Search results for: Wang Hong

Authors: Philip A. Moore Jr., Jerry Martin, Hong Li

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Research has shown that over half of the nitrogen (N) excreted from broiler chickens is emitted to the atmosphere before the manure is removed from the barns, resulting in air and water pollution, as well as the loss of a valuable fertilizer resource. The objective of this study was to determine the fertilizer efficiency of N captured from the exhaust air from poultry houses using acid scrubbers. This research was conducted using 24 plots located on a Captina silt loam soil. There were six treatments: (1) unfertilized control, (2) aluminum sulfate (alum) scrubber solution, (3) potassium bisulfate scrubber solution, (4) sodium bisulfate scrubber solution, (5) sulfuric acid scrubber solution and (6) ammonium nitrate fertilizer dissolved in water. There were four replications per treatment in a randomized block design. The scrubber solutions were obtained from acid scrubbers attached to exhaust fans on commercial broiler houses. All N sources were applied at an application rate equivalent to 112 kg N ha⁻¹. Forage yields were measured five times throughout the growing season. Five months after the fertilizer sources were applied, a rainfall simulation study was conducted to determine the potential effects on phosphorus (P) runoff. Forage yields were significantly higher in plots fertilized with scrubber solutions from potassium bisulfate and sodium bisulfate than plots fertilized with scrubber solutions made from alum or sulfuric acid or ammonium nitrate, which were higher than the controls (7.61, 7.46, 6.87, 6.72, 6.45, and 5.12 Mg ha ⁻¹, respectively). Forage N uptake followed similar trends as yields. Phosphorus runoff and water soluble P was significantly lower in plots fertilized with the scrubber solutions made from aluminum sulfate. This study demonstrates that N captured using ammonia scrubbers is as good or possibly better than commercial ammonium nitrate fertilizer.

Keywords: air quality, ammonia emissions, nitrogen fertilizer, poultry

Procedia PDF Downloads 198

Authors: Di Wang, Li Fang, Shengyu Fang, Jianhua Li, Honghong Dong, Zhongzhi Zhang

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Heavy oily refinery wastewater with the characteristics of high concentration of toxic organic pollutant, poor biodegradability and complicated dissolved recalcitrant compounds is intractable to be degraded. In order to reduce the concentrations of COD and total nitrogen pollutants which are the major pollutants in heavy oily refinery wastewater, the Anoxic - Oxic microbiological technology relies mainly on anaerobic microbial reactor which works with methanogenic archaea mainly that can convert organic pollutants to methane gas, and supplemented by aerobic treatment. The results of continuous operation for 2 months with a hydraulic retention time (HRT) of 60h showed that, the COD concentration from influent water of anaerobic reactor and effluent water from aerobic reactor were 547.8mg/L and 93.85mg/L, respectively. The total removal rate of COD was up to 84.9%. Compared with the 46.71mg/L of total nitrogen pollutants in influent water of anaerobic reactor, the concentration of effluent water of aerobic reactor decreased to 14.11mg/L. In addition, the average removal rate of total nitrogen pollutants reached as high as 69.8%. Based on the data displayed, Anoxic - Oxic microbial technology shows a great potential to dispose heavy oil sewage in energy saving and high-efficiency of biodegradation.

Keywords: anoxic - oxic microbiological technology, COD, heavy oily refinery wastewater, total nitrogen pollutant

Procedia PDF Downloads 491

Authors: Saqib Ali, Man-Qun Wang

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The Japanese pine sawyer, Monochamus alternatus Hope (Coleoptera: Cerambycidae), is a major pest of pines and it is also the key vector of the exotic pinewood nematode in China. In the present study, we cloned, expressed, and purified a chemosensory protein (CSP) in M. alternatus. We surveyed its expression in various developmental stages of male and female adult tissues and determined its binding affinities for different pine volatiles using a competitive binding fluorescence assay. A CSP known as CSP5 in M. alternatus was obtained from an antennal cDNA library and expressed in Escherichia coli. Quantitative reverse transcription polymerase chain reaction results indicated that the CSP5 gene was mainly expressed in male and female antennae. Competitive binding assays were performed to test the binding affinity of recombinant CSP5 to 13 odour molecules of pine volatiles. The results showed that CSP5 showed very strong binding abilities to myrcene, (+)-β-pinene, and (−)-isolongifolene, whereas the volatiles 2-methoxy-4-vinylphenol, p-cymene, and (+)-limonene oxide have relatively weak binding affinity at pH 5.0. Three volatiles myrcene, (+)-β-pinene, and (−)-isolongifolene may play crucial roles in CSP5 binding with ligands, but this needs further study for confirmation. The sensitivity of insect to host plant volatiles can effectively be used to control and monitor the population through mass trapping as part of integrated pest management programs.

Keywords: olfactory-specific protein, volatiles, competitive binding assay, expression characteristics, qPCR

Procedia PDF Downloads 127

Authors: Chung-Kwei Wang, Kuo-Ying Lo

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The study is aimed to examine main and moderation effect of Chinese traditional social wisdom ‘Ren-qing Shi-kuon' the adjustment of social worker students during their practicum. Ren-qing Shi-ku as a social wisdom has been emphasized by collective-oriented Chinese society for thousand years. Based on interview and literature review, we operationalized the concept as four factors, including ‘harmonious interaction’, ‘understanding and tolerance’, ‘empathetic communication’ and ‘rule abiding’. We administer the scale to 96 social worker senior students before their summer practicums begins and collect their response on emotion labor, emotional exhaustion, work load, work satisfaction. We also ask their supervisors rated their performance on empathy, interpersonal relationships, performance on practicum and their Ren-qing Shi-ku performance. Results indicated that self-ratings of students on Ren-qing Shi-ku scale are correlated with rating from their supervisors. Students who have higher Ren-qing Shi-ku have better adjustment and higher ratings from their supervisor. Ren-qing Shi-ku also moderate effects of surface acting labor and work load on emotional exhaustion and work satisfaction. However, Ren-qing Shi-ku seems more beneficial under low work load situations. The finding of this study suggested traditional social skill training might be very effective for social service providers in a collective-oriented culture.

Keywords: emotion labor, ren-qing shi-ku, emotional exhaustion, work satisfaction and performance

Procedia PDF Downloads 489

Authors: Kun Chen, Yan Wang, Yangyu Zhao, Shufang Li, Lian Chen, Xiaoyue Guo, Jue Zhang, Jing Fang

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The coupling strength between uterine electromyography (UEMG) and Fetal heart rate (FHR) signals during peripartum reflects the fetal biophysical activities. Therefore, UEMG-FHR coupling characterization is instructive in assessing placenta function. This study introduced a physiological marker named elevated frequency of UEMG-FHR coupling (E-UFC) and explored its predictive value for pregnancies complicated by pre-eclampsia and small for gestational age (SGA). Placental insufficiency patients (n=12) and healthy volunteers (n=24) were recruited and participated. UEMG and FHR were recorded non-invasively by a trans-abdominal device in women at term with singleton pregnancy (32-37 weeks) from 10:00 pm to 8:00 am. The product of the wavelet coherence and the wavelet cross-spectral power between UEMG and FHR was used to weight these two effects in order to quantify the degree of the UEMG-FHR coupling. E-UFC was exacted from the resultant spectrogram by calculating the mean value of the high-coherence (r > 0.5) frequency band. Results showed the high-coherence between UEMG and FHR was observed in the frequency band (1/512-1/16Hz). In addition, E-UFC in placental insufficiency patients was weaker compared to healthy controls (p < 0.001) at group level. These findings suggested the proposed approach could be used to quantitatively characterize the fetal biophysical activities, which is beneficial for early detection of placental insufficiency and reduces the occurrence of adverse pregnancy.

Keywords: uterine electromyography, fetal heart rate, coupling analysis, wavelet analysis

Procedia PDF Downloads 200

Authors: Edward K. Boahen, Brunel E. Bouya-Moko, Changda Wang

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The major threat to online social network (OSN) users is account compromisation. Spammers now spread malicious messages by exploiting the trust relationship established between account owners and their friends. The challenge in detecting a compromised account by service providers is validating the trusted relationship established between the account owners, their friends, and the spammers. Another challenge is the increase in required human interaction with the feature selection. Research available on supervised learning (machine learning) has limitations with the feature selection and accounts that cannot be profiled, like application programming interface (API). Therefore, this paper discusses the various behaviours of the OSN users and the current approaches in detecting a compromised OSN account, emphasizing its limitations and challenges. We propose a deep learning approach that addresses and resolve the constraints faced by the previous schemes. We detailed our proposed optimized nonsymmetric deep auto-encoder (OPT_NDAE) for unsupervised feature learning, which reduces the required human interaction levels in the selection and extraction of features. We evaluated our proposed classifier using the NSL-KDD and KDDCUP'99 datasets in a graphical user interface enabled Weka application. The results obtained indicate that our proposed approach outperformed most of the traditional schemes in OSN compromised account detection with an accuracy rate of 99.86%.

Keywords: computer security, network security, online social network, account compromisation

Procedia PDF Downloads 115

Authors: Xue Wang, Li-Wei Fan

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The technology innovation has become the driving force of social and economic development and transformation. The guidance and support of public policies is an important condition to promote the realization of technology innovation goals. Policy effectiveness evaluation is instructive in policy learning and adjustment. This paper reviews existing studies and systematically evaluates the effectiveness of policy-driven technological innovation. We used 167 articles from WOS and CNKI databases as samples to clarify the measurement of technological innovation indicators and analyze the classification and application of policy evaluation methods. In general, technology innovation input and technological output are the two main aspects of technological innovation index design, among which technological patents are the focus of research, the number of patents reflects the scale of technological innovation, and the quality of patents reflects the value of innovation from multiple aspects. As for policy evaluation methods, statistical analysis methods are applied to the formulation, selection and evaluation of the after-effect of policies to analyze the effect of policy implementation qualitatively and quantitatively. The bibliometric methods are mainly based on the public policy texts, discriminating the inter-government relationship and the multi-dimensional value of the policy. Decision analysis focuses on the establishment and measurement of the comprehensive evaluation index system of public policy. The economic analysis methods focus on the performance and output of technological innovation to test the policy effect. Finally, this paper puts forward the prospect of the future research direction.

Keywords: technology innovation, index, policy effectiveness, evaluation of policy, bibliometric analysis

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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 153

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

Procedia PDF Downloads 164

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 129

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

Procedia PDF Downloads 231

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

Procedia PDF Downloads 175

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

Procedia PDF Downloads 152

Authors: Sunho Seo, Younghwan Shin, Jong-Hong Park, Sooeun Song, Junsung Kim, Jusik Yun, Yongkyun Kim, Jong-Moon Chung

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In order to effectively cope with large and complex disasters, disaster response training is needed. Recently, disaster response training led by the ROK (Republic of Korea) government is being implemented through a 4 year R&D project, which has several similar functions as the HSEEP (Homeland Security Exercise and Evaluation Program) of the United States, but also has several different features as well. Due to the unpredictiveness and diversity of disasters, existing training methods have many limitations in providing experience in the efficient use of disaster incident response and recovery resources. Always, the challenge is to be as efficient and effective as possible using the limited human and material/physical resources available based on the given time and environmental circumstances. To enable repeated training under diverse scenarios, an AR (Augmented Reality) and VR (Virtual Reality) combined simulator is under development. Unlike existing disaster response training, simulator based training (that allows remote login simultaneous multi-user training) enables freedom from limitations in time and space constraints, and can be repeatedly trained with different combinations of functions and disaster situations. There are related systems such as ADMS (Advanced Disaster Management Simulator) developed by ETC simulation and HLS2 (Homeland Security Simulation System) developed by ELBIT system. However, the ROK government needs a simulator custom made to the country's environment and disaster types, and also combines the latest information and communication technologies, which include AR, VR, and MPEG-DASH (Moving Picture Experts Group - Dynamic Adaptive Streaming over HTTP) technology. In this paper, a new disaster response training simulator is proposed to overcome the limitation of existing training systems, and adapted to actual disaster situations in the ROK, where several technical features are described.

Keywords: augmented reality, emergency response training simulator, MPEG-DASH, virtual reality

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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

Procedia PDF Downloads 389

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

Procedia PDF Downloads 396

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: Chih-Jer Lin, Jian-Hong Hou

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Industry 4.0 is a vision of integrated industry implemented by artificial intelligent computing, software, and Internet technologies. The main goal of industry 4.0 is to deal with the difficulty owing to competitive pressures in the marketplace. For today’s manufacturing factories, the type of production is changed from mass production (high quantity production with low product variety) to medium quantity-high variety production. To offer flexibility, better quality control, and improved productivity, robot manipulators are used to combine material processing, material handling, and part positioning systems into an integrated manufacturing system. To implement the automated system for sheet metal bending operations, motion planning of a 7-degrees of freedom (DOF) robot is studied in this paper. A virtual reality (VR) environment of a bending cell, which consists of the robot and a bending machine, is established using the virtual robot experimentation platform (V-REP) simulator. For sheet metal bending operations, the robot only needs six DOFs for the pick-and-place or tracking tasks. Therefore, this 7 DOF robot has more DOFs than the required to execute a specified task; it can be called a redundant robot. Therefore, this robot has kinematic redundancies to deal with the task-priority problems. For redundant robots, Pseudo-inverse of the Jacobian is the most popular motion planning method, but the pseudo-inverse methods usually lead to a kind of chaotic motion with unpredictable arm configurations as the Jacobian matrix lose ranks. To overcome the above problem, we proposed a method to formulate the motion planning problems as optimization problem. Moreover, a genetic algorithm (GA) based method is proposed to deal with motion planning of the redundant robot. Simulation results validate the proposed method feasible for motion planning of the redundant robot in an automated sheet-metal bending operations.

Keywords: redundant robot, motion planning, genetic algorithm, obstacle avoidance

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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

Abstract:

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

Abstract:

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

Procedia PDF Downloads 85

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

Abstract:

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

Procedia PDF Downloads 49

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

Abstract:

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

Procedia PDF Downloads 256

Authors: Peijen Pamela Chuang, Tzu-Hua Wang

Abstract:

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

Procedia PDF Downloads 75

Authors: Szu-Hua Wang

Abstract:

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 188

Authors: Chris Schoborg, Morgan C. Wang

Abstract:

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 54

Authors: Zhaoan Wang

Abstract:

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 131