Circadian behavior in mammals is orchestrated by neurons within the suprachiasmatic nucleus (SCN), yet the neuronal population necessary for the generation of timekeeping remains unknown. We show ...that a subset of SCN neurons expressing the neuropeptide neuromedin S (NMS) plays an essential role in the generation of daily rhythms in behavior. We demonstrate that lengthening period within Nms neurons is sufficient to lengthen period of the SCN and behavioral circadian rhythms. Conversely, mice without a functional molecular clock within Nms neurons lack synchronous molecular oscillations and coherent behavioral daily rhythms. Interestingly, we found that mice lacking Nms and its closely related paralog, Nmu, do not lose in vivo circadian rhythms. However, blocking vesicular transmission from Nms neurons with intact cell-autonomous clocks disrupts the timing mechanisms of the SCN, revealing that Nms neurons define a subpopulation of pacemakers that control SCN network synchrony and in vivo circadian rhythms through intercellular synaptic transmission.
•Nms neurons act as cellular pacemakers to regulate circadian period•Abolishing the molecular clock of Nms neurons disrupts in vivo circadian rhythms•NMS and NMU are dispensable for sustained behavioral circadian rhythms•Blocking synaptic transmission from Nms neurons disrupts coherent daily rhythms
Using several gain-of-function and loss-of-function genetic experiments, Lee et al. demonstrate that Neuromedin S-containing neurons function as SCN pacemakers to integrate circadian behavioral rhythms. This finding and the novel mouse models presented are important for understanding the neuronal circuitry of mammalian circadian rhythms.
Display omitted
•Many different oxy-carbon species are formed on Pt and spill over onto Al2O3.•Enolate, ester, and acetone species are more reactive than acetate species.•The concentration of ...oxy-carbon species does not correlate with the CO2 production rate.•Oxy-carbon surface species are inert spectators in the propane oxidation mechanism.
The growth of oxygenated carbonaceous (oxy-carbon) species on the surface of Pt/Al2O3 during total oxidation of propane is analyzed in detail—including their composition, their location on the catalyst surface, their reactivity, and their role in the propane oxidation mechanism—by in situ diffuse reflectance infrared Fourier-transform spectroscopy (DRIFTS). Platinum nanoparticles catalyze the transformation of propane into many different oxy-carbon surface species, including acetate, enolate, aliphatic ester, and acetone, which spillover and grow on the Al2O3 support. There is no correlation between the concentration of oxy-carbon surface species and the rate of CO2 production in the gas-phase, which indicates that these species are inert spectators in the propane oxidation mechanism. Temperature-programmed oxidation of the oxy-carbon surface species reveals that enolate, aliphatic ester, and acetone species are removed from the surface by combustion at similar temperatures with an activation barrier of 112kJ/mol, whereas acetate species are removed at higher temperatures with an activation barrier of 147kJ/mol. Both the formation and combustion of oxy-carbon surface species occur in pathways that are parallel to, and orders-of-magnitude slower than, the main pathway to CO2 production.
Predicting the citations of scholarly paper Bai, Xiaomei; Zhang, Fuli; Lee, Ivan
Journal of informetrics,
February 2019, 2019-02-00, Letnik:
13, Številka:
1
Journal Article
Recenzirano
Odprti dostop
Citation prediction of scholarly papers is of great significance in guiding funding allocations, recruitment decisions, and rewards. However, little is known about how citation patterns evolve over ...time. By exploring the inherent involution property in scholarly paper citation, we introduce the Paper Potential Index (PPI) model based on four factors: inherent quality of scholarly paper, scholarly paper impact decaying over time, early citations, and early citers’ impact. In addition, by analyzing factors that drive citation growth, we propose a multi-feature model for impact prediction. Experimental results demonstrate that the two models improve the accuracy in predicting scholarly paper citations. Compared to the multi-feature model, the PPI model yields superior predictive performance in terms of range-normalized RMSE. The PPI model better interprets the changes in citation, without the need to adjust parameters. Compared to the PPI model, the multi-feature model performs better prediction in terms of Mean Absolute Percentage Error and Accuracy; however, their predictive performance is more dependent on the parameter adjustment.
In 2019, a new definition for strict liability was introduced to the Penal Code as part of the historic Criminal Law Reform Act. Since this provision, section 26H, was designed to clarify the law, ...this article explores whether it can achieve that goal. By examining the intellectual history and recent judicial practice of strict liability in Singapore, I argue that section 26H succeeds in entrenching the “formal” or “elemental” approach to the concept. This is an advancement over the legal thought of the pre-reform era, in which the compatibility of strict liability with the Penal Code was widely doubted. However, the usefulness of section 26H to the statutory interpretation of specific offences is questionable. Indeed, section 26H must itself be interpreted carefully, or the law may become dangerously unstable. This illustrates the elusiveness of legal clarity and the limits of criminal law reform via codification.
PurposeThe study aims to explore and develop a smart route planning system for the cross-docking delivery operations of a large supermarket chain using an action research (AR) approach and assessing ...through a design science research (DSR) lens.Design/methodology/approachThis study took a problem-solving AR (PAR) approach toward the delivery operational issue of the case firm. The research process has accorded with the solution incubation and the refinement phases defined by a DSR framework. An intervention-based research framework for DSR is developed to assess the validity of this study as a DSR research and derive mid-range theories.FindingsDramatic operational and financial improvements were achieved for the case firm. Significant and unintended environmental and social benefits were also found. A design proposition (DP) and several mid-range theories are proposed as an extension of AR research to DSR research.Research limitations/implicationsA problem-solving DSR research can be better assessed by the intervention-based DSR framework developed in this study. DSR studies should be encouraged for both practical and theoretical advancement purposes.Practical implicationsA challenging business problem-solving study can be tackled effectively through an industry/academic collaboration taking a PAR approach to deliver substantial values and organization transformational results.Social implicationsDrivers and store associates are safer with smart delivery operations in the case firm.Originality/valueThere are still limited PAR design science case studies in the supply chain/logistics research literature. The research experience and findings gained from this study provide more insights toward how this type of research can be conducted and assessed.
A quasi-experimental field study was undertaken to examine whether the source credibility of point-of-decision (POD) prompts would affect their effectiveness in increasing stair use. POD prompts ...attributed either to a more credible source, a less credible source, or nothing were randomly installed in three student halls of residence at a public university in Hong Kong (plus a control). The stair and elevator use of residents were recorded by view-from-top surveillance cameras and counted using motion-detection software, resulting in 14,189 observations. The findings show that all the POD prompts can yield, as hypothesized, a significant positive effect on stair use. The relative increase in stair use was 2.49% on average. However, contrary to our second hypothesis, the POD prompt attributed to the more credible source was not the most effective intervention. The implications of these findings are discussed in conclusion.
Highly sensitive, wearable and durable strain sensors are vital to the development of health monitoring systems, smart robots and human machine interfaces. The recent sensor fabrication progress is ...respectable, but it is limited by complexity, low sensitivity and unideal service life. Herein a facile, cost‐effective and scalable method is presented for the development of high‐performance strain sensors and stretchable conductors based on a composite film consisting of graphene platelets (GnPs) and silicon rubber. Through calculation by the tunneling theory using experimental data, the composite film has demonstrated ideal linear and reproducible sensitivity to tensile strains, which is contributed by the superior piezoresistivity of GnPs having tunable gauge factors 27.7–164.5. The composite sensors fabricated in different days demonstrate pretty similar performance, enabling applications as a health‐monitoring device to detect various human motions from finger bending to pulse. They can be used as electronic skin, a vibration sensor and a human‐machine interface controller. Stretchable conductors are made by coating and encapsulating GnPs with polydimethyl siloxane to create another composite; this structure allows the conductor to be readily bent and stretched with sufficient mechanical robustness and cyclability.
Sensors and conductors are fabricated from developed graphene/elastomer composites. Demonstrating response time below 50 ms, high cycling durability and a gauge factor of over 100, the sensors work well as a health‐monitoring device, sound signal collector and human‐machine interface detector. The conductors can be readily bent and stretched with exceptional mechanical robustness and cyclability.
Emerging evidence points toward an intricate relationship between the pandemic of coronavirus disease 2019 (COVID-19) and diabetes. While preexisting diabetes is associated with severe COVID-19, it ...is unclear whether COVID-19 severity is a cause or consequence of diabetes. To mechanistically link COVID-19 to diabetes, we tested whether insulin-producing pancreatic β cells can be infected by SARS-CoV-2 and cause β cell depletion. We found that the SARS-CoV-2 receptor, ACE2, and related entry factors (TMPRSS2, NRP1, and TRFC) are expressed in β cells, with selectively high expression of NRP1. We discovered that SARS-CoV-2 infects human pancreatic β cells in patients who succumbed to COVID-19 and selectively infects human islet β cells in vitro. We demonstrated that SARS-CoV-2 infection attenuates pancreatic insulin levels and secretion and induces β cell apoptosis, each rescued by NRP1 inhibition. Phosphoproteomic pathway analysis of infected islets indicates apoptotic β cell signaling, similar to that observed in type 1 diabetes (T1D). In summary, our study shows SARS-CoV-2 can directly induce β cell killing.
Display omitted
•SARS-CoV-2 infects β cells in COVID-19 patients and human islets in vitro•SARS-CoV-2 infection causes β cell death and reduced GSIS in vitro•Phosphoproteomics shows SARS-CoV-2 spike protein and virus induce apoptotic kinases•High neuropilin-1 levels support β cell selectivity, and inhibitors block infection
Diabetic patients are at risk for severe COVID-19, but the virus may further damage insulin-secreting β cells. Wu et al. found that patient β cells are virally infected and the highly expressed neuropilin-1 receptor is critical for viral entry, causing cell death and reduced insulin secretion, exacerbating diabetes in patients.
Display omitted
•CO adsorption induces agglomeration of isolated Pd atoms.•The rate of H2 permeation across PdCu decreases with increasing CO concentration.•CO inhibits H2 transport by adsorbing only ...on Pd sites and blocking H2 dissociation.•PdCu is more resistant to CO poisoning than Pd.
Pd and PdCu alloy membranes are promising candidates for separating hydrogen from mixed gas streams due in part to their infinite selectivity to hydrogen separation. However, other gases such as CO can inhibit hydrogen transport across Pd-based membranes. In this work, the mechanism by which CO inhibits hydrogen transport across a 25 μm-thick Pd47Cu53 (mol%) membrane is investigated by operando infrared-reflection absorption spectroscopy (IRAS) in the 373–533 K temperature range. In the absence of hydrogen, CO adsorbs on three different sites on the PdCu surface: (1) bridging between contiguous Pd atoms, (2) on top of isolated Pd atoms surrounded by Cu atoms, and (3) on top of oxidized Cu atoms. CO induces agglomeration of isolated Pd atoms on the PdCu surface, which is driven by the higher stability of CO adsorbed on bridging sites between Pd atoms than on isolated Pd atoms surrounded by Cu atoms. The rate of hydrogen permeation across the PdCu alloy membrane decreases with increasing CO concentration in the feed gas, and the poisoning effect of CO is more severe at lower temperatures. CO inhibits hydrogen transport across the membrane by adsorbing only on Pd sites on the PdCu surface and blocking H2 dissociation on these sites. Due to the weaker interaction of CO with PdCu alloy surfaces than with Pd, the PdCu alloy is more resistant to CO poisoning than pure Pd.
Globally, the recommendation services have become important due to the fact that they support e-commerce applications and different research communities. Recommender systems have a large number of ...applications in many fields, including economic, education, and scientific research. Different empirical studies have shown that the recommender systems are more effective and reliable than the keyword-based search engines for extracting useful knowledge from massive amounts of data. The problem of recommending similar scientific articles in scientific community is called scientific paper recommendation. Scientific paper recommendation aims to recommend new articles or classical articles that match researchers' interests. It has become an attractive area of study since the number of scholarly papers increases exponentially. In this paper, we first introduce the importance and advantages of the paper recommender systems. Second, we review the recommendation algorithms and methods, such as Content-based, collaborative filtering, graph-based, and hybrid methods. Then, we introduce the evaluation methods of different recommender systems. Finally, we summarize the open issues in the paper recommender systems, including cold start, sparsity, scalability, privacy, serendipity, and unified scholarly data standards. The purpose of this survey is to provide comprehensive reviews on the scholarly paper recommendation.
PDF
