Real-Time Tracking of Human Neck Postures and Movements

Improper neck postures and movements are the major causes of human neck-related musculoskeletal disorders. To monitor, quantify, analyze, and detect the movements, remote and non-invasive based methods are being developed for prevention and rehabilitation. The purpose of this research is to provide a digital platform for analyzing the impact of human neck movements on the neck musculoskeletal system. The secondary objective is to design a rehabilitation monitoring system that brings accountability in the treatment prescribed, which is shown in the use-case model. To record neck movements effectively, a Smart Neckband integrated with the Inertial Measurement Unit (IMU) was designed. The initial task was to find a suitable position to locate the sensors embedded in the Smart Neckband. IMU-based real-world kinematic data were captured from eight research subjects and were used to extract kinetic data from the OpenSim simulation platform. A Random Forest algorithm was trained using the kinetic data to predict the neck movements. The results obtained correlated with the novel idea proposed in this paper of using the hyoid muscles to accurately detect neck postures and movements. The innovative approach of integrating kinematic data and kinetic data for analyzing neck postures and movements has been successfully demonstrated through the efficient application in a rehabilitation use case with about 95% accuracy. This research study presents a robust digital platform for the integration of kinematic and kinetic data that has enabled the design of a context-aware neckband for the support in the treatment of neck musculoskeletal disorders.

Design of a Bench-Scale Tubular Reactor Similar to Plug Flow Reactor for Gas-Phase Kinetic Data Generation-Illustration with the Pyrolysis of Octanoic Acid

The material described in this article deals with waste conversion into energy vectors by pyrolysis, steam cracking, or oxidation of liquid biomass, carried out at small to medium scale. The design of a bench-scale experimental setup devoted to gas phase kinetic data generation in a tubular reactor under laminar regime close to plug flow is detailed based on a very simple approach. Validation of the designed bench-scale setup was successfully carried out within the context of octanoic acid pyrolysis by generating kinetic data with satisfactory measurement repeatability and material balances. The key to this positive result is that axial dispersion coefficient is much smaller in gas-phase than in liquid-phase, thus allowing the designed small sized tubular reactor to be close to the plug flow reactor. Such a feature of the axial dispersion coefficient is not well known by the wider public. Besides, octanoic acid was selected as surrogate for carboxylic acids because of their key role in various industrial applications (combustion of ethyl biodiesel; production of biofuel and biosourced chemicals).

4,6-Dichloro-5-Nitrobenzofuroxan: Different Polymorphisms and DFT Investigation of Its Reactivity with Nucleophiles

This research focuses on the X-ray structure of 4,6-dichloro-5-nitrobenzofuroxan 1 and of some of its amino derivatives (4a, 4e, 4g, and 4l) and on DFT calculations concerning the nucleophilic reactivity of 1. We have found that by changing the solvent used for crystallization, it is possible to obtain 4,6-dichloro-5-nitrobenzofuroxan (1) in different polymorphic structures. Moreover, the different torsional angles observed for the nitro group in 1 and in its amino derivatives (4a, 4e, 4g, and 4l) are strictly dependent on the steric hindrance of the substituent at C-4. DFT calculations on the course of the nucleophilic substitution confirm the role of the condensed furoxan ring in altering the aromaticity of the carbocyclic frame, while chlorine atoms strongly influence the dihedral angle and the rotational barrier of the nitro group. These results corroborate previous observations based on experimental kinetic data and give a deep picture of the reaction with amines, which proceeds via a “non-aromatic” nucleophilic substitution.

Kinetics, Isotherms and Thermodynamic Studies on Removal of Divalent Copper using Mallet Flower Leaf Powder as Bio-Adsorbent

The effectiveness and efficacy of Mallet Flower Leaf Powder (MFLP) as a bio-sorbent for the removal of heavy metal copper ions from the aqueous solutions have been studied. Experiments were conducted varying the pH, agitation time, temperature, biosorbent size and dosage as parameters. Speed of the mixing is kept at 200 rpm. The analysis of copper was done by using Atomic Absorption Spectrophotometer (AAS). The adsorption of copper was found to be dependent on pH and a maximum removal of 98.78 % was obtained at an optimum pH of 6.0. The optimum biosorbent dosage was 1 g for an agitation time of 40 min. The biosorption data obtained were validated for the best isotherm. The data collected were verified with the available adsorption isotherms. Experimental data obtained was well represented by Langmuir (RL = 0.161, qm = 5.96 mg/g, R2 = 0.9142), Freundlich (n = 0.64, Kf = 0.79L/g, R2 = 0.9995) and Tempkin (R2 = 0.9083, bT = 267.63) isotherms, indicating favorable biosorption. The experimental data obtained were tested for the best fit and the Freundlich Model has yielded the best correlation with the highest regression coefficient, R2 = 0.9844. Kinetic data has also been presented using thermodynamic analysis and the pseudo second order model was found to be the best fit with a correlation coefficient of 0.999. For the removal of copper from the solution, bioadsorbent showed a maximum adsorption capacity of 5.96 mg/g. HIGHLIGHTS Removal of divalent copper from the aqueous solution using Mallet Flower Leaf powder Atomic Absorption Spectroscopy, Scanning Electron Microscopy and Fourier transform infrared analysis were used to characterize the Mallet Flower Leaf Powder Kinetic data has been presented using thermodynamic analysis and the pseudo second order model was found to be the best fit with a correlation coefficient of 0.999 The maximum adsorption capacity of MFLP for copper was found to be 5.96 mg/gm GRAPHICAL ABSTRACT

Near-Wall Aggregation of Amyloidogenic Aβ 1-40 Peptide: Direct Observation by the FRET

The formation of amyloid fibrils is one of the variants of the self-organization of polypeptide chains. For the amyloid aggregation, the solution must be oversaturated with proteins. The interface of the liquid (solution) and solid (vessel walls) phases can trigger the adsorption of protein molecules, and the resulting oversaturation can initiate conformational transitions in them. In any laboratory experiment, we cannot exclude the presence of surfaces such as the walls of vessels, cuvettes, etc. However, in many works devoted to the study of amyloid formation, this feature is not considered. In our work, we investigated the behavior of the Aβ 1-40 peptide at the water–glass, water–quartz, and water–plastic interface. We carried out a series of simple experiments and showed that the Aβ 1-40 peptide is actively adsorbed on these surfaces, which leads to a significant interaction and aggregation of peptides. This means that the interface can be the place where the first amyloid nucleus appears. We suggest that this effect may also be one of the reasons for the difficulty of reproducing kinetic data when studying the aggregation of the amyloid of the Aβ 1-40 peptide and other amyloidogenic proteins

Study of Adsorption Properties of Bentonite Clay

The clay used in this study was the bentonite from Mostagnem, Algeria. This material is used in many fields such as drilling, foundry, painting, ceramics, etc. It can also be applied in the treatment of wastewaters from chemical industries by means of adsorption. In this chapter the physicochemical properties of bentonite were determined by using several analyses techniques such as chemical composition, XRD, FTIR and SBET. The bentonite was intercalated by aluminum poly-cations solution and cethytrimethyl ammonium bromide. The acid activation of natural bentonite was performed by treatment with hydrochloric acid at different concentrations. The surface water pollutants removed by the modified bentonites are bemacid yellow E-4G and reactive MX-4R dyes, and fungicide chlorothalinil. The Langmuir and Freundlich adsorption models were applied to describe the related isotherms. The pseudo-first order and pseudo-second order kinetic models were used to describe the kinetic data. The changes of enthalpy, entropy and Gibbs free energy of adsorption process were also calculated.

Sorption of Uranium (VI) From Aqueous Solution Using Nanomagnetite Particles; Singly and Coated With Humic Acid

Magnetite nanoparticles (Fe3O4) and humic acid coated magnetite nanoparticles (Fe3O4/HA) were investigated for the removal of U(VI) from aqueous solution. Batch sorption experiments were studied as a function contact time, adsorbent mass, U(VI) concentration and pH. The sorption kinetic data follow the pseudo-second order while the isotherms are found to obey Langmuir model with maximum capacity (Qmax) of 230, 196 mg/g for Fe3O4 and Fe3O4/HA, respectively. The study reveals that humic acid decreases the sorption capacity due to the formation of a polyanionic organic coating and thus altering the surface properties of the particles and reduces the magnetite aggregation and stabilizes the magnetite suspension.

Agglomerative Clustering of Growing Squares

We study an agglomerative clustering problem motivated by interactive glyphs in geo-visualization. Consider a set of disjoint square glyphs on an interactive map. When the user zooms out, the glyphs grow in size relative to the map, possibly with different speeds. When two glyphs intersect, we wish to replace them by a new glyph that captures the information of the intersecting glyphs. We present a fully dynamic kinetic data structure that maintains a set of n disjoint growing squares. Our data structure uses $$O\bigl (n \log n \log \log n\bigr )$$ O ( n log n log log n ) space, supports queries in worst case $$O\bigl (\log ^2 n\bigr )$$ O ( log 2 n ) time, and updates in $$O\bigl (\log ^5 n\bigr )$$ O ( log 5 n ) amortized time. This leads to an $$O\bigl (n\,\alpha (n)\log ^5 n\bigr )$$ O ( n α ( n ) log 5 n ) time algorithm to solve the agglomerative clustering problem. This is a significant improvement over the current best $$O\bigl (n^2\bigr )$$ O ( n 2 ) time algorithms.