•New dynamic predictive maintenance framework.•Complete process from data-driven prognostics to maintenance decisions.•New data-driven prognostics method based on the Long Short-Term Memory ...classifier.•Discussion of imperfect prognostics information impact on maintenance decisions.•Verification of the proposed methodology performance through a real application.
In Prognostic Health and Management (PHM) literature, the predictive maintenance studies can be classified into two groups. The first group focuses on the prognostics step but does not consider the maintenance decisions. The second group addresses the maintenance optimization question based on the assumptions that the prognostics information or the degradation models of the system are already known. However, none of the two groups provides a complete framework (from data-driven prognostics to maintenance decisions) investigating the impact of the imperfect prognostics on maintenance decision. Therefore, this paper aims to fill this gap of literature. It presents a novel dynamic predicive maintenance framework based on sensor measurements. In this framework, the prognostics step, based on the Long Short-Term Memory network, is oriented towards the requirements of operation planners. It provides the probabilities that the system can fail in different time horizons to decide the moment for preparing and performing maintenance activities. The proposed framework is validated on a real application case study. Its performance is highlighted when compared with two benchmark maintenance policies: classical periodic and ideal predicted maintenance. In addition, the impact of the imperfect prognostics information on maintenance decisions is discussed in this paper.
The identification of the active sites for the electrochemical reduction of CO2 (CO2RR) to specific chemical products is elusive, owing in part to insufficient data gathered on clean and atomically ...well‐ordered electrode surfaces. Here, ultrahigh vacuum based preparation methods and surface science characterization techniques are used with gas chromatography to demonstrate that subtle changes in the preparation of well‐oriented Cu(100) and Cu(111) single‐crystal surfaces drastically affect their CO2RR selectivity. Copper single crystals with clean, flat, and atomically ordered surfaces are predicted to yield hydrocarbons; however, these were found experimentally to favor the production of H2. Only when roughness and defects are introduced, for example by electrochemical etching or a plasma treatment, are significant amounts of hydrocarbons generated. These results show that structural and morphological effects are the key factors determining the catalytic selectivity of CO2RR.
Subtle changes in the preparation of well‐oriented Cu(100) and Cu(111) single‐crystal surfaces affect their CO2RR selectivity. Clean, flat, atomically ordered surfaces are predicted to yield hydrocarbons; but these actually favor production of H2. Only when roughness and defects are introduced, significant amounts of hydrocarbons are generated. Structural and morphological effects are the key factors determining the catalytic selectivity of CO2RR.
This study investigates the genuine impacts of education expansion, education inequality, and parental dependency on intergenerational mobility. It utilizes data from the Global Database on ...Intergenerational Mobility for 153 countries and cohorts born between the 1940s and 1980s. By employing a causal machine learning approach to address confounding problems, this research reveals that education expansion can promote intergenerational mobility to a certain extent. However, its effectiveness is partially diminished by education inequality and may be ineffective if parental dependency exists at a high level. Furthermore, this study also indicates that while gender inequality in intergenerational mobility still exists, its degree has been significantly reduced across generations. When compared to parental dependency, gender effects are far less important. Therefore, there is a need to reassess the roles of parental dependency and gender bias in intergenerational mobility, especially when parental dependency is currently underestimated, and gender bias is overemphasized.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Synthetic polymers have shown promise in combating multidrug‐resistant bacteria. However, the biological effects of sequence control in synthetic antimicrobial polymers are currently not well ...understood. As such, we investigate the antimicrobial effects of monomer distribution within linear high‐order quasi‐block copolymers consisting of aminoethyl, phenylethyl, and hydroxyethyl acrylamides made in a one‐pot synthesis approach via photoinduced electron transfer–reversible addition–fragmentation chain transfer polymerisation (PET‐RAFT). Through different combinations of monomer/polymer block order, antimicrobial and haemolytic activities are tuneable in a manner comparable to antimicrobial peptides.
The antimicrobial effects of monomer distribution within linear high‐order quasi‐block copolymers consisting of aminoethyl, phenylethyl, and hydroxyethyl acrylamides have been investigated. Sequence control results in bacterial genus specific killing.
This study explores how climate policy uncertainty (CPU) affects research and development (R&D) investment of heavy emitter firms in the United States during 2000–2019. Our empirical evidence ...indicates that while CPU exerts a positive impact on R&D investment of general firms, it seems to be a completely different story for heavy emitter firms. After a battery of sensitivity tests, we find a robust negative impact of CPU on R&D investment of heavy emitters, suggesting that those firms play a “wait‐and‐see” strategy in response to changes in environmental policies until more is known to make decisions. However, such behavior is not observed in light emitters. Even among heavy emitters, we show that the impact of CPU is only pronounced in heavy emitters with more technology uncertainty. Further analyses show such an impact varies with management sentiment, managerial ability, and firm maturity. Our findings have implications for policymaking and corporate strategy of heavy emitters in response to CPU.
The reasonable disposal of plant biomass containing heavy metals (HMs) is a difficult problem for the phytoremediation technology. This review summarizes current literature that introduces various ...disposal and utilization methods (heat treatment, extraction treatment, microbial treatment, compression landfill, and synthesis of nanomaterials) for phytoremediation plants with HMs. The operation process and technical parameters of each disposal method are different. HMs can migrate and transform in different disposal processes. Some disposal and utilization methods can get some by-products. The main purpose of this paper is to provide reference for technical parameters and characteristics of various disposal and utilization methods, so as to choose and use the appropriate method for the treatment of plant biomass containing HMs after phytoremediation.
•There are various methods for the treatment of plant biomass with heavy metals.•Heavy metals can migrate and transform in different disposal processes.•The operation process and technical parameters of each disposal method are different.•Many factors should be considered in choosing a reasonable disposal method.•The combination of multiple disposal methods can be considered.
In this work, two defective zirconium-based metal-organic frameworks (Zr-MOFs), MOF-808-OH and MOF-808-NH
2
, were synthesized by partially replacing the 1,3,5-benzenetricarboxylate building block ...with 5-hydroxyisophthalate and 5-aminoisophthalate, respectively. The structural features of the defective materials were analyzed by powder X-ray diffraction (PXRD), scanning electron microscopy (SEM), nitrogen physisorption at 77 K, and thermogravimetric analysis (TGA). Importantly, the number of defect sites determined
via
proton nuclear magnetic resonance (
1
H-NMR) analysis of the digested materials was approximately 7 mol% for MOF-808-OH and 3 mol% for MOF-808-NH
2
. The presence of the defect sites increased the number of acidic centers on Zr-clusters originating from missing-linker nodes which accounted for a remarkable adsorption capacity towards various anionic organic dyes and chromium (
vi
) species. Compared to standard MOF-808, the defect-engineered ones showed significant increments by 30-60% in trapping capacity for anionic contaminants including sunset yellow, quinoline yellow, methyl orange, and potassium dichromate, while they exhibited modest improvements by 5-15% in the removal of cationic dyes, namely malachite green and methylene blue.
Two defective MOF-808 materials synthesized by a facile mixed-linker approach show significantly higher adsorption capacity compared to standard MOF-808.
This paper sheds further lights on the environmental Kuznets curve literature by considering a new possible driving factor of environmental quality, the economic complexity. The results consistently ...show that there exists an inverted U-shaped relationship between economic complexity and CO
2
emissions.
The identification and isolation of genes underlying quantitative trait loci (QTLs) associated with agronomic traits in crops have been recently accelerated thanks to next-generation sequencing ...(NGS)-based technologies combined with plant genetics. With NGS, various revisited genetic approaches, which benefited from higher marker density, have been elaborated. These approaches improved resolution in QTL position and assisted in determining functional causative variations in genes. Examples of QTLs/genes associated with agronomic traits in crops and identified using different strategies based on whole-genome sequencing (WGS)/whole-genome resequencing (WGR) or RNA-seq are presented and discussed in this review. More specifically, we summarize and illustrate how NGS boosted bulk-segregant analysis (BSA), expression profiling, and the construction of polymorphism databases to facilitate the detection of QTLs and causative genes.
The swift development of next-generation sequencing (NGS) has accelerated quantitative trait locus (QTL) mapping and gene discovery in crops.
High-throughput NGS-based genotyping platforms provide an extensive capacity to develop comprehensive polymorphism datasets including SNPs, InDels, structural variations, and genomic rearrangement.
Whole-genome resequencing combined with bulk-segregant analysis offers a high density of informative SNPs, helping to detect QTLs without genotyping the entire mapping population. However, phenotyping of the entire population is still required.
RNA-seq is useful to simultaneously genotype and phenotype segregating populations, releasing genomic information on mRNA and expression levels.
Polymorphism databases generated by whole-genome sequencing using large-accession collections constitute new shared resources that facilitate QTL detection and gene discovery.
The world is in a clash between the perspectives of economic expansion and sustainable environment. The high pace of technological progress opens space for fostering economic growth but at the same ...time, it creates a big dilemma for humans in protecting the environmental quality. The environmentally specific technologies are expected to help human beings to achieve dual objectives of economic prosperity and environmental sustainability. Despite its importance, attention to the role of environmental-related technologies in reducing environmental degradation is limited. This paper, therefore, intends to discover the impact of environmental-related technologies on the ecological footprint for 20 OECD from 1990 to 2015. The results endorse a long-run relationship between ecological footprint and green technologies, renewable energy, international trade, energy intensity, and real income. Environmental-related technologies and renewable energy consumption are found to be impetuous to sustainable development. The study provides relevant implications for policymakers to support the development and adoption of green technologies.
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