• Molecules and Cells
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• v.45 no.8
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• pp.513-521
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• 2022

Cytotoxic T lymphocyte antigen-4 (CTLA-4) is an immune checkpoint molecule that is mainly expressed on activated T cells and regulatory T (Treg) cells that inhibits T-cell activation and regulates immune homeostasis. Due to the crucial functions of CTLA-4 in T-cell biology, CTLA-4-targeted immunotherapies have been developed for autoimmune disease as well as cancers. CTLA-4 is known to compete with CD28 to interact with B7, but some studies have revealed that its downstream signaling is independent of its ligand interaction. As a signaling domain of CTLA-4, the tyrosine motif plays a role in inhibiting T-cell activation. Recently, the lysine motif has been shown to be required for the function of Treg cells, emphasizing the importance of CTLA-4 signaling. In this review, we summarize the current understanding of CTLA-4 biology and molecular signaling events and discuss strategies to target CTLA-4 signaling for immune modulation and disease therapy.

• Journal of the Chungcheong Mathematical Society
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• v.23 no.3
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• pp.443-452
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• 2010

This work deals with the existence of uncountably many bounded positive solutions for the third order nonlinear neutral delay differential equation $$\frac{d^3}{dt^3}[x(t)+p(t)x(t-{\tau})]+f(t,x(t-{{\tau}_1}),{\ldots},x(t-{{\tau}_k}))=0,\;t{\geq}t_0$$ where ${\tau}>0$, ${\tau}_i{\in}{\mathbb{R}^+}$ for $i{\in}\{1,2,{\ldots},k\}$, $p{\in}C([t_0,+{\infty}),{\mathbb{R}^+})$ and $f{\in}C([t_0,+{\infty}){\times}{\mathbb{R}^k},{\mathbb{R}})$.

• International Journal of Advanced Culture Technology
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• v.11 no.1
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• pp.343-348
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• 2023

As the IoT market continues to grow, security threats to IoT devices with limited resources are also increasing. However, the application of security technology to the existing system to IoT devices with limited resources is impossible due to the inherent characteristics of IoT devices. Various methods for solving related problems have been studied in existing studies to solve this problem. Therefore, this study analyzes the characteristics of domestic IoT authentication standards and existing research to propose an algorithm that applies blockchain-based authentication and lightweight encryption algorithms to IoT equipment with limited resources. In this study, a key generation method was applied using a Lamport hash-chain and data integrity between IoT devices were provided using a Merkle Tree, and an LEA encryption algorithm was applied using confidentiality in data communication. In the experiment, it was verified that the efficiency is high when the LEA encryption algorithm, which is a lightweight encryption algorithm, is applied to IoT devices with limited resources.

• Korean Journal of Poultry Science
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• v.25 no.3
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• pp.129-136
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• 1998

This experiment was carried out to investigate the effect of feeding system on performance in Korean Native Commercial Chicken. A total 864 birds produced from (Cornish ♂ X (Korean Native Chicken ♂ XRhode Island Red♀)♀ ] crossbreeds in National Livestock Research Institute, for 16 weeks. Feeding system of T1 and T$_2$ were same types from hatch to 8 weeks, starter diets(O~4 weeks, mash, ME 3,100kcal, CP 22.94%), grower diets(4~8 weeks, crumble, ME 3,100kcal, CP 19.31%). Nutrient content of finisher diets of T$_1$(pellet, ME 3,200kcal, CP 20.44%) was higher than T$_2$(mash, ME 3,100kcal, CP 14.88%) in order to improve meat quality for 8~16 weeks. Fertility and hatchability of Korean Native Commercial Chicken was 83.9% and 69.7%, respectively. Viabilities of T$_1$ and T$_2$ at 0, 4, 8, 12 and 16 weeks were 98.8%, 97.9%, 96.5% and 99.1%, 95. 8%, 92.8%, 90.3%, respectively. The viability of 0 to 8 weeks was not significantly in feed treatments, but 12 and 16 weeks was significantly T$_1$ higher than T$_2$(P<0.05). Body weights of T$_1$and T$_2$ at 4, 8, 12 and 16 weeks were 551g, 1,379g, 2,441g, 3,056g and 554g, 1,360g, 2,254g, 2,956g, respectively. The body weight of 0 to 8 weeks was not significantly feed treatments but 12 and 16 weeks was significantly T1 higher than T$_2$(P<0.05). Feed conversion of T$_1$ and T$_2$ to 4, 8,12 and 16 weeks were 1.91, 2.28, 3.34, 4.23 and 1.90, 2.28, 3.53, 4.46, respectively. The feed conversion of 0 to 8 weeks was not significantly feed treatments but 12 and 16 weeks was significantly T$_1$ lower than T$_2$(P<0.05). The ME intake 1 bird per 1 day of T$_1$ and T$_2$were 3S9kcal, 357kca1, respectively, not significantly feed treatments but CP intake were 24.8g, 20.3g, respectively. T$_2$ was lower than T$_1$(P$_1$ and T$_2$were 13,426kca1, 13,819Ykcal, respectively, not significantly feed treatments but CP requirement per kg body weight gain were 928g, 763g, respectively, T$_2$ was lower than T$_1$(P<0.05).

• Korean Journal of Food Science and Technology
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• v.44 no.4
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• pp.460-466
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• 2012

Through an analysis of T-2 and HT-2 toxins in corn and brown rice, the effect of enzymatic deacetylation of T-2 toxin on HT-2 toxin was investigated. Gas chromatography (GC) with electron capture detection and high-performance liquid chromatography (HPLC) with fluorescence detection were used for quantitative determination. T-2 toxin was converted into HT-2 (84-86%) within 15 min in the presence of crude protein extracts from corn and brown rice. The absence of T-2 conversion was observed for autoclaved samples, in which the enzymes were inactivated. When phosphate buffered saline, followed by methanol, was used as the extraction solvent, recoveries of T-2 toxin spiked at 50 and 200 ${\mu}g/kg$ were from 60 to 87%, whereas those of HT-2 in the autoclaved samples were 0%. In non-autoclaved samples, recoveries of HT-2 were 37-66%, whereas those of T-2 were negligible. However, the conversion of T-2 into HT-2 was not observed when samples were extracted by methanol/water.

• Journal of Practical Engineering Education
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• v.16 no.4
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• pp.449-457
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• 2024

AIoT, the intelligent Internet of Things, refers to a technology that collects data measured by IoT devices and applies machine learning technology to create and utilize predictive models. Existing research on AIoT technology education focused on building an educational AIoT platform and teaching how to use it. However, there was a lack of case studies that taught the process of automatically creating and utilizing machine learning models from data measured by IoT devices. In this paper, we developed a case study using a machine learning model for AIoT technology education. The case developed in this paper consists of the following steps: data collection from AIoT devices, data preprocessing, automatic creation of machine learning models, calculation of accuracy for each model, determination of valid models, and data prediction using the valid models. In this paper, we considered that sensors in AIoT devices measure different ranges of values, and presented an example of data preprocessing accordingly. In addition, we developed a case where AIoT devices automatically determine what information they can predict by automatically generating several machine learning models and determining effective models with high accuracy among these models. By applying the developed cases, a variety of educational contents using AIoT, such as prediction-based object control using AIoT, can be developed.

• Asian-Australasian Journal of Animal Sciences
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• v.11 no.1
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• pp.17-20
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• 1998

Sixteen local sheep (8 male + 8 female) of about six months old with average live weight 10.78 $({\pm}1.11)$ kg were allocated into four treatments. The treatments (T) are : $T_0$ = Restricted grazing without concentrate; $T_1$, $T_2$ and $T_3$ = Grazing + 100, 200 and 300 g concentrate per sheep daily. Live weight of grazing (7.30 hrs daily) sheep was recorded in each week. The uncastrated male sheep were slaughtered for carcass and non-carcass parameters. Statistically significant (p < 0.05) differences were observed in live weight gain (g/day) among the treatments ($T_0=15.71$; $T_1=22.66$; $T_2 =32.66$ and $T_3=40.47$). The dressing % were : ($T_0=32.75$, $T_1=38.50$, $T_2=36.90 $ and $T_3=37.75$). The warm carcass weight represented 37.21% of live weight. Significant (p < 0.01) correlation were observed for live weight with carcass weight (r = 0.99) and dressing % (r = 0.88). Concentrate supplement increase live weight gain in sheep on grazing. Live weight is a good indicator to assess carcass characteristics.

• Smart Media Journal
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• v.11 no.3
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• pp.18-25
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• 2022

Neuromorphic computing generally shows significantly better power, area, and speed performance than neural network computation using CPU and GPU. These characteristics are suitable for resource-constrained IoT environments where energy consumption is important. However, there is a problem in that it is necessary to modify the source code for environment setting and application operation according to heterogeneous IoT devices that support neuromorphic computing. To solve these problems, NAAL was proposed and implemented in this paper. NAAL provides functions necessary for IoT device control and neuromorphic architecture abstraction and inference model operation in various heterogeneous IoT device environments based on common APIs of NAAL. NAAL has the advantage of enabling additional support for new heterogeneous IoT devices and neuromorphic architectures and computing devices in the future.

• Bulletin of the Korean Mathematical Society
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• v.21 no.2
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• pp.127-135
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• 1984

In this paper, we find the Fourier series of X(t, .omega.).mem. $L^{2}$$_{s.a.p.}$ and the Parseval relation of X(t, .omega.).mem. $L^{2}$$_{s.a.p.}$. In section 2, we investigate some basic properties of X(t, .omega.).mem. $L^{2}$$_{s.a.p.}$ In section 3, we show that the mean of X(t, .omega.).mem. $L^{2}$$_{s.a.p.}$ exists and in section 4, after showing the existence of Fourier exponents and Fourier coefficients of X(t, .omega.).mem. $L^{2}$$_{s.a.p.}$. we give the Parseval relation of X(t, .omega.).mem. $L^{2}$$_{s.a.p.}$. For convenience we will denote X(t, .omega.) as X(t) in what follows.hat follows.

• Journal of Korea Multimedia Society
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• v.6 no.4
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• pp.658-667
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• 2003

Developing tailor made Multimedia courseware ensuring effective implementation of instruction strategies is a challenge that manifests in myriad problems of software design and coding. In this paper an attempt has been made to analyse and identify coding and implementation problems, in the backdrop of using two different multimedia software development tools i.e. Visual Basic and Toolbook, which underpin the development and effectiveness of use of multimedia courseware. Solutions to such problems have been discussed in context of Tool book. The examples presented in this paper are based on the experience of designing and implementation of two large scale professional quality Multimedia courseware development projects.