Search Results (17,821)

This study analyses the relationship between non-performing loans (NPLs) and innovation systems at a global level. The data were obtained from the World Bank and the Global Innovation Index over the period 2013–2022 for 149 countries. The k-means algorithm was used to verify the presence of clusters in the data. Since k-means is an unsupervised machine-learning algorithm, we compared the Silhouette coefficient with the Elbow method to find an optimization. The results show that the optimal number of clusters is three, as suggested using the Elbow Method. Furthermore, a panel data analysis was conducted. Results show that the level of NPLs is positively associated with cultural and creative services exports as a percentage of total trade and innovation input sub-index and negatively associated with the Hirsch Index, ICT services exports as a percentage of total trade, ICT services imports as a percentage of total trade, and information and communication technologies. Full article

Truck skidding crashes on horizontal curves pose a significant road safety concern, with improper braking being the primary cause. A data- and model-integrated driven method is proposed to investigate the mechanism and recommend the maximum safe braking deceleration rates without skidding (abbreviated as MSBDRs) for trucks on horizontal curves. Firstly, a comprehensive road–vehicle interaction model was developed, considering dynamic changes in brake force distribution, vertical tire load, and longitudinal and side friction during braking. Secondly, leveraging the “HighD” data set and employing cluster analysis principles, parameter data were extracted using Python and Matlab. Finally, through parameterizing model inputs, the transient dynamic response of trucks was examined, the potential of truck skidding was predicted, and the MSBDRs were recommended. The results indicate the following. (1) There is little concern of truck skidding during car-following braking maneuvers; however, there is a high potential of truck skidding during emergency braking maneuvers. (2) The MSBDR is 4.5 m/s² on a limit-minimum-radius horizontal curve; however, when combined with steep slopes, an overspeed exceeding 20%, and extremely wet road conditions, respectively, the MSBDRs decrease to 4 m/s², 3 m/s², and 2 m/s². These results provide a theoretical foundation for braking strategies in autonomous vehicles. Full article

Traditionally, “ancient villages” are communities that date back to a previous era, possess abundant traditional resources, and hold significant historical, social, cultural, ecological, and economic significance. This study examines the geographical and chronological development of 2957 traditional communities in the Yangtze River Basin and extensively employs GIS spatial analysis, geostatistical analysis, and historical literature review to study the evolution of the locations of traditional settlements under various factors. The study’s findings revealed that: (1) From a geographical standpoint, the traditional villages in the study area present a distribution state of “two cores, small aggregation, and many dispersions”. The two core clusters are located at the intersection of Hunan, Guizhou, and Chongqing provinces, where the natural geographical advantages attracted people from different dynasties to settle here. (2) From a temporal perspective, the quantity of traditional villages shows a growing trend, and the distribution center of each dynasty shows an east–west direction. Among them, the shift from the Song to the Yuan dynasties marked the period of greatest change in village distribution, which originated from the Song Dynasty’s quick economic growth. In addition, the village distribution was clustered in the eastern part of the country, adapting to the needs of commercial trade. When the Song Dynasty fell, the society was in turmoil, and the villages were transferred to the central region to avoid the war. The Yuan Dynasty also laid down the fundamental distribution pattern of conventional villages. (3) From the standpoint of choosing a village location, most of them are distributed in mountainous, hilly, and plain regions; the gentle slopes of 0°~15° are favored by people. Sufficient water sources, abundant precipitation, and a suitable climate are also necessary choices. (4) From the perspective of driving factors, traditional village distribution in the basin is impacted by historical, cultural, social, and ecological factors. Included among these, traditional village distribution is inversely connected with socio-economic variables. Under the interaction of two factors, the distribution will be more affected. To summarize, the complex human geographic factors together create the conventional village dispersal pattern, and examining these elements holds substantial practical importance for comprehending, safeguarding, and preserving traditional villages. Full article

Background: Sweet potato (Ipomoea batatas (L.) Lam.) is widely cultivated as an important food crop. However, the molecular regulatory mechanisms affecting root tuber development are not well understood. Methods: The aim of this study was to systematically reveal the regulatory network of sweet potato root enlargement through transcriptomic and metabolomic analysis in different early stages of sweet potato root development, combined with phenotypic and anatomical observations. Results: Using RNA-seq, we found that the differential genes of the S1 vs. S2, S3 vs. S4, and S4 vs. S5 comparison groups were enriched in the phenylpropane biosynthesis pathway during five developmental stages and identified 67 differentially expressed transcription factors, including AP2, NAC, bHLH, MYB, and C2H2 families. Based on the metabolome, K-means cluster analysis showed that lipids, organic acids, organic oxides, and other substances accumulated differentially in different growth stages. Transcriptome, metabolome, and prophetypic data indicate that the S3-S4 stage is the key stage of root development of sweet potato. Weighted gene co-expression network analysis (WGCNA) showed that transcriptome differential genes were mainly enriched in fructose and mannose metabolism, pentose phosphate, selenium compound metabolism, glycolysis/gluconogenesis, carbon metabolism, and other pathways. The metabolites of different metabolites are mainly concentrated in amino sugar and nucleotide sugar metabolism, flavonoid biosynthesis, alkaloid biosynthesis, pantothenic acid, and coenzyme A biosynthesis. Based on WGCNA analysis of gene-metabolite correlation, 44 differential genes and 31 differential metabolites with high correlation were identified. Conclusions: This study revealed key gene and metabolite changes in early development of sweet potato root tuber and pointed out potential regulatory networks, providing new insights into sweet potato root tuber development and valuable reference for future genetic improvement. Full article

Background/objectives: Pseudomonas aeruginosa can cause community-acquired infections affecting various body sites. The present retrospective study investigated the genetic diversity of 173 isolates (166 clinical, 7 environmental) of P. aeruginosa collected from clinical pathology laboratories in Abidjan, Côte d’Ivoire (2001–2011). Methods: Multiple-Locus Variable Number of Tandem Repeats (VNTR) Analysis (MLVA) using 13 loci was applied to all isolates and compared to published MLVA data. The antibiotics status of the isolates was compiled when available and compared to published profiles. Results: Among 95 isolates analyzed for their antibiotics status, 14 displayed concerning resistance profiles: five multidrug-resistant (MDR) and nine extensively drug-resistant (XDR). MLVA typing revealed a high genetic diversity (>130 genotypes), with many genotypes represented by a single strain. Notably, thirteen clusters (≥4 related isolates) were observed. Some clusters displayed close genetic relatedness to isolates from France, Korea, and well-studied strains (ST560, LES and PA14). Comparative analysis suggested the presence of international high-risk MDR clones (CC233, CC111) in Côte d’Ivoire. Importantly, MLVA clustering revealed a close relationship of CC235-MDR strains with a locally identified cluster (group 9). Conclusions: These findings support MLVA as a reliable and cost-effective tool for low-resource settings, allowing the selection of relevant strains for future whole genome sequence analyses. This approach can improve outbreak investigations and public health interventions aimed at curbing MDR P. aeruginosa transmission within hospitals and at the national level. Full article

In the era of digitalisation, the construction industry is fast embracing digital technology, which evolved from Industry 4.0 (fourth industrial revolution [4IR]). Built environment programmes (BEPs) are expected to meet the needs of the digitalisation era via Education 4.0. Education 4.0 aims to transform education’s future with diverse digital automation and innovative paedagogical procedures. Studies concerning Education 4.0 in Nigeria’s BEPs are scarce. Hence, this study aims to appraise Education 4.0 and investigate the perceived issues facing implementing Education 4.0 in Higher Education Institutions (HEIs), using BEPs as a case study. The findings intend to improve Education 4.0 implementation practices in BEPs. Data were sourced from 40 participants across Nigeria for better coverage and representation via a semi-structured interview approach. The participants were knowledgeable about Education 4.0 and Nigeria’s BEPs. This study adopted a thematic analysis of the virtually collected data and presented the findings in themes. This study shows that Education 4.0 implementation in Nigeria’s BEPs is lax and should be overhauled to improve achieving Sustainable Development Goal 4 (SDG 4)—quality education—and other related SDGs. The findings reveal that improved Education 4.0 can enhance the achievement of SDG 4. The findings cluster the perceived 18 hindrances facing Education 4.0 implementation into three main groups. Also, the findings proffer feasible measures to improve Education 4.0 implementation in Nigeria’s HEIs, using BEPs as a case study, via improved transformative competencies, technological advancement, innovative paedagogical procedures, and stakeholders’ collaboration to improve achieving SDG 4. The proposed framework could assist in creating new values and transforming the students’ BEP competencies via stakeholder collaboration and Education 4.0 for the private sector (future talents’ beneficiary), thus fostering their employability. Full article

Background/Objectives: The ancient tea plant germplasm resources are rich in genetic diversity and provide an important basis for the genetic diversity in tea germplasm resources. To explore the genetic diversity of ancient tea plant germplasm resources in Jiulong County, Sichuan Province. Methods: 59 ancient tea tree germplasm resources were analyzed using simple sequence repeat (SSR) molecular markers and chemical composition analysis. Results: The results showed that a total of 83 alleles were amplified by 23 pairs of SSR primers, with an average observed allele number (Na) of 3.6 and an effective allele number (Ne) of 2.335. The average Shannon information index (I) and the polymorphic information content (PIC) of the primers were 0.896 and 0.446, respectively. The results of the UPGMA cluster analysis showed that 59 ancient tea tree samples could be classified into five different subgroups. Based on the results of chemical composition analysis, two specific tea germplasm resources with high amino acid content, 10 excellent germplasm resources with tea polyphenol content over 20% and some other tea germplasm resources were identified. Conclusions: This study reveals that Jiulong’s ancient tea tree germplasm exhibits significant genetic diversity and includes valuable tea tree planting resources. These findings provide a foundational framework for the conservation, detailed exploration and sustainable utilization of these resources. Full article

(1) Background: The observational retrospective study aimed to investigate the prevalence of personality disorders (PDs) and their association with psychopathological symptoms in a group of patients with cocaine addiction. (2) Methods: Ninety-five medical records of the Pathological Addictions Service of the National Health Service of Lecce (Italy) were analyzed. PDs were diagnosed using the Structured Clinical Interview for DSM-IV Axis II Personality Disorders (SCID-II) and psychopathological symptoms were investigated through the Symptom Checklist 90-Revised (SCL-90-R). (3) Results: Ninety-two out of ninety-five patients met the criteria for at least one PD (96.8%), almost 35% had two Cluster B PDs, and over 25% had three Cluster B PDs. Nine out of ninety-five people met the criteria for all Cluster B PDs. Among the Cluster B PDs, it emerged that the most frequent diagnosis was that of narcissistic–borderline–antisocial (over 20% of the total sample). The analysis highlighted that mental suffering is prevalent in those with multiple comorbid Cluster B PDs. Specifically, depression and psychoticism exceed the clinical cut-off (T score > 63) in all patient groups. At the same time, anxiety and obsessions–compulsions are complained of only by those with more than two PDs as well as the level of general distress. Furthermore, anxiety, hostility, and paranoid ideation are significantly higher in the group of patients with more than three PDs. (4) Conclusions: Further studies should better investigate the relationship between the two aspects and describe the causal effects of PDs on psychopathological symptoms or, on the contrary, the effects of the substance on mental health and the worsening of personality alterations. Full article

Interpretive structural modeling (ISM) is a widely used technique to establish hierarchical relationships among a set of variables in diverse domains, including sustainability. This technique is generally coupled with MICMAC (Matrice d’Impacts Croisés Multiplication Appliquée á un Classement (cross-impact matrix multiplication applied to classification)) to classify variables in four clusters, although the manual application of the technique is complex and prone to error. In one of the previous works, a novel concept of reduced conical matrix was introduced, and the SmartISM software was developed for the user-friendly implementation of ISM and MICMAC. The web-based SmartISM software has been used more than 48,123 times in 87 countries to generate ISM models and MICMAC diagrams. This work attempts to identify existing approaches to fuzzy ISM and fuzzy MICMAC and upscale the SmartISM to incorporate fuzzy approaches. The fuzzy set theory proposed by Zadeh 1965 and Goguen 1969 helps the decision makers to provide their input with the consideration of vagueness in the real environment. The systematic review of 32 studies identified five significant approaches that have used different linguistic scales, fuzzy numbers, and defuzzification methods. Further, the approaches have differences in either using single or double defuzzification, and the aggregation of inputs of decision makers either before or after defuzzification, as well as the incorporation of transitivity either before or after defuzzification. A roadmap was devised to aggregate and generalize different approaches. Further, two of the identified approaches have been implemented in SmartISM 2.0 and the results have been reported. Finally, the comparative analysis of different approaches using SmartISM 2.0 in the area of digital transformation shows that, with a wide flexibility of fuzzy scales, the results converge and improve the confidence in the final model. The roadmap and SmartISM 2.0 will help in the implementation of fuzzy ISM and fuzzy MICMAC in a more robust and informed way. Full article

Drought represents a major environmental threat to global agricultural productivity. Employing plant growth-promoting rhizobacteria (PGPR) offers a promising strategy to enhance plant growth and resilience under drought stress. In this study, the strain G124, isolated from the arid region of Qinghai, was characterized at the molecular level, and its ability to enhance plant drought tolerance was validated through pot experiments. The findings revealed that the strain G124 belongs to Bacillus pacificus, with a 99.93% sequence similarity with B. pacificus EB422 and clustered within the same clade. Further analysis indicated that the strain G124 demonstrated a variety of growth-promoting characteristics, including siderophore production, phosphate solubilization, and the synthesis of indole-3-acetic acid (IAA), among others. Moreover, inoculation with B. pacificus G124 resulted in significant enhancements in plant height, leaf area, chlorophyll content, relative water content, and root development in both Arabidopsis thaliana and Medicago sativa seedlings under drought conditions. Additionally, G124 boosted antioxidant enzyme activities and osmolyte accumulation, while reducing malondialdehyde (MDA) and reactive oxygen species (ROS) levels in M. sativa seedlings exposed to drought. These findings suggest that B. pacificus G124 holds significant promise for enhancing plant drought tolerance and could be effectively utilized in crop management strategies under arid conditions. Full article

The article develops a methodological and practical basis for assessing the attractiveness of regional tourist sites from the point of view of educational tourism. An assessment methodology was created, including groups of criteria and sub-criteria (6 and 53, respectively), selected based on expert evaluation; a matrix was formed, allowing us to calculate integral indicators step by step, which was tested on the example of 50 objects of five regions of Kazakhstan (Central, Northern, Southern, Western and Eastern). In addition, the article implements hierarchical cluster analysis on three blocks of parameters: the first—indicators characterizing the level of education development in the context of 17 regions and 3 cities of republican significance; the second—indicators reflecting the cultural development of the country’s regions; the third—parameters showing the level of development of tourism activities in the regions of Kazakhstan, which allowed us to obtain three clusters that can be used to develop recommendations for the development of education in the regions of Kazakhstan. As a conceptual complementary component of the system of implementation of educational tourism, an audio guide “Tourist sites of Karaganda” was developed and uploaded on the izi.Travel platform. Full article

Mining activities, particularly in large excavations like the Bingham Canyon Copper Mine in Utah, have been increasingly linked to respiratory conditions due to heavy-metal-enriched waste and dust. Operating continuously since 1906, the Bingham Canyon Copper Mine contributes 4.4% of the Salt Lake Valley PM2.5 pollution. However, the extent of its contributions to larger-sized particulate matter (PM10) dust, soil and water contamination, and human health impacts is largely unknown. Aerosol optical depth data from Sentinel-2 imagery revealed discernible dust clouds downwind of the mine and smelter on non-prevailing-wind days, suggesting potential heavy metal dispersion from this fugitive dust and subsequent deposition to nearby surface soils. Our analysis of topsoils from across the western Salt Lake Valley found mean arsenic, copper, lead, and zinc concentrations to be well above global background concentrations. Also, the minimum values for arsenic and maximum values for lead were well above the US EPA regional screening levels for residential soils. Thus, arsenic is the metal of greatest concern for impacts on human health. Elevated concentrations of all metals were most notable near the mine, smelter, and tailings pond. Our study linked these elevated heavy metal levels to regional asthma outcomes through cluster analysis and distance-related comparison tests. Significant clusters of high asthma rates were observed in regions with elevated topsoil heavy metal concentrations, impacting both low- and high-income neighborhoods. The findings of this preliminary study suggest that the mine, smelter, and recent construction activities, especially on lands reclaimed from former tailings ponds, could be contributing to atmospheric dust containing high levels of heavy metals and exacerbating asthma outcomes for residents. However, the methods used in the study with aggregated health outcome data cannot determine causal links between the heavy metal contents of soil and health outcomes; they can only point to potential links and a need for further investigation. Such further investigation should involve individual-level data and control for potential confounding factors, such as socioeconomic status, access to healthcare, and lifestyle factors, to isolate the effect of metal exposures on asthma outcomes. This study focused on atmospheric deposition as a source of heavy metal enrichment of topsoil. However, future research is also essential to assess levels of heavy metals in subsoil parent materials and local surface and groundwaters to be able to assess the links between the sources or methods of soil contamination and health outcomes. Full article

The multifunctionality model is receiving more and more attention from policymakers as a result of recent initiatives to build more resilient and sustainable food systems as well as the potential for increased farm revenue. This paper explores the role of multifunctional farming in the Italian agriculture viewed through the lens of an entrepreneurial strategy grounded on-farm diversification. Farm diversification strategies, which broaden the farm’s traditional boundaries to include additional activities at the farm level, help the evolution towards multifunctionality. A policy-driven transition towards multifunctional farming has been noticed in Italy during the past few decades, which has prompted a strategic reconfiguration of the farm’s business models. Drawing on the identified activity of portfolio diversification, this study provides an overview of the analyzed 49,429 Italian farms, by articulating diversification strategies into four entrepreneurial activities, which are related to on/off-farm/farm-related or farm-diverse diversification strategies. This article has attempted to verify the presence of farm types that responded to portfolio diversification management strategies through the use of a cluster analysis on data from the general census of Italian agriculture. Supporting new patterns in the adoption of business models focused on multifunctionality should be considered in European rural development policies. Full article

The rapid growth of the aviation industry highlights the need for strong safety management. Analyzing data on unsafe aviation events is crucial for preventing risks. This paper presents a new method that integrates the Transformer network model, clustering analysis, and feature network modeling to analyze Chinese text data on unsafe aviation events. Initially, the Transformer model is used to generate summaries of event texts, and the performance of three pre-trained Chinese models is evaluated and compared. Next, the Jieba tool is applied to segment both summarized and original texts to extract key features of unsafe events and prove the effectiveness of the pre-trained Transformer model in simplifying lengthy and redundant original texts. Then, cluster analysis based on text similarity categorizes the extracted features. By solving the correlation matrix of these features, this paper constructs a feature network for unsafe aviation events. The network’s global and individual metrics are calculated and then used to identify key feature nodes, which alert aviation professionals to focus more on the decision-making process for safety management. Based on the established network and these metrics, a data-driven hidden danger warning strategy is proposed and illustrated. Overall, the proposed method can effectively analyze Chinese texts of unsafe aviation events and provide a basis for improving aviation safety management. Full article

This study used epigenomic methylation differential expression analysis to identify primary biomarkers in patients with amyotrophic lateral sclerosis (ALS). We combined electronic medical record datasets from MIMIC-IV (United States) and NHIRD (Taiwan) to explore ALS comorbidities in depth and discover any comorbidity-related biomarkers. We also applied word2vec to these two clinical diagnostic medical databases to measure similarities between ALS and other similar diseases and evaluated the statistical assessment of the odds ratio to discover significant comorbidities for ALS subjects. Important and representative DNA methylation biomarker candidates could be effectively selected by cross-comparing similar diseases to ALS, comorbidity-related genes, and differentially expressed methylation loci for ALS subjects. The screened epigenomic and comorbidity-related biomarkers were clustered based on their genetic functions. The candidate DNA methylation biomarkers associated with ALS were comprehensively discovered. Gene ontology annotations were then applied to analyze and cluster the candidate biomarkers into three different groups based on gene function annotations. The results showed that a potential testing kit for ALS detection can be composed of SOD3, CACNA1H, and ERBB4 for effective early screening of ALS using blood samples. By developing an effective DNA methylation biomarker screening mechanism, early detection and prophylactic treatment of high-risk ALS patients can be achieved. Full article