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Photocatalytic H2O2 production from water and air using porous organic polymers
No full textProducing hydrogen peroxide (H2O2) from H2O and O2 under visible light irradiation is a promising solar-to-chemical energy conversion technology. Hydrogen peroxide has versatile applications as a green oxidant and liquid energy carrier but has been produced through energy-intensive and complex anthraquinone processes. Herein, we report the rational design of efficient and stable porous organic polymer (POP) containing redox centers, anthraquinone photocatalyst (ANQ-POP) for solar H2O2 production. ANQ-POP is readily synthesized with stable dioxin-linkages via efficient one-pot, transition-metal-free nucleophilic aromatic substitution reactions between 1,2,3,4,5,6,7,8-octafluoro-9,10-anthraquinone (OFANQ) and 2,3,6,7,10,11-hexahydroxytriphenylene (HHTP). Exhibiting a fibrillar morphology, ANQ-POP boasts a high surface area of 380 m2???g???1 and demonstrates thermal stability. With 10 % ethanol, ANQ-POP yields an H2O2 production rate of 320 ??mol g???1 under visible light irradiation. Moreover, ANQ-POP alone can efficiently produce H2O2 without any photosensitizers and cocatalysts. Density functional theory calculations reveal that the quinone groups of the anthraquinone moieties can serve as redox centers for H2O2 production under light irradiation. Furthermore, unlike most conventional photocatalysts, it can produce H2O2 using only water and air by catalyzing both oxygen reduction and evolution reactions under light irradiation. Our findings provide an efficient, eco-friendly pathway for photocatalytic production of H2O2 under mild reaction conditions using a dioxin-derived POP-based photocatalyst
Alkylation of nucleobases by 2-chloro-N,N-diethylethanamine hydrochloride (CDEAH) sensitizes PARP1-deficient tumors
No full textTargeting BRCA1-and BRCA2-deficient tumors through synthetic lethality using poly(ADP-ribose) polymerase inhibitors (PARPi) has emerged as a successful strategy for cancer therapy. PARPi monotherapy has shown excellent efficacy and safety profiles in clinical practice but is limited by the need for tumor genome mutations in BRCA or other homologous recombination genes as well as the rapid emergence of resistance. In this study, we identified 2-chloro-N,N-diethylethanamine hydrochloride (CDEAH) as a small molecule that selectively kills PARP1-and xeroderma pigmentosum A-deficient cells. CDEAH is a monofunctional alkylating agent that preferentially alkylates guanine nucleobases, forming DNA adducts that can be removed from DNA by either a PARP1-dependent base excision repair or nucleotide excision repair. Treatment of PARP1-deficient cells leads to the formation of strand breaks, an accumulation of cells in S phase and activation of the DNA damage response. Furthermore, CDEAH selectively inhibits PARP1-deficient xenograft tumor growth compared to isogenic PARP1-proficient tumors. Collectively, we report the discovery of an alkylating agent inducing DNA damage that requires PARP1 activity for repair and acts synergistically with PARPi
Antecedents of circular manufacturing and its effect on environmental and financial performance: A practice-based view
No full textDespite the worldwide recognition of the Circular Economy (CE) philosophy, its comprehensive adoption in manufacturing is not well understood in literature and practice. This study theorizes circular manufacturing (CM) by extending the cleaner production concept according to the design thinking of CE. Drawing on the practice-based view, it develops a conceptual model on the antecedents and performance outcomes of CM and the moderating role of Industry 4.0 (I4.0) production technologies on CM-to-environmental and financial per-formance relationships. The research adopts a mixed-methods approach to examine the hypothesized relation-ships. Survey data from 255 Chinese manufacturers are analyzed using structural equation modeling and hierarchical regression. Two qualitative case studies verify the survey findings and offer additional insights. The findings suggest that by strengthening a CE culture and integrated management systems, firms can improve CM implementation and consequently environmental and financial performance. However, investing in I4.0 pro-duction technologies may not enhance the impact. Our research contributes to the literature by conceptualizing and operationalizing CM as a new construct. It also provides guidelines for implementing CE in manufacturing
Magnetite nanoparticles embedded on reduced graphene oxide as an anode material for high capacity and long cycle-life Li-ion battery
No full textA facile and cost-effective method was developed for the synthesis of "magnetite/reduced graphene oxide" nanocomposite, as an anode material for lithium-ion batteries. The fabricated composite was characterized by different instrumental analyses including XRD, Raman, XPS, SEM, TEM, and FTIR, as well as various electro-chemical (i.e. battery) tests. Such broad examination revealed the structure of the prepared material and its electrochemical behavior. It was found that the fabricated composite has a number of advantages over the currently utilized electrode materials such as cost efficiency, high Li ion storage (2528 mAh/g at 0.05 A/g at 1st discharge), cycle stability of 986 mAh/g over 100 cycles at a current density of 0.1 A/g, and eventually Coulombic efficiency of about 100 %. In comparison, the reduced graphene oxide (rGO) shows inferior per-formances, such as a constant capacity of 462 mAh/g, and a slower kinetics of the ion storage. Consequently, the synthesized low-cost anode material seems to be an attractive candidate for development of the next-generation energy-storage devices, used in electrical vehicles, and portable electronic instruments
Image-free Domain Generalization via CLIP for 3D Hand Pose Estimation
No full textRGB-based 3D hand pose estimation has been successful for decades thanks to large-scale databases and deep learning. However, the hand pose estimation network does not operate well for hand pose images whose characteristics are far different from the training data. This is caused by various factors such as illuminations, camera angles, diverse backgrounds in the input images, etc. Many existing methods tried to solve it by supplying additional large-scale unconstrained/target domain images to augment data space; however collecting such large-scale images takes a lot of labors. In this paper, we present a simple image-free domain generalization approach for the hand pose estimation framework that uses only source domain data. We try to manipulate the image features of the hand pose estimation network by adding the features from text descriptions using the CLIP (Contrastive Language-Image Pretraining) model. The manipulated image features are then exploited to train the hand pose estimation network via the contrastive learning framework. In experiments with STB and RHD datasets, our algorithm shows improved performance over the state-of-the-art domain generalization approaches
Process-Data Quality: The True Frontier of Process Mining
No full textSince its emergence over two decades ago, process mining has flourished as a discipline, with numerous contributions to its theory, widespread practical applications, and mature support by commercial tooling environments. However, its potential for significant organisational impact is hampered by poor quality event data. Process mining starts with the acquisition and preparation of event data coming from different data sources. These are then transformed into event logs, consisting of process execution traces including multiple events. In real-life scenarios, event logs suffer from significant data quality problems, which must be recognised and effectively resolved for obtaining meaningful insights from process mining analysis. Despite its importance, the topic of data quality in process mining has received limited attention. In this paper, we discuss the emerging challenges related to process-data quality from both a research and practical point of view. Additionally, we present a corresponding research agenda with key research directions
Enhancing water oxidation catalysis by controlling metal cation distribution in layered double hydroxides
No full textThe sluggish kinetics of the oxygen evolution reaction (OER), the limiting step of the electrochemical water splitting process, hinders the eventual commercialization of this important renewable energy strategy. Hence, the development of efficient electrocatalysts for this reaction is crucial. Multi-metal-based (hydr)oxides are promising OER electrocatalysts because the electronic interactions between multiple constituent metal cations can potentially enhance electrochemical performances. However, complex compositions may not always lead to positive synergistic effects. The appropriate distribution of the cations is also critical. However, the high dispersibility of cations in these hydroxides renders the control of their distribution challenging. Herein, an approach is reported to control the metal cation distribution in layered double hydroxides (LDHs) to improve their OER performances. Restacking of exfoliated NiFe and CoAl LDH nanosheets leads to electrochemical synergistic effects between different nanosheets. As far as it is known, the restacked LDH described herein exhibits the lowest overpotential (224 mV) and Tafel slope (34.26 mV dec???1) among reported powder-type (hydr)oxide and alloy OER electrocatalysts with more than three different metal cations. Thus, a new design approach is suggested to enhance the electrochemical performances of LDHs
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No full textSeismic fragility curves play a crucial role in assessing potential seismic losses and predicting structural damage caused by earthquakes. This study compares non-sampling-based methods of seismic fragility curve derivation, particularly the probabilistic seismic demand model (PSDM) and finite element reliability analysis (FERA), both of which require employing sophisticated finite element analysis to evaluate and predict structural damage caused by earthquakes. In this study, a three-dimensional finite element model of API 5L X65, a buried gas pipeline widely used in Korea, is constructed to derive seismic fragility curves. Its seismic vulnerability is assessed using nonlinear time-history analysis. PSDM and a FERA are employed to derive seismic fragility curves for comparison purposes, and the results are verified through a comparison with those from the Monte Carlo Simulation (MCS). It is observed that the fragility curves obtained from PSDM are relatively conservative, which is attributed to the assumption introduced to consider the uncertainty factors. In addition, this study provides a comprehensive comparison of seismic fragility curve derivation methods based on sophisticated finite element analysis, which may contribute to developing more accurate and efficient seismic fragility analysis
