Search results for: Yan Wang; Mathis Stock

Authors: Songwu Shen, Garrett Drysdale, Veerendranath Mannepalli, Qihua Dai, Yuan Wang, Yuli Chen, David Qian, Utkarsh Kakaiya

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Hardware accelerator has been a promising solution to reduce the cost of cloud data centers. This paper investigates the QoS enhancement of the acceleration of an important datacenter workload: the webserver (or proxy) that faces high computational consumption originated from secure sockets layer (SSL) or transport layer security (TLS) procession in the cloud environment. Our study reveals that for the accelerator maintenance cases—need to upgrade driver/firmware or hardware reset due to hardware hang; we still can provide cryptography services by switching to software during maintenance phase and then switching back to accelerator after maintenance. The switching is seamless to server application such as Nginx that runs inside a VM on top of the server. To achieve this high availability goal, we propose a comprehensive fallback solution based on Intel® QuickAssist Technology (QAT). This approach introduces an architecture that involves the collaboration between physical function (PF) and virtual function (VF), and collaboration among VF, OpenSSL, and web application Nginx. The evaluation shows that our solution could provide high reliability, availability, and scalability (RAS) of hardware cryptography service in a 7x24x365 manner in the cloud environment.

Keywords: accelerator, cryptography service, RAS, secure sockets layer/transport layer security, SSL/TLS, virtualization fallback architecture

Procedia PDF Downloads 159

Authors: Liwen Wang, Yuting Chen, Tong Wu, Shaolei Hu

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In order to enhance the security of critical financial infrastructure, this study carries out a transformation of the architecture of a financial trading terminal to a zero trust architecture (ZTA), constructs an active defense system for cybersecurity, improves the security level of trading services in the Internet environment, enhances the ability to prevent network attacks and unknown risks, and reduces the industry and security risks brought about by cybersecurity risks. This study introduces the SDP technology of ZTA, adapts and applies it to a financial trading terminal to achieve security optimization and fine-grained business grading control. The upgraded architecture of the trading terminal moves security protection forward to the user access layer, replaces VPN to optimize remote access, and significantly improves the security protection capability of Internet transactions. The study achieves 1. deep integration with the access control architecture of the transaction system; 2. no impact on the performance of terminals and gateways, and no perception of application system upgrades; 3. customized checklist and policy configuration; 4. introduction of industry-leading security technology such as single-packet authorization (SPA) and secondary authentication. This study carries out a successful application of ZTA in the field of financial trading and provides transformation ideas for other similar systems while improving the security level of financial transaction services in the Internet environment.

Keywords: zero trust, trading terminal, architecture, network security, cybersecurity

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Authors: Yangming Zhu, Mingming Guo, Xiaozan Wang

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Introduction: The purpose of this study is to integrate functional training into physical education to test the effectiveness of functional training in improving the physical fitness (PF) and sport skills (SS) of female college students. Methods: A total of 54 female college students from East China Normal University were selected for this study (27 in the experimental group and 27 in the control group), and 13 weeks of the experimental intervention was conducted during the semester. During the experimental period, the experimental group was functionally trained for 1 hour per week. The control group performed one-hour weekly sports (such as basketball, football, etc.) as usual. Before and after the experiment, the national students' physical fitness test was used to test the PF of the experimental group and the control group, and the SS of the experimental group and the control group were tested before and after the intervention. Then using SPSS and Excel to organize and analyze the data. Results: The independent sample T-test showed that there was no significant difference in the PF and SS between the experimental group and the control group before the experiment (T PF=71.86, p PF> 0.05, Tₛₛ=82.41,pₛₛ > 0.05); After the experiment, the PF of the experimental group was significantly higher than that of the control group (T Improve=71.86, p Improve < 0.05); after the experiment, the SS of the experimental group was significantly higher than that of the control group (Tₛₛ = 1.31, pₛₛ <0.01) Conclusions: Integrating functional training into physical education can improve the PF of female college students. At the same time, the integration of functional training into physical education can also effectively improve the SS of female college students. Therefore, it is suggested that functional training be integrated into the daily physical education of female college students so as to improve their PF and SS.

Keywords: functional training, physical fitness, sport skills, female college students

Procedia PDF Downloads 131

Authors: Haitao Yang, Jianming Lv, Fei Xu, Xintong Wang, Yilin Huang, Lanting Xia, Xuewu Zhu

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Given a fixed fund, purchasing fewer hosts of higher capability or inversely more of lower capability is a must-be-made trade-off in practices for building a Hadoop big data platform. An exploratory study is presented for a Housing Big Data Platform project (HBDP), where typical big data computing is with SQL queries of aggregate, join, and space-time condition selections executed upon massive data from more than 10 million housing units. In HBDP, an empirical formula was introduced to predict the performance of host clusters potential for the intended typical big data computing, and it was shaped via a regression approach. With this empirical formula, it is easy to suggest an optimal cluster configuration. The investigation was based on a typical Hadoop computing ecosystem HDFS+Hive+Spark. A proper metric was raised to measure the performance of Hadoop clusters in HBDP, which was tested and compared with its predicted counterpart, on executing three kinds of typical SQL query tasks. Tests were conducted with respect to factors of CPU benchmark, memory size, virtual host division, and the number of element physical host in cluster. The research has been applied to practical cluster procurement for housing big data computing.

Keywords: Hadoop platform planning, optimal cluster scheme at fixed-fund, performance predicting formula, typical SQL query tasks

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Authors: Zakia Belhadj, Bing He, Hua Zhang, Xueqing Wang, Wenbing Dai, Qiang Zhang

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Mononuclear phagocyte system (MPS) forms an abominable obstacle hampering the tumor delivery efficiency of nanoparticles. Passively targeted nanocarriers have received clinical approval over the past 20 years. However, none of the actively targeted nanocarriers have entered clinical trials. Thus it is important to endue effective targeting ability to actively targeted approaches by overcoming biological barriers to nanoparticle drug delivery. Here, it presents that an Esomeprazole-based preconditioning strategy for regulating nanocarrier-MPS interaction to substantially prolong circulation time and enhance tumor targeting of nanoparticles. In vitro, the clinically approved proton pump inhibitor Esomeprazole “ESO” was demonstrated to reduce interactions between macrophages and subsequently injected targeted vesicles by interfering with their lysosomal trafficking. Of note, in vivo studies demonstrated that ESO pretreatment greatly decreased the liver and spleen uptake of c(RGDm7)-modified vesicles, highly enhanced their tumor accumulation, thereby provided superior therapeutic efficacy of c(RGDm7)-modified vesicles co-loaded with Doxorubicin (DOX) and Gefitinib (GE). This MPS-preconditioning strategy using ESO provides deeper insights into regulating nanoparticles interaction with the phagocytic system and enhancing their cancer cells' accessibility for anticancer therapy.

Keywords: esomeprazole (ESO), mononuclear phagocyte system (MPS), preconditioning strategy, targeted lipid vesicles

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Authors: Jianghao Hu, Hongyu Wang

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The effective and efficient human pose estimation algorithm is an important task for real-time human pose estimation on mobile devices. This paper proposes a light-weight human key points detection algorithm, Light-Weight Network for Real-Time Pose Estimation (LWPE). LWPE uses light-weight backbone network and depthwise separable convolutions to reduce parameters and lower latency. LWPE uses the feature pyramid network (FPN) to fuse the high-resolution, semantically weak features with the low-resolution, semantically strong features. In the meantime, with multi-scale prediction, the predicted result by the low-resolution feature map is stacked to the adjacent higher-resolution feature map to intermediately monitor the network and continuously refine the results. At the last step, the key point coordinates predicted in the highest-resolution are used as the final output of the network. For the key-points that are difficult to predict, LWPE adopts the online hard key points mining strategy to focus on the key points that hard predicting. The proposed algorithm achieves excellent performance in the single-person dataset selected in the AI (artificial intelligence) challenge dataset. The algorithm maintains high-precision performance even though the model only contains 3.9M parameters, and it can run at 225 frames per second (FPS) on the generic graphics processing unit (GPU).

Keywords: depthwise separable convolutions, feature pyramid network, human pose estimation, light-weight backbone

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Authors: Kate Benedicta Amenador, Dianjian Wang, Bright Nkrumah

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This extensive bibliometric study explores the dynamic influence of artificial intelligence in the field of English as a Foreign Language (EFL) between 2012 and 2024. The study, which examined 4,500 articles from Google Scholar, Modern Language Association Linguistics Abstracts, Web of Science, Scopus, Researchgate, and library genesis databases, indicates that AI integration in EFL is on the rise. This notable increase is ascribed to a variety of transformative events, including increased academic funding for higher education and the COVID-19 epidemic. The results of the study identify leading contributors, prominent authors, publishers and sources, with the United States, China and the United Kingdom emerging as key contributors. The co-occurrence analysis of key terms reveals five clusters highlighting patterns in AI-enhanced language instruction and learning, including evaluation strategies, educational technology, learning motivation, EFL teaching aspects, and learner feedback. The study also discusses the impact of various AIs in enhancing EFL writing skills with software such as Grammarly, Quilbot, and Chatgpt. The current study recognizes limitations in database selection and linguistic constraints. Nevertheless, the results provide useful insights for educators, researchers and policymakers, inspiring and guiding a cross-disciplinary collaboration and creative pedagogical techniques and approaches to teaching and learning in the future.

Keywords: artificial intelligence, bibliometrics study, VOSviewer visualization, English as a foreign language

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Authors: S. Chuenchooklin

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This research was conducted in the Lower Ping River Basin downstream of the Bhumibol Dam and the Lower Wang River Basin in Tak Province, Thailand. Most of the tributary streams of the Ping can be considered as ungauged catchments. There are 10- pumping station installation at both river banks of the Ping in Tak Province. Recently, most of them could not fully operate due to the water amount in the river below the level that would be pumping, even though included water from the natural river and released flow from the Bhumibol Dam. The aim of this research was to increase the performance of those pumping stations using weir projects in the Ping. Therefore, the river analysis system model (HEC-RAS) was applied to study the hydraulic behavior of water surface profiles in the Ping River with both cases of existing conditions and proposed weirs during the violent flood in 2011 and severe drought in 2013. Moreover, the hydrologic modeling system (HMS) was applied to simulate lateral streamflow hydrograph from ungauged catchments of the Ping. The results of HEC-RAS model calibration with existing conditions in 2011 showed best trial roughness coefficient for the main channel of 0.026. The simulated water surface levels fitted to observation data with R2 of 0.8175. The model was applied to 3 proposed cascade weirs with 2.35 m in height and found surcharge water level only 0.27 m higher than the existing condition in 2011. Moreover, those weirs could maintain river water levels and increase of those pumping performances during less river flow in 2013.

Keywords: HEC-RAS, HMS, pumping stations, cascade weirs

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Authors: Ting Wang, Pierre Marle, Vera I. Slaveykova, Kristin Schirmer, Wei Liu

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Metal-based nanoparticles (NPs) are considered detrimental to aquatic organisms due to their potential accumulation. However, little is known about the mechanisms underlying these effects and their species-specificity. Here, we used stable silver (Ag) NPs (20 nm, from 10 to 500 μg/L) with a low dissolution rate (≤2.4%) to study the bioaccumulation and biological impacts in two freshwater gastropods: Lymnaea stagnalis and Planorbarius corneus. No mortality was detected during the experiments. Ag bioaccumulation showed a dose-related increase with an enhanced concentration in both species after 7d exposure. L. stagnalis displayed a higher accumulation for AgNPs than P. corneus (e.g., up to 18- and 15-fold in hepatopancreas and hemolymph, respectively), which could be due to the more active L. stagnalis having greater contact with suspended AgNPs. Furthermore, the hepatopancreas and stomach were preferred organs for bioaccumulation compared to the kidney, mantle and foot. Regarding biological responses, the hemolymph rather than hepatopancreas appeared more susceptible to oxidative stress elicited by AgNPs, as shown by significantly increasing lipid peroxidation (i.e., formation of malondialdehyde). Neurotoxicity was detected in L. stagnalis when exposed to high concentrations (500 μg/L). Comparison with impacts elicited by dissolved Ag revealed that the effects observed on AgNPs exposure were mainly attributable to NPs. These results highlighted the relationship between the physiological traits, bioaccumulation, and toxicity responses of these two species to AgNPs and demonstrated the necessity of species-specificity considerations when assessing the toxicity of NPs.

Keywords: nanotoxicity, freshwater gastropods, species-specificity, metals, physiological traits

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Authors: Yun-na Wu, Zhen Wang

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Due to the economic downturn and the deterioration of the living environment, the development of residential buildings as high energy consuming building is gradually changing from “extensive” to green building in China. So, the evaluation system of green building is continuously improved, but the current evaluation work has the following problems: (1) There are differences in the cost of the actual investment and the purchasing power of residents, also construction target of green residential building is single and lacks multi-objective performance development. (2) Green building evaluation lacks regional characteristics and cannot reflect the different regional residents demand. (3) In the process of determining the criteria weight, the experts’ judgment matrix is difficult to meet the requirement of consistency. Therefore, to solve those problems, questionnaires which are about the green residential building for Ningxia area are distributed, and the results of questionnaires can feedback the purchasing power of residents and the acceptance of the green building cost. Secondly, combined with the geographical features of Ningxia minority areas, the evaluation criteria system of green residential building is constructed. Finally, using the improved group AHP method and the grey clustering method, the criteria weight is determined, and a real case is evaluated, which is located in Xing Qing district, Ningxia. A conclusion can be obtained that the professional evaluation for this project and good social recognition is basically the same.

Keywords: evaluation, green residential building, grey clustering method, group AHP

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Authors: Xinyuan Zou, Qihui Tang, Shujian Wang, Yulin Huang, Jie Gui, Xiangping Liu, Gang Liu, Yanqiang Tao

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Childhood trauma can have a long-lasting influence on individuals and contribute to mental disorders, including depression and anxiety. The current study aimed to explore the symptomatic and developmental patterns of depression, anxiety, and stress among adolescents who have suffered from childhood trauma. A total of 3,598 college students (female = 1,617 (44.94%), Mean Age = 19.68, SD Age = 1.35) in China completed the Childhood Trauma Questionnaire (CTQ) and the Depression, Anxiety, and Stress Scales (DASS-21), and 2,337 participants met the selection standard based on the cut-off scores of the CTQ. The symptomatic network and directed acyclic graph (DAG) network approaches were used. The results revealed that males reported experiencing significantly more physical abuse, physical neglect, emotional neglect, and sexual abuse compared to females. However, females scored significantly higher than males on all items of DASS-21, except for “Worthless”. No significant difference between the two genders was observed in the network structure and global strength. Meanwhile, among all participants, “Down-hearted” and “Agitated” appeared to be the most interconnected symptoms, the bridge symptoms in the symptom network, as well as the most vital symptoms in the DAG network. Apart from that, “No-relax” also served as the most prominent symptom in the DAG network. The results suggested that intervention targeted at assisting adolescents in developing more adaptive coping strategies with stress and regulating emotion could benefit the alleviation of comorbid depression, anxiety, and stress.

Keywords: symptom network, childhood trauma, depression, anxiety, stress

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Authors: Tianyou Wang

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Students' own intrinsic motivation is the main source of energy for learning activities, and their self-efficacy becomes a key factor affecting the learning effect. In today's increasingly common situation of online vocal music teaching, virtualized teaching scenarios have brought a considerable impact on students' personal efficacy. Since personal efficacy is the result of the interaction between environmental factors and subject characteristics, an empirical study was conducted to investigate the changes in students' self-efficacy, influencing factors, and characteristics in online vocal teaching scenarios based on the three dimensions of teachers, students, and technology. One hundred valid questionnaires were studied through a quantitative survey. The results showed that students' personal efficacy was significantly lower in online learning environments compared to offline vocal teaching and showed significant differences due to factors such as gender and class type; students' self-efficacy in online vocal teaching was significantly affected by factors such as technological environment, teaching style, and information technology ability. Based on the results of the study, it is recommended to pay attention to inquiry and practice in the teaching design, use singing projects as the teaching organization, grasp the learning process with the orientation of problem-solving, push the applicable vocal music teaching resources in time, lead students to explore and refine the problems and push students to learn independently according to the goals and plans.

Keywords: vocal pedagogy, self-efficacy, online learning, intrinsic motivation, information technology

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Authors: Hatice Torcu Koc, Zeliha Erdogan

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This study presented the investigation of the population structure of Upeneus moluccensis in order to provide further knowledge and to compare the data with the studies before and thus help in the management of the population in the İskenderun Bay. For this purpose, a total of 370 golden-banded goatfish were caught by a commercial vessel monthly at a depth of 50-60 m. from İskenderun Bay in the years 2016-2018. Von Bertalanffy growth equation,length-weight relationships, sex ratio, age, condition, and gonado and hepato-somatic index values of U.peneus moluccensis specimens were determined. For this, the lengths and weights were measured using a dial caliper of 0.05 mm and a sensitive balance. Total lengths were 7.2–17.5 cm in females and 7.0–17.9 cm in males, while total weight ranges for females and males were 3.91-64.26 g and 3.69-60.95 g., respectively. Length-weight relationship for all individuals was calculated as W=0.004*L³ ³⁸, R²=0.85. Growth parameter was determined as L∞= 20.75 cm, k=0.33, t₀= - 0.56. The age readings were done by using the Bhattacharya method. The population was composed of 3 ages (1-3). The sex ratio was found as 1:1.42, corresponding to 41.4% males and 58.6% females, in favor of females (p<0.05). Values of the average condition and hepatosomatic index were found to be shown a similar pattern for males (1.088, 1.104) and females (1.124, 1.177), respectively. According to GSI values, the spawning period started in March and increased to April, May, and September. It was estimated that total (Z) mortality, natural (M) mortality, and fishing (F) mortality rates were estimated as Z=0.94 year-¹, M=0.033 year-¹, and F=0.63 year-¹, respectively. As the exploitation rate was estimated to be E=0.67, it can be shown that the golden-banded goatfish stock was influenced by overfishing. The findings of this study are very important to point out the population of U. moluccensis, which penetrated into the eastern Mediterranean Sea of Türkiye due to global heating and the construction of the Suez Canal and to be basic data for the next fisheries investigations.

Keywords: biology, U. moluccensis, invasive, lessepsian, İskenderun Bay

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Authors: Abosede Omowumi Babatunde

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While the Niger Delta region satisfies the global thirst for oil, the inhabitants have not been adequately compensated for the use of their ancestral land. Besides, the ruthless exploitation and destruction of the natural environment upon which the inhabitants of the Niger Delta depend for their livelihood and sustenance by the activities of oil multinationals, pose major threats to food security in the region and by implication, Nigeria in general, Africa, and the world, given the present global emphasis on food security. This paper examines the effect of oil exploitation on household food security, identify key gaps in measures put in place to address the changes to livelihoods and food security and explore what should be done to improve the local people access to sufficient, safe and culturally acceptable food in the Niger Delta. Data is derived through interviews with key informants and Focus Group Discussions (FGDs) conducted with respondents in the local communities in the Niger Delta states of Delta, Bayelsa and Rivers as well as relevant extant studies. The threat to food security is one important aspect of the human security challenges in the Niger Delta which has received limited scholarly attention. In addition, successive Nigerian governments have not meaningfully addressed the negative impacts of oil-induced environmental degradation on traditional livelihoods given the significant linkages between environmental sustainability, livelihood security, and food security. The destructive impact of oil pollution on the farmlands, crops, economic trees, creeks, lakes, and fishing equipment is so devastating that the people can no longer engage in productive farming and fishing. Also important is the limited access to modern agricultural methods for fishing and subsistence farming as fishing and farming are done using mostly crude implements and traditional methods. It is imperative and urgent to take stock of the negative implications of the activities of oil multinationals for environmental and livelihood sustainability, and household food security in the Niger Delta.

Keywords: challenges, food security, Nigeria's Niger delta, oil

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Authors: Lin Huang, Bo Wang, Armando Borgna

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Dehydration of glycerol to acrolein was conducted with solid acid catalysts in liquid phase in a batch reactor and in gas phase in a fix-bed reactor, respectively. In the liquid-phase reaction, ZSM-5, H3PO4-modified ZSM-5 and heteropolyacids including H3PW12O40•xH2O (HPW) and Cs2.5H0.5PW12O40 (CsPW) were studied as catalysts. High temperatures and high boiling point solvents such as sulfolane improved the selectivity to acrolein through suppressing the formation of polyglycerols and coke. Catalytic results and temperature-programmed desorption of ammonia showed that the yield of acrolein increased with increasing catalyst acidity within the range of weak acid strength. Weak acid sites favored the selectivity to acrolein whereas strong acid sites promoted the formation of coke. ZSM-5 possessing only acid sites led to a high acrolein yield, while heteropolyacid catalysts with strong acid sites produced a low acrolein yield. In the gas-phase reaction, HPW and CsPW supported on metal oxides such as SiO2, γ-Al2O3, SiO2-Al2O3, ZrO2 and silicate TUD-1 were studied as catalysts. HPW/TUD-1 was most active for the production of acrolein, followed by HPW/SiO2. An acrolein yield of 61 % was obtained over HPW/TUD-1. X-ray diffraction study suggested that HPW and CsPW were stable and more dispersed on SiO2, silicate TUD-1 and SiO2-Al2O3. It was found that the structures of HPW and CsPW were destroyed by interaction with γ-Al2O3 and ZrO2. Compared to CsPW/TUD-1, the higher acrolein yield with HPW/TUD-1 may be attributed to more Brønsted acid sites on HPW/TUD-1, based on preliminary pyridine adsorption IR study.

Keywords: dehydration, glycerol, acrolein, solid acid catalysts, gas-phase, liquid-phase

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Authors: Chengcao Sun, Cuili Yang, Shujun Li, Ruilin Xue, Yongyong Xi, Liang Wang, Dejia Li

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Backgrounds: A few lines of evidence show that Sulforaphane (SFN) has anti-fibrosis effect in liver tissue via Nrf2-mediated inhibition of TGF-β/Smad signaling. However, its effects on muscular dystrophic fibrosis remain unknown. This work was undertaken to evaluate the effects of SFN on fibrosis in dystrophic muscle. Methods: 3-month-old male mdx mice were treated with SFN by gavage (2 mg/kg body weight per day) for 3 months. Gastrocnemius, tibial anterior and triceps brachii muscles were collected for related analysis. Fibrosis in skeletal muscles was analyzed by Sirius red staining. Histology and morphology of skeletal muscles were investigated by H&E staining. Moreover, the expressions of Nrf2, NQO1, HO-1, and TGF-β/Smad signaling pathway were detected by western blot, qRT-PCR, immunohistochemistry and immunofluorescence assays. Results: Our results demonstrated that SFN treatment significantly decreased and improved morphological features in mdx muscles. Moreover, SFN increased the expression of muscle phase II enzymes NQO1 and HO-1 and significantly decreased the expression of TGF-β1，p-smad2, p-smad3, α-SMA, fibronectin, collagen I, PAI-1, and TIMP-1 in Nrf2 dependent manner. Additionally, SFN significantly decreased the expression of CD45 and TNF-α. Conclusions: Collectively, these results show that SFN can ameliorate muscle fibrosis in mdx mice by Nrf2-induced inhibition of TGF-β/Smad signaling pathway, which indicate Nrf2 may be useful for the treatment of muscular dystrophy.

Keywords: sulforaphane, Nrf2, TGF-β/smad signaling, duchenne muscular dystrophy, fibrosis

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Authors: Chia-li Wang

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The surge of service and commerce platforms, such as e-commerce and internet-of-things, have rapidly changed our lives. How to avoid the congestion and get the job done in the platform is now a common problem that many people encounter every day. This requires platform users to make decisions about when to enter the platform. To that end, we investigate the strategic entering time of a simple platform containing random numbers of buyers and sellers of some item. Upon a trade, the buyer and the seller gain respective profits, yet they pay the cost of waiting in the platform. To maximize their expected payoffs from trading, both buyers and sellers can choose their entering times. This creates an interesting and practical framework of a game that is played among buyers, among sellers, and between them. That is, a strategy employed by a player is not only against players of its type but also a response to those of the other type, and, thus, a strategy profile is composed of strategies of buyers and sellers. The players' best response, the Nash equilibrium (NE) strategy profile, is derived by a pair of differential equations, which, in turn, are used to establish its existence and uniqueness. More importantly, its structure sheds valuable insights of how the entering strategy of one side (buyers or sellers) is affected by the entering behavior of the other side. These results provide a base for the study of dynamic pricing for stochastic demand-supply imbalances. Finally, comparisons between the social welfares (the sum of the payoffs incurred by individual participants) obtained by the optimal strategy and by the NE strategy are conducted for showing the efficiency loss relative to the socially optimal solution. That should help to manage the platform better.

Keywords: double-sided queue, non-cooperative game, nash equilibrium, price of anarchy

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Authors: Levent Taylan Ozgur Yildirim, Qihao Qian, John Yilin Wang

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A critical review of assessments of geological carbon dioxide (CO2) storage resources in Pennsylvania and the surrounding region was completed with a focus on the studies of Midwest Regional Carbon Sequestration Partnership (MRCSP), United States Department of Energy (US-DOE), and United States Geological Survey (USGS). Pennsylvania Geological Survey participated in the MRCSP Phase I research to characterize potential storage formations in Pennsylvania. The MRCSP’s volumetric method estimated ~89 gigatonnes (Gt) of total CO2 storage resources in deep saline formations, depleted oil and gas reservoirs, coals, and shales in Pennsylvania. Meanwhile, the US-DOE calculated storage efficiency factors using log-odds normal distribution and Monte Carlo sampling, revealing contingent storage resources of ~18 Gt to ~20 Gt in deep saline formations, depleted oil and gas reservoirs, and coals in Pennsylvania. Additionally, the USGS employed Beta-PERT distribution and Monte Carlo sampling to determine buoyant and residual storage efficiency factors, resulting in 20 Gt of contingent storage resources across four storage assessment units in Appalachian Basin. However, few studies have explored CO2 storage resources in shales in the region, yielding inconclusive findings. This article provides a critical and most up to date review and analysis of geological CO2 storage resources in Pennsylvania and the region.

Keywords: carbon capture and storage, geological CO2 storage, pennsylvania, appalachian basin

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Authors: Chechen Liao, Pui-Lai To, Yi-Hui Wang

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Recently location-based augmented reality games (LBS+AR) have become increasingly popular as a major form of entertainment. Location-based augmented reality games have provided a lot of opportunities for face-to-face interaction among players. Prior studies also indicate that the social side of location-based augmented reality games are one of the major reasons for players to engage in the games. However, the impact of the usage of location-based augmented reality games has not been well explored. The study examines how interpersonal interaction affects social capital and health through playing location-based augmented reality games. The study also investigates how social capital mediates the relationships between interpersonal interaction and health. The study uses survey method to collect data. Six-hundred forty-seven questionnaires are collected. Structural equation modeling is used to investigate the relationships among variables. The causal relationships between variables in the research model are tested. The results of the study indicated that four interpersonal attraction attributes, including ability, proximity, similarity, and familiarity, are identified by ways of factor analysis. Interpersonal attraction is important for location-based augmented reality game-players to develop bonding and bridging social capital. Bonding and bridging social capital have a positive impact on the mental and social health of game-players. The results of the study provide academic and practical implications for future growth of location-based augmented reality games.

Keywords: health, interpersonal interaction, location-based augmented reality games, social capital

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Authors: Shay Kee Tan, Kok Haur Ng, Jennifer So-Kuen Chan

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This paper extends the conditional autoregressive range (CARR) model to multivariate CARR (MCARR) model and further to the two-stage MCARR-return model to model and forecast volatilities, correlations and returns of multiple financial assets. The first stage model fits the scaled realised Parkinson volatility measures using individual series and their pairwise sums of indices to the MCARR model to obtain in-sample estimates and forecasts of volatilities for these individual and pairwise sum series. Then covariances are calculated to construct the fitted variance-covariance matrix of returns which are imputed into the stage-two return model to capture the heteroskedasticity of assets’ returns. We investigate different choices of mean functions to describe the volatility dynamics. Empirical applications are based on the Standard and Poor 500, Dow Jones Industrial Average and Dow Jones United States Financial Service Indices. Results show that the stage-one MCARR models using asymmetric mean functions give better in-sample model fits than those based on symmetric mean functions. They also provide better out-of-sample volatility forecasts than those using CARR models based on two robust loss functions with the scaled realised open-to-close volatility measure as the proxy for the unobserved true volatility. We also find that the stage-two return models with constant means and multivariate Student-t errors give better in-sample fits than the Baba, Engle, Kraft, and Kroner type of generalized autoregressive conditional heteroskedasticity (BEKK-GARCH) models. The estimates and forecasts of value-at-risk (VaR) and conditional VaR based on the best MCARR-return models for each asset are provided and tested using Kupiec test to confirm the accuracy of the VaR forecasts.

Keywords: range-based volatility, correlation, multivariate CARR-return model, value-at-risk, conditional value-at-risk

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Authors: Peijen Pamela Chuang, Tzu-Hua Wang

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To address the notion of educational equity, undergo the global pandemic, a digital learning system was cross-disciplinarily designed by a 15-year-experienced teaching practitioner. A study was performed on students through the use of this pioneering e-learning system, in which Taiwanese students with different learning styles and special needs have a foreign language- English as the target subject. 121 students are particularly selected from an N= 580 sample spread across 20 inclusive and special education schools throughout districts of Taiwan. To bring off equity, the participants are selected from a mix of different socioeconomic statuses. Grouped data, such as classroom observation, individual learning preference, prerequisite knowledge, learning interest, and learning performance of the population, is carefully documented for further analyzation. The paper focuses on documenting the awareness and needs of this pedagogical methodology revolution, data analysis of UX (User Experience), also examination and system assessment of this system. At the time of the pilot run, this newly-developed e-learning system had successfully applied for and received a national patent in Taiwan. This independent research hoped to expand the awareness of the importance of individual differences in SDG4 (Substantial Development Goals 4) as a part of the ripple effect, and serve as a comparison for future scholars in the pedagogical research with an interdisciplinary approach.

Keywords: e-learning, educational equity, foreign language acquisition, inclusive education, individual differences, interdisciplinary innovation, learning preferences, SDG4

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Authors: Patrick C. H. Morel, Ian W. Barugh, Kirsty L. Chidgey

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The aim of this study was to quantify the level of piglet deaths in outdoor farrowing systems in New Zealand. A total of 14 farms were visited, the farmers interviewed, and data collected. A total of 10,154 sows were kept on those farms representing an estimated 33% of the NZ sow herd or 80% of the outdoor sow herd in 2016. Data from 25,911 litters was available for the different analyses. The characteristics and reproductive performance for the years 2015-2016 from the 14 farms surveyed in this study were analysed, and the following results were obtained. The average percentage of stillbirths was 7.1% ranging between 3.5 and 10.7%, and the average pre-weaning live-born mortality was 16.7% ranging between 3.7% and 23.6%. The majority of piglet deaths (89%) occurred during the first week after birth, with 81% of deaths occurring up to day three. The number of piglets born alive was 12.3 (8.0 to 14.0), and average number of piglets weaned per sow per year was 22.4, range 10.5-27.3. The average stocking rate per ha (number of sows and mated gilts) was 15.3 and ranged from 2.8 to 28.6. The sow to boar ratio average was 20.9:1 and the range was 7.1: 1 to 63:1. The sow replacement rate ranged between 37% and 78%. There was a large variation in the piglet live-born mortality both between months within a farm and between farms within a given month. The monthly recorded piglet mortality ranged between 7.7% and 31.5%, and there was no statistically significant difference between months on the number of piglets born, born alive, weaned or on pre-weaning piglet mortality. Twelve different types of hut/farrowing systems were used on the 14 farms. No difference in piglet mortality was observed between A-Frame, A-Frame Modified and for Box-shape huts. There was a positive relationship between the average number of piglets born per litter and the number of piglets born alive (r=0.975) or the number weaned per litter (r=0.845). Moreover, as the average number of piglets born-alive increases, both pre-weaning live-born mortality rate and the number of piglets weaned increased. An increase of 1 piglet in the number born alive corresponds to an increase of 2.9% in live-born mortality and an increase of 0.56 piglets weaned. Farmers reported that staff are the key to success with the key attributes being: good and reliable with attention to detail and skills with the stock.

Keywords: mortality, piglets, outdoor, pig farm

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Authors: Szu-Hua Wang

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Urban areas contain abundant potential biochemical storages and renewable and non-renewable flows. Urban natural environments for breeding natural assets and urban economic development for maintaining urban functions can be analyzed form the concept of ecological economic system. Land use change and ecosystem services change are resulting from the interactions between human activities and environments factually. Land use change due to human activities is the major cause of climate change, leading to serious impacts on urban ecosystem services, including provisioning services, regulating services, cultural services and supporting services. However, it lacks discussion on the interactions among urban land use change, ecosystem services change, and extreme precipitation events. Energy synthesis can use the same measure standard unit, solar energy, for different energy resources (e.g. sunlight, water, fossil fuels, minerals, etc.) and analyze contributions of various natural environmental resources on human economic systems. Therefore, this research adopts the concept of ecological, economic systems and energy synthesis for analyzing dynamic spatial impacts of land use change on ecosystem services, using the Taipei area as a case study. The analysis results show that changes in land use in the Taipei area, especially the conversion of natural lands and agricultural lands to urban lands, affect the ecosystem services negatively. These negative effects become more significant during the extreme precipitation events.

Keywords: urban ecological economic system, extreme precipitation events, ecosystem services, energy

Procedia PDF Downloads 190

Authors: Chris Schoborg, Morgan C. Wang

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In the realm of the National Football League (NFL), substantial dedication of time and effort is invested by both players and coaches in meticulously analyzing the game footage of their opponents. The primary aim is to anticipate the actions of the opposing team. Defensive players and coaches are especially focused on deciphering their adversaries' intentions to effectively counter their strategies. Acquiring insights into the specific play type and its intended direction on the field would confer a significant competitive advantage. This study establishes pre-snap information as the cornerstone for predicting both the play type (e.g., deep pass, short pass, or run) and its spatial trajectory (right, left, or center). The dataset for this research spans the regular NFL season data for all 32 teams from 2013 to 2022. This dataset is acquired using the nflreadr package, which conveniently extracts play-by-play data from NFL games and imports it into the R environment as structured datasets. In this study, we employ a recently developed machine learning algorithm, XGBoost. The final predictive model achieves an impressive lift of 2.61. This signifies that the presented model is 2.61 times more effective than random guessing—a significant improvement. Such a model has the potential to markedly enhance defensive coaches' ability to formulate game plans and adequately prepare their players, thus mitigating the opposing offense's yardage and point gains.

Keywords: lift, NFL, sports analytics, XGBoost

Procedia PDF Downloads 56

Authors: Zhaoan Wang

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Research in predictive maintenance modeling has improved in the recent years to predict failures and needed maintenance with high accuracy, saving cost and improving manufacturing efficiency. However, classic prediction models provide little valuable insight towards the most important features contributing to the failure. By analyzing and quantifying feature importance in predictive maintenance models, cost saving can be optimized based on business goals. First, multiple classifiers are evaluated with cross-validation to predict the multi-class of failures. Second, predictive performance with features provided by different feature selection algorithms are further analyzed. Third, features selected by different algorithms are ranked and combined based on their predictive power. Finally, linear explainer SHAP (SHapley Additive exPlanations) is applied to interpret classifier behavior and provide further insight towards the specific roles of features in both local predictions and global model behavior. The results of the experiments suggest that certain features play dominant roles in predictive models while others have significantly less impact on the overall performance. Moreover, for multi-class prediction of machine failures, the most important features vary with type of machine failures. The results may lead to improved productivity and cost saving by prioritizing sensor deployment, data collection, and data processing of more important features over less importance features.

Keywords: automated supply chain, intelligent manufacturing, predictive maintenance machine learning, feature engineering, model interpretation

Procedia PDF Downloads 133

Authors: Hsin-Chih Lai, Yung-Lung Lee, Yun-Yao Chi, Ching-Yi Horng, Pei-Chih Wu, Hsien-Chang Wang

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Taiwan, a climatically challenged island, has always been keen on the issue of water resource management due to its limitations in water storage. Since water resource management has been the focal point of many adaptations to climate change, there has been a lack of attention on another issue, water quality. This study chooses the Errer River Basin as the experimental focus for water quality in Taiwan. With the Errer River Basin being one of the most polluted rivers in Taiwan, this study observes the effects of climate change on this river over a period of time. Taiwan is also targeted by multiple typhoons every year, the heavy rainfall and strong winds create problems of pollution being carried to different river segments, including into the ocean. This study aims to create an impact and risk assessment on Errer River Basin, to show the connection from climate change to potential extreme events, which in turn could influence water quality and ultimately human health. Using dynamic downscaling, this study narrows the information from a global scale to a resolution of 1 km x 1 km. Then, through interpolation, the resolution is further narrowed into a resolution of 200m x 200m, to analyze the past, present, and future of extreme events. According to different climate change scenarios, this study designs an assessment index on the vulnerability of the Errer River Basin. Through this index, Errer River inhabitants can access advice on adaptations to climate change and act accordingly.

Keywords: climate change, adaptation, water quality, risk assessment

Procedia PDF Downloads 352

Authors: Qiming Wang

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Dynamic polymer networks (DPNs) crosslinked by dynamic bonds have received intensive attention because of their special crack-healing capability. Diverse DPNs have been synthesized using a number of dynamic bonds, including dynamic covalent bond, hydrogen bond, ionic bond, metal-ligand coordination, hydrophobic interaction, and others. Despite the promising success in the polymer synthesis, the fundamental understanding of their self-healing mechanics is still at the very beginning. Especially, a general analytical model to understand the interfacial self-healing behaviors of DPNs has not been established. Here, we develop polymer-network based analytical theories that can mechanistically model the constitutive behaviors and interfacial self-healing behaviors of DPNs. We consider that the DPN is composed of interpenetrating networks crosslinked by dynamic bonds. bonds obey a force-dependent chemical kinetics. During the self-healing process, we consider the The network chains follow inhomogeneous chain-length distributions and the dynamic polymer chains diffuse across the interface to reform the dynamic bonds, being modeled by a diffusion-reaction theory. The theories can predict the stress-stretch behaviors of original and self-healed DPNs, as well as the healing strength in a function of healing time. We show that the theoretically predicted healing behaviors can consistently match the documented experimental results of DPNs with various dynamic bonds, including dynamic covalent bonds (diarylbibenzofuranone and olefin metathesis), hydrogen bonds, and ionic bonds. We expect our model to be a powerful tool for the self-healing community to invent, design, understand, and optimize self-healing DPNs with various dynamic bonds.

Keywords: self-healing polymers, dynamic covalent bonds, hydrogen bonds, ionic bonds

Procedia PDF Downloads 187

Authors: Chaomeng Liu, Li Li, Xiao Wang, Li Ren, Qinge Zhang

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Late-life depression (LLD) is a prevalent mental disorder among the elderly, frequently accompanied by significant cognitive decline, and has emerged as a worldwide public health concern. Microglia, astrocytes, and peripheral immune cells play pivotal roles in regulating inflammatory responses within the central nervous system (CNS) across diverse cerebral disorders. This review commences with the clinical research findings and accentuates the recent advancements pertaining to microglia and astrocytes in the neuroinflammation process of LLD. The reciprocal communication network between the CNS and immune system is of paramount importance in the pathogenesis of depression and cognitive decline. Stress-induced downregulation of tight and gap junction proteins in the brain results in increased blood-brain barrier permeability and impaired astrocyte function. Concurrently, activated microglia release inflammatory mediators, initiating the kynurenine metabolic pathway and exacerbating the quinolinic acid/kynurenic acid imbalance. Moreover, the balance between Th17 and Treg cells is implicated in the preservation of immune homeostasis within the cerebral milieu of individuals suffering from LLD. The ultimate objective of this review is to present future strategies for the management and treatment of LLD, informed by the most recent advancements in research, with the aim of averting or postponing the onset of AD.

Keywords: neuroinflammation, late-life depression, microglia, astrocytes, central nervous system, blood-brain barrier, Kynurenine pathway

Procedia PDF Downloads 46

Authors: Sanjiv Kumar Soni, Chetna Janveja

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The approach of utilizing zero cost kitchen waste residues for growing suitable strains of fungi for the induction of a cocktail of hydrolytic enzymes and ethanol generation has been validated in the present study with the objective of developing an indigenous biorefinery for low cost bioethanol production with the generation of zero waste. Solid state fermentation has been carried out to evaluate the potential of various steam pretreated kitchen waste residues as substrates for the co-production of multiple carbohydrases including cellulases, hemicellulases, pectinase and amylases by a locally isolated strain of Aspergillus niger C-5. Of all the residues, potato peels induced the maximum yields of all the enzyme components corresponding to 64.0±1.92 IU of CMCase, 17.0±0.54 IU of FPase , 42.8±1.28 IU of β-glucosidase, 990.0±28.90 IU of xylanase, 53.2±2.12 IU of mannanase, 126.0±3.72 IU of pectinase, 31500.0±375.78 IU of α-amylase and 488.8±9.82 IU of glucoamylase/g dry substrate respectively. Saccharification of various kitchen refuse residues using inhouse produced crude enzyme cocktail resulted in the release of 610±10.56, 570±8.89, 435±6.54, 475±4.56, 445±4.27, 385±4.49, 370±6.89, 490±10.45 mg of total reducing sugars/g of dried potato peels, orange peels, pineapple peels, mausami peels, onion peels, banana stalks, pea pods and composite mixture respectively revealing carbohydrate conversion efficiencies in the range of 97.0-99.4%. After fermentation of released hexoses by Saccharomyces cerevisae, ethanol yields ranging from 80-262 mL/ kg of dry residues were obtained. The study has successfully evaluated the valorization of kitchen garbage, a highly biodegradable component in Municipal Solid Waste by using it as a substrate for the in-house co-production of multiple carbohydrases and employing the steam treated residues as a feed stock for bioethanol production. Such valorization of kitchen garbage may reduce the level of Municipal Solid Waste going into land-fills thus lowering the emissions of greenhouse gases. Moreover, the solid residue left after the bioconversion may be used as a biofertilizer for improving the fertility of the soils.

Keywords: kitchen waste, bioethanol, solid waste, bioconversion, waste management

Procedia PDF Downloads 401

Authors: Yang Yu, Jian Wang, Jiqiang Liu, Lei Han, Xudong He, Shaohua Lv

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As the increasing network attacks become more and more complex, network situation assessment based on log analysis cannot meet the requirements to ensure network security because of the low quality of logs and alerts. This paper addresses the lack of consideration of security attributes of hosts and attacks in the network. Identity and effectiveness of Distributed Denial of Service (DDoS) are hard to be proved in risk assessment based on alerts and flow matching. This paper proposes a multi-dimension threat situation assessment method based on network security attributes. First, the paper offers an improved Common Vulnerability Scoring System (CVSS) calculation, which includes confident risk, integrity risk, availability risk and a weighted risk. Second, the paper introduces deterioration rate of properties collected by sensors in hosts and network, which aimed at assessing the time and level of DDoS attacks. Third, the paper introduces distribution of asset value in security attributes considering features of attacks and network, which aimed at assessing and show the whole situation. Experiments demonstrate that the approach reflects effectiveness and level of DDoS attacks, and the result can show the primary threat in network and security requirement of network. Through comparison and analysis, the method reflects more in security requirement and security risk situation than traditional methods based on alert and flow analyzing.

Keywords: DDoS evaluation, improved CVSS, network security attribute, threat situation assessment

Procedia PDF Downloads 209