Sustainability, Vol. 15, Pages 16311: Optimal Green Technology Choice for Firms under an Emission Trading Scheme: End of Pipe vs. Cleaner Production Sustainability doi: 10.3390/su152316311 Authors: Xuemei Yuan Shuai Jin Haibin Zhang Green technology innovation helps to improve both economic and environmental performance simultaneously. How to invest in green technology innovation under emission trading policy is a current issue worthy of attention. However, existing research has not delved into the choices of different green technology innovation models, namely cleaner production technology and end of pipe technology, available to firms and governments under the joint implementation of other policies. Thus, this paper studies the optimal model of green technology innovation under emission trading policy and emission tax policy by constructing a two stage game model suitable for complex decision analysis. The results show that regardless of the value of emission trading price, the optimal green technology innovation choice of the firms is cleaner production technology. Furthermore, the results show that neither conflict nor consistency always exists between governments and firms choices. When the emission trading price is high, the choice of governments and firms is in conflict; when the emission trading price is low, the choice of the two is consistent, both prefer cleaner production. This study not only enriches the existing research in theory but also provides support for governments to guide the choice of firms and achieve a win-win situation in practice.
In the era of smart computing, edge computing, and machine intelligence, the Internet of Things (IoT) is paving a greater role in establishing hyperconnective, cost effective infrastructure for monitoring the environment. With the increase in the level of urbanization, increasing air pollution in cities is an alarming situation. Therefore, it is necessary to continuously monitor the pollution and carry out spatial analysis of the changes in air pollution on a real time basis. To monitor and manage air pollutants, it is essential to put in place monitoring stations to plan controlling measures. Although commercial pollution monitoring stations are present, they are limited in number, expensive, and fixed in specific strategic locations. A pollution monitoring system that can be replicated easily, automatically collects and analyzes data, and is cost effective is essential. This study has involved the development and experimentation of a network of smart IoT sensors in Nagpur metropolis. The developed smart air pollution monitoring system combines IoT technology with real time pollution monitoring. The developed smart air pollution monitoring system measures and monitors temperature, humidity and pollutant concentration of Carbon Monoxide, Ozone, Carbon Dioxide, Sulphur Dioxide and PM2.5 and Nitrous oxides simultaneously through one compact device. This paper discusses the architecture and design of the IoT system for air pollution monitoring, with a case study of its establishment in Nagpur metropolis. The study envisages to support Sustainable Development Goals - SDG11 which aims to reduce the environmental impact of cities by improving air quality.
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Class imbalance is one of many problems of customer churn datasets. One of the common problems is class overlap, where the data have a similar instance between classes. The prediction task of customer churn becomes more challenging when there is class overlap in the data training. In this research, we suggested a hybrid method based on tabular GANs, called CTGAN ENN, to address class overlap and imbalanced data in datasets of customers that churn. We used five different customer churn datasets from an open platform. CTGAN is a tabular GAN based oversampling to address class imbalance but has a class overlap problem. We combined CTGAN with the ENN under sampling technique to overcome the class overlap. CTGAN ENN reduced the number of class overlaps by each feature in all datasets. We investigated how effective CTGAN ENN is in each machine learning technique. Based on our experiments, CTGAN ENN achieved satisfactory results in KNN, GBM, and XGB machine learning performance for customer churn predictions. We compared CTGAN ENN with common over sampling and hybrid sampling methods, and CTGAN ENN achieved outperform results compared with other sampling methods. We provide a time consumption algorithm between CTGAN and CTGAN ENN. CTGAN ENN achieved less time consumption than CTGAN. Our research work provides a new framework to handle customer churn prediction problems with several types of imbalanced datasets and can be useful in real world data from customer churn prediction.
Background Tuberculosis (TB) is caused by a bacterium called Mycobacterium tuberculosis (Mtb). The incidence of TB patients is increasing globally and the wide spread of multi and extensively drug resistant TB poses a significant burden to patients. This situation calls for an urgent medical need to develop new anti TB drugs. Through our proprietary medicinal chemistry platform on D series 26 membered thiopeptide, we have identified a few lead compounds, such as AJ 099 and AJ 206 that exert potent activity against multi drug resistant TB strains.
Method In vitro minimal inhibitory concentration (MIC) was measured and a Mtb infected human macrophage model was used to evaluate anti mycobacterial activity of our compounds in drug sensitive or multidrug resistant TB isolates. Cellular toxicity and some in vitro ADME tests were also performed and examined.
Result We found that our lead compounds exert potent anti TB activity on H37Rv(MIC: 0.125 0.5 Î¼g/mL) and showed similar MIC levels in multidrug resistant clinical isolates. In the macrophage infection model, AJ 099 and AJ 206 showed comparable antimycobacterial effects to isoniazid. These compounds showed no cytotoxicity, relatively safe ADME properties, and no hERG inhibition. In vitro antibacterial activity in multi drug resistant M. tuberculosis strainsAntibacterial activity in macrophage infection modelIn vitro ADMET properties of lead compounds
Conclusion AJ 099 and AJ 206 may be potential anti TB therapeutic agents that possess novel modes of action, low cardiac and cellular toxicities. DisclosuresYoung Jin Son, A&J Science: Employee of A&J Science| A&J Science: Ownership Interest| KHIDI: Grant/Research Support Hee Jong Hwang, PhD, A&J Science: Stocks/Bonds| KHIDI: Grant/Research Support Clovis Shyaka, n/a, A&J Science: Employee of A&J Science Dahyun Kim, n/a, A&J Science: Employee of A&J Science Jusuk Lee, Ph. D., A&J Science: Employee of A&J Science
Microstructural and mechanical evolution of sintered nano silver joints on bare copper substrates during high temperature storageMeng Jiang, Yang Liu, Ke Li, Zhen Pan, Quan Sun, Yongzhe Xu, Yuan TaoSoldering & Surface Mount Technology, Vol. ahead of print, No. ahead of print, pp. The purpose of this paper is to study the reliability of sintered nano silver joints on bare copper substrates during high temperature storage (HTS).In this study, HTS at 250 °C was carried out to investigate the reliability of nano silver sintered joints. Combining the evolution of the microstructure and shear strength of the joints, the degradation mechanisms of joints performance were characterized. The results indicated that the degradation of the shear properties of sintered nano silver joints on copper substrates was attributed to copper oxidation at the silver/copper interface and interdiffusion of interfacial elements. The joints decreased by approximately 57.4% compared to the original joints after aging for 500 h. In addition, severe coarsening of the silver structure was also an important cause for joints failure during HTS.This paper provides a comparison of quantitative and mechanistic evaluation of sintered silver joints on bare copper substrates during HTS, which is of great importance in promoting the development of sintered silver technology.
The integration of low carbon technologies and more efficient power system operation are key components in the transition to a sustainable future. To support this, power system operators are leveraging data from an ever expanding network of sensors. Due to their ability to measure several different physical parameters, fiber optic sensors are recognized as an important enabling technology and offer many interesting opportunities to improve situational awareness in power systems. This paper presents an extensive overview of fiber optic sensors in power system applications, with particular focus on the needs of the power system sector and how these may change as the system continues to evolve. The intention is to provide the reader with a review that clearly discusses the current and future trends in power system sensors applications and connect these to the most recent developments in fiber optic sensor technology.
Purpose The high energy photon source (HEPS) is the first fourth generation synchrotron photon source in China (Jiang et al. in Sci Sin Phys Mech Astron 44:1075–1094, 2014). The strip electrode and its power supply provide necessary hardware support for correcting the magnetic field of the wiggler as reported by Zhao and Yin (Particle accelerator technology, Higher Education Press, Beijing, 2006). The design of the conventional power supply for accelerators, with a large output current and high output voltage, making it easy to achieve high stability of the output current. The strip electrode power supply poses difficulties in achieving high stability due to its small output current and voltage. Because of size limitations, as well as the requirements of the power architecture, there are currently no commercial products for this type of power supply.
Method Designed and developed 32 strip electrode power supplies. Considering the large number of power supplies and limited space, a rack structure design was adopted, placing all power supplies in one rack. The main circuit of the power supply adopts a full bridge transformation structure (Chao et al. in Radiat Detect Technol
Method 6:470–478, 2022), and the control scheme adopts full digital control based on FPGA (Long and Cheng in At Energy Sci Technol 43:780–784, 2009). The power supply has two control modes: local operation and remote operation as reported by Lu (Particle accelerator technology, Hunan University, Changsha, 2010).
Result The test shows that all power supplies meet the indicator requirements, with a stability of less than 100 ppm.
Conclusions The strip electrode power supply can effectively correct the multipole integral field error and improve the integral field performance of the wiggler.
In the last 50 years, the impressive results on chemical kinetics from crossed molecular beam experiments have been assisted by theoretical and particularly computational progress, among which are: (1) the design and implementation of the SIMBEX (SImulation of Molecular Beam EXperiments) procedure on parallel and distributed computers aimed at rationalizing the dynamical behavior of the investigated systems on the ab initio computed molecular interactions; (2) the establishing of theoretical and computational research and educational networks (like the Quantum Reactive Scattering and European Chemistry Thematic Network), the assembling of virtual research communities (like the meta and the grid chemistry ones within the Collaboration in Science and Technology (COST) initiatives to enhance synergic and cooperative work levering on highly productive platforms; (3) the participation in the management of both the Italian and the European grid infrastructures initiatives; (4) the development of molecular open science enabled cloud services within the European Open Science Cloud (EOSC). Levering on the mentioned collaborative efforts, important open science initiatives have been implemented. The present paper illustrates a prototype model apparatus for the production of methane out of CO2 using renewable energy sources and a prosumer (producer–consumer) model for delivering online chemistry competence tests. Finally, a suggestion is made to establish networked local services of the academy for high school education.
Science communication plays a pivotal role in cultural engagement and life long science learning. However, historically marginalized communities remain undervalued in these efforts due to practices that prioritize specific individuals, such as those who are affluent, college educated, able bodied, and already scientifically engaged. Science communicators can avoid these practices by acknowledging the intersecting historical and cultural dimensions surrounding science beyond those of the majority culture and practicing inclusive science communication efforts. Here, we define and describe the importance of inclusive science communication and outline how we use an asset based community engagement framework in a place based education program"s communication practices with rural communities in the Southwestern United States. We describe how we designed our communication spaces, found our voice, and effectively communicate with non English speaking and bilingual communities. We provide examples from the We are Water program, demonstrating how we utilize inclusive science communication practices to engage more widely with diverse communities and create space for community voices to be heard and shared. We conclude that the use of inclusive science communication strategies and an asset based community engagement framework has allowed the We are Water program to connect with rural communities while communicating in a way that elevates historically marginalized voices, creates space for communities to share their own experiences through memories and stories, and honors diverse perspectives and ways of knowing.
A double edged sword: social media use and creativityGuangxi Zhang, Sunfan MaoInformation Technology & People, Vol. ahead of print, No. ahead of print, pp. The use of social media is an integral part of modern life, yet the impact of social media on creativity is a paradox. Drawing on the conservation of resources theory, the authors propose that social media, as an ecological condition, both nurture and deplete resources. Accordingly, the authors investigated two inconsistent mechanisms: creative self efficacy and ego depletion. Study 1 established the within person effects of social media use on creativity by tracking 64 college students for five working days. Using a sample of 493 employee–leader matched dyads in a national bank, Study 2 tested the entire model. Study 3 is a follow up experiment based on a sample of 160 participants. The results consistently showed that: (1) social media use had a positive impact on creativity in general; (2) social media use increased ego depletion and creative self efficacy, which were two inconsistent mediators; (3) hedonic use of social media reduced the negative impact of cognitive use of social media on ego depletion. This research sheds new light on the paradox between social media use and creativity and highlights the benefits of the balanced use of social media features. This research has implications for creative stimulation and job design in digital contexts.
Background Thiopeptides are structurally complex natural products that exert potent antimicrobial activity against Gram positive pathogens by inhibiting bacterial protein synthesis. However, there has not been any attempt to conduct extensive medicinal chemistry campaign on these natural products, due to their chemical complexity. The advent of efficient syntheses of thiopeptides led us to identify promising pre clinical candidates: AJ 024 against Clostridioides difficile and AJ 147 against Staphylococcus aureus for the indication of impetigo.
Method AJ 024 was screened against extensively classified C. difficile clinical isolates. Its time kill kinetics and in vivo mouse efficacy were investigated against hypervirulent C. difficile ribotype 027. Metagenomic sequencing (16S rRNA) was performed to examine AJ 024"s impact on gut microbiome. Similarly, AJ 147 was screened against methicillin resistant S. aureus clinical isolates. Its time kill kinetics, as well as its in vivo SSTI model were investigated. Pro inflammatory cytokines were measured. Pharmacokinetic studies of these two agents, as well as their ADME properties and toxicity have also been investigated.
Result AJ 024 has potent antibacterial activity, along with rapid bactericidal action against C. difficile ribotype 027 resulting in 99.99% reduction in 4X MIC in 3 hours. No recurrence was observed in the mouse in vivo model and this was corroborated by our 16S rRNA sequencing data. AJ 024 exerts minimal impact on beneficial gut microbiome. AJ 147 exhibited a potent antibacterial activity against mupirocin resistant S. aureus. In vivo efficacy in a SSTI model revealed that AJ 147 is x1,000 more active than mupirocin. AJ 147 downregulates pro inflammatory cytokines, such as IL 1Ã and IL 6, that might elicit beneficial host immune response. Impact of AJ 024 on gut microbiomeInvestigation of AJ 024"s impact on gut microbiome through 16s rRNA sequencingIn vivo efficacy of AJ 147 in SSTI modelAJ 147 compares favorably to mupirocin and downregulates pro inflammatory cytokines
Conclusion Our medicinal chemistry campaign on thiopeptide antibiotics have led us to identify two preclinical candidates, AJ 024 and AJ 147. These two agents possess distinctive advantages compared to the first line of treatments for each indication. Efforts are being directed to the completion of IND enabling studies. DisclosuresHee Jong Hwang, PhD, A&J Science: Stocks/Bonds| KHIDI: Grant/Research Support Young Jin Son, A&J Science: Employee of A&J Science| A&J Science: Ownership Interest| KHIDI: Grant/Research Support Dahyun Kim, n/a, A&J Science: Employee of A&J Science Jusuk Lee, Ph. D., A&J Science: Employee of A&J Science Clovis Shyaka, n/a, A&J Science: Employee of A&J Science
There is an urgent demand to reduce the plastic mass as it has become a serious environmental concern. Plastic bottles made of PET (polyethylene terephthalate) have been widely used for water, milk, and other beverages packaging. PET blow molding process has sought researchers’ attention for the fabrication of light weight PET bottles with reduced cost. In this study, lightweight PET bottles were fabricated by reducing the weight of PET, usually used for manufacturing PET bottle in industry. Here, initially computer simulation was performed for designing the preform with reduced weight and the stretch blow molding process was used to fabricate carbonated soft drink PET bottles. The computer simulation was performed under the same conditions as the experiment using non isothermal models to analyze the blowing phenomena, velocity, temperature, thickness distributions, and stretch ratio through stretching path of PET bottles. Experimental and simulation results were compared with existing PET bottle to confirm that the stretch blow molding simulation was significant for designing and fabricating of weight reduced PET bottle through the stretch blow molding process.
Tips and trips: a structural model of guests’ intentions to stay and tip for AI based services in hotelsCristian Morosan, Aslihan Dursun CengizciJournal of Hospitality and Tourism Technology, Vol. ahead of print, No. ahead of print, pp. Given the rapid development in artificial intelligence (AI), the hotel industry is deploying AI based systems. In line with this important development, this study aims to examine the impact of trust in the hotel and AI related performance ambiguity on consumers’ engagement with AI based systems. This study ultimately examined the impact of engagement on consumers’ intentions to stay in hotels offering such systems, and intentions to tip. This study developed a conceptual model based on the social cognition theory. The study used an online survey methodology and collected data from a nationwide sample of 400 hotel consumers from the USA. The data analysis was conducted with structural equation modeling. Consumers’ engagement is strongly influenced by their trust in the hotel but not by performance ambiguity associated with AI. In turn, engagement strongly influenced consumers’ intentions to stay in hotels that have such systems and their intentions to tip. As AI systems capable of making decisions for consumers are becoming increasingly present in hotels, little is known about the way consumers engage with such systems and whether their engagement leads to economic impact. This is the first study that validated a model that explains intentions to stay and tip for services facilitated by autonomous AI based systems that can make decisions for consumers.鉴于人工智能领域的快速发展, 酒店业正在部署基于人工智能的系统。为此, 本研究探讨了客人对酒店的信任和与AI相关的性能模糊性对消费者与基于AI的系统互动的影响。最终, 本研究考察了参与度对客人在提供此类系统的酒店住宿意愿和小费意愿的影响。本研究基于社会认知理论开发了一个概念模型。研究采用在线调查方法, 从美国全国范围的400名酒店消费者中收集数据, 并采用结构方程建模进行数据分析。消费者的参与度受酒店的信任强烈影响, 但不受与AI相关的性能模糊性的影响。反过来, 参与度强烈影响了消费者在提供此类系统的酒店住宿和给小费的意愿。随着能够代表消费者做出决策的人工智能（AI）系统在酒店中日益普及, 人们对消费者如何与这类系统互动以及他们的互动是否会产生经济影响知之甚少。这是第一项验证了一个可以解释在自主的基于AI系统的服务下住宿和给小费意愿的模型的研究。