Earticle

Emotion regulation is the ability to modify the intensity and time course of emotional experiences and expressions to manage arousal, such as negative and positive responses. Emotion regulation is crucial for the development of adaptive social functioning. Few studies have a measurement method for identifying neural markers to examine the correlation between neural and behavior response of emotion regulation. We assessed whether neural and behavior responses to attention-emotion integration task were related to emotion regulation capacities. Before and after the negative and positive video clips were shown, EEG was recorded while participants performed attention-emotion integration task. P100, P300 amplitude, and latency were closely correlated with each other. Specially, after the negative video clip was shown, the larger the P100 amplitudes at the specific positions, the longer the P300 latencies at these same positions during attention-emotion integration task. The longer the P300 latencies at the specific positions, the longer the delay in response time. Also, there is and individual differences in ERP components and response time during attention-emotion integration task. Individuals who had larger and longer amplitude and latency of ERP components showed longer response times during attention-emotion integration task, regardless of whether video clips were presented or not. This characteristic was related to the enhanced emotion regulation.

Currently, aging population has been increased dramatically with development in medical technologies and dining experiences. And, incurable diseases can be healed more easily than before with this development. Many scientists strive to find ways regarding how to extend life. In this situation, the bio-industry has been to the fore to get solutions for prolongs human life at the moment of the economic crisis. Many developed countries attempt to kick-start the bio-industry and their attempts are also to promote their economy through the bio-investments. Additionally, energy crisis has emerged as an overriding concern in consequence of the diminishing fossil fuels. Many countries in the world try to find alternative energy sources to replace fossil fuels. Examples of alternative energy sources are clean energies such as solar power, wind power, and bio-energy. In the field of the bio-industry, palm oil is a very beneficial source that can be applied to many purposes: medical applications, new energy sources, and food applications. Official data shows that the bio-industry in the US is superior to the bio-industry in the EU. And, the European countries try to catch up the US which is a leading country over the world in the field of the bio-industry. This paper studies how bio-industry affects macroeconomic factors empirically. In other words, this paper studies recent empirical developments regarding the bio-industry using the Granger-causality test with Indonesia’s palm oil data. This paper finds that GDP has a unidirectional causality and a reciprocal causality with macroeconomic factors. However, GDP has no causality with ‘beginning stock’ of palm oil. ‘Ending stock’ of palm oil has a unidirectional causality and a reciprocal causality with macroeconomic factors. Overall, our empirical test results show that economic growth affects development in the bio-industry. And, the most noteworthy feature of the bio-industry nowadays is that M&A has been spread over the world to acquire the most recent bio-technology economically.

In the production of medical images, noise reduction and contrast enhancement are important methods to increase qualities of processing results. Wavelet transforms have shown promising results for localization in both time and frequency, and hence have been used for image processing applications including noise removal. By using the edge-based denoising and adaptive nonlinear histogram stretching, a novel medical image enhancement algorithm is proposed. First, a medical image is decomposed by wavelet transform, and then all high frequency sub-images are decomposed by Haar transform. At the same time, edge detection with Sobel operator is performed. Second, noises in all high frequency sub-images are reduced by edge-based soft-threshold method. Third, high frequency coefficients are further enhanced by adaptive weight values in different sub-images. Through the inverse Haar transform and the inverse wavelet transform, the enhanced image is obtained. Finally, the proposed adaptive nonlinear histogram stretching method is applied to increase the contrast of resultant image. Experimental results show that the proposed algorithm can enhance a low contrast medical image while preserving edges effectively without blurring the details.

This study attempts to measure the effect on depression of support programs for female family caregivers of dementia patients. Subjects are female family caregivers of dementia patients in Seoul and Gyeonggi-do. A total of 54 women were studied, with an experimental group of 28 and a control group of 26. Through the interview with female family caregivers of dementia patients, a review of the literature, and the participation of specialists, a support program fitting the Korean situation was developed, which the experimental group underwent through a total of 8 sessions for 2-3 hours a day once a week. No special intervention was given to the control group. Depression of the experimental group and the control group was measured through before and after the test. Depression change between the experimental group and control group was analyzed with t-test. The research found that depression of female family caregivers of dementia patients became significantly lowered in the experimental group compared with the control group after the support program. Hence, the support program for female family caregivers of dementia patients was verified as a safe and effective program for lowering depression in female family caregivers.

This study aims to investigate preliminary early childhood teachers’ recognition of children’s addiction to media and alternative solutions. The research subjects were 33 students (preliminary early childhood teachers) in an early childhood education institute. The data collected were coded according to the content from group interview sessions and classified by concepts and topics. The results suggest that parents’ inappropriate child-rearing was mostly held responsible for children’s addiction to media, which is harmful for their physical development and has not been given necessary attention by society. Secondly, the participants suggested social support, namely that parents can get education and treatment services about incorrect child-rearing attitudes. Therefore, to prevent children’ s media addiction and to make better educational use of media, early childhood education institutions, counseling centers, and local social service centers have to provide guidebooks on appropriate media education, instructions for parenting, or training opportunities for improving the parent-child relationship, which young children and parents should easily be able to benefit from. Also, experts need to carry out a detailed plan for this process.

This study was conducted to examine the application effect of a medical information management system for the prevention of depression in mastectomy patients. The subjects were divided into an experimental group (n=62) and a control group (n=62). To verify the effects of the information mediation, this study used a progress method for measurement in the form of an application test and a follow-up test. The results of this study are as follows: First, it showed significantly the factors of health behavior on depression in the degree of education, nutrient intake, exercise, insomnia, and personality type (p<.05). Secondly, it was found that the experimental group had a tendency toward gradually developing more variation from 70.2% to 83.1% in health behavior performance than the control group with regard to the measurement of depression over the application timeframe. Therefore, it is concluded that a medical information management system is effective in relieving mastectomy patients from depression over the physical, psychological, and social changes they experience.

The extension of healthy life expectancy as well as average life expectancy in modern societies has become a very important social issue. In particular, functional foods rather than medicines for extending the healthy life is becoming a very important issue. For this, in this paper, we will study the efficiency of drinking the lacquer beverage which is a kind of functional foods that help to improve liver function using speech signal analysis. Usually, molar pronunciation becomes clumsily according to Korean Oriental Medicine diagnosis theory if the liver function is improved. Therefore, we will investigate the change of 3 formant frequency bandwidth which is associated with a molar pronunciation through the drinking of the lacquer beverage before and after. Finally, the effectiveness of this research is demonstrated by several experiments.

To find the new raw material having skin care activity, P. oleracea of organic native plant was extracted and concentrated with solvent extracting method. As a cosmetic active material, it is to develop an active raw molecule for discovering new skin pathway such as anti-aging, whitening and wrinkle skin improvement. The skin irritating evaluations (in-vitro) were performed to confirm the skin safety of its extract. Both free radical scavenging activity and collagen biosynthesis activity for skin anti-aging activity were evaluated with control sample (pure ascorbic acid). Melanin inhibition activity (in-vitro) as a skin lightning effect, to find the skin whitening was tested to use its material. As an application study, two high functional emulsion lotion having almost natural sources containing P. oleracea extract were formulated without any preservatives and totally evaluated the skin improvement effect (whitening, anti-aging activity and fine wrinkle diminish effect, human volunteer test, in-vivo). Therefore, the organic P. oleracea extract can contribute to the development of new natural active ingredients for advanced skin care cosmetic.

In this paper, we synthesized hypercross-linked conjugated chromophores with light absorption characteristics during cross-linking of aromatic monomers, such as naphthalene with dimethoxy methane, Phloroglucinol with terephthaldehyde and Phloroglucinol with dichloro-p-xylene from Friedal-Crafts reaction. DRS UV Vis spectroscopy confirms conjugated quinonoid matrix by their broad light absorption characteristics extending from 1000 to 200 nm. Absorbance maximum occurred close to 400 nm. So, the catalyst functions to cross-link the monomers by –CH2– bridges and subsequently dehydrogenate the bridges to form quinonoids. The FTIR spectroscopy showed their characteristic quinonoid vibrations between 1600 and 1700 cm-1. From the thermogravimetric analysis, thermal stability of the microporous polymers was found to be good. Their SEM images showed microspheres of 1 to 5μm size built with tiny particles. Their surfaces were not smooth. The maximum NOx sorption of 13% was obtained for the hypercross-linked polymer of Phloroglucinol with dichloro-p-xylene.

This paper utilizes grounded theory in studying the sharing of experiences by a group of university hospital medical doctors. Based on empirical data and the application of knowledge sharing theory, a theoretical framework for a comprehensive approach to knowledge sharing by doctors in the long term is developed. The 20 participants in this study all have more than 10 years of medical experience and are specialists working in university hospitals in Korea. In addition each participants also hold the position of associate professor or higher at the associated medical school. Four in-depth interview and studies were conducted. For the paradigm model of grounded theory, the concepts were drawn from the causal condition, contextual condition, main context, intervening condition, interaction strategy and result. Low level categories were identified and then high level categories were extracted from them. In this study, ‘the process of development through the sharing of experience’ is identified as being the key category. This study is meaningful in that it, unlike existing studies of knowledge sharing, tries to understand and explain the significance and process of knowledge sharing as experienced by medical doctors. While most of the literature about knowledge sharing focuses on a quantitative analysis, this study utilizes qualitative methodology, particularly grounded theory, to understand the substance or meaning the doctors experienced whilst sharing their knowledge. The study suggests how to improve the quality of the knowledge concerned, organize such knowledge and/or advance its utilization and sharing.

The specific objective of this paper is to develop a computer vision algorithm to detect and count tangerine flowers in an image for estimate tangerine crops. The algorithm consists of image acquisition, Gaussian filter to remove noise, white color detection, counting of tangerine flowers. A Gaussian filter was used to reduce noise and illumination adjustment as much as possible for better clarity. It is observed that the developed method gives better valid output for tangerine flower detection in natural outdoor lighting, with different lighting condition without any alternative lighting source to control the luminance. The simulation result reveals that the method is reliable, feasible and efficient compared to other existing methods.

Recognizing human activities based on user’s contextual information is becoming more important to the success of context-aware pervasive computing. In this paper, we define activities and introduce a six-layer activity model. We also describe our algorithm to perform activity recognition. The key contextual information is location, and other pieces of contextual information are also used in our study. To evaluate our algorithm we collected user data from twenty test users while they performed daily activities. We present a comprehensive experimental evaluation and discuss the results.

To compare Vestibular-CNS function on the HF and HB condition confirmed to balance normal state of a posture. The vestibular and CNS displacements analyzed at the five ranges from the H-FB: Head of forward and backward. Vestibule-CNS function (VeC) shows the vestibular variation appear to through the CNS from the spinal cord. The average different outputs obtained greatest the perturbations: VeHB-CNO-B displacement at 10.88±2.71, VeHB-CNC-B displacement at 10.76±2.68, VeHB-CNO-A displacement at 10.077±2.33, VeNC-CNC-A displacement at 10.58±2.72. Our results will be to show an impact of at least postural control by the H-FB function. CHF-CNC-A and CHB-CNC-A displacement of the moment identified to inertia from CNS. The Vestibular HF-HB was affected to maintain for the balance by the CNS of HF-HB.

It is necessary to implementation of system contain intelligent decision making algorithm considering individual characteristics because existing u-Health system is simply monitoring obtained data from sensor network. In this paper, we designed inference system using case based reasoning method and implemented knowledge base that case for fire and damage of biological. We used K-Nearest Neighbor algorithm for recommend best similar case and input 3.000 EA by case for fire and damage context case base. As a result, we obtained about 86.6% average accuracy for damage of biological case and about 83.9% average accuracy for fire case. We implemented u-Health monitoring system using inference result.

Studies have proven the diagnostic efficiency of multiple markers for ovarian cancer diagnosis with in vitro diagnostic multivariate index assays. We compared the diagnostic performance of multiple marker combinations and carbohydrate antigen (CA) 125 alone, a widely utilized tumor marker, for early ovarian cancer detection. Overall, 257 serum samples from Korean women, including 204 patients with benign tumors and 53 patients with ovarian cancer, were analyzed. We used 22 serum markers showing specific reaction to ovarian cancer was the concentration value obtained from xMAP™ bead-based technology (Luminex Corp.). To identify markers that combined well with CA125, a multivariate model that comprised combinations of 2–3 marker, including CA125, was created, and the best marker combinations were selected by assessing area under the receiver-operating curves (AUCs). The AUC values of CA125 alone, CA125+M2, and CA125+M2+M4 were 69.96%, 76.63%, and 81.28%, respectively. It was confirmed that multiple marker combinations including CA125 showed better diagnostic performance than CA125 alone for early-stage ovarian cancer diagnosis.

In this paper, we proposed a method for configuring each component of a gel documentation system for the miniaturization and penetration of the system. To miniaturize the UV illuminator part, the minimum type of UVB lamp was adopted along with ballasts that can drive four lamps. As the imaging system, a conventional compact digital camera, which has a similar performance to that of a DSLR, was adopted. By developing and supplementing the PC remote control function of which lack in the low-end digital camera, the price and size of the gel doc equipment can be significantly reduced while still maintaining the performance and function of the gel doc. The proposed system showed comparable performance and image quality to those of the existing Gel documentation system even though if it was small and inexpensive.

In this study a noble TMS-induced artifact removal method is developed and discussed by estimating its parameters for various aspects of data, such as sampling rate, filtering order and ICA decomposition method, in both the EEG time series and in the independent components of the EEG by using the EEG data obtained from four healthy subjects who were receiving single pulse TMS-EEG and sham-EEG stimulus on the left Broca’s area. A total of four healthy male subjects without any neurological disorder were selected in this study. ICA filters trained on the reduced version of 60 channel EEG data collected during single pulse TMS-EEG and sham-EEG recordings and identified the reduced number of statistically independent source channels. The decomposition algorithm of ICA considered in this study includes Jader , FastICA and cICA. The ICA components originating from the TMS-induced artifact are classified by comparing the cross-correlation coefficients between single pulse TMS-EEG and sham-EEG stimulus after ICA decomposition. Then, the estimation of parameters in the TMS-induced artifact removal for sampling rate 1.45kHz, filtering order 100 and ICA decomposition method FastICA was evaluated by the change of the ratio of the cross-correlation coefficients between single pulse TMS-EEG and sham-EEG stimulus before and after the ICA decomposition. The results showed the consistency in the assessment of the availability of the TMS-induced artifact removal suggesting the efficiency and the reliability of the method developed in this study.

The rapid and widespread construction of structures calls for rigorous structural health monitoring (SHM) programs throughout the construction, operation and maintenance phases. Thus, much of a structure’s success or failure depends upon efficient SHM programs. The basic technology underlying the SHM program’s ability to detect cracks and failures can be incorporated with Wireless Sensor Network technology for more robust SHM. The agility of the WSN is, therefore, a prominent factor for a successful SHM program. Unpredictable external events, such as earthquakes or serious impacts are an inevitable fact of life. During such an event, the WSN should continue to be active and efficient enough to perform the assigned tasks without failure. The never miss an opportunity scheme (NMAOS) model, which is a prototype based on multi-agent technology, is proposed in this paper to provide agility to the Wireless Sensor Network.

Marine fungi are the potential and promising sources for biologically active secondary metabolite productions. Secondary metabolites are the chemical compounds that are produced during the stationary phase of the organism. Many years of study revealed that fungi are excellent sources for novel bioactive secondary metabolites. In the present study fungi were isolated from marine water samples and serial dilution method was performed to isolate single colonies. Later microscopic and macroscopic observations were done to identify the organism. Organisms are inoculated into medium for production of secondary metabolites. One week later ethyl acetate is added to the broth in 1:1 ratio and kept for incubation in shaker. Solvent is separated by separating funnel and solvent is extracted by rotavapour to collect the crude extract. Crude extract is dissolved in DMSO and further tested for biological activities. The Fungi was identified as Fusarium species and its secondary metabolites showed potential antimicrobial activity. The present work was attempted to isolate organisms which are capable of producing efficient antibacterial and antifungal compounds. Further we identified the organism as Fusarium sp. The future scope of this work is to isolate these biologically active compounds to use in pharmaceutical applications.

National Industrial Security Center of National Intelligence Service has announced that information leakages by insiders occurred at the total of 294 cases during the last 8 years. Difficulty of acquiring omen of a security incident and the fact that insiders usually have legitimate privileges make prevent security defense. Therefore, we need to research about developing methods to obtain factors for prediction of information leakage by insiders in a whole new different perspective. When an insider tries to do something malicious, biometric information of the body changes due to tension. This means that biometric information can be used as factor for detecting malicious activities of an insider. In this paper, we propose the proactive detection technique that can detect malicious behaviors of an insider by biometric information. Additionally, we compare proposed technique with other techniques that use biometric information in the security field.

Mobile computing is a relatively new field. While the challenges arising from mobility and the limitations of the portable devices are relatively well understood, there is no consensus yet as to what should be done to address these challenges. A comprehensive solution has to address many different aspects, such as the issue of dynamically changing bandwidth, the power, computational, and other limitations of the portable devices, or the varying availability of services in different environments. In this paper, we present our architecture for such adaptive mobile applications. We motivated the architecture by classifying likely mobile applications and identified common properties. The architecture intends to be more general than previous work with respect to adaptability, flexibility, and user mobility. We developed various pieces of the overall architecture and collected some preliminary experience with adaptive mobile applications. We give an overview of the intersection of the areas of software architecture and mobile applications. We consider the mobile applications, which represent the computing functionality designed to migrate across hardware devices at runtime and execute on mobile hardware platforms, and the mobile systems, which are computing applications that include mobile software and hardware elements. We are developing the components of a flexible and general-purpose runtime infrastructure to facilitate the rapid development and deployment of such adaptive mobile applications. We will evaluate our infrastructure by implementing a number of wireless applications and by building simulation tools to validate the scalability of our architecture when considering metropolitan and provincial cellular systems.

Production of antimicrobial peptides has gained lot of significance in the present day research. Most of the recombinant proteins are generally produced from IPTG inducible E. coli BL21(DE3). As an alternative, considering the factors like cost and toxic nature of IPTG, salt inducible Escherichia coli GJ1158 was used in the present study for the production of synthetic cationic antimicrobial peptide by fed batch fermentation. This study was conducted to optimize the physico–chemical parameters viz., dissolved oxygen concentration (DOC) and nutritional factors viz., carbon, nitrogen and phosphate sources on bacterial growth and peptide production. Even after increase in DOC more than 30 % in batch culture has no effect on expression, but significant improvement in fed-batch cultivation was observed beyond 30% DOC. Supplementation of production medium with different pulses of nutrient sources like dextrose mono hydrate, yeast extract and Na2HPO4 enhanced the expression in fed batch fermentation process even without disturbing the cell growth at 40 % DOC. When growth reached 15 g/L of dry cell weight, culture was induced with 150 mM NaCl and further cultured for next 15 hr (16.37 g/L dry cell weight). Approximately, 258 mg/L of pure peptide was obtained by using modified GYEON medium. The peptide thus produced is tested for its antimicrobial activity, devoid of hemolytic activity. The fed-batch fermentation which emphasizes, this was the highest reported concentration of recombinant synthetic peptide from salt inducible expression host till to date, which manages to gratify the present day industrial production of the peptides cost-effectively.

Single Nucleotide Polymorphisms (SNPs), a single DNA base varying from one individual to another, are believed to be the most frequent form responsible for genetic differences. Haplotypes have more information for disease-associating than individual SNPs or genotypes; it is substantially more difficult to determine haplotypes through experiments. Hence, computational methods that can reduce the cost of determining haplotypes become attractive alternatives. MEC, as a standard model for haplotype reconstruction, is fed by fragments input to infer the best pair of haplotypes with minimum errors needing correction. It is proved that haplotype reconstruction in the MEC model is a NP-Hard problem. Thus, researchers’ desire reduced running time and obtaining acceptable results. Heuristic algorithms and different clustering methods are employed to achieve these goals. In this paper, Harmony Search (HS) is considered a clustering approach. Extensive computational experiments indicate that the designed HS algorithm achieves a higher accuracy than the genetic algorithm (GA) or particle swarm optimization (PSO) to the MEC model in most cases.

This innovative model is presented to study the effect of non-Newtonian behavior of blood flow through a radially non-symmetric multiple stenosis artery using Herschel-Bulkely fluid model. The numerical illustration presented at the end of the paper provides the results for the resistance to flow, apparent viscosity and the wall shear stress through their graphical representations. It has been shown that the resistance to flow, apparent viscosity and wall shear stress increases with the size of the stenosis but these increases is comparatively small due to non-Newtonian behavior of the blood indicating the usefulness of its rheological character in the functioning of the diseased arterial circulation. Few comparisons with the existing results have been made in order to validate the applicability of the present model.

Data Mining is one of the most motivating area of research that is become increasingly popular in health organization. Data Mining plays an important role for uncovering new trends in healthcare organization which in turn helpful for all the parties associated with this field. This survey explores the utility of various Data Mining techniques such as classification, clustering, association, regression in health domain. In this paper, we present a brief introduction of these techniques and their advantages and disadvantages. This survey also highlights applications, challenges and future issues of Data Mining in healthcare. Recommendation regarding the suitable choice of available Data Mining technique is also discussed in this paper.

Catheter ablation along the posterior aspect of the left atrium has a small but real risk of esophageal perforation. This left atrioesophageal fistula formation is associated with multiple gaseous and/or septic embolic events causing cerebral and myocardial damage. The main objective is to mathematically model the ablation associated with delivery of radiofrequency (RF) energy to treat atrial fibrillation in order to control the temperature rise in the esophageal lumen. We model the heat exchange problem in a time-dependent multi-region for the catheter ablation therapy, with particular application to RF thermal ablation on the atrial tissue. From the selected set of geometric and operational parameters, benchmark calculations result in graphical representations. The proposed solutions enable whether quantitative or qualitative the study of temperature behavior whenever in space or in time. These enhance the physical understanding of what factors can affect the esophageal temperature and how to most accurately measure it. The model is sufficiently explicit to be, in turn, applied to different performances of one ablation procedure, or even to other thermal techniques.