The dielectrophoretic (DEP) separation of cell, using microelectrodes structure, has been limited to small scale due to size of the substrate. This work was carried out to extend the capability of microelectrodes system by orientating the microelectrodes in three dimensions (3-D) for larger scale dielectrophoretic separation of microorganism. The designed 3-D separation chamber consists of microelectrodes on two opposing walls. Based on the FEMLAB simulation, the electric field was seen to be generated across the chamber, rather than between adjacent electrodes in the same plane like in the small scale system. This configuration led to a stronger electric field in the bulk medium. The experimental results showed that the 3-D microelectrodes chamber behaved similar to the system with microelectrodes on one wall. The effects of the main parameters such as voltage, frequency and flow rates were similar to that of the systems with all the electrodes on one wall, but on the overall, capture more cells. A gap size between 250 – 500 μm resulted in an electric field which is strong enough to hold cells while giving a reasonable cross sectional area at the same time. Although there is some improvement achieved by 3-D system, it is still not very much, as compared to the small scale system.
For testing the homogeneity of variances, modifications of well-known tests are known which combine rigorous theory with resampling (bootstrap). We propose versions of these tests, which are computationally simpler (although asymptotically equivalent). The earlier procedures used the smooth bootstrap with two thousand bootstrap replications per sample whereas our proposals use only the classical bootstrap (or percentile method) with just one thousand bootstrap replications per sample, and also required much less computing time. Our proposals cover the Ansari-Bradley-, Mood- and Klotz-tests. We explain their superiority over the existing methodologies available in textbooks and packages.
This paper presents the chaotic pulse train (CPT) waveforms of the vertical electric field generated by lightning observed in Malaysia. Focusing on the position where these electric field changes occur in a number of cloud to ground (CG) flashes, these CPTs were detected in different ways of occurrences, durations, intensities and amplitudes. Seventy-six chaotic pulse trains were found in this study from a sum of 172 CG flash records from three thunderstorm days. The fast field antenna was employed to do the field measurements. As opposed to the typical occurrence of chaotic pulse trains prior to subsequent strokes as reported in the literature, this study has found chaotic pulse trains occurring in different places along the CG electric field waveforms.
The unsteady mixed convection boundary layer flow near the forward stagnation point of a two-dimensional symmetric body prescribed by a uniform heat flux rate is studied in this paper. The main aim of the investigation is to identify situations in which dual solutions for the steady-state flow can be determined when the flow is opposing. It is also shown that there is a smooth transition from the unsteady initial flow (short time) to the final steady state flow (large time).
Tetanus is an acute, potentially fatal disease caused by Clostridium tetani. It is characterized by generalized, painful spasms and rigidity of skeletal muscles. We present two fatal cases and discuss the potential causes that lead to mortality in cases of tetanus infection
Robot-assisted surgery is gaining popularity worldwide and there is increasing scientific interest to explore the potential of soft continuum robots for minimally invasive surgery. However, the remote control of soft robots is much more challenging compared with their rigid counterparts. Accurate modeling of manipulator dynamics is vital to remotely control the diverse movement configurations and is particularly important for safe interaction with the operating environment. However, current dynamic models applied to soft manipulator systems are simplistic and empirical, which restricts the full potential of the new soft robots technology. Therefore, this article provides a new insight into the development of a nonlinear dynamic model for a soft continuum manipulator based on a material model. The continuum manipulator used in this study is treated as a composite material and a modified nonlinear Kelvin-Voigt material model is utilized to embody the visco-hyperelastic dynamics of soft silicone. The Lagrangian approach is applied to derive the equation of motion of the manipulator. Simulation and experimental results prove that this material modeling approach sufficiently captures the nonlinear time- and rate-dependent behavior of a soft manipulator. Material model-based closed-loop trajectory control was implemented to further validate the feasibility of the derived model and increase the performance of the overall system.
The specific heats (Csp) of neat polyvinyl alcohol (NPVOH) and 40 phr glycerol plasticized polyvinyl alcohol (PPVOH) were measured using a method known as power compensate differential scanning calorimetry. A high purity sapphire (Al2O3) was used as a reference material. NPVOH has a melting temperature of approximately 480 K, while PPVOH has a value of 30 K lower than NPVOH. The amplitude increment of Csp for NPVOH was also higher than PPVOH at melting stage. Overall, Csp of NPVOH is lower than PPVOH because glycerol has reduced the rigidity of PVOH and subsequently induced the motion of molecular structure at an elevated temperature. Based on the specific heat outcomes, neat PVOH and glycerol plasticized PVOH required 1173.544 J/g and 1946.631 J/g, respectively, to heat from 330 to 550 K.
Parkinson Disease (PD) is a neurodegenerative disorder of the central nervous system that often impairs the patient’s motor skills, speech and other functions. The four cardinal signs of parkinsonism are resting tremor, bradykinesia, cogwheel rigidity and postural instability. The prevalence of depression in PD ranges from 4% to 75%. However depression in PD is often mistakenly as the presentation of the disease itself. Therefore this paper reviewed the clinical feature of depression in PD and explored the aetiology of depression in PD.
Nickel (Ni), cobalt (Co), and zinc (Zn) loaded on fibrous silica KCC-1 was investigated for CO2 methanation reactions. Ni/KCC-1 exhibits the highest catalyst performance with a CH4 formation rate of 33.02 × 10-2 molCH4 molmetal-1 s-1, 1.77 times higher than that of Co/KCC-1 followed by Zn/KCC-1 and finally the parent KCC-1. A pyrrole adsorption FTIR study reveals shifting of perturbed N-H stretching decreasing slightly with the addition of metal oxide, suggesting that the basic sites of catalyst were inaccessible due to metal oxide deposition. The strengths of basicity were found to follow sthe equence KCC-1, Ni/KCC-1, Zn/KCC-1, and Co/KCC-1. The data were supported by N2 adsorption desorption analysis, where Co/KCC-1 displayed the greatest reduction in total surface area whereas Ni/KCC-1 displayed the least reduction. The elucidation of difference mechanism pathways has also been studied by in situ IR spectroscopy studies to determine the role of different metal oxides in CO2 methanation. It was discovered that Ni/KCC-1 and Co/KCC-1 follow a dissociative mechanism of CO2 methanation in which the CO2 molecule was dissociated on the surface of the metal oxide before migration onto the catalyst surface. This was confirmed by the evolution of a peak corresponding to carbonyl species (COads) on a metal oxide surface in FTIR spectra. Zn/KCC-1, on the other hand, showed no such peak, indicating associative methanation pathways where a hydrogen molecule interacts with an O atom in CO2 to form COads and OH. These results offers a better understanding for catalytic studies, particularly in the field of CO2 recycling.
Parkinson's disease (PD) is a severely debilitating neurodegenerative disease, affecting the motor system, leading to resting tremor, cogwheel rigidity, bradykinesia, walking and gait difficulties, and postural instability. The severe loss of dopaminergic neurons in the substantia nigra pars compacta causes striatal dopamine deficiency and the presence of Lewy bodies indicates a pathological hallmark of PD. Although the current treatment of PD aims to preserve dopaminergic neurons or to replace dopamine depletion in the brain, it is notable that complete recovery from the disease is yet to be achieved. Given the complexity and multisystem effects of PD, the underlying mechanisms of PD pathogenesis are yet to be elucidated. The advancement of medical technologies has given some insights in understanding the mechanism and potential treatment of PD with a special interest in the role of microRNAs (miRNAs) to unravel the pathophysiology of PD. In PD patients, it was found that striatal brain tissue and dopaminergic neurons from the substantia nigra demonstrated dysregulated miRNAs expression profiles. Hence, dysregulation of miRNAs may contribute to the pathogenesis of PD through modulation of PD-associated gene and protein expression. This review will discuss recent findings on PD-associated miRNAs dysregulation, from the regulation of PD-associated genes, dopaminergic neuron survival, α-synuclein-induced inflammation and circulating miRNAs. The next section of this review also provides an update on the potential uses of miRNAs as diagnostic biomarkers and therapeutic tools for PD.
Parkinson's disease (PD) is a neurodegenerative disease of the central nervous system caused due to the loss of dopaminergic neurons. It is classified under movement disorder as patients with PD present with tremor, rigidity, postural changes, and a decrease in spontaneous movements. Comorbidities including anxiety, depression, fatigue, and sleep disorders are observed prior to the diagnosis of PD. Gene mutations, exposure to toxic substances, and aging are considered as the causative factors of PD even though its genesis is unknown. This paper reviews PD etiologies, progression, and in particular measurable indicators of PD such as neuroimaging and electrophysiology modalities. In addition to gene therapy, neuroprotective, pharmacological, and neural transplantation treatments, researchers are actively aiming at identifying biological markers of PD with the goal of early diagnosis. Neuroimaging modalities used together with advanced machine learning techniques offer a promising path for the early detection and intervention in PD patients.