Traditional Evaluation Research Articles

Ceļš uz savu valsti Annas Brigaderes romānā “Kvēlošā lokā”

Anna Brigadere’s (1861–1933) novel “The Glowing Circle” (Kvēlošā lokā, 1928) is the writer’s only novel. The article examines how Brigadere recreated the path to the state’s founding in the novel and how she interpreted the events of that time. The aim of the article is to show in which aspects Brigadere creates the novel as the historical memory and cultural basis of the nation and in which aspects she expresses the views of her social group. The article uses materials in Latvian and German from the collections of the Museum of Literature and Music. The article uses case analysis – primary research case analysis and explanatory case analysis – to look at museum materials and their relationship to the text of the novel, as well as discourse analysis. Brigadere emphasises in the novel that the Republic of Latvia was established at a time when two countries (Russia and Germany) were trying to include it in their circle of interests, when people were involved in the war, and when it gradually became clear that only their own country could save the nation. In the novel, Brigadere opposes social-democratic and communist views. With the final solution of the novel, she joins the positivist tradition of Latvian literature.

Towards more reliable evaluation in pedestrian detection by rethinking “ignore regions”

It remains a challenging task to detect pedestrians in crowds and it needs more efforts to understand why the detectors fail. When we perform an error analysis based on the traditional evaluation strategy, we find that it produces many misleading false positives, which in fact cover occluded pedestrians. The reason for this is that we usually have two kinds of annotations in the dataset: regular pedestrians (detection targets) labeled by full-body boxes and ignored pedestrians (NOT detection targets) labeled by visible boxes. Ignored pedestrians are labeled as an additional category termed the “ignore region”. Nevertheless, our detectors always predict a full-body box for each pedestrian. This gap results in the following case: when a detector successfully predicts a full-body box for those ignored pedestrians, a false positive is triggered due to the low overlap between the predicted full-body box and the labeled visible box for the ignored pedestrian. This becomes even more harmful as the detector improves and becomes more capable of locating occluded pedestrians. To alleviate this issue, we devise a new pedestrian detection pipeline, which considers the additional visible box at both the detection and evaluation stages. During detection, we predict an extra visible box apart from the full-body box for every instance; during evaluation, we employ visible boxes instead of full-body boxes to match the “ignore region”. We apply the new pipeline to dozens of detection methods and validate the effectiveness of our pipeline in reducing the over-reporting of false positives and providing more reliable evaluation results.

Research Progress in Traditional Applications, Phytochemistry, Pharmacology, and Safety Evaluation of Cynomorium songaricum.

Cynomorium songaricum Rupr. (CSR) belongs to the family Cynomoriaceae. It is a perennial succulent parasitic herb with a reddish-brown coloration, predominantly submerged in sand and lacking chlorophyll. Traditionally, it has been used in ethnic medicine to treat various diseases, such as gastric ulcers, indigestion, bowel movements, and improving sexual function. To comprehensively collect CSR data, extensive literature searches were conducted using medical, ecological, and scientific databases such as Google Scholar, PubMed, Science Direct, Web of Science, and China National Knowledge Infrastructure (CNKI). This article summarizes and categorizes research on the uses, phytochemical characteristics, pharmacological activities, and toxicity of ethnic medicine, with the aim of establishing a solid foundation and proposing new avenues for exploring and developing potential applications of CSR. So far, a total of 98 compounds have been isolated and identified from CSR, including flavonoids, terpenes, steroids, and other compounds. It is worth noting that flavonoids and polysaccharides have significant antioxidant and anti-inflammatory properties. In addition, these compounds also show good application prospects in anti-tumor, antioxidant, anti-aging, anti-fatigue, anti-diabetes, and other aspects. Although extensive progress has been made in the basic research of CSR, further research is still needed to enhance the understanding of its mechanism of action and explore more unknown compounds. Our review indicates that CSR has broad prospects and deserves further research.

A decentralized and security-enhanced professional title evaluation system in universities under mobile Internet of Things

Digital online application is a commonly used method for professional title evaluation in colleges and universities. With the rapid development of the mobile Internet of Things, the fastest way for users to access the evaluation system is through mobile devices. However, this also poses security challenges to the traditional professional title evaluation system. Therefore, this paper proposes a decentralized and security-enhanced digital title evaluation system in mobile IoT. Since the system uses blockchain to implement a decentralized review process, the transparency and fairness of the review process are guaranteed. At the same time, the review data and reviewer information in the system are encrypted and stored in the distributed network to ensure the security and non-tamperability of the data. All review records are recorded on the blockchain, and anyone can view and verify the legitimacy of the review results. Additionally, the system incorporates security enhancement mechanisms such as identity verification, smart contracts, and auditing functions to improve the credibility of the evaluation process and prevent cheating under mobile IoT. Experiments have shown that this system has important application value in the field of professional title review in universities, which can improve review efficiency, reduce human intervention, and provide strong support for the credibility of review results.

Dynamic Assessment of Photovoltaic-Storage Integrated Energy Stations Health Incorporating Subjective and Objective Characteristics

Photovoltaic-storage integrated systems, which combine distributed photovoltaics with energy storage, play a crucial role in distributed energy systems. Evaluating the health status of photovoltaic-storage integrated energy stations in a reasonable manner is essential for enhancing their safety and stability. To achieve an accurate and continuous assessment of the health status of photovoltaic-storage integrated energy stations, a dynamic evaluation method is proposed in this study. This method integrates both subjective and objective characteristics. Initially, considering the evaluation needs of low-carbon operation and health status for photovoltaic-storage integrated energy stations, a comprehensive health status evaluation system is developed. The significance of each indicator is subjectively analyzed, while also considering objective characteristics and sensitivity of indicators. The integration of subjective and objective characteristics is achieved using principles from game theory. Subsequently, through the establishment of the Grey-TOPSIS evaluation model, both positive and negative correlations of the health status of photovoltaic-storage integrated energy stations are determined, resulting in the derivation of a health status vector. Furthermore, the introduction of time-weight vectors and the incorporation of a time dimension enable dynamic evaluation and the comprehensive observation of health status. Finally, the scientific validity and effectiveness of the proposed evaluation method are demonstrated through practical examples, with comparisons made to traditional evaluation methods. The results clearly indicate that this method offers higher sensitivity when evaluating the health of photovoltaic-storage integrated energy stations.

РЕЗУЛЬТАТЫ ПРИМЕНЕНИЯ ПРЕПАРАТА НАПРАВЛЕННОЙ БИОКОРРЕКЦИИ И ПРЕПАРАТА, СОДЕРЖАЩЕГО ЛАКТОФЕРРИН, В КОМПЛЕКСНОМ ЛЕЧЕНИИ ХРОНИЧЕСКОГО ГЕНЕРАЛИЗОВАННОГО ПАРОДОНТИТА У ПАЦИЕНТОВ С ПЕРВИЧНЫМ ГИПОТИРЕОЗОМ

Subject In the traditional complex treatment of inflammatory periodontal diseases, antibacterial, antiseptic and anti-inflammatory agents are of paramount importance. These products allow you to obtain not only a positive clinical result, but can also manifest their negative properties, having an ambiguous effect on the microbiome of the oral cavity and periodontal tissue. The use of targeted biocorrection drugs and immunocorrectors has a significant local anti-inflammatory effect with minimal side effects. Their use in the complex treatment of chronic generalized periodontitis has not been studied enough.
 Aim. To evaluate the effectiveness of using a targeted biocorrection drug and a phytocomplex with lactoferrin in the complex treatment of chronic generalized periodontitis in patients with primary hypothyroidism.
 Material and methods. We observed 90 patients with the main diagnosis of primary hypothyroidism aged 44–59. The patients were divided into 3 groups: in group No. 1, 30 patients received traditional primary periodontal therapy, in group No. 2, 30 patients in whom this therapy was combined with a directed biocorrection drug, in group No. 3, 30 people for whom traditional primary periodontal therapy was combined with a directed biocorrection drug and a drug containing lactoferrin. The comparison group included 30 gender and age-matched patients with chronic generalized periodontitis without thyroid pathology. All patients underwent clinical, X-ray and index evaluation of periodontal tissues. 
 Results. In patients of group No. 1, after traditional treatment, clinical and index evaluation data indicated the persistence of inflammatory processes in periodontal tissues. In groups No. 2 and No. 3 on the background of traditional treatment and additionally administered.
 Conclusions. The addition of a traditional treatment regimen for chronic generalized periodontitis with a targeted biocorrection drug and a drug containing lactoferrin is justified and effective.

METHODOLOGY FOR ASSESSING THE EFFECTIVENESS OF THE AIR DEFENSE SYSTEM

This academic article introduces a pioneering methodology for the comprehensive assessment of air defense systems, addressing existing shortcomings in evaluation approaches. The subject of this study revolves around the development and implementation of an advanced methodology for assessing air defense systems. еThe primary aim is to rectify existing evaluation shortcomings by introducing a holistic model that significantly enhances both efficiency and effectiveness in the evaluation of air defense systems. This methodology incorporates critical elements such as system description, mission, objectives, combat environment, threat, and concept. By explicitly considering factors like system flexibility, survivability, and operational concepts, the study surpasses traditional evaluations, providing a nuanced understanding of the capabilities inherent in air defense systems. The methodology places particular emphasis on the importance of threat analysis, addressing uncertainties related to enemy forces and tactics. Additionally, the study introduces an innovative evaluation model employing tactical scenarios to assess system reliability, availability, and durability, integrating combat environment factors and potential adversary combat options. The research contributes to the academic discourse by providing a systematic and thorough approach to air defense system evaluation, tailored to the complexities of modern warfare and in alignment with the evolving military and technological landscapes. The article suggests avenues for future research to delve into nuanced criteria selection and aggregation methods, aiming to further refine the proposed evaluation methodology.

Generative approaches for solving tangram puzzles

The Tangram is a dissection puzzle composed of seven polygonal pieces that can form different patterns. Solving the Tangram is an irregular shape packing problem known to be NP-hard. This paper investigates the application of four deep-learning architectures—Convolutional Autoencoder, Variational Autoencoder, U-Net, and Generative Adversarial Network—specifically designed for solving Tangram puzzles. We explore the potential of these architectures in learning the complex spatial relationships inherent in Tangram configurations. Our experiments show that the Generative Adversarial Network competes well with other architectures and converges considerably faster. We further prove that traditional evaluation metrics based on pixel accuracy often fail in assessing the visual quality of the generated Tangram solutions. We introduce a loss function based on a Weighted Mean Absolute Error that prioritizes pixels representing inter-piece sections over those covered by individual pieces. Extending this loss function, we propose a novel evaluation metric as a more fitting measure for assessing Tangram solutions compared to traditional metrics. This investigation advances our understanding of the capabilities of artificial intelligence in complex geometrical problem domains.

How Implementing a Digital Competency Management System Reduced Nurse Training Cost and Improved NPD Practitioner Satisfaction in a Pediatric Hospital.

Traditional competency evaluations and manual tracking created a problem within one organization. Subjective competency assessments and inconsistent recordkeeping resulted in increased organizational costs. These factors increased the workload of nursing professional development (NPD) practitioners, leading to job dissatisfaction and turnover. The project lead evaluated how implementing a digital competency management system (CMS) affected nurse training costs and assessed NPD practitioners' satisfaction after the digital CMS conversion. A cost analysis compared training costs before and after implementation of a digital CMS. A pre- and postsurvey compared NPD practitioners' satisfaction before and after digital implementation. A digital CMS provided a centralized repository and educational platform, which saved $500,000 in training costs and increased NPD practitioners' job satisfaction by decreasing workload and creating meaningful mechanisms to accurately assess staff knowledge and skills. The NPD practitioners showed tangible outcome measures and return on investment by combining adult learning and technology. [J Contin Educ Nurs. 2024;55(5):239-245.].

The Role of Personal Traits in Financing Decisions: Emotional Biases as a Mediating Variable – An Empirical Study of a Sample of French Companies

This article discusses the advantages of behavioral methods in the field of corporate finance by examining three main variables: personal traits (narcissism, psychopathy, and Machiavellianism) as independent variables, financing decisions as a dependent variable, and emotional biases as an intermediary variable. This approach provides a different perspective from traditional rationality theories and allows for an analysis that can fill some of the gaps related to the financing structure of the company. In addition, this study aims to find a framework for reading the personal traits of managers and knowing their impact on financing decisions through emotional biases.

Research on the Safety Evaluation Method for Quayside Container Cranes Based on the Best–Worst Method–Pythagorean Fuzzy VIKOR Approach

In the port domain, quayside container cranes are an indispensable component of maritime freight transport. These cranes are not only costly but also associated with safety accidents that often result in casualties and property loss, severely impacting port operations and the surrounding environment. Given their complex operational environment, rapid technological updates, high dependency on human factors, and the challenges of maintenance and inspection, the safety of quayside container cranes is a significant concern for port enterprises and managers. This paper, based on the operational modes and structural characteristics of the cranes, divides them into five main systems and identifies twenty-eight safety evaluation indicators, covering a comprehensive range of risk factors from equipment integrity to operator behavior, as well as environmental factors. However, numerous pain points exist in the safety risk evaluation process of quayside container cranes, such as fuzziness, uncertainty, and complex multi-criteria decision-making (MCDM) environments. These issues make traditional safety evaluation methods inadequate in accurately reflecting the actual safety conditions. Therefore, this paper proposes a safety evaluation method for quayside container cranes based on the Best–Worst Method (BWM) and Pythagorean hesitant fuzzy VIKOR. This method effectively overcomes the uncertainties and fuzziness of traditional safety evaluation methods by integrating the decision maker’s preference information from the BWM and the fuzzy handling capability of Pythagorean hesitant fuzzy sets, enhancing the accuracy and reliability of the evaluation results. A case study was conducted on a quayside container crane at a specific port. Through empirical analysis, the feasibility of the proposed method was validated. Overall, the safety evaluation method for quayside container cranes based on the BWM and Pythagorean hesitant fuzzy VIKOR proposed in this paper enriches the theoretical research on the safety risk assessment of quayside container cranes and offers a new approach and tool for port enterprises and managers in practice.

Present and future screening programs for diabetic retinopathy: a narrative review.

Diabetes is a prevalent global concern, with an estimated 12% of the global adult population affected by 2045. Diabetic retinopathy (DR), a sight-threatening complication, has spurred diverse screening approaches worldwide due to advances in DR knowledge, rapid technological developments in retinal imaging and variations in healthcare resources.Many high income countries have fully implemented or are on the verge of completing a national Diabetic Eye Screening Programme (DESP). Although there have been some improvements in DR screening in Africa, Asia, and American countries further progress is needed. In low-income countries, only one out of 29, partially implemented a DESP, while 21 out of 50 lower-middle-income countries have started the DR policy cycle. Among upper-middle-income countries, a third of 59 nations have advanced in DR agenda-setting, with five having a comprehensive national DESP and 11 in the early stages of implementation.Many nations use 2-4 fields fundus images, proven effective with 80-98% sensitivity and 86-100% specificity compared to the traditional seven-field evaluation for DR. A cell phone based screening with a hand held retinal camera presents a potential low-cost alternative as imaging device. While this method in low-resource settings may not entirely match the sensitivity and specificity of seven-field stereoscopic photography, positive outcomes are observed.Individualized DR screening intervals are the standard in many high-resource nations. In countries that lacks a national DESP and resources, screening are more sporadic, i.e. screening intervals are not evidence-based and often less frequently, which can lead to late recognition of treatment required DR.The rising global prevalence of DR poses an economic challenge to nationwide screening programs AI-algorithms have showed high sensitivity and specificity for detection of DR and could provide a promising solution for the future screening burden.In summary, this narrative review enlightens on the epidemiology of DR and the necessity for effective DR screening programs. Worldwide evolution in existing approaches for DR screening has showed promising results but has also revealed limitations. Technological advancements, such as handheld imaging devices, tele ophthalmology and artificial intelligence enhance cost-effectiveness, but also the accessibility of DR screening in countries with low resources or where distance to or a shortage of ophthalmologists exists.

Privacy preserving rare itemset mining

In recent years, rare pattern mining has shown great vitality in some real-world fields, such as disease diagnosis, criminal behavior analysis, anomaly detection in networks, and so on. When data organizations publish or share information publicly, shared data can be at risk of leakage as data mining techniques may discover sensitive knowledge and information. To keep competitors from obtaining hidden information after processing the database, privacy-preserving data mining (PPDM) has been proposed and studied widely. However, most of the techniques in PPDM are applied to frequent pattern mining and cannot deal with the privacy protection problems in rare pattern mining, such as network vulnerability detection and abnormal medical data. To address this limitation, we introduce a privacy-preserving technique for rare pattern mining. In this paper, two novel algorithms named Longest Transaction-Minimum Item Number (LT-MIN) and Longest Transaction-Maximum Item Number (LT-MAX) are proposed to hide sensitive rare itemsets and return the sanitized database. These two algorithms succeed in hiding target itemsets while minimizing the side effects on the original database. What's more, they employ a projection mechanism to reduce the time spent scanning the database. Besides using the traditional evaluation criteria in PPDM, we also propose two additional similarity measures to evaluate the performance from the perspective of the itemsets and the structural integrity of the database. The experimental results indicate that the proposed algorithms can hide sensitive rare itemsets successfully and efficiently, and the evaluation methods used can become the evaluation criteria for privacy-preserving rare itemset mining (PPRIM).

Construction and application of a composite model for acid mine drainage quality evaluation based on analytic hierarchy process, factor analysis and fuzzy comprehensive evaluation: Guizhou Province, China, as a case.

The process of mining activities often causes the formation of acid mine drainage (AMD). Through rock fractures and underground rivers, AMD can easily enter the groundwater environment near mines and cause serious pollution to water quality. In order to effectively evaluate the quality of polluted mine water and to understand its threat to the ecosystem around the mine. In this study, four AMD pollution distribution areas, Guiyang City, Bijie City, Qianxinan Prefecture, and Qiandongnan Prefecture in Guizhou Province, were used as the study area. A composite model for mine water quality evaluation was constructed using factor analysis (FA), analytic hierarchy process (AHP), and fuzzy comprehensive evaluation (FCE). Furthermore, by introducing the weighted average method and the level characteristic value (J), the water quality type and the water body environmental quality were evaluated comprehensively, respectively. Compared with the traditional evaluation model, the AHP-FA-FCE model has obvious advantages in the selection of evaluation indicators, the determination of indicator weights, and the comprehensive evaluation of water quality types, and the evaluation results obtained are more reasonable and accurate. Three common factors mainly controlled by mineral oxidation factor, human activity factor, and mineral dissolution factor were extracted by dimension reduction of the original hydrochemical data by FA. The water quality of the mine water samples was evaluated using SO4 2- , Fe, Al, Mn, Na, and F- as evaluation indicators, and the results showed that the mine water samples in the study area as a whole were dominated by class V water, which accounted for 77.78% of the total. Based on the statistical analysis of the original data, it was found that influenced by the water-rock interactions in the study area and the AMD pollution components, the hydrochemical type of the mine water is mainly SO4 2- -Ca-Mg type. The water body environmental quality of mine water in four areas, Guiyang City, Qianxinan Prefecture, Bijie City, and Qiandongnan Prefecture, is from excellent to poor. The average level characteristic value of all the areas is more than 3, and the overall environmental quality of the water body is poor. The strong water-rock interaction and mining activities in the study area may be the main cause of AMD pollution. The results of this study may provide some theoretical reference for the water quality evaluation of AMD-polluted areas. PRACTITIONER POINTS: A composite model for mine water quality evaluation was constructed. A factor analysis-based evaluation indicator selection method is proposed. This study improved the weighting process of the traditional fuzzy comprehensive evaluation. A water quality discriminant based on the weighted average method is proposed. The water environmental quality of various types of mine water was evaluated.

Integrating single-cell and bulk expression data to identify and analyze cancer prognosis-related genes

Compared with traditional evaluation methods of cancer prognosis based on tissue samples, single-cell sequencing technology can provide information on cell type heterogeneity for predicting biomarkers related to cancer prognosis. Therefore, the bulk and single-cell expression profiles of breast cancer and normal cells were comprehensively analyzed to identify malignant and non-malignant markers and construct a reliable prognosis model. We first screened highly reliable differentially expressed genes from bulk expression profiles of multiple breast cancer tissues and normal tissues, and inferred genes related to cell malignancy from single-cell data. Then we identified eight critical genes related to breast cancer to conduct Cox regression analysis, calculate polygenic risk score (PRS), and verify the predictive ability of PRS in two data groups. The results show that PRS can divide breast cancer patients into high-risk group and low-risk group. PRS is related to the overall survival time and relapse-free interval and is a prognosis factor independent of conventional clinicopathological characteristics. Breast cancer is usually regarded as a cancer with a relatively good prognosis. In order to further explore whether this workflow can be applied to cancer with poor prognosis, we selected lung cancer for a comparative study. The results show that this workflow can also build a reasonable prognosis model for lung cancer. This study provides new insight and practical source code for further research on cancer biomarkers and drug targets. It also provides basis for survival prediction, treatment response prediction, and personalized treatment.

AI-ML algorithm for enhanced performance management: A comprehensive framework using Backpropagation (BP) Algorithm

In the era of economic globalization and heightened market competition, organizations face the imperative to establish robust performance evaluation mechanisms that drive both organizational development and individual employee motivation. This article delves into the multifaceted factors influencing employee performance, encompassing personal attributes, interpersonal relations, and work standards. The study takes a deep dive into the transformative integration of AI-ML algorithms, proposing a comprehensive framework for elevated performance management. Through the application of machine learning algorithms, this research seeks to revolutionize performance appraisals, impacting crucial HR processes such as employee selection, promotions, terminations, training initiatives, and remuneration adjustments. The investigation provides nuanced insights into the synergy between artificial intelligence, machine learning, and traditional performance evaluation methodologies, offering profound perspectives on contemporary organizational practices amid evolving challenges.

Evaluation of Saturation Interpretation Methods for Ultra-Low Permeability Argillaceous Sandstone Gas Reservoirs: A Case Study of the Huangliu Formation in the Dongfang Area

Ultra-low permeability argillaceous sandstone reservoirs have become a significant focus for exploration and development. Saturation is a crucial parameter in evaluating such reservoirs. Due to the low porosity, low permeability, complex pore structure, and strong heterogeneity in ultra-low permeability argillaceous sandstone reservoirs, traditional evaluation methods are unable to achieve the required level of interpretation accuracy. To improve the accuracy of gas saturation calculations in ultra-low permeability argillaceous sandstone gas reservoirs, the conductivity characteristics of the ultra-low permeability argillaceous sandstone gas reservoirs in the Huangliu Formation in the Dongfang area, China, were analyzed through rock physics experimental data and geological information. The results revealed the clay content in the study area to range from 6% to 33.4%. Influenced by burial depth and temperature, kaolinite and montmorillonite transform into illite and chlorite, and the cation exchange capacity is not correlated with the clay content. This suggests that the effects of cation-attached conductivity can be ignored. The regional variation in rock electrical parameters is significant. When the lithology coefficient is a = 1, the consolidation index m varies between 1.25 and 1.75. When the lithology coefficient is b = 1, the saturation index n varies between 1.6 and 1.96. Under the influence of high temperature and pressure, the reservoirs in the study area exhibit two distinct characteristics on the capillary pressure curve, fractal dimension, and effective porosity index intersection diagram, (1) In Class I reservoirs, there is a strong correlation between the formation factor and natural gamma, as well as porosity, and a logarithmic relationship between the saturation exponent and the formation factor; and (2) in Class II reservoirs, there is a strong power-law relationship between the formation factor and porosity, as well as a logarithmic relationship between the saturation exponent and formation factor. Based on experimental and logging data, reservoir classification was conducted using core-scale logging and principal component analysis. Additionally, a saturation interpretation model was developed using multivariate regression, based on rock electrical parameters. The actual application results demonstrate that compared to the fixed rock resistivity saturation model, this model has reduced the average absolute error by 5.9%. The calculated values are consistent with the gas saturation analysis of the core at the pure gas section as determined by cable testing sampling. This model meets the requirements of practical production. The study of this interpretation method is of great significance for the formulation of development plans for ultra-low permeability offshore argillaceous sandstone gas reservoirs.

Comprehensive evaluation of dam seepage safety combining deep learning with Dempster-Shafer evidence theory

Seepage state is one of the most important factors affecting the safety and durability of dams, which calls for accurate observation and evaluation. Traditional dam seepage evaluation mainly focusses on single monitoring points, and ignores the uncertainty and subjectivity with multi-sensor fusion. This paper presents an evaluation method of dam seepage based on Dempster-Shafer (D-S) evidence theory and deep neural network (DNN). In view of the nonlinearity of the monitoring data and the difference of seepage influencing factors, attention mechanism (AM) and long short-term memory (LSTM) model are combined to evaluate dam seepage safety of single monitoring points, which provides the basis for the comprehensive evaluation. The case study demonstrates that the average RMSE, MAE and MAPE values of AM-LSTM are of minimal losses and higher fitting accuracy. The forecast results of the proposed comprehensive evaluation approach are consistent with the actual dam seepage state, demonstrating its reasonability and reliability.

Noise Mapping and Measurements for Sound Environment Assessment in a Typical Chinese Water-Rich Village

The construction of beautiful villages in China is carrying more and more demand for leisure and health care, thus increasing requirements for the quality of the village environment. In this paper, Huanggongwang in Fuyang, Zhejiang Province in China, a typical water-rich village, was selected as the research object to study the sound environment quality by adapting noise mapping and field measurements. A village acoustic simulation model was established by the layout of the villages, roads, and water system; the three-dimensional spatial distribution of sound pressure level was based on actual sound source identification and measurements for sound environment evaluation. The result shows that the combination of the arithmetic mean value method for sound pressure level and noise pollution index approach can better represent the characteristics of sound environment quality compared with traditional noise evaluation standards. The average sound pressure level measured on-site in the village was 62.4 dB(A), and the PN index was 0.83, which reveals the importance of resolving the issue of environmental noise in the villages. Moreover, this evaluation method excludes the chance of actual measurement results. Therefore, it provides a better measure of the quality of the rural sound environment, which serves as a basis for the scientific planning of rural construction.

Cultural Reflections on the Great and Originating Period

Since the 1980s, Chen Lai has been attempting to resolve the binary opposition between tradition and modernity. He has contemplated the position of tradition in modern society from the perspective of “multicultural structures”, emphasizing the continuity of traditions of value rationality. In an exceptional move, he has departed from monistic universality and established “poly-universalism” to rethink the mode of existence of universality. He argues that universality is not an exclusive mode in which one must select one universalism or another, but rather that each civilization contains inherent universality. While certain conditions are required to realize universality, one cannot comprehensively replace the universal values of one civilization with those of another. Based on this cultural view, and considering the relationship between the basic principles of Marxism and traditional Chinese culture, Chen upholds the essence of benevolence, promotes the new four virtues, and reflects on the value of traditional Confucian virtues in contemporary China.