Stress Estimation Using Digital Image Correlation with Compensation of Camera Motion-Induced Error.

Measurement of stress levels from an in-service structure can provide important and useful information regarding the current state of a structure. The stress relaxation method (SRM) is the most conventional and practical method, which has been widely accepted for measuring residual stresses in metallic materials. The SRM showed strong potential for stress estimation of civil engineering structures, when combined with digital image correlation (DIC). However, the SRM/DIC methods studied thus far have practical issues regarding camera vibration during hole drilling. To minimize the error induced by the camera motion, the imaging system is installed at a distance from the specimen resulting in the low pixel density and the large extent of the inflicted damage. This study proposes an SRM/DIC-based stress estimation method that allows the camera to be removed during hole drilling and relocated to take the after-drilling image. Since the imaging system can be placed as close to the specimen as possible, a high pixel density can be achieved such that subtle displacement perturbation introduced by a small damage can be acquired by DIC. This study provides a detailed mathematical formulation for removing the camera relocation-induced false displacement field in the DIC result. The proposed method is validated numerically and experimentally.

Bayesian Prediction of Pre-Stressed Concrete Bridge Deflection Using Finite Element Analysis.

Vertical deflection has been emphasized as an important safety indicator in the management of railway bridges. Therefore, various standards and studies have suggested physics-based models for predicting the time-dependent deflection of railway bridges. However, these approaches may be limited by model errors caused by uncertainties in various factors, such as material properties, creep coefficient, and temperature. This study proposes a new Bayesian method that employs both a finite element model and actual measurement data. To overcome the limitations of an imperfect finite element model and a shortage of data, Gaussian process regression is introduced and modified to consider both, the finite element analysis results and actual measurement data. In addition, the probabilistic prediction model can be updated whenever additional measurement data is available. In this manner, a probabilistic prediction model, that is customized to a target bridge, can be obtained. The proposed method is applied to a pre-stressed concrete railway bridge in the construction stage in the Republic of Korea, as an example of a bridge for which accurate time-dependent deflection is difficult to predict, and measurement data are insufficient. Probabilistic prediction models are successfully derived by applying the proposed method, and the corresponding prediction results agree with the actual measurements, even though the bridge experienced large downward deflections during the construction stage. In addition, the practical uses of the prediction models are discussed.

Uniaxial Static Stress Estimation for Concrete Structures Using Digital Image Correlation.

This paper proposes a static stress estimation method for concrete structures, using the stress relaxation method (SRM) in conjunction with digital image correlation (DIC). The proposed method initially requires a small hole to be drilled in the concrete surface to induce stress relaxation around the hole and, consequently, a displacement field. DIC measures this displacement field by comparing digital images taken before and after the hole-drilling. The stress level in the concrete structure is then determined by solving an optimization problem, designed to minimize the difference between the displacement fields from DIC and the one from a numerical model. Compared to the pointwise measurements by strain gauges, the full-field displacement obtained by DIC provides a larger amount of data, leading to a more accurate estimation. Our theoretical results were experimentally validated using concrete specimens, demonstrating the efficacy of the proposed method.

Effect of Statins on Survival Following Stroke in Patients With Cancer.

The objective of this study was to investigate the potential benefits of statin therapy initiation in acute stroke in patients with active cancer. This study was conducted in two parts. First, data from patients who are presented with stroke and active cancer were obtained from prospectively collected multicenter hospital-based stroke registries. Patients were classified into statin user and non-user groups; the statin group was further divided into low-potency and high-potency statin subgroups. The primary outcome was time to mortality. Second, we obtained data from the Korean National Health Information Service-National Sample Cohort (NHIS-NSC) database for external validation and analyzed the effect of statins on mortality, taking compliance into consideration. For the stroke registry cohort, statin use was independently associated with reduced mortality in a multivariable model [hazard ratio (HR) = 0.675, 95% confidence interval (CI) = 0.457-0.996]. There was no interaction between statin use and cancer characteristics, vascular risk factors, or laboratory findings. A dose-dependent relationship between statin use and survival was also demonstrated. Analysis of the NHIS-NSC database found a similar association between statin therapy and reduced mortality (adjusted HR = 0.64, 95% CI = 0.45-0.90) and this effect persisted even after controlling for the adherence of statin use (HR = 0.60, 95% CI = 0.41-0.89). Statin therapy could be associated with reduced mortality in patients with acute stroke and active cancer.

Computer Vision-Based Structural Displacement Measurement Robust to Light-Induced Image Degradation for In-Service Bridges.

The displacement responses of a civil engineering structure can provide important information regarding structural behaviors that help in assessing safety and serviceability. A displacement measurement using conventional devices, such as the linear variable differential transformer (LVDT), is challenging owing to issues related to inconvenient sensor installation that often requires additional temporary structures. A promising alternative is offered by computer vision, which typically provides a low-cost and non-contact displacement measurement that converts the movement of an object, mostly an attached marker, in the captured images into structural displacement. However, there is limited research on addressing light-induced measurement error caused by the inevitable sunlight in field-testing conditions. This study presents a computer vision-based displacement measurement approach tailored to a field-testing environment with enhanced robustness to strong sunlight. An image-processing algorithm with an adaptive region-of-interest (ROI) is proposed to reliably determine a marker's location even when the marker is indistinct due to unfavorable light. The performance of the proposed system is experimentally validated in both laboratory-scale and field experiments.

Concrete Crack Identification Using a UAV Incorporating Hybrid Image Processing.

Crack assessment is an essential process in the maintenance of concrete structures. In general, concrete cracks are inspected by manual visual observation of the surface, which is intrinsically subjective as it depends on the experience of inspectors. Further, it is time-consuming, expensive, and often unsafe when inaccessible structural members are to be assessed. Unmanned aerial vehicle (UAV) technologies combined with digital image processing have recently been applied to crack assessment to overcome the drawbacks of manual visual inspection. However, identification of crack information in terms of width and length has not been fully explored in the UAV-based applications, because of the absence of distance measurement and tailored image processing. This paper presents a crack identification strategy that combines hybrid image processing with UAV technology. Equipped with a camera, an ultrasonic displacement sensor, and a WiFi module, the system provides the image of cracks and the associated working distance from a target structure on demand. The obtained information is subsequently processed by hybrid image binarization to estimate the crack width accurately while minimizing the loss of the crack length information. The proposed system has shown to successfully measure cracks thicker than 0.1 mm with the maximum length estimation error of 7.3%.

Zwitterionic surface coating of quantum dots reduces protein adsorption and cellular uptake.

We have studied the effect of the zwitterionic surface coating of quantum dots (QDs) on their interaction with a serum supplemented cell medium and their internalization by human cervical carcinoma (HeLa) cells. Zwitterionic QDs showed negligible adsorption of human serum albumin (HSA) selected as a model serum protein, in contrast to similar but negatively charged QDs. The incorporation of zwitterionic QDs by HeLa cells was found to be lower than for negatively charged QDs and for positively charged QDs, for which the uptake yield was largest. Our results suggest that the suppression of protein adsorption, here accomplished by zwitterionic QD surfaces, offers a strategy that allows for reducing the cellular uptake of nanoparticles.

Quantum Dots in an Amphiphilic Polyethyleneimine Derivative Platform for Cellular Labeling, Targeting, Gene Delivery, and Ratiometric Oxygen Sensing.

Amphiphilic polyethyleneimine derivatives (amPEIs) were synthesized and used to encapsulate dozens of quantum dots (QDs). The QD-amPEI composite was ∼100 nm in hydrodynamic diameter and had the slightly positive outer surface that suited well for cellular internalization. The QD-amPEI showed very efficient QD cellular labeling with the labeled cell fluorescence intensity more than 10 times higher than conventional techniques such as Lipofectamine-assisted QD delivery. QD-amPEI was optimal for maximal intracellular QD delivery by the large QD payload and the rapid endocytosis kinetics. QD-amPEI platform technology was demonstrated for gene delivery, cell-specific labeling, and ratiometric oxygen sensing. Our QD-amPEI platform has two partitions: positive outer surface and hydrophobic inside pocket. The outer positive surface was further exploited for gene delivery and targeting. Co-delivery of QDs and GFP silencing RNAs was successfully demonstrated by assembling siRNAs to the outer surfaces, which showed the transfection efficiency an order of magnitude higher than conventional gene transfections. Hyaluronic acids were tethered onto the QD-amPEI for cell-specific targeted labeling which showed the specific-to-nonspecific signal ratio over 100. The inside hydrophobic compartment was further applied for cohosting oxygen sensing phosphorescence Ru dyes along with QDs. The QD-Ru-amPEI oxygen probe showed accurate and reversible oxygen sensing capability by the ratiometric photoluminescence signals, which was successfully applied to cellular and spheroid models.

Benign childhood epilepsy with centrotemporal spikes: to treat or not to treat.

BACKGROUND AND PURPOSE: The aim of this study was to evaluate the benefits and risks of oxcarbazepine (OXC) monotherapy in children with newly diagnosed, benign partial epilepsy based on clinico-electrical and neuropsychological evaluation over time. METHODS: The study was open label, prospective, multicenter based. A total of 39 children with BRE were involved in the study. They were randomized into two groups (T; treatment with OXC, NT; No treatment) to compare the effectiveness of OXC treatment. All children underwent EEGs with quantification and a comprehensive battery of neuropsychological tests at the first visit and follow up visit at 6 months. RESULTS: The subjects made a slight progress in general intelligence measures over time in both groups (95.4±10.5 to 97.6±7.5 for T, 107.6±17.3 to 111.4±18.6 for NT). Memory and frontal executive functions did not change over time in both groups in terms of the memory quotient (MQ) (106.7±27.5 to 103.4± 19.3 for T, 105.8±13.2 to 104.9±17.2 for NT) and executive intelligence quotient (EIQ) (114.7±18.3 to 108.9±12.5 for T, 100.6±25.1 to 101.2±13.9 for NT). However, when sub-domain scores were compared between the two groups, the treatment group got significantly worse over time in the verbal fluency test (11.5±3.8 to 8.0±1.4 for T, 10.3±3.9 to 11.5±2.1 for NT; p<0.05) and level 1 of Stroop test (9.3±3.0 to 7.5±1.3 for T, 11.0±3.7 to 11.2±2.6 for NT; p<0.05). The subjects might have cognitive and behavioral difficulties in association with frontal lobe dysfunctions, but these difficulties did not seem to be dependent on the number of seizures, the abundance of subclinical epileptiform discharges, or the anti-epileptic treatment. CONCLUSIONS: We think that OXC monotherapy is effective for children with BRE, but is to be given to the selected patients such as patients with prolonged or frequent seizures. However, further studies are needed to have a better understanding in this matter.

Comparison of serum zinc levels measured by inductively coupled plasma mass spectrometry in preschool children with febrile and afebrile seizures.

BACKGROUND: Changes in levels of trace elements have been proposed to underlie febrile seizures. Particularly, low zinc levels have been proposed as related factor of febrile seizure. In this study, we investigated whether mean serum zinc levels differed between children with febrile seizure and afebrile seizure. METHODS: Using inductively coupled plasma mass spectrometry, serum zinc levels were measured in 288 children who had been diagnosed with febrile seizures (N=248) and afebrile seizures (N=40). Mean serum zinc levels were compared between the 2 groups. RESULTS: Mean serum zinc level was 60.5±12.7 µg/dL in the febrile seizure group and 68.9 ±14.5 µg/dL in the afebrile seizure group. A significant difference in serum zinc levels was observed between the febrile and afebrile seizure groups (P<0.001). CONCLUSIONS: Zinc levels in children with febrile seizure were significantly lower than those in children with afebrile seizure.

Identification and distribution of Bacillus species in doenjang by whole-cell protein patterns and 16S rRNA gene sequence analysis.

Many bacteria are involved in fermentation of doenjang and Bacillus species are known to perform significant roles. Although the SDS-PAGE technique has been frequently used for classification and identification of bacteria in various samples, there has been no investigation of the microbial diversity in doenjang. This study aims to investigate the identification and distribution of dominant Bacillus species in doenjang using SDS-PAGE profiles of whole cell proteins and 16S rDNA sequencing. SDS-PAGE of whole cell proteins of the reference Bacillus strains yielded differential banding patterns that could be considered to be highly specific fingerprints. Bacterial strains isolated from doenjang samples were grouped using whole cell protein patterns, which were confirmed by the analysis of 16S rDNA sequencing. B. subtilis was found to be the most dominant strain in most of the samples, and B. licheniformis and B. amyloliquefaciens were less frequently detected. The results obtained in this study showed that a combined identification method, SDS-PAGE patterns of whole cell proteins and subsequent 16S rDNA sequence analysis, could successfully identify Bacillus species isolated from doenjang.

Analysis of bacterial and fungal communities in Japanese- and Chinese-fermented soybean pastes using nested PCR-DGGE.

The microbial diversity of Japanese- and Chinese-fermented soybean pastes was investigated using nested PCR-denaturing gradient gel electrophoresis (DGGE). Five Japanese-fermented soybean paste samples and three Chinese-fermented soybean paste samples were analyzed for bacteria and fungi. Extracted DNA was used as a template for PCR to amplify 16S rRNA and 18S rRNA genes. The nearly complete 16S rRNA and 18S rRNA genes were amplified using universal primers, and the resulting products were subsequently used as a template in a nested PCR to obtain suitable fragments for DGGE. Tetragenococcus halophilus and Staphylococcus gallinarum were found to dominate the bacterial microbiota in Japanese samples, whereas Bacillus sp. was detected as the predominant species in Chinese samples. DGGE analysis of fungi in soybean pastes determined the presence of Aspergillus oryzae and Zygosaccharomyces rouxii in most of the Chinese and Japanese samples. Some differences were observed in the bacterial diversity of Japanese- and Chinese-fermented soybean pastes.

Analysis of microbial communities in doenjang, a Korean fermented soybean paste, using nested PCR-denaturing gradient gel electrophoresis.

Doenjang is a traditional Korean fermented soybean paste that provides a major source of protein. The microbial diversity of 10 samples of doenjang (5 commercially manufactured products and 5 homemade products) was investigated using nested PCR-denaturing gradient gel electrophoresis (DGGE). In the first step, the nearly complete 16S rRNA and 18S rRNA genes were amplified using universal primers. Subsequently, these products were used as a template in a nested PCR to obtain fragments suitable for DGGE. The bacterial DGGE profile targeting the V3 region of the 16S rRNA gene indicated that lactic acid bacteria such as Leuconostoc mesenteroide, Tetragenococcus halophilus, and Enterococcus faecium were the predominant species. However, bands corresponding to Bacillus species, known to be the main organisms in doenjang, were not detected under the conditions described above. When selective PCR was conducted using a primer specific for Bacillus species, Bacillus subtilis and B. licheniformis were detected in several doenjang samples. In analysis of fungi, Mucor plumbeus, Aspergillus oryzae, and Debaryomyces hansenii were the most common species in the doenjang samples. On the basis of DGGE, a few differences in community structure were found for different samples. Also, cluster analysis of the DGGE profile revealed that the microbial diversity did not differ clearly between commercially manufactured and homemade products. The nested PCR-DGGE technique was used for the first time in this study to asses a microbial community in doenjang and proved to be effective in profiling microbial diversity.

Prevalence and Correlates of Depressive Symptoms among North Korean Defectors Living in South Korea for More than One Year.

OBJECTIVE: This study examined the prevalence and correlates of depressive symptoms in North Korean defectors who have been living in South Korea for more than one year. METHODS: We used questionnaires developed by the authors to collect sociodemographic data in addition to the Center for Epidemiologic Studies Depression Scale (CES-D), the Psychosocial Well-being Index to measure stress, and a social support scale. A total of 367 subjects were included in this study. RESULTS: The results showed that 30.5% of the men and 34.7% of the women reported depressive symptoms, and 33.1% of the men and 36.1% of the women exhibited signs of severe distress. Correlates of depressive symptoms were lack of occupation [odds ratio (OR)=2.198, 95% confidence interval (CI), 1.247-3.873], having escaped without family (OR=1.725, 95% CI, 1.006-2.959), and a poor subjective sense of health status (OR=3.111, 95% CI, 1.591-6.085). CONCLUSION: Continuing vocational training and career management, psychological support programs, and intensive physical health services are needed to improve the mental health of this population.