network combined with damage parameters to predict fretting fatigue crack initiation lifetime

The fretting problem occurs at two contact surfaces sustaining small relative displacement, and it reduces the fatigue lifetime dramatically. Estimating accurate fretting fatigue lifetime plays an important role in engineering applications. Due to the complicated stress state, and high-stress gradient in the contact surface, the average methods are necessary to obtain the precise lifetime, but the critical distance for the average zone is difficult to estimate. In this work, Artificial Neural Network (ANN) tool combined with damage parameters is proposed to determine the optimal critical distance for different fretting conditions. This tool can also be used to accurately predict the crack initiation lifetime. The fretting fatigue lifetimes calculated by using this approach have shown good agreement with experimental results from literatures. In addition, rough estimates of critical distance for different cases are made based on the numerical results.

Mineral Exploration Scenario in India: Prospect, Promise and Policy Reforms

Abstract India is endowed with unique geological and tectonic setting conducive to host potential mineral resources. A look at the mineral resource status of selected minerals in India indicates abundant and/or adequate resources of iron, chromite, manganese, bauxite, coal, limestone, dolomite, mica, zinc, graphite but deficient to scarce resources of nickel, cobalt, molybdenum, copper, sulphur, potash, apatite, rock phosphate, gold, PGE’s, diamond etc., in spite of the vast obvious geological potential (OGP) blocks that exist in India. The OGP blocks have been estimated to around 1 lakh Km2 for gold, 3 lakh Km2 for diamond, 1.6 lakh km2 for base metals, 8000 km2 for PGEs and 5000 km2 for iron ores. By a rough estimate only 10% of this is explored and less than 2% is mined. The Reserve to Resource ratio which, as per mineral exploration practice, should be over 50% is woefully low for most of the minerals. For instance it is 17% for bauxite, 14% for copper, 24% for iron 14% for lead-Zinc, 8% for limestone and 30% for chromite etc. This calls for highly focused exploration strategy at high confidence level. India need to take a leaf out of strategies of many other countries and frame her own policy based on OGP areas to trigger the mining growth by accelerating mineral exploration programme. Benefits that flow from the mineral exploration/mining sector have huge impact on local populace, industry especially mineral dependent industries, employment and overall prosperity. Recent amendments in the Mines and Minerals (Development and Regulations) Act-1957 in the year 2021, have sought to bring out the potential of the mineral sector such as to increase the revenue of the State, escalate employment, maintain the continuity of mining operation, increase production, time bound operationalization of mines, increase the speed of exploration and auction of mineral resources and lastly to resolve the long pending issues that have decelerated the growth of this sector. This is an encouraging step and likely to bear fruits. These legislative and policy reforms in the mineral exploration and mining sector have laid down a sustainable road map that aims to boost mineral output by 200% in the next 7 years and raise the GDP contribution to 2.5%. Mineral laws Amendments Act 2020 are transformative and investor friendly. Mining is now defined as legal entity and hence seamless transfer of mining lease is possible. New auction mechanism instituted will ensure transparency, eliminate discretion, reducing bureaucratic delay and easier trading of mineral rights. Setting up of District Mineral foundation (DMF) will work for the interest and benefit of mining related operations and overcome the local resistance to the mineral exploration and mining activities. The National Mineral Exploration Trust (NMET) will focus on extending more financial assistance to government and also the private sectors to augment advance technology and will surely give fillip to exploration initiatives. The paper deals with such ideas in relation to the required thrust in mineral exploration sector in Indian context.

Design and Analysis of Double Stator Swing Rotating Permanent Magnet Spherical Motor

This article presents a new type of double stator swing rotating permanent magnet spherical motor (DSSRPMSM), which can realize swing, rotation, and helical motion and is used in industrial robots, gyroscopes, satellite communications, and other fields. The proposed spherical motor consists of two stators and a hollow rotor with permanent magnet (PM) poles on its inner and outer surfaces. Compared with most spherical motor with hollow coil and traditional PM synchronous motor, the structure of the motor is different and novel, and it is difficult to find a more perfect design theory and method. Thus, this article introduces the new idea of motor design in detail. First, the structure and working principle of the motor are introduced, and the original design of the motor is carried out. The 2-D rough estimation and 3-D FEM accurate simulation calculation are carried out, and the electromagnetic characteristics of the motor are obtained, including magnetic flux density distribution, torque, and loss. The simulation results meet the design specifications of the motor. A prototype was built and tested. The experimental results are in good agreement with the 3-D FEM analysis. The design method provides a theoretical basis for the design of this kind of spherical motor. The research results lay a foundation for the subsequent optimization of the motor.

Empirical roughness coefficients for moderate floods in an open conduit cave: Fullers stream canyon, Culverson Creek Cave System, West Virginia

Open conduit modeling of cave stream floods can yield useful information about water velocities and shear stresses, which can in turn be used to estimate sediment transport capabilities. All such calculations require roughness coefficients for estimating energy losses and a priori knowledge of either discharge or flow depths to set model boundary conditions. However, the difficulties associated with observing in-cave floods generally preclude measuring discharge; roughness coefficients must be assumed based on channel properties. To overcome these challenges, we monitored stream flow depths in Fullers Cave, Greenbrier County, West Virginia using pressure transducers, and simultaneously measured stage and discharge in a karst window immediately upstream of the cave. Five pressure transducers were deployed opportunistically along a 93-meter-long reach in a 10+ meter high canyon averaging 1.5 to 3 meters wide. Stage-discharge relationships were determined for the karst window using an electromagnetic flow meter for floods with peak discharges of 1.66 m3 s-1 or less. The collected data was used to obtain the empirical Manning’s n roughness values, head losses, and energy gradients. Calculated floodwater velocities are comparable to values obtained from scallops on passage walls. Major energy losses were observed where breakdown partially occludes the passage. At peak flow, Manning n values average 0.053 for reaches typified as cobble-floored canyons, but n was 0.069 in the breakdown reach. Roughness values declined exponentially with increasing discharge, but friction slopes calculated using head losses show more complex relationships with discharge. Notably, n values back calculated using bed gradients differ from those calculated using measured head losses by as little as 12%, so the use of bed gradients in roughness estimations will generally yield reasonable approximations of flow conditions. Fullers Cave experiences significantly larger open conduit floods than we observed, so additional work is needed to estimate roughness coefficients for higher discharges. Our empirical roughness coefficients can be applied to similar cave passages in other caves and contexts, including modeling slot canyon-like channels, and our methods demonstrate a technique for measuring hard to obtain data. The addition of data for open conduit conduits significantly expands the range of environments that can be modeled using empirical data beyond pipe-full caves. Applications include studying flooding, sediment transport, and bedrock erosion process. All of these topics will be addressed in Fullers in the future.

Effects of boundary layer thickness on the estimation of equivalent sandgrain roughness in zero-pressure-gradient boundary layers

Effects of boundary layer thickness on the estimation of equivalent sandgrain roughness in zero-pressure-gradient boundary layers

Friction reduction of Al2O3, SiO2, and TiO2 nanoparticles added to non-Newtonian water based mud in a rotating medium

In drilling industry, energy consumption counts from 20 to 40 percent of total costs. Enhanced water-based mud (WBM) drilling fluids with nanoparticles can save energy in drilling processes. An in-house Taylor-Couette flow system (TCS) was developed at Australian University (AU) to study WBM enhanced by Al2O3, SiO2, and TiO2 nanoparticles. The TCS is really a practical tool to help well drillers with a rough idea of viscosity when nanoparticles are added. The TCS for sure cannot substitute advanced rheometry. The goal of the present experiment is to produce a rough estimate in field operation. Experimental results were examined with several rheology models in our previous publications. In the present work, the enhanced WBM of Al2O3, SiO2, and TiO2 nanofluids are compared with each other at very low volume fractions of 0.05%, 0.1%, 0.5% and 1% and at TCS rotational speeds of 200–1600 RPM. Results in form of consistency charts for shear stress and apparent viscosity are presented here. It is observed that both shear stress and apparent viscosity were reduced for all the nanofluids. Also results for Darcy friction factor were evaluated. It is observed that TiO2 nanofluid friction factor was significantly reduced by 42–76% at the volume fraction of 0.05%; Al2O3 by 36–50% at 0.1%; TiO2 by 40–53% at 0.5%; and Al2O3 by 23–50% at 1.0%; respectively. SiO2 nanofluid friction factor was lightly reduced by 30–45%. Enhancement of WBM with nanoparticles were significant at lower volume fractions and at lower TCS speeds.

Analytical model based estimation of line edge roughness induced [formula omitted] variability in nanowire FETs

The line edge roughness (LER) is one of the most dominant sources of variability in sub 10 nm technology node devices such as FinFET and Nanowire FET (NWFET). Earlier, analytical models of LER based threshold voltage (VT) variability on FinFET have been comprehensively explored. However, the analytical modeling front for NWFET is still an open challenge. Specifically, the previous FinFET inspired analysis used a cross-sectional area-equivalent circular diameter as effective diameter (Deff). The Deff defines the local VT for a cross-section that enables a percolation based VT estimation for the NWFET. In this work, we show that minimum local diameter (Dmin) is a better predictor. Dmin captures the quantum confinement locally more accurately in the highly scaled NWFETs of interest to enable accurate percolation. The model is tested for LER infused NWFET structures and shows an excellent match against the well-calibrated Sentaurus TCAD deck with the RMS error less than 1.5 mV. The model is 5×105 times computationally efficient in comparison to conventional TCAD simulations. Moreover, the proposed Dmin based analytical model is 2.3× better in terms of accuracy and 10× faster as opposed to the state-of-the-art (i.e. Deff based model). Such analytical models can be integrated in BSIM CMG platform to enable device scaling study and its impact on circuit level performance predictions.

Laser Cleaning Surface Roughness Estimation Using Enhanced GLCM Feature and IPSO-SVR

In order to evaluate the effect of laser cleaning, a new method of workpiece surface roughness estimation is proposed. First, a Cartesian robot and visible-light camera are used to collect a large number of surface images of a workpiece after laser cleaning. Second, various features including the Tamura coarseness, Alexnet abstract depth, single blind/referenceless image spatial quality evaluator (BRISQUE), and enhanced gray level co-occurrence matrix (EGLCM) are computed from the images above. Third, the improved particle swarm optimization (IPSO) is used to improve the training parameters of support vector regression (SVR). The learning factor of SVR adopts the strategy of dynamic nonlinear asynchronous adaptive adjustment to improve its optimization-processing ability. Finally, both the image features and the IPSO-SVR are considered for the surface roughness estimation. Extensive experiment results show that the accuracy of the IPSO-SVR surface roughness estimation model can reach 92.0%.

High Level of Unwarranted Clinical Variation in the Use of Lower Extremity Revascularisation Procedures in Hungary (2013–2017)

Assessment of variations in the use of lower extremity open vascular surgical procedures (LEOPEN) and lower extremity endovascular procedures (LEENDO) across small geographic areas in Hungary from 2013 to 2017. Introduction of a new metric giving a rough estimate of unwarranted clinical variation in revascularisation practice. Spatial variation (at local administrative unit level) of referral for LEOPEN and LEENDO was evaluated through a retrospective analysis using healthcare administrative data of all beneficiaries in Hungary. The same assessment was performed for percutaneous coronary intervention in acute myocardial infarction (PCIAMI). The latter was considered a reasonable comparator (similar at risk population, well organised, guideline driven patient pathways, small room for referral discretion). Consequently, the ratio of spatial variations of LEOPEN and LEENDO to PCIAMI (as a reference) are thought to reflect unwarranted clinical variation. A total of 109 882 procedures were identified in the database (LEOPEN, LEENDO, PCIAMI) affecting 85 083 patients. While estimates of spatial variations for LEOPEN and LEENDO turned out to be high (systematic component of variation [SCV] 0.09 and 0.21, respectively), PCIAMI showed a low SCV value of 0.02. Consequently, the ratios of SCVs were SCV/SCVref = 4.67 (LEOPEN) and SCV/SCVref = 10.3 (LEENDO), indicating high levels of unwarranted clinical variation. The analysis showed that patients living in different locations of Hungary face very different odds of having lower extremity revascularisation procedures (open or endovascular). This spatial variation is thought to be related mainly to the failure in vascular service organisation. The newly introduced numerical estimate of unwarranted clinical variation may support within, and also between, system comparisons.

INFLUENCE OF URBAN LAND EXPROPRIATION ON CRIME RATE BASED ON AFFECTIVE DISORDER AND ANXIETY FACTORS

INFLUENCE OF URBAN LAND EXPROPRIATION ON CRIME RATE BASED ON AFFECTIVE DISORDER AND ANXIETY FACTORS

Silicones with different crosslinking patterns: Assessment from the perspective of their suitability for biomaterials

Silicones are one of the most important classes of synthetic biomaterials. In order to become stand-alone objects, they must be cross-linked. This can be achieved by chemical (radical, addition or condensation reactions) or physical (supramolecular interactions) processes, each requiring the presence of complementary functional groups and specific deployment conditions (organic, organo-metallic or metallic often non-removable catalyst, temperature, pressure, UV-irradiation, etc.), and leading to materials with particular characteristics in terms of bulk structure and surface. A number of such model networks have been prepared and evaluated from the perspective of their suitability as biomaterials. After the structural characterization by FT-IR spectroscopy aimed mainly at identifying residual functional groups that could affect their behavior, the samples were subjected to specific tests. Thus, the hydrolytic and enzymatic stability were studied in aqueous environments with different pH values. The surface analysis was done by atomic force microscopy (AFM), which allowed the highlighting of the topography and the estimation of the average roughness. The water, formamide, methylene iodide, and buffer solutions` contact angles, as well as blood interfacial tension were also determined. The biocidal activity against a series of fungi and bacteria was studied. The bio- and mucoadhesion of the films were evaluated by an appropriate technique, and the cell adhesion test was performed on Normal Human Dermal Fibroblasts (NHDF). The results indicate that, regardless of the crosslinking pattern, the films are hydrophobic, hydrolytically stable and biocompatible but bio-/mucoadhesivity are low, which recommends them as sutures and the series crosslinked by addition would be suitable for extrusion processes with “click” crosslinking.

Distributed collaborative navigation based on rank-defect free network

To improve the navigation performance for network operations, a 3-dimension distributed collaborative navigation method based on rank-defect free network is proposed. Only the nodes’ rough position estimations and their relative ranges are required and the information is shared through wireless communication. The situation is highly addressed where none or only one anchor is deployed. Due to the lack of necessary measurements to fully determine the absolute positions of all agents, the algorithm providing additional constraints is developed to derive the unique solution. The characteristics of the algorithm and the factors that influence the navigation accuracy are discussed. Comprehensive simulations are conducted with different network topologies, number of agents, initial position errors and range measurement uncertainties to verify the effectiveness of the proposed method. The influences of various configurations imposed on the accuracy of the collaborative navigation are researched and quantified in the perspective of the network rank-defect.