Life cycle assessment (LCA) of electrically-enhanced POME filtration: Environmental impacts of conductive-membrane formulation and process operating parameters.

This study assessed the environmental impacts of the formulation of graphene oxide (GO)/multi-walled carbon nanotubes (MWCNTs) conductive membranes and of the process operating parameters of electrically-enhanced palm oil mill effluent (POME) filtration. Two different analyses approaches were employed, cradle-to-gate approach for conductive membrane production and gate-to-gate approach for the POME filtration process. The parameters in conductive-membrane formulation (e.g. the weight ratio of carbon nanomaterials, and concentration of GO/MWCNT nanohybrids) and process operating parameters (e.g. electric field strength and electricity operating mode) were investigated. The findings herein are twofold. Firstly, for the fabrication of GO/MWCNT conductive membranes, the best weight ratio of GO:MWCNTs was found to be 1:9, given its superior membrane electrical conductivity with lower environmental impacts by 8.51% compared to pristine MWCNTs. The most suitable concentration of carbon nanomaterials was found to be 5 wt%, given its lowest impacts on resource depletion, human health, and ecosystems. Secondly, for the electrically-enhanced POME filtration, the optimum process operating parameters were found to be the application of an electric field of 300 V/cm in the continuous mode, given its lower environmental impacts (22.99%-89.30%) secondary to its requirement of the least electricity to produce permeate. The present study has established not only the optimized conditions in membrane formulation but also the operating parameters of electrically-enhanced filtration; such findings enable the use of cleaner production and sustainable approach to minimize fouling for industrial applications, whilst maintaining excellent efficiency.

Cultivation of Chlorella vulgaris in Column Photobioreactor for Biomass Production and Lipid Accumulation.

Microalgae have been used as energy resources in recent decades to mitigate the global energy crisis. As the demand for pure microalgae strains for commercial use increases, designing an effective photobioreactor (PBR) for mass cultivation is important. Chlorella vulgaris, a local freshwater microalga, was used to study the algal biomass cultivation and lipid production using various PBR configurations (bubbling, air-lift, porous air-lift). The results show that a bubbling column design is a better choice for the cultivation of Chlorella vulgaris than an air-lift one. The highest biomass concentration in the bubbling PBR was 0.78 g/L while the air-lift PBR had a value of 0.09 g/L. Key operating parameters, including draft-tube length and bubbling flowrate, were then optimized based on biomass production and lipid yield. The highest lipid content was in the porous air-lift PBR and the air-lift PBR with shorter draft tube (35 cm) was also better than a longer one (50 cm) for algal cultivation, but the microalgae attachment on the inner tube of PBR always occurred. The highest biomass concentration could be produced under the highest gas flowrate of 2.7 L/min, whereas the lowest dry cell mass was under the lowest gas flowrate of 0.2 L/min.

Scenedesmus quadricauda for Nutrient Removal and Lipid Production in Wastewater.

Scenedesmus quadricauda, a local freshwater microalga, was used to treat primary settled and filtrate wastewater and to produce algal lipid. For the primary settled wastewater, the maximum biomass concentrations of acclimated and unacclimated microalgae were 0.995 g/L and 0.940 g/L, respectively. Over 90% orthophosphate and 95% ammonia nitrogen in the acclimated and unacclimated cultures, respectively, were removed after five days. The lipid contents of the microalgae were higher than 13% in all cultures. The highest growth rate occurred in the 25% filtrate culture. Over 80% phosphate was removed under the 25% and 50% filtrate cultures within six days, while over 90% ammonia nitrogen was removed within five days under both conditions. The lipid content was the highest (18.1%) under the 50% filtrate condition. C16:0, C18:2n6, and C18:3n3 were dominant fatty acids. In conclusion, S. quadricauda is a viable candidate for wastewater treatment and lipid production.

Robust Ellipse Fitting Based on Maximum Correntropy Criterion With Variable Center.

The presence of radically irregular data points (RIDPs), which are referred to as the subset of measurements that represents no or little information, can significantly degrade the performance of ellipse fitting methods. We develop an ellipse fitting method that is robust to RIDPs based on the maximum correntropy criterion with variable center (MCC-VC), where an adaptable Laplacian kernel is used. For single ellipse fitting, we formulate a non-convex optimization problem and divide it into two subproblems, one to estimate the kernel bandwidth and the other the kernel center. We design sufficiently accurate convex approximation to each subproblem that will lead to computationally efficient closed-form solutions. The two subproblems are solved in an alternate manner until convergence is reached. We also investigate coupled ellipses fitting. While there exist multiple ellipses fitting methods in the literature, we develop a coupled ellipses fitting method by exploiting the underlying special structure, where the associations between the data points and ellipses are absent in the problem. The proposed method first introduces an association vector for each data point and then formulates a non-convex mixed-integer optimization problem to establish the data associations, which is approximately solved by relaxing it into a second-order cone program. Using the estimated data associations, we then extend the proposed single ellipse fitting method to accomplish the final coupled ellipses fitting. The proposed method is shown to perform significantly better than the existing methods using both simulated data and real images.

Approaches to characterizing oscillatory burst detection algorithms for electrophysiological recordings.

BACKGROUND: Cognitive processes are associated with fast oscillations of the local field potential and electroencephalogram. There is a growing interest in targeting them because these are disrupted by aging and disease. This has proven challenging because they often occur as short-lasting bursts. Moreover, they are obscured by broad-band aperiodic activity reflecting other neural processes. These attributes have made it exceedingly difficult to develop analytical tools for estimating the reliability of detection methods. NEW METHOD: To address this challenge, we developed an open-source toolkit with four processing steps, that can be tailored to specific brain states and individuals. First, the power spectrum is decomposed into periodic and aperiodic components, each of whose properties are estimated. Second, the properties of the transient oscillatory bursts that contribute to the periodic component are derived and optimized to account for contamination from the aperiodic component. Third, using the burst properties and aperiodic power spectrum, surrogate neural signals are synthesized that match the observed signal's spectrotemporal properties. Lastly, oscillatory burst detection algorithms run on the surrogate signals are subjected to a receiver operating characteristic analysis, providing insight into their performance. RESULTS: The characterization algorithm extracted features of oscillatory bursts across multiple frequency bands and brain regions, allowing for recording-specific evaluation of detection performance. For our dataset, the optimal detection threshold for gamma bursts was found to be lower than the one commonly used. COMPARISON WITH EXISTING METHODS: Existing methods characterize the power spectrum, while ours evaluates the detection of oscillatory bursts. CONCLUSIONS: This pipeline facilitates the evaluation of thresholds for detection algorithms from individual recordings.

Robust Ellipse Fitting With Laplacian Kernel Based Maximum Correntropy Criterion.

The performance of ellipse fitting may significantly degrade in the presence of outliers, which can be caused by occlusion of the object, mirror reflection or other objects in the process of edge detection. In this paper, we propose an ellipse fitting method that is robust against the outliers, and thus maintaining stable performance when outliers can be present. We formulate an optimization problem for ellipse fitting based on the maximum entropy criterion (MCC), having the Laplacian as the kernel function from the well-known fact that the l1 -norm error measure is robust to outliers. The optimization problem is highly nonlinear and non-convex, and thus is very difficult to solve. To handle this difficulty, we divide it into two subproblems and solve the two subproblems in an alternate manner through iterations. The first subproblem has a closed-form solution and the second one is cast as a convex second-order cone program (SOCP) that can reach the global solution. By so doing, the alternate iterations always converge to an optimal solution, although it can be local instead of global. Furthermore, we propose a procedure to identify failed fitting of the algorithm caused by local convergence to a wrong solution, and thus, it reduces the probability of fitting failure by restarting the algorithm at a different initialization. The proposed robust ellipse fitting method is next extended to the coupled ellipses fitting problem. Both simulated and real data verify the superior performance of the proposed ellipse fitting method over the existing methods.

Non-Invasive Heart Rate Estimation From Ballistocardiograms Using Bidirectional LSTM Regression.

Non-invasive heart rate estimation is of great importance in daily monitoring of cardiovascular diseases. In this paper, a bidirectional long short term memory (bi-LSTM) regression network is developed for non-invasive heart rate estimation from the ballistocardiograms (BCG) signals. The proposed deep regression model provides an effective solution to the existing challenges in BCG heart rate estimation, such as the mismatch between the BCG signals and ground-truth reference, multi-sensor fusion and effective time series feature learning. Allowing label uncertainty in the estimation can reduce the manual cost of data annotation while further improving the heart rate estimation performance. Compared with the state-of-the-art BCG heart rate estimation methods, the strong fitting and generalization ability of the proposed deep regression model maintains better robustness to noise (e.g., sensor noise) and perturbations (e.g., body movements) in the BCG signals and provides a more reliable solution for long term heart rate monitoring.

Classification of Brainwaves Using Convolutional Neural Network.

Classification of brainwaves in recordings is of considerable interest to neuroscience and medical communities. Classification techniques used presently depend on the extraction of low-level features from the recordings, which in turn affects the classification performance. To alleviate this problem, this paper proposes an end-to-end approach using Convolutional Neural Network (CNN) which has been shown to detect complex patterns in a signal by exploiting its spatiotemporal nature. The present study uses time and frequency axes for the classification using synthesized Local Field Potential (LFP) data. The results are analyzed and compared with the FFT technique. In all the results, the CNN outperforms the FFT by a significant margin especially when the noise level is high. This study also sheds light on certain signal characteristics affecting network performance.

Monitoring the Relative Blood Pressure Using a Hydraulic Bed Sensor System.

We propose a nonwearable hydraulic bed sensor system that is placed underneath the mattress to estimate the relative systolic blood pressure of a subject, which only differs from the actual blood pressure by a scaling and an offset factor. Two types of features are proposed to obtain the relative blood pressure, one based on the strength and the other on the morphology of the bed sensor ballistocardiogram pulses. The relative blood pressure is related to the actual by a scale and an offset factor that can be obtained through calibration. The proposed system is able to extract the relative blood pressure more accurately with a less sophisticated sensor system compared to those from the literature. We tested the system using a dataset collected from 48 subjects right after active exercises. Comparison with the ground truth obtained from the blood pressure cuff validates the promising performance of the proposed system, where the mean correlation between the estimate and the ground truth is near to 90% for the strength feature and 83% for the morphology feature.

Prognostic factors and adjuvant therapy in uterine carcinosarcoma.

PURPOSE OF INVESTIGATION: The objective of this retrospective study was to investigate prognostic variables and impact of adjuvant therapy in uterine carcinosarcoma. METHODS: The clinical information and pathological confirmation were reviewed for cases with uterine carcinosarcoma from 1984 to 2005. A total of 45 patients were eligible for analysis. RESULTS: The median follow-up for survivors was 84 months. Five-year overall survival and progression-free survival (PFS) rates were 36.5% and 33.8%, respectively for Stage I-IV. Distant site metastasis with/without pelvic failure occurred in 83.3% of those with recurrence/progression. By multivariate analysis, older age (p = 0.001) and more than half of myometrial invasion (p = 0.002) were significant predictors of death, while only myometrial invasion (p = 0.022) was significantly associated with PFS. Stratified analyses demonstrated a monotonic trend of chemotherapy or chemoradiation to decrease death. CONCLUSIONS: Our results suggested that age and depth of myometrial invasion were significant prognostic factors, and chemotherapy or chemoradiation seemed to be beneficial for uterine carcinosarcoma.

Multiple Instance Dictionary Learning for Beat-to-Beat Heart Rate Monitoring From Ballistocardiograms.

A multiple instance dictionary learning approach, dictionary learning using functions of multiple instances (DL-FUMI), is used to perform beat-to-beat heart rate estimation and to characterize heartbeat signatures from ballistocardiogram (BCG) signals collected with a hydraulic bed sensor. DL-FUMI estimates a "heartbeat concept" that represents an individual's personal ballistocardiogram heartbeat pattern. DL-FUMI formulates heartbeat detection and heartbeat characterization as a multiple instance learning problem to address the uncertainty inherent in aligning BCG signals with ground truth during training. Experimental results show that the estimated heartbeat concept obtained by DL-FUMI is an effective heartbeat prototype and achieves superior performance over comparison algorithms.

Spatial correlation coefficient images for ultrasonic detection.

In ultrasonics, image formation and detection are generally based on signal amplitude. In this paper, we introduce correlation coefficient images as a signal-amplitude independent approach for image formation. The correlation coefficients are calculated between A-scans digitized at adjacent measurement positions. In these images, defects are revealed as regions of high or low correlation relative to the background correlations associated with noise. Correlation coefficient and C-scan images are shown to demonstrate flat-bottom-hole detection in a stainless steel annular ring and crack detection in an aluminum aircraft structure.

Peritoneal metastasis in primary cervical cancer: a case report.

PURPOSE OF INVESTIGATION: Peritoneal metastasis presenting at initial diagnosis of squamous carcinoma of the uterine cervix is extremely rare. However, one such case was treated successfully with curative treatment. CASE: A 43-year-old woman presented with FIGO Stage IVA cervical carcinoma and underwent concurrent chemoradiation (CCRT) with weekly cisplatin. During CCRT, she suffered from acute lower abdominal pain, high fever, and leukocytosis. Computed tomography (CT) favored a tubo-ovarian abscess, while [18F] fluorodeoxyglucose positron emission tomography (FDG-PET) showed a lesion midway between the umbilicus and symphysis pubis. An exploration by laparoscopy, an omental metastasis adhering to the bladder dome was excised. This patient finished CCRT encompassing the disease extent including the trochar sites and no evidence of disease was noted 50 months after initial diagnosis. CONCLUSION: Though peritoneal metastasis above the pelvis seems ominous, curative treatment may still be viable in selected patients, even in surgical Stage IVB.

Supraclavicular lymph node metastases in cervical cancer.

PURPOSE OF INVESTIGATION: To evaluate the outcome and prognostic factors of patients with supraclavicular lymph node (SCLN) involvement at primary diagnosis. METHODS: We reviewed the medical records of cervical cancer patients primarily treated at Chang Gung Memorial Hospital between 1987 and 2005. Thirty-three patients with histologically confirmed SCLN metastasis at primary diagnosis were eligible for analysis. Clinical and pathological features were analyzed for association with outcome. RESULTS: The 3- and 5-year survival rates of patients with SCLN metastasis were 16.5% and 16.5%, respectively. Multivariate analysis showed the serum level of squamous cell carcinoma antigen (SCC-Ag) < 15 ng/ml at initial diagnosis (p = 0.021) and staging/restaging including [18F] fluoro-2-deoxy-D-glucose positron emission tomography (FDG-PET) (p = 0.006) to be associated with a better prognosis. CONCLUSION: Primary SCLN metastasis in cervical cancer is not incurable. The benefit from PET findings might help in selecting appropriate patients for curative primary and/or salvage treatment.

Maximization of cell growth and lipid production of freshwater microalga Chlorella vulgaris by enrichment technique for biodiesel production.

Chlorella vulgaris was cultivated under limitation and starvation and under controlled conditions using different concentrations of nitrate (NaNO3) and phosphate (K2HPO4 and KH2PO4) chemicals in modified Bold basal medium (BBM). The biomass and lipid production responses to different media were examined in terms of optical density, cell density, dry biomass, and lipid productivity. In the 12-day batch culture period, the highest biomass productivity obtained was 72.083 mg L-1 day-1 under BBM - NcontrolPlimited condition. The highest lipid content, lipid concentration, and lipid productivity obtained were 53.202 %, 287.291 mg/L, and 23.449 mg L-1 day-1 under BBM - NControlPDeprivation condition, respectively. Nitrogen had a major effect in the biomass concentration of C. vulgaris, while no significant effect was found for phosphorus. Nitrogen and phosphorus starvation was found to be the strategy affecting the lipid accumulation and affected the lipid composition of C. vulgaris cultures.

Enhancement of Chlorella vulgaris harvesting via the electro-coagulation-flotation (ECF) method.

This article explores the potential of using an electro-coagulation-flotation (ECF) harvester to allow flotation of microalgae cells for surface harvesting. A response surface methodology (RSM) model was used to optimize ECF harvesting by adjusting electrode plate material, electrode plate number, charge of the electrodes, electrolyte concentration, and pH value of the culture solution. The result revealed that three aluminum electrode plates (one anode and two cathodes), brine solution (8 g/L), and acidity (pH = 4) of culture solution (optimized ECF harvester) The highest flocculant concentration was measured at 2966 mg/L after 60 min and showed a 79.8 % increase of flocculation concentration. Such results can provide a basis for designing a large-scale microalgae harvester for commercial use in the future.

Modification of membrane function, protein synthesis, and heat killing effect in cultured Chinese hamster cells by glycerol and D2O1.

Glycerol and D2O can provide a protective effect to Chinese hamster V79 cells receiving heat treatment. The mechanism for this effect is assumed to be the ability of these agents to stabilize proteins which implies that one of the possible heat-killing mechanisms is the inactivation of a heat-sensitive molecule (protein?). In addition, we observed that heat can alter the membrane permeability rapidly, and glycerol can reduce the initial heat-induced membrane permeability changes (determined by aminoisobutyric acid uptake). Although not as effective as cycloheximide, glycerol and D2O can retard protein synthesis. These two processes can add to the protective effect of stabilizing cellular protein against heat killing. Since glycerol and D2O added during the heat-conditioning period can interfere with the appearance of thermotolerance, the mechanisms for the protective effect of glycerol and D2O are likely to be different from heat-induced thermotolerance. We propose that the heat-sensitive molecule protected by D2O or glycerol may also play a role in the triggering process of the thermotolerance phenomenon. If the conditioning heat treatment is sufficient to affect this molecule but not other cellular targets, thus allowing the cell to survive, thermotolerance may be observed in surviving cells in response to second or continued heat treatment. Depending on the severity of the heat effect, this heat-sensitive molecule may continue to exist after a conditioning heat treatment in medium containing glycerol or D2O, and therefore, the response of the cells to the challenging heat is altered little. This proposed mechanism is capable of explaining several thermotolerance experimental protocols. Since glycerol can also reduce the toxicity of vincristine, microtubule-related protein is probably one of the proteins stabilized by this agent. D2O also probably affects microtubule protein, because the cells heated in medium containing D2O show little topological changes.

Testing non-wearable fall detection methods in the homes of older adults.

In this paper, we describe two longitudinal studies in which fall detection sensor technology was tested in the homes of older adults. The first study tested Doppler radar, a two-webcam system, and a depth camera system in ten apartments for two years. This continuous data collection allowed us to investigate the real-world setting of target users and compare the advantages and limitations of each sensor modality. Based on this study, the depth camera was chosen for a current ongoing study in which depth camera systems have been installed in 94 additional older adult apartments. We include a discussion of the different sensor systems, the pros and cons of each, and results of the fall detection and false alarms in the older adult homes.

Nucleotide sequence of two 3'-termini of rRNA in the sea urchin Lytechinus variegatus.

The 3'-terminus of 26 S rRNA from the sea urchin Lytechinus variegatus has been determined by oligonucleotide fingerprinting, S1 nuclease mapping and terminal nucleotide analysis. There are two species of 26 S rRNA of approximately equal abundance, one 19 nucleotides longer than than other.

An ovary in luteal phase mimicking common iliac lymph node metastasis from a primary cutaneous peripheral primitive neuroectodermal tumour as revealed by 18-fluoro-2-deoxyglucose positron emission tomography.

A 30-year-old female underwent surgical removal of a primary cutaneous peripheral primitive neuroectodermal tumour (PNET) of the left thigh. A subsequent 18-fluoro-2-deoxyglucose (FDG) positron emission tomography (PET) scan showed abnormal accumulation of FDG in the left upper pelvic region, consistent with metastasis to a left common iliac node. A series of follow-up imaging studies revealed that a cyst of the corpus luteum of ovary was responsible for the abnormal FDG accumulation.