Increasingly, circular economy (CE) has been adopted globally to operationalize supply chain sustainability. The development of industry 4.0 technologies provides a new opportunity to improve the ...effectiveness and efficiency of adoption of CE, in particular, from the waste management perspective. More recently, scholars acknowledge the need for more studies on industry 4.0 and CE-driven sustainability aspects in supply chains. This research aims to fill the literature void and make a contribution from the perspective of smart waste management in supply chains using industry 4.0-based CE operations. Eleven key drivers were identified through semi-structured interviews, administered to experienced supply chain practitioners in China. A fuzzy DEMATEL method was used to analyse the interrelationships among these key drivers. The results show that the most fundamental causal drivers of smart waste management are overcoming operational challenges, recovering value, speeding up operations, saving cost and improving profit. There is a virtuous cycle between market demand and the improving price-performance ratio of industry 4.0 technologies. Our findings are part of the development of a bottom-up approach to adopting smart waste management in supply chains. The interrelationships identified in this research provide valuable insights into driving forces. Organizations, policy makers and technology providers can apply these insights when utilizing industry 4.0 technologies to improve supply chain waste management in line with the CE principle, and to achieve supply chain sustainability.
Past toy recalls have led to an increase in consumer concerns while toy manufacturers and retailers increasingly outsource and create longer supply chains, making it more challenging for them to ...ensure toy safety. This article examines firms making toy recall announcements to assess the impact operational characteristics have on the negative stock market reaction to the announcement. 135 toy recall announcements in the U.S. from 1979 to 2016 were analyzed using event study and cross-sectional regression. While a toy recall announcement results in a negative stock market reaction, our results show that greater levels of business diversification, inventory slack, and a longer time to recall are all associated with a less negative stock market reaction. In contrast, greater capacity slack is associated with a more negative stock market reaction. We find no evidence that geographic diversification or financial slack influences the stock market reaction, nor have reactions changed appreciably over time. This article contributes to the product harm and product recall literature by focusing on these operational elements. Managers should be aware of the benefits of greater slack and business diversification while planning their business, and the impact of a longer time to recall.
•Event study examined operational characteristics influence on impact of toy recall.•Greater inventory slack gives a less negative stock market reaction.•Longer time to recall gives less negative stock market reaction.•More business diversification gives a less negative stock market reaction.•Greater capacity slack gives a more negative stock market reaction.
This report aims to describe the restorative outcome of 5,491 implant-supported single crowns, fixed partial dentures, and splinted restorations that were prescribed or had implants placed during the ...study period. Timing of the complications and the relationship between the complications and different factors (practitioner, patient, and restoration) are examined.
Dental clinicians qualified in or before December 2004, registered in Victoria, and placing and/or restoring implants in private practice were invited to participate in the study. Data extraction was conducted by two trained and calibrated research assistants with specific training in implant terminology and previous research experience extracting data from dental records. Prostheses average time observed/in function was calculated using the difference between the definitive restoration date and the patient record examination date or the date of implant/restoration lost. Both descriptive statistics and generalized linear mixed modeling were used to describe the restorative complications.
Over the study period a total of 499 mechanical complications were recorded. Single-implant crowns had the largest sample size (n = 4,760) and a recorded complication rate of 2.56 per 100 prostheses per year. The majority of screw loosenings recorded in this study were inadequately described. In single-implant crowns, abutment screw loosening occurred at a rate of 0.07 per 100 per year while unspecified screw loosening occurred at a rate of 0.53. Lateral screw loosening was more common in lateral screw-retained implant crowns (1.06) than decementation was in cement-retained implant crowns (0.57). Esthetics (0.25), veneer chipping or fracture (0.41), and food packing/contact point issues (0.53) also represent significant portions of the restorative complications. Each type of complication presented with a slightly different timing profile. Clustering within the first year was common. The ratio of screw loosening between the group who prescribed between 1 and 100 during the study period and those who prescribed more than 501 implant restorations was 1:0.15 (P = .005). Patients with operator-reported attrition had double the rate of veneer fracture (P = .005). Contact point issues were approximately three times more common in the posterior segment (P = .001).
During the period of January 2005 to December 2009, screw loosening, lateral screw loosening, decementation, esthetic complication, veneer chipping or fracture, and food packing/contact point issues were recorded at different rates for different types of prostheses in the private practices included in this study. Clusters of several complications within the first year were observed. For single-implant crowns, screw-loosening complications were less frequent in the more experienced group. Operator-reported attrition was related to higher rate of veneering material fracture. More contact point complications were found in the posterior regions of the oral cavity.
The creation of human induced pluripotent stem cells (hiPSCs) has provided an unprecedented opportunity to study tissue morphogenesis and organ development through 'organogenesis-in-a-dish'. Current ...approaches to cardiac organoid engineering rely on either direct cardiac differentiation from embryoid bodies (EBs) or generation of aligned cardiac tissues from predifferentiated cardiomyocytes from monolayer hiPSCs. To experimentally model early cardiac organogenesis in vitro, our protocol combines biomaterials-based cell patterning with stem cell organoid engineering. 3D cardiac microchambers are created from 2D hiPSC colonies; these microchambers approximate an early-development heart with distinct spatial organization and self-assembly. With proper training in photolithography microfabrication, maintenance of human pluripotent stem cells, and cardiac differentiation, a graduate student with guidance will likely be able to carry out this experimental protocol, which requires ∼3 weeks. We envisage that this in vitro model of human early heart development could serve as an embryotoxicity screening assay in drug discovery, regulation, and prescription for healthy fetal development. We anticipate that, when applied to hiPSC lines derived from patients with inherited diseases, this protocol can be used to study the disease mechanisms of cardiac malformations at an early stage of embryogenesis.
Healthy skeletal muscle possesses the extraordinary ability to regenerate in response to small‐scale injuries; however, this self‐repair capacity becomes overwhelmed with aging, genetic myopathies, ...and large muscle loss. The failure of small animal models to accurately replicate human muscle disease, injury and to predict clinically‐relevant drug responses has driven the development of high fidelity in vitro skeletal muscle models. Herein, the progress made and challenges ahead in engineering biomimetic human skeletal muscle tissues that can recapitulate muscle development, genetic diseases, regeneration, and drug response is discussed. Bioengineering approaches used to improve engineered muscle structure and function as well as the functionality of satellite cells to allow modeling muscle regeneration in vitro are also highlighted. Next, a historical overview on the generation of skeletal muscle cells and tissues from human pluripotent stem cells, and a discussion on the potential of these approaches to model and treat genetic diseases such as Duchenne muscular dystrophy, is provided. Finally, the need to integrate multiorgan microphysiological systems to generate improved drug discovery technologies with the potential to complement or supersede current preclinical animal models of muscle disease is described.
Human tissue‐engineered skeletal muscles hold promise as a novel tool to study muscle pathophysiology in vitro. Herein, the biology of muscle development is reviewed and the progress made in generating functional human engineered muscle tissues from primary and induced pluripotent stem cells is highlighted. The utility of these microphysiological systems for disease modeling and patient‐specific drug development is further discussed.
We report a mild, electrochemical trihydrodefluorination (e-THDF) for breaking highly stable C-F bonds in trifluoromethyl arenes to form the corresponding methyl arene products. Uniquely, this ..."green" approach relies on the
in situ
generation of Lewis acidic silyl cations that mediate fluoride abstraction. Overall, e-THDF has significantly improved functional group tolerance over current methods and should inspire the continued development of defluorinative processes.
We report a mild, electrochemical trihydrodefluorination (e-THDF) for breaking highly stable C-F bonds in trifluoromethyl arenes to form the corresponding methyl arene products.
Abstract
We present high-resolution
K
-band emission spectra of the quintessential hot Jupiter HD 189733 b from the Keck Planet Imager and Characterizer. Using a Bayesian retrieval framework, we fit ...the dayside pressure–temperature profile, orbital kinematics, mass-mixing ratios of H
2
O, CO, CH
4
, NH
3
, HCN, and H
2
S, and the
13
CO/
12
CO ratio. We measure mass fractions of
logH
2
O
=
−
2.0
−
0.4
+
0.4
and
logCO
=
−
2.2
−
0.5
+
0.5
, and place upper limits on the remaining species. Notably, we find logCH
4
< −4.5 at 99% confidence, despite its anticipated presence at the equilibrium temperature of HD 189733 b assuming local thermal equilibrium. We make a tentative (∼3
σ
) detection of
13
CO, and the retrieved posteriors suggest a
12
C/
13
C ratio similar to or substantially less than the local interstellar value. The possible
13
C enrichment would be consistent with accretion of fractionated material in ices or in the protoplanetary disk midplane. The retrieved abundances correspond to a substantially substellar atmospheric C/O = 0.3 ± 0.1, while the carbon and oxygen abundances are stellar to slightly superstellar, consistent with core-accretion models which predict an inverse correlation between C/O and metallicity. The specific combination of low C/O and high metallicity suggests significant accretion of solid material may have occurred late in the formation process of HD 189733 b.
The dialkyl-ortho-biaryl class of phosphines, commonly known as Buchwald-type ligands, are among the most important phosphines in Pd-catalyzed cross-coupling. These ligands have also been ...successfully applied to several synthetically valuable Ni-catalyzed cross-coupling methodologies and, as demonstrated in this work, are top performing ligands in Ni-catalyzed Suzuki Miyaura Coupling (SMC) and C–N coupling reactions, even outperforming commonly employed bisphosphines like dppf in many circumstances. However, little is known about their structure–reactivity relationships (SRRs) with Ni, and limited examples of well-defined, catalytically relevant Ni complexes with Buchwald-type ligands exist. In this work, we report the analysis of Buchwald-type phosphine SRRs in four representative Ni-catalyzed cross-coupling reactions. Our study was guided by data-driven classification analysis, which together with mechanistic organometallic studies of structurally characterized Ni(0), Ni(I), and Ni(II) complexes allowed us to rationalize reactivity patterns in catalysis. Overall, we expect that this study will serve as a platform for further exploration of this ligand class in organonickel chemistry as well as in the development of new Ni-catalyzed cross-coupling methodologies.
Use of computational methods to predict gene regulatory networks (GRNs) from gene expression data is a challenging task. Many studies have been conducted using unsupervised methods to fulfill the ...task; however, such methods usually yield low prediction accuracies due to the lack of training data. In this article, we propose semi-supervised methods for GRN prediction by utilizing two machine learning algorithms, namely, support vector machines (SVM) and random forests (RF). The semi-supervised methods make use of unlabelled data for training. We investigated inductive and transductive learning approaches, both of which adopt an iterative procedure to obtain reliable negative training data from the unlabelled data. We then applied our semi-supervised methods to gene expression data of
Escherichia coli
and
Saccharomyces cerevisiae
, and evaluated the performance of our methods using the expression data. Our analysis indicated that the transductive learning approach outperformed the inductive learning approach for both organisms. However, there was no conclusive difference identified in the performance of SVM and RF. Experimental results also showed that the proposed semi-supervised methods performed better than existing supervised methods for both organisms.
Abstract
Inference is crucial in modern astronomical research, where hidden astrophysical features and patterns are often estimated from indirect and noisy measurements. Inferring the posterior of ...hidden features, conditioned on the observed measurements, is essential for understanding the uncertainty of results and downstream scientific interpretations. Traditional approaches for posterior estimation include sampling-based methods and variational inference (VI). However, sampling-based methods are typically slow for high-dimensional inverse problems, while VI often lacks estimation accuracy. In this paper, we propose
α
-deep probabilistic inference, a deep learning framework that first learns an approximate posterior using
α
-divergence VI paired with a generative neural network, and then produces more accurate posterior samples through importance reweighting of the network samples. It inherits strengths from both sampling and VI methods: it is fast, accurate, and more scalable to high-dimensional problems than conventional sampling-based approaches. We apply our approach to two high-impact astronomical inference problems using real data: exoplanet astrometry and black hole feature extraction.
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