Explore the vast range of titles available.

For its promise in enhancing sustainability, the global value chain (GVC) has grown in relevance and sparked many studies. Due to different value activities in multiple countries and industry clusters, the competition and cooperation among value chains have attracted the considerable attention of business leaders and academicians worldwide. GVC-related sustainability research is a niche area despite its widespread presence in the literature. To bridge the gap, we use scientometric analysis in this paper, examining the corpus of 753 articles published in Web of Science journals from 2001 till 2021. This review illuminates the research performance constituents (e.g., most prolific authors, nations, institutions, and journals), the themes and issues that underpin the fields’ intellectual structure, and transforming discoveries. GVC depends on nine basic clusters for sustainability research (i.e., global value chain participation, gendered global production network, repositioning organisational dynamics, labour stands, learning opportunities, Internet era). Future studies can be conducted to generate new knowledge across ten thematic (based on keywords) clusters (i.e., market liberalisation, trade pollution nexus, value chain dynamics, global value chain reconfiguration, non-governmental organisation, multipolar governance). A model that encompasses current knowledge of the global value chain for sustainability is developed, and avenues for future research are provided.

Protein side chain dynamics play a vital role in many biological processes, but differentiating mobile from rigid side chains remains a technical challenge in structural biology. Solution NMR spectroscopy is ideally suited for this but suffers from limited signal-to-noise, signal overlap, and a need for fractional 13C or 2H labeling. Here we introduce a simple strategy measuring initial 1H relaxation rates during a 1H TOCSY sequence like DIPSI-2, which can be appended to the beginning of any multi-dimensional NMR sequence that begins on 1H. The TOCSY RF field compels all 1H atoms to behave similarly under the influence of strong coupling and rotating frame cross-relaxation, so that differences in relaxation rates are due primarily to side chain mobility. We apply the scheme to a thermostable mutant Pin1 WW domain and demonstrate that the observed 1H relaxation rates correlate well with two independent NMR measures of side-chain dynamics, cross-correlated 13C relaxation rates in 13CβH2 methylene groups and maximum observable 3J couplings sensitive to the χ1 side chain dihedral angle (3JHα,Hβ, 3JN,Hβ, and 3JCO,Hβ). The most restricted side chains belong to Trp26 and Asn40, which are closely packed to constitute the folding center of the WW domain. None of the other conserved aromatic residues is as immobile as the first tryptophan side chain of the WW domain. The proposed 1H relaxation methodology should make it relatively easy to measure side chain dynamics on uniformly 15N- or 13C-labeled proteins, so long as chemical shift assignments are obtainable.

A poly(dimethylsiloxane-co-(3-aminopropyl)methylsiloxane) polymer (PDMS with 20.3 mol % of (3-aminopropyl)methyl siloxane monomer) has been labeled randomly with 1-pyreneacetyl groups to generate a series of polysiloxanes (Py-PDMS) with pyrenyl contents ranging from 0.7 mol % to 5.2 mol % of the total number of structural units. The remainder of the amino groups were acetylated to avoid intra-chain quenching of the excited singlet states of pyrene via exciplex formation with free amino groups while allowing the formation of excimers to proceed. The fluorescence spectra and temporal decays of the Py-PDMS samples were acquired in tetrahydrofuran (THF), N,N-dimethylformamide (DMF), and dioxane. blob, the average rate constant for intra-chain pyrene excimer formation, was determined from the analysis of the fluorescence decays. blob was found to equal 1.16 (±0.13) × 109, 1.14 (±0.12) × 109, and 0.99 (±0.10) × 109 s−1 in THF, DMF, and dioxane, respectively, at room temperature. They are the largest values found to date for any polymeric backbone in these solvents. The qualitative relationship found here between blob and the chemical structures of the polymers indicates that the luminescence characteristics of randomly labeled polymers is a very useful method to probe the long range dynamics of chains of almost any polymer that is amenable to substitution by a lumophore.

Entering the COVID-19 pandemic wreaked havoc on supply chains. Reacting to the pandemic and adaptation in the “new normal” have been challenging tasks. Exiting the pandemic can lead to some after-shock effects such as “disruption tails.” While the research community has undertaken considerable efforts to predict the pandemic’s impacts and examine supply chain adaptive behaviors during the pandemic, little is known about supply chain management in the course of pandemic elimination and post-disruption recovery. If capacity and inventory management are unaware of the after-shock risks, this can result in highly destabilized production–inventory dynamics and decreased performance in the post-disruption period causing product deficits in the markets and high inventory costs in the supply chains. In this paper, we use a discrete-event simulation model to investigate some exit strategies for a supply chain in the context of the COVID-19 pandemic. Our model can inform managers about the existence and risk of disruption tails in their supply chains and guide the selection of post-pandemic recovery strategies. Our results show that supply chains with postponed demand and shutdown capacity during the COVID-19 pandemic are particularly prone to disruption tails. We then developed and examined two strategies to avoid these disruption tails. First, we observed a conjunction of recovery and supply chain coordination which mitigates the impact of disruption tails by demand smoothing over time in the post-disruption period. Second, we found a gradual capacity ramp-up prior to expected peaks of postponed demand to be an effective strategy for disruption tail control.

The very long molecules found in synthetic polymers, and their tendency to entangle and partially crystallize, impart many of the polymers' useful properties. However, these same characteristics also mean that chain dynamics are slow, which impedes potential self-healing. Yanagisawa et al. developed a family of ether-thiourea linear polymers that form hydrogen-bonded networks and still manage to stay amorphous. The polymers are stiff, showing the strength of the hydrogen bonding; however, because these bonds can easily reform, the polymer is also able to self-heal when compressed. Science , this issue p. 72 A stiff amorphous polymer can be repaired without heating, solely by compression. Expanding the range of healable materials is an important challenge for sustainable societies. Noncrystalline, high-molecular-weight polymers generally form mechanically robust materials, which, however, are difficult to repair once they are fractured. This is because their polymer chains are heavily entangled and diffuse too sluggishly to unite fractured surfaces within reasonable time scales. Here we report that low-molecular-weight polymers, when cross-linked by dense hydrogen bonds, yield mechanically robust yet readily repairable materials, despite their extremely slow diffusion dynamics. A key was to use thiourea, which anomalously forms a zigzag hydrogen-bonded array that does not induce unfavorable crystallization. Another key was to incorporate a structural element for activating the exchange of hydrogen-bonded pairs, which enables the fractured portions to rejoin readily upon compression.

Soft and conformable wearable electronics require stretchable semiconductors, but existing ones typically sacrifice charge transport mobility to achieve stretchability. We explore a concept based on the nanoconfinement of polymers to substantially improve the stretchability of polymer semiconductors, without affecting charge transport mobility. The increased polymer chain dynamics under nanoconfinement significantly reduces the modulus of the conjugated polymer and largely delays the onset of crack formation under strain. As a result, our fabricated semiconducting film can be stretched up to 100% strain without affecting mobility, retaining values comparable to that of amorphous silicon. The fully stretchable transistors exhibit high biaxial stretchability with minimal change in on current even when poked with a sharp object. We demonstrate a skinlike finger-wearable driver for a light-emitting diode.

This research proposes an efficient analysis method with an implicit integration method for multibody chain dynamics. Absolute Cartesian coordinates which are related to the body reference frame are used as generalized coordinates. Contact between a sprocket and chain links is formulated as a circle to circle contact. Chain links are connected by bushing elements. Newton-Raphson method is used to solve the combined equations of motion, constraints, and implicit integration formulas. Jacobian matrix must be calculated and LU decomposed with the implicit integration method in Newton-Raphson method. Since Cartesian coordinates with respect to the body reference frame are used as the generalized coordinates and the contact and bushing elements exist between two bodies, the Jacobian matrix for these elements depended on only the relative motion of two adjacent bodies. Therefore, the Jacobian matrix hardly changes unless the relative motion changes significantly. This research investigates the Jacobian matrix to find small-changing and large-changing submatrices. Investigation showed that 65.4 % and 34.6 % of the Jacobian matrix belong to the small changing and the large changing submatrices, respectively. The small changing submatrices are calculated and LU decomposed only once at the initial time and reused at every time step afterwards. The large changing submatrices are updated and LU decomposed at every time step. As the sprocket rotates, the generalized coordinate sequence of the Jacobian matrix for the links is shifted one by one to keep the Jacobian matrix change of the small change submatrices small until the end of simulation time. The proposed method is implemented and its results are compared to those obtained from the original method which updates and LU decomposes the whole Jacobian matrix at every time step. Numerical experiments showed that the proposed method is about 11 times faster and yields almost identical results to the original method.

Since the experimental characterization of the low-pressure region of water’s phase diagram in the early 1900s, scientists have been on a quest to understand the thermodynamic stability of ice polymorphs on the molecular level. In this study, we demonstrate that combining the MB-pol data-driven many-body potential for water, which was rigorously derived from “first principles” and exhibits chemical accuracy, with advanced enhanced-sampling algorithms, which correctly describe the quantum nature of molecular motion and thermodynamic equilibria, enables computer simulations of water’s phase diagram with an unprecedented level of realism. Besides providing fundamental insights into how enthalpic, entropic, and nuclear quantum effects shape the free-energy landscape of water, we demonstrate that recent progress in “first principles” data-driven simulations, which rigorously encode many-body molecular interactions, has opened the door to realistic computational studies of complex molecular systems, bridging the gap between experiments and simulations. The molecular modelling of water has been a long sought-after goal in computational sciences for more than 50 years. Here, the authors show that the data-driven many-body MB-pol potential can provide a realistic representation of the phase diagram of water.

The exciting applications of molecular motion are still limited and are in urgent pursuit, although some fascinating concepts such as molecular motors and molecular machines have been proposed for years. Utilizing molecular motion in a nanoplatform for practical application has been scarcely explored due to some unconquered challenges such as how to achieve effective molecular motion in the aggregate state within nanoparticles. Here, we introduce a class of near infrared-absorbing organic molecules with intramolecular motion-induced photothermy inside nanoparticles, which enables most absorbed light energy to dissipate as heat. Such a property makes the nanoparticles a superior photoacoustic imaging agent compared to widely used methylene blue and semiconducting polymer nanoparticles and allow them for high-contrast photoacoustic imaging of tumours in live mice. This study not only provides a strategy for developing advanced photothermal/photoacoustic imaging nanoagents, but also enables molecular motion in a nanoplatform to find a way for practical application. Molecular motion has attracted a wide range of interest for different applications. Here, the authors develop nanoparticles with internal molecular motion upon near infrared absorption and use the nanoparticles for photoacoustic imaging and demonstrate this application in vivo.