Comprehensive Index Research Articles

A Comprehensive Evaluation Method for Environmental Pollution in Tourist Attractions Based on Improved Principle Component Analysis

In order to address the problem of the reliability of current environmental pollution assessment methods, a comprehensive assessment method of environmental pollution in tourist scenic spots based on improved principle component analysis was proposed. First air, water, and soil pollution for data tourist attractions in the top 5 metropolitan cities of India are collected. Then, the original pollution data is cleaned, the data clustering method is used to classify the pollution data, and the comprehensive evaluation index system of environmental pollution in tourist attractions is established. Finally, the comprehensive evaluation method is implemented to calculate the evaluation values of various indicators, and the comprehensive assessment results of pollution at tourist attractions are obtained. The experimental results show that the correlation of the evaluation index is always controlled above 0.90, the convergence rate of the method is fast, the optimal solution can be approached within 150 iterations, and the application effect is good.

Recycling steel slag as aggregate in developing an ultra-thin friction course with high comprehensive road performance

The demand for skid-resistant and wear-resistant alternative aggregates in the preparation of ultra-thin friction course (UTFC) asphalt mixtures is a key direction for achieving high durability and low-carbon development in pavement maintenance. As a typical industrial waste, steel slag with high alkalinity and strong adhesion can facilitate the mechanical property of asphalt mixtures. However, few researches focused on the impact of steel slag on the comprehensive road performance of UTFC mixtures. Hence, the issue merits systematic exploration. In this study, the chemical components, microstructure and morphological characteristics of three steel slags (GXSS, HBSS and IMSS) obtained from different sources were surveyed. Then the stone matrix asphalt (SMA)-5 and open-grade friction courses (OGFC)-5 mixtures with different steel slags were fabricated. And their comprehensive road performances were quantitatively explored via the improved radar chart. The results indicate that steel slag with approximately 40 % Ca content, about 20 % Fe content, irregular shapes and tiny pores endows its wear resistance and strong adhesion. IMSS demonstrates the largest average angularity and form 2D values of 3850 and 7.28, respectively, representing its significant crowding function and interlocking structure. Incorporating steel slag remarkably reinforces the rutting resistance, skid resistance and anti-interlayer shear performance of UTFC. While the effect of water stability and crack resistance of UTFC depend on the category of steel slag. All three steel slags manifest the improvement function on the comprehensive assessment indexes (CAI) of OGFC-UTFC. IMSS-OGFC reveals the optimal comprehensive road performance, achieving the highest CAI of 0.9909. It is inferred that steel slag is more suitable for OGFC-UTFC than SMA-UTFC due to its relatively high CAI and consistent performance regardless of the steel slag type.

Selection Process Based on Advancing the Development of a Science and Technology Law System with Chinese Features

The significance of advancing socialist S&T legal system building with Chinese features is examined in this paper, along with the extensive effects it has on S&T innovation and economic growth. Against the backdrop of an increasingly competitive global scientific and technology landscape, China’s ability to innovate and achieve sustainable growth hinges on the establishment of an ideal science and technology legislative framework. This essay first examines the primary obstacles to China’s development of a science, technology, and innovation (S&T) legal system, including inadequate protection for intellectual property rights, a flawed process for transforming scientific and technological advancements, and an insufficient system for encouraging enterprise innovation. Then, this research presents a quantitative analysis model to optimize the path of science and technology legal building by applying the improved particle swarm optimization method (PSO). The model takes into account a wide range of variables, including the degree of intellectual property protection, the strength of legal backing, the pace at which scientific and technological advancements are transformed, etc. Through the analysis of simulation data, the model also confirms the promotion effect of the legal system construction on the quantity of patent applications, the success rate of innovation projects, the enterprise R&D expenditure, and the expansion of the local economy. The study’s findings demonstrate that bolstering the science and technology legal system can effectively encourage businesses to boost R&D investment and foster regional economic development in addition to greatly raising the quantity of patent applications and the success rate of innovation projects. The rigorous intellectual property protection laws and ideal legal framework for the conversion of accomplishments greatly boost the regional innovation vitality and economic efficiency, particularly in the case study of Zhongguancun in Beijing and East China. Moreover, adaptive weighting is used to enhance the PSO algorithm and optimize the development of science and technology legal system’s comprehensive performance index, thereby confirming the model’s viability and efficacy. The study’s findings offer theoretical justification and helpful advice for China’s development of a science and technology legal framework, which is crucial for fostering innovation in these fields and boosting the country’s competitiveness.

Evaluation of the Smart Logistics Based on the SLDI Model: Evidence from China

Smart logistics (SL) reflects the digital transformation of the logistics industry, which is key for economic development. Most evaluations are based on the application of technology in SL, and few studies have evaluated SL from a comprehensive perspective. The paper builds the SL development index (SLDI) model from five dimensions based on the driving force, pressure, state, impact, and response (DPSIR) model and identifies the indicator weight by the entropy weight technique. The paper employs the ETDK method, a combined quantitative approach that incorporates entropy weight (E), the technique for order preference by similarity to an ideal solution (TOPSIS) (T), the Dagum Gini coefficient (D), and Kernel density estimation (K), to calculate the closeness degree, analyze spatial-temporal differentiation, and explain the distribution characteristics using data from China spanning 2013 to 2021. The findings show that (1) The SL evaluation is multidimensional and cannot be evaluated only based on technical indicators. A comprehensive evaluation indicator system is necessary. (2) A combined quantitative approach can measure SL development from multiple perspectives and get a clearer picture of the characteristics and regional differences of SL. (3) Influenced by economic development, infrastructure, regional clusters, location, talent, etc., the overall SL development is improving yearly, but SL development in different regions is unbalanced and has different distribution characteristics. The SLDI model developed in this paper will provide a more scientific and reasonable tool for comprehensively evaluating SL. The findings are helpful in proposing suggestions and optimization approaches for subsequent research on SL evaluation and development.

Evaluating the Impact of Elementary School Urban Neighborhood Color on Children’s Mentalization of Emotions through Multi-Source Data

To address the challenge of quantitatively assessing the mentalization of emotions in color design schemes, this study uses Baidu Street View images and deep learning, integrates multi-source data, and innovatively constructs a color data model based on a comprehensive color indicator system for the quantitative assessment and visual representation of how the color environments of elementary school urban neighborhoods impact children’s mentalization of emotions. This model systematically incorporates physical color indicators, integrates elements such as perceptual frequency, and provides a novel perspective for color planning. The study’s results reveal that color metrics significantly impact children’s mentalization of emotions across multiple dimensions, with gender and age emerging as important influencing factors. Additionally, significant correlations were found between color and environmental elements such as building façades, roads, and signs. The study provides urban planners and architects with a practical color data model and recommendations for the revitalization of elementary school urban neighborhoods, offering a scientific basis for optimizing color design.

Purification Resistance Index: A new water quality assessment method toward drinking water production

Water quality assessment plays a significant role in ensuring the availability of clean and safe water. The Water Quality Index (WQI) model method has been developed to provide a basis for assessing water quality by integrating various water quality parameters. However, existing WQIs do not “actively” consider the difficulty of water treatment from raw water to specific water use scenarios. This study proposes a novel model framework, named as Purification Resistance Index (PRI), quantitatively evaluating not only the exceedance of pollutants but also how difficult they can be removed in the water treatment process. The framework is built based on the conventional drinking water treatment processes, with sub-indices for coagulation-sedimentation (rc), filtration (rf), disinfection (rd), and advanced treatment (ra). The model considers appropriate weights assigned to each sub-index to calculate the purification resistance, resulting in a comprehensive index for water quality evaluation. Case studies on nationwide and citywide water source reservoirs demonstrated the applicability of PRI approach. PRI breakthrough the traditional water quality risk assessment paradigm and extents to engineering region and provide useful tools for water source supervision, drinking water treatment plant planning and updating, operation control, and other purposes. Water authority, water utility and municipal design institute will all benefit. It is open for more localized practices validation and discussion.

Development of a Maturity Model for the Digital transformation of companies in the context of Construction Industry 4.0

The construction industry is characterized by a low level of productivity and digitalization, as well as the critical perceived instability of costs, deadlines and quality. One way to address these challenges is to increase the use of digital methods and technologies in the future. Optimal use of these can help to improve the quality of planning and execution and optimize the operation of existing buildings. The challenge is the implementation and integration of these methods and technologies into existing company structures. In many cases, companies do not have a unified understanding of the current state of digitization in their organization. This article closes this research gap and presents the development of a novel maturity model for construction companies in the context of Construction Industry 4.0, the Digital Construction Company Maturity Model (DCCMM). Based on a literature review, the appropriate technologies used in the construction industry are identified and the basic requirements for the maturity model are defined. Once implemented, the model comprises five dimensions and 28 assessment parameters that describe digital transformation across six maturity levels. The conceptual model is tested and validated in eight construction companies. This is done in the context of qualitative interviews. The DCCMM serves as a holistic framework for the individual classification of companies in terms of digital transformation. This provides construction companies with a transparent and comprehensible indication of the degree of digitalization of their own structures. The result will make a significant contribution to further digitalization in the construction industry.

Pavement Crack Detection and Identification Based on Improved YOLOv8

Aiming at the problem of poor real-time performance and low precision of traditional pavement crack detection, an improved YOLOv8 algorithm is proposed to realize the automatic pavement crack detection and identification. Firstly, the crack image is manually labeled by LabelImg labeling software, and then the model parameters are obtained by improving YOLOv8 network. The improved method includes introducing a convolution block attention module (CBAM) to enhance the feature extraction ability, and optimizing the weighted intersection-to-union ratio (Wiou) loss function. Through comprehensive evaluation indexes (F1-measure and mAP@50-95%), the performance of the original model and the improved model in pavement crack detection and recognition is compared. The results show that the improved model has improved the detection precision, F1 value and mAP@50-95% value, which are 2.91%, 3.29% and 1.7% respectively. These results show that the improved model has significant practical significance in realizing the automatic identification of pavement cracks.

Digital Sharing of Social Public Resources and Its Influencing Factors: Insight from China

Digital sharing of social public resources (SPRs) is an approach of resource-allocation that can effectively compensate for the limitations of time, space and communication modes in accessing SPRs and achieve the balanced allocation of them. The purpose of this paper is to study the development level of digital sharing of SPRs and its influencing factors. The panel data of 31 Chinese provinces from 2015 to 2020 are collected. A comprehensive evaluation index system for digital sharing of SPRs is constructed to evaluate its development level using the Global Entropy Weight Method (GEWM). And the influencing factors of the sharing level are systematically identified based on the stepwise regression model. The results show that: the development level of digital sharing of SPRs varies significantly among Chinese provinces and cities, but the overall development level is gradually increasing. The government fiscal expenditure capacity, industrial structure, regional economic development level, scientific and technological innovation capacity, and urbanization level can promote the digital sharing of SPRs. The degree of external openness and regional population size have negative effects on the digital sharing of SPRs.

Fast co-pyrolysis of corncob with plastics: Evaluation of thermal behavior using deconvolution procedure, kinetic analysis and product characterization

In this study, the co-pyrolysis of corncob (CC) with polyethylene terephthalate (PET) and polyvinyl chloride (PVC) was first carried out at different blending ratios in a concentrating photothermal TGA (CP-TGA) to gain insights into their thermal behavior, pyrolysis characteristics and kinetic analysis under high heating rate conditions (≥500°C/min). The change in comprehensive pyrolysis index (CPI) for CC/PET and CC/PVC blends was 514 % and 125 %, respectively, when their blending ratio was increased from 25 wt% to 75 wt%. The decomposition rate (Rp %/min) for CC/PET and CC/PVC blends with an increased heating rate showed a favorable co-pyrolysis process. Rapid heating leads to complexity and simultaneous overlapping of the co-pyrolysis components; therefore, the devolatilization phase (active pyrolysis zone) was divided into pseudo-reactions using the Fraser-Suzuki deconvolution function. The deconvolution results of the blend samples fitted well with experimental results (R2 ≥ 0.997). The three pseudo components of CC in the CC25PET75% blend relatively reduced the needed activation energy (E) for PET degradation to about 130 %. With the blending ratio increase, the synergistic activity of pseudo hemicellulose presented trends of an increasing E in CC/PET blends, whereas CC/PVC blends showed decreasing trends. The relative ΔEa deviation revealed that most blend samples would promote an active synergistic reaction. The resultant co-pyrolysis oil from photothermal fixed bed pyrolyzer contained promising bio-renewable platform chemicals such as levoglucosenone, furfural, D-allose, etc. The synergistic interactions between pseudo-lignin and PET contributed to a significant reduction in activation energy and higher selectivity of acetic acid due to the degradation of the ester bonds in PET and the carboxyl groups in lignin. The results of this work could serve as a guide for selecting appropriate reaction parameters for optimal co-pyrolysis synergism.

The Power of Culture: Business Nationalist Culture and ESG Performance

High-quality development is the theme of China’s economic and social development in the new era, and corporate ESG performance is a comprehensive indicator for evaluating the level of corporate environmental responsibility, social responsibility and governance, as well as an important yardstick for identifying the high-quality development of enterprises. This paper takes Chinese non-financial listed companies from 2011 to 2022 as the research sample and empirically examines the impact of corporate nationalism culture on corporate ESG performance and its mechanism by quantifying corporate nationalism culture using the text of corporate annual reports, natural language processing and text analysis methods. The results of the study show that corporate nationalism culture significantly enhances corporate ESG performance. The mechanism analysis suggests that corporate nationalism culture, as an internal informal system, can play a governance role and promote corporate ESG practices by changing attention allocation and mitigating agency problems. The positive effect of corporate nationalism culture on corporate ESG performance is more pronounced in the grouping of firms with lower institutional investor shareholding, fewer analysts’ attention and embedded party organisations. A heterogeneity analysis reveals that the corporate nationalism culture driving effect on corporate ESG performance is more significant in the subsample of firms with weak financing constraints, in the growth period and in the decline period. This study reveals the positive role of soft cultural factors in enhancing corporate ESG performance, providing useful managerial evidence for companies to integrate ESG concepts at the strategic level for high-quality economic development.

Exploring the competency of the comprehensive complication index over the clavien-dindo classification in standard percutaneous nephrolithotomy: a call for better complication reporting.

The Comprehensive Complication Index (CCI) was introduced in 2013 to overcome the limitations of the Clavien-Dindo Classification (CDC) in grading postoperative complications. The objective of this study to assess the predictive value of the CDC and the CCI for postoperative course in patients undergoing standard adult percutaneous nephrolithotomy (PCNL). A retrospective analysis of 320 renal units that underwent standard PCNL between July 2021 - April 2023 was conducted. The CDC and CCI systems assessed complications occurring within the first 30 days after surgery. A second CCI score was calculated only on the highest CDC grade, and this score was referred to as the noncumulative CCI. A comparative analysis was conducted to determine the predictive efficacy of both evaluation methods regarding the postoperative course. The postoperative complication rate was 23.1% (74/320). Eight patients (2.5%) experienced multiple complications, resulting in a higher total CCI score than the noncumulative CCI (p = 0.010). Correlation analysis revealed that the CCI correlated with the length of hospital stay (LOS) more precisely than the noncumulative CCI (CCI: r = 0.335; p = 0.004 vs. noncumulative CCI: r = 0.325; p = 0.005). Compared with patients with a single complication, those with multiple complications had similar demographics, preoperative stone characteristics, and intraoperative features. Cumulative CCI proves to be a more effective predictor of LOS and complication burden in standard PCNL than CDC. Hence, using CCI to evaluate complications after PCNL may be a more appropriate approach.

Spatial zoning and effect evaluation of county high-standard farmland siting delineation for sustainable cultivated land use in China: A case study in Dali, Shaanxi

High-standard farmland construction is critical for sustainable land use and food security in China. Currently, scientific siting delineation for high-standard farmland at the county level is lacking. Delineation through evaluation and zoning is essential to improve land productivity. This study focuses on Dali County in Shaanxi Province, Fenwei Plain. It analyzes cultivated land changes using the land use transfer matrix and the PLUS. By integrating macro “township-parcel-grid” and micro “farmer” perspective, it establishes a comprehensive evaluation system for high-standard farmland delineation. We delineate construction zones and evaluate potential effect of high-standard farmland. The results reveal that: (1) From 2000 to 2020, the cultivated land area generally decreased. The permanent basic farmland positively contributes to the increase of cultivated land. Land use simulation in 2030 results show that the urgency for land consolidation. (2) The delineated high-standard farmland area in Dali is 85,081 hm2, with comprehensive evaluation index values ranging from 0.2229 to 0.5970, indicating that Dali has the potential for continuous construction of high-standard farmland. (3) This study zones high-standard farmland construction according to the difficulty and time sequence. Delineated high-standard farmland can play potential effect of agglomeration and demonstration, sustainable and coordinated development and grain production capacity increasing. We offer a scientific method for delineating zones of high-standard farmland within county, providing recommendations for sustainable high-standard farmland construction. It serves as a reference for the gradual conversion of all permanent basic farmland to high-standard farmland in China.

Ecological vulnerability assessment and spatial-temporal variations analysis in typical ecologically vulnerable areas of China

Ecological vulnerability assessment is crucial for environment protection, ecological restoration and resource utilization. However, many former studies have limitations in the indicator system of the assessment, which were not comparable for different types of ecologically vulnerable areas. It is difficult to apply directly to the ecological vulnerability assessment of different types and in various regions. Aiming to solve these problems, the study proposed a well-established and comprehensive indicator system for ecological vulnerability assessment and conducted ecological vulnerability assessment application of five types of typical ecologically vulnerable areas of China based on remote sensing, meteorological, geographic and other data. The results show that the average EVIs value of Zhangbei County ranging from 0.525 to 0.559 are the highest among the five research areas during the four periods, followed by Zoige region and Xiamen bay. However, the region with the lowest average EVI value varies. In 2005 and 2015, it was Taihe County, while in 2010 and 2020, it was the Sanjiangyuan region. The variation of average EVIs in the five typical areas presents slight fluctuation and remains generally stable from 2005 to 2020. It indicates that the environmental protection measures and projects undertaken by the Chinese government in recent years have had a striking effect, curbing the trend of ecological environment deterioration.

Assessment of waterlogging hazard during maize growth stage in the Songliao plain based on daily scale SPEI and SMAI

Waterlogging is one of the major disasters affecting crop yield and food security. The Songliao Plain, located in the mid-latitude region and known as the "Golden Maize Belt," is severely impacted by waterlogging, which significantly affects maize yield. Therefore, it is essential to conduct a detailed assessment of the waterlogging hazard for maize in the Songliao Plain and to apply the results to agricultural meteorological disaster prevention and mitigation measures. In this study, a comprehensive waterlogging hazard assessment index was constructed by combining environmental factors conducive to disaster and disaster-causing factors. Environmental factors included terrain slope, distance from rivers, and soil clay content, while disaster-causing factors included daily SPEI and SMAI during the maize growing season in the Songliao Plain from 1982 to 2020. The results indicate that: (1) The spatial distribution of waterlogging hazard in the Songliao Plain ranges from extremely high to extremely low, showing a gradual decrease from west to east. The western and southern parts of the Songliao Plain, such as Baicheng, Songyuan, Changchun, and Fuxin, are more prone to waterlogging disasters. (2) During different maize growth stages, the spatial distribution of high and extremely high levels of waterlogging hazard exhibited significant heterogeneity. There were notable differences in the duration of waterlogging around the year 2000, with a reduction in the duration of extremely high and high levels of waterlogging after 2000. (3) A Pearson correlation analysis was conducted between the comprehensive waterlogging hazard index and SIF (Solar-Induced Fluorescence) data during different maize growth stages. The results showed a strong correlation between the comprehensive waterlogging hazard index and SIF data, with the highest correlation coefficient reaching −0.9 and a p-value less than 0.05. The comprehensive maize waterlogging hazard index can be used for precise and timely assessment of waterlogging hazard during different growth stages of maize, and it has a positive impact on improving the ability to prevent and mitigate waterlogging risks.

Assessment of health risks based on different populations and sources of heavy metals on agricultural lane in Tengzhou City by APCS-MLR models.

To identify the sources of heavy metals in local soils and their risks to human health. This study quantified the concentrations of eight heavy metals in 504 soil samples collected in Tengzhou, China. The ecological risks of a single heavy metal (EI), a comprehensive ecological risk index (RI), and a health risk assessment model were used to evaluate the level of contamination in the city. The results of the research study indicate that there are different levels of heavy metal pollution in rural and urban agricultural areas in Tengzhou. Moreover, the spatial variability of mercury (Hg) is considerable, reaching 0.96, indicating a significant impact of anthropogenic activities. For the ecological risk, the heavy metal element with the highest EI value was mercury with a mean value of 67.22 and a peak value of 776.00. The heavy metal with the lowest mean EI value was Zn with only 1.03. Meanwhile, the average RI is only 128.59, but some areas have an RI as high as 842.2. The sources of heavy metals were identified using principal component analysis, correlation analysis, and an absolute principal component score multiple linear regression model (APCS-MLR). The non-carcinogenic risk for children, the carcinogenic risk for children, and the carcinogenic risk for adults were 1.23, 2.42×10-4 and 1.00×10-4, respectively, and these values exceeded their respective recommended values, and As and Cr had some carcinogenic hazards. Heavy metals in the soil come from natural, industrial, traffic and agricultural sources and represent 39.59%, 29.48%, 25.17% and 5.77%, respectively. The main source of heavy metals in local agricultural soils is the geological background, and the government needs to strengthen the monitoring of As and Cr in drinking water resources, as well as reduce traffic pollution and factory waste emissions to reduce Hg in soils.

Spatialization and Analysis of China’s GDP Based on NPP/VIIRS Data from 2013 to 2023

The quality of nighttime light (NTL) data is an important factor affecting the estimation of gross domestic product (GDP), but most studies do not use the latest NPP/VIIRS V2 annual composite product, and there is a lack of China’s GDP estimation products in recent years. To address this problem, this paper studies the NPP/VIIRS remote sensing estimation method for the GDP in mainland China from 2013 to 2023. First, the remote sensing data are preprocessed, and the noise masking method is used to remove outliers. The total amount of NTL, average NTL value, and comprehensive NTL index data are extracted. Combined with the GDP data from the Statistical Yearbook, a fitting model of the GDP and NTL index is constructed. The differences between different GDP estimation models are compared and analyzed, and the optimal model is selected as the estimation model. In addition, through the optimal fitting model, GDP spatial estimation products from 2013 to 2023 are produced. Moreover, the spatiotemporal variation characteristics of the GDP in mainland China are analyzed, with a focus on the spatiotemporal variation of GDP decline regions and the changes in the GDP rankings of provinces and cities. The main conclusions include the following: (1) In the time regression analysis, the linear model MNL has a strong correlation with the GDP, with an R2 of 0.972. This model is selected as the optimal fitting model to calculate the spatial data of the GDP. (2) The spatial distribution of the GDP in mainland China is high in the east and low in the west, and it shows a characteristic of extending from the provincial capital to the surrounding cities. The connectivity between adjacent high-GDP areas continues to increase. (3) From 2013 to 2023, the GDP in most parts of China showed an upward trend, with 98.56% of pixels growing and only 0.99% of pixels declining. The declining pixels are mainly distributed in heavy industrial cities supported by fossil fuel resources, such as Ordos, Daqing, Aksu, etc. (4) Compared with statistical data, the overall difference of the GDP estimated by NTL data is not large, and the relative error is between 0.04% and 1.95%. From the perspective of the GDP ranking of each province, the ranking of most provinces is not much different, fluctuating between ±2. A small number of provinces have large ranking differences due to reasons such as dominant industries and power supply. By spatializing the GDP data of mainland China in the past 11 years, the spatiotemporal changes of the GDP within mainland China were analyzed. The research results can provide support for government economic decisions such as urban development.

Optimization study of tail-lateral occupant injury and restraint system for an off-road vehicle ramp rollover

The process of rollover accidents involving specialized vehicles is characterized by intense motion and long duration. Although these accidents are infrequent, they often lead to a high fatality rate. In this study, we utilized LS-Dyna software to simulate the rollover of a vehicle on a side ramp. This simulation aimed to verify the reliability of our model establishment by comparing the vehicle’s motion attitude and center-of-mass acceleration with experimental results. Additionally, we sought to investigate the lateral occupant injuries that occur in the tail section of a certain type of specialized vehicle during a rollover. Initially, we obtained the vehicle’s motion trajectory and the dummy’s motion state through simulation. Subsequently, we extracted the injury response of each part of the dummy. We then simplified the entire vehicle model and made improvements to the occupant restraint system, ultimately designing an enhanced system. Finally, we approximated and replaced the entire vehicle model by establishing an approximation model. We combined this with an optimization algorithm to optimize the occupant restraint system. The simulation results demonstrate that the improved occupant restraint system significantly reduces the axial force on the neck of the occupant and the comprehensive evaluation index of injury. Furthermore, the simulation results for each component fall below the injury limit value specified in the FMVSS208 crash occupant protection standard. Therefore, the improved occupant restraint system proposed in this study effectively mitigates lateral occupant injury during rollover accidents.

Core outcome sets and benchmarking complications: Defining best practices for standardized outcome reporting in liver transplantation

The comparison of outcomes in liver transplantation (LT) is hampered by using clinically non-relevant surrogate endpoints and considerable variability in reported relevant post-transplant outcomes. Such variability stems from non-standard outcome measures across studies, variable definitions of the same complication, and different timing of reporting. The Clavien-Dindo classification was established to improve the rigor of outcome reporting but is non-specific to an intervention and there are unsolved dilemmas specifically related to liver transplantation. Core Outcome Sets (COS) have been used in other specialties to standardize outcomes research, but have not been defined for LT. Thus, we use the five major benchmarking studies published to date to define a 10-measure COS for LT using previously validated metrics. We further provide standard definitions for each of the 10 measures that may be used in international research on the topic. These definitions also include standard time-points for recording to facilitate between-study comparisons and future meta-analysis. These 10 outcomes are paired with 3 validated, procedure-independent metrics, including the Clavien-Dindo Classification and the Comprehensive Complications Index (CCI®). The Clavien scale and CCI® are specifically reviewed to enhance their utility in LT, and their use along with the COS is explored. We encourage future studies to employ this COS along with the Clavien-Dindo grading system & CCI® to improve reproducibility and generalizability of research concerning liver transplantation.

Robust retrofits for rural house envelope considering construction quality and occupant behavior uncertainties: A MOO-integrated Taguchi method

Due to the underdeveloped socio-economic environment, the uncertainties in construction quality and occupant behavior are more prominent for rural house than urban residential buildings. If these uncertainties are not considered, there are higher risks of inaccurate performance prediction, unrealistic retrofit decisions and causing serious performance gap. To address this challenge, this paper proposes a robust envelope retrofitting workflow that combine deterministic multi objective optimization (MOO) and Taguchi method. This workflow stands out for its utilizing mature deterministic MOO to fast approximate Alternative schemes, and utilizing Taguchi method to handle uncertainties, reducing some key disadvantages of traditional robust design optimization (RDO), such as heavy calculating burden, overly conservative solution and difficulty to predefine proper robust objectives or performance target value. The proposed workflow consists of four main steps, formulating Alternative schemes by deterministic MOO, screening highly sensitive uncertain parameters by uncertainty and global sensitivity analysis, formulating Typical uncertain scenarios by orthogonal experiments (OE) and calculating the comprehensive robustness indicators. Results show that by employing the proposed workflow, the selected robust optimal solution not only proves to be robust but also leads to preferable performance enhancements. Compared with the reference mode, the energy efficiency has been improved by 33.2% to 49.4%, the discomfort hours have been reduced by 0.4% to 26.5%, and the robustness has been enhanced by 36.1%.