• The Journal of Asian Finance, Economics and Business
• /
• 제8권10호
• /
• pp.239-247
• /
• 2021

Central Bank authorities should carefully manage inflation rate uncertainties to achieve economic growth and development not only in the short-run but also in the long-run. Since inflation is a key macroeconomic variable, an increased understanding about its behavior is undoubtedly important. Thus, paper employs unit root with breakpoints to examine the mean reverting behavior of inflation rate in the Philippines using monthly data from 2002 to 2020. Empirically, the unit root breakpoint innovational and additive outlier tests favor the stationarity or mean reverting behavior of inflation in the Philippines. Also, results of standard unit root tests, ADF, PP, GLS-Dickey-Fuller, KPSS and NP, provide strong evidence of mean reverting processes. The mean reverting behavior of inflation rate reveals that the monetary policy using inflation targeting framework has succeeded in reducing chronic inflation persistence in the Philippines. Thus, this research supports inflation targeting policy that aims to maintain general price level stability for the Philippine economy's long-term growth and development prospects. The findings of this research remain important for the central bankers for not only providing them better understanding about the behavior of inflation rate, but also helping them formulate and implement policy reforms related to money, credit and banking.

• 대한금속재료학회지
• /
• 제47권10호
• /
• pp.613-620
• /
• 2009

The Kachanov-Rabotnov (K-R) creep model was proposed to accurately model the long-term creep curves above $10^5$ hours of Alloy 617. To this end, a series of creep data was obtained from creep tests conducted under different stress levels at $950^{\circ}C$. Using these data, the creep constants used in the K-R model and the modified K-R model were determined by a nonlinear least square fitting (NLSF) method, respectively. The K-R model yielded poor correspondence with the experimental curves, but the modified K-R model provided good agreement with the curves. Log-log plots of ${\varepsilon}^{\ast}$-stress and ${\varepsilon}^{\ast}$-time to rupture showed good linear relationships. Constants in the modified K-R model were obtained as ${\lambda}$=2.78, and $k=1.24$, and they showed behavior close to stress independency. Using these constants, long-term creep curves above $10^5$ hours obtained from short-term creep data can be modeled by implementing the modified K-R model.

• Biomolecules & Therapeutics
• /
• 제28권3호
• /
• pp.282-291
• /
• 2020

Inhaled solvents such as toluene are of particular concern due to their abuse potential that is easily exposed to the environment. The inhalation of toluene causes various behavioral problems, but, the effect of short-term exposure of toluene on changes in emotional behaviors over time after exposure and the accompanying pathological characteristics have not been fully identified. Here, we evaluated the behavioral and neurochemical changes observed over time in mice that inhaled toluene. The mice were exposed to toluene for 30 min at a concentration of either 500 or 2,000 ppm. Toluene did not cause social or motor dysfunction in mice. However, increased anxiety-like behavior was detected in the short-term after exposure, and depression-like behavior appeared as delayed effects. The amount of striatal dopamine metabolites was significantly decreased by toluene, which continued to be seen for up to almost two weeks after inhalation. Additionally, an upregulation of serotonin 1A (5-HT_1A) receptor in the hippocampus and the substantia nigra, as well as reduced immunoreactivity of neurogenesis markers in the dentate gyrus, was observed in the mice after two weeks. These results suggest that toluene inhalation, even single exposure, mimics early anxiety-and delayed depression-like emotional disturbances, underpinned by pathological changes in the brain.

• 한국물환경학회지
• /
• 제20권1호
• /
• pp.48-54
• /
• 2004

Two methods, a Ceriodaphnia algal uptake suppression test (CAUST) and a new toxicity test based on temperature control (TTBTC) which are based on feeding behaviour and temperature control, respectively, were developed and compared for the adoption as the better methodology for short-term toxicity screening. As previously published by Lee et aI., (1997), the CAUST method is based on the feeding behaviour of C. dubia and requires as little as 1 hour of contact time between C. dubia neonates and toxicant. However, even though CAUST requires only 1 hour of contact time, this method still take many hours for the preparation and measurement. Before the test starts, neonate digestive tracts were cleared by feeding yeast to the daphnids, Neonates were then exposed to toxicant, followed by addition of Scenedesmus subspiatus into the bioassay vessels. Daphnids were examined under the bright-field microscope with the presence of algae (indicated by a green colored digestive tract) or the absence of algae. Uptake indicated no toxic effect, whereas, absence of uptake indicated toxic inhibition. Unlike CAUST, the newly developed method (TTBTC) is based on just temperature control for the toxicity test of C. dubia. Initially, neonates are exposed to toxicants while the temperature of water bath containing media increased to $35.5^{\circ}C$. After 1.25 hour of contact time, the number of the daphnids, either live (no toxic effect) or dead (toxic effect), is counted without the aid of any instrument. In both methods, median effective concentrations ($EC_{50}$ values) were computed based on the results over a range of dosed toxicant concentrations. It showed that TTBTC was as sensitive as the standard 48-hour acute bioassay and CAUST. TTBTC and CAUST were much more sensitive than the I-hour I.Q. test and 30-minute Microtox. This study indicates that TTBTC is an easier and more rapid toxicity test than the standard 48-hour acute bioassay and even CAUST.

• Structural Engineering and Mechanics
• /
• 제62권3호
• /
• pp.373-380
• /
• 2017

Concrete structures are often subjected to long-term static and short-term dynamic loads. Due to a relatively low tensile strength and energy dissipating characteristics, the impact resistance of concrete is considered poor. This study investigates the feasibility of using polypropylene fibers to improve the impact resistance of reinforced concrete slabs. Fourteen polypropylene fiber reinforced concrete slabs were fabricated and tested using a drop weight test. The effects of slab thickness, fiber volume fractions, and impact energy on the dynamic behaviors were evaluated mainly in terms of impact resistant, crack patterns, and failure modes. The post impact induced strains versus time responses were obtained for all slabs. The results showed that adding the polypropylene fiber at a dosage of 0.90% by volume of concrete leads to significant improvement in the overall structural behavior of the slabs and their resistance to impact loading. Interestingly, the enhancement in the behavior of the slabs using a higher fiber dosage of 1.2% was not as good as achieved with 0.90%.

• Structural Engineering and Mechanics
• /
• 제47권1호
• /
• pp.1-25
• /
• 2013

A combined thermal and mechanical action in roller compacted concrete (RCC) dam analysis is carried out using a three-dimensional finite element method. In this work a numerical procedure for the simulation of construction process and service life of RCC dams is presented. It takes into account the more relevant features of the behavior of concrete such as hydration, ageing and creep. A viscoelastic model, including ageing effects and thermal dependent properties is adopted for the concrete. The different isothermal temperature influence on creep and elastic modulus is taken into account by the maturity concept, and the influence of the change of temperature on creep is considered by introducing a transient thermal creep term. Crack index is used to assess the risk of occurrence of crack either at short or long term. This study demonstrates that, the increase of the elastic modulus has been accelerated due to the high temperature of hydration at the initial stage, and consequently stresses are increased.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 1992년도 하계학술대회 논문집 A
• /
• pp.495-497
• /
• 1992

Hourly load forecasting has become indispensable for practical simulation of electric power system as the system become larger and more complicated. To forecast the future hourly load the cyclic behavior of electric load which follows seasonal weather, day or week and office hours is to be analyzed so that the trend of the recent behavioral change can be extrapolated for the short term. For the long term, on the other hand, the changes in the infra-structure of each electricity consumer groups should be assessed. In this paper the concept and process of hourly load forecasting for hourly load is introduced.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 19-21 Oct. 1992
• /
• pp.70-73
• /
• 1992

This paper describes the modeling of human memory using a nerve field model which is proposed for modeling the mechanism of brain mathematically. In our model, two phases of memory, retention and recollection, are focused on. The former consists of two stages, short-term memory (STM) and long-term memory (LTM). The proposed model consists of three parts, the STM Layer, LTM Layer and the Intermediate Layer between them. Each of these is constructed by a nerve field. In the STM Layer, memorized information is retained dynamically in the form of the reverberating states of units within the layer, while in the LTM Layer, it is stored statically in the form of structures of the weight on the links between units. the Intermediate Layer is introduced to translate this dynamic representation in the STM Layer to the LTNI Layer, and also to extract the static information from the STM Layer. In addition to this, we consider the recollection of information stored in the LTM. Finally, the behavior of this model is demonstrated by computer simulation.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
• /
• 제19권2호
• /
• pp.61-71
• /
• 2008

Attention-deficit hyperactivity disorder (ADHD) is characterized by inattention, hyperactivity, impulsiveness and problems in other higher cognitive processes such as executive function deficits. Currently, there are many treatment modalities, of which pharmacotherapy is the most strongly supported by scientific and clinical evidence. Stimulants, which are first choice in the pharmacological treatment of ADHD, block dopamine reuptake by binding the dopamine transporter and so increasing the concentration of dopamine in synaptic clefts. Stimulants are effective in improving core ADHD symptoms, as well as the nonspecific symptoms, such as aggressiveness and oppositional behavior. Frequently reported short-term adverse effects are decreased appetite, sleep disturbance, headache, dizziness and irritability. Although questions have been raised about the long-term side effects of stimulants, including growth suppression, cardiovascular events, and abuse potential, there is no clear evidence to support these concerns.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제8권11호
• /
• pp.4016-4027
• /
• 2014

Understanding network latency is important for providing consistent and acceptable levels of services in network-based applications. However, due to the difficulty of estimating applications' network demands and the difficulty of network latency modeling the management of network resources has often been ignored. We expect that, since network latency repeats cycles of congested states, a systematic classification method for network status would be helpful to simplify issues in network resource managements. This paper presents a simple empirical method to classify network status with a real operational network. By observing oscillating behavior of end-to-end latency we determine networks' status in run time. Five typical network statuses are defined based on a long-term stability and a short-term burstiness. By investigating prediction accuracies of several simple numerical models we show the effectiveness of the network status classification. Experimental results show that around 80% reduction in prediction errors depending on network status.