Appl. Sci., Volume 9, Issue 10 (May-2 2019) – 207 articles

The aim of this study was to use near-infrared time-resolved spectroscopy (TRS) to determine the absolute values of cerebral blood volume (CBV) and cerebral hemoglobin oxygen saturation (ScO₂) during the immediate transition period in term neonates and the changes in optical properties such as the differential pathlength factor (DPF) and reduced scattering coefficient (μ_s’). CBV and ScO₂ were measured using TRS during the first 15 min after birth by vaginal delivery in term neonates who did not need resuscitation. Within 2–3 min after birth, CBV showed various changes such as increases or decreases, followed by a gradual decrease until 15 min and then stability (mean (SD) mL/100 g brain: 2 min, 3.09 (0.74); 3 min, 3.01 (0.77); 5 min, 2.69 (0.77); 10 min, 2.40 (0.61), 15 min, 2.08 (0.47)). ScO₂ showed a gradual increase, then kept increasing or became a stable reading. The DPF and μ_s’ values (mean (SD) at 762, 800, and 836 nm) were stable during the first 15 min after birth (DPF: 4.47 (0.38), 4.41 (0.32), and 4.06 (0.28)/cm; μ_s’: 6.54 (0.67), 5.82 (0.84), and 5.43 (0.95)/cm). Accordingly, we proved that TRS can stably measure cerebral hemodynamics, despite the dramatic physiological changes occurring at this time in the labor room. Full article

Neural network shows great potential in modulation classification because of its excellent accuracy and achievability but overfitting and memorizing data noise often happen in previous researches on automatic digital modulation classifier. To solve this problem, we utilize two neural networks, namely MentorNet and StudentNet, to construct an automatic modulation classifier, which possesses great performance on the test set with −18–20 dB signal-to-noise ratio (SNR). The MentorNet supervises the training of StudentNet according to curriculum learning, and deals with the overfitting problem in StudentNet. The proposed classifier is verified in several test sets containing additive white Gaussian noise (AWGN), Rayleigh fading, carrier frequency offset and phase offset. Experimental results reveal that the overall accuracy of this classifier for common eleven modulation types was up to 99.3% while the inter-class accuracy could be up to 100%, which was much higher than many other classifiers. Besides, in the presence of interferences, the overall accuracy of this novel classifier still could reach 90% at 10 dB SNR indicting its excellent robustness, which makes it suitable for applications like military electronic warfare. Full article

The aim of this study was to predict chronic diseases in individual patients using a character-recurrent neural network (Char-RNN), which is a deep learning model that treats data in each class as a word when a large portion of its input values is missing. An advantage of Char-RNN is that it does not require any additional imputation method because it implicitly infers missing values considering the relationship with nearby data points. We applied Char-RNN to classify cases in the Korea National Health and Nutrition Examination Survey (KNHANES) VI as normal status and five chronic diseases: hypertension, stroke, angina pectoris, myocardial infarction, and diabetes mellitus. We also employed a multilayer perceptron network for the same task for comparison. The results show higher accuracy for Char-RNN than for the conventional multilayer perceptron model. Char-RNN showed remarkable performance in finding patients with hypertension and stroke. The present study utilized the KNHANES VI data to demonstrate a practical approach to predicting and managing chronic diseases with partially observed information. Full article

Black liquor, a valuable by-product of the pulp production process, is used for the recovery of chemicals and serves as an energy source for the pulp mill. Before entering the recovery unit, black liquor runs through several stages of evaporation, wherein the solids content (SC) can be used to control the evaporation effectiveness. In the current study, the time-domain nuclear magnetic resonance (TD-NMR) technique was applied to determine the SC of black liquor. The TD-NMR system was modified for flowing samples, so that the black liquor could be pumped through the system, followed by the measurement of the spin-spin relaxation rate, R₂. A temperature correction was also applied to reduce deviations in the R₂ caused by the sample temperature. The SC was calculated based on a linear model between the R₂ and the SC values determined gravimetrically, where good agreement was shown. The online TD-NMR system was tested at a pulp mill for the SC estimation of weak black liquor over seven days without any fouling, which demonstrated the feasibility of the method in a harsh industrial environment. Therefore, the potential of the TD-NMR technology as a technique for controlling the black liquor evaporation process was demonstrated. Full article

Based on the motion principle of bionic earthworms, we designed and fabricated a novel crawling robot driven by pneumatic power. Its structure is divided into four segments, and its motion process is periodic with high stability. Due to the pneumatic suction cups mounted on its feet, it is able to crawl on smooth horizontal, inclined, or vertical walls. On this basis, we designed a novel underactuated steering mechanism. Through the tendons on both sides and the springs installed on the side of the robot, we accurately controlled the steering motion of the robot. We analyzed the steering process in detail, calculated the influence of external parameters on the steering process of the robot, and simulated the trajectory of the robot in the steering process. The experimental results validated our analysis. In addition, we calculate the maximum thrust that each segment of the robot can provide, and determine the maximum load that the robot can bear during climbing motions. Full article

Sodium hydroxide-modified graphene oxide was used as manganese oxides support for the preparation of nanocomposites via a one-pot preparation route for the degradation of Reactive Black 5. The nanocomposites were characterized for their structure by X-ray diffraction, for their textural properties by Nitrogen adsorption, and for their surface chemistry by Fourier transform infrared spectroscopy, potentiometric titration, and thermal analysis measurements. The nanocomposites prepared showed to possess high activity for the degradation/oxidation of Reactive Black 5 at ambient conditions, without light irradiation, which was higher than that of the precursors manganese oxides and can be attributed to the synergistic effect of the manganese oxides and the modified graphene oxide. Full article

Many new consumer applications are based on the use of automatic speech recognition (ASR) systems, such as voice command interfaces, speech-to-text applications, and data entry processes. Although ASR systems have remarkably improved in recent decades, the speech recognition system performance still significantly degrades in the presence of noisy environments. Developing a robust ASR system that can work in real-world noise and other acoustic distorting conditions is an attractive research topic. Many advanced algorithms have been developed in the literature to deal with this problem; most of these algorithms are based on modeling the behavior of the human auditory system with perceived noisy speech. In this research, the power-normalized cepstral coefficient (PNCC) system is modified to increase robustness against the different types of environmental noises, where a new technique based on gammatone channel filtering combined with channel bias minimization is used to suppress the noise effects. The TIDIGITS database is utilized to evaluate the performance of the proposed system in comparison to the state-of-the-art techniques in the presence of additive white Gaussian noise (AWGN) and seven different types of environmental noises. In this research, one word is recognized from a set containing 11 possibilities only. The experimental results showed that the proposed method provides significant improvements in the recognition accuracy at low signal to noise ratios (SNR). In the case of subway noise at SNR = 5 dB, the proposed method outperforms the mel-frequency cepstral coefficient (MFCC) and relative spectral (RASTA)–perceptual linear predictive (PLP) methods by 55% and 47%, respectively. Moreover, the recognition rate of the proposed method is higher than the gammatone frequency cepstral coefficient (GFCC) and PNCC methods in the case of car noise. It is enhanced by 40% in comparison to the GFCC method at SNR 0dB, while it is improved by 20% in comparison to the PNCC method at SNR −5dB. Full article

Gymnema sylvestre is a plant that is enriched in bioactive compounds. In particular, gymnemic acids (GA) and phenolic compounds (PC) are pharmaceutically important. There is a commercial demand for naturally occurring bioactive compounds, but their availability is limited due to geographical and seasonal variations. The elicitation approach can enhance the biosynthesis of phytochemicals during in vitro culture of G. sylvestre. Here, to further improve gymnemic acid II (GA II) and phenolic compounds (PC) production by G. sylvestre, cell suspension cultures (CSC), which has attracted attention for the production of essential phytochemicals, was explored using copper oxide nanoparticles (CuO NPs). Callus was obtained on MS medium containing 2,4-dichlorophenoxyacetic acid, kinetin, phytoagar, and sucrose. Agar-free MS medium was used to initiate CSC, which was treated with three concentrations of CuO NPs (1, 3 or 5 mg/L). Treatment for 48 h with 3 mg/L CuO NPs resulted in the greatest yields of GA II, total phenolics, and flavonoids. The cultures also displayed pronounced antioxidant, antidiabetic, anti-inflammatory, antibacterial, antifungal, and anticancer activities. The use of CuO NPs (3 mg/L) significantly increased the production of GA II (nine-fold) and PC compared to unamended CSC. We propose that CSC and use of nanoparticles (NPs) as a new generation of elicitors, offer a suitable prospect for the production of bioactive compounds. Full article

An analysis is carried out to evaluate the effects of heat and mass transfer in an electro-osmotic flow of third order fluid via peristaltic pumping. Solutions are derived for small wave number and Peclet number. The emerging non-linear mathematical model is solved analytically and compared numerically by the built-in scheme of working software. The table is inserted for shear stress distribution and a graph for comparison of solution techniques and accuracy of obtained results. The effects of various parameters of interest on pumping, trapping, temperature, heat transfer coefficient, and concentration distribution have been studied graphically. Electro-osmotic exchange of energy and mass has a role in reservoir engineering, chemical industry, and in micro-fabrication technologies. Full article

In the present paper, the fatigue life assessment of notched structural components is performed by applying a critical plane-based multiaxial fatigue criterion. Such a criterion is formulated by using the control volume concept related to the strain energy density criterion. The verification point is assumed to be at a given distance from the notch tip. Such a distance is taken as a function of the control volume radii around the notch tip under both Mode I and Mode III loading. The accuracy of the present criterion is evaluated through experimental data available in the literature, concerning titanium alloy notched specimens under uniaxial and multiaxial fatigue loading. Full article

The dynamic response of a simply supported double-beam system under moving loads was studied. First, in order to reduce the difficulty of solving the equation, a finite sin-Fourier transform was used to transform the infinite-degree-of-freedom double-beam system into a superimposed two-degrees-of-freedom system. Second, Duhamel’s integral was used to obtain the analytical expression of Fourier amplitude spectrum function considering the initial conditions. Finally, based on finite sin-Fourier inverse transform, the analytical expression of dynamic response of a simply supported double-beam system under moving loads was deduced. The dynamic response under successive moving loads was calculated by the analytical method and the general FEM software ANSYS. The analysis results show that the analytical method calculation results are consistent with ANSYS’ calculation, thus validating the analytical calculation method. The simply supported double-beam system had multiple critical speeds, and the flexural rigidity significantly affected both peak vertical displacement and critical speed. Full article

Manifold learning is a powerful dimensionality reduction tool for a hyperspectral image (HSI) classification to relieve the curse of dimensionality and to reveal the intrinsic low-dimensional manifold. However, a specific characteristic of HSIs, i.e., irregular spatial dependency, is not taken into consideration in the method design, which can yield many spatially homogenous subregions in an HSI scence. Conventional manifold learning methods, such as a locality preserving projection (LPP), pursue a unified projection on the entire HSI, while neglecting the local homogeneities on the HSI manifold caused by those spatially homogenous subregions. In this work, we propose a novel multiscale superpixelwise LPP (MSuperLPP) for HSI classification to overcome the challenge. First, we partition an HSI into homogeneous subregions with a multiscale superpixel segmentation. Then, on each scale, subregion specific LPPs and the associated preliminary classifications are performed. Finally, we aggregate the classification results from all scales using a decision fusion strategy to achieve the final result. Experimental results on three real hyperspectral data sets validate the effectiveness of our method. Full article

Electrical stimulation is a promising therapeutic approach for the regeneration of large bone defects. Innovative electrically stimulating implants for critical size defects in the lower jaw are under development and need to be optimized in silico and tested in vivo prior to application. In this context, numerical modelling and simulation are useful tools in the design process. In this study, a numerical model of an electrically stimulated minipig mandible was established to find optimal stimulation parameters that allow for a maximum area of beneficially stimulated tissue. Finite-element simulations were performed to determine the stimulation impact of the proposed implant design and to optimize the electric field distribution resulting from sinusoidal low-frequency ( $f=20\mathrm{Hz}$ ) electric stimulation. Optimal stimulation parameters of the electrode length $h_{\mathrm{el}}=25\mathrm{m}\mathrm{m}$ and the stimulation potential ${\phi }_{\mathrm{stim}}=0.5\mathrm{V}$ were determined. These parameter sets shall be applied in future in vivo validation studies. Furthermore, our results suggest that changing tissue properties during the course of the healing process might make a feedback-controlled stimulation system necessary. Full article

In this paper, the energy method is employed to analytically investigate the influence of time delay in signal transmission on synchronization between two coupled FitzHugh-Nagumo (FHN) neurons. Unlike pre-existing methods that deal with synchronization problems, our major idea is to consider the change rate of the energy of the synchronization error system, since the original system’s synchronization is equivalent to the disappearance of the energy of the error system. In rewriting the original coupled system in the corresponding energy coordinates based on the energy method, we find that the change rate of energy of the error system can be divided into two parts (periodic and non-periodic). The synchronization criterion for the original system can then be obtained by letting the non-periodic part of the change rate of the energy be less than zero. The correctness of the analysis is illustrated with numerical simulations. Our analytical results show that time delay in signal transmission has very significant effects on the synchronization between two FHN neurons. If the time delay in signal transmission is not taken into account in the two coupled FHN neurons, synchronous spikes cannot be achieved in the system for any given coupling strength. By adjusting the value of the time delay in signal transmission, the neural system can freely switch between neural rest and synchronous spikes. This means that time delay in signal transmission is crucial for the occurrence of synchronous spikes in the FHN neural system, which contributes to our understanding of the interaction between neurons. We analytically show the influence of the time delay on the synchronization between two FHN neurons, which was seldom considered by other researchers. Full article

Continuous glucose monitoring (CGM) sensors have led a paradigm shift to painless, continuous, zero-finger pricking measurement in blood glucose monitoring. Recent electrochemical CGM sensors have reached two-week lifespans and no calibration with clinically acceptable accuracy. The system with the recent CGM sensors is identified as an “integrated glucose monitoring system,” which can replace finger-pricking glucose-testing for diabetes treatment decisions. Although such innovation has brought CGM technology closer to realizing the artificial pancreas, discomfort and infection problems have arisen from short lifespans and open wounds. A fully implantable sensor with a longer-term lifespan (90 days) is considered as an alternative CGM sensor with high comfort and low running cost. However, it still has barriers, including surgery for applying and replacing and frequent calibration. If technical refinement is conducted (e.g., stability and reproducibility of sensor fabrication), fully implantable, long-term CGM sensors can open the new era of continuous glucose monitoring. Full article

Laser welding presents a core position in the health sector. This process has had an outstanding impact on the surgical procedures from many medical areas, such as on vascular and nervous surgeries. The aim of the present research is to present an overview on the evolution of laser welding of vascular and nervous tissues. These surgeries present many advantages, such as an absence of foreign-body reactions and aneurysms and good tensile strengths. However, despite the sutureless nature of the process, complementary sutures have been applied to support the procedure success. An important concern in vascular and nervous laser welding is the thermal damage. The development of temperature-controlled feedback systems has reduced this concern with a very precise control of the laser parameters. The bonding strength of vascular and nerve laser welds can be enhanced with the application of solder solutions, bonding materials, and laser-activated dyes. Alternative techniques to laser welding, such as photochemical tissue bonding and electrosurgical high-frequency technologies, have also been tested for vascular and nervous repairs. Full article

Textile Reinforced Mortar (TRM) is a composite material that has already been successfully used as an externally bonded strengthening means of existing structures. The bond of TRM with various substrates is of crucial importance for determining the degree of exploitation of the textile. However, little is known on the effect of elevated/high temperatures on the TRM-to-substrate bond characteristics while relevant testing protocols are also lacking. This study focuses on the experimental assessment of the TRM-to-masonry bond after exposure of masonry wallettes unilaterally furnished with TRM strips at 120 °C and 200 °C for 1 h. The shear bond tests on cooled-down specimens were carried out using the single-lap/single-prism set-up. Two TRM systems were investigated sharing the same type of textile, which is a dry AR glass fiber one (either in a single-layer or in a double-layer configuration) and different matrices: one normal weight (TRNM) and another lightweight (TRLM) of equal compressive strengths. At control conditions (non-heated specimens) and after exposure at a nominal air temperature of 120 °C, both single-layer TRM systems exhibited similar bond capacities. After exposure at a nominal air temperature of 200 °C single-layer and double-layer TRNM overlays outperformed their TRLM counterparts. A critical discussion is based on phenomenological evidence and measured response values. Full article

The liquid phase of foam systems plays a major role in improving the fluidity of oil, by reducing oil viscosity and stripping oil from rock surfaces during foam-flooding processes. Improving the oil displacement capacity of the foam’s liquid phase could lead to significant improvement in foam-flooding effects. Oil-liquid interfacial tension (IFT) is an important indicator of the oil displacement capacity of a liquid. In this study, several surfactants were used as foaming agents, and polymers were used as foam stabilizers. Foaming was induced using a Waring blender stirring method. Foam with an oil-liquid IFT of less than 10–3 mN/m was prepared after a series of adjustments to the liquid composition. This study verified the possibility of a foam system with both an ultra-low oil-liquid IFT and high foaming properties. Our results provide insight into a means of optimizing foam fluids for enhanced oil recovery. Full article

In this study, we propose a new simple degree-of-freedom fluctuation model that accurately reproduces the probability density functions (PDFs) of human–bicycle balance motions as simply as possible. First, we measure the time series of the roll angular displacement and velocity of human–bicycle balance motions and construct their PDFs. Next, using these PDFs as training data, we identify the model parameters by means of particle swarm optimization; in particular, we minimize the Kolmogorov–Smirnov distance between the human PDFs from the participants and the PDFs simulated by our model. The resulting PDF fitnesses were over $98.7\%$ for all participants, indicating that our simulated PDFs were in close agreement with human PDFs. Furthermore, the Kolmogorov–Smirnov statistical hypothesis testing was applied to the resulting human–bicycle fluctuation model, showing that the measured time responses were much better supported by our model than the Gaussian distribution. Full article

The classification of marine vessels is one of the important problems of maritime traffic. To fully exploit the complementarity between different features and to more effectively identify marine vessels, a novel feature structure fusion method based on spectral regression discriminant analysis (SF-SRDA) was proposed. Firstly, we selected the different convolutional neural network features that better describe the characteristics of ships, and constructed the features based on graphs by the similarity metric. Then we weighed the concatenate multi-feature and fused their structures according to the linear relationship assumption. Finally, we constructed the optimization formula to solve the fusion features and structure by using spectral regression discriminant analyses. Experiments on the VAIS dataset show that the proposed SF-SRDA method can reduce the feature dimension from the original 102,400 dimensions to 5 dimensions, that the classification accuracy of visible images can reach 87.60%, and that that of the infrared image can reach 74.68% at daytime. The experimental results demonstrate that the proposed method can not only extract the optimal features from the original redundant feature space, but also greatly reduce the dimensions of the feature. Furthermore, the classification performance of SF-SRDA also gets a promising result. Full article

Filter-based spectral beam combining (FSBC) is a promising power-scaling concept for high-power, broad-linewidth fiber lasers, as it relaxes the requirements for linewidth control and also the sizes of the individual beams. As the combining element in the FSBC system, the steep-edge filter plays a major role in achievement of the combining efficiency and the beam quality. In this case, we combine the uncorrelated surface roughness model and the combining efficiency model, and we conduct a comprehensive analysis of the effects of surface roughness, thickness error, and incident angle on the filter’s optical properties and the combining efficiency, in order to determine the optimal configuration for the laser beam-combining system. The simulation results show a good agreement with the measured ones. Meanwhile, through the adoption of the angular spectrum theory, this paper has also conducted a preliminary analysis of the influence of the combining elements on the quality of the combined beam, and some theoretical instructions on the future design of the spectral beam-combining system are provided. Full article

The continuous decrease in the size of lithographic technology nodes has led to the development of source and mask optimization (SMO) and also to the control of defocus becoming stringent in the actual lithography process. Due to multi-factor impact, defocusing is always changeable and uncertain in the real exposure process. But conventional SMO assumes the lithography system is ideal, which only compensates the optical proximity effect (OPE) in the best focus plane. Therefore, to solve the inverse lithography problem with more uniformity of pattern in different defocus variations, we proposed a defocus robust SMO (DRSMO) approach that is driven by a defocus sensitivity penalty function for the first time. This multi-objective optimization samples a wide range of defocus disturbances and it can be proceeded by the mini-batch gradient descent (MBGD) algorithm effectively. The simulation results showed that a more robust defocus source and mask can be designed through DRSMO optimization. The defocus sensitivity factor s_β maximally decreased 63.5% compared to conventional SMO, and due to the low error sensitivity and the depth of defocus (DOF), the process window (PW) was further enlarged effectively. Compared to conventional SMO, the exposure latitude (EL) maximally increased from 4.5% to 10.5% and DOF maximally increased 54.5% (EL = 5%), which proved the validity of the DRSMO method in improving the focusing performance. Full article

A new configuration of a discharge chamber and power source for the treatment of up to 1 L of liquid is presented. A leakage transformer, energizing two metal electrodes positioned above the liquid, limits the discharge current inductively by utilizing the weak magnetic coupling between the primary and secondary coils. No additional means to avoid arcing (electric short-circuiting), e.g., dielectric barriers or resistors, are needed. By using this technique, exceeding the breakdown voltage leads to the formation of transient spark discharges, producing non-thermal plasma (NTP). These discharges effected significant changes in the properties of the treated liquids (distilled water, physiological saline solution, and tap water). Considerable concentrations of nitrite and nitrate were detected after the plasma treatment. Furthermore, all tested liquids gained strong antibacterial efficacy which was shown by inactivating suspended Escherichia coli and Staphylococcus aureus. Plasma-treated tap water had the strongest effect, which is shown for the first time. Additionally, the pH-value of tap water did not decrease during the plasma treatment, and its conductivity increased less than for the other tested liquids. Full article

Missing value imputation approaches have been widely used to support and maintain the quality of traffic data. Although the spatiotemporal dependency-based approaches can improve the imputation performance for large and continuous missing patterns, additionally considering traffic states can lead to more reliable results. In order to improve the imputation performances further, a section-based approach is also needed. This study proposes a novel approach for identifying traffic-states of different spots of road sections that comprise, namely, a section-based traffic state (SBTS), and determining their spatiotemporal dependencies customized for each SBTS, for missing value imputations. A principal component analysis (PCA) was employed, and angles obtained from the first principal component were used to identify the SBTSs. The pre-processing was combined with a support vector machine for developing the imputation model. It was found that the segmentation of the SBTS using the angles and considering the spatiotemporal dependency for each state by the proposed approach outperformed other existing models. Full article

Many medical imaging data, especially the magnetic resonance imaging (MRI) data, usually have a small sample size, but a large number of features. How to reduce effectively the data dimension and locate accurately the biomarkers from such kinds of data are quite crucial for diagnosis and further precision medicine. In this paper, we propose a hybrid feature selection method based on machine learning and traditional statistical approaches and explore the brain abnormalities of schizophrenia by using the functional and structural MRI data. The results show that the abnormal brain regions are mainly distributed in the supramarginal gyrus, cingulate gyrus, frontal gyrus, precuneus and caudate, and the abnormal functional connections are related to the caudate nucleus, insula and rolandic operculum. In addition, some complex network analyses based on graph theory are utilized on the functional connection data, and the results demonstrate that the located abnormal functional connections in brain can distinguish schizophrenia patients from healthy controls. The identified abnormalities in brain with schizophrenia by the proposed hybrid feature selection method show that there do exist some abnormal brain regions and abnormal disruption of the network segregation and network integration for schizophrenia, and these changes may lead to inaccurate and inefficient information processing and synthesis in the brain, which provide further evidence for the cognitive dysmetria of schizophrenia. Full article

In electricity markets, energy storage systems (ESSs) have been widely used to regulate frequency in power system operations. Frequency regulation (F/R) relates to the short-term reserve power used to balance the real-time mismatch of supply and demand. Every alternating current power system has its own unique standard frequency level, and frequency variation occurs whenever there is a mismatch of supply and demand. To cope with frequency variation, generating units—particularly base-loader generators—reduce their power outputs to a certain level, and the reduced generation outputs are used as a generation reserve whenever frequency variation occurs in the power systems. ESSs have recently been implemented as an innovative means of providing the F/R reserve previously provided by base-loader generators, because they are much faster in responding to frequency variation than conventional generators. We assess the economic benefits of ESSs for F/R, based on a new forecast of long-term electricity market price and real power system operation characteristics. For this purpose, we present case studies with respect to the South Korean electricity market as well as simulation results featuring key variables, along with their implications vis-à-vis electricity market operations. Full article

Transmission error is the key index for characterizing the transmission precision of precision reducers, and its accurate measurement is significant for the precision evaluation of precision reducers. Transmission error is generally measured under the conditions of zero-load and low speed. However, low speed is a general concept and there is no general standard of measurement speed or solid scientific basis. Therefore, it is difficult to obtain consistent transmission precision evaluation results for the same precision reducer. The concept of optimal measurement speed in the transmission precision evaluation of precision reducers was put forward in order to reduce the influence of measurement speed. The determination method of optimal measurement speed was proposed and the calculation model of the optimal measurement speed was established, according to the Stribeck friction model of precision reducers. Taking a certain type of RV reducer as an example, the transmission error measurement experiments were carried out under different speeds. The friction torque of the RV reducer and the peak-to-peak value of the measured transmission error were the least under the optimal measurement speed. The influence of speed on the measurement results can be effectively reduced. The determination of optimal measurement speed of transmission errors could improve the measurement precision of the transmission errors for the objective evaluation of transmission precision of precision reducers. Full article

This paper presents a static unitary detector (STUD)-based laser detection and ranging (LADAR) sensor with a 16-to-1 transimpedance-combining amplifier for high spatial resolution three-dimensional (3-D) applications. In order to readout the large size of a photodetector for better results of 3-D information without any reduction of the bandwidth, the partitioning photosensitive cell method is embedded in a 16-to-1 transimpedance-combining amplifier. The effective number of partitioning photosensitive cells and signal-combining stages are selected based on the analysis of the partitioning photosensitive cell method for the optimum performance of a transimpedance-combining amplifier. A prototype chip is fabricated in a 0.18-μm CMOS technology. The input referred noise is 41.9 pA/√Hz with a bandwidth of 230 MHz and a transimpedance gain of 70.4 dB·Ω. The total power consumption of the prototype chip is approximately 86 mW from a 1.8-V supply, and the TICA consumes approximately 15.4 mW of it. Full article

The Spirulina maxima exact from a non-thermal ultrasonic process (UE) contains 17.5 mg/g of total chlorophyll, compared to 6.24 mg/g of chlorophyll derived from the conventional 70% ethanol extraction at 80 °C for 12 h (EE). The UE also showed relatively low cytotoxicity against murine microglial cells (BV-2) and inhibited the production of the inflammatory mediators, NO and PGE₂. The UE also effectively suppresses both mRNA expression and the production of pro-inflammatory cytokines, such as TNF-α, IL-6 and IL-1β, in a concentration-dependent manner. Notably, TNF-α gene and protein production were most strongly down-regulated, while IL-6 was the least affected by all ranges of treatment concentrations. This work first demonstrated a quantitative correlation between mRNA expression and the production of cytokines, showing that suppression of TNF-α gene expression was most significantly correlated with its secretion. These results clearly proved that the anti-inflammatory effects of Spirulina extract from a nonthermal ultrasonic process, which yielded high concentrations of intact forms of chlorophylls, were increased two-fold compared to those of conventional extracts processed at high temperature. Full article

The aim of the study was to determine the still not completely described microbiome associated with the aquatic fern Azolla filiculoides. During the experiment, 58 microbial isolates (43 epiphytes and 15 endophytes) with different morphologies were obtained. We successfully identified 85% of microorganisms and assigned them to 9 bacterial genera: Achromobacter, Bacillus, Microbacterium, Delftia, Agrobacterium, and Alcaligenes (epiphytes) as well as Bacillus, Staphylococcus, Micrococcus, and Acinetobacter (endophytes). We also studied an A. filiculoides cyanobiont originally classified as Anabaena azollae; however, the analysis of its morphological traits suggests that this should be renamed as Trichormus azollae. Finally, the potential of the representatives of the identified microbial genera to synthesize plant growth-promoting substances such as indole-3-acetic acid (IAA), cellulase and protease enzymes, siderophores and phosphorus (P) and their potential of utilization thereof were checked. Delftia sp. AzoEpi7 was the only one from all the identified genera exhibiting the ability to synthesize all the studied growth promoters; thus, it was recommended as the most beneficial bacteria in the studied microbiome. The other three potentially advantageous isolates (Micrococcus sp. AzoEndo14, Agrobacterium sp. AzoEpi25 and Bacillus sp. AzoEndo3) displayed 5 parameters: IAA (excluding Bacillus sp. AzoEndo3), cellulase, protease, siderophores (excluding Micrococcus sp. AzoEndo14), as well as mineralization and solubilization of P (excluding Agrobacterium sp. AzoEpi25). Full article