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 12μm and pitch of 50μm was prepared. The as-made piezoelectric composite material behaved 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 piezoelectric composite. The array element was measured to have a central frequency of 20MHz and a fractional bandwidth of approximately 77% at -6dB. 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 such phased array were validated through Field II simulations. These promising results suggest 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.

We have developed a cast microfluidic chip for concentration gradient generation that contains a thin (~5 μm^2 crosssectional area) microchannel. Durable 2 μm-high microchannel mold features with a smooth bell-shaped sidewall were fabricated by exposing SU-8 photoresist to diffused 185 nm UV light emitted by a low-cost ozone lamp from the backside of the substrate to ensure sufficient crosslinking of small regions of the SU-8 photoresist. An H-shaped microfluidic configuration was used, in which the thin channel was able to maintain constant diffusion fronts beyond purely static diffusion confirmed with experiment. We also demonstrated the long-term effects of a gradient of nerve growth factor on axon elongation by primary neuronal cells cultured in the microfluidic channel.

This review analyzes the preparation and characterization of metal organic frameworks (MOFs) and their application as photocatalysts for water purification. The study begins by highlighting the problem of water scarcity and the different solutions for purification, including photocatalysis with semiconductors such as MOFs. It also describes the different methodologies that can be used for the synthesis of MOFs, paying attention to the purification and activation steps. The characterization of MOFs and the different approaches that can be followed to learn on the photocatalytic processes are also detailed. Finally, the work reviews literature focused on the degradation of contaminants from water using MOF-based photocatalysts under light irradiation.

Detection of the region of interest (ROI) is a critical step in laryngeal image analysis for the delineation of glottis contour. The process can improve both computational efficiency and accuracy of the image segmentation task, which will facilitate subsequent analysis and characterization of the vocal fold vibration as it correlates with voice quality and pathology. This study aims to develop machine learning based approaches for automatic detection of ROI for glottis image sequences captured by high-speed video-endoscopy (HSV), a clinical laryngeal imaging modality. In particular, we first applied the supporting vector machine (SVM) method using histogram of oriented gradients (HOG) feature descriptor, and second, trained a convolutional neural network (CNN) model for this task. Comparisons are made for both approaches in terms of accuracy of recognition and computation time.

In the present work a novel, portable and innovative eNose composed of a surface acoustic wave (SAW) sensor array based ZIF-8, and ZIF-67 nanocrystals (pure and combined with gold nanoparticles) as sensitive layers has been tested as a non-invasive system to detect and differentiate disease markers, such as acetone, ethanol and ammonia, related with early diagnosis of diabetes mellitus through exhaled breath. The sensors have been prepared by spin coating, achieving continuous and homogenous sensitive layers. Low concentrations (5 ppm, 10 ppm and 25ppm) of the marker analytes were measured, obtaining high sensitivities, good reproducibility, short time response and fast signal recovery.

The aim of the study was to evaluate the influence of transduser design and its elements, and their materials on temperature in deeper layers of tissues measurement results. A digital modeling was performed to evaluate the influence of the properties of transduser design elements. Experimental research was carried out. Revealed that the accuracy, similar to that of an invasive method using needle probes, can be achieved by measuring the temperature in deeper muscle layers using the proposed transducer.

In this work, pure TiO₂ and nano-magnetic of Fe₃O₄/TiO₂ were synthesized for degradation of 2,4-dichlorophenol (2, 4-DCP) as an organic pollutant. A range of analytical techniques including XRD, DRS, FESEM, and VSM were employed to reveal the crystal structure, morphology and property of the nanocomposite. The XRD results showed the prepared samples including 100% anatase phase. We obtained the band gap energy 2.9 and 2.8 eV for pure TiO₂ and Fe₃O₄/TiO₂ respectively. VSM results demonstrate that easy, fast separation and redispersion of Fe₃O₄/TiO₂ sample can be realized. We obtained 62% and 31% degradation of 2,4-DCP in the presence of  Fe₃O₄/TiO₂  and pure TiO₂ under visible light respectively.

The importance of detecting bacteria in various food products is ever-increasing, due to recent food trends that lend themselves to food contamination. Additionally, the detection of probiotics in food products is of increasing importance to consumers, who realize the benefits of probiotics on one’s diet. Existing technologies for detection of bacteria in food are accurate, but most are slow, increasingly costly and unsuitable for applications outside of research laboratories. Optic approaches have recently emerged as an alternative, allowing rapid detection of bacterial presence. This study employs a portable kinetics fluorometer, fabricated in-house, in conjunction with NADH sensitive fluorescence reporter for analysis of various food products. The presence of bacteria is detected in 5 minutes. Both pathogenic and probiotic bacteria were detected in food products, such as raw chicken and beef, spoiled lettuce and contaminated water, yogurt, and kombucha tea. The cellular activity of two probiotic pills was also verified. All samples displayed varying levels of bacterial activity. The study indicates the viability of biosensors being used as an alternate method to detect bacteria in food products – and the viability of a fluorescence-based biosensor to detect viable bacteria. The approach is suitable for both laboratory and field determinations.

Immunosensors have been widely developed to use antibodies to detect a pathogen of interest; it is interesting to look at the effect of nonspecific antibody binding to E. coli using electrochemical methods. IgG antibody not specific to E. coli O157:H7 was crosslinked onto a screen-printed carbon electrode. The presence of E. coli at 4, 4 × 10², 4 × 10⁵, and 4 × 10⁸ CFU/mL on the electrode surface was detected via linear sweep voltammetry (LSV) and electrochemical impedance spectroscopy (EIS). Current transfer at both electrodes was reduced as the concentration of bacteria increased; however, the calibration of number of cells to decreased current was nonlinear for IgG-modified electrodes. The nonlinearity is confirmed by EIS measurements which showed highest impedance at 4 CFU/mL E. coli when impedance should be the lowest. FESEM images showed higher binding of cells when IgG is present compared to electrodes with reduced graphene oxide (rGO) alone. Electrodes with rGO alone show less attachment of E. coli, with EIS showing a linear calibration profile, while LSV shows not much difference in current values for all concentrations aside from the highest concentration. These results suggest that nonspecific binding can provide false signals in electrochemical measurements, and it is crucial to provide proper controls. 

Hydrogen is a promising energy carrier, exploitable to extract energy from fossil fuels, biomasses as well as intermittent renewable energy sources and its generation from fossil fuels with CO₂ separation at the source is one of the most promising pathway for fossil fuels utilization. This work is focused on a particular configuration, called Reformer and Membrane Module (RMM), which alternates stages of Steam Reforming (SR) reaction with H2 separation stages to overcome the thermodynamic limits of the conventional SR. The configuration has numerous advantages with respect to the more studied and tested membrane reactors and has been tested on a pilot scale during a pilot-scale research project. Although the numerous modelling works appeared in the literature, the design features of the material exchanger (in the so-called RMM architecture) of different geometrical configurations have not been developed and the mass transfer correlations, capable of providing design tools useful for such membrane modules, are not available. The purpose of this work is therefore to apply a physical-mathematical model of the mass transfer, in three different geometries, considering both concentration polarization and membrane permeation, in order to: i) simulate the cited experimental results, ii) estimate the scaling-up correlations for the “material exchange modules”; iii) identify the mass transfer limiting regime in relation to the gas mass flow rate.

Nanofibers appearing functional properties show a great promise as allowing constituents for a wide range of medical applications. In this work, Polycaprolactone (PCL), Silver Nitrate (AgNO₃) and Zinc Oxide (ZnO) were used for fabrication of nanofiber composite material by co-axial electrospinning (CAE) process. 5, 10, and 15 wt. % concentrations of PCL were utilized and different amount of AgNO₃ and ZnO were used in entire samples. Morphological analyses of the electrospun nanocomposites were done by scanning electron microscopy (SEM) and AgNO₃, ZnO and PCL materials’ functional groups were determined by Fourier Transform Infrared Spectroscopy (FTIR). Before co-axial electrospinning, physical properties such as liquid state ac conductivity, density and viscosity were measured for all solutions. Capacitance (C_p) and D-factors (tanδ) of nanocomposite materials are measured for the frequency range of 20Hz – 3MHz and the solid state alternating current (ac) conductivity, permittivity (ε’) and dielectric loss (ε’’) were calculated for all solutions after co-axial electrospinning. Effects of concentration percentages of PCL and AgNO₃ on real and imaginary parts of dielectric constant and solid state ac conductivity have been analyzed and comparisons have been made by the results obtained.

Pb found in rain water is not only caused by tin roof on houses but also caused by the pollution of industrial activities, vehicles and land clearing activity by fire. Pb pollutant dissolves and enters into rain water storages and it’s consumed as drinking. Pb can cause bad impact to human, for example disruption of enzyme, anemia and low intelligence. The purposes of this research are (1) to evaluate Pb, pH and turbidity level in rain water, (2) to analyze the effectiveness of mollusk sand filtration and the absorption of activity carbon to decrease Pb, turbidity and  pH, and (3) to analyze the correlation of Pb, length of stay and smoking habit on public health. This research is an experimental by using pre and post test designs with control and observational by using cross sectional design. The research was conducted in urban and rural areas of Pontianak and Kubu Raya regency. The sampling was done in determining the number of samples of Pb, pH and turbidity in rain water. The analyzing the data by using computer program. The results show that: (1) the average of Pb, pH and turbidity level before treatment is considered high at 131.7 µg/L on Pb, turbidity at 20 NTU and low pH at 5.2. After the treatment was the Pb has decreased to 0.71 µg/L and turbidity has to 5.66 NTU, pH to 6.9 and (2) Rain water treatment is very effective to decrease Pb for 99.4% and turbidity for 72%, and (3) there is a correlation among Pb found in rain water, length of stay and smoking activity to public health. Recommends that: the residents of Pontianak and Kubu Raya to process rain water before consuming. The rain water treatment can be done by applying mollusk sand filtration and absorption of active carbon.

Considering the high potential of hydrogen (H₂) as a clean energy carrier, the implementation of high performance and cost-effective biohydrogen (bioH₂) purification techniques is of vital importance, particularly in fuel cell applications. In this context, membrane technology is a potentially energy-saving solution to obtain high-quality biohydrogen. The most promising poly(ionic liquid) (PIL) - ionic liquid (IL) composite membranes previously studied by our group for CO₂/N₂ separation, containing pyrrolidinium-based PILs with fluorinated or cyano-functionalized anions, were chosen as starting point to explore the potential of PIL–IL membranes for CO₂/H₂ separation. The CO₂ and H₂ permeation properties at the typical conditions of biohydrogen production (T =308 K and 100 kPa of feed pressure) were measured and discussed. PIL–IL composites prepared with [C(CN)₃]^– anion showed higher CO₂/H₂ selectivities and H₂ diffusivities compared to those containing [NTf₂]^– anion. All the membranes revealed CO₂/H₂ separation performances above the upper bound for this specific separation, highlighting the composite incorporating 60 wt% of [C₂mim][C(CN)₃] IL.

Thanks to advanced semiconductor microfabrication technology, chip-scale integration and miniaturization of lab-on-a-chip components, silicon-based optical biosensors have made significant progress for the purpose of point-of-care diagnosis. In this review, we provide an overview of the state-of-the-art in evanescent field biosensing technologies including interferometer, microcavity, photonic crystal, and Bragg grating waveguide-based sensors. Their sensing mechanisms and sensor performances, as well as real biomarkers for label-free detection, are exhibited and compared. We also review the development of chip-level integration for lab-on-a-chip photonic sensing platforms, which consist of the optical sensing device, flow delivery system, optical input and readout equipment. At last, some advanced system-level CMOS-chip packaging examples are presented, indicating the commercialization potential for the low cost, high yield, portable biosensing platform leveraging CMOS processes.

The alignment of nanostructures in materials such as lyotropic liquid crystals (LLCs) templated materials has the potential to signicantly improve their performances. However, accurately characterising and quantifying the alignement of such fine structures remains very challenging. In situ small angle X-ray scattering (SAXS) and molecular dynamics were employed for the first time to understand the hexagonal LLC alignment process with magnetic nanoparticles under a magnetic field. The enhanced alignment has been illustrated from the distribution of azimuthal intensity in the samples exposed to magnetic field. Molecular dynamics simulations reveal the relationship between the imposed force of the magenetic nanoparticles under magnetic field and the force transferred to the LLC cylinders which leads to the LLC alignment. The combinational study with experimental measurement and computational simulation will enable the development and control of nanostructures in novel materials for various applications.

This paper discusses the computer-aided (CAD) classification between Hepatocellular Carcinoma (HCC), i.e., the most common type of liver cancer, and Liver Abscess, based on ultrasound image texture features and Support Vector Machine (SVM) classifier. Among 79 cases of liver diseases, with 44 cases of HCC and 35 cases of liver abscess, this research extracts 96 features of Gray-Level Co-occurrence Matrix (GLCM) and Gray-Level Run-Length Matrix (GLRLM) from the region of interests (ROIs) in ultrasound images. Three feature selection models, i) Sequential Forward Selection, ii) Sequential Backward Selection, and iii) F-score, are adopted to determine the identification of these liver diseases. Finally, the developed system can classify HCC and liver abscess by SVM with the accuracy of 88.875%. The proposed methods can provide diagnostic assistance while distinguishing two kinds of liver diseases by using a CAD system.

Under the main features required on portable devices in electrochemical instrumentation is to have a small size, low power consumption, economically affordable, and precision in the measurements. This paper describes the development of a programmable Embedded Potentiostat System (EPS) capable of performing electrochemical sensing over system-on-a-chip platforms. Furthermore, the study explains a circuit design and develops some validation of the entire system. The hardware validation is performed by electrochemical experiments such as Double Step Chronoamperometry (DSC), Linear Sweep Voltammetry (LSV) and Cyclic Voltammetry (CV); moreover, a comparison of the experimental signals between a commercial potentiostat and the EPS was done by analysis of errors on the response signal. Results illustrate that the EPS is capable of handling currents in the range of absolute values of 86.44 to 3000 nA, and having control voltages in the range of ± 2 V. The device can support from 50 to 2000 samples per second. The EPS capabilities were compared with other compact potentiostats. The programmable EPS is an original approach which hugely reduces the hardware complexity and leads the way to create new applications for Point-of-Care or industrial developments with a reusable full electronics module.

Diabetic patients need long-term and frequent glucose monitoring to assist in insulin intake. The current finger-prick devices are painful and costly which make noninvasive glucose sensors highly demanded. In this review paper, we discuss several advanced electromagnetic (EM) wave based technologies for noninvasive glucose measurement, including infrared (IR) spectroscopy, photoacoustic (PA) spectroscopy, Raman spectroscopy, fluorescence, optical coherent tomography (OCT) and microwave sensing. Development and progress of each method are discussed regarding fundamental principle, system setup and experimental results. Despite the promising achievements reported previously, there is no established product to obtain FDA approval or survive marketing test. Limitations and prospects of these techniques are discussed at the end of this review.

Adipose-derived stem cells (ADSCs) were suggested for treating degenerative osteoarthritis, suppressing inflammatory responses, and repairing damaged soft tissues. Moreover, the ADSCs have the potential to undergo self-renewal and differentiate into bone, tendon, cartilage, and ligament. Recently, investigation of the self-renewal and differentiation of the ADSCs becomes an attractive area. In this work, a pneumatic microdevice has been developed to study the gene expression of the ADSCs after the stimulation of multi-axial tensile strain. The ADSCs were cultured on the microdevice and experienced multi-axial tensile strain during a 3-day culture course. Self-renewal and differentiation abilities were investigated by mRNA expressions of NANOG, SOX2, OCT4, SOX9, PPAR-γ, and RUNX2. The result showed that the genes related self-renewal were significantly up-regulated after the tensile stimulation. Higher proliferation ratio of the ADSCs was also shown by cell viability assay. The microdevice provides a promising platform for cell-based study under mechanical tensile stimulation.

Wetting of deformable substrates has gained significant interest over the past decade due to its extensive applications and uses. This interest has developed due to technological advances which are able to capture interfacial behavior taking place when a liquid droplet is placed on a deformable substrate. Researchers have developed different theories to explain processes taking place in the process of wetting of deformable/soft substrates. For the scope of this review, we will consider the fluid to be Newtonian, partially wetting, and surface forces are incorporated with the help of disjoining/conjoining pressure acting in the vicinity of the apparent, three-phase contact line. The following subjects are briefly reviewed: (i) Equilibrium of droplets on soft substrates. It is shown that properties of the disjoining/conjoining pressure isotherm and properties of the deformable substrate determine both the shape of the liquid droplet and deformation of the substrate; (ii) Equilibrium conditions of droplets on deformable substrates. It is shown that for a droplet to be at equilibrium on a deformable substrate under consideration, Jacobi’s sufficient condition is satisfied; (iii) Hysteresis of contact angle of sessile droplets on deformable substrates. It is shown that as the elasticity of the deformable substrate is increased, both advancing and receding contact angles are reduced.

In this study, fig leaves, zeolite and alginate were used to prepare a biocomposite for the adsorption of Pb(II) ions. Effects of pH, temperature, initial lead concentration and contact time on the adsorption process have been investigated. The amount of adsorbed lead per gram of sorbent was found to be approximately 150.3 mg/g. The prepared biocomposite possesses promising adsorption potential. Maximum uptake of Pb(II) ions (85%) has been achieved at pH 6, with 25 mg/L of initial concentration and at a temperature of 288.15 K. The data correlated well with Freundlich and D-R models. The adsorption was physical in nature.

This research was presented the special designed microfluidic device generated for sperm separation based on assumption of different surface electrical charged of sperms X and Y. However, to avoid ethical problem, the microfluidic chip has been tested with the mimic electrical charged particles, TiO₂-coated Polystyrene beads, (TiO₂-coated Ps-beads), instead of spermatozoa. The work has been separated into three main parts. Firstly, the simply but efficient fabrication of negatively charged TiO₂-coated Ps-beads has been presented. In addition, various characterization techniques such as X-ray diffraction (XRD), Tungsten Scanning Electron Microscopy (W-SEM) with energy-dispersive X-ray spectroscopy (EDS) mode, and X-ray Absorption Spectroscopy (XAS), have been reported in this work to elucidate the reasons behind the persistence of negatively charged on the surface of TiO₂-coated Ps-beads. Results show that  the fabricated TiO₂-coated Ps-beads was partly coated in the mixed forms of amorphous Ti⁴⁺ and had caused a negatively charge to appear on the surface after fabrication and had sustained its electrical charged for long. Secondly, process of simulation and fabrication of microfluidic device was presented. Finally the negatively charged TiO₂-coated Ps-beads were tested in this microfluidic devices. For design of microfluidic devices integrated with a couple of microelectrodes, the simulated structures were fabricated by photolithographic technique and tested with the Ps-beads. Percentage of validation for Ps-beads separation indicated that the 100 mm-distance-between-electrodes microfluidic device exhibits to be the highest performance prototype at 86.96%. For further confirmation, another model so called the single path prototype has been established. It is confirmed by 92.59% of validation for the utilization of the device. The successfully designed microfluidic devices can be examined with actual spermatozoa later. Furthermore, process to fabricate the negatively charged TiO₂-coated Ps-beads can be established as testified samples for development of other microfluidic devices.

The objective of this study is to preliminarily evaluate a new CT-biopsy guidance device, an origami needle guide. The device is created by laser cutting the structure from a sheet of cardboard, 3D printing two radiocontrast agent grids on to the surface and folding the structure into a rectangular prism with a viewing window. An abdominal imaging phantom was used to evaluate the device through CT imaging and the targeting of lesions for needle insertion. The lesion targeting trials resulted in a mean targeting error of 1.88 mm with a standard deviation of 0.73 mm. The device attaches to the patient and is rigid enough to adequately support standard biopsy needles, reducing the effect of gravity and the risk of laceration by the needles, making it potentially advantageous for biopsy of superficial lesions and lesions approached from a horizontal orientation. The device supports insertion of multiple needles at once, making it particularly suitable for composite ablation using multiple needles. Another advantage of the device is that it can guide off-axial needle insertion. The low-cost and disposability of the device make it well-suited for the minimally invasive image guided therapy environment.

This review analyzes the synthesis and characterization of biomass-derived carbons for adsorption of emerging contaminants from water. The study begins with the definition and different types of emerging contaminants more often founded in water streams and the different technologies available for their removal including adsorption. It also describes the biomass sources that could be used for the synthesis of biochars and activated carbons. The characterization of the adsorbents and the different approaches that could be employed for the study of the adsorption processes are also detailed. Finally, the work reviews in detail some studies of the literature focused on the adsorption of emerging contaminants on biochars and activated carbons synthesized from biomass precursors.

A membrane ozonation contactor was built to investigate ozonation using tubular membranes and to inform computational fluid dynamics (CFD) studies. Non-porous tubular polydimethylsiloxane (PDMS) membranes of 1.0 – 3.2 mm inner diameter were tested at ozone gas concentrations of 110 – 200 g m−3 and liquid side velocities of 0.002 m s−1 – 0.226 m s−1. The dissolved ozone concentration could be adjusted to up to 14 mg O3 L−1 and increased with decreasing membrane diameter and liquid side velocity. Experimental mass transfer coefficients and molar fluxes of ozone were 1.1∙10−5 mol m−2 s−1 and 2.4∙10−6 m s−1, respectively, for the smallest membrane. CFD modelling could predict the final ozone concentrations but slightly overestimated mass transfer coefficients and molar fluxes of ozone. Model contaminant degradation experiments and UV absorption measurements of ozonated water samples in both ozone (O3) and peroxone (H2O2/O3) reaction systems in pure water, river water, wastewater effluent and solutions containing humic acid show that the contactor system can be used to generate information on the reactivity of ozone with different water matrices. Combining simple membrane contactors with CFD allows predicting ozonation performance under a variety of conditions leading to improved bubble-less ozone systems for water treatment.

The article reviews the current status of label-free integrated optical sensors focusing on the evolution over the years of their analytical performance. At first a short introduction to the evanescent wave optics is provided followed by detailed description of the main categories of label-free optical sensors including sensors based on surface plasmon resonance (SPR), grating coupler, photonic crystals, ring resonators and interferometric transducers. After a short reference to SPR techniques, including localized SPR, integrated optical sensors i.e., grating-couplers, interferometers, photonic crystals, microring resonators are reviewed. For each type of sensor, the detection principle is first provided followed by description of the different transducer configurations so far developed and their performance as biosensors. Finally, a short discussion about the current limitations and future perspectives of integrated label-free biosensors optical sensors is provided

Model-based design has received considerable attention in biological and chemical industries over the last two decades. However, the parameter uncertainties of first-principle models are critical in model-based design and have led to the development of robustification concepts. Various strategies were introduced to solve the robust optimization problem. Most approaches suffer from either unreasonable computational expense or low approximation accuracy. Moreover, they are not rigorous and do not consider robust optimization problems where parameter correlation and equality constraints exist. In this work, we propose a highly efficient framework for solving robust optimization problems with the so-called point estimation method (PEM). The PEM has a fair trade-off between computation expense and approximation accuracy and can be easily extended to problems of parameter correlations. From a statistical point of view, moment-based methods are used to approximate robust inequality and equality constraints. We also suggest employing the information from global sensitivity analysis to further simplify robust optimization problems with a large number of uncertain parameters. We demonstrate the performance of the proposed framework with two case studies where one is to design a heating/cooling profile for the essential part of a continuous production process and the other is to optimize the feeding profile for a fed-batch reactor of the penicillin fermentation process. The results reveal that the proposed approach can be used successfully for complex (bio)chemical problems in model-based design.

The aim of this study is to provide the scientists with a straightforward correlation that can be applied for predicting the Fanning friction factor and consequently the pressure drop during blood flow in small caliber vessels. Due to the small diameter of the conduit, the Reynolds numbers are low and thus the flow is laminar. The study has been conducted using CFD simulations validated with relevant experimental data acquired using an appropriate experimental set-up. The experiments concern pressure drop measurement during the flow of a blood analogue that follows the Casson model, i.e. an aqueous glycerol solution that contains a small amount of xanthan gum and exhibits similar behavior to blood, in a smooth, stainless steel microtube (L=5.6cm and D=400 μm). The interpretation of the resulting numerical data led to the proposal of a simplified model that incorporates the effect of the flow rate, the hematocrit value (35-55%) and the vessel diameter (300-1800 μm) and predicts with better than ±10% the Fanning friction factor and consequently the pressure drop during laminar blood flow in small caliber vessels.

Bioprocesses for the production of renewable energies and materials lack efficient separation processes for the utilized microorganisms such as algae and yeasts. Dissolved air flotation (DAF) and microflotation are promising approaches to overcome this problem. The efficiency of these processes depends on the ability of microorganisms to aggregate with microbubbles in the flotation tank. In this study, different new or adapted aggregation models for microbubbles and microorganisms are compared and investigated for their range of suitability to predict the separation efficiency of microorganisms from fermentation broths. The complexity of the heteroaggregation models range from an algebraic model to a 2D population balance model (PBM) including the formation of clusters containing several bubbles and microorganisms. The effect of bubble and cell size distributions on the flotation efficiency is considered by applying PBMs, as well. To determine the impact of the model assumptions, the modeling approaches are compared and classified for their range of applicability. Evaluating computational fluid dynamics (CFD) of a DAF system shows the heterogeneity of the fluid dynamics in the flotation tank. Since analysis of the streamlines of the tank show negligible backmixing, the proposed aggregation models are coupled to the CFD data by applying a Lagrangian approach.

Phononic crystals are periodic composite structures with specific resonant features that are gaining strength in the field as liquid sensors. The introduction of a structural defect in an otherwise periodic regular arrangement can generate a resonant mode, also called defect mode, inside the characteristic band gaps of phononic crystals. The morphology, as well as the frequency in which these defect modes appear, can give useful information on the composition and properties of an analyte. Currently, only gain, and frequency measurements are performed using phononic crystal sensors. Other measurements like the transient response have been implemented in resonant sensors such as quartz microbalances showing great results and proving to be a great complimentary measure to the gain and frequency measurements. In the present paper, a study of the feasibility of using the transient response as a measure to acquire additional information about the analyte is presented. Theoretical studies using the transmission line model were realized to show the impact of variations in the concentration of an analyte, in this case, lithium carbonate solutions, in the transient time of the system. Experimental realizations were also performed showing that the proposed measurement scheme presents significant changes in the resulting data, indicating the potential use of this measure in phononic crystal sensors. This proposed measure could be implemented as a stand-alone measure or as a compliment to current sensing modalities.

Software-based ultrasound imaging systems provide high flexibility that allows easy and fast adoption of newly developed algorithms. However, the extremely high data rate required for data transfer from sensors (e.g., transducers) to the ultrasound imaging systems is a major bottleneck in the software-based architecture, especially in the context of real-time imaging. To overcome this limitation, in this paper, we present a Binary cLuster (BL) code, which yields an improved compression ratio compared to the exponential Golomb code. Owing to the real-time encoding/decoding features without overheads, the universal code is a good solution to reduce the data transfer rate for software-based ultrasound imaging. The performance of the proposed method was evaluated using in vitro and in vivo data sets. It was demonstrated that the BL-beta code has a good stable lossless compression performance of 20 ~ 30% while requiring no auxiliary memory or storage.

In this contribution, we aim to show that opinion dynamics and population balance modeling can benefit from an exchange of problems and methods. To support this claim, the Deffuant-Weisbuch model, a classical approach in opinion dynamics, is formulated as a population balance model. This new formulation is subsequently analyzed in terms of moment equations, and conservation of the first and second order moment is shown. Exemplary results obtained by our formulation are presented and agreement with the original model is found. Also the influence of the initial distribution is studied. Additionally, the Deffuant-Weisbuch model is transferred to engineering and interpreted as mass transfer between liquid droplets which results in a more flexible formulation compared to alternatives from the literature. On the one hand, it is concluded that the transfer of opinion-dynamics problems to the domain of population balance modeling offers some interesting insights as well as stimulating challenges for the population-balance community. On the other hand, it is inferred that population-balance methods can contribute to the solution of problems in opinion dynamics. In a broad outlook, some further possibilities of how the two fields can possibly benefit from a close interaction are outlined.

The photoreduction of CO2 is an intriguing process, which allows the synthesis of fuels and chemicals. One of the limitations for CO2 photoreduction in the liquid phase is its low solubility in water. This point has been here addressed by designing a fully innovative concept of pressurized photoreactor, allowing operation up to 20 bar and applied to improve the productivity of this very challenging process. The photoreduction of CO2 in the liquid phase was performed using commercial TiO2 (Evonink P25), TiO2 obtained by flame spray pyrolysis (FSP) and gold doped P25 (0.2 wt% Au-P25) in the presence of Na2SO3 as hole scavenger (HS). The different reaction parameters (catalyst concentration, pH and amount of HS) have been addressed. The products in liquid phase were formic acid and formaldehyde. Moreover, for longer reaction time and with total consumption of HS, gas phase products formed (H2 and CO) after accumulation of significant amount of organic compounds in the liquid phase, due to their consecutive photoreforming. Enhanced CO2 solubility in water was achieved by adding a base (pH= 12-14). In basic environment, CO2 formed carbonates which further reduced to formaldehyde and formic acid and consequently formed CO/CO2+H2 in the gas phase through photoreforming. The deposition of small Au nanoparticles (3-5 nm) (NPs) onto TiO2 was found to quantitatively influence the products distribution and increase the selectivity towards gas phase products.

This work reports of the use of a bench scale chemostat (CSTR) in continuous mode and of a pilot scale membrane bioreactor (MBR) in fed-batch mode to intensively produce acetic and butyric acids using Cl. butyricum grown on synthetic media. These studies were then used to perform a cost estimation study of the MBR system to assess the potential economic impact of this proposed methodology. The MBR system was found highly productive reaching 37.88 g L-1 h-1 of acetic and 14.44 g L-1 h-1 of volumetric cell productivity, favoring acetic acid production to butyric at a ratio 3:1. The cost of preparation and production of carboxylic acids using this system was found as 0.0062 £PS/kg respectively and an up to 99% carbon recovery.

Molecular detection of pathogens in clinical samples often requires pretreatment techniques, including immunomagnetic separation and magnetic silica bead (MSB)-based DNA purification to obtain the purified DNA of pathogens. These two techniques usually rely on handling small tubes containing a few millilitres of the sample and manual operation, implying that an automated system encompassing both techniques is needed for larger quantities of the samples. Here, we report a 3D-printed microfluidic platform that enables bacterial preconcentration and genomic DNA (gDNA) purification for improving the molecular detection of target pathogens in blood samples. The device consists of two microchannels and one chamber, which can be used to preconcentrate pathogens bound to antibody-conjugated magnetic nanoparticles (Ab-MNPs) and subsequently extract gDNA using magnetic silica beads (MSBs) in a sequential manner. The device was able to preconcentrate very low concentrations of pathogens and extract their genomic DNA in 10 mL of 10% blood within 30 min, and thus allowed polymerase chain reaction (PCR) and quantitative PCR to detect 1 colony forming unit of Escherichia coli O157:H7 in 10% blood. The results suggest that the 3D-printed microfluidic platform is highly useful for lowering the limitations on molecular detection in blood by preconcentrating the target pathogen and isolating its DNA in a large volume of the sample.

Abstract: This study evaluates the effect of paravertebral spinal injection (PSI), utilizing both subjective and objective assessments in chronic low back pain (LBP) associated with facet joint arthrosis over a one-month duration. Subjective questionnaires included the Visual Analogue Scale (VAS) for pain, Oswestry Disability Index, Health Survey SF-12, and the short Falls Efficacy Scale International (FES-I). Objective assessments included in-clinic gait and timed-up-and-go (TUG) tests using wearable sensors, as well as 48-hour daily physical activity (DPA) monitored using a chest-worn tri-axial accelerometer. Subjective and objective measures were performed prior to treatment, immediately after the treatment, and one-month afterthe treatment. Eight LBP patients were recruited for this study (mean age = 54±13 years, body mass index = 31.41±6.52 kg/m2, 50% males). Results show significant decrease in pain (~55%, p<0.05) and disability (Oswestry scores, ~21%, p<0.05). In-clinic gait and TUG were also significantly improved (~16% and ~18% faster walking and shorter TUG, p<0.05); however, DPA (including percentage of physical activities (walking and standing) and the number of steps) showed no significant change after PSI (p>0.25; effect size≤0.44). We hypothesize that DPA may continue to be truncated by conditioned fear-avoidance, a psychological state that may prevent increase in daily physical activity to avoid pain.

Blood perfusion quantification is important vital parameters in different diagnostic procedure, using infrared thermography imaging; it is reliable to use this technique as non-contact, non-invasive blood flow measurement method. Therefore, we developed a measurement protocol for blood flow over the arm's anterior surface. By using the superficial brachial and radial veins to be monitored under the impact of cold-excitation of (2 °C to 5 °C), the blood perfusion signal was detected using thermal imager of long-wave infrared spectral range (LWIR, 7μm - 14 μm). The simulation of Penne's bioheat transfer equation was performed to be compared with results obtained from the infrared thermography. Furthermore, the proposed blood flow monitoring using external adjusting of the excitation temperature, by using (cold-compress, or cold air-stream) applied to the region under testing. The signal detected resembles to the hemodynamic pulse of the superficial veins, in the definition of systolic and diastolic phases of the cardiac cycle. Moreover, statistical analysis applied to the BFIRT signals from 24 subjects to estimate the skin's mean temperature after recovery from the thermal excitation.

Advanced electrode designs have made single-unit neural recordings commonplace among modern neuroscience research. However, single-unit resolution remains out of reach for the intrinsic neurons of the gastrointestinal system. Single-unit recordings of the enteric (gut) nervous system have been conducted in anesthetized animal models and excised tissue, but there is a large physiological gap between awake and anesthetized animals, particularly for the enteric nervous system. Here, we describe the opportunity for advancing enteric neuroscience offered by single-unit recording capabilities in awake animals. We highlight the primary challenges to microelectrodes in the gastrointestinal system including structural, physiological, and signal quality challenges.

The presence of dyes in wastewater effluents made from the textile industry is a major environmental problem due to their complex structure and poor biodegradability. In this study, a cationic lignin polymer was synthesized via the free radical polymerization of lignin with [2- (methacryloyloxy) ethyl] trimethylammonium chloride (METAC) and used to remove anionic azo-dyes (reactive black 5, RB5, and reactive orange 16, RO16) from simulated wastewater. The effects of pH, salt and concentration of dyes, well as the charge density and molecular weight of lignin-METAC polymer on dye removal were examined. Results demonstrated that lignin-METAC was an effective flocculant for the removal of dye via charge neutralization and bridging mechanisms. The dye removal efficiency of lignin-METAC polymer was independent of pH. The dosage of the lignin polymer required for reaching the maximum removal had a linear relationship with the dye concentration. The presence of inorganic salts including NaCl, NaNO3 and Na2SO4 had marginal effect on the dye removal. Under the optimized conditions, greater than 98 % of RB5 and 94 % of RO16 were removed at lignin-METAC concentrations of 120 mg/L and 105 mg/L in the dye solutions, respectively.

Magneto-optic surface plasmon resonance (MOSPR) based sensors are highly attractive as next generation biosensors. However, these sensors suffer from oxidation leading to degradation of performance, reproducibility of the sensor surface because of the difficulty of removing adsorbed materials, and degradation of sensor surface during surface cleaning, and these limit their applications. In this paper, I propose MOSPR-based biosensors with 0 to 15 nm thick inert polycarbonate laminate plastic as a protective layer and theoretically demonstrate the practicability of our approach in water-medium for three different probing samples: ethanol, propanol, and pentanol. I also investigate microstructure and magnetic properties. The chemical composition and layered information of the sensor are investigated using X-ray reflectivity and X-ray diffraction analyses and these show distinct fcc-Au (111) phases, as dominated by the higher density of conduction electrons in Au as compared to Co. The magnetic characterization measured with the in-plane magnetic field to the sensor surface for both the as-deposited and annealed multilayers showed isotropic easy axis magnetization parallel to the multilayer interface at a saturating magnetic field of <100 Oe. The sensor showed a maximum sensitivity of 5.5 × 10⁴%/RIU for water-ethanol media and the highest detection level of 2.5 × 10⁻⁸ for water-pentanol media as the protective layer is increased from 0 to 15 nm.c

Computational fluid dynamics (CFD) has, in the last decade, being an essential problem solving tool in industries such as pharmaceutical, pulp, petrochemical as well as Oil and Gas processing. The use of CFD for mixer design is unpopular in many countries in Africa. Therefore, this study investigates the characteristics of Brine-Surfactant mixing in a horizontal pipeline using CFD. The CFD is conducted by AnsysFluent software (licensed). A T-junction pipe is created and meshed with unstructured tetrahedral elements using design modeler. Discretization is done by Finite Volume Method (FVM), cell-centered scheme with Second-Order Upwind Scheme. The pressure term is introduced into the continuity equation by SIMPLE (Semi-Implicit Method for Pressure Linked Equations) algorithm. The kinetic epsilon model, also known as k-e model is administered to define the properties of the fluid and geometry, such as velocity, species mole fraction, pipe diameter. The boundary conditions is selected based on filed data. The rate of fluid flow in the primary region is 650 bbl/day at 400psi in 4in diameter pipeline, which is 100m long. The numerical simulation was based upon the governing equations such s continuity, Navier’s stoke, energy as well as specie transport equations. The findings shows that higher concentration results in increased mixing time, while 2% conc. of surfactant reaches homogeneity in 20 minutes at 72 meters of the pipe length. The result validated with field detail and the empirical result from literature, and is consistent. This study provide insight on industrial mixer design, chemical injection system, as well as gas pipeline design and optimization, especially in multiphase scale transport.

High porosity and mass transport properties of microfiltration polymeric membranes benefits nutrients supply to cells when used as scaffolds in interstitial perfusion bioreactors for tissue engineering. High nutrients transport is assumed when pore size and porosity of the membrane are in the micrometric range. The present work demonstrates that the study of membrane fouling by proteins present in the culture medium, though not done usually, should be included in the routine testing of new polymer membranes for this intended application. Two poly(ε-caprolactone) microfiltration membranes presenting similar average pore size (~0.7µm) and porosity (>80%) but different external surface porosity and pore size have been selected as case study. The present work demonstrates that a membrane with lower surface pore abundance and smaller external pore size (~0.67 µm), combined with adequate hydrodynamics and tangential flow filtration mode is usually more convenient to guarantee high flux of nutrients. On the contrary, having large external pore size (~1.70µm) and surface porosity would incur in important internal protein fouling that could not been prevented with the operation mode and hydrodynamics of the perfusion system. Additionally, the use of glycerol in the drying protocols of the membranes might cause plasticization and a consequent reduction of mass transport properties due to membrane compaction by the pressure exerted to force perfusion. Therefore, preferentially, drying protocols that omit the use of plasticizing agents are recommended.

In this report we have discussed the important role of molecular modeling, especially the use of the molecular dynamics method, in investigating transport processes in nanoporous materials such as membranes. With the availability of high performance computers, molecular modeling can now be used to study rather complex systems at a fraction of the cost or time requirements of experimental studies. Molecular modeling techniques have the advantage of being able to access spatial and temporal resolution which are difficult to reach in experimental studies. For example, sub-Angstrom level spatial resolution is very accessible as is sub-femtosecond temporal resolution. Due to these advantages, simulation can play two important roles: Firstly because of the increased spatial and temporal resolution, it can help understand phenomena not well understood. As an example, we discuss the study of reverse osmosis processes. Before simulations were used it was thought the separation of water from salt was purely a coulombic phenomenon. However, by applying molecular simulation techniques, it was clearly demonstrated that the solvation of ions made the separation in effect a steric separation and it was the flux which was strongly affected by the coulombic interactions between water and the membrane surface. Additionally, because of their relatively low cost and quick turnaround (by using multiple processor systems now increasingly available) simulations can be a useful screening tool to identify membranes for a potential application. To this end, we have described our studies in determining the most suitable zeolite membrane for redox flow battery applications. As computing facilities become more widely available and new computational methods are developed, we believe molecular modeling will become a key tool in the study of transport processes in nanoporous materials.

Transient analysis of gas flow in pipeline was studied. Finite Element Method based on ANSYS FLOTRAN was used to account for changes in pressure, temperature and flow rate. Compressibility factor function of temperature and pressure was considered. For non-isothermal transient results, the pressure and the flowrate gave wave propagation as a result of slow transients created by demand condition at the outlet end of custody transfer. Results obtained were in agreement with the demand restrictions at the outlet end of custody transfer indicating that the predictions are accurate and reliable. The results demonstrated that the Finite Element Method gave accurate prediction of pressure, temperature and flowrate in transient gas studies. For steady state non-isothermal model, results showed that the magnitude of the average pressure drop was higher when pressure was predicted with constant compressibility factor, but the same average pressure drop was reduced when the pressure was predicted with variable compressibility factor, z. Since compressibility factor is a function of temperature and pressure, the above findings signifies that in the case when gas temperature does not stabilize, the prediction of pressure with isothermal model and constant compressibility factor will lead to significant errors.

In the last decades bioresorbable and biodegradable polymers have gained a very good reputation both in research and in industry thanks to their unique characteristics. They are, indeed, able to ensure high performances and biocompatibility, at the same time avoiding post-healing surgical interventions for devices removal. In the medical device industrial use of such biopolymers, it is widely known that product formulation and manufacturing need to follow specific procedures in order to ensure both proper mechanical properties and desired degradation profile. Moreover, also the sterilization method is crucial and its impact on physical properties is generally underestimated. In this work we focused our attention on the effect of different terminal sterilization methods on two commercially available poly(L-lactide-co-ε-caprolactone) with equivalent chemical composition (70% PLA and 30% PCL) and relatively similar initial molecular weight, but different chains arrangement and crystallinity. Results obtained show that crystallinity plays a key role, helping in preserving the narrow distribution of chains and, as a consequence, defined physical properties. These statements can be used as guidelines for a better choice of the most adequate biodegradable polymers in the production of resorbable medical devices.

Polyurethanes are materials with a strong structure-property relationship. The goal of this research was to study the effect of a polyol blend composition of polyurethanes on its properties using a mixture design and setting mathematic models for each property. Water absorption, hydrolytic degradation, contact angle, tensile stretch, hardness and modulus were studied. Additionally, Thermal stability was studied by thermogravimetric analysis. Area under the curve was used to evaluate the effect of polyol blend composition on thermal stability and kinetics of water absorption and hydrolytic degradation. Least squares were used to calculate the regression coefficients. Models for the properties were significant, and lack of fit was not (P<0.05). Fit statistics suggest both good fitting and prediction. Water absorption, hydrolytic degradation and contact angle were mediated by the hydrophilic nature of the polyols. Tensile strength, modulus and hardness could be regulated by the molecular weight and hydroxyl index of the polyols. Regression of DTG curves from thermal analysis showed improvement of thermal stability with the increase of PCL and PE. An ANOVA test of the model terms demonstrated that three component effects on bulk properties like water absorption, hydrolytic degradation, hardness, tensile strength and modulus, and the PEG*PCL interaction with the contact angle, which is a surface property. Mixture design application allowed for an understanding of the structure-property relationship through mathematic models.     

Breast cancer is the second cause of fatality among all cancers for women. Automatic classification of breast cancer lesions in mammograms is a challenging task due to the irregularity and complexity of the location, size, shape, and texture of these lesions. The intensity dissimilarity has been found between breast cancer tissues and normal tissues, when a multi-spectral anatomical mammographic screening scans have been done. In this work, two approaches have been evaluated to classify the breast tumor lesions. The first one is through Gabor wavelet features and the second one is Statistical features. Subsequently, support vector machine, Multilayer Perceptron and KNN classifiers have been used with computer based method for breast tumor classification.

The diagnosis of Cardio-Vascular diseases (CVD) is highly dependent on analysis of ECG signals. ECG analysis can be helpful in estimating the underlying cause and condition of heart in cardiac abnormality. The effectiveness of ECG signal analysis in detection of CVDs is widely accepted by professional healthcare service provider. Many algorithms have been proposed but almost all of them have some kind of limitations, and these limitations largely influence the effectiveness of ECG analysis. The performed research work is dedicated for design of unique self-organizing maps (SOMs) based neural network for classification of arrhythmia according to a particular ECG signal, the generation of SOMs is based on the certain unique signatures of ECG signals and have potential to classify different cardiac conditions. For extraction of unique features from ECG signals, we have proposed to use Fast Discrete Stockwell Transform (FDST). Since the proposed technique is a result of combining two different techniques hence called as hybrid technology. The purpose of using FDST is to identify unique signatures of ECG signals in a more improved manner than existing one, the term improved is used because it has several advantages over existing techniques such as wavelet and Fourier Transform based methods. Results obtained from the implementation of the technique are capable in visualizing the ECG sinus rhythm and arrhythmia conditions in form of unique SOM for each associated arrhythmia condition. This unique SOM based classification makes them ideal for being used as a diagnostic tool. This ability of arrhythmia classification using FDST and SOMs makes the technique unique and useful providing valuable information about patient condition. Using proposed technology a portable diagnosis tool for monitoring of patient at their site may be facilitated later, that will improve the quality of life of the patient by diagnosing cardiac condition.

A high-level control algorithm capable of generating position and torque references from surface electromyography signals (sEMG) has been designed. It is applied to a shape memory alloy (SMA) actuated exoskeleton used in active rehabilitation therapies for elbow joints. The sEMG signals are filtered and normalized according data collected online during the first seconds of~therapy sessions. The control algorithm uses the sEMG signals to promote active participation of patients during the therapy session. In order to generate the position reference pattern with good precision, the sEMG normalized signal is compared with a pressure sensor signal to detect the intention of each movement. The algorithm has been tested in simulations and with healthy people for control of an elbow exoskeleton in flexion–extension movements. The results indicate that sEMG signals from elbow muscles in combination with pressure sensors that measure arm–exoskeleton interaction can be used as inputs for the control algorithm, which adapts the reference for exoskeleton movements according a patient's intention.

AbstractWhile the technology is relatively new, low cost 3D printing has impacted many aspects of human life. 3D printers are being used as manufacturing tools for a wide variety of devices in a spectrum of applications ranging from diagnosis to implants to external prostheses. The ease of use and availability of 3D design software and low cost has made 3D printing an accessible manufacturing and fabrication tool in many research laboratories. 3D printers can print materials with varying density, optical character, strength and chemical properties providing platforms for a huge number of strategies that can be chosen for user’s needs. In this review, we focus on applications in biomedical diagnostics and how this revolutionary technique is facilitating development of low cost, sensitive and often geometrically complex tools. 3D printing in fabrication of microfluidics, supporting equipment, optical and electronic components of diagnostic devices is presented. Emerging diagnostic 3D bioprinting as a tool to incorporate living cells or biomaterials into 3D printing is also discussed.

The superharmonic imaging of tissue has the potential for high spatial and contrast resolutions, compared to the fundamental and second harmonic imaging. For this technique, the spectral bandwidth of an ultrasound transducer is divided for transmission of ultrasound and reception of its superharmonics (i.e., higher than the second harmonic). Due to the spectral division for the transmission and reception, transmitted ultrasound energy is not sufficient to induce superharmonics in media without using contrast agents, and it is difficult that a transducer has a -6-dB fractional bandwidth of higher than 100%. For the superharmonic imaging of tissue, thus, multi-frequency array transducers are the best choice if available; transmit and receive elements are separate and have different center frequencies. However, the construction of a multi-frequency transducer for intravascular ultrasound (IVUS) imaging is particularly demanding because of its small size of less than 1 mm. Here, we report a recently developed dual-element focused IVUS transducer for the third harmonic imaging of tissue, which consists of a 35-MHz element for ultrasound transmission and a 105-MHz element for third harmonic reception. For high quality third harmonic imaging, both elements were fabricated to have the same focus at 2.5 mm. The results of tissue mimicking phantom tests demonstrated that the third harmonic images produced by the developed transducer had higher spatial resolution and deeper imaging depth than the fundamental images.

Cough peak flow (CPF) is a measurement to evaluate the risk of cough dysfunction and can be measured using various devices, such as spirometers. However, complex device setup and the face mask required to be firmly attached to the mouth impose burdens on both patients and their caregivers. Therefore, this study develops a novel cough strength evaluation method using cough sounds. This paper presents an exponential model to estimate CPF from the cough peak sound pressure level (CPSL). We investigated the relationship between cough sounds and cough flows and the effects of a measurement condition of cough sound, microphone type, and participant’s height and gender on CPF estimation accuracy. The results confirmed that the proposed model estimated CPF with a high accuracy. The absolute error between CPFs and estimated CPFs were significantly lower when the microphone distance from the participant’s mouth was within 30 cm than when the distance exceeded 30 cm. Analysis of the model parameters showed that the estimation accuracy was not affected by participant’s height or gender. These results indicate that the proposed model has the potential to improve the feasibility of measuring and assessing CPF.

Biomass is a widely distributed and renewable source of carbon. The main objective of this work is to produce an activated carbon from coconut shells with suitable characteristics to separate CO2 from biogas. The textural characterization of the adsorbent has been determined. Pure component adsorption isotherms of CO2 and CH4 at 30, 50 and 70 °C have been measured. Moreover, the performance of the produced activated carbon, as potential adsorbent for CO2 capture from a CO2/CH4 gas mixture has been evaluated under dynamic conditions in a purpose-built fixed-bed setup.

Some contaminants of emerging concern (CECs) are known to survive conventional wastewater treatment plants, which introduce them back to the environment and can potentially cycle up in drinking water supplies. This is especially concerning because of the inherent ability of some CECs to induce physiological effects in humans at very low doses. Advanced oxidation processes (AOPs) such as TiO2 based photocatalysis are of prominent interest for addressing CECs in aqueous environments. Natural water resources often contain dissolved metal cations concentrations in excess of targeted CEC concentrations. These cations may significantly, adversely impact degradation of CECs by scavenging TiO2 surface generated electrons. Consequently, simple pseudo first order or Langmuir-Hinshelwood kinetics are not sufficient for reactor design and process analysis in some scenarios. Rhodamine B dye and dissolved copper cations were studied as reaction surrogates to demonstrate that TiO₂ catalyzed degradation for very dilute solutions is very nearly completely due to homogeneous reaction with hydroxyl radicals and that in this scenario the hole trapping pathway has negligible impact. Chemical reaction kinetic studies were then carried out to develop a robust model for RB/metal reactions that is exact in the electron pathways for hydroxyl radical production and metal scavenging.

The aim of this work is to evaluate the impact of proposed modifications to conventional capturing and discharging effluents devices in Subsurface Flow Wetland (SSFW) systems. Main modifications proposed consist on extending the influence of the capture and discharge device in such a way that the SSFW width and height are fully covered. Additionally an SSFW prototype was built as pilot including the proposed modifications and the impact of the innovative device is measured based on the efficiency of the Chemical Oxygen Demand (COD) removal as compared to a traditionally built SSFW. The results show that for the innovative device, the COD removal was 10% higher than for the conventional device.

Purification of biologically-derived therapeutics is a major cost contributor to the production of this rapidly growing class of pharmaceuticals. Monoclonal antibodies comprise a large percentage of these products therefore new antibody purification tools are needed. Small peptides, as opposed to traditional antibody affinity ligands such as Protein A, may have advantages in stability and production costs. Multiple heptapeptides that demonstrate Fc binding behavior that have been identified from a combinatorial peptide library using M13 Phage Display are presented herein. Seven unique peptide sequences of diverse hydrophobicity and charge were identified. All seven peptides showed strong binding to the four major human IgG isotypes, human IgM, as well as binding to canine, rat, and mouse IgG. These seven peptides were also shown to bind human IgG4 from DMEM cell culture media with 5% FCS and 5 g/L ovalbumin present. These peptides may be useful as surface ligands for antibody detection and purification purposes. Molecular docking and classical molecular dynamics (MD) simulations were conducted to elucidate the mechanisms and energetics for the binding of these peptides to the Fc region. The binding site was found to be located between the two glycan chains inside the Fc fragment. Both hydrogen bonding and hydrophobic interactions were found to be crucial for the binding interactions. Excellent agreement for the binding strength was obtained between experimental results and simulations.

Three-dimensional (3D) cell culture systems can be regarded as suitable platforms to bridge the huge gap between animal studies and two-dimensional (2D) monolayer cell culture to study chronic diseases such as cancer. In particular, the preclinical platforms for multicellular spheroid formation and culture can be regarded as ideal in vitro tumor models. The complex tumor microenvironment such as hypoxic region and necrotic core can be recapitulated in 3D spheroid configuration. Cells aggregated in spheroid structures can better illustrate the performance of anti-cancer drugs as well. Various methods have been proposed so far to create such 3D spheroid aggregations. Both conventional techniques and microfluidic methods can be used for generation of multicellular spheroids. In this review paper, we first discuss various spheroid formation phases. Then, the conventional spheroid formation techniques such as bioreactor flasks, liquid overlay and hanging droplet technique are explained. Next, a particular topic of the hydrogel in spheroid formation and culture is explored. This topic has received less attention in the literature. Hydrogels entail some advantages to the spheroid formation and culture such as size uniformity, the formation of porous spheroids or hetero-spheroids as well as chemosensitivity and invasion assays and protecting from shear stress. Finally, microfluidic methods for spheroid formation and culture are briefly reviewed.

Image processing is a field of which its popularity increases and continues and, that grows dynamically with new technologies. Nowadays, image processing finds itself in use in almost every field. One of these uses is undoubtedly in the field of medicine, where diagnosis and treatment planning are made from images and, which is constantly changing with newly developed techniques. Of course, the most important factor in using this so widely in the medical field is the acquisition of images on every medical field. With the help of these images, the complaints can be seen more easily and the doctor can follow a path in the treatment of the disease. In our study, we used the Region Growing segmentation method to detect the intestinal mass. This study compares the area determined by the specialist with the area obtained with the segmentation process and, it is seen that the created software system can be used as an auxiliary system to specialist doctors.

Optoelectronic devices are gold standard for 3D evaluation in clinics but due to the complexity of such kind of hardware and the lack of access for patients affordable, transportable and easy to use systems must be developed to be largely used in daily clinics. The Kinect^TM sensor presents various advantages compared to optoelectronic devices: price, transportability but also some limitations: (in)accuracy of the skeleton detection and tracking as well as the limited amount of available points that make 3D evaluation impossible. To overcome these limitations a novel method has been developed to perform 3D evaluation of the upper limbs. This system is coupled to rehabilitation exercises allowing functional evaluation while performing physical rehabilitation. To validate this new approach a double step method was used. The first step is a laboratory validation where the results obtained with the Kinect^TM have been compared with results obtained with an optoelectronic device, 40 healthy young adults participated in this first part. The second step was to determine the clinical relevance of such kind of measurement. Results of the healthy subjects were compared with a group of 22 elderly adults and a group of 10 chronic stroke patients to determine if different patterns can be observed. The new methodology and the different steps of the validations are presented in this paper.

Given their severity and non-healing nature, diabetic chronic wounds are a significant concern to the 30.3 million Americans diagnosed with diabetes mellitus (2015). Peripheral arterial diseases, neuropathy, and infection contribute to the development of these wounds, which lead to an increased incidence of lower extremity amputations. Early recognition, debridement, offloading, and controlling infection are imperative for timely treatment. However, wound characterization and treatment are highly subjective and based largely on the experience of the treating clinician. Many wound dressings have been designed to address particular clinical presentations, but a prescriptive method is lacking for identifying the particular state of chronic, non-healing wounds. The authors suggest that recent developments in wound dressings and biosensing may allow for the quantitative, real-time representation of the wound environment, including exudate levels, pathogen concentrations, and tissue regeneration. Development of such sensing capability could enable more strategic, personalized care at the onset of ulceration and limit the infection leading to amputation. This review presents an overview of the pathophysiology of diabetic chronic wounds, a brief summary of biomaterial wound dressing treatment options, and biosensor development for biomarker sensing in the wound environment.

Placing the needle inside the epidural space for locoregional anesthesia is a challenging procedure, which even today is left to the expertise of the operator. Recently, we have demonstrated that the use of optically sensorized needles significantly improve the effectiveness of such procedure. Here we propose an optimized configuration, where the optical fiber strain sensor is directly integrated inside the epidural catheter. The new design allows to solve the biocompatibility issues and increases the versatility of the former configuration. Through an in vivo study carried out on a porcine model we confirm the reliability of our approach, which also opens the way to catheter monitoring during its insertion inside biological spaces.

Oscillometric blood pressure (BP) devices currently estimate a single point but do not identify fluctuations in BP or distinguish them from variations in response to physiological properties. In this paper, to analyze BP normality based on oscillometric measurements, we use statistical approaches including kurtosis, skewness, Kolmogorov-Smirnov, and correlation tests. Then, to mitigate uncertainties, we use a deep neural network (DNN) to determine the confidence limits (CLs) of BP measurements based on their normality. The proposed DNN regression model decreases the standard deviation of error (SDE) of the mean error (ME) and the mean absolute error (MAE) and reduces the uncertainty of the CLs and SDEs of the proposed technique. We validate the normality of the distribution of the BP estimation distribution which fits the Gaussian distribution very well. We use a rank test in the DNN regression model to demonstrate the independence of the artificial SBP and DBP estimations. First, we perform statistical tests to verify the normality of the BP measurements for individual subjects. The proposed methodology provides accurate BP estimations and reduces the uncertainties associated with the CLs and SDEs based on the DNN regression estimator.

Molecular and morphological properties of poly(vinyl chloride) grains produced by suspension polymerization of VCM in the presence of a mixture of three kind of initiators (i.e. fast, mild and slow) (named as Cok process) was experimentally investigated in a pilot-scale reactor. The results obtained here were initially compared with a isothermal regular process (named as control process) and then with those obtained already for other productivity-enhancing polymerization techniques (i.e. nonisothermal and fast initiator dosage process). The results showed that, in contrast to nonisothermal and fast initiator dosage process, the addition of initators mixture at the beginning of the reaction has the smallest influence on molecular weight and polydispersity index compared to control process. It is obvioused that Cok-PVC grains have the lowest cold plasticizer absorption and porosity among these mentioned processes. Scanning electron microscopy (SEM) showed that the particles produced by Cok process are more regularly shaped, with a smoother surface compared with the control product. According to the literatures, all three productivity-enhancing techniques lead to an apparent quality enhancement, higher flowability and greater bulk density of final grains. While both processes of continous initiator dosage and nonisothermal polymerization broaden the particle size distribution of final PVC grains, applying initiator mixture produces particles with the same particle size distribution as control process. The SEM images processing showed that Cok process deccelerates the formation of a three-dimensional skeleton of primary particles relative to the control polymerization. In comparison with nonisothermal trajectory and continous fast initiator dosage system, the Cok polymerization process leads to the most delay of motionless conversions and fusion time as well.

In this study, the coating order of two monomers in the shell polymerization process of core–shell nanoparticles was altered to facilitate easy coating and optimize the properties of the coated surface to simplify the additional coating formulation process. To obtain a glass transition temperature suitable for coating, a core was synthesized by the copolymerization of an acryl monomer. A perfluoro monomer and silane monomer were additionally added to synthesize nanoparticles exhibiting both water–oil repellency and anchoring properties. In order to realize various surface properties, the nanoparticles underwent surface modification and cellulose fiber was introduced. Through the various data described in this text, the surface properties improved with the order of introduction of the two monomers.

The air is not the same as thousands and hundreds of years ago. In the air, suspended particles originate from natural phenomena like dust storms or volcanic activities, as well as anthropogenic pollutants such as fuel engine exhaust and everyday activities at home. The total particles in the air can be classified by sizes, such as PM10, PM2.5 or ultrafine particles. However, there are many other important factors in addition to the particle size, influencing the particle behavior and affecting our health. The surface area, chemical and biological composition, aspect ratio, and the charge are all factors characteristic of particles. OoC microfluidic chips are very useful for the pollutant toxicity measurements on various body tissues. A better understanding of pollutants will help to trace these to the potential sources. The data from the on-the-ground and satellite monitoring can be integrated into models, helping to predict and prevent pollution exposure.

Data generation using high throughput technologies has led to the accumulation of diverse types of molecular data.These data have different types (discrete,real,string etc.) and occur in various formats and sizes. Datasets including gene expression, miRNA expression, protein-DNA binding data (ChIP-Seq/ChIP-ChIP), mutation data(copy number variation, single nucleotide polymorphisms), GO annotations, protein-protein interaction and disease-gene association data are some of the commonly used genomic datasets to study biological processes. Each of them provides a unique, complementary and partly independent view of the genome and hence embed essential information about their regulatory mechanisms. In order to understand the functions of genes, proteins and analyze mechanisms arising out of their interactions, information provided by each of these datasets individually may not be sufficient. Therefore integrating these multi-omic data and inferring regulatory interactions from the integrated dataset provides a system level biological insights in predicting gene functions and their phenotypic outcomes. To study genome functionality through interaction networks, different methods have been proposed for collective mining of information from an integrated dataset. We survey here data integration approaches using state-of-the-art techniques such as network integration, Bayesian networks, regularized regression (LASSO) and multiple kernel learning methods.

We propose an electrocardiogram (ECG) signal-based algorithm to estimate the respiratory rate is a significant informative indicator of physiological state of a patient. The consecutive ECG signals reflect the information about the respiration because inhalation and exhalation make transthoracic impedance vary. The proposed algorithm extracts the respiration-related signal by finding out the commonality between the frequency and amplitude features in the ECG pulse train. The respiration rate can be calculated from the principle components after the procedure of the singular spectrum analysis. We achieved 1.7569 breaths per min of root-mean-squared error and 1.7517 of standard deviation with a 32-seconds signal window of the Capnobase dataset, which gives notable improvement compared with the conventional Autoregressive model based estimation methods.

To date, several independent methods and algorithms exist exploiting constraint-based stoichiometric models to find metabolic engineering strategies that optimize microbial production performance. Optimization procedures based on metaheuristics facilitate a straightforward adaption and expansion of engineering objectives as well as fitness functions, while being particularly suited for solving problems of high complexity. With the increasing interest in multi-scale models and a need for solving advanced engineering problems, we strive to advance genetic algorithms, which stand out due to their intuitive optimization principles and proven usefulness in this field of research. A drawback of genetic algorithms is that premature convergence to sub-optimal solutions easily occurs if the optimization parameters are not adapted to the specific problem. Here, we conducted comprehensive parameter sensitivity analyses to study their impact on finding optimal strain designs. We further demonstrate the capability of genetic algorithms to simultaneously handle (i) multiple, non-linear engineering objectives, (ii) the identification of gene target-sets according to logical gene-protein-reaction associations, (iii) minimization of the number of network perturbations, and (iv) the insertion of non-native reactions, while employing genome-scale metabolic models. This framework adds a level of sophistication in terms of strain design robustness, which is exemplarily tested on succinate overproduction in Escherichia coli.

The development of organ-on-chip and biological scaffolds is currently requiring simpler methods to microstructure biocompatible materials in three dimensions, fabricate structural and functional elements in biomaterials or modify the physicochemical properties of desired substrates. Aiming at addressing this need, a low-power CD-DVD-Blu-ray laser pickup head was mounted on a programmable three-axis micro-displacement system in order to modify the surface of polymeric materials in a local fashion. Thanks to a specially-designed method using a strongly absorbing additive coating the materials of interest, it has been possible to establish and precisely control processes useful in microtechnology for biomedical applications. The system was upgraded with blu-ray laser for additive manufacturing and ablation on a single platform. In this work, we present the application of these fabrication techniques to the development of biomimetic cellular culture platforms thanks to the simple integration of several features typically achieved with traditional, less cost-effective microtechnology methods in one step or through replica-molding. Our straightforward approach indeed enables great control of local laser microablation or polymerization for true on-demand biomimetic micropatterned designs in transparent polymers and hydrogels and is allowing integration of microfluidics, microelectronics, surface microstructuring and transfer of superficial protein micropatterns on a variety of biocompatible materials.

This paper provides orthogonal moments (OM) such as, Zernike Moments(ZM), Psuedo Zernike Moments(PZM) and Orthogonal Fourier Mellin Moments(OFMM) for the analysis of melanoma images. The moment invariants may vary with respect to geometric variations. For the analysis of orthogonal moments hundred random melanoma images and hundred non-melanoma images have been taken into consideration from the database of 570 melanoma images and 250 non-melanoma images respectively. Orthoganal moments have been computed by varying the phase angles from 10° to 40° with an equal interval of 10° degree for the orders 2, 4,8,16,32,64,128,256 respectively. For the optimal OMs Particle Swarm Optimization (PSO) technique have been used. These set of extracted optimal OMs have been further applied to classify melanoma images. Support Vector Machine (SVM) has been used for the classification of [1]sensitivity=88.78%.

The consequences of a fall on an elderly person can be reduced if the accident is attended by medical personnel within the first hour. Independent elderly people use to stay alone for long periods of time, being in more risk if they suffer a fall. The literature offers several approaches for detecting falls with embedded devices or smartphones using a triaxial accelerometer. Most of these approaches were not tested with the target population, or are not feasible to be implemented in real-life conditions. In this work, we propose a fall detection methodology based on a non-linear classification feature and a Kalman filter with a periodicity detector to reduce the false positive rate. This methodology requires a sampling rate of only 25 Hz; it does not require large computations or memory and it is robust among devices. We test our approach with the SisFall dataset achieving 99.4% of accuracy. Then, we validate it with a new round of simulated activities with young adults and an elderly person. Finally, we give the devices to three elderly persons for full-day validations. They continued with their normal life and the devices behaved as expected.

In our previous works we have proposed design equations that can predict with reasonable accuracy the transition point from homogeneous to heterogeneous regime as well as the gas holdup and the mean Sauter diameter at the homogeneous regime. The validity of the proposed correlations was checked with data obtained using different geometrical configurations and several Newtonian and non-Newtonian liquids as well as the addition of surfactants. However, in all the experiments the gas phase was atmospheric air. This work investigates the effect of gas phase properties by conducting experiments employing various gases (i.e., air, CO₂, He) that cover a wide range of physical property values. Experiments revealed that only the use of low-density gas (He) has a measurable effect on bubble column performance. More precisely, when the low-density gas (He) is employed, the transition point shifts to higher gas flow rates and the gas holdup decreases, a fact attributed to the lower momentum force exerted by the gas. In view of the new data, the proposed correlations have been slightly modified to include the effect of gas phase properties and it is found that they can predict the aforementioned quantities with an accuracy of ±15%. It has been also proved that CFD simulations are an accurate means for assessing the flow characteristics inside a bubble column.

Structural system design is the process of giving form to a set of interconnected components subjected to loads and design constraints while navigating a complex design space. While safe designs are relatively easy to develop, optimal designs are not. Modern computational optimization approaches employ population based metaheuristic algorithms to overcome challenges with the system design optimization landscape. However, the choice of the initial population, or ground structure, can have an outsized impact on the resulting optimization. This paper presents a new method of generating such ground structures, using a combination of topology optimization (TO) and a novel system extraction algorithm. Since TO generates monolithic structures, rather than systems, its use for structural system design and optimization has been limited. In this paper, truss systems are extracted from topologies through morphological analysis and artificial intelligence techniques. This algorithm, and its assessment, constitutes the key contributions of this paper. The structural systems obtained are compared with ground truth solutions to evaluate the performance of the algorithms. The generated structures are also compared against benchmark designs from the literature. The results indicate that the presented truss generation algorithm produces structures comparable to those generated through metaheuristic optimization, while mitigating the need for assumptions about initial ground structures.

A membrane can be represented by an energy landscape that solutes or colloids must cross. A model accounting for the momentum and the mass balances on the membrane energy landscape establishes a new way of writing for the Darcy law. The counter pressure in the Darcy law is no longer written as the result of an osmotic pressure difference but rather as a function of colloid-membrane interactions. The ability of the model to describe the physics of the filtration is discussed in detail. This model is solved on a simplified energy landscape to derive analytical relationships that describe the selectivity and the counter pressure from ab-initio operating conditions. The model shows that the stiffness of the energy landscape has an impact on the process efficiency: a gradual increase in interactions (like with hourglass pore shape) can reduce the separation energetic cost. It allows the introduction of a new paradigm to increase membrane efficiency: the accumulation that is inherent to the separation must be distributed across the membrane. Asymmetric interactions thus lead to direction-dependent transfer properties and the membrane exhibits diode behavior. These new transfer opportunities are discussed.

Numerical simulations of turbulent flows in a stirred dead-end membrane bioreactor are performed by the RNG k-ε model based on finite volume method using Fluent codes. Comparisons of numerical and experimental results confirm the reliability and feasibility of the constructed model. Flow structures such as wake flows and circulation loops in stirred flows were well simulated. An increase of stirring speed is proposed to use to minimize the low velocity region. The single vane stirrer is found to be beneficial for biological separations. Results reveal that the increase of vane number can enhance the mixing effect in flow domains. However, a circular disk stirrer goes against the formation of vertical circulations. The six-vane stirrer is found to be able to provide a uniform distribution of high shear stress.

Neural microprobes represent an important component of neural prosthetic systems where implanted microprobes record the electro-potentials generated by specific thoughts in the brain and convey the signals to algorithms trained to interpret these thoughts. Here, we present novel elongated multi-site neural probe that can reach depths greater than 10mm. We hypothesize that reaching such depth allows the recording of cognitive signals required to drive cognitive prosthetics. The impedance of the recording sites on the probes was on the order of 500 kΩ at 1 kHz, which is consistent with probes used for neurophysiological recordings. The probes were made porous using Xenon Difluoride (XeF₂) dry etching to improve the biocompatibility and their adherence to the surrounding neural tissue. Numerical studies were performed to determine the reliability of the porous probes. We implanted the elongated probe in rats and show that the elongated probes are capable of simultaneously recording both spikes and local field potentials (LFPs) from various recording sites.

In this work the efficiency of a new μ-mixer design is investigated. As in this type of devices the Reynolds number is low, mixing is diffusion dominated and it can be enhanced by creating secondary flows. In this study we propose the introduction of helical inserts into a straight tube to create swirling flow. The influence of the insert’s geometrical parameters (pitch and length of the propeller blades) and of the Reynolds number on the mixing efficiency and on the pressure drop are numerically investigated. The mixing efficiency of the device is assessed by calculating a number, i.e. the Index of Mixing Efficiency that quantifies the uniformity of concentration at the outlet of the device. The influence of the design parameters on the mixing efficiency is assessed by performing a series of “computational” experiments, in which the values of the parameter are selected using DOE methodology. Finally using the numerical data, appropriate design equations are formulated, which, for given values ​​of the design parameters, can estimate with reasonable accuracy both the mixing efficiency and the pressure drop of the proposed mixing device.

Current commercially available instruments for monitoring mitochondrial respiration are incapable of single cell measurements. Therefore, we developed a three-electrode, Clark-type biosensor suitable for mitochondrial respirometry in single oocytes and embryos. The biosensor was embedded in a PMMA (polymethyl methacrylate) micro-chamber to allow investigation of single oocytes/embryos immersed in up to 100 µL of respiration buffer. The micro-chamber was completely sealed to avoid oxygen exchange between the inside of the chamber and the atmosphere, while being maintained at a temperature of 38.5 ˚C to preserve cell viability. Using amperometry, the oxygen consumption of cells inside the micro-chamber was measured as a change in output current and converted to femto-mol (fmol) oxygen consumed per second based on calibrations with known buffer oxygen concentrations. The sensor measured basal cell respiration supported by endogenous substrates, respiration associated with proton leak induced by inhibition of the adenosine triphosphate (ATP) synthase (complex V) with oligomycin, and the maximal non-coupled respiratory capacity revealed by Carbonyl cyanide-4-(trifluoromethoxy)phenylhydrazone (FCCP) titration. Some potential applications of this oxygen sensor system include evaluating effects of metabolic therapies on oocyte bioenergetics, and monitoring mitochondrial function throughout oocyte maturation and blastocyst development to predict embryo viability to compliment assisted reproductive technologies

While the importance of continuous monitoring of electrocardiographic (ECG) or photoplethysmographic (PPG) signals to detect cardiac anomalies is generally accepted in preventative medicine, there remain major barriers to its actual widespread adoption. Most notably, current approaches tend to lack real-time capability, exhibit high computational cost, and be based on restrictive modeling assumptions or require large amounts of training data. We propose a lightweight and model-free approach for the online detection of cardiac anomalies such as ectopic beats in ECG or PPG signals based on the change detection capabilities of Singular Spectrum Analysis (SSA) and nonparametric rank-based cumulative sum (CUSUM) control charts. The procedure is able to quickly detect anomalies without requiring the identification of fiducial points such as R-peaks and is computationally significantly less demanding than previously proposed SSA-based approaches. Therefore, the proposed procedure is equally well suited for standalone use and as an add-on to complement existing (e.g. heart rate (HR) estimation) procedures.

In this work modeling and analysis of an integrated opto-fluidic sensor, with a focus on achievement of single mode optical confinement and continuous flow of micro particles in the microfluidic channel for Lab-on-a Chip (LOC) sensing application is presented. This sensor consists of integrated optical waveguides, microfluidic channel among other integrated optical components. A continuous flow of micro particles in a narrow fluidic channel is achieved by maintaining the two sealed chambers at different temperatures and by maintaining a constant pressure of 1Pa at the centroid of narrow fluidic channel geometry. The analysis of silicon on insulator (SOI) integrated optical waveguide at an infrared wavelength of 1550nm for single mode sensing operation is presented. The optical loss is found to be 0.0005719dB/cm with an effective index of 2.2963. The model presented in this work can be effectively used to detect the nature of micro particles and continuous monitoring of pathological parameters for sensing applications.

Crystallization behavior of hexadecane (C₁₆H₃₄), octadecane (C₁₈H₃₈), eicosane (C₂₀H₄₂), and docosane (C₂₂H₄₆) dispersions of similar mean droplet diameter (x_50.2 ≈ 15 µm) was investigated in quiescent systems and compared to crystallization under mechanical stress. In quiescent systems, the required supercooling decreased with increasing chain length of the alkanes to initiate crystallization. Crystallization of alkane dispersions under mechanical stress resulted in similar onset crystallization supercooling, as during quiescent crystallization. Increase of mechanical stress did not affect the onset crystallization supercooling within alkane dispersions.

This work deals with the numerical investigation of the delivery of potential therapeutic agents through dentinal discs (i.e. a cylindrical segment of the dentinal tissue) towards the dentin-pulp junction. The aim is to assess the main key features (i.e. molecular size, initial concentration, consumption rate, disc porosity and thickness) that affect the delivery of therapeutic substances to the dental pulp and consequently to define the necessary quantitative and qualitative issues related to a specific agent before its potential application in clinical practice. The CFD code used for the computational study is validated with relevant experimental data obtained using micro Laser Induced Fluorescence (μ-LIF) a non-intrusive optical measuring technique. As the phenomenon is diffusion dominated and strongly dependent on the molecular size, the time needed for the concentration of released molecules to attain a required value can be controlled by their initial concentration. Finally, a model is proposed which, given the maximum acceptable time for the drug concentration to attain a required value at the pulpal side of the tissue along with the aforementioned key design parameters, is able to estimate the initial concentration to be imposed and vice versa.

A cuprous oxide (Cu₂O) thin layer served as the base for a non-enzymatic glucose sensor in an alkaline medium, 0.1 NaOH solution, with a linear range of 50-200 mg/dL using differential pulse voltammetry (DPV) measurement. An X-ray photoelectron spectroscopy (XPS) study confirmed the formation of the cuprous oxide layer on the thin gold film sensor prototype. Quantitative detection of glucose in both phosphate-buffered saline (PBS) and undiluted human serum were carried out. Neither ascorbic acid nor uric acid even at a relatively high concentration level of 100mg/dL in serum interfered with the glucose detection, demonstrating the excellent selectivity of this non-enzymatic cuprous oxide thin layer based glucose sensor. Chronoamperometry (CA) and single potential amperometric voltammetry were used to verify the measurements obtained by differential pulse voltammetry (DPV), and the positive results validated that the detection of glucose in a 0.1 M NaOH alkaline medium by DPV measurement was effective. Nickel, platinum and copper are commonly used metals for non-enzymatic glucose detection. The performance of these metal-based sensors for glucose detection using DPV were also evaluated. Cuprous oxide (Cu₂O) thin layer based sensor showed the best sensitivity for glucose detection among the sensors evaluated.

We compared performance of a novel encoding Lempel-Ziv complexity (ELZC) with approximate entropy (ApEn), sample entropy (SmpEn) and permutation entropy (PerEn) as nonlinear metric to assess ECG quality. Firstly to compare performance of discerning randomness and inherent nonlinear properties within time series, this study calculated the aforementioned four nonlinear complexity values on several typical artificial time series i.e., Gauss noise, two kinds of noisy time series, two kinds of Logistic series and periodic series, respectively. Then for analyzing sensitivity of the aforementioned four complexity methods to content level of different types noise within ECG recordings, we investigated variation trend of ELZC, ApEn, SmpEn and PerEn in several synthetic ECG recordings containing different types noise (i.e., baseline wander, muscle artefacts, electrode motion, power line and mixed noise) and different signal noise ratios (i.e., 15, 10, 5, 0, −5 and −10 dB). Finally, the four complexity methods were employed to classify the quality of real ECG recordings from the PhysioNet/Computing in Cardiology Challenge 2011 (CINC 2011) of the MIT databases, then receiver operating characteristic curves (ROC) and their corresponding area under curve (AUC) were yielded. The results showed ELZC could not only distinguish randomness and chaotic within time series but also reflect content level of noise within time series, and the highest AUC of PerEn, ELZC, SmpEn and ApEn were 0.850, 0.695, 0.474 and 0.461, respectively. The results demonstrated PerEn and ELZC were more effectively than ApEn and SmpEn for assessing ECG quality.

Background: Lithium di-silicate dental ceramics bonding, realized by using different resins, is strictly dependent on micro-mechanical retention and chemical adhesion. The aim of this in vitro study was to investigate the capability of a 1070 nm fiber laser for their surface treatment. Methods: Samples were irradiated by a pulsed fiber laser at 1070 nm with different parameters (Peak Power from 5 kW to 5 kW, RR 20 kHz, speed from 10 to 50 mm/s, total Energy Density from 1.3 to 27 kW/cm²) and the thermal elevation during the experiment was recorded by a Fiber Bragg Grating (FBG) temperature sensor. Subsequently, the surface modifications were analysed by optical microscope, Scanning Electron Microscope (SEM) and Energy Dispersive X-ray Spectroscopy (EDS). Results: With a Peak Power of 5 kW, RR of 20 kHz and speed of 50 mm/s, the microscopic observation of the irradiated surface showed increased roughness with small areas of melting and carbonization. EDS analysis revealed that, with these parameters, there are no evident differences between laser-processed samples and controls. Thermal elevation during laser irradiation ranged between 5 °C and 9 °C. Conclusions: 1070 nm fiber laser can be considered as a good device to increase the adhesion of Lithium di-silicate ceramics.

Cardamom is plant of the Zingiberaceae family. It has been used for the treatment of many diseases such as migraine, bronchitis, stomach and intestinal disorders. Cardamom contains triterpenes, resins, starch and fatty compounds. Phytosterols (stigmasterol, campesterol and β-sitosterol) are a group steroid alcohol in plants. They are used food, medicine and cosmetic industry. They are protective effects against some types of cancer too. Phytosterols are found in the vegetable oil such as the spindle, corn and soybean oil. This paper deals with the maximum oil and β-sitosterol yield were investigated by means of the supercritical CO₂ extraction of cardamom. The effect of operating parameters as temperature, pressure and CO₂ flow rate were investigated on oil yield. The amount of β-sitosterol was analyzed by Gas Chromatography-Mass Spectrometry (GC-MS) at optimized conditions. The optimized conditions were recorded as temperature of 40^oC, pressure of 200 bar and CO₂ flow rate of 4 L/min. The maximum oil yield and amount of β-sitosterol were found as 74.83 mg oil/g seed and 4.73 mg β-sitosterol/g seed cardamom under these conditions.

Ionic liquids (ILs) have gained interest among researchers due to its tunable properties that can be used in wide applications. However, toxicity and bio-degradation studies of ILs proved that most of the aromatic ILs, such as imidazolium is highly toxic and non-biodegradable. Several advance oxidation processes (AOPs) have been investigated by researchers to evaluate the efficiency of the systems for the removal of ILs from wastewater. However, the issue on relative high cost and environmental concern has limited the application of these AOPs in industry. In this research, photocatalytic study using hybrid nano-materials was conducted to evaluate the efficiency of this system as an alternative AOP system for removal of ILs from wastewater. The synergistic effect of adsorption-photodegradation was introduced by depositing Fe-TiO₂ onto the functionalized activated carbon (AC). Nano-TiO₂ was synthesized using micromulsion method before modification with transition metal and deposited onto the oxidized AC. Photodegradation reaction of 1-butyl-3-methylimidazolium chloride [bmim]Cl was investigated under simulated visible light irradiation. It was observed that the overall efficiency of the system was increased with the increasing amount of Fe dopant. Investigation on the extrinsic factors such as solution pH, initial concentration of ILs and photocatalyst dosage showed to significantly affect the overall efficiency of the systems where the optimum condition for the system was observed at pH 10, with initial ILs at 1mM at 1 g/L of photocatalyst. The best performance photocatalyst was 0.2Fe-TiO₂/AC.