Automated lying-posture tracking is important in preventing bed-related disorders such as pressure injuries, sleep apnea, and lower-back pain. Prior research studied in-bed lying posture tracking using sensors of different modalities (e.g., accelerometer and pressure sensors). However, there remain significant gaps in research about how to design efficient in-bed lying posture tracking systems. These gaps can be articulated through several research questions as follows. First, can we design a single-sensor, pervasive, and inexpensive system that can accurately detect lying postures? Second, what computational models are most effective in the accurate detection of lying postures? Finally, what physical configuration of the sensor system is most effective for lying posture tracking? To answer these important research questions, in this article, we propose a comprehensive approach to design a sensor system that uses a single accelerometer along with machine learning algorithms for in-bed lying posture classification. We design two categories of machine learning algorithms based on deep learning and traditional classification with handcrafted features to detect lying postures. We also investigate what wearing sites are most effective in accurate detection of lying postures. We extensively evaluate the performance of the proposed algorithms on nine different body locations and four human lying postures using two datasets. Our results show that a system with a single accelerometer can be used with either deep learning or traditional classifiers to accurately detect lying postures. The best models in our approach achieve an F-Score that ranges from 95.2% to 97.8% with a coefficient of variation from 0.03 to 0.05. The results also identify the thighs and chest as the most salient body sites for lying posture tracking. Our findings in this article suggest that because accelerometers are ubiquitous and inexpensive sensors, they can be a viable source of information for pervasive monitoring of in-bed postures.

Animal welfare remains a very important issue in the livestock sector but monitoring animal welfare in an objective and continuous way remains a serious challenge. Monitoring animal welfare based upon physiological measurements instead of audio-visual scoring of behaviour would be a step forward. One of the obvious physiological signals related to welfare and stress is heart rate. The objective of this research was to measure heart rate (beat per minutes) on pigs with technology that soon will be affordable. Affordable heart rate monitoring is done today at large scale on humans using the Photo Plethysmography (PPG) technology. We used PPG sensors on pig’s body to test whether it allows getting reliable heart rate signal. A continuous wavelet transform (CWT)-based algorithm is developed to decouple the cardiac pulse waves from the pig. Three different wavelets, namely 2^nd, 4^th and 6^th order Derivative of Gaussian (DOG, are tested. We show results of the developed PPG-based algorithm against electrocardiograms (ECG) as a reference measure for heart rate and this for an anesthetized versus a non-anesthetised animal. We tested three different anatomical body positions (ear, leg and tail) and give results for each body position of the sensor. In summary, it can be concluded that the agreement between PPG-based heart rate technique and reference sensor goes from 91 to 95 percentage. In this paper we showed the potential of using the PPG-based technology to assess pig’s hear rate.

The chicken embryo is a widely used experimental animal-model in many studies such as developmental biology and to study the physiological responses and adaptation to altered environments as well as for cancer and neurobiology research. Embryonic heart rate is an important physiological variable useful as an index reflecting the embryo's natural activity and is considered one of the most difficult parameters to measure. An acceptable measurement technique of embryonic heart rate should provide a reliable cardiac signal quality while maintaining adequate gas exchange through the eggshell along the incubation and embryonic developmental period. In this paper, we presented a detailed design and methodology for a non-invasive PPG-based prototype (Egg-PPG) for real-time and continuous monitoring of embryonic heart rate during incubation. An automatic embryonic cardiac wave detection algorithm, based on normalised spectral entropy, is described. The developed algorithm successfully estimated the embryonic heart rate with 98.7% accuracy. We believe that the developed overall system presented in this paper is showing a promising solution for non-invasion, real-time monitoring of embryonic cardiac signal, which can be used in both experimental studies (e.g., developmental embryology and cardiovascular research) and in industrial incubation applications.

The compatibility of graphene or graphene oxide with its dispersion medium (polymer) plays a critical role in the formation nanocomposite materials with significant property improvements. Environmentally friendly miniemulsion polymerization, which allows a formation of nanoencapsulation in an aqueous phase and high molecular weight polymer/composite production is one promising method. In this study, we screened a series of amphiphilic modifiers and found that the quaternary ammonium (ar-vinyl benzyl) trimethyl ammonium chloride (VBTAC) pending carbon double bonds could effectively modify the graphene oxide (GO) to be compatible with the organophilic monomer. After that, free radical miniemulsion polymerization could successfully synthesize stable latex of exfoliated poly (methyl methacrylate) (PMMA)/ GO nanocomposite. The final latex had an extended storage life and a relatively uniform particle size distribution. X-ray powder diffraction (XRD), transmission electron microscopy (TEM), and scanning electron microscopy (SEM) analysis of this latex and its films indicated successful encapsulation of exfoliated nano-dimensional graphene oxide inside a polymer matrix.

There are many pollution and environment problem in the human ecosystem. There are different methods are used to removal of sulfur from sour gases for example Basic Claus process and Modified Claus process . There are different chemical software are used for simulation and optimization of Claus process for example Aspen Plus and Chemcad ECT. The Gibbs free energy method is introduced and model of Claus process. There are new parameter are introduced in reaction furnace to reduce the error from 33% to 7 %. The waste heat boiler is installed at the reaction furnace in which high pressure stream is produced and study the decomposition the hydrogen sulphide. The new rate of reaction is introduced of the enhancement of H2 production in chemical process. The simulation of reaction furnace in Aspen plus software is the maximum utilization of process. Due to suitable operating condition of reaction furnace is caused the maximum destruction of ammonia gas in the reactor. When we are increasing the oxygen concentration and temperature of feed is causing decreasing the ammonia production in reaction furnace. It is below than acceptance value of ammonia is 150 ppm in the reaction furnace. The presence of oxygen components, Sulfur oxide, hydroxide components are effect on decreasing the amount of ammonia in furnace and temperature is about at 1350⁰C. It is noted that when the production of sulfur recovery is decrease in Claus process and the production of carbon monoxide is increase in the thermal section at the existence. Now we are work on parametric studies of furnace that could be causes the production of ammonia destruction and CO emission in the Claus process. Due to optimize the reaction furnace parameter are help to get large of sulfur production, ammonia gas destruction, increased the catalyst life and decreased of dangerous gases.

Total Hip Arthroplasty is one of the most successful surgery. However, due to the worldwide growing population life expectancy and the related incidence of age-dependent bone diseases, a growing number of cases of intra-operative fractures lead to revision surgery with high rates of morbidity and mortality. Surgeons choose the type of the implant, either cemented or cementless prosthesis, on the basis of the age, the quality of the bone and the general medical conditions of the patients. Generally, no quantitative measures are available to assess the intra-operative fracture risk. Consequently, the decision-making process is mainly based on medical operators’ expertise and qualitative information obtained by imaging. Motivated by this scenario, we here propose a mechanical-supported strategy to assist surgeons in their decisions, by giving intelligible maps of the risk fracture which take into account the interplay between actual strength distribution inside the bone tissue and its response to the forces exerted by the implant. To this end, we produce charts and patient-specific synthetic “traffic-light” indicators of fracture risk, by making use of ad hoc analytical solutions to predict the stress levels in the bone by means of CT-based mechanical and geometrical parameters of the patient. We felt that, if implemented in a friendly software or proposed as an app, the strategy could constitute a practical tool to help the medical decision-making process, in particular with respect to the choice of adopting cemented or cementless implant

Central nervous system (CNS) uses vision, vestibular, and somatosensory information to maintain body stability. Research has shown that there is more lumbar proprioception error among low back pain (LBP) individuals as compared to healthy people. In this study, two groups of 20 healthy people and 20 non-specific low back pain participants (LBP) took part in this investigation. This investigation focused on somatosensory sensors and in order to alter proprioception, a vibrator (frequency of 70Hz, amplitude of 0.5 mm) was placed on the soleus muscle area of each leg and two vibrators were placed bilaterally across the lower back muscles. Individuals, whose vision was occluded, were placed on two surfaces (foam and rigid) on force plate, and trunk angles were recorded simultaneously. Tests were performed in 8 separate trials; the independent variables were vibration (4 levels) and surface (2 levels) for within subjects and 2 groups (healthy and LBP) for between subjects (4×2×2). MANOVA and multi-factor ANOVA tests were done. Linear parameters for center of pressure (COP) (deviation of amplitude, deviation of velocity, phase plane portrait (PPP), and overall mean velocity) and nonlinear parameters for COP and trunk angle ((recurrence quantification analysis) RQA and Lyapunov exponents) were chosen as dependent variables. Results indicated that NSLBP individuals relied more on ankle proprioception for postural stability. Similarly, RQA parameters for the COP on both sides and for the trunk sagittal angle indicated more repeated patterns of movement among the LBP cohort. Analysis of short and long Lyapunov exponents showed that people with LBP caused no use of all joints in their bodies (non-flexible), are less stable than healthy subjects.

There is a huge interest in developing novel hollow fiber (HF) membranes able to modulate neural differentiation to produce in vitro blood-brain barrier (BBB) models for biomedical and pharmaceutical research, due to the low cell-inductive properties of the polymer HFs used in current BBB models. In this work, poly(ε-caprolactone) (PCL) and composite PCL/graphene (PCL/G) HF membranes were prepared by phase inversion and were characterized in terms of mechanical, electrical, morphological, chemical, and mass transport properties. The presence of graphene in PCL/G membranes enlarged the pore size and the water flux and presented significantly higher electrical conductivity than PCL HFs. Biocompatibility assay showed that PCL/G HFs significantly increased C6 cells adhesion and differentiation towards astrocytes, may be attributed to their higher electrical conductivity in comparison to PCL HFs. On the other hand, PCL/G membranes produced a cytotoxic effect on the endothelial cell line HUVEC presumably related with a higher production of intracellular reactive oxygen species induced by the nanomaterial in this particular cell line. These results prove the potential of PCL HF membranes to grow endothelial cells and PCL/G HF membranes to differentiate astrocytes, the two characteristic cell types that could develop in vitro BBB models in future 3D co-culture systems.

The requirements for using noncyanide imitation gold plating as decorative electroplating are increasing; thus, continuously improving the quality of the coating of the imitation gold plating and optimizing the coating process have become the current priority. In this work, hydroxyethylidene diphosphonic acid (HEDP) was used as the main complexing agent, CuSO4·5H2O, ZnSO4·7H2O and NaSnO3·3H2O were the main salts, and NaOH and anhydrous sodium carbonate were used as the buffers to prepare the electroplating solution. Using sodium citrate (SC), sodium potassium tartrate (SS), sodium gluconate (SG), and glycerol (Gl) as four additives, the effects of the number of carboxyl groups on the properties of a Cu-Zn-Sn alloy coating were compared. The electrochemical analysis showed that Cu-Zn-Sn alloy codeposition occurred at -0.50 V vs. Hg|HgO. The scanning electron microscopy (SEM) results showed that the particle size of the coatings obtained with carboxyl-containing additives was more uniform than that obtained with the electroplating solution without additives. The X-ray fluorescence spectrometry (XRF) analysis revealed that the composition of the Cu-Zn-Sn alloy coating obtained by using SC as an additive in the electroplating solution was 89.75 wt% Cu, 9.61 wt% Zn, and 0.64 wt% Sn, and the color of the coating was golden yellow. The X-ray diffraction (XRD) pattern showed that the coating was a mixture of Cu, Cu5Zn8, CuSn, Cu6Sn5, and CuZn phases. The analysis of the electroplating solution by UV, IR and NMR spectroscopy methods indicates that the additives improve the coating by affecting the complexation reaction of metal ions. These results can provide technical and theoretical guidance for developing Cu-Zn-Sn ternary alloy electrodeposition technology with the new cyanide-free HEDP alkaline electroplating system.

We extend our high-resolution MRI-based Finite Element (FE) head model, previously presented and validated in [1–3], by considering the heterogeneities of the white matter structures captured through the use of Magnetic Resonance Elastography (MRE). This approach imparts more sophistication to our numerical model and yields results that more closely match experimental results. It is found that the peak pressure more closely matches the experiments as compared to the heterogeneous case. Qualitatively, we find differences in stress wave propagation near the corpus callosum and the corona radiata, which are stiffer on average than the global white matter. We are able to study the effects of these stiff structures on transient stress wave propagation within the cerebrum, something that cannot be done with a homogenized material model.

Nowadays, inherently safer designs are considered as key priorities to prevent or mitigate serious incidents with devastating consequences. The need for process safety assessment during early design phases has motivated the development of several contributions related to computer-aided assessment methodologies in order to measure the inherent safety of chemical processes. In this work, the large-scale production of chitosan from shrimp wastes was evaluated from process safety point of view using the numerical descriptive inherent safety technique (NuDIST).To this end, simulation of the chitosan production was performed using Aspen Plus ® to obtain extended mass and energy balances. The assessment of all the chemicals involved within the process was carried out for the following safety parameters: explosivity (EXP), flammability (FL) and toxicity (TOX). The safety assessment of the process included the parameters of temperature (T), pressure (P) and heat of reaction (HR). The maximum chemical safety score was estimated in 171.01 with ethanol as main contributor to the parameter of explosivity and flammability. The score associated with operating data was calculated in 209.30 and heat of reaction reported to be the most affecting parameter. The NuDIST score was estimated in 380.30. This NuDIST value revealed the low hazards associated with the handling of substances such as shrimp wastes, chitosan and water, as well as the non-extreme temperature and pressure conditions. In general, the large-scale production of chitosan from shrimp shells showed to be an inherently safe alternative of waste valorization.

Microalgal harvesting is one of the most challenging processes in the development of algal research and development. Several methods, such as centrifugation, flocculation, and filtration, are available at the laboratory scale. However, the requirement of expensive pieces of equipment and the possibility of biomass contamination are recurring gaps that hinder the development of microalgae I+D in different parts of the world. Recently, the electroflotation has been proved as a suitable method for the harvesting of different species of microalgae and cyanobacteria. To this day, there are no companies that sell laboratory-scale electroflotation equipment; this is mainly due to the gap in the knowledge on which factors (time, mixing rate, number of electrodes, and others) will affect the efficiency of concentration without reducing the biomass quality. This paper aims to build an innovative low-cost electroflotation system under 300 USD with cheap and resistant materials. To achieve our goal, we test the interaction of three variables (time, mixing rate, and amount of electrodes) were evaluated. Results showed that an efficiency closer to 100% could be achieved under 20 minutes using >10 electrodes and 150 rpm. We hope this innovative approach can be used by different researchers to improve our knowledge of the concentration and harvesting of algae and cyanobacteria.

We previously reported that corneal fibroblasts within 3D fibrin matrices secrete, bind, and organize fibronectin into tracks that facilitate cell spreading and migration. Other cells use these fibronectin tracks as conduits, which leads to the development of an interconnected cell/fibronectin network. In this study, we investigate how cell induced reorganization of fibrin correlates with fibronectin track formation in response to two growth factors present during wound healing: PDGF BB, which stimulates cell spreading and migration; and TGFβ1, which stimulates cellular contraction and myofibroblast transformation. Both PDGF BB and TGFb1 stimulated global fibrin matrix contraction (P < 0.005), however cell and matrix patterning were different. We found that during PDGF BB induced cell spreading, fibronectin was organized simultaneously with the generation of tractional forces at the leading edge of pseudopodia. Over time this led to the formation of an interconnected network consisting of cells, fibronectin and compacted fibrin tracks. Following culture in TGFβ1, cells were less motile, produced significant local fibrin reorganization, and formed fewer cellular connections as compared to PDGF BB (P < 0.005). Although bands of compacted fibrin tracks developed in between neighboring cells, fibronectin labeling was not generally present along these tracks, and the correlation between fibrin and fibronectin labeling was significantly less than that observed in PDGF BB (P < 0.001). Taken together, our results show that cell-induced ECM reorganization can occur independently from fibronectin patterning. Nonetheless, both events seem to be coordinated, as corneal fibroblasts in PDGF BB secrete and organize fibronectin as they preferentially spread along compacted fibrin tracks between cells, producing an interconnected network in which cells, fibronectin and compacted fibrin tracks are highly correlated. This mechanism of patterning could contribute to the formation of organized cellular networks that have been observed following corneal injury and refractive surgery.

Stroke often results in impaired gait, which can limit community ambulation and the quality of life. Recent works have shown the feasibility of transcranial Direct Current Stimulation (tDCS) as an adjuvant treatment to facilitate gait rehabilitation. Since the cerebellum plays an essential role in balance and movement coordination, which is crucial for independent overground ambulation, so, we investigated the effects of cerebellar tDCS (ctDCS) on the post-stroke overground gait performance in chronic stroke survivors. Fourteen chronic post-stroke male subjects were recruited based on convenience sampling at the collaborating hospitals where ten subjects finally participated in the ctDCS study. We evaluated the effects of two ctDCS montages with 2mA direct current, a) optimized configuration for dentate stimulation with 3.14cm² disc anode at PO10h (10/5 EEG system) and 3.14cm² disc cathode at PO9h (10/5 EEG system), and b) optimized configuration for leg lobules VII-IX stimulation with 3.14cm² disc anode at Exx8 (electrodes defined by ROAST) and 3.14cm² disc cathode at Exx7. We found ctDCS to be acceptable by all the exposed subjects. The ctDCS intervention had an effect on the 'Normalised Step length Affected side' (p=0.1) and 'Gait Stability Ratio' (p=0.0569), which was found using Wilcoxon signed-rank test at 10% significance level. Also, ctDCS montage specific effect was found using a two-sided Wilcoxon rank-sum test at a 5% significance level for 'Step Time Affected Leg' (p=0.0257) and '%Stance Time Unaffected Leg' (p=0.0376). Moreover, the changes in the quantitative gait parameters across both the montages were found to be correlated to the mean electric field strength in the lobules based on partial least squares regression analysis (R² statistic = 0.6574) where the mean electric field strength at the cerebellar lobules, Vermis VIIIb, Ipsilesional IX, Vermis IX, Ipsilesional X, had the most loading. In conclusion, our feasibility study indicated the potential of a single session of ctDCS to contribute to the immediate improvement in the balance and gait performance in terms of gait-related indices and clinical gait measures.

This article presents a methodology for the design of rehabilitation devices that considers factors involved in a clinical environment. This methodology integrates different disciplines that work together. The methodology is composed by 3 phases and 13 stages with specific tasks, the first phase includes the clinical context considering the requirements of the patient and therapist during the rehabilitation, the second phase is focused in engineering based on the philosophy of digital twin, and in the third phase is evaluated the device. This article explains the characteristics of the methodology and how it was applied in the design of an exoskeleton for passive rehabilitation of the upper limb.

Diabetes is a life-long illness, it requires life-long solution. Today’s treatment is trading one type of pain with another, never truly ride off the illness. When Artificial Pancreas (AP) offered a possibility of cure, it stirred up a great deal of interest in the diabetic community (1). The system was based on artificial intelligence. It can automate the dosing of insulin to reduce high blood sugar levels overnight. The most dangerous time for diabetes. Artificial Pancreas may be able to allow diabetic patients to sleep through the night without waking up to check and manage their blood glucose levels. It was a significant advancement. However, the achievement was limited: 76.4% in range with the system vs. 67.8% without the system. This accomplishment was creditable, but not optimal. If Artificial Pancreas was to be offered as a viable treatment for diabetes, it must be a life-long solution and must be a total solution. Artificial Pancreas has failed in this challenge. We decided to pursue an alternative approach, a self-regulated system: bioartificial pancreas. It has the potential became a complete cure.

EIT-MESHER (https://github.com/EIT-team/Mesher) is C++ software, based on the CGAL library, which generates high quality Finite Element Model tetrahedral meshes from binary masks of 3D volume segmentations. Originally developed for biomedical applications in Electrical Impedance Tomography (EIT) to address the need for custom, non-linear refinement in certain areas (e.g. around electrodes), EIT-MESHER can also be used in other fields where custom FEM refinement is required, such as Diffuse Optical Tomography (DOT).

In this study, silver-strontium doped hydroxyapatite (AgSr-HA)/chitosan composite coatings were deposited on stainless steel (SS) substrate via electrophoretic deposition (EPD) technique. The EPD parameters such as the concentration of Ag Sr-HA particles in the suspension, applied voltage and deposition time were optimized on by the Taguchi Design of Experiment (DoE) approach. DOE approach elucidated that the “best” coating was obtained at; the deposition voltage of 20V, deposition time of 7 minutes, and at 5 g/L of Ag Sr-HA particles in the suspension. The optimum coatings were characterized by using scanning electron microscopy (SEM) and energy dispersive X-ray (EDX) spectroscopy. SEM images confirmed the deposition of chitosan/Ag Sr-HA on the SS substrate. The wettability studies indicated the hydrophilic nature of the chitosan/Ag Sr-HA coatings, which confirmed the suitability of the developed coatings for orthopedic applications. The average surface roughness of the chitosan/Ag Sr-HA coatings was in a suitable range for the attachment of bone marrow stromal cells. Chitosan/Ag Sr-HA coatings showed a potent antibacterial effect against the Gram-Positive and Gram-negative bacteria.

The search for lower cost materials that reduce pressure drop in fluid transport systems in oil and gas industries to conserve pumping energy is of paramount importance. Polymers are known to reduce pressure drop in pipeline oil-water flows in a process referred to as drag reduction (DR). The effect of partially hydrolysed polyacrylamide, polyethylene oxide, aloe vera mucilage and their mixtures as drag reducing polymers (DRPs) on pressure gradient (pressure drop; Δp) in pipeline oil-water flows was studied. The experiment was carried out in flow rig with 0.02-m diameter straight unplasticised polyvinylchloride (uPVC) pipe, two centrifugal pumps, control valves and two storage tanks. Tap water (ρ = 997 Kg/m³ and µ = 0.89 cP) and diesel (ρ = 832 Kg/m³ and µ = 1.66 cP) were used as the test fluid at ambient condition. The polymer mixture total concentration (MTC) of 30 and 400 ppm at different mixing proportion, mixture Reynolds number (Re_mix) and oil input volume were investigated. The results show increase in pressure gradient with increase in oil input volume in both single-phase water flow and oil-water flow before adding drag reducing polymers (DRPs). But Δp decreased after adding DRPs with increase in Reynolds number (Re) or Re_mix and decrease in the oil-phase Re, vice versa. The results further showed higher reduction in pressure drop by the polymer mixture than in each of the polymer used at the same conditions. The rigidness of the biopolymer was improved by adding synthetic polymers which result to increase in DR efficiency.The search for lower cost materials that reduce pressure drop in fluid transport systems in oil and gas industries to conserve pumping energy is of paramount importance. Polymers are known to reduce pressure drop in pipeline oil-water flows in a process referred to as drag reduction (DR). The effect of partially hydrolysed polyacrylamide, polyethylene oxide, aloe vera mucilage and their mixtures as drag reducing polymers (DRPs) on pressure gradient (pressure drop; Δp) in pipeline oil-water flows was studied. The experiment was carried out in flow rig with 0.02-m diameter straight unplasticised polyvinylchloride (uPVC) pipe, two centrifugal pumps, control valves and two storage tanks. Tap water (ρ = 997 Kg/m³ and µ = 0.89 cP) and diesel (ρ = 832 Kg/m³ and µ = 1.66 cP) were used as the test fluid at ambient condition. The polymer mixture total concentration (MTC) of 30 and 400 ppm at different mixing proportion, mixture Reynolds number (Re_mix) and oil input volume were investigated. The results show increase in pressure gradient with increase in oil input volume in both single-phase water flow and oil-water flow before adding drag reducing polymers (DRPs). But Δp decreased after adding DRPs with increase in Reynolds number (Re) or Re_mix and decrease in the oil-phase Re, vice versa. The results further showed higher reduction in pressure drop by the polymer mixture than in each of the polymer used at the same conditions. The rigidness of the biopolymer was improved by adding synthetic polymers which result to increase in DR efficiency.

Phenotype variation is produced through a complex of interactions between genotype and environment. Phenotype, genotype, and environment are addresses the relationship between architecture and identity. The term genotype biology and phenotype have been adopted into architecture in the late twentieth century. Genotypes are abstract relational models that govern the arrangement of space, and the principle of organizing space and phenotypes is the real realization of genotypes in the physical environment. The genotype is a reflection that is not only about the spatial organization but also the nature of social and cultural patterns. Then this study purpose to an understanding of the connectedness variant phenotype from a genotype and environment. The repetition pattern being stable structure in variation phenotype uses as a database to finding an identity in architecture. The method used in this research was Levi Strauss's structuralism and multi-layer of a biological system. This research samples traditional Malay houses in West Borneo, Indonesia. These houses have a unique site and existing environment. The houses can be found mainly along the river. The results found from the phenotype, genotype, and environment have value and meaning as a traditional Malay house rule in West Borneo which was always handed down from generation to generation.

Cell free systems are a widely used research tool in systems and synthetic biology and a promising platform for manufacturing of proteins and chemicals. In the past, cell free biology was primarily used to better understand fundamental biochemical processes. Notably, E. coli cell free extracts were used in the 1960s to decipher the sequencing of the genetic code. Since then, the transcription and translation capabilities of cell free systems have been repeatedly optimized to improve energy efficiency and protein yield. Today, cell free systems, in combination with the rise of synthetic biology, have taken on a new role as a promising technology for just in time manufacturing of therapeutically important biologics and high-value small molecules. They have also been implemented in an industrial scale for the production of antibodies and cytokines. In this review, we discuss the evolution of cell free systems, advancements in cell free protein synthesis, and cell free metabolic engineering, and conclude with discussing the importance and feasibility of mathematical modeling in cell free systems.

Almond (Prunus dulcis (Mill.) D.A.Webb) is one of the most important nut crops both in terms of area and production. Over the last decades, an important part of the beneficial actions for health associated with their consumption was attributed to the phenolic compounds, mainly accumulated in almond skin. Interestingly, after cold-pressed oil extraction, most of these antioxidant phenolic compounds are retained in a skin-enriched by-product, so-called almond cold-pressed oil residue. In Morocco, ranked fifth producer in the world, this production generates an important part of this valuable byproduct. In the present study, using a multivariate Box-Behnken design, an ultrasound-assisted extraction (USAE) method of phenolic compounds from Moroccan almond cold-pressed oil residue was developed and validated. Response surface methodology resulted in the optimal extraction conditions: the use of aqueous EtOH 53.0% (v/v) as green solvent, applying an US frequency of 27.0 kHz for an extraction duration of 29.4 min. The present USAE allowed substantial gains in terms of extraction efficiency compared to conventional heat reflux extraction. Applied to 3 different local Beldi genotypes growing at 3 different experimental sites, the optimal USAE conditions led to a total phenolic content of 13.86 mg/g dry weight (DW). HPLC analysis revealed that the main phenolic compounds from this valuable byproduct were: chlorogenic acid followed by protocatechuic acid, p-hydrobenzoic acid and p-coumaric acid. The accumulation of these phenolic compounds appeared to be more dependent on the genetic background than on the environmental impact here represented by the 3 experimental culture sites. Both in vitro cell free and cellular antioxidant assays were performed, and revealed the great potential of these extracts. In particular, correlation analysis evidenced the prominent roles of chlorogenic acid, protocatechuic acid and p-hydrobenzoic acid. To summarize, the USAE method presented here is a quick, green, simple and efficient validated USAE for the possible valorization of antioxidant phenolic compounds from Moroccan almond cold-Pressed oil residues, making it possible to generate extracts with attractive antioxidant activities for future nutraceutical and/or cosmetic applications.

The interest in dry EEG electrodes has increased in recent years and especially as everyday suitability earplugs for measuring drowsiness or focus of auditory attention. However, the challenge is still the need for a good electrode material, which is reliable and can be easily processed for highly personalized applications. Laser processing as used here is a fast and very precise method to produce personalized electrode configurations that meet the high requirements of in-ear EEG electrodes, for example. The arrangement of the electrodes on the very flexible and compressible mats allows an exact alignment of the electrodes to the ear mold and contributes to a high wearing comfort, as no edges or metal protrusions are present. For better transmission properties, an adapted coating process for surface enlargement of platinum electrodes is used, which allows easy control of the thickness and growth form of the porous layer. The porous platinum-copper alloy is chemically very stable, shows no exposed copper residues and enlarges the effective surface area by 40. In a proof-of-principle experiment, these porous platinum electrodes could be used to measure the Berger effect in a dry state using just one ear of a test person. Their signal-to-noise ration and frequency transfer function is comparable to gel-based silver/silver chloride electrodes.

This study presents a new kinetic scheme for the mass yield prediction of waste lignocellulosic biomasses treated by Hydrothermal Carbonization (HTC). The proposed reactions are based on the decomposition, solubilization, and polymerization of each main fraction of the biomass: cellulose, hemicellulose, and lignin. The ash content was assumed to be inert. The kinetic parameters have been obtained by non-linear adjustment using a data set with 220 experimental runs collected from the literature. The results indicate that the pre-exponential factors range was from 7.33 x10¹ to 1.412x10⁵ min^-1, and activation energies were between 33.75 y 225.3 kJ/mol. A good fit is achieved between the observed and predicted data with an R² of 0.81 and an RMSE of 7.7 %. The proposed scheme was validated with the experimental data obtained by the HTC of sawdust (Pinus radiata) and rapeseed (Brassica napus). The experiments were carried out at temperatures of 190, 220, and 250 ºC and reaction times of 0, 30, 60, 90, and 120 min. The predicted values showed an average error of 2.3 and 3.5 %, respectively. Therefore, the kinetic scheme is a useful tool in the conversion analysis of waste biomass treated by HTC.

The prevention, mitigation and treatment of movement impairments, ideally, requires early diagnosis or identification. As the human movement system has physiological and functional redundancy, movement limitations do not promptly arise at the onset of physical decline. A such, prediction of movement limitations is complex: it is unclear how much decline can be tolerated before movement limitations start and how humans select compensatory movement strategies for a task. Adding to the challenge is the lack of general applicable and consensus terminology on movement limitations. Currently, the term ‘homeostatic reserve’ or ‘physiological reserve’ is used to refer to the redundancy of the human biological system, but this does not describe the redundancy in the muscle architecture of the human body. This article therefore proposes CaReMoOC, a framework incorporating neuromusculoskeletal capacity (accumulation of neuromusculoskeletal resources over the lifespan), reserve (task-specific difference between capacity and task demand), movement objectives (considerations made to plan a movement), and compensation (use of NMSK resources to respond to the task demand). Two forms of compensation are Compensation for Capacity, when capacity does not meet the task demands, and Compensation for Movement Objectives, when the movement is changed due to for example a fear of falling. This article demonstrates the framework for healthy ageing, providing an overview of age-related capacity decline (neural, skeletal, muscular system) and shifted weighting of movement objectives (energy, pain, stability, speed) relevant for experimental and modelling research in biomechanics and motor control. CaReMoOC provides a means to communicate hypotheses and theories on movement impairments and limitations. To predict movement limitations, we need to find ways to quantify NMSK reserve.

Cell free systems are a widely used research tool in systems and synthetic biology and a promising platform for manufacturing of proteins and chemicals. In the past, cell free biology was primarily used to better understand fundamental biochemical processes. Notably, E. coli cell free extracts were used in the 1960s to decipher the sequencing of the genetic code. Since then, the transcription and translation capabilities of cell free systems have been repeatedly optimized to improve energy efficiency and protein yield. Today, cell free systems, in combination with the rise of synthetic biology, have taken on a new role as a promising technology for just in time manufacturing of therapeutically important biologics and high-value small molecules. They have also been implemented in an industrial scale for the production of antibodies and cytokines. In this review, we discuss the evolution of cell free systems, advancements in cell free protein synthesis, and cell free metabolic engineering, and conclude with discussing the importance and feasibility of mathematical modeling in cell free systems.

The 2019 Novel Coronavirus (COVID-19) has caused an acute reduction in world supplies of personal protective equipment (PPE) due to increased demand. To combat the impending shortage of equipment including N95 masks, the George Washington University Hospital (GWUH) developed a 3D printed reusable N95 comparable respirator that can be used with multiple filtration units. We evaluated several candidate prototype respirator models, 3D printer filaments, and filtration units detailed here. Our most recent working model was based on a respirator found on an open source maker website and was developed with PLA (printer filament), a removable cap, a removable filtration unit consisting of two layers of MERV 16 sandwiched between MERV 13, and removable elastic bands to secure the mask. Our candidate mask passed our own suction test protocol to evaluate leakage and passed a qualitative Bitrix N95 fit test at employee health at GWUH. Further efforts are directed at improving the current model for seal against face, comfort, and sizing. The 3D model is available upon request and in the supplement of this paper. We welcome collaboration with other institutions and suggest other facilities consider mask fit for their own population when exploring this concept.

Nowadays, the uses of laser and optics in the medical areas are extremely vivid, especially low-level laser therapy. The light with the wavelength of 633 nm to 1200 nm could penetrate and propagate deep in biological tissue. To develop the low-level laser therapy device, optimizing light delivery is critical to accurately stimulate the biological effects inside the biological tissue. Nevertheless, each form of the tissues at each zone on the body had various refractive optic, absorption, scattering, and anisotropy coefficients. This paper describes the simulation results of low-level laser propagation from skin surface at the lower spine, the knee, the femur and the prostate gland with four wavelengths (633 nm, 780 nm, 850 nm, and 940 nm) by the Monte Carlo method. These simulation results are the base for developing the low-level laser therapy device, that could be used in clinical for treating the fracture, knee osteoarthritis, spinal degeneration, and benign prostatic hypertrophy.

Finding an optimal combination of features and classifier is still an open problem in the development of automatic heartbeat classification systems, especially when applications that involve resource-constrained devices are considered. In this paper, a novel study of the selection of informative features and the use of a random forest classifier while following the recommendations of the Association for the Advancement of Medical Instrumentation (AAMI) and an inter-patient division of datasets is presented. Features were selected using a filter method based on the mutual information ranking criterion on the training set. Results showed that normalized R-R intervals and features relative to the width of the QRS complex are the most discriminative among those considered. The best results achieved on the MIT-BIH Arrhythmia Database were an overall accuracy of 96.14% and F1-scores of 97.97%, 73.06%, and 90.85% in the classification of normal beats, supraventricular ectopic beats, and ventricular ectopic beats respectively. In comparison with other state of the art approaches tested under similar constraints, this work represents one of the highest performances reported to date while relying on a very small feature vector.

Microfluidics technology has not impacted the delivery and accessibility of point of care health services like diagnosis of infectious disease diagnosis, monitoring health or delivering interventions. Most microfluidics prototypes from academic research are not easy to manufacture with industrial scale fabrication techniques and cannot be operated without complex manipulations of supporting equipment and additives such as labels or reagents. We propose a label- and reagent-free inertial spiral microfluidic device to separate red blood, white blood and dendritic cells from blood fluid for applications in health monitoring and immunotherapy. We demonstrate that using larger channel widths in the range of 200 to 600 µm allows separation of cells into multiple streams according to different size ranges and we utilize a novel technique to collect the closely separated focused cell streams without constricting the channel. When tested on actual human blood cells, 77% of dendritic cells were separated and 80% of cells remained viable after our assay. Our contribution is a method to adapt spiral inertial microfluidic designs to separate more than two cell types in the same device which is robust against clogging, simple to operate and suitable for fabrication and deployment in resource-limited populations.

Myoelectric control is the cornerstone of many assistive technologies used in clinical practice, such as prosthetics and orthoses, and human-computer interaction, such as virtual reality control. Although the performance of such devices exceeds 90\% in controlled environments, myoelectric devices still face challenges in robustness to variability of daily living conditions. Within this survey, the intrisic physiological mechanisms limiting practical implementations of myoelectric devices were explored: the limb position effect and the contraction intensity effect. The degradation of electromyography (EMG) pattern recognition in the presence of these factors was demonstrated on six datasets, where performance was 13% and 20% lower in realistic environments compared to controlled environments for the limb position and contraction intensity effect, respectively. The experimental designs of limb position and contraction intensity literature were surveyed. Current state-of-the-art training strategies and robust algorithms for both effects were compiled and presented. Recommendations for future limb position effect studies include: the collection protocol providing exemplars of 6 positions (four limb positions and three forearm orientations), three-dimensional space experimental designs, transfer learning approaches, and multi-modal sensor configurations. Recommendations for future contraction intensity effect studies include: the collection of dynamic contractions, nonlinear complexity features, and proportional control.

Paper-based sensors, microfluidic platforms and electronic devices have attracted attention in the past couple of decades because they are flexible, can be recycled easily, environmentally friendly, and inexpensive. Here we report a paper aptamer-based potentiometric sensor to detect the whole Zika virus for the first time with a minimum sensitivity of 2.6 nV/Zika and the minimum detectable signal (MDS) of 1.2x10⁶ Zika. Our paper sensor works very similar to a P-N junction where a junction is formed between two different wet regions with different electrochemical potentials near each other on the paper. These two regions with slightly different ionic contents, ionic species and concentrations, produce a potential difference given by the Nernst equation. Our paper sensor consisted of a 2-3 mm x 10 mm segments of a paper with a conducting silver paint contact patches on its two ends. The paper is soaked in a buffer solution containing aptamers designed to bind to the capsid proteins on Zika. Atomic force microscopy studies were carried out to show both the aptamer and Zika become immobilized in the paper. We then added the Zika (in its own buffer) to the region close to one of the silver-paint contacts. The Zika virus (40 nm diameter with 43 kDa or 7.1x10^-20 gm weight), became immobilized in the paper’s pores and bonded with the resident aptamers creating a concentration gradient. The potential measured between the two silver paint contacts reproducibly became more negative as upon adding the Zika. We also showed that an LCD powered by the sensor, can be used to detect the sensor output.

Our main objective in this work was to examine the possibility of non-intrusive, label-free, detection of whole Zika viruses using terahertz signals with or without a targeting/binding oligonucleotide (aptamers). We report for the first time the use of terahertz electromagnetic waves (0.75 THz – 1.1 THz) to detect Zika viruses. The Zika/aptamer complexes showed a reproducible terahertz reflection coefficient minimum at 1.064 THz while the Zika virus’s reflection minimum was at 1.073 THz. Of different substrates we examined, the polyester petri dish provided a very low loss and excellent terahertz transmission. To increase the interaction between the terahertz signal and the sample we also used polyester microbeads coated with aptamers. We then measured the terahertz reflection from the microbeads as a function of Zika concentration. The resulting terahertz Zika sensor had sensitivity of 63 Hz/Zika and minimum detectable signal of ~ 16x10³ Zika. Other substrates such as Graphene on polyethylene terephthalate (PET), 50 nm-thick gold film on polycarbonate, thin (30 um-thick) glass slide and Teflon were also examined. Graphene substrate enabled direct detection of the Zika without any aptamers.

Biomolecular structure drives function, and computational capabilities have progressed such that the prediction and computational design of biomolecular structures is increasingly feasible. Because computational biophysics attracts students from many different backgrounds and with different levels of resources, teaching the subject can be challenging. One strategy to teach diverse learners is with interactive multimedia material that promotes self-paced, active learning. We have created a hands-on education strategy with a set of fifteen modules that teach topics in biomolecular structure and design, from fundamentals of conformational sampling and energy evaluation to applications like protein docking, antibody design, and RNA structure prediction. Our modules are based on PyRosetta, a Python library that encapsulates all computational modules and methods in the Rosetta software package. The workshop-style modules are implemented as Jupyter Notebooks that can be executed in the Google Colaboratory, allowing learners access with just a web browser. The digital format of Jupyter Notebooks allows us to embed images, molecular visualization movies, and interactive coding exercises. This multimodal approach may better reach students from different disciplines and experience levels as well as attract more researchers from smaller labs and cognate backgrounds to leverage PyRosetta in their science and engineering research. All materials are freely available at https://github.com/RosettaCommons/PyRosetta.notebooks.

Development of accelerometer-based lameness (mobility) detection has focused on cow behaviors such as lying and walking. Several studies, usually small, have reported levels of accuracy up to 91%. However, there has been limited independent replication of these results. In this study, behavior measures previously identified as being associated with lameness such as lying bouts and walking time are examined in relation to mobility score. On a research farm and a commercial farm, four trials were completed with 65 grazing cows. The cows had differing mobility scores ranging from perfect mobility to impaired mobility. Behavior was monitored using leg worn accelerometers. In general, behavior and mobility associations identified in previous studies were not found. Behavior monitoring with accelerometers as a basis to classify impaired mobility in pasture-based contexts thus remains challenging.

In tele-monitoring, wireless body area networks (WBANs), sleep analysis and other applications involving electroencephalogram (EEG) signal, due to the high number of EEG recording channels, long recording time and several repetition of recordings to reach the highest signal-to-noise ratio, the amount of acquired data by the sensors is too large, demanding use of some compression procedure. Compressed sensing can be considered as one of the most effective compression methods in terms of compression ratio, which needs the underlying signal be sparse or have sparse representation in an appropriate domain. EEG signal is not sparse in time domain, therefore, in this paper correlation based weighted recursive least squares dictionary learning algorithm (CBW-RLS) is proposed that uses between-channel correlations to sparsify EEG signals. Due to the low-rank structure of EEG signals, exploiting between-channel correlations increase the sparsity level of the model while reducing the computational cost of dictionary learning procedure. This is done by merely updating the dictionary atoms which are involved in the sparse model of the previous data, reducing the total number of data used at each iteration and speeding up the dictionary learning algorithm. The simulation results show that the proposed method has better performance in terms of both quality of the EEG reconstruction and the computational cost compared to the other methods.

Organoid engineering promises to revolutionize medicine with wide ranging applications of scientific, engineering, and clinical interest, including precision and personalized medicine, gene editing, drug development, disease modeling, cellular therapy, and a basic understanding of human development. Organoids are a three-dimensional (3D), miniature, caricature of a target organ, are initiated with stem/progenitor cells, and are extremely promising tools to model organ function. The biological basis for organoids is that they foster stem cell-self renewal, differentiation, and self-organization, recapitulating tissue structure or function better than 2D systems. In this review, we first discuss the importance of epithelial organs and the general properties of epithelial cells to provide context for the liver, pancreas, and gall bladder and rationale for organoid cultures. Next, we develop a general framework to understand self-organization, tissue hierarchy, and organoid cultivation. For each of these areas, we provide historical context, and review both a wide range of biological and/or biophysical/mathematic perspectives that enhances understanding of organoids. Next, we review existing techniques and progress in hepatobiliary and pancreatic organoid engineering. To do this, we review organoids from both primary tissues, cell lines, and stem cells, and introduce engineering studies when applicable. Noninvasive assessment of 1 organoids can reveal underlying biology and enable improved assays for growth, metabolism, and function. Applications of organoid for cell therapy are also discussed. Taken together, we establish a broad strong scientific foundation for organoids and provide an in-depth review of hepatic, biliary and pancreatic organoids.

Aim: To develop an index for quantitative assessment of the upper limb motor function in children with cerebral palsy before and after robot-assisted therapy. Method: An upper limb motor function index was developed using kinematic, surface electromyography and three-axis inertial measurements unit data collected from 15 children with cerebral palsy (CP) and 15 typically developed children. Children with CP underwent 18 robot-assisted therapy sessions with the REAplan device. All children were evaluated, using kinematic data from the REAplan, electromyography and three-axis inertial measurements unit readings from its accelerometer. A principal component analysis was conducted to produce an evaluation index, which is able to detect the deviation from the upper limb motor function of typically developing children group. Children with CP were evaluated twice before and after the intervention with Box and Blocks test and Finger-To-Nose test. The discriminative and concurrent validity of the upper limb motor function index were investigated. Results: The upper limb motor function index was higher in children with CP post therapy (p<0.001). Finger-To-Nose test values improved after robot-assisted therapy (p<0.03). A weak but positive correlation was observed between upper limb motor function index and clinical tests (r=0.012, p=0.95 and r=0.13, p= 0.54 for Box and Blocks test and Finger-To-Nose test respectively). Interpretation: The upper limb motor function index successfully differentiated between the typically developing children and children with CP and was effective in assessing the improvement of the upper limb motor function after robot-assisted therapy. The upper limb motor function index could be extended to assess and monitor rehabilitation therapies of other populations, such as those with stroke and Parkinson’s disease.

Microsystems are key enabling technologies, with applications found in almost every industrial field, including in-vitro diagnostic, energy harvesting, automotive, telecommunication, drug screening, etc. Microsystems, such as microsensors and actuators, are typically made up of components below 1000 microns in size that can be manufactured at low-unit cost through mass-production. Yet, the development of microsystems for commercial or educational purposes, has typically been limited to upper income countries due to the initial investment costs associated with the microfabrication equipment and processes. However, recent technological advances have enabled the development of low-cost microfabrication tools. In this paper, we describe a range of low-cost approaches and equipment (below £1000), developed or adapted and implemented in our laboratories. We describe processes including photolithography, micromilling, 3D printing, xurography and screen-printing used for the microfabrication of structural and functional materials. The processes that can be used to shape a range of materials with sub-millimetre feature sizes are demonstrated here in the context of Lab-on-Chips, but they can be adapted for other applications. We anticipate that this paper, which will enable researchers to build a low-cost microfabrication toolbox in a wide range of settings, will spark a new interest in microsystems.

The role of circulating plasma cells (CPCs) and circulating leukemic cells (CLCs) as biomarkers for several blood cancers, such as multiple myeloma and leukemia, respectively, have recently been reported. These markers can be attractive due to the minimally invasive nature of their acquisition through a blood draw (i.e., liquid biopsy) negating the need for painful bone marrow biopsies. CPCs or CLCs can be used for cellular/molecular analyses, such as immunophenotyping or fluorescence in situ hybridization (FISH). FISH, which is typically carried out on slides involving complex workflows, becomes problematic when operating on CLCs or CPCs due to their relatively modest numbers. Here, we present a microfluidic device for characterizing CPCs and CLCs enriched from peripheral blood using immunofluorescence or FISH. The microfluidic possessed an array of cross-channels (2-4 µm in depth and width) that interconnected a series of input and output fluidic channels. Placing a cover plate over the device formed microtraps, the size of which was defined by the width and depth of the cross-channels. This microfluidic chip allowed for automating immunofluorescence and FISH requiring the use of small volumes of reagents, such as antibodies and probes, as compared to slide-based immunophenotyping and FISH. In addition, the device could secure FISH results in <4 h compared to 2-3 d for conventional FISH.

The purpose of this study is to determine the equilibrium conditions for the formation of a mixture of propane and normal butane hydrates including temperature, pressure and mole fraction. In order to prevent the formation of hydrates in the cooling path, it is necessary to examine the conditions of hydrate formation and provide solutions. Modeling of hydrate formation conditions was performed using Hydoff software and compared with experimental results in this field, which obtained an acceptable error percentage. The range of temperature is between 267-276 °C and the molar percentage of propane is 0.7,0.8 and 0.9 and the mathematical equation was presented to predict hydrate formation. By analyzing the results, it was found that by increasing the concentration of ethane in the presence of other compounds, hydrate growth increased and hydrates formed more stable, also by increasing the concentration of propane and normal butane the amount of equilibrium pressure will decrease.

The separation of microparticles with respect to different properties such as size and material is a research field of great interest. Dielectrophoresis, a phenomenon which is capable of addressing multiple particle properties at once, can be used to perform a chromatographic separation. However, the selectivity of current dielectrophoretic particle chromatography (DPC) techniques is limited. Here we show a new approach for DPC based on differences in the dielectrophoretic mobilities and the crossover frequencies of polystyrene particles. Both differences are addressed by modulating the frequency of the electric field to generate positive and negative dielectrophoretic movement to achieve multiple trap and release cycles of the particles. A chromatographic separation of different particle sizes revealed a voltage dependency of this method. Additionally, we showed the frequency bandwidth influence on separation using one example. The DPC method developed was tested with model particles but offers possibilities to separate a broad range of plastic and metal microparticles or cells and to overcome currently existing limitations in selectivity.

In the present paper four passive micromixers designs (G1, G2, G3 and G4) inspired on distillation columns trays were proposed. The devices performance was assessed by numerical simulations. The mixing performance was investigated for a Reynolds number range from 0.01 to 100 and channel height of 200 µm, 500 µm and 1000 µm for oil/ethanol flow. G1 and G4 designs provided high mixing index (> 0.975). The G1 device achieved superior mixing performance with a moderate pressure drop (about 0.5 MPa) due to the induced flow recirculation pattern for a relative high flow rate of 0.21 L/min, highlighting the potential use of such microdevice for scale-up and numbering-up of microdevices in modular chemical plant processing.

State-of-the-art dielectrophoretic (DEP) separation techniques provide unique properties to separate particles from a liquid or particles with different properties such as material, morphology or size from each other. However, such separators do not operate at throughput that is sufficient for a vast fraction of separation tasks. The reason for this limitation is that, in order to move particles by dielectrophoresis, high electric field gradients to drive the separation are required. Conventionally, those gradients are generated by electrode microstructures that limit the maximum channel size. Here, we investigate DEP filtration, a technique that uses open porous microstructures instead of microfluidic devices to easily increase the filter cross section and therefore also the processable throughput by several orders of magnitude. Previously, we already separated baker’s yeast by DEP filtration in open porous ceramic structures. Now, we give a more elaborate experimental study about DEP filtration in these open porous structures and separate model particles, that are an order of magnitude smaller (500 nm, polystyrene), from aqueous suspensions. Almost 100% separation at flow rates of up to 9 mL min^-1 was achieved while the majority of the trapped particles could be recovered. We show how particle separation depends on key parameters (voltage, throughput, filter structure size). Further, we work towards selective particle separation and show that particle separation is very dependent on the particle polarizability: This creates the possibility to adjust selectivity by changing the electrical conductivity of the suspension around that of the particle. This study highlights the unique qualities of dielectrophoretic filtration enabling switchable, selective, and scalable particle separation to solve existing problems such as cell separation or precious metal recovery.

The separation of microparticles with respect to different properties such as size and material is a research field of great interest. Dielectrophoresis, a phenomenon which is capable of addressing multiple particle properties at once, can be used to perform a chromatographic separation. However, the selectivity of current dielectrophoretic particle chromatography (DPC) techniques is limited. Here we show a new approach for DPC based on differences in the dielectrophoretic mobilities and the crossover frequencies of polystyrene particles. Both differences are addressed by modulating the frequency of the electric field to generate positive and negative dielectrophoretic movement to achieve multiple trap and release cycles of the particles. A chromatographic separation of different particle sizes revealed a voltage dependency of this method. Additionally, we showed the frequency bandwidth influence on separation using one example. The DPC method developed was tested with model particles but offers possibilities to separate a broad range of plastic and metal microparticles or cells and to overcome currently existing limitations in selectivity.

Microfluidics is facing critical challenges in the quest of miniaturizing, integrating, and automating in vitro diagnostics, including the increasing complexity of assays, the gap between the macroscale world and the microscale devices, and the diverse throughput demands in various clinical settings. Here a “3D extensible” microfluidic design paradigm that consists of a set of basic structures and unit operations was developed for constructing any application-specific assay. Four basic structures- check valve (in), check valve (out), double-check valve (in and out), and on-off valve, were designed to mimic basic acts in biochemical assays. By combining these structures linearly, a series of unit operations can be readily formed. We then proposed a “3D extensible” architecture to fulfill the needs of the function integration, the adaptive “world-to-chip” interface, and the adjustable throughput in the X, Y, and Z directions, respectively. To verify this design paradigm, we developed a fully integrated loop-mediated isothermal amplification microsystem that can directly accept swab samples and detect Chlamydia trachomatis automatically with a sensitivity one order higher than that of the conventional kit. This demonstration validated the feasibility of using this paradigm to develop integrated and automated microsystems in a less risky and more consistent manner.

The aim of performed studies was to fabricate an antibacterial and degradable scaffold that may be used in the field of skin regeneration. To reach the degradation criterion the biocompatible polyurethane (PUR), obtained by using amorphous macrodiol α,ω-dihydroxy(ethylene-butylene adipate) macrodiol (PEBA), was used and processed with so-called “fast-degradable” polymer polylactide (PLA) (5 wt% or 10 wt%). To meet the antibacterial requirement obtained hybrid PUR-PLA scaffolds (HPPS) were modified with ciprofloxacin (Cipro) (2 wt% or 5 wt%), the fluoroquinolone antibiotic inhibiting growth of bacteria such as Pseudomonas aeruginosa, Escherichia Coli and Staphylococcus aureus, which are main cause of wound infections. Obtained unmodified and Cipro-modified HPPS were studied towards their chemical composition to detect presence or absence of characteristic functional groups of PUR, PLA and Cipro, and as well to indicate the participation of hydrogen bonds in the HPPS structure in dependence on PLA addition and ciprofloxacin modification. Mechanical properties were studied to determine the possible application of HPPS as a skin tissue scaffold. Scanning electron microscopy (SEM) was used to study morphology of unmodified and Cipro-modified HPPS and to performed elementary analysis by using energy-dispersive x-ray spectroscopy (EDX) of obtained materials. Finally, the microbiological tests were performed to indicate the antibacterial effect of Cipro-modified HPPS on S.aureus growth. Performed studies showed that Cipro-modified HPPS, obtained by using 5 % of PLA, possess suitable mechanical characteristic, morphology, degradation rate and demanded antimicrobial properties to be further developed as a potential scaffolds for skin tissue engineering.

Microbial production is a promising method that can overcome major limitations in conventional methods of lycopene production, such as low yields and variations in product quality. Significant efforts have been made to improve lycopene production by engineering either the 2-C-methyl-D-erythritol 4-phosphate (MEP) pathway or mevalonate (MVA) pathway in microorganisms. To further improve lycopene production, it is critical to utilize metabolic enzymes with high specific activities. Two enzymes, 1-deoxy-D-xylulose-5-phosphate synthase (Dxs) and farnesyl diphosphate synthase (IspA), are required in lycopene production using MEP pathway. Here, we evaluated the activities of Dxs and IspA of Vibrio sp. dhg, a newly isolated and fast-growing microorganism. Considering that the MEP pathway is closely related to the cell membrane and electron transport chain, the activities of the two enzymes of Vibrio sp. dhg were expected to be higher than the enzymes of E. coli. We found that Dxs and IspA in Vibrio sp. dhg exhibited 1.08-fold and 1.38-fold higher catalytic efficiencies, respectively. Consequently, the heterologous overexpression improved the specific lycopene production by 1.88-fold. Our findings could be widely utilized to enhance production of lycopene and other carotenoids.

Photoelectrocatalytic water splitting by using various TiO₂ nanostructures is a promising approach to generate hydrogen without harmful byproducts. However, their effective performance is restricted by some drawbacks such as high rapid electron-hole pair recombination and backward reaction producing H₂O. Thus in this study, the probability of enhancing hydrogen generation rate by adding methanol as a sacrificial agent to the anodic chamber of a two-compartment photoelectrochemical cell is investigated. Herein, one-dimensional elongated TiO₂ nanorods that were fabricated via a facile one-pot hydrothermal method are utilized as potent photoanode. Voltammetric characterizations confirm that addition of alcoholic sacrificial agent has a significant effect on photoelectrochemical properties of TiO₂ nanorods which by adding 10 wt% of methanol, the photocurrent density and photoconversion efficiency increased from 0.8mA.cm^-2 to 1.5mA.cm^-2 and from 0.28% to 0.45%, respectively. The results of photoelectrocatalytic water splitting indicated that the hydrogen generation rate in the presence of methanol was about 1.2 times higher than that from pure water splitting. These enhancements can be attributed to the key role of methanol. Methanol molecules not only inhibit the electron-hole pair recombination but also accelerate the hydrogen generation rate by sharing their hydrogen atoms.

Here, we report a simple and effective method for separation of gram-negative bacteria using aptamer-modified microbeads and acoustophoresis. As acoustophoresis allows for simultaneous washing and size-dependent separation in continuous flow mode, we efficiently obtained gram-negative bacteria that showed high affinity without any additional washing steps. The proposed device has a simple and efficient channel design, utilizing a long, square-shaped microchannel that shows excellent separation performance in terms of the purity, recovery, and concentration factor. Microbeads (10 µm) coated with the GN6 aptamer can specifically bind gram-negative bacteria. Using acoustophoresis, gram-negative bacteria-bound microbeads and other unbound/contaminants can be separated by size with high purity and recovery. The device demonstrated excellent separation performance, with high recovery (up to 98%), high purity (up to 99%), and a high volume rate (500 µL/min), and a concentration factor of up to 20×. The acoustophoresis microfluidic device also showed binding affinity to multiple strains of gram-negative bacteria, but not to gram-positive bacteria. This study presents a new paradigm for early diagnosis of bacterial infectious diseases. In addition to detecting living bacteria or bacteria-derived biomarkers, this protocol can be extended to monitoring the contamination of water resources, and may aid quick responses to bioterrorism and pathogenic bacterial infections.

The feasibility of a steady-state visual evoked potential (SSVEP) brain-computer interface (BCI) with a single flicker stimulus for multiple-target decoding has been demonstrated in a number of recent studies. The single-flicker BCIs have mainly employed the direction information for encoding the targets, i.e. different targets are placed at different spatial directions relative to the flicker stimulus. The present study explored whether visual eccentricity information can also be used to encode target for the purpose of increasing the number of targets in the single-flicker BCIs. A total number of 16 targets were encoded, placed at eight spatial directions, and two eccentricities (2.5° and 5°) relative to a 12 Hz flicker stimulus. Whereas distinct SSVEP topographies were elicited when participants gazed at targets of different directions, targets of different eccentricities were mainly represented by different signal-to-noise ratios (SNRs). Using a canonical correlation analysis-based classification algorithm, simultaneous decoding of both direction and eccentricity information was achieved, with an average offline 16-class accuracy of 66.8±16.4% averaged over 12 participants and a best individual accuracy of 90.0%. Our results demonstrate a single-flicker BCI with a substantially increased target number towards practical applications.

A method for classification is introduced in this article, and it is tested on ADNI database to diagnose alzheimer’s disease (AD). It is obvious that tunning the performance of a classification to get better results is a complicated problem, and when we want model’s accuracy or other peformance measurments higher than 90%, the problem will be more complicated. In this study, we tried and succeeded to discover a method to solve this problem. The final feature set can be used clustering too, because outgrowth feature set of the proposed method is invigorated. In the recent years, a lot of activities is done to develop computer aided systems (CAD) for alzheimer’s disease diagnosis. Most of these recently developed systems concenterated on extracting and combining features from MRI, PET, CSF, and …; in this article, we made attempt to do so and utilized one more technique to increase classification performance. Finding and producing the best features to solve three binary classification problems of AD vs. Normal Control (NC), Mild Cognitive Impairment (MCI) vs. NC, and MCI vs. AD are the purposes of this article. Experiments indicate performance and effectiveness rates of the proposed method, which are accuracies of 98.81%, 81.61%, and 81.40% for AD vs. NC, MCI vs. NC, and AD vs. MCI classification problems, respectively. As can be seen, using this method increased the performance of the three binary problems incredibly.

A portable urea sensor for use in the fast flow condition was fabricated using porous polytetrafluoroethylene (PTFE) membranes coated with amine-functionalized parylene, parylene-A, by vapor deposition. To generate a specific electrochemical sensor signal from urea, the urea-hydrolyzing enzyme urease was immobilized on the parylene-A-coated PTFE membranes via chemical crosslinking using glutaraldehyde. The urease-immobilized membranes were assembled in a polydimethylsiloxane (PDMS) fluidic chamber, and a screen-printed carbon three-electrode system was used for electrochemical measurements. The success of urease immobilization was confirmed using fluorescence microscopy, scanning electron microscopy, and Fourier-transform infrared spectroscopy. The optimum concentration of urease for immobilization on the parylene-A-coated PTFE membranes was determined to be 48 mg/mL, and the optimum number of membranes in the PDMS chamber was found to be 8. Using these optimized conditions, we fabricated the urea biosensor and monitored urea samples under various flow rates ranging from 0.5 to 10 mL/min in the flow condition using chronoamperometry. To test the applicability of the sensor for physiological samples, we used it for monitoring urea concentration in the waste peritoneal dialysate of a patient with chronic renal failure, at a flow rate of 0.5 mL/min.

This work is aimed at the development of innovative, easy and cheap methods for the stabilization, inertization and valorisation of the organic fraction of municipal solid waste (OFMSW). For the first time, two original processes for transforming the organic waste into an inert, odorless and sanitized material were here proposed. The first one, called dual step, starts with grinding of the OFMSW, by means of an industrial shredder. After being finely ground, the organic waste was exposed to a sterilization process by means of UV/ozone radiations or thermal treatment (stabilization phase) in order to obtain a complete removal of the OFMSW’s bacterial activity. By means of several microbiological analyses, the best sterilization method was chosen. The incorporation in a thermosetting matrix was, then, carried out through mixing the sterilized and finely ground organic waste into a water soluble urea formaldehyde (UF) based resin, with a formaldehyde content less than 1% wt, followed by a thermal treatment for UF-resin crosslinking (inertization phase). An alternative cheaper and easier process, called one step, was also proposed and investigated, by combining the sterilization with the curing thermal process (at higher temperature) of the thermosetting matrix. The preliminary experimental results reported in this paper suggest that both the proposed methods could be considered suitable for the production of high valorized innovative OFMSW-derived panels or bricks, that could find application in several fields, such as building or constructions materials. Finally a brief description of the prototype machinery is reported properly designed for implementing OFMSW stabilization and valorisation processes developed in this research work.

Purpose: To improve numerical simulation of the non-contact tonometry test by using Arbitrary Eulerian-Lagrangian deforming mesh in the coupling between computational fluid dynamics model of an air jet and finite element model of the human eye. Methods: Computational fluid dynamics model simulated impingement of the air puff and consisted of 25920 wedge6 elements and employed Spallart-Allmaras model to simulate capture turbulence of the air jet. The time span of the jet wais 30 ms and maximum Reynolds number

The improvement of the methane combustion activity was observed in cyclic temperature-programmed and isothermal reactions over Pd/ZrO2 catalysts by simple reduction/re-oxidation treatment. The catalytic activity increased during the initial stages of isothermal reaction, and the light-off temperature was lowered as the number of cycles increased in the cyclic temperature-programmed reaction. To reveal the origin of activation, variations in the reduction properties after the activation period were carefully investigated through CH4 temperature-programmed reduction (TPR) measurements. From the CH4-TPR results, it was confirmed that the reduction temperature decreased significantly after activation. The observation of the CH4-TPR peak at relatively low temperatures is directly proportional to the catalytic activity of CH4 combustion. It was therefore concluded that repeated reduction/re-oxidation occurred in the reactant stream, and this phenomenon allowed the combustion reaction to proceed more easily at lower temperatures.

Background: This research presents the use of photoplethsmography combined with Traditional Tibetan Pulse reading for the estimation of the three energies of a person: Activity, Transformation and Stability. The growing interest to revive traditional finger pulse reading attests of the need to find alternative ways to approach complex multi-source diseases as well as individualised diagnostic wearable or portable cost effective systems. Method: Our work is presented in two studies. The first study presents the development of the technique of photoplethsmography to classify the three energies. The second study presents a validation of this methodology on mental stress and relaxation. Results: Energies classification achieved a sensitivity above 85% and specificity above 72%. Mental stress and relaxation could be significantly discriminated from baseline condition. Harmonic analysis gave further insights into the dynamic of the pulse wave under stress/relaxation. Conclusion: The photoplethsmogram contains information pertaining to the mental and physiological state of a person as interpreted with the Eastern energies concepts. The implication of this work points towards a holistic understanding and impact of human activities, health and its environment.

Buerger's disease or Thromboangiitis Obliterans (TAO) is a nonatherosclerotic segmental vascular disease which affects small and medium arteries and veins in the upper and lower extremities. Based on pathological findings, TAO can be considered as a distinct form of vasculitis that is most prevalent in young male smokers. There is no definitive cure for this disease as therapeutic modalities are limited in number and efficacy. Surgical bypass has limited utility and 24% of patients will ultimately require amputation. Recently, studies have shown that therapeutic angiogenesis and immunomodulatory approaches through the delivery of cells to target tissues are potential options for ischemic lesion treatment. In this review, we summarize the current knowledge of TAO treatment and provide an overview of stem cell-based treatment modalities.

A hydrothermal pretreatment of the microalga Nannochloropsis gaditana at mild temperatures has been studied in order to reduce N and O content in the biocrude obtained by hydrothermal liquefaction (HTL). The work is focused on the evaluation of temperature, reactor loading and time (factors) to maximize the yield of the pretreated biomass and the heteroatom contents transferred from the microalga biomass to the aqueous phase (responses). The study followed the factorial design and response surface methodology. An equation for every response has been obtained, which leads to the accurate calculation of the operating conditions required to obtain a given value of these responses. Temperature and time are critical factors with a negative effect on the pretreated biomass yield, but a positive one on the N and O recovery in the aqueous phase. The slurry concentration has to be low to increase heteroatom recovery and high to maximize the pretreated microalga yields

Data can be illustrated in shapes, and the shapes could provide insight for data modeling and information extraction. Topological data analysis provides an alternative insight in biomedical data analysis and knowledge discovery with the algebra topology tools. In present work, we study the application of topological data analysis for personalized electrocardiographic signal classification toward arrhythmia analysis. Using phase space reconstruction technique, the signal samples are converted into point clouds for topological analysis facility. With topological techniques the persistence landscapes from the point clouds are extracted as features to perform the arrhythmia classification task. We find that the proposed method is robust to the training set size, with only a training set size of 20% percents, the normal heartbeat class are 100% recognized, ventricular beats for 97.13%, supra-ventricular beats for 94.27% and fusion beats for 94.27% within the corresponding experiments. The property of keeping high performance when using smaller training sample proves that the proposed method is especially applicable to personalized analysis. With the present study, we show that the topological data analysis technique could be a useful tool in biomedical signal analysis, and provide powerful ability in personalized analysis.

The art work of this present paper is to show properly conditions and aspects to reach stability in the process control, as also to avoid instability, by using digital PID controllers, with the intention of help the industrial community. The discussed control strategy used to reach stability is to manipulate variables that are directly proportional to their controlled variables. To validate and to put the exposed principles into practice, it was done two simulations of a continuous fermentation tank process start-up with the yeast strain S. Cerevisiae NRRL-Y-132, in which the substrate feed stream contains different types of sugar derived from cane bagasse hydrolysate. These tests were carried out through the resolution of conservation laws, more specifically mass and energy balances, in which the fluid temperature and level inside the tank were the controlled variables. The results showed the facility in stabilize the system by following the exposed proceedings.

Commercial sleep devices and mobile-phone applications for scoring sleep are gaining ground. In order to provide reliable information about the quantity and/or quality of sleep, their performance needs to be assessed against the current gold-standard, i.e. polysomnography (PSG; measuring brain, eye and muscle activity). We here assessed some commercially available sleep trackers, namely; a commercial activity tracker: Mi band (Xiaomi, BJ, CHN), a scientific actigraph: Motionwatch 8 (CamNTech, CB, UK), and a much used sleep application: Sleep Cycle (Northcube, GOT, SE). We recorded 27 nights in healthy sleepers using PSG and these devices. Surprisingly, all devices had very poor agreement with the gold standard. Sleep parameter comparisons revealed that specifically the Mi band and the sleep cycle application had difficulties in detecting wake periods which negatively affected the total sleep time and sleep efficiency estimations. However, all 3 devices were good in detecting the most basic parameter, the actual time in bed. In summary, our results suggest that, to-date; available sleep trackers do not provide meaningful sleep analysis but may be interesting for simply tracking times in bed. A much closer interaction with the scientific field seems necessary if reliable information shall be derived from such devices in the future.

Visual Evoked Potentials (VEPs) are used in clinical applications in ophthalmology, neurology and extensively in brain computer interface (BCI) research. BCI literature covers steady state VEP (SSVEP) and code modulated VEP (c-VEP) BCIs along with sophisticated methods to improve information transfer rates (ITR). There is a gap of knowledge regarding the VEP adaptation dynamics, physiological generation mechanisms and relation with BCI performance. A simple dual display VEP switch was developed to test signatures elicited by non-isochronic, non-singular, low jitter stimuli at the rates of 10, 32, 50 and 70 reversals per second (rps). Non-isochronic, low-jitter stimulation elicits Quasi-Steady-State VEPs (QSS-VEPs) that are utilized for simultaneous generation of transient VEP and QSS-VEP. QSS-VEP is a special case of c-VEPs and it is assumed that it shares the similar generators of the SSVEPs. Eight subjects were recorded and the performance of the overall system was analyzed by means of Receiver Operating Characteristic (ROC) curves, accuracy plots and ITRs. In summary QSS-VEPs performed better than transient VEPs. It was found that in general 32rps stimulation had the highest ROC area, accuracy and ITRs in general. To investigate the reasons behind this, adaptation dynamics of transient VEPs and QSS-VEPs at all four rates were analyzed and speculated. Moreover, QSS-VEPs were found to lead to higher accuracy by the template matching compared to SSVEPs at 10rps and 32rps.

Body acceleration due the heartbeat-induced reaction forces can be measured as smartphone accelerometer (m-ACC) signals. Our aim was to test the feasibility of using m-ACC to detect changes induced by stress by ultra-short heart rate variability (USV) indices (SDNN and RMSSD). Sixteen healthy volunteers were recruited; m-ACC was recorded while in supine position, during spontaneous breathing (REST) and during one minute of mental stress (MS) induced by arithmetic serial subtraction task, simultaneous with conventional ECG. Beat occurrences were extracted from both ECG and m-ACC and used to compute USV indices using 60, 30 and 10s durations, both for REST and MS. A feasibility of 93.8% in the beat-to-beat m-ACC heart rate series extraction was reached. In both ECG and m-ACC series, compared to REST, in MS the mean beat duration was reduced by 15% and RMSSD decreased by 38%. These results show that short term recordings (up to 10 sec) of cardiac activity using smartphone’s accelerometers are able to capture the decrease in parasympathetic tone, in agreement with the induced stimulus.

Dietary polyphenols exist in two forms; extractable polyphenols (EPP) or compounds solubilised by aqueous/organic solvents, and non-extractable polyphenols (NEPP) or compounds remain in the corresponding residues after the extraction. At present, most researchers focus on EEP fractions, while NEPP is neglected. Thus, this study aimed to release NEPP from the remaining powder residue of Barhi date palm kernels (BDPK) with acid hydrolysis. The related extraction conditions were determined and optimised using response surface methodology (RSM) for maximisation of NEPP with highest cytotoxic and antioxidant activities. The face-centred central composite design (FCCCD) was used to establish treatments based on three independent variables, namely; extraction temperature, time, and solvent/sample ratio. Under the optimal conditions, the experimental values for DPPH radical-scavenging capacity of NEPP (IC50=57.52µg/mL), and cytotoxicity of NEPP against A549 and HT29 cells were IC50=17.4 µg/mL and 31.4µg/mL, respectively. The experimental values were in agreement with those predicted by RSM models, confirming the suitability of the model employed and the success of RSM for optimisation of the extraction conditions for NEPP from BDPK. These results indicate that NEPP from industrial date fruit waste could be a promising candidate as natural antioxidants with significant antiproliferation effect against A549 and HT29 cancer cells in-vitro.

This study presents the development of a number of finite element (FE) models of the pelvis using different continuum and structural modelling approaches. Four FE models were developed using different modelling approaches: continuum isotropic, continuum orthotropic, hybrid isotropic and hybrid orthotropic. The models were subjected to an iterative adaptation process based on the Mechanostat principle. Each model was adapted to a number of common daily living activities (walking, stair ascent, stair descent, sit-to-stand and stand-to-sit) by applying onto it joint and muscle loads derived using a musculoskeletal modelling framework. The resulting models, along with a structural model previously developed by the authors, were compared visually in terms of bone architecture, and their response to a single load case was compared to a continuum FE model derived from CT imaging data. The main findings of this study were that the continuum orthotropic model was the closest to the CT derived model in terms of load response albeit having less total bone volume, suggesting that the role of material directionality in influencing the maximum orthotropic Young's modulus should be included in continuum bone adaptation models. In addition, the hybrid models, where trabecular and cortical bone were distinguished, had similar outcomes, suggesting that the approach to modelling trabecular bone is less influential when the cortex is modelled separately.

The fetal heart rate (FHR) is a screening signal for preventing fetal hypoxia during labor. When experts analyze this signal, they have to position a baseline and identify decelerations and accelerations. These steps can potentially be automated and made more objective by data processing analysis, but training and evaluation datasets are required. Here, we describe a dataset of 155 FHR recordings in which a reference baseline, accelerations and decelerations have been annotated by expert consensus. 66 FHR recordings with a shared expert analysis have been included in a training dataset, and 90 other FHR recordings with a non-shared expert analysis have been included in an evaluation dataset. Researchers wishing to evaluate their automatic analysis method should submit their results for comparison with the expert consensus. The dataset also contains the results produced by 11 re-coded automatic analysis methods from the literature. All the data are available at http://utsb.univ-catholille.fr/fhr-review.

The presence of azo dyes in textile effluents is an issue of major concern due to their potential impact on the environment and human health. In this study we investigate the photocatalytic degradation under visible light of Reactive Violet 5 (RV5), an azo dye widely used in the textile industry. A preliminary screening of different titania-based catalysts was carried out to identify the best candidate for RV5 removal. The selected catalyst was then tested in a stirred and aerated lab-scale reactor illuminated with a light LED source (λmax = 460 nm). The effects of pH, catalyst load and hydrogen peroxide additions on the efficiency of dye removal were evaluated. Under the best conditions (pH 10, 3 g/L of catalyst and 60 mM hydrogen peroxide), the dye solution was completely decolorized in about 2 h. Overall, the results obtained suggest that the proposed process may represent a suitable method for the removal of RV5 from textile effluents.

The deaf impairment is among the most substantial health problem worldwide, that can lead to various personal, economical, and social crisis. Therefore, it is critical for developing an efficient way to facilitate communication between deaf-dumb impaired and normal people. Herein, we have rationally designed a new digitally computerized and mobile smart system as an efficient communication tool between deaf impaired and normal Arabian people. This is based on two main steps, including creating a digital output for the hand gestures using gloves flex sensors equipped with a three-axis accelerometer that is controlled using a microcontroller. The digital results are compared to that in a words-based “database”, where Arabs use expressions not alphabet in their communication. The second step is translation or conversion the outputs of the first stage into written texts and voices. The newly developed system allows Arabian deaf to translate words of ordinary people into gestures using a speech recognition system with an impressive accuracy over 90 % without the needing for a webcam, colored gloves, and/or online translator. The presented system can be used on any android or windows.

Background: This research presents the use of photoplethsmography combined with Traditional Tibetan Pulse reading for the estimation of the three energies of a person: Activity, Transformation and Stability. The three energies derive from the four elements which are known from antiquity, both East and West, which considered life and the cosmos as an inseparable whole. Therefore the three energies composing the human functions are a reflection of our life as well as the cosmos. Method: Our work is presented in two studies. The first study presents the development of the technique of photoplethsmography to classify the three energies. The second study presents a validation of this methodology on mental stress and relaxation. Results: Energies classification achieved a sensitivity above 85% and specificity above 86%. Mental stress and relaxation could be significantly discriminated from baseline condition. Harmonic analysis gave further insights into the dynamic of the pulse wave under stress/relaxation. Conclusion: The photoplethsmogram contains information pertaining to the mental and physiological state of a person as interpreted with the Eastern energies concepts. The implication of this work points towards a holistic understanding and impact of human activities, health and its environment.

This study investigates distillery wastewater, commonly known as vinasse, as a potential culture medium for the production of Chlorella vulgaris and its most relevant metabolites. The effect of vinasse concentration on the composition of the biomass (proteins, carbohydrates and lipids) was evaluated in treatments performed in 6-L tubular air-lift reactors. The reactors were operated at 25 °C for 18 days, in total darkness, under a continuous flow of air. Results showed a rapid growth of microalgae in the first ten days, when an average production of 0.87 g/L was reached. Then, the daily biomass productivity began to decrease, up to an average value of 11.8 g/L at the 16th day. For all treatments, there was a significant reduction in the concentration of most metabolites in the first eight days. This was likely due to the adaptation of the biomass to the new conditions, with a the transition from autotrophic to heterotrophic metabolism. From the 10th day, the concentration of metabolites in the biomass began to increase, reaching a nearly constant value at the 16th day. The observed maximum concentrations (%w/w) were: 48.95% proteins, 2.88% xylose, 7.82% glucose, 4.54% arabinose, 8.28% fructose and 4.82% lipids. These values were only marginally affected by the type of treatment. Overall, the results obtained suggest that vinasse is a promising and sustainable medium for the growth of C. vulgaris and the production of valuable metabolites.

The fetal heart rate (FHR) is a screening signal for preventing fetal hypoxia during labor. When experts analyze this signal, they have to position a baseline and then identify decelerations and accelerations. These steps can potentially be automated and made more objective by signal processing analysis. Various methods have been described in the literature but there are no open-source programs for performing these steps. The MATLAB toolbox presented here comprises a standard signal pre-processing function, 11 re-coded literature methods for fetal heart rate analysis, a signal viewer (enabling annotation by an expert) and an evaluation procedure with various criteria measuring intrarater agreement.

In a thin-volume photobioreactor where a concentrated suspension of microalgae is circulated throughout the established spatial irradiance gradient, microalgal cells experience a time-variable irradiance. Deploying this feature is the most convenient way of obtaining the so-called “flashing light” effect, improving biomass production in high irradiance. This work investigates the light flashing features of sloping wavy photobioreactors, a recently proposed type, by introducing and validating a Computational Fluid Dynamics model. Two characteristic flow zones (straight top-bottom stream and local recirculation stream), both effective toward light flashing, have been found and characterised: a recirculation-induced frequency of 3.7 Hz and straight flow-induced frequency of 5.6 Hz were estimated. If the channel slope is increased, the recirculation area becomes less stable while the recirculation frequency is nearly constant with flow rate. The validated CFD model is a mighty tool that could be reliably used to further increase the flashing frequency by optimising the design, the dimensions, the installation and the operational parameters of the sloping wavy photobioreactor.

The cooperation between humans and robots is becoming increasingly important in our society. Consequently, there is a growing interest in the development of models that can enhance the interaction between humans and robots. A key challenge in the Human-Robot Interaction (HRI) field is to provide robots with cognitive and affective capabilities, developing architectures that let them establish empathetic relationships with users. Several models have been proposed in recent years to solve this open-challenge. This work provides a survey of the most relevant attempts/works. In details, it offers an overview of the architectures present in literature focusing on three specific aspects of HRI: the development of adaptive behavioural models, the design of cognitive architectures, and the ability to establish empathy with the user. The research was conducted within two databases: Scopus and Web of Science. Accurate exclusion criteria were applied to screen the 1007 articles found (at the end 30 articles were selected). For each work, an evaluation of the model is made. Pros and cons of each work are detailed by analysing the aspects that can be improved so that an enjoyable interaction between robots and users can be established.

The study of the distribution and health risk assessment is meaningful to provide basic data for environmental management．To investigate the pollution of potential toxic organics and their health risk to human beings, water samples were collected at 7 sites of main surface water of Beijing during wet and dry seasons respectively. The targeted 92 organics were detected, including phthalates (PAEs), volatile organic compounds (VOCs), polycyclic aromatic hydrocarbons (PAHs) and phenols. The results showed that: there were 56 organics detected out, and the number ratios of detected compounds to the total compounds of the same kind increased as the following: VOCs, phthalates, phenols, PAHs. 8 VOCs were detected in wet season, and 3 in dry season. The concentration of 2,2-Dichloropropane was highest as 10.62ug/L, while the concentrations of other VOCs were below 5ug/L; There were 11 phthalates detected during dry season. The content of Bis(2-methoxyethyl) phthalate was highest as 188.47ng/L; 17 phenols were found in samples during wet season, and the highest concentration was 1244.73ng/L for 4-nitrophenol; PAHs could be detected in all samples, and the detected compounds and the corresponding average concentrations were higher in wet seasons than those in dry seasons, which indicated that non-point pollution was possibly the main pollution source. The health risk assessment of the detected 56 pollutants by using a model from US EPA showed that, the risk caused by the four kinds of toxic organics in this study was in the acceptable ranges.

A crucial role is played by personal biomedical data when it comes to maintaining proficient access to health records by patients as well as health professionals. However, it is difficult to get a unified view pertaining to health data that have been scattered across various health center/hospital sections. To be specific, health records are distributed across many places and cannot be found integrated easily. In recent years, blockchain is regarded as a promising explanation that helps to achieve individual biomedical information sharing in a secured way along with privacy preservation, because of its benefit of immutability. This research work put forwards a blockchain-based managing scheme that helps to establish interpretation improvements pertaining to electronic biomedical systems. In this scheme, two blockchain were employed to construct the base of it, where the second blockchain algorithm is used to generate a secure sequence for the hash key that generated in first blockchain algorithm. The adaptively feature enable the algorithm to use multiple data types and combine between various biomedical images and text records as well. All the data, including keywords, digital records as well as the identity of patients are private key encrypted along with keyword searching capability so as to maintain data privacy preservation, access control and protected search. The obtained results which show the low latency (less than 750 ms) at 400 requests / second indicate the ability to use it within several health care units such as hospitals and clinics.

Cognitive deterioration caused by illness or aging often occurs before symptoms arise, and their timely diagnosis is crucial to reducing its medical, personal, and societal impacts. Brain-Computer Interfaces (BCIs) stimulate and analyze key cerebral rhythms, enabling reliable cognitive assessment that can accelerate diagnosis. The BCI system presented analyzes Steady-State Visually Evoked Potentials (SSVEPs) elicited in subjects of varying age to detect cognitive aging, predict its magnitude, and identify its relationship with SSVEP features (band power and frequency detection accuracy), which were hypothesized to indicate cognitive decline due to aging. The BCI system was tested with subjects of varying age to assess its ability to detect aging-induced cognitive deterioration. Rectangular stimuli flickering at theta, alpha, and beta frequencies were presented to subjects, and frontal and occipital EEG responses were recorded. These were processed to calculate detection accuracy for each subject and calculate SSVEP band power. A neural network was trained using the features to predict cognitive age. The results showed potential cognitive deterioration through age-related variations in SSVEP features. Frequency detection accuracy declined after age group 20–40 and band power, throughout all age groups. SSVEPs generated at theta and alpha frequencies, especially 7.5 Hz, were the best indicators of cognitive deterioration. Here, frequency detection accuracy consistently declined after age group 20-40 from an average of 96.64% to 69.23%. The presented system can be used as an effective diagnosis tool for age related cognitive decline.

A common reactor type in the chemical and process industry is the fixed-bed reactor. Accurate modeling can be achieved with particle-resolved Computational Fluid Dynamic (CFD) simulations. However, the underlying bed morphology plays a paramount role. Synthetic bed-generation methods are much more flexible and faster than image-based approaches. In this study, we look critically at the two different bed generation methods: Discrete Element Method (DEM) (in the commercial software STAR-CCM+) and the rigid-body model (in the open-source software Blender). The two approaches are compared in terms of synthetically generated beds with experimental data of overall and radial porosity, particle orientation, as well as radial velocities. Both models show accurate agreement for the porosity. However, only Blender shows similar particle orientation than the experimental results. The main drawback of the DEM is the long calculation time and the shape approximation with composite particles.

Tissue engineering has the potential for repairing large bone defects, which impose a heavy financial burden on the public health. However, difficulties with O₂ delivery to the cells residing in the interior of tissue engineering scaffolds make it challenging to grow artificial tissues of clinically-relevant sizes. This study uses image-based simulation in order to provide insight into how to better optimize the scaffold manufacturing parameters, and the culturing conditions, in order to resolve the O₂ bottleneck. To do this, high resolution 3D X-ray images of two common scaffold types (salt leached foam and non-woven fiber mesh) are fed into a Lattice Boltzmann Method fluid dynamics and reactive Lagrangian Scalar Tracking mass transfer solvers. The obtained findings indicate that the scaffolds should have maximal surface area-to-solid volume ratios, for higher chances of the molecular collisions with the cells. Furthermore, the cell culture media should be flown through the scaffold pores as fast as practically possible (without detaching or killing the cells). Finally, we have provided a parametric sweep that maps how the molecular transport within the scaffolds is affected by variations in rates of O₂ consumption by the cells. Ultimately, the results of this study are expected to benefit the computer-assisted design of tissue engineering scaffolds and culturing experiments.

Bioimpedance measurements are used increasingly in health applications because bioelectric parameters have been associated with anatomical and physiological properties, thus enabling to distinguish medical conditions. For bone fracture diagnostics, nevertheless, there is no established non-invasive method. Ex vivo studies and In vivo bioimpedance procedures, both invasive and non-invasive, on mammalians long bones are associated with promising results. In this work, out of a total of 568 papers, we reviewd 59 articles that mention long bone integrity by electric properties, be it Bioimpedance Analysis, Electrical Impedance Spectroscopy or Electrical Impedance Tomography. The papers are described in three sections, “Ex vivo measurements”, “In vivo invasive measurements” and “In vivo non-invasive measurements”. This review allows to establish the basics to planning the development of new technology to detect bone fracture via bioimpedance measurements.

Background: medical devices are designed, tested and placed on the market in a highly regulated environment. Wearable sensors are crucial components of various medical devices: design and validation of wearable sensors, if managed according to international standards, can foster innovation while respecting regulatory requirements. Material and methods: the purpose of this paper is to take into consideration the upcoming EU Medical Device Regulation 2017/245 and the current and future IEC and ISO standards that set methods for design and validation of medical devices, with a focus on wearable sensors. Risk classification according to the regulation is described. The international standards IEC 62304, IEC 60601, ISO 14971 and ISO 13485 are reviewed to define regulatory restrictions during design, pre-clinical validation and clinical validation of devices that include wearable sensors as crucial components. Results: current and future regulatory restrictions are described, and an integrated method for design planning, validation and clinical testing is described Discussion: application of this method to design wearable sensors should be evaluated in the future in order to assess its potentially positive impact to fostering innovation and to the time-to-market of the device.

Centrifuges are commonly required devices in medical diagnostics facilities as well as scientific laboratories. Although there are commercial and open source centrifuges, costs of the former and required electricity to operate the latter, limit accessibility in resource-constrained settings. There is a need for low-cost, human-powered, verified and reliable lab-scale centrifuge. This study provides the designs for a low-cost 100% 3-D printed centrifuge, which can be fabricated on any low-cost RepRap-class fused filament fabrication (FFF) or fused particle fabrication (FPF)-based 3-D printer. In addition, validation procedures are provided using a web camera and free and open source software. This paper provides the complete open source plans including instructions for fabrication and operation for a hand-powered centrifuge. This study successfully tested and validated the instrument, which can be operated anywhere in the world with no electricity inputs obtaining a radial velocity of over 1750rpm and over 50N of relative centrifugal force. Using commercial filament the instrument costs about US$25, which is less than half of all commercially available systems; however, the costs can be dropped further using recycled plastics on open source systems for over 99% savings. The results are discussed in the contexts of resource-constrained medical and scientific facilities.

Transdermal alcohol biosensors have the ability to detect the alcohol that emanates from the bloodstream and diffuses through the skin. However, they have suffered from long-term fouling of the sensor element and drift in the resulting sensor readings over time. Here, we report a disposable cartridge platform that solves the problem of sensor fouling, and an enzymatic detection pathway that minimizes baseline drift for sensitive detection. Laboratory characterization of the enzymatic alcohol sensor demonstrates a linear sensor range of between 0 and 50 mM. Further, we show continuous transdermal alcohol data recorded with a human subject over 48 hours.

This study presents a platform for ex-vivo detection of cancer nodules, addressing automation of medical diagnoses in surgery and associated histological analyses. The proposed approach takes advantage of the property of cancer to alter the mechanical and acoustical properties of tissues, because of changes in stiffness and density. A force sensor and an ultrasound probe were combined to detect such alterations during force-regulated indentations. To explore the specimens, regardless of their orientation and shape, a scanned area of the test sample was defined using shape recognition applying optical background subtraction to the images captured by a camera. The motorized platform was validated using seven phantom tissues, simulating the mechanical and acoustical properties of ex-vivo diseased tissues, including stiffer nodules that can be encountered in pathological conditions during histological analyses. Results demonstrated the platform’s ability to automatically explore and identify the inclusions in the phantom. Overall, the system was able to correctly identify up to 90.3% of the inclusions by means of stiffness in combination with ultrasound measurements, paving pathway towards robotic palpation during intraoperative examinations.

High-tech augmentative and alternative communication (AAC) methods are on a constant rise; however, the interaction between the user and the assistive technology is still challenged for an optimal user experience centered around the desired activity. This review presents a range of signal sensing and acquisition methods utilized in conjunction with the existing high-tech AAC platforms for speech disabled individuals, including imaging methods, touch-enabled systems, mechanical and electro-mechanical access, breath-activated methods, and brain computer interfaces (BCI). The listed AAC sensing modalities are compared in terms of ease of access, affordability, complexity, portability, and typical conversational speeds. A revelation of the associated AAC signal processing, encoding, and retrieval highlights the roles of machine learning (ML) and deep learning (DL) in the development of intelligent AAC solutions. The demands and the affordability of most systems were found to hinder the scale of usage of high-tech AAC. Further research is indeed needed for the development of intelligent AAC applications reducing the associated costs and enhancing the portability of the solutions for a real user’s environment. The consolidation of natural language processing with current solutions also needs to be further explored for the amelioration of the conversational speeds. The recommendations for prospective advances in coming high-tech AAC are addressed in terms of developments to support mobile health communicative applications.

The reaction mechanism of the carboxylation of K-2-naphthoxide was investigated by density functional theory calculations and spectroscopic studies. The reaction intermediates and products were confirmed by CO₂ adsorbed-FTIR and ¹H-NMR measurements. Four steps of the reaction pathway were identified: CO₂ activation, electrophilic substitution, CO₂-K complex rearrangement, and H-shift, producing 2-hydroxy-1-naphthoic acid (2,1-HNA), 2-hydroxy-3-naphthoic acid (2,3-HNA), and 2-hydroxy-6-naphthoic acid (2,6-HNA). The occurrence of CO₂-K complex rearrangement was also confirmed. These energy profiles of reaction pathways for the reaction intermediates were well consistent the experimental results on the carboxylation of K-2-naphthoxide.

In this study, the efficiency of an anaerobic treatment system for wastewater from a South African poultry slaughterhouse was evaluated using a lab-scale static granular bed reactor (SGBR). The down-flow SGBR (2 L) was operated continuously for 138 days under mesophilic conditions (35-37 ˚C), at hydraulic retention times (HRTs) ranging from 24 to 96 h and average organic loading rates (OLRs) of 0.78 to 5.74 g COD/L.day. The SGBR achieved an average chemical oxygen demand (COD) removal efficiency of 80% and the maximum COD removal achieved was 95%, at an HRT of 24 h and average OLR of 5.74 g COD/L.day. The optimization of the SGBR, with regard to a suitable HRT and OLR, was determined using response surface methodology (RSM). The optimal SGBR performance with regard to the maximum COD removal efficiency was predicted for an OLR of 12.49 g COD/L.day and a HRT of 24 h, resulting in a 95.5% COD removal efficiency. The model R2 of 0.9638 indicated that the model is a good fit and is suitable to predict the COD removal efficiency for the SGBR.

Based on a modified dice-and-fill technique, a PIN-PMN-PT single crystal 1-3 composite with the kerf of 12 μm and pitch of 50 μm was prepared. The as-made piezoelectric composite material behaved with high piezoelectric constant (d33 = 1500 pC/N), high electromechanical coefficient (kt = 0.81), and low acoustic impedance (16.2 Mrayls). Using lithography and flexible circuit method, a 48-element phased array was successfully fabricated from such a piezoelectric composite. The array element was measured to have a central frequency of 20 MHz and a fractional bandwidth of approximately 77% at −6 dB. Of particular significance was that this PIN-PMN-PT single crystal 1-3 composite-based phased array exhibits a superior insertion loss compared with PMN-PT single crystal and PZT-5H-based 20 MHz phased arrays. The focusing and steering capabilities of the obtained phased array were demonstrated theoretically and experimentally. These promising results indicate that the PIN-PMN-PT single crystal 1-3 composite-based high frequency phased array is a good candidate for ultrasound imaging applications.

The motivation of this work is to investigate experimentally the influence of non-thermal plasma (NTP) application on the reaction kinetics of atmospheric pressure steam gasification of charcoal using a thermostatically controlled drop tube reactor. A gliding-arc generator provides about 1 kW electrical power NTP. For comparison thermal gasification is investigated under comparable flow and specific energy input conditions providing additional heat to the steam. Optical temperature measurement 20 cm flow down of the NTP zone is utilized to characterize the specific enthalpy of the reactive flow. The composition of produced syngas is measured by a gas analyzer and used for the calculation of gas flow rates. The results show a NTP-enhancement on the production of individual syngas components (H2, CO, CH4), especially on hydrogen production by around 39%. The syngas-based carbon conversion and hydrogen release are calculated from the carbon and hydrogen balance between the correspondent content in syngas and in the feedstock. The NTP promoted the carbon conversion and hydrogen release by 25% and 31%, respectively. The first-order reaction kinetics are determined by data-fitting in an Arrhenius diagram. The plasma enhanced the reaction rate coefficients by 27%. Based on experimental results and other literature, possible plasma-induced reactions are proposed.

Low temperature cofired ceramics (LTCC) have conquered a niche segment in biological microelectromechanical systems (BioMEMS) during the last two decades. Since 3-dimensional assembly and rapid prototyping capability are outstanding features of the technology, bioreactors with complex geometry can easily be produced. Particularly needed functions are working electrodes, e.g. for impedance measurements and reference electrodes consisting in platinum or silver-silver chloride. Although the distinct grainy surface of thick film materials influences the double layer properties, data describing the bioelectronic interface and biocompatibility of common thick film materials are rarely published up to now. This works aims to fill this gap by studying the surface properties, composition, electrochemical properties and biocompatibility of commercially available thick film materials. It was found that thick film gold is suitable as electrode material in direct cell contact since an appropriate proliferation of the cell culture was observed. Poly(3,4-ethylenedioxythiophene) coating decreases the absolute value of the zeta potential of thick film gold from 16.55 V to 11.78 mV without any change in vitality of the cells. Thick film platinum layers have a porous structure entailing an enlargement of the effective surface by a factor of 21.6 and can be used as reference instead of silver/silver chloride, which was identified to be incompatible with cell culture. The investigations show that some commercially available cost-effective thick film materials are compatible with cell culture and the here presented data give an orientation for the use of the same in LTCC bioreactors.

A highly dirt resistant paint for building facades without chemicals harmful to nature and environment, is developed which resolves the unattractive disfigurement of building walls caused by dirt. The experimentation is scientifically and statistically planned with the aid of computer programming. It consists of a sequence of phases which include the selection of appropriate raw materials, adopting of Basic Language computer programming to generate a target population of paint formulations. The average PVC percentage is computed using theory and found to be 54.98% for the target population of 543143 paint formulations hence verifies the literature results. Experimentation and statistical analysis are performed to compare the classical conventional agitator with latest lab equipment like Nano mill and it is concluded that Nano mill performs better on the average than conventional agitator in preparation of paint formulations. Hence the sample of paint formulations is prepared on Nano mill and tested in laboratory using advanced available technology for the analysis and comparison of paint properties to determine the best paint formulation. The results are analyzed using Analysis Of Variance Technique (ANOVA) and it is concluded that the paint formulation named “O3” has the highest dirt resistance on the average. The final selected formula O3 is compared with three other competitor paints in market under natural environment for a period of almost one year. A regression model is also constructed to study the effect of environmental factors like time, temperature and humidity on dirt resistance of paints. It is found that O3 formulation is the best environment friendly which performs equally well with one competitor paint and has higher dirt resistance than two other competitor paint formulations containing harmful chemicals. The regression model of dirt resistance on variables including time, temperature and humidity shows that these factors are significantly affecting the dirt resistance of a given paint at 5% level of significance. 95.34% variation in the dirt resistance of a given paint is due to and explained by the given factors. The regression model is useful to predict the average dirt resistance of a given paint with a certain level of confidence. The project exemplifies the work of an applied research from conceptualization to successful commercialization for the paint industry.

Disease classification based on biological data is an important area in bioinformatics and biomedical research. It helps the doctors and medical practitioners for the early detection of disease and support them as a computer-aided diagnostic tool for accurate diagnosis, prognosis, and treatment of disease. Earlier Microarray gene expression data have wide application for the classification of disease, but now Next-generation sequencing (NGS) has replaced the Microarray technology. From the last few years, RNA sequence (RNA-Seq) data are widely used for the transcriptomic analysis. Hence, RNA-Seq based classification of disease is in its infancy. In this article, we present a general framework for the classification of disease constructed on RNA-Seq data. This framework will guide the researchers to process RNA-Seq, extract relevant features and apply the appropriate classifier to classify any kind of disease.

The advancements in the study of the human sense of touch are fueling the field of haptics. This is paving the way for augmenting the sensory perception during objects palpation in tele-surgery, and reproducing the information through tactile feedback. Here, we present a novel tele-palpation apparatus that enables the user to detect nodules with various distinct stiffness buried in an ad-hoc polymeric phantom. The contact force measured by the platform was encoded using a neuromorphic model and reproduced on the index fingertip of a remote user through a haptic glove embedding a piezoelectric disk. We assessed the effectiveness of this feedback in allowing nodule identification under two experimental conditions of real-time telepresence: In Line of Sight (ILS), where the platform was placed in the visible range of a user; and the more demanding Not In Line of Sight (NILS), with the platform being 50 km apart. We found that the entailed percentage of identification was higher for stiffer inclusions with respect to the softer ones (average of 74% within the duration of the task), in both telepresence conditions evaluated. These promising results call for further exploration of tactile augmentation technology for telepresence in medical interventions.

Among the most important variables in the design of falling film microreactors (FFMRs) is the liquid film thickness as well as the gas/liquid interfacial area, which dictate the mass and heat transfer rates. In a previous work conducted in our lab the characteristics of a free-falling Newtonian liquid film have been studied and appropriate correlations have been proposed. In this work the geometrical characteristics of a non-Newtonian shear thinning liquid, flowing in an inclined open microchannel, have been experimentally investigated and design correlations that can predict with reasonable accuracy the features of a FFMR have been proposed. The test section used was an open μ-channel with square cross section (Wo=1200 μm) made of brass which can be set to various inclination angles. The liquid film characteristics were measured by a non-intrusive technique that is based on the features of a μ-PIV system. Relevant CFD simulations revealed that the volume average dynamic viscosity over the flow domain is practically the same as the corresponding asymptotic viscosity value, which can thus be used in proposed the design equations. Finally, a generalized algorithm for the design of FFMRs, containing non-Newtonian shear thinning liquids, is suggested.

The Abdominal Aortic Aneurysm (AAA) is a local dilation of the abdominal aorta and it is a cause for serious concern because of the high mortality associated with its rupture. Consequently, the understanding of the phenomena related to the creation and the progression of an AAA is of crucial importance. In this work the complicated interaction between the blood flow and the AAA wall is numerically examined using a fully coupled Fluid-Structure Interaction (FSI) method. The study investigates the possible link between the dynamic behaviour of an AAA and the blood viscosity variations attributed to the haematocrit value, while it also incorporates the pulsatile blood flow, the non-Newtonian behaviour of blood and the hyperelasticity of the arterial wall. It was found that blood viscosity has no significant effect on von Mises stress magnitude and distribution, whereas there is a close relation between the haematocrit value and the Wall Shear Stress (WSS) magnitude in AAAs. This WSS variation can possibly alter the mechanical properties of the arterial wall and increase its growth rate or even its rupture possibility. The relationship between haematocrit and dynamic behaviour of an AAA can be helpful in designing a patient specific treatment.

Ti and Ti alloys are materials usually used in contact with hard tissue for applications such as artificial joints and dental implants. Ti6Al4V is a very common alloy used for dental implants, owing to its good mechanical properties and corrosion resistance. Nevertheless, because of uncertainties regarding the toxicity of vanadium and its influence on the human body, other Ti alloys containing no vanadium and retaining suitable properties are used. In this work Ti6Al4V and Ti6Al7Nb were oxidized in a water solution of calcium acetate (Ca(CH3COO)2) and calcium glycerophosphate (Ca(PO4CH(CH2OH)2) by Plasma Electrolytic Oxidation (PEO) for 20 minutes and then were hydrothermally treated (HTT) in water (pH=7) and in potassium hydroxide (KOH) solution (pH=11) for 2 hours at 200°C in a pressurized reactor. The surface morphologies, elemental composition and phase components were characterized by Scanning Electron Microscopy (SEM), Energy Dispersive Spectroscopy (EDS) and X-Ray Diffraction (XRD), respectively. The surface roughness was measured by Atomic Force Microscope (AFM) and thickness measurements were made by SEM and thickness gauge. Also, corrosion tests were made to evaluate the corrosion behavior of the two alloys. The aim of this study is to compare two viable Ti alloys, Ti6Al4V and Ti6Al7Nb, and to attain on their surface hydroxyapatite (HA) coating improving the osseointegration, as it simulates a human bone.

In this work, an enzymatic sensor, based on a bionanocomposite film consisting of a polyelectrolyte complex (PEC) [Chitosan/kappa-carrageenan] doped with gold nanoparticles (AuNPs) encapsulating glucose oxidase (GOD) deposited on a gold electrode (Au) for glucose sensing, is described. Using the electrocatalytic synergy of AuNPs and GOD as a model of enzyme, the variation of the current (µA) as a function of the log of the glucose concentration (log [glucose]), shows 3 times higher sensitivity for the modified electrode (283.9) compared to that of the PEC/GOD modified electrode (93.7), with a detection limit of about 5 µM and a linearity range between 10µM and 7mM. The response of the PEC/AuNPs/GOD based biosensor also presents good reproducibility, stability and negligible interfering effects from ascorbic acid, uric acid, urea and creatinine. The applicability of the PEC/AuNPs/GOD based biosensor was tested in glucose-spiked saliva samples and acceptable recovery rates were obtained.

Three-dimensional (3D) cell culture is considered more clinically relevant in mimicking the structural and physiological conditions of tumors in vivo compared to two-dimensional cell cultures. In recent years, high-throughput screening (HTS) in 3D cell arrays has been extensively used for drug discovery because of its usability and applicability. Herein, we developed a microfluidic spheroid culture device (μFSCD) with a concentration gradient generator (CGG) that enabled cells to form spheroids and grow in the presence of cancer drug gradients. The device is composed of concave microwells with several serpentine micro-channels which generate a concentration gradient. Once the colon cancer cells (HCT116) formed a single spheroid (approximately 120 μm in diameter) in each microwell, spheroids were perfused in the presence of the cancer drug gradient irinotecan for 3 days. The number of spheroids, roundness, and cell viability, were inversely proportional to the drug concentration. These results suggest that the μFSCD with a CGG has the potential to become an HTS platform for screening the efficacy of cancer drugs.

Mixing is considered as a critical process parameter (CPP) during process development due to its significant influence on reaction selectivity and process safety. Nevertheless, mixing issues are difficult to identify and solve owing to their complexity and dependence on knowledge of kinetics and hydrodynamics. In this paper, we proposed an optimization methodology using Computational Fluid Dynamics (CFD) based compartmental modelling to improve mixing and reaction selectivity. More importantly, we have demonstrated that through the implementation of surrogate-based optimization, the proposed methodology can be used as a computationally non-intensive way for rapid process development of reaction unit operations. For illustration purpose, reaction selectivity of a process with Bourne competitive reaction network is discussed. Results demonstrate that we can improve reaction selectivity by dynamically controlling rates and locations of feeding in the reactor. The proposed methodology incorporates mechanistic understanding of the reaction kinetics together with an efficient optimization algorithm to determine the optimal process operation and thus can serve as a tool for quality-by-design (QbD) during product development stage.

One control challenge in prosthetic legs is seamless transition from one gait mode to another. User intent recognition (UIR) is a high-level controller that tells a low-level controller to switch to the identified activity mode, depending on the user’s intent and environment. We propose a new framework to design an optimal UIR system with simultaneous maximum performance and parsimony for gait mode recognition. We use multi-objective optimization (MOO) to find an optimal feature subset that creates a trade-off between these two conflicting objectives. The main contribution of this paper is two-fold: (1) a new gradient-based multi-objective feature selection (GMOFS) method for optimal UIR design; and (2) the application of advanced evolutionary MOO methods for UIR. GMOFS is an embedded method that simultaneously performs feature selection and classification by incorporating an elastic net in multilayer perceptron neural network training. Experimental data are collected from six subjects, including three able-bodied subjects and three transfemoral amputees. We implement GMOFS and four variants of multi-objective biogeography-based optimization (MOBBO) for optimal feature subset selection, and we compare their performances using normalized hypervolume and relative coverage. GMOFS demonstrates competitive performance compared to the four MOBBO methods. We achieve a mean classification accuracy of 97.14% ± 1.51% and 98.45% ± 1.22% with the optimal selected subset for able-bodied and amputee subjects, respectively, while using only 23% of the available features. Results thus indicate the potential of advanced optimization methods to simultaneously achieve accurate, reliable, and compact UIR for locomotion mode detection of lower-limb amputees with prostheses.