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Facial information is essential in daily life, but relatively little is known about whether seeing a face improves people’s decision quality. This experimental paper studies the loan-approval decisions based on the historical cash-loan data with real repayment outcomes and exogenously varies whether and how a borrower’s facial information is provided. We find that facial information does not improve subjects’ decisions, despite the fact that it can predict repayment behavior in a machine-learning algorithm. This is because subjects have various biases in evaluating facial photos, and they rely excessively on facial information in making the loan-approval decisions. This paper was accepted by Yan Chen, behavioral economics and decision analysis. Funding: J. Meng received financial support from the National Natural Science Foundation of China [Grants 71103003, 71471004, and 71822301]. Supplemental Material: Data files and the online appendix are available at https://doi.org/10.1287/mnsc.2022.4436 .

The Tibetan Plateau (TP) with a large landmass serves as an obstacle that hinders westerly flows and alters climate downwind. Here, we investigate the TP influence on the magnitude and spatial distribution of wintertime fine particulate matter (PM2.5) concentrations downwind and associated underlying mechanisms. Based on simulations using an Earth system model, we show that the removal of the TP would reduce surface PM2.5 concentrations by −30.4% in the Sichuan basin (SC) and by −12.4% in the North China Plain (NCP), but increase the concentrations by 18.1% in eastern China (EC), suggesting that the TP could naturally intensify PM2.5 pollution in SC and NCP. If the TP were absent, more meridional circulations would turn into zonal ones and the East Asian winter monsoon would become weaker. There would be less precipitation and lower humidity over SC and EC in the south, while the opposite occurs over NCP in the north. Consequently, the changes in circulations would result in a net outflow of PM2.5 from SC and NCP, but a net inflow of PM2.5 to EC. In response to the spatial changes in precipitation, wet deposition would decrease in SC and EC but increase in NCP. PM2.5 production would reduce in SC and EC but amplify in NCP, following the changes in humidity. In magnitude, the changes in transport and wet deposition would be dominant in SC and NCP, while in EC, transport, wet deposition, and chemical production would be equally important. This study illustrates significant and heterogeneous impacts of the TP on air quality downwind.

To compare overall agreement between magnetic resonance imaging (MRI)-ultrasound (US) fusion biopsy (FB) and MRI cognitive fusion biopsy (CB) of the prostate and determine which factors affect agreement for prostate cancer (PCa) who underwent both modalities in a prospective within-patient protocol.From August 2017 to January 2021, patients with at least one Prostate Imaging ReportingData System (PI-RADS) 3 or higher lesion on multiparametric MRI underwent transrectal FB and CB in a prospective within-patient protocol. CB was performed for each region of interest (ROI), followed by FB, followed by standard 12 core biopsy. Patients who were not on active surveillance were analysed. The primary endpoint was agreement for any PCa detection. McNemar's test and kappa statistic were used to analyse agreement. Chi-square test, Fisher's exact test and Wilcoxon rank sum test were used to analyse disagreement across clinical and MRI spatial variables. A multivariable generalized mixed-effect model was used to compare the interaction between select variables and fusion modality. Statistics were performed using SAS and R.Ninety patients and 98 lesions were included in the analysis. There was moderate agreement between FB and CB (In a within-patient protocol of patients not on active surveillance, FB and CB performed similarly for PCa detection and with moderate agreement. Anterior location was associated with significantly higher disagreement, whereas other patient and lesion characteristics were not. Additional studies are needed to determine optimal biopsy technique for sampling anterior ROI.

The proteasome was validated as an oncology target following the clinical success of VELCADE (bortezomib) for injection for the treatment of multiple myeloma and recurring mantle cell lymphoma. Consequently, severalgroups are pursuing the development of additional small-molecule proteasome inhibitors for both hematologic and solid tumor indications. Here, we describe MLN9708, a selective, orally bioavailable, second-generation proteasome inhibitor that is in phase I clinical development. MLN9708 has a shorter proteasome dissociation half-life and improved pharmacokinetics, pharmacodynamics, and antitumor activity compared with bortezomib. MLN9708 has a larger blood volume distribution at steady state, and analysis of 20S proteasome inhibition and markers of the unfolded protein response confirmed that MLN9708 has greater pharmacodynamic effects in tissues than bortezomib. MLN9708 showed activity in both solid tumor and hematologic preclinical xenograft models, and we found a correlation between greater pharmacodynamic responses and improved antitumor activity. Moreover, antitumor activity was shown via multiple dosing routes, including oral gavage. Taken together, these data support the clinical development of MLN9708 for both hematologic and solid tumor indications. Cancer Res; 70(5); 1970–80

Supplementary Data, Figure Legends 1-3 from Evaluation of the Proteasome Inhibitor MLN9708 in Preclinical Models of Human Cancer

Supplementary Figure 3 from Evaluation of the Proteasome Inhibitor MLN9708 in Preclinical Models of Human Cancer

Supplementary Figure 1 from Evaluation of the Proteasome Inhibitor MLN9708 in Preclinical Models of Human Cancer

Supplementary Figure 2 from Evaluation of the Proteasome Inhibitor MLN9708 in Preclinical Models of Human Cancer

Despite the implementation of the Clean Air Action Plan by the Chinese government in 2013, the issue of increasing surface ozone (O3) concentrations remains a significant environmental concern in China. In this study, we used an improved regional climate–chemistry–ecology model (RegCM-Chem-YIBs) to investigate the impact of anthropogenic emissions, meteorological factors, and CO2 changes on summer surface O3 levels in China from 2008 to 2018. Compared to its predecessor, the model has been enhanced concerning the photolysis of O3 and the radiative impacts of CO2 and O3. The investigations showed anthropogenic emissions were the primary contributor to the O3 increase in China, responsible for 4.08–18.51 ppb in the North China Plain. However, changed meteorological conditions played a crucial role in decreasing O3 in China and may have a more significant impact than anthropogenic emissions in some regions. Changed CO2 played a critical role in the variability of O3 through radiative forcing and isoprene emissions, particularly in southern China, inducing an increase in O3 on the southeast coast of China (0.28–0.46 ppb) and a decrease in southwest and central China (−0.51 to −0.11 ppb). Our study comprehensively analyzed O3 variation across China from various perspectives and highlighted the importance of considering CO2 variations when designing long-term O3 control policies, especially in high-vegetation-coverage areas.

Bone defects often require operative intervention with the use of bone graft. Two sources of autologous bone graft include reamer-irrigator-aspirate (RIA) and bone marrow aspirate concentrate (BMC). Osteoprogenitor cells and osteoconductive proteins have been identified in both sources. This study collected samples of these cells and proteins from a canine model and cultured them on human cancellous allograft bone blocks. Findings suggest that BMC may be preferred for indications that allow for delivery via injection, saturation of the patient's tissues, or an implanted scaffold, whereas RIA may be preferred when the biologic augment is delivered as a scaffold or graft.

This study introduces a beam-reinforced plate (BRP) finite element model to predict the deformation behavior of a rectangular duct system under positive gauge pressure, and further investigates the existing design procedures employed in practice. A commonly used methodology is to model rectangular duct systems subjected to internal pressure as individual thin plates to predict maximum deflections and set stress limitations. One of the assumptions these existing models are based on is to assume the stiffness of reinforcements is infinite, which obviously is not consistent with the real duct behavior. The proposed BRP model not only accounts for the deformation of the stiffeners, but also the geometric non-linearity of the plates under a uniform internal pressure. By comparing deflection predictions from a whole duct finite element model, it is shown that that the BRP model can predict the deformation behavior accurately under certain circumstances. Parametric studies were performed to understand how geometric variables affect the deflections of duct panels. Therein limitations of the proposed model are discussed and defined. Based on these limitations, further research is recommended to develop plate models that can accurately predict the behavior of complicated duct systems.

A study was performed to investigate the effects of aspect ratio, material gauge, material properties, joint spacing, loading type and magnitude on the mechanical performance of rectangular ductwork. The SMACNA Industrial Duct Construction Standard (1st and 2nd Editions) rectangular ductwork design standards were reviewed, and theoretical equations contained in the existing literature were identified and evaluated. Allowing for round-off error, the calculations performed in this investigation agreed closely with the SMACNA approach. Finite element predictions of duct deformation were intermediate to the DMI experimental data and those obtained using the SMACNA design procedures, for both 10 gauge and 16 gauge wall thicknesses and twelve load cases.

Black carbon (BC) aerosol emissions are complex and have important environmental and meteorological effects. In China, the temporal and spatial variations in BC in different atmospheric environmental conditions need to be fully understood. Based on the long-term observational BC data in seven atmospheric background stations in China from 2006 to 2020, combined with meteorological data, emission source data, enhanced vegetation index (EVI) data, and aerosol optical depth (AOD) data, we comprehensively analyzed the characteristics of temporal and spatial variations, long-term evolution, and influencing factors of BC in China. The results showed that the BC and AOD values of different atmospheric environments in China were quite different, and BC positively contributed to AOD. The spatial distribution was high in the east and low in the west owing to the differences in emission sources and meteorological conditions. The

Carbon monoxide (CO) is an important trace gas in the troposphere, while the El Niño-Southern Oscillation (ENSO) phenomenon is the most important tropical climate variability. ENSO is known to influence interannual variation in meteorological variables on the global scale but its influence on atmospheric CO over large areas in a long term is uncertain. Here we report a strong positive teleconnection between the El Niño–Southern Oscillation (ENSO) in winter (November to February) to tropospheric CO over the North Atlantic European region (NAE) in the following spring (March to May). This ENSO teleconnection is evident in trajectory-mapped airborne CO data (In-service Aircraft for a Global Observing System, IAGOS) over 2002–2019. CO concentrations in El Niño years are 5–20 ppbv higher than those in La Niña years over the NAE troposphere. The regional mean difference from the surface to 300 hPa is 9.4 ppbv (7.6% of the mean). The correlation coefficient (r) between the ENSO index and detrended CO concentrations in the NAE is 0.67 at 400 hPa and 0.63 near the surface, both statistically significant at the 95% level. Such a teleconnection is also observed in independent surface observations, with r ranging from 0.57 to 0.74, all at 95% significance level. From analysis of fire emissions and atmospheric conditions, combined with tagged CO simulations using a chemical transport model, GEOS-Chem, we conclude that this teleconnection results from the combined effects of ENSO on both biomass burning and atmospheric transport. We find that in El Niño years, CO emissions from biomass burning are significantly enhanced in Northern Hemispheric South America, Southeast Asia, and North America due to warmer air temperatures and lowered precipitation. In addition, ENSO enhances CO transport from these regions to the NAE by enhancing upward and northeastward motions in the fire regions, accelerating westerlies over 20°N–40°N, and prompting ascents over the Atlantic and descents over Europe, while reducing CO outflow at the eastern boundary of Europe. The combined effect of ENSO on both CO emissions and CO transport leads to interannual variability in tropospheric CO over the NAE.

We hypothesize that managers use stock dividends or splits to cater to gambling investors who are willing to pay a premium for stocks with lottery-like features. Using proprietary account-level trading records, we find that retail investors, particularly those with a strong gambling preference, become strong net buyers following the announcement of stock dividends, while professional investors unload their holdings. Moreover, we find that positive market reactions to stock dividends is positively associated with increases in gambling investors.

Satellite retrievals of the column-averaged dry air mole fractions of CO2 (XCO2) could help to improve carbon flux estimation due to their good spatial coverage. In this study, in order to assimilate the GOSAT (Greenhouse Gases Observing Satellite) XCO2 retrievals, the Global Carbon Assimilation System (GCAS) is upgraded with new assimilation algorithms, procedures, a localization scheme, and a higher assimilation parameter resolution. This upgraded system is referred to as GCASv2. Based on this new system, the global terrestrial ecosystem (BIO) and ocean (OCN) carbon fluxes from 1 May 2009 to 31 December 2015 are constrained using the GOSAT ACOS (Atmospheric CO2 Observations from Space) XCO2 retrievals (Version 7.3). The posterior carbon fluxes from 2010 to 2015 are independently evaluated using CO2 observations from 52 surface flask sites. The results show that the posterior carbon fluxes could significantly improve the modeling of atmospheric CO2 concentrations, with global mean bias decreases from a prior value of 1.6 ± 1.8 ppm to −0.5 ± 1.8 ppm. The uncertainty reduction (UR) of the global BIO flux is 17 %, and the highest monthly regional UR could reach 51 %. Globally, the mean annual BIO and OCN carbon sinks and their interannual variations inferred in this study are very close to the estimates of CarbonTracker 2017 (CT2017) during the study period, and the inferred mean atmospheric CO2 growth rate and its interannual changes are also very close to the observations. Regionally, over the northern lands, the strongest carbon sinks are seen in temperate North America, followed by Europe, boreal Asia, and temperate Asia; in the tropics, there are strong sinks in tropical South America and tropical Asia, but a very weak sink in Africa. This pattern is significantly different from the estimates of CT2017, but the estimated carbon sinks for each continent and some key regions like boreal Asia and the Amazon are comparable or within the range of previous bottom-up estimates. The inversion also changes the interannual variations in carbon fluxes in most TransCom land regions, which have a better relationship with the changes in severe drought area (SDA) or leaf area index (LAI), or are more consistent with previous estimates for the impact of drought. These results suggest that the GCASv2 system works well with the GOSAT XCO2 retrievals and shows good performance with respect to estimating the surface carbon fluxes; meanwhile, our results also indicate that the GOSAT XCO2 retrievals could help to better understand the interannual variations in regional carbon fluxes.

Evapotranspiration (ET) is a major component of water and energy budgets in terrestrial ecosystems and quantifying ET over a heterogeneous land surface is of extraordinary significance. However, pr...

Past studies typically have focused on whether people perceive more rare risk after experiencing catastrophic disasters. We show that people can also feel less risk with unexpected lucky disaster experience. By exploring a novel identification strategy based on households’ expectations, we find that households perceive less (more) risk when they experience disasters that have lower (higher) fatalities than what was expected. This opposite experience effect of rare disasters is substantial. A one standard deviation increase in the negative (positive) experience shock is associated with a 1.71% decrease (a 1.31% increase) in the life insurance-to-portfolio ratio. We discuss three possible mechanisms to account for our empirical findings: incomplete information learning, salience theory, and change in risk preferences.

Black carbon (BC) aerosol is a significant and short-lived climate forcing factor. Here, the direct effects of BC emissions from India (IDBC) and China (CNBC) are investigated in East Asia during summer using the state-of-the-art regional climate model RegCM4. In summer, IDBC and CNBC account for approximately 30% and 46% of the total BC emissions in Asia, respectively. The total BC column burden from the two countries and corresponding TOA effective radiative forcing are 1.58 mg m−2and +1.87 W m−2in East Asia, respectively. The regional air temperature increases over 0.3 K at maximum and precipitation decreases 0.028 mm day−1on average. Individually, IDBC and CNBC each can bring about rather different effects on regional climate. IDBC can result in a cooling perturbation accompanied by a substantially increased cloud amount and scattering aerosol loading, resulting in a complex response in the regional precipitation, while CNBC can lead to regional warming, and further induce a local flood in northern China or drought in southern China depending on the opposite but significant circulation anomalies. CNBC plays a dominant role in modulating the regional climate over East Asia due to its higher magnitude, wider coverage, and stronger climate feedback. The direct effect of the total BC from both countries is not a linear combination of that of IDBC and CNBC individually, suggesting that the regional climate responses are highly nonlinear to the emission intensity or aerosol loading, which may be greatly related to the influences of the perturbed atmospheric circulations and climate feedback.

Haze pollution in recent decades varies largely with both pollutant emissions and meteorological conditions. Using the discrete wavelet transform (DWT) method, we separate these two influences on haze variations in southern China in the time series of haze observations from 1981 to 2011. This helps us to identify the meteorological influence on interannual variation in haze occurrences in southern China and thus observe a teleconnection between the thermal forcing of sea surface temperature (SST) in the central and eastern Pacific and wintertime haze occurrences in southern China (R = − 0.51, p < 0.05). The total haze days in winter is highest among all seasons over southern China and the climotological mean of number of winter haze days is 7.5 days for the region. Compared with the normal winters, the regional mean of the number of haze days in southern China is reduced by ~ 5 days in the winters with above-normal Niño3.4 SST (during El Niño phases), but increased by ~ 4 days in the winters with below-normal Niño3.4 SST (during La Niña phases). In the warm SST winters, the cumulative consequences of strong winds, more precipitation, and a more unstable atmosphere with an “upper colder and lower warmer” vertical pattern leading to more ascendance can all hinder haze formation, whereas in the cold SST winters, opposite meteorological conditions are favorable to haze formation. These meteorological conditions induced by anomalous SST make wintertime haze pollution in southern China vary from year to year to a large extent. This study suggests a strong sensitivity of winter haze occurrences in southern China to the viability of the SST in the central and eastern Pacific.

This paper investigates the presence of local bias in the peer-to-peer (P2P) lending market and explores the social heterogeneous factors that may affect the formulation of the investor's local bias. We find that local biases are commonly present among investors. Investors have a 9.3% higher probability and put 105% more money in lending to local borrowers. We also find that overinvesting in local loans is correlated with higher default risk, lower recovery rate, and lower realized return, suggesting the underperformance of these locally biased investors. By taking advantage of the diverse local culture and institutional features in China, we further show that social heterogeneity, including geography, language, and social trust, affects the degree of local biases in the P2P lending market. We propose two debiasing techniques from the P2P platforms’ perspective.

Ozone pollution in China is influenced by meteorological processes on multiple scales. Using regression analysis and weather classification, we statistically assess the impacts of local and synoptic meteorology on daily variability in surface ozone in eastern China in summer during 2013–2018. In this period, summertime surface ozone in eastern China (20–42∘ N, 110–130∘ E) is among the highest in the world, with regional means of 73.1 and 114.7 µg m−3, respectively, in daily mean and daily maximum 8 h average. Through developing a multiple linear regression (MLR) model driven by local and synoptic weather factors, we establish a quantitative linkage between the daily mean ozone concentrations and meteorology in the study region. The meteorology described by the MLR can explain ∼43 % of the daily variability in summertime surface ozone across eastern China. Among local meteorological factors, relative humidity is the most influential variable in the center and south of eastern China, including the Yangtze River Delta and the Pearl River Delta regions, while temperature is the most influential variable in the north, covering the Beijing–Tianjin–Hebei region. To further examine the synoptic influence of weather conditions explicitly, six predominant synoptic weather patterns (SWPs) over eastern China in summer are objectively identified using the self-organizing map clustering technique. The six SWPs are formed under the integral influence of the East Asian summer monsoon, the western Pacific subtropical high, the Meiyu front, and the typhoon activities. On average, regionally, two SWPs bring about positive ozone anomalies (1.1 µg m−3 or 1.7 % and 2.7 µg m−3 or 4.6 %), when eastern China is under a weak cyclone system or under the prevailing southerly wind. The impact of SWPs on the daily variability in surface ozone varies largely within eastern China. The maximum impact can reach ±8 µg m−3 or ±16 % of the daily mean in some areas. A combination of the regression and the clustering approaches suggests a strong performance of the MLR in predicting the sensitivity of surface ozone in eastern China to the variation of synoptic weather. Our assessment highlights the importance of meteorology in modulating ozone pollution over China.

Great attention has been paid to the long-term decline in terrestrial near-surface wind speed (SWS) in China. However, how the SWS varies with regions and seasons and what modulates these changes remain unclear. Based on quality-controlled and homogenized terrestrial SWS data from 596 stations, the covarying SWS patterns during the Asian Summer Monsoon (ASM) and the Asian Winter Monsoon (AWM) seasons are defined for China using empirical orthogonal function (EOF) analysis for 1961–2016. The dominant SWS features represented by EOF1 patterns in both seasons show a clear decline over most regions of China. The interannual variability of the EOF1 patterns is closely related to the Northeast Asia Low Pressure (NEALP) and the Arctic Oscillation (AO), respectively. The EOF2 and EOF3 patterns during ASM (AWM) season describe a dipole mode of SWS between East Tibetan Plateau and East China Plain (between East Tibetan Plateau and Northeast China), and between Southeast and Northeast China (between Northeast China and the coastal areas of Southeast China), respectively. These dipole structures of SWS changes are closely linked with the oceanic-atmospheric oscillations on interannual scale., We acknowledge supports from the National Science Foundation of China (41822101, 41888101, 41971022 and 41772180), the Strategic Priority Research Program of the Chinese Academy of Sciences (XDB26020000), fellowship for the National Youth Talent Support Program of China (Ten Thousand People Plan), fellowship for Youth Talent Support Program of Fujian Province and the Innovation Team Project (IRTL1705). This research was also funded by the Swedish Formas (2017-01408). Cesar Azorin-Molina was supported by the IBER-STILLING project RTI2018-095749-A-100 (MCIU/AEI/FEDER,UE), the VENTS project AICO/2021/023 (GVA) and the CSIC Interdisciplinary Thematic Platform PTI-CLIMA.

In recent years, ozone pollution becomes a serious environmental issue in China. A good understanding of source-receptor relationships of ozone transport from aboard and inside China is beneficial to mitigating ozone pollution there. To date, these issues have not been comprehensively assessed, especially for highly polluted regions in the central and eastern China (CEC), including the North China Plain (NCP), Twain-Hu region (THR), Yangtze River Delta (YRD), Pearl River Delta (PRD), and Sichuan Basin (SCB). Here, based on simulations over 2013-2020 from a well-validated chemical transport model, GEOS-Chem, we show that foreign ozone accounts for a large portion of surface ozone over CEC, ranging from 25.0% in THR to 39.4% in NCP. Focusing on transport of domestic ozone between the five regions in CEC, we find that atmospheric transport can largely modulate regional interactions of ozone pollution in China. At the surface, THR receives the largest amount of ozone from the other four regions (54.2% of domestic ozone in the receptor region, the same in below), followed by PRD (32.3%), SCB (26.7%), YRD (21.1%), and NCP (18.0%). Meanwhile, YRD exports largest amount of ozone to the other regions, ranging from 8.9% in SCB to 28.4% in THR. Although SCB is relatively isolated and thus impacts NCP, YRD, and PRD weakly (2.2%), export of SCB ozone to THR reaches 9.3%. The regional ozone transport over CEC, occurring mostly in the lower troposphere, is mainly modulated by the East Asian monsoon circulations, proximity between source and receptor regions, seasonal changes of ozone production, and topography.

Description, Continued rise of the tropopause after 2000 in the Northern Hemisphere is mainly due to tropospheric warming., Tropopause height (H) is a sensitive diagnostic for anthropogenic climate change. Previous studies showed increases in H over 1980–2000 but were inconsistent in projecting H trends after 2000. While H generally responds to temperature changes in the troposphere and stratosphere, the relative importance of these two contributions is uncertain. Here, we use radiosonde balloon observations in the Northern Hemisphere (NH) over 20°N to 80°N to reveal a continuous rise of H over 1980–2020. Over 2001–2020, H increases at 50 to 60 m/decade, which is comparable to the trend over 1980–2000. The GPS radio occultation measurements from satellites and homogenized radiosonde records are in good agreement with those results. The continuous rise of the tropopause in the NH after 2000 results primarily from tropospheric warming. A large trend in H remains after major natural forcings for H are removed, providing further observational evidence for anthropogenic climate change.

Deformation was measured as a function of internal static gauge pressure for galvanized steel spiral 12 in. × 43 in. (305 mm × 1092 mm) flat oval ducts. Both unreinforced and externally reinforced ducts were considered. Dial deflection gauges were used to measure the duct deformation at prescribed locations on the top and bottom surface of the test duct and compared to corresponding predictions generated using a nonlinear finite element model that accounted for the self-weight of the duct walls. The Average Wall Thickness (AWT) method was utilized to account for the presence of a continuous spiral seam. Shell elements were employed to represent the thin-walled structure of the ducts. External trapeze reinforcements spaced 3 ft (0.91 m), 6 ft (1.83 m), and 12 ft (3.66 m) apart were modeled using beam elements. The non-linear finite element model of the duct system was found to yield realistic deformation predictions. It was concluded that finite element modeling can be used to guide decisions regarding the selection of a thicker duct wall, or inclusion of either internal or external reinforcement, if concerns exist about excessive duct or reinforcement deformation caused by high internal gauge pressures.

The Sichuan Basin (SCB), to the east of the Tibetan Plateau (TP), experiences severe ozone (O

Disruptive innovation forces small-business managers to innovate by carrying out exploitation and exploration activities simultaneously. This ambidexterity is crucial to the survival of today’s businesses, especially small and medium-sized enterprises (SMEs). In the organizational structure of SMEs, the manager and owner play an essential role in determining the business orientation. This study examined the influence of SME managers’ social networks on the organization’s ambidexterity and its impact on the firm’s innovation performance. This study used two moderating variables in the form of two internal factors in respect to managers: how proactive they are and their commitment to innovation. The study population was drawn from SMEs in the creative manufacturing sector in Indonesia and Taiwan, with a total sample of 224 SMEs, including 101 from Indonesia and 123 from Taiwan. The analytical technique was the PLS-SEM, conducted by the Smart-PLS software version 3.3.6: Hamburg, Germany. The results supported the construction in both countries. The results of the multiple-group analysis show that the SMEs in Indonesia exhibited greater ambidexterity, commitment to innovation, and innovation performance than those in Taiwan.

Unreinforced 12 in. × 23 in. (305 mm × 584 mm) galvanized steel flat oval ducts were tested to measure deformations when internal static gauge pressures were applied. The experiments were performed on spiral seam non-corrugated duct. Finite element models with discrete ring seams and an average wall thickness approach were utilized to represent the continuous spiral seam, and therein predict duct deflections at prescribed locations along the duct wall. Predicted deflections from the finite element models were tabulated and compared to experimental data. Satisfactory agreement between model predictions and test data were obtained from a non-linear finite element analysis that employed a simplified average wall thickness to characterize the spiral seam and duct wall. It is straightforward to implement the average wall thickness methodology in finite element modeling of duct deformation.

When many cities need quantitative forecasts of air quality to adjust industrial production plans and urbanization development, how to build an efficient forecast model remain a challenge. Methodology for quantitative prediction of air quality can no longer rely on single‐site observations, and thus approaches that require fewer input data and are more efficient and more reliable need to be explored. This paper proposes the principles and steps of a new model using the empirical orthogonal function (EOF) and principal component regression (PCR), which is a hybrid EOF‐PCR approach that decomposes the panel data of PM2.5 and predictors into spatial structures (EOFs) and time expansion coefficients (ECs) by EOF analysis, establishes the PCR of the ECs of PM2.5, and simulates the PM2.5 concentrations in each city by projecting the fitted ECs through EOFs. The very heart of the new model is the PCR modeling and projection. The results are presented for PM2.5 concentrations over Jiangsu Province in eastern China. The results show that this EOF‐PCR model, which is based on EC1s with a cumulative variance contribution rate above 90%, has an average prediction accuracy of 65%. The model performs best in spring and autumn, better in summer and worst in winter. Most predictors have a maximum lag of a week, and they are quite different among seasons. Considering the influence of the spatial distributions of predictors, rather than covariates at a single site, this model can reflect regional influences and effectively improve the simulation effect.

Biomass burning has become one of the prominent sources of air pollution in Northeast China, where the land is largely covered by forest, grasslands, and agricultural crops. Nevertheless, the impact of biomass burning on air quality and the sensitivity of such impact to weather are rarely documented. In this study, we addressed these issues using satellite fire radiative power (FRP) and surface PM2.5 and CO data at 24 stations during fire seasons (March, April, October and November) in Northeast China from 2015 to 2017. Fire-polluted days were identified by tracing air parcels at the stations back to fire regions using a trajectory model, the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model. The results show that 60–80% the polluted days in Northeast China can be attributed to biomass burning in the fire seasons, varying among subregions due to the differences in landscapes, fire activities, and weather conditions. On fire-polluted days, the mean PM2.5 and CO concentrations from all observation stations in Northeast China reached 111 μg m−3 and 1.3 mg m−3, respectively. The hourly PM2.5 and CO concentrations on fire-polluted days could reach as high as 1000 μg m−3 and 10 mg m−3, respectively. By subregions, the mean PM2.5 concentrations were 128, 112, 102, 106 μg m−3, respectively, in the central, eastern, northern, and southern subregions, while mean CO concentrations were 1.2, 1.3, 0.8, 1.5 mg m−3, respectively, in the four corresponding subregions. On average, PM2.5 and CO concentrations on fire-polluted days elevated, respectively, by 22–54% and 4–11% from those on no-fire-polluted days, with the largest enhancement in the central subregion and the least in the southern subregion. We classified six predominant weather patterns during the fire seasons. When Northeast China was ahead of a strong Siberian High, fire-polluted days were least and FRP was weakest among the six patterns in most subregions, leading to lowest enhancement of PM2.5 and CO in the subregions. In contrast, two weather patterns exacerbated PM2.5 and CO pollution the most during fire episodes. Under one of the weather patterns, Northeast China was under a stagnant high-pressure system, resulting in poor dispersion conditions and thus high PM2.5 and CO pollution. The other pattern was characterized with high humidity and southwesterlies ahead of a trough, which brought about strong hygroscopic growth and regional transport of fire emissions. The degree to which the weather patterns impacted air pollution during fires varied largely among subregions. This study highlights the combined impacts of biomass burning and weather on air pollution. The findings and the developed methodology are helpful for forecasting air quality and implementing mitigation strategies during biomass burning.

Studies of the effect of market shocks on individuals’ risk-taking behavior often cannot determine whether the effect arose due to a change in an individual’s preferences or beliefs. This paper investigates the effect of a specific fat-finger shock – an external algorithmic trading error – that generated no information about market fundamentals and thus should not have induced a change in beliefs. Using both OLS and propensity-score matching DID methods, we find that investors who traded during the shock significantly reduced risk taking, while those who did not trade did not change their behavior. The significant effect was short-lived, mainly driven by the experience of small realized losses, and found only among small individual investors but not among large individual investors. The evidence suggests that the change in risk taking is likely attributable to a change in preferences.