Robustness Testing Research Articles

Metamorphic Robustness Testing for DeepL Translation

Due to the complexity and flexibility of natural languages, such robustness testing involving the ability of machine translation software to handle incorrect or unintended input are extremely challenging, especially if there is no human oracle or reference translation. In this paper, using metamorphic robustness testing methods, we compare the translation of the primitive input with the translation of a subsequent input that has different types of very small changes and may cause large changes in the translation results. The lack of robustness of the DeepL translation is shown by our experiments, these preliminary results show that metamorphic testing has potential in the field of natural language processing.

Banks’ return reaction to freedom, sentiment, and uncertainty

The paper aims to investigate the impact of freedom dimensions, investor sentiment, and uncertainty on bank stock returns. Additionally, this study examines the interaction between economic freedom dimensions and oil prices. To meet the study’s objectives, a two-step GMM estimator was applied to the data collected from 173 banks in 18 Middle East and North Africa (MENA) region countries during 2010–2020. The findings revealed that the influence of economic, business, and labour freedoms on banks’ stock returns was negative and significant, but government spending was positive and significant. The results for the region’s monarchies indicated similar effects to those of the entire MENA region, except for lagged bank stock returns that were negative. Besides, both investor sentiment and uncertainty positively impact bank stock returns. In addition, it was found that the interaction between freedom and oil price significantly and positively impacted bank performance. The robustness testing results confirmed this finding. Moreover, this research stands out as one of the limited investigations that have scrutinized the 18 MENA countries, which are predominantly Islamic and characterized by their distinct social norms, geography, and cultural identities.

Impact of Intelligent Manufacturing on Total-Factor Energy Efficiency: Mechanism and Improvement Path

Intelligent technology is the core driving force of the fourth industrial revolution, which has an important impact on high-quality economic development. In this paper, the panel data of 30 provinces from 2006 to 2019 were selected to construct a regression model to conduct an empirical analysis on the role and mechanism of intelligent manufacturing in improving total factor energy efficiency. The research results show that first, the productivity effect, scale effect and resource allocation effect of intelligent manufacturing can significantly improve the energy efficiency of the total factor, and the conclusion is still established after endogenous treatment and robustness testing. Second, the results of the action mechanism show that labor price distortion and carbon emission trading policy are important mechanisms for intelligent manufacturing to improve total-factor energy efficiency. Specifically, the corrected labor price can enhance the motivation of enterprise research and development and innovation and solve the dilemma of the low-end industrial structure, thus improving the efficiency of total-factor energy efficiency. The carbon emission trading policy strengthens the willingness of enterprises to improve the process, eliminate backward equipment and increase the research and development of green technology, and it has a positive regulatory role in the process of improving total-factor energy efficiency in intelligent manufacturing.

Implementation of AHP and Black Box Testing to the Development of an Information System for Assessing the Feasibility of BUMDES Submissions

The existence of institutional village enterprises (BUMDES) has never been adequately monitored in terms of the growth of village-owned businesses in each village. According to the data, there are 17 BUMDES in the Muara District that have been inactive for the most part. Due to the difficulty of monitoring the progress of BUMDES, a significant number of them have become stalled or even inactive. In addition, many BUMDES managers are frequently unprepared to operate the newly opened business. Readiness in terms of the quality of human resources also affects the formation of BUMDES. Consequently, the objective of this study is to facilitate the monitoring of business developments carried out by BUMDES actors in their respective villages, thereby facilitating the feasibility assessment of BUMDES. Aside from that, the purpose of this study is to determine the viability of applying for BUMDES as one of the requirements for obtaining a recommendation from the village head for submission to the Village Ministry. The feasibility analysis employs the AHP method with multiple parameters, including business age, business type, and business capital. According to research findings with applications, several BUMDES are declared unfit, while others are declared feasible. BUMDES with declared eligibility has AHP values ranging from 0.382 to 0.619. Meanwhile, BUMDES that are unworthy receives AHP values ranging from 0.235 to 0.239. It can also be determined based on the weight of each criterion as to whether or not it is appropriate for BUMDES. While the results of black box testing for the system's feasibility using 10 types of testing, including Equivalence Partitioning, Boundary Value Analysis/Limit Testing, Comparison Testing, Sample Testing, Robustness Testing, Behavior Testing, Performance Testing, Requirement Testing, Endurance Testing, and Cause-and-Effect Relationship Testing. Based on the test results, the system is 100% feasible to be used by users.

The Impact of Basic Public Health Services on Migrant Peasant Workers’ Urban Integration: Evidence from China

The key to promoting urbanization in China is to achieve urban integration of migrant peasant workers, and basic public health services may have a potential social impact on the subjective welfare of migrant peasant workers. In this paper, we use data from the China Migrants Dynamic Survey (CMDS) to study the impact of basic public health services on the urban integration of migrant peasant workers. The results show that basic public health services can significantly improve the probability of migrant peasant workers’ urban integration. The conclusions remain robust after mitigating potential endogeneity issues using the propensity score matching method (PSM), the CMP method, and robustness testing by replacing the explanatory variables with the reduced tail treatment. Further research found that the impact of basic public health services on migrant peasant workers’ urban integration is heterogeneous. The urban integration effect of basic public health services is more significant in male, high school and above, migrant peasant workers’ groups. The urban integration effect of basic public health services gradually increases with upgrading of the urban grade at the second-tier city and higher urban levels, and it also plays a vital role in the urban integration of the migrant peasant workers at the third-tier city and lower urban levels. Our findings also provide an evidence-based policy for China to promote equalizing basic public health services and a path to the urbanization of migrant peasant workers.

In-vivo along muscle fascicle strain heterogeneity is not affected by image registration parameters: Robustness testing of combined magnetic resonance-diffusion tensor imaging method

Coupled with diffusion tractography, non-rigid registration of high-resolution anatomical MR images allows the calculation of local strains along human skeletal muscle fascicles in-vivo. A reference study (passively imposed lengthening of gastrocnemius medial muscle) reported local shortening and lengthening occurring along the same muscle fascicles. However, the robustness of strain amplitudes and distribution patterns should be studied, as the heterogeneity of local length changes has major implications for muscle function. Using a previous image set of human medial gastrocnemius (GM) we aimed at testing: (1) the consistency of our MRI-DTI analysis workflow against changes made to the software environments, (2) the hypothesis that non-rigid demons algorithm tuning parameters (16 paired combinations were tested) are not a significant determinant of muscle fiber direction strain heterogeneity caused by passive knee extension. A profoundly altered analysis workflow did reproduce the original results well, showing a general pattern of proximally lengthened and distally shortened muscle fascicles (strain amplitude range: 21%–67%). Hierarchical shift function analyses and pairwise comparison of strain distributions between 10 equal parts of the tracked GM fascicles confirmed the hypothesis showing no significant effects of tuning parameters determining the in-vivo deformation field inhomogeneity. The findings show the robustness of the MRI-DTI method, and confirming the hypothesis, also the consistency of along muscle fascicle strain heterogeneity patterns against parameter selection. However, the strain amplitudes do vary with parameter choices. New studies are indicated to determine optimal tuning parameters to achieve accurate strain amplitudes compared to exact strains.

A novel hybrid BPNN model based on adaptive evolutionary Artificial Bee Colony Algorithm for water quality index prediction

With the accelerated industrialization and urbanization process, water pollution in rivers is being increasingly worsened, and has caused a series of ecological and environmental issues. The prediction of river water quality index (WQI) is a prerequisite for river pollution prevention and management. However, the water quality data series is non-smooth and non-linear, and a strong coupling relationship between different water quality parameters that influence each other is observed, making it an inevitable problem to accurately predict water quality parameters. To this end, a combination of machine learning and intelligent optimization algorithms was hereby used to break this dilemma. Specifically, a Back Propagation Neural Network (BPNN) model was established using the Artificial Bee Colony (ABC) algorithm, with the three adaptive evolutionary strategies, i.e., dynamic adaptive factors, probability selection and gradient initialization combined to form the Adaptive Evolutionary Artificial Bee Colony (AEABC) algorithm. The experimental results of this algorithm demonstrate that the AEABC-BPNN model only requires 14 iterations to converge in this case. The predictions of WQI can reduce the error evaluation indicators of mean square error (MSE) to 0.2745, which is at least 25.2% lower than those of the rest algorithms compared, and the mean absolute percentage error (MAPE) is lower than 7.58%. In four WQIs, the prediction interval coverage percentage (PICP) reaches 100%. Besides, robustness testing experiments were also designed to verify that the AEABC-BPNN model still outperforms the rest of the algorithms in terms of prediction accuracy when guided by historical error data. The proposed model plays a pivotal role in water pollution management in rivers and lakes, and has scientific significance for future water environmental protection.

Validation of the Reveal® 3-D for Gluten Assay for Detection of Gluten in Clean-in-Place Rinses and Stainless Steel Environmental Surfaces: AOAC Performance Tested MethodSM 122201.

Reveal® 3-D for Gluten is an immunochromatographic assay for the qualitative detection of gluten in environmental samples. The test uses monoclonal antibodies reactive to prolamins in wheat. The objective of the study was to validate the Reveal 3-D test for detection of gluten in clean-in-place rinse and swabs from a stainless steel surface. Elements of the study included food selectivity and interference testing, matrix testing, an assay robustness study, and reagent stability/lot-to-lot consistency testing. Wheat flour was used as the spiking material for all matrixes. In selectivity and interference testing, nine target matrixes all tested positive and 36 of 39 non-target matrixes tested negative. Almond flour, sesame flour, and cornstarch produced positive results as 100% commodities; reactivity can be eliminated with dilution or by testing without use of food extraction buffer, which is not a standard part of the environmental testing method. With a gluten spike at 9.3 mg/kg, chestnut flour, guar gum, and xanthan gum as 100% commodities inhibited the ability of the assay to detect gluten when tested without dilution. In quaternary ammonium clean-in-place rinse and swabs from stainless steel, 100% positive results were obtained at levels of 2.8 mg/kg and 4.7 µg/100 cm2, respectively. Results of independent laboratory testing of swabs from stainless steel supported those of internal trials. Robustness testing showed that introducing variations to three operating parameters simultaneously had no adverse effect on assay performance. In the reagent stability study, data supported kit expiration dating of 11 months. Results of the current study show that the Reveal test is an accurate and reliable method for qualitative detection of gluten in select clean-in-place rinse and environmental samples. The Reveal test was able to detect gluten at levels of 2.8 ppm in clean-in-place rinse and 4.7 µg/100 cm2 in swabs from stainless steel.

Financial asset allocation and green innovation

<abstract> <p>Sustainable development is a key issue of global concern, and countries around the world are striving to promote green development. From the perspective of financial asset allocation motivation, this paper explores the impact of financial asset allocation on green innovation based on the data of A-share listed non-financial companies from 2011 to 2021. First, there is an inverted U-shaped relationship between the proportion of financial asset allocation and the green innovation of physical enterprises, that is, as the proportion of financial asset allocation increases, the green innovation output of enterprises first increases and then decreases. After robustness testing, the conclusion still holds. Second, further testing of the intermediary mechanism shows that the moderate holding of short-term financial assets by real enterprises can increase the output of green innovation by alleviating financing constraints, which is manifested as the "reservoir" effect. The "crowding out" effect plays a leading role when overallocation of financial assets reduces liquidity supply and capital expenditure, which in turn reduces green innovation output. Third, in the test of financial asset allocation preference, it is found that the short-term financial assets held by enterprises mainly play a "reservoir" effect, that is, they tend to be "preventive" motives. Holding long-term financial assets mainly exerts a "crowding out" effect, that is, tends to "seek profits" motives. Finally, there are differences in the impact of financial asset allocation on green innovation output among enterprises with different property rights, different monetary policies and different social responsibilities.</p> </abstract>

A Validated Liquid Chromatographic Method for the Estimation of Imatinib Mesylate in Dosage Forms: Application to Chemometrics based Robustness Testing and Greenness Assessment

An eco-friendly liquid chromatography method was developed for determining imatinib mesylate in pharmaceuticals. During pre-development studies, Using a greener mobile phase and a combination of qualitative and semi-quantitative green metrics techniques, the environmental sustainability of the procedure was maintained. Methanol:water (pH maintained at 3.5 using orthophosphoric acid) at 75:25%, v/v flowing at 1 mL/min was the final mobile phase used on a C-18 column. The diode array detector detected imatinib at 262 nm. Method specificity, accuracy, precision, selectivity and system suitability were tested over a linear concentration range of 5-120 μg/mL of imatinib. The limit of detection and limit of quantitation values were 1.5 and 5.0 μg/mL, respectively. In addition, the factorial design showed the procedure to be reliable with minimum testing. Finally, the method recovered the maximum (> 99%) of the analyte from the dosage form. Overall, the present method is suitable for routine applications in quality control of dosage forms of imatinib.

Investigation of the sunspots and GDP nexus: The case of Balkan countries

The phenomenon known as sunspots refers to regions of the Sun?s photosphere that are darker than their surroundings because their surface temperature is lower. The sunspot growth theory, however debatable, is one of the first explanations for economic development that explains how variations in the Sun?s activity affect the business cycle. Jevons developed the sunspot hypothesis in 1875. To reevaluate this notion, this research uses correlation and regression analysis to explore the relationship between sunspots and GDP in the context of 11 Balkan nations over the years 1960-2021. By extending the sample of nations in panel regression models to include all nations on Earth, further robustness testing is accomplished. It was found that there exist significantly negative medium strength correlations between sunspots and gross domestic product values of 8 out of 11 Balkan countries. Similar findings were obtained using simple linear regression analysis. The results of the cross-country panel regression models further highlight the negative impact of solar activity on economic activity, which is also associated with nations that are located at higher latitudes.

Cellphone laws and rear-end accidents

In an attempt to reduce accident frequency caused by distraction involving cellphone use, the state of California enacted two sets of laws banning cellphone use while driving. We examine the relationship between laws to ban cellphone use while driving and rear-end accident frequency in California. Using a panel data set that groups accidents by geographic location, we find evidence that the association between California’s handheld cellphone ban and the number of rear-end accidents is negative and statistically significant. In robustness testing, we find this result is unaltered when we use a broader definition of “collision accident.” These results have implications for public safety and transportation, automobile insurance markets and insurance regulation.

Effect of childbearing-age women's family status on the health status of three generations: evidence from China.

It is widely recognized that inequalities in social status cause inequalities in health. Women in a family often directly influence three generations-women themselves, their children and their parents -yet the effect of women's family status on their own health status and that of the two generations before and after is not clear. Taking data from the China Family Panel Studies, this study used an ordered response model to investigate the effect of childbearing-age women's family status on the health status of three generations. The results showed that increases in childbearing-age women's family status improved the health status of the women themselves and their children. Unlike previous studies, however, we found that higher family status did not improve parents' health status but decreased it. The mechanism analysis indicated that women's family status influenced the health status of three generations through economic conditions, resource allocation, and child discipline. The results held after robustness testing. Our findings contribute to knowledge in related fields and provide theoretical support for policies that empower women.

Digital transformation, risk-taking, and innovation: Evidence from data on listed enterprises in China

This study uses text mining technology to construct an index of digital transformation and discusses the impact of digital transformation on enterprise innovation and its mechanisms from theoretical and empirical perspectives. It also analyzes whether digital transformation can significantly enhance enterprises’ value through innovation. The findings are presented as follows: first, digital transformation has a positive and significant impact on enterprise innovation, and this finding holds true when we conduct robustness testing and endogeneity processing. Second, the influence of digital transformation on enterprise innovation varies significantly according to enterprise size, ownership, and industry. Third, risk-taking plays an intermediary role between digital transformation and innovation. Fourth, the innovation incentive effect of digital transformation has a value enhancement function with a two-year lag, while it lacks a value enhancement function in the current year, following year, or next three years. In the modern era of innovation-driven and cross-border integration, this study deepens the theoretical understanding of innovation-driven and digital transformation. It also promotes the deeper integration of real and digital economies in practice.

Conflict with children, psychological depression, and problematic internet use among Chinese older adults: The moderating effect of sociability and living situation.

Problematic internet use among the elderly is an emerging area as previous studies focused more among the young people. Only a few studies focused on problematic internet use at the level of individual characteristics of older adults or on mitigating factors at the level of the older adult's family, ignoring family-level disruptive factors. The purpose of study is to investigate the relationship between conflict with children and problematic internet use among the elderly, as well as the mediating mechanisms and boundary conditions of the relationship. The valid sample of study composed of 428 older adults from 39 different villages and communities in central China. Data analyses were conducted by SPSS, MPLUS, and SmartPLS software. To test our hypotheses, we implement several quantitative methods, including confirmatory factor analysis (CFA), correlations analysis, and ordinary least squares (OLS) regression. Also, we employed partial least square structural equation modeling (PLS-SEM) for robustness testing. The results indicated that conflict with children was positively associated with problematic internet use of old people; psychological depression mediated the relationship between conflict with children and old adults' problematic internet use; sociability moderated the effect of conflict with children on psychological depression; and living situation moderated the effect of psychological depression on problematic internet use among the elderly. The current research improved the understanding of the mechanisms that produce problematic internet use among the elderly and helped prevent or reduce problematic internet use in older adults in terms of family support systems and individual ability characteristics.

Fast absolute 3D CGO-based electrical impedance tomography on experimental tank data

Objective. To present the first 3D CGO-based absolute EIT reconstructions from experimental tank data. Approach. CGO-based methods for absolute EIT imaging are compared to traditional TV regularized non-linear least squares reconstruction methods. Additional robustness testing is performed by considering incorrect modeling of domain shape. Main Results. The CGO-based methods are fast, and show strong robustness to incorrect domain modeling comparable to classic difference EIT imaging and fewer boundary artefacts than the TV regularized non-linear least squares reference reconstructions. Significance. This work is the first to demonstrate fully 3D CGO-based absolute EIT reconstruction on experimental data and also compares to TV-regularized absolute reconstruction. The speed (1–5 s) and quality of the reconstructions is encouraging for future work in absolute EIT.

The Comprehensive Impact of Outward Foreign Direct Investment on China’s Carbon Emissions

Outward foreign direct investment (OFDI), as an important carrier of global technology and industrial transfer, will significantly impact the home country’s environment. Therefore, using data from 30 Chinese provinces gathered between 2004 and 2019, we empirically analyze the impact of OFDI on China’s carbon emissions across two dimensions: total carbon emissions and carbon emission efficiency. In addition, when the previous studies explored the impact of OFDI on carbon emissions, there were few studies on the synergistic emission reduction effect of OFDI. Therefore, based on sorting out previous research, we incorporated OFDI, technological progress, industrial structure upgrading, international trade, and carbon emissions into the same analytical framework. Based on the classic fixed model, we introduce the interaction term further to explore the synergistic emission reduction effect of OFDI. Our model suggests that OFDI has increased total carbon emissions, but the associated reverse technology spillover has improved carbon emission efficiency. We also found a synergistic emission reduction effect between OFDI and technological progress, international trade, and industrial structure upgrading. This synergistic effect suppresses the growth of total carbon emissions and improves carbon emissions efficiency. Robustness testing confirmed these results. This research also provides a relatively novel perspective for China to achieve the goals of “carbon peaking” and “carbon neutrality”.

Utilization and out-of-pocket expenses of primary care among the multimorbid elderly in China: A two-part model with nationally representative data.

Multimorbidity has become an essential public health issue that threatens human health and leads to an increased disease burden. Primary care is the prevention and management of multimorbidity by providing continuous, comprehensive patient-centered services. Therefore, the study aimed to investigate the determinants of primary care utilization and out-of-pocket expenses (OOPE) among multimorbid elderly to promote rational utilization of primary care and reduce avoidable economic burdens. The study used data from CHARLS 2015 and 2018, which included a total of 4,384 multimorbid elderly aged 60 and above. Guided by Grossman theory, determinants such as education, gender, marriage, household economy, and so on were included in this study. A two-part model was applied to evaluate primary care utilization and OOPE intensity in multimorbid populations. And the robustness testing was performed to verify research results. Primary care visits rate and OOPE indicated a decline from 2015 to 2018. Concerning primary outpatient care, the elderly who were female (OR = 1.51, P < 0.001), married (OR = 1.24, P < 0.05), living in rural areas (OR = 1.77, P < 0.001) and with poor self-rated health (OR = 2.23, P < 0.001) had a significantly higher probability of outpatient utilization, whereas those with middle school education (OR = 0.61, P < 0.001) and better household economy (OR = 0.96, P < 0.001) had a significantly less likelihood of using outpatient care. Rural patients (β = -0.72, P < 0.05) may have lower OOPE, while those with better household economy (β = 0.29, P < 0.05; β = 0.58, P < 0.05) and poor self-rated health (β = 0.62, P < 0.001) occurred higher OOPE. Regarding primary inpatient care, adults who were living in rural areas (OR = 1.48, P < 0.001), covered by Urban Employee Basic Medical Insurance (UEBMI) or Urban Rural Basic Medical Insurance (URBMI) (OR = 2.46, P < 0.001; OR = 1.81, P < 0.001) and with poor self-rated health (OR = 2.30, P < 0.001) had a significantly higher probability of using inpatient care, whereas individuals who were female (OR = 0.74, P < 0.001), with middle school education (OR = 0.40, P < 0.001) and better household economy (OR = 0.04, P < 0.001) had a significantly lower tendency to use inpatient care. Significantly, more OOPE occurred by individuals who were women (β = 0.18, P < 0.05) and with better household economy (β = 0.40, P < 0.001; β = 0.62, P < 0.001), whereas those who were covered by URBMI (β = -0.25, P < 0.05) and satisfied with their health (β = -0.21, P < 0.05) had less OOPE. To prompt primary care visits and reduce economic burden among subgroups, more policy support is in need, such as tilting professional medical staff and funding to rural areas, enhancing awareness of disease prevention among vulnerable groups and so on.

INTERNET USE, FINANCE ACQUISITION AND RETURNING MIGRANT WORKERS’ HOME ENTREPRENEURSHIP — EMPIRICAL ANALYSIS BASED ON CLDS2016

Whether Internet use can inspire returning migrant workers’ home entrepreneurship is of great practical significance for promoting rural revitalization. Based on the data of China Labor Dynamic Survey (CLDS) in 2016, this paper empirically studies the impact of Internet use on returning migrant workers’ home entrepreneurship. The results show that, firstly, Internet use can significantly improve the entrepreneurial probability of migrant workers returning home by 8%. The results remain significant after using the instrumental variables method for endogenous problem solving and propensity score matching, changing the sample size for robustness testing. Secondly, Internet use promotes migrant workers returning home to make entrepreneurial choices mainly through expanding informal finance and obtaining formal finance. However, the mechanism of expanding informal finance has only been effective for returning migrant workers with higher level of social trust. Thirdly, Internet use has heterogeneous impact on returning migrant workers’ home entrepreneurship, which is reflected in the fact that Internet use will more significantly promote the entrepreneurial probability of migrant workers returning home with necessity entrepreneurship motivation, close to banks, eastern and central regions and developed areas, and internet use will also significantly promote the probability of opportunity entrepreneurship among migrant workers returning home who are satisfied with their household economic situation. Therefore, it is necessary to further improve the construction of broadband infrastructure in rural areas, especially western and developing areas, set up training platforms for returning migrant workers’ home entrepreneurship, promote employment through entrepreneurship and stimulate regional economic vitality, so as to accelerate rural revitalization.

Does China's low-carbon action reduce pollution emissions? A quasi-natural experiment based on the low-carbon city construction.

To achieve the goal of "carbon peak and carbon neutrality", it is crucial for China to effectively control environmental pollution in low-carbon action (LCA). Based on the evidence from 283 cities in China from 2007 to 2019, the difference-in-differences (DID) method is applied to explore the impact of LCA on pollutant emissions represented by the pilot of low-carbon city construction (LCCC) in China. The main findings are as follows. First of all, the LCCC suppresses pollution emissions, and the basic conclusions are still stable after endogenous treatment and robustness testing. Secondly, the mechanism analysis reveals that the main path of LCCC affecting pollution reduction comes from the progress of green technology and the upgrading of industrial structure. Finally, the heterogeneity analysis shows that the pollution reduction effect of the LCCC is better in the eastern region and cities with higher level of green economy development. Based on the policy standpoint of environmental protection, the LCCC has opened up a reasonable exploration path for China and other countries in the world to carry out effective pollution reduction.