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Big data analytics (BDA) is regarded as an advanced tool for achieving sustainable development as part of the grand challenges (GCs). However, it is not clear how BDA can be used by data scientists to solve the GCs with multisource data in a cross-disciplinary approach. Based on a case study of city-based dangerous goods transportation (DGT), this paper explores how data scientists use BDA to triangulate data, methods, knowledge and solutions for solving GCs. The contribution of this study is threefold: (1) it contributes to research on GCs and discusses how BDA can be used in problem solving for multidomain GCs from a management perspective; (2) it enriches the theory of information triangulation and proposes several steps for information triangulation in BDA to solve GCs; and (3) it contributes some practical implications for the management of organizations when solving social problems and pursuing sustainable development.

We investigate the route choice behavior of pedestrians under the condition of local view by using a field observation in a subway station and a microscopic pedestrian model with discrete space representation. The local view of a pedestrian means that the pedestrian's field of vision can be blocked by obstacles. Several typical phenomena with respect to behavior affected by the local view of pedestrians are observed through recording the movement of pedestrians in the subway station. Based on these observed phenomena and behaviors, a route choice model considering the effect of local view of pedestrians is developed. In the model, an algorithm for dividing feasibly vision areas is formulated. Two algorithms for computing the potential fields are then developed based on the results of dividing feasibly vision areas. By numerical experiments, the simulation results of the model are compared with the empirical observations to validate the model.

Exploring efficient, stable, and earth-abundant electrocatalysts for oxygen evolution reaction (OER) is of great significance for clean and renewable energy conversion technologies. In this work, in situ uniform Ni-doped tungsten carbide (Ni/WCX) nanoparticles (~3 nm) on carbon nanofibers (Ni/WCX-CNFs) that were to function as efficient OER catalysts were developed. Both the composition and electronic state of tungsten carbide (WCX: W-WC-W2C) could be regulated through varied Ni coupling. Owing to the synergistic effect between Ni and WCX, the reaction kinetics were facilitated, resulting in improved OER activity with low overpotentials of η10 = 350 mV (modified glassy carbon electrode) and η10 = 335 mV (self-supporting electrode). This work opens a facile territory for the development of cost-effective and highly promising OER electrocatalysts for use in real life applications.

Whether investor sentiment affects stock prices is an issue of long-standing interest for economists. We conduct a comprehensive study of the predictability of investor sentiment, which is measured directly by extracting expectations from online user-generated content (UGC) on the stock message board of Eastmoney.com in the Chinese stock market. We consider the influential factors in prediction, including the selections of different text classification algorithms, price forecasting models, time horizons, and information update schemes. Using comparisons of the long short-term memory (LSTM) model, logistic regression, support vector machine, and Naive Bayes model, the results show that daily investor sentiment contains predictive information only for open prices, while the hourly sentiment has two hours of leading predictability for closing prices. Investors do update their expectations during trading hours. Moreover, our results reveal that advanced models, such as LSTM, can provide more predictive power with investor sentiment only if the inputs of a model contain predictive information.

Nowadays flexible high-performance electromagnetic interference (EMI) shielding materials are greatly demanded in military and daily purpose. To yield high shielding effectiveness (SE), the traditional metallic EMI materials always require a large mass of loading in a composite matrix, which is uneconomic and harmful to the mechanical property of the materials. Herein the homogeneous decoration of Ag nanoparticles on a light-weight and robust carbon nanotube sponge (CNTS) based 3D conductive scaffold is introduced. The flexible Ag/CNTS/PDMS composites exhibit an extremely high and tunable EMI shielding performance with improved mechanical strength and high conductivity. The maximum EMI SE is measured to be even greater than 90 dB in the X-band (8–12 GHz) with a low loading of Ag (3%, wt %) and CNTS (4%, wt %). In addition, the 3D inter-connected pore structure enables EM waves to reflect multiple times inside the Ag/CNTS hybrids which results in a strong absorption ability. The total EMI shielding property can be further conveniently controlled by tuning the Ag-deposition parameters as well as the thickness of the sample. The current approach successfully avoids the dispersion problem of the fillers and will be of great importance in development of high-performance EMI shielding materials.

We investigated whether genetic susceptibility to tuberculosis (TB) influences lung adenocarcinoma development among never-smokers using TB genome-wide association study (GWAS) results within the Female Lung Cancer Consortium in Asia. Pathway analysis with the adaptive rank truncated product method was used to assess the association between a TB-related gene-set and lung adenocarcinoma using GWAS data from 5512 lung adenocarcinoma cases and 6277 controls. The gene-set consisted of 31 genes containing known/suggestive associations with genetic variants from previous TB-GWAS. Subsequently, we followed-up with Mendelian Randomization to evaluate the association between TB and lung adenocarcinoma using three genome-wide significant variants from previous TB-GWAS in East Asians. The TB-related gene-set was associated with lung adenocarcinoma (p = 0.016). Additionally, the Mendelian Randomization showed an association between TB and lung adenocarcinoma (OR = 1.31, 95% CI: 1.03, 1.66, p = 0.027). Our findings support TB as a causal risk factor for lung cancer development among never-smoking Asian women.

Solar thermal and coal are two major energy sources in solar aided power generation (SAPG) systems. Reasonably distinguishing the solar shares of the total electricity output is a problem that must be solved. This study modeled the energy balance, exergy balance and solar exergy balance of the key subsystems in an SAPG system. Meanwhile, this study also designed a new solar share evaluation method by tracing solar exergy flows and allocating exergy destruction. How and how much solar exergy was transferred from the sun to electricity could be theoretically estimated by analyzing the distributions of solar share and solar exergy destruction. The proposed method considered energy level differences between solar energy and coal without assuming plant efficiency or solar shares in each energy stream to be constant. The proposed method could not only be used to calculate solar-generated electricity on the point of exergy transfer and destruction, but also be further used for excavating the potential of solar share expansion.

For bilinguals, language control is needed for selecting the target language during language production. Numerous studies have examined the neural correlates of language control and shown a close relationship between language control and domain-general cognitive control. However, it remains unknown how these brain regions coordinate with each other when bilinguals exert cognitive control over linguistic and nonlinguistic representations. We addressed this gap using an extended unified structural equation modeling (euSEM) approach. Sixty-five Chinese-English bilinguals performed language switching and nonverbal switching tasks during functional magnetic resonance imaging (fMRI) scanning. The results showed that language control was served by a cooperative brain network, including the frontal lobe, the parietal cortex, subcortical areas, and the cerebellum. More importantly, we found that language control recruited more subcortical areas and connections from frontal to subcortical areas compared with domain-general cognitive control, demonstrating a reconfigurable brain network. In addition, the reconfiguration efficiency of the brain network was mainly determined by general cognitive ability but was also mediated by second language (L2) proficiency. These findings provide the first data-driven connectivity model that specifies the brain network for language control in bilinguals and also shed light on the relationship between language control and domain-general cognitive control.

The driving force for the comovement in stock returns is a long-standing debate between classical asset pricing theory and behavioral finance theory. It has become critically important recently for understanding systemic risk and risk contagion in the market. In this study, we propose complex networks enabled new methods to measure the causal comovement of individual stocks and the comovement structure of the market, which facilitate the examination of all kinds of hypotheses of comovement theories in a unified framework. Using a sample of the Chinese stock market from Jan. 1, 2006 to Dec. 31, 2016, we find that the degree of comovement generally intensifies over time, with a drastic increase from 2011 to 2015, while the comovement structure of the market changes with different market situations. Most importantly, our study reveals the driving force of causal comovement among individual stocks; that is, sentiment-based factors related to the market index indeed induce excess causal comovement in returns beyond that can be justified by fundamental factors including beta coefficient, book-to-market ratio, liquidity, profitability and volatility. Our study also reveals the determinants of comovement structure, which are attributable to the change of investors' behaviors in different periods. It turns out that investors in the Chinese stock market care about risk-return relationship in normal periods, while they seem to care only about risk in crisis periods.

In the era of big data, it is extremely challenging to decide what information to receive and filter out in order to effectively acquire high-quality information, particularly in social media where large-scale User Generated Contents (UGC) is widely and quickly disseminated. Considering that each individual user in social network can take actions to drive the process of information diffusion, it is naturally appealing to aggregate spreading information effectively at the individual level by regarding each user as a social sensor. Along this line, in this paper, we propose a framework for effective information acquisition in social media. To be more specific, we introduce a novel measurement, the preference-based Detection Ability to evaluate the ability of social sensors to detect diffusing events, and the problem of effective information acquisition is then reduced to achieving social sensing maximization through discovering valid social sensors. In pursuit of social sensing maximization, we propose two algorithms to resolve the longstanding problems in traditional greedy methods from the perspectives of efficiency and performance. On the one hand, we propose an efficient algorithm termed LeCELF, which resolves the redundant re-evaluations in the traditional Cost-Effective Lazy Forward (CELF) algorithm. On the other hand, we observe the participation paradox phenomenon in the social sensing network, and proceed to propose a randomized selection-based algorithm called FRIENDOM to choose social sensors to improve the effectiveness of information acquisition. Experiments on a disease spreading network and real-world microblog datasets have validated that LeCELF greatly reduces the running time, whereas FRIENDOM achieves a better detection performance. The proposed framework and corresponding algorithms can be applicable in many other settings in resolving information overload problems.

Organizational improvisation has been increasingly observed in information systems development (ISD), which leads to both positive and negative results. Extant studies have examined how to conduct effective improvisation, but findings are mainly based on variance-based models; a process model is missing. Our study fills this gap by conducting an in-depth case study of the Tencent messaging system development. Our study identifies a four-phase process model featuring, a continuous iteration between improvisational search and build. Our findings make important contributions to organizational improvisation literature in ISD and general management and provide a step-by-step guide for ISD managers to conduct effective improvisation.

The U.S. housing collapse in 2007 is widely blamed for inducing a financial crisis that spread to the real economy and caused a severe and prolonged downturn. This paper develops a model to investigate the role of gasoline price shocks in triggering the housing market collapse and identifies a new channel through which energy price shocks affect the financial market and the macro economy. Results suggest that unanticipated gasoline price shocks increase the cost of work commutes, lower the value of homes away from the city center, and increase foreclosure rates as homeowners either cannot afford mortgage payments amid elevated gas expenditures or seek to abandon underwater homes. The model predicts that gasoline price shocks disproportionately affect suburban households that face greater exposure due to longer commutes and lower incomes. Empirical evidence from the 2007–08 housing collapse is presented to corroborate this theory.

The inhibitory mechanism during the reaction between peptides from Phascolosoma esculenta and angiotensin I converting enzyme (ACE) was studied. Thermodynamics features of the peptide-ACE binding reaction measured by isothermal titration calorimetry (ITC) assay, combining with the decrease of ACE inhibition within 24 h implied that Gly-Asn-Gly-Ser-Gly-Tyr-Val-Ser-Arg decomposed during the reaction and played as a substrate-type inhibitor. The hydrolysate Gly-Asn-Gly-Ser-Gly-Tyr-Val (GNGSGYV) without ACE inhibitory activity was identified by UPLC & Q-TOF MS, while the hydrolysate Ser-Arg (SR) showed competitive inhibition of ACE with IC50 value of 790 μM. However, GNGSGYV and SR have synergistic effect on ACE and result in an ACE inhibitory IC50 value of 170 μM. The synergistic mechanism illustrated by two-step molecular docking discovered that SR firstly attacked the catalytic Zn of ACE and formed coordinate bond, and then GNGSGYV bound with the arginine of SR and residues along the channel of ACE active site by hydrogen bonds to block the substrate from entering. The circular dichroism spectra also verified that SR and GNGSGYV significantly changed the secondary structure of ACE.

Purpose Lung cancer is the leading cause of cancer death worldwide, and the predominant risk factor for its development is smoking. Thymidylate synthase (TYMS) is a key enzyme in DNA synthesis that catalyzes the conversion of deoxyuridine monophosphate to dTMP. Rs931794, a single nucleotide polymorphism located in the TYMS gene, was suggested to be associated with cancer risk. Methods To analyze the interaction between rs3819102 and environmental factors on the risk of lung cancer in a Chinese population, single nucleotide polymorphismscan was used to genotype this polymorphism in 974 lung cancer cases and 1005 control subjects. Results The frequencies of TT, CT, and CC genotypes of TYMS rs3819102 were 61.8%, 32.9%, and 5.3% in controls, and 53.8%, 38.4%, and 7.8% in cases, respectively. Compared with the TT genotype, the CT (odds ratio [OR], 1.380; 95% confidence interval [CI], 1.131-1.683), and CC (OR, 1.786; 95% CI, 1.213-2.644) genotypes were associated with an increased risk of lung cancer after adjustment for age, gender, smoking status, and family history. The C allele of rs3819102 is the risk allele for lung carcinogenesis in a dominant model (OR, 1.435; 95% CI, 1.188-1.735). In a stratified analysis, the risk effects of both the CT and CC genotypes of rs3819102 were more evident in subgroups of smokers and people without a family history of cancer. Conclusion The rs3819102 polymorphism in TYMS might increase susceptibility to environmental factors and contribute to the risk of lung cancer. The C allele is a risk allele in lung carcinogenesis.

Domain-general cognitive control is closely related to language control during bilingual language production. Previous neural imaging studies have revealed a highly overlapped but rewired brain network for language control and nonverbal cognitive control. In the present study, we examined this issue from a training perspective. Two groups of participants performed the language switching task at pre-and post-tests during functional magnetic resonance imaging (fMRI) scanning. After the pre-test, the experimental group received 8-day training in a non-verbal switching task, while the control group performed an unrelated color judgement task. We found that only the experimental group but not the control group showed decreased strength of connectivity from the ventral lateral frontal cortex to the left caudate nucleus and from the medial surface of the frontal lobe to the left thalamus. These results indicate an increased efficiency after nonverbal training for the frontal cortex to implement domain-general suppression and monitoring in a domain-specific conflict context during bilingual language and lexical selections. This study is the first to investigate the transfer effects of nonverbal cognitive control on the brain network of bilingual language control and shed light on the mechanisms of how domain-general cognitive control may underpin bilingual language control.

In recent years, China's environmental regulation efforts have mainly focused on severely polluted “key regions.” The central government has designated the “three rivers and three lakes basins” (3Rs3Ls) as key regions for water pollution control and has imposed a variety of regulations to improve water quality in those basins. This paper evaluates the effects of the water quality regulations on firms' emissions of chemical oxygen demand (COD) and productivity in the 3Rs3Ls basins. We find that although the water quality regulations forced many small, heavily-polluting firms to shut down, they had no statistically significant effects on surviving firms' productivity because they were ineffective in reducing their COD emissions. A policy that forces the surviving firms to reduce their emissions would reduce their output values and productivity, at least in the short run. However, the effect is likely to be small. Specifically, a 10% reduction in total COD emissions from the industrial sectors would require only a 0.1% reduction in output values under the current production technologies. These findings are robust to alternative specifications and sampling strategies.

With the increasing use of recommender systems in various application domains, many algorithms have been proposed for improving the accuracy of recommendations. Among a number of other dimensions of recommender systems performance, long-tail (niche) recommendation performance remains an important challenge, due in large part to the popularity bias of many existing recommendation techniques. In this study, we propose CORE, a cosine-pattern-based technique, for effective long-tail recommendation. Comprehensive experimental results compare the proposed approach to a wide variety of classical, widely-used recommendation algorithms and demonstrate its practical benefits in accuracy, flexibility, and scalability, in addition to the superior long-tail recommendation performance.

The relationship between foreign entry mode choice and the performance of small-medium sized enterprises (SMEs) has been an overarching theme of research of the past decade. However, the research in this area has been hampered by the difficulty of defining and measuring performance. In this study, we used a multi-item measure of performance, which takes into account the relative importance of each measure and the perceived level of satisfaction, to analyse 146 SMEs in Norway. Our regression analysis shows that firm characteristics: size and sector of operation, significantly influence performance. However, prior international experience did not significantly influence performance. In terms of entry mode via international joint venture, trust and congruity of goals between partners have a positive and significant influence on performance.

Nature reserves are hubs of biodiversity conservation in China, but their spatial distributions are not in line with the priority set based on biological criteria. This raises some fundamental questions: What caused this discrepancy? How was the spatial distribution of nature reserves determined in China? This paper aims to address these questions using a unique nation-wide county-level database. Our results reveal that although ecological factors play a significant role in nature reserve designations, economic considerations appear to be more significant in explaining the spatial distribution of local nature reserves in China. The opportunity cost of land conservation affects both the probability of designation and the amount of land designated for nature reserves in a county, and the effects vary by region, type of nature reserves, and time period of designation. Implications of these results for new nature reserve designations and for sustainable conservation of the existing protected areas are discussed.

Objective To observe effects of rosiglitazone (RSG) infusion therapy on perihematomal peroxisome-proliferator-activated receptor gamma (PPARγ), glutamate, blood-brain barrier (BBB) permeability, and brain edema. Methods Fifty male rabbits (2.8–3.4 kg) were randomly assigned to a normal control (NC) group, model control (MC) group, RSG group, minimally invasive surgery (MIS) group, or MIS and RSG (MIS+RSG) group. Intracranial hemorrhage was induced in all rabbits except for the NC group. MIS procedures were performed to evacuate the intracranial hemorrhage 6 hours after the intracranial hemorrhage model was prepared successfully. The animals were sacrificed on day 7, and the perihematomal brain tissue was obtained to determine PPARγ, glutamate, and BBB permeability. Results Compared with the MC group, the MIS group displayed a remarkable decrease in PPARγ, glutamate, and BBB permeability. The RSG group showed similar results in glutamate level and BBB permeability but a significant increase in PPARγ. The MIS+RSG group displayed an increase in PPARγ and a more significant decrease in glutamate, BBB permeability, and neurologicl deficit scores compared with the other groups. Conclusions Performing MIS followed by RSG infusion therapy might increase PPARγ expression and might be more efficacious for reducing glutamate level and BBB permeability and improving neurologic function than MIS or RSG therapy used alone.

Solar aided power generation (SAPG) technology has been proven as an efficient way to use solar energy for power generation purpose. In a SAPG plant, a solar field consisting of parabolic solar collectors is normally used to supply the solar heat to preheat feedwater and replace the high-pressure extraction steam. However, the outlet temperature of reheated steam decreased with the integration of solar thermal which sacrificed the system performance. As an improvement, the second solar field was proposed to preheat the reheated steam to maintain its outlet temperature and the average temperature of regenerative Rankine cycle before or after solar integration. Through a case study using A 600 MW supercritical SAPG plant operating in fuel-saving Using solar to preheat feedwater and reheated steam could improve overall cycle efficiency and solar-to-electricity efficiency by 1.91% and 6.01%, respectively. The solar share was expanded from 9.53% to 17.26%. The electricity generated per solar aperture area under the design condition was 187.96 W/m2, which was 26.91% higher than that of the system without the second solar field.

Financial development has been found to have mixed effects on CO2 emissions. One reason appears to be the relationship is not linear, as is assumed in most earlier studies. This paper re-examines the relationship between financial development and CO2 emissions based on a panel data of 61 countries categorised as high- and middle-income economies, from 1990 to 2018. This study uses the linear ARDL and nonlinear ARDL (NARDL) methods to analyse the impact of positive and negative shocks in financial development on CO2 emissions. Additionally, the panel causality between the variables is also investigated. The analyses from ARDL and NARDL reveal that in the long run, financial development helps to minimise CO2 emissions for high income economies, but it raises CO2 emissions and thereby decreases environmental quality for middle-income economies. Supporting our nonlinear hypothesis, we find that both negative and positive shocks of financial development have significant impacts on CO2 emissions, while the latter have a more profound effect. In particular, the findings suggest that the impacts of financial development on CO2 emissions are distinctive in high- and middle-income economies, leading to useful policy implications, including the suggestion that international development bodies help middle-income countries to incorporate consideration of environmental effects into the operation of their financial institutions and systems at an earlier stage of development than would generally be the case.

Solar-aided power generation (SAPG) is an effective method for achieving clean and efficient production of electricity. The unique characteristics of the non-concentrating solar energy and air preheating process open up a novel method for low-cost and efficient solar/coal hybrid power generation. In the proposed novel SAPG, non-concentrating solar energy achieves high solar-to-electricity efficiency by efficiently integrating it with the air preheating process. Additionally, the new system generates electricity at a low cost by applying non-concentrating solar collectors. The results reveal that based on a typical 1000 MW coal-fired power plant, the proposed SAPG generates 12.6 MWe of additional output power with a 0.57% increase in coal-based thermal efficiency, and reduces the exergy loss during the air preheating process by 36.6%. Owing to the low cost and efficient utilization of non-concentrating solar energy, the cost of solar-generated electricity of the proposed SAPG is only 47.4% of that of the conventional SAPG. The high thermal and economic performance of the proposed SAPG opens up a low-cost and efficient solar/coal hybrid power generation mode through the integration of non-concentrating solar energy and air preheating process.

Superconducting nanowires single-photon detectors (SNSPDs or SSPDs) have emerged as an attractive single-photon detection technology with high performance. Two types of SNSPDs have been developed so far. One is the standard-fiber-coupled SNSPD with the light normally incident on the meandered nanowires, the other is waveguide-coupled SNSPD with the nanowires fabricated on the surface of the waveguide which guides photons while the fiber is coupled to the waveguide. Here we propose a new type of SNSPD integrated with microfiber. The photons are guided by a microfiber and evanescently absorbed by the nanowire of SNSPD when the nanowire is parallel and very close to the microfiber. The numerical simulation results show that the fiber to detector coupling efficiency can be close to unity with optimized device structure/parameters. With a minimal total NbN nanowire length of about 300 μ m, the absorption of the nanowire can reach 90%.

The present study investigated the neural correlates of naming disadvantage of the dominant language under the mixed language context. Twenty one unbalanced Chinese-English bilinguals completed a cued picture naming task while being scanned with functional magnetic resonance imaging (fMRI). Behavioral results showed that naming pictures in the second lanuage (L2) was significantly slower than naming pictures in the first language (L1) under a single language context. When comparing picture naming in L2 to naming in L1, enhanced activity in the left inferior parietal lobule and left cerebellum was observed. On the contrary, naming pictures in Chinese (L1) was significantly slower than naming in English (L2) under the mixed language context. The fMRI results showed that bilateral inferior frontal gyri, right middle frontal gyrus, and right supplementary motor area were activated to a greater extent in L1 than in L2. These results suggest that the dominant language is inhibited to a greater extent to ensure the production of the second language under the mixed language context. Therefore, more attentional control resources are recruited when bilinguals produced the dominant language. The present study, for the first time, reveals neural correlates of L1 naming disadvantage under the mixed language context.

The focus of this paper is the dynamic shear characteristics of titanium alloy Ti-6Al-4V at large strain rates. Dynamic load testing of titanium alloy Ti-6Al-4V are performed by the split Hopkinson pressure bar (SHPB) at different strain rates, which involve the SHPB compression test and the SHPB shear test. The material behaviour during the tests are measured and recorded. The strain rates for the compression and shear tests range from 5.0 × 102 s−1 to 9.0 × 103 s−1 and 1.0 × 104 s−1 to 3.0 × 105 s−1, respectively. The effect of competing mechanisms—strain rate hardening and thermal softening—on the adiabatic shear band is analysed. A size effect on shear band width is also found. According to the results, a modified Johnson–Cook (J–C) constitutive model is applied to tests at an ultrahigh strain rate. Furthermore, a finite element method (FEM) simulation is conducted to validate different aspects of the methodology. The SHPB shear test is confirmed as a process of pure shear. A comparison of the shear stress-strain curves from the mechanical tests and simulation show good agreement based on the modified J-C constitutive model.