LOAD-DEFLECTION BEHAVIOR OF RATTAN CHAIR SEATS

The static and fatigue performances of seat foundations of natural rattan chairs subjected to vertical loads were investigated.  Static performance evaluation results indicate that rattan strip weaving patterns have significant effects on the vertical load carrying capacity and stiffness performance of chair seat foundations.  Herringbone and grid pattern woven seat foundations had significantly higher vertical load carrying capacity than those made with a square-corner pattern.  Square-corner pattern seat foundations yielded a softer sitting surface than herringbone and grid patterns.  Herringbone and grid pattern seat foundations can provide firmer sitting feel and good deep down support for heavier sitters.  The Burger model could be used to describe the force-deformation-time behavior of a rattan woven seat foundation subjected to vertical cyclic loading

Tensile and Bending Moment Resistances of T-Shaped Joints in Rattan Chairs

Effects of inner fastener type, wrapping pattern and material type, and member material type on ultimate tensile and bending moment resistances of T-shaped joints in rattan chair construction were investigated based on the L9 (34) orthogonal array experimental design. The range analyses indicated that the order of impact on ultimate tensile loads of four factors was inner fastener type > wrapping pattern > member material type > wrapping material type, whereas the order of impact on ultimate bending moment was inner fastener type > wrapping material type > wrapping pattern > member material type. Analysis of variance indicated that inner fastener type affected ultimate tensile and bending moment the most among the four factors with percentages of contribution of 51.19 and 47.06 to tensile and bending moment, respectively. Optimal combinations of factors and their levels that yielded the highest ultimate tensile and bending moment resistances were identified for T-shaped, end-to-side joints in rattan materials

Yi Qi Qing Re Gao Attenuates Podocyte Injury and Inhibits Vascular Endothelial Growth Factor Overexpression in Puromycin Aminonucleoside Rat Model

Proteinuria is the hallmark of chronic kidney disease. Podocyte damage underlies the formation of proteinuria, and vascular endothelial growth factor (VEGF) functions as an autocrine/paracrine regulator. Yi Qi Qing Re Gao (YQQRG) has been used to treat proteinuria for more than two decades. The objective of this study was to investigate the protective effect and possible mechanisms of YQQRG on puromycin aminonucleoside (PAN) rat model. Eighty male Sprague-Dawley rats were randomized into sham group, PAN group, PAN + YQQRG group, and PAN + fosinopril group. Treatments were started 7 days before induction of nephrosis (a single intravenous injection of 40 mg/kg PAN) until day 15. 24 h urinary samples were collected on days 5, 9, and 14. The animals were sacrificed on days 3, 10, and 15, respectively. Blood samples and renal tissues were obtained for detection of biochemical and molecular biological parameters. YQQRG significantly reduced proteinuria, elevated serum albumin, and alleviated renal pathological lesions. YQQRG inhibited VEGF-A, nephrin, podocin, and CD2AP mRNA expression and elevated nephrin, podocin, and CD2AP protein levels starting on day 3. In conclusion, YQQRG attenuates podocyte injury in the rat PAN model through downregulation of VEGF-A and restoration of nephrin, podocin, and CD2AP protein expression

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Multidifferential study of identified charged hadron distributions in ZZ-tagged jets in proton-proton collisions at s=\sqrt{s}=13 TeV

Jet fragmentation functions are measured for the first time in proton-proton collisions for charged pions, kaons, and protons within jets recoiling against a $Z$ boson. The charged-hadron distributions are studied longitudinally and transversely to the jet direction for jets with transverse momentum 20 $< p_{\textrm{T}} < 100$ GeV and in the pseudorapidity range $2.5 < \eta < 4$. The data sample was collected with the LHCb experiment at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 1.64 fb$^{-1}$. Triple differential distributions as a function of the hadron longitudinal momentum fraction, hadron transverse momentum, and jet transverse momentum are also measured for the first time. This helps constrain transverse-momentum-dependent fragmentation functions. Differences in the shapes and magnitudes of the measured distributions for the different hadron species provide insights into the hadronization process for jets predominantly initiated by light quarks.Comment: All figures and tables, along with machine-readable versions and any supplementary material and additional information, are available at https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-013.html (LHCb public pages

Study of the B−→Λc+Λˉc−K−B^{-} \to \Lambda_{c}^{+} \bar{\Lambda}_{c}^{-} K^{-} decay

The decay $B^{-} \to \Lambda_{c}^{+} \bar{\Lambda}_{c}^{-} K^{-}$ is studied in proton-proton collisions at a center-of-mass energy of $\sqrt{s}=13$ TeV using data corresponding to an integrated luminosity of 5 $\mathrm{fb}^{-1}$ collected by the LHCb experiment. In the $\Lambda_{c}^+ K^{-}$ system, the $\Xi_{c}(2930)^{0}$ state observed at the BaBar and Belle experiments is resolved into two narrower states, $\Xi_{c}(2923)^{0}$ and $\Xi_{c}(2939)^{0}$, whose masses and widths are measured to be $$m(\Xi_{c}(2923)^{0}) = 2924.5 \pm 0.4 \pm 1.1 \,\mathrm{MeV}, \\ m(\Xi_{c}(2939)^{0}) = 2938.5 \pm 0.9 \pm 2.3 \,\mathrm{MeV}, \\ \Gamma(\Xi_{c}(2923)^{0}) = \phantom{000}4.8 \pm 0.9 \pm 1.5 \,\mathrm{MeV},\\ \Gamma(\Xi_{c}(2939)^{0}) = \phantom{00}11.0 \pm 1.9 \pm 7.5 \,\mathrm{MeV},$$ where the first uncertainties are statistical and the second systematic. The results are consistent with a previous LHCb measurement using a prompt $\Lambda_{c}^{+} K^{-}$ sample. Evidence of a new $\Xi_{c}(2880)^{0}$ state is found with a local significance of $3.8\,\sigma$, whose mass and width are measured to be $2881.8 \pm 3.1 \pm 8.5\,\mathrm{MeV}$ and $12.4 \pm 5.3 \pm 5.8 \,\mathrm{MeV}$, respectively. In addition, evidence of a new decay mode $\Xi_{c}(2790)^{0} \to \Lambda_{c}^{+} K^{-}$ is found with a significance of $3.7\,\sigma$. The relative branching fraction of $B^{-} \to \Lambda_{c}^{+} \bar{\Lambda}_{c}^{-} K^{-}$ with respect to the $B^{-} \to D^{+} D^{-} K^{-}$ decay is measured to be $2.36 \pm 0.11 \pm 0.22 \pm 0.25$, where the first uncertainty is statistical, the second systematic and the third originates from the branching fractions of charm hadron decays.Comment: All figures and tables, along with any supplementary material and additional information, are available at https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-028.html (LHCb public pages

Measurement of the ratios of branching fractions R(D∗)\mathcal{R}(D^{*}) and R(D0)\mathcal{R}(D^{0})

The ratios of branching fractions $\mathcal{R}(D^{*})\equiv\mathcal{B}(\bar{B}\to D^{*}\tau^{-}\bar{\nu}_{\tau})/\mathcal{B}(\bar{B}\to D^{*}\mu^{-}\bar{\nu}_{\mu})$ and $\mathcal{R}(D^{0})\equiv\mathcal{B}(B^{-}\to D^{0}\tau^{-}\bar{\nu}_{\tau})/\mathcal{B}(B^{-}\to D^{0}\mu^{-}\bar{\nu}_{\mu})$ are measured, assuming isospin symmetry, using a sample of proton-proton collision data corresponding to 3.0 fb${ }^{-1}$ of integrated luminosity recorded by the LHCb experiment during 2011 and 2012. The tau lepton is identified in the decay mode $\tau^{-}\to\mu^{-}\nu_{\tau}\bar{\nu}_{\mu}$. The measured values are $\mathcal{R}(D^{*})=0.281\pm0.018\pm0.024$ and $\mathcal{R}(D^{0})=0.441\pm0.060\pm0.066$, where the first uncertainty is statistical and the second is systematic. The correlation between these measurements is $\rho=-0.43$. Results are consistent with the current average of these quantities and are at a combined 1.9 standard deviations from the predictions based on lepton flavor universality in the Standard Model.Comment: All figures and tables, along with any supplementary material and additional information, are available at https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-039.html (LHCb public pages

Essays on the Internationalization of Emerging Market Multinational Enterprises

This thesis studies the internationalization of emerging market multinational enterprises (EMNEs). Chapters 2, 3, 4, and 5 focus on the case of Chinese multinational enterprises (MNEs). Chapter 2 reviews extant literature about the internationalization of Chinese MNEs published from 1985 to 2021, proposes research frameworks, and finally provides suggestions for future research attention. Chapter 3 introduces four main international business theories and analyzes how the theories are developed in explaining the internationalization process of Chinese MNEs. The four theories are the OLI (Ownership, Location, and Internalization advantages) paradigm, the Uppsala model, the LLL (Linkage-Leverage-Learning) framework, and the Springboard perspective. Chapter 4 investigates the effect of post-cross-border mergers and acquisitions (CBMAs) of short and long terms on the innovation performance of Chinese MNEs. Using a sample of CBMAs between 1997 and 2017, empirical results show that CBMAs foster the innovation performance of Chinese MNEs in the short and long terms. The significant effects keep persistent when Chinese MNEs invest in targets from different industries or located in innovative countries. Moreover, comparing the innovation level of the host country and targets, the results suggest that Chinese MNEs are mainly interested in exploiting the benefits related to the innovative environment rather than in the specific knowledge of the target. Chapter 5 adopts a case-study approach to specifically explore the advantages and disadvantages of Chinese electric vehicle (EV) firms when they expand to European markets, and then suggests solutions to mitigate the disadvantages. Chinese EV firms’ competitiveness over rivals in Europe comes from maintaining the advantages accumulated in the Chinese market and overcoming potential challenges encountered in Europe. Chapter 6 extends the scope of EMNEs by involving MNEs from different emerging countries. It compares the effect of inward European foreign direct investments (FDIs) from Brazil, Russia, India, and China (BRIC) on technological collaboration between Europe and individual BRIC countries and explores whether such impact varies with the innovation performance of European regions. The results are different across BRIC countries. Inward FDI from India and China is the most critical trigger to stimulate technological collaboration. Interestingly, India and Brazil are willing to collaborate with non-innovative European regions, but China is more interested in collaborating with innovative European regions. However, Russia does not contribute to technological collaboration with Europe.This thesis studies the internationalization of emerging market multinational enterprises (EMNEs). Chapters 2, 3, 4, and 5 focus on the case of Chinese multinational enterprises (MNEs). Chapter 2 reviews extant literature about the internationalization of Chinese MNEs published from 1985 to 2021, proposes research frameworks, and finally provides suggestions for future research attention. Chapter 3 introduces four main international business theories and analyzes how the theories are developed in explaining the internationalization process of Chinese MNEs. The four theories are the OLI (Ownership, Location, and Internalization advantages) paradigm, the Uppsala model, the LLL (Linkage-Leverage-Learning) framework, and the Springboard perspective. Chapter 4 investigates the effect of post-cross-border mergers and acquisitions (CBMAs) of short and long terms on the innovation performance of Chinese MNEs. Using a sample of CBMAs between 1997 and 2017, empirical results show that CBMAs foster the innovation performance of Chinese MNEs in the short and long terms. The significant effects keep persistent when Chinese MNEs invest in targets from different industries or located in innovative countries. Moreover, comparing the innovation level of the host country and targets, the results suggest that Chinese MNEs are mainly interested in exploiting the benefits related to the innovative environment rather than in the specific knowledge of the target. Chapter 5 adopts a case-study approach to specifically explore the advantages and disadvantages of Chinese electric vehicle (EV) firms when they expand to European markets, and then suggests solutions to mitigate the disadvantages. Chinese EV firms’ competitiveness over rivals in Europe comes from maintaining the advantages accumulated in the Chinese market and overcoming potential challenges encountered in Europe. Chapter 6 extends the scope of EMNEs by involving MNEs from different emerging countries. It compares the effect of inward European foreign direct investments (FDIs) from Brazil, Russia, India, and China (BRIC) on technological collaboration between Europe and individual BRIC countries and explores whether such impact varies with the innovation performance of European regions. The results are different across BRIC countries. Inward FDI from India and China is the most critical trigger to stimulate technological collaboration. Interestingly, India and Brazil are willing to collaborate with non-innovative European regions, but China is more interested in collaborating with innovative European regions. However, Russia does not contribute to technological collaboration with Europe