Search Results (840)

In an age of heightened environmental awareness and the pressing need for net-zero emissions, concerns over rising energy consumption in cement production, responsible for 5–8% of global CO₂ emissions, have intensified. This paper proposes a novel pioneering framework that integrates Shannon’s entropy and Multi-Criteria Decision Making (MCDM) methods to steer the cement industry towards sustainability and net-zero emissions. Utilizing Shannon’s entropy, the research impartially determines the significance of multiple criteria, reducing biases in decision-making for energy efficiency in cement production. Four MCDM methods (TOPSIS, VIKOR, ELECTRE, WSM) are applied to rank energy efficiency alternatives, providing a nuanced analysis of options for the cement industry. The study integrates sensitivity analysis to evaluate the robustness of MCDM methods under varying conditions, assessing the impact of changes in criteria weights on the ranking of energy efficiency alternatives and showcasing the adaptability of the proposed framework. Examining six diverse scenarios reveals the framework’s adaptability and the versatility of the Horizontal Roller Mill (HRM), with the Vertical Roller Mill (VRM) emerging as a cost-effective emission reduction alternative. This interdisciplinary approach, integrating information theory, decision science, and environmental engineering, extends beyond industry relevance, providing valuable insights aligned with global sustainability goals. Harmonizing economic viability with ecological responsibility, this report offers an instructive guide, propelling the cement industry toward a more sustainable future. 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

In this study, we examined how the nonlinearity $\alpha$ of the Langevin equation influences the behavior of extremes in a generated time series. The extremes, defined according to run theory, result in two types of series, run lengths and surplus magnitudes, whose complex structure was investigated using the visibility graph (VG) method. For both types of series, the information measures of the Shannon entropy measure and Fisher Information Measure were utilized for illustrating the influence of the nonlinearity $\alpha$ on the distribution of the degree, which is the main topological parameter describing the graph constructed by the VG method. The main finding of our study was that the Shannon entropy of the degree of the run lengths and the surplus magnitudes of the extremes is mostly influenced by the nonlinearity, which decreases with with an increase in $\alpha$. This result suggests that the run lengths and surplus magnitudes of extremes are characterized by a sort of order that increases with increases in nonlinearity. Full article

Genetic diversity is crucial for determining the evolutionary potential of a species and is essential for developing optimal conservation strategies. The impact of habitat fragmentation on the genetic diversity of food-deceptive orchids seems to be unpredictable because of their specialized seed and pollen dispersal mechanisms. The habitat of deceptive Cypripedium flavum was severely fragmented during the past half century. This study investigated the genetic diversity and structure of seven fragmented Cypripedium flavum populations in Shangrila County using AFLP markers. A total of 376 alleles were identified, with a range of 70 to 81 alleles per locus. The species exhibited considerable genetic diversity, as evidenced by an average Nei’s gene diversity (H) of 0.339 and a Shannon’s information index (I) of 0.505, with all loci being polymorphic. Based on Molecular Variance (AMOVA), 8.75% of the genetic differentiation was found among populations, while the remaining 91.25% of genetic variation occurred within populations. Population structure analysis revealed that the C. flavum germplasm can be categorized into 2 distinct groups, among which there was significant gene flow. Despite habitat fragmentation, C. flavum still retained a high level of genetic diversity, and the substantial gene flow (5.0826) is a key factor in maintaining the genetic diversity. These findings offer valuable insights for the conservation and potential use of C. flavum genetic resources. Full article

Male Idesia polycarpa, which display distinct morphological and physiological traits, exhibit greater adaptability to stressful environments than females. However, the connection between this adaptability and rhizosphere processes remains unclear. Here, we investigate the differences in root bacterial community structures between male and female plants at different developmental stages, identifying bacterial strains associated with plant sex through functional predictions. This study aims to inform the optimal allocation of male and female plants during cultivation and provide a theoretical basis for sex identification and breeding. Samples from seven-year-old male and female plants were collected during the flowering (May) and fruit ripening (October) stages. Rhizosphere nutrient content and bacterial diversity were analyzed using Illumina high-throughput sequencing technology. The results demonstrate that total nitrogen (TN), total carbon (TC), and available potassium (AK) varied between sexes at different times. No significant differences between male and female plants were observed in the Shannon, Simpson, and Chao1 indexes during the flowering period. However, the Chao1 and Shannon indexes were significantly higher at fruit maturity in male rather than female plants. The predominant phyla of rhizosphere bacteria were Pseudomonadota, Acidobacteriota, and Actinomycetes. Interestingly, from flowering to fruit ripening, the dominant phyla in both male and female plants shifted from Actinomycetes to Pseudomonadota. A significant correlation was observed between pH and AK and rhizosphere bacteria (p < 0.05), with metabolism being the main functional difference. This study provides preliminary insights into the functional predictions and analyses of bacteria associated with Idesia polycarpa. The above findings lay the groundwork for further investigation into the sex-specific differences in microbial flora across different developmental stages, elucidating the mechanisms underlying flora changes and offering theoretical support for the high-quality management of Idesia polycarpa. Full article

Cardamom (Elettaria cardamomum (L.) Maton) plays a crucial role in Guatemala’s agriculture, supporting local families and covering 169,429.29 ha (making it the world’s leading producer). Since its introduction to Guatemala in 1910, limited research has focused on unraveling the diversity and defining morphological traits critical for selecting excellent accessions. In this study, we examined 17 morphological traits across 288 accessions to identify key features associated with the germplasm. The comprehensive analysis employed principal component analysis, a morphological composite value (F-value), linear regression, and hierarchical clustering. The Shannon–Wiener diversity index ranged from 0.10 to 2.02, indicating the variation in diversity among traits. Principal component analysis and hierarchical clustering revealed six distinct germplasm groups. The comprehensive analysis facilitated the selection of 14 excellent accessions, and the regression equation incorporating criteria such as plant height, capsule color, panicle number per plant, panicle length, rhizome color, cluster number per panicle, cluster node length, and capsule number per cluster to identify cardamom germplasm. To develop a conservation strategy for the two putative foreign varieties (‘Malabar’ and ‘Mysore’/’Vazhukka’) introduced in Guatemala based on plant height, another 12 accessions were selected with a second comprehensive evaluation. This information offers insights into cardamom diversity for informed selection enhancing national utilization, productivity, and conservation. Full article

Higher-order relationships are a central concept in the science of complex systems. A popular method of attempting to estimate the higher-order relationships of synergy and redundancy from data is through the O-information. It is an information–theoretic measure composed of Shannon entropy terms that quantifies the balance between redundancy and synergy in a system. However, bias is not yet taken into account in the estimation of the O-information of discrete variables. In this paper, we explain where this bias comes from and explore it for fully synergistic, fully redundant, and fully independent simulated systems of $n=3$ variables. Specifically, we explore how the sample size and number of bins affect the bias in the O-information estimation. The main finding is that the O-information of independent systems is severely biased towards synergy if the sample size is smaller than the number of jointly possible observations. This could mean that triplets identified as highly synergistic may in fact be close to independent. A bias approximation based on the Miller–Maddow method is derived for the O-information. We find that for systems of $n=3$ variables the bias approximation can partially correct for the bias. However, simulations of fully independent systems are still required as null models to provide a benchmark of the bias of the O-information. Full article

The processes involved in encoding and decoding signals in the human brain are a continually studied topic, as neuronal information flow involves complex nonlinear dynamics. This study examines awake human intracranial electroencephalography (iEEG) data from normal brain regions to explore how biological sex influences these dynamics. The iEEG data were analyzed using permutation entropy and statistical complexity in the time domain and power spectrum calculations in the frequency domain. The Bandt and Pompe method was used to assess time series causality by associating probability distributions based on ordinal patterns with the signals. Due to the invasive nature of data acquisition, the study encountered limitations such as small sample sizes and potential sources of error. Nevertheless, the high spatial resolution of iEEG allows detailed analysis and comparison of specific brain regions. The results reveal differences between sexes in brain regions, observed through power spectrum, entropy, and complexity analyses. Significant differences were found in the left supramarginal gyrus, posterior cingulate, supplementary motor cortex, middle temporal gyrus, and right superior temporal gyrus. This study emphasizes the importance of considering sex as a biological variable in brain dynamics research, which is essential for improving the diagnosis and treatment of neurological and psychiatric disorders. Full article

Inspired by classical polar codes, whose coding rate can asymptotically achieve the Shannon capacity, researchers are trying to find their analogs in the quantum information field, which are called quantum polar codes. However, no one has designed a quantum polar coding scheme that applies to quantum computing yet. There are two intuitions in previous research. The first is that directly converting classical polar coding circuits to quantum ones will produce the polarization phenomenon of a pure quantum channel, which has been proved in our previous work. The second is that based on this quantum polarization phenomenon, one can design a quantum polar coding scheme that applies to quantum computing. There are several previous work following the second intuition, none of which has been verified by experiments. In this paper, we follow the second intuition and propose a more reasonable quantum polar stabilizer code construction algorithm than any previous ones by using the theory of stabilizer codes. Unfortunately, simulation experiments show that even the stabilizer codes obtained from this more reasonable construction algorithm do not work, which implies that the second intuition leads to a dead end. Based on the analysis of why the second intuition does not work, we provide a possible future direction for designing quantum stabilizer codes with a high coding rate by borrowing the idea of classical polar codes. Following this direction, we find a class of quantum stabilizer codes with a coding rate of 0.5, which can correct two of the Pauli errors. Full article

Sorghum has a long history of cultivation in China. In this study, we aimed to clarify the genetic relationships and genetic variation trends in widely used Chinese sorghum hybrids which were released from the 1970s to 2010s and attempted to analyze the changes in sorghum breeding. A total of 257 alleles were detected by 51 polymorphic SSR markers among 69 widely used hybrids; an average of 5.04 alleles were detected by each marker. The average Shannon’s index and polymorphism information content (PIC) of markers were 1.39 and 0.70, respectively. Nei’s genetic diversity index continuously increased in four different breeding development stages (1973–1982, 1983–1992, 1993–2002, and 2003–2014). Genetic diversity gradually increased among the sorghum hybrids. Genetic similarity coefficients in the four breeding development stages first showed an increasing trend, and then a decreasing trend, finally stabilizing with an average value of 0.65. The genetic similarity changes in hybrids in early and late maturing areas were consistent at different breeding development stages. The genetic similarity coefficients in late maturing areas were constantly higher than those in the early maturing areas. This is related to China’s creative utilization of A₂ cytoplasmic male sterile materials in the 1990s. A cluster analysis determined that 69 hybrids were divided into two groups, A and B. Group A could be further subdivided into four subgroups. These findings could provide a reference for parental selection and hybrid breeding in sorghum improvement programs. Full article

By using 14 SSR primer pairs, we here analyzed and compared the amplification results of 534 DNA samples from six red sugar beet germplasm resources under three treatments. These data were used to explore the sampling strategy for the aforementioned resources. Based on the sampling strategy results, 21 SSR primer pairs were used to evaluate the genetic diversity of 47 red sugar beet germplasm resources. The six population genetic parameters used for exploring the sampling strategy unveiled that individual plants within the population had a relatively large genetic distance. The genetic parameters Ne, I, and Nei’s of the randomly mixed sampling samples increased rapidly between 10 and 30 plants before decreasing. Therefore, when SSR technology was used to analyze the genetic diversity of the red sugar beet germplasm resources, the optimal sampling gradient for each population was the adoption of a random single-plant mixed sampling sample of no less than 10 plants and no more than 30 plants. The 21 SSR primer pairs were used to detect genetic diversity in 30 random mixed samples of 47 resources. The average polymorphic information content (PIC) was 0.5738, the average number of observed alleles (Na) was 4.1905, the average number of effective alleles (Ne) was 2.8962, the average Shannon’s information index (I) was 1.1299, the average expected heterozygosity (Nei’s) was 0.6127, and the average expected heterozygosity (He) was 0.6127. The genetic distance of the 47 germplasm resources ranged from 0.0225 to 0.551 (average: 0.316). According to the population structure analysis, the most suitable K value was six, which indicated the presence of six populations. Based on the clustering analysis results, the 47 germplasm resources were segregated into six groups, with obvious clustering and some germplasm resources noted for having groups with close genetic relationships. We here established a more accurate and scientific sampling strategy for analyzing the genetic diversity of red sugar beet germplasm resources by using SSR molecular markers. The findings provide a reference for collecting and preserving red sugar beet germplasms and protecting their genetic diversity. Full article

The crop and crop wild relative (CWR) checklist of Lithuania was created containing 2630 taxa. The checklist comprises 1384 native taxa including archaeophytes and 1246 neophytes. In total, 699 taxa (26.6%) are defined for food and forage use. A list of 144 CWR priority species with 135 native species and archaeophytes and 9 naturalized species was generated. In total, 53 genera of food and forage species belonging to 15 families are represented by the priority CWR. Two approaches for CWR genetic reserve selection have been employed in this study: (1) CWR-targeted evaluation of preselected sites, including Natura 2000 sites, national protected areas, and other effective area-based conservation measures (OECMs), such as ancient hillfort sites and ecological protection zones of water bodies; (2) analysis of large georeferenced plant databases. Forty-five potential genetic reserve sites have been selected by the first approach covering 83 species or 57.6% of the national CWR priority list. With the second approach, the in situ CWR National Inventory database has been created by combining data from the Database of EU habitat mapping in Lithuania (BIGIS), Herbarium Database of the Nature Research Centre (BILAS), Lithuanian Vegetation Database (EU-LT-001), and Global Biodiversity Information Facility (GBIF). Hotspot analysis of CWR species richness and number of observations suggested that higher CWR diversity is more likely to be found in protected areas. However, Shannon diversity and Shannon equitability indices showed that the areas outside of the protected areas are also suitable for CWR genetic reserve establishment. Full article

Meconopsis integrifolia is an endangered Tibetan medicinal plant with significant medicinal and ornamental value. Understanding its genetic diversity and structure is crucial for its sustainable utilization and effective conservation. Here, we develop a set of SSR markers based on transcriptome data to analyze the genetic diversity and structure of 185 individuals from 16 populations of M. integrifolia. The results indicate that M. integrifolia exhibits relatively high genetic diversity at the species level (the percentage of polymorphic bands PPB = 91.67%, Nei’s genetic diversity index He = 0.2989, Shannon’s information index I = 0.4514) but limited genetic variation within populations (PPB = 12.08%, He = 0.0399, I = 0.0610). The genetic differentiation among populations is relatively high (the coefficient of gene differentiation GST = 0.6902), and AMOVA analysis indicates that 63.39% of the total variation occurs among populations. This suggests that maintaining a limited number of populations is insufficient to preserve the overall diversity of M. integrifolia. Different populations are categorized into four representative subclusters, but they do not cluster strictly according to geographical distribution. Limited gene flow (Nm = 0.2244) is likely the main reason for the high differentiation among these populations. Limited seed and pollen dispersal abilities, along with habitat fragmentation, may explain the restricted gene flow among populations, highlighting the necessity of conserving as many populations in the wild as possible. Full article

The genetic diversity and structure of 17 populations of J. curcas, including 92 accessions from different provenances (tropical and subtropical), were investigated and effectively evaluated using twelve inter-simple sequence repeats (ISSRs) and seven pairs of florescence-amplified fragment-length polymorphism (AFLP) primers. Genetic diversity, at the overall level among populations of J. curcas based on the ISSR markers, showed that the observed number of alleles (Na) was 1.593, the effective number of alleles (Ne) was 1.330, Nei’s gene diversity (H) was 0.200, Shannon’s information index (I) was 0.303, and the percentage of polymorphic loci was 59.29%, indicating moderate genetic diversity between and within the different populations of J. curcas. Based on the genetic diversity analysis of AFLP markers, there were 1.464 (Na) and 1.216 (Ne) alleles, Nei’s gene diversity (H) was 0.132, Shannon’s information index (I) was 0.204, and the percentage of polymorphic loci was 46.40%. The AMOVA analysis showed that this large variance was due to differences within the populations, with genetic distinctions and limited gene flow among those from varied regions. The 17 populations were clustered into five main groups via UPGMA clustering analysis based on Nei’s genetic distance, and the genetic relationships among the populations exhibited no significant correlations with geographical provenances. The genetic variation among Chinese populations of J. curcas distributed in dry-hot valley areas was remarkable, and the American germplasm presented with distinct genetic differentiation. Full article

Exploring the phenotypic trait variation and diversity of Lycium ruthenicum germplasm resources can support selection, breeding, and genetic improvement, enhancing agricultural production. This study collected 213 wild Lycium ruthenicum seedlings from a resource nursery in Alxa League, Inner Mongolia. These seedlings originated from eight sources across four provinces. Using 11 pseudo-qualitative traits and 20 quantitative traits, the phenotypic variation of the germplasm was analyzed. The analysis involved the coefficient of variation, Shannon–Wiener index (H), Simpson’s genetic diversity index (D), principal component analysis, correlation analysis, and Q-type cluster analysis. The results showed that the variation range of 31 phenotypic traits across the 213 Lycium ruthenicum germplasm resources was 17.26% to 105.41%, with an average coefficient of variation of 39.85%. The H and D indexes ranged from 0.18 to 1.58 and 0.20 to 0.75, respectively. For the 11 pseudo-qualitative traits, the H and D ranges were 0.18 to 1.58 and 0.07 to 0.74, with average values of 0.77 and 0.42. For the quantitative traits, the H and D ranges were 0.54 to 1.49 and 0.25 to 0.75, with average values of 1.21 and 0.63. This indicates that Lycium ruthenicum germplasm resources exhibit significant phenotypic diversity, with quantitative traits showing higher diversity than pseudo-qualitative traits. Principal component analysis revealed that the cumulative variance contribution rate of the first 10 principal components was 74.03%, comprehensively reflecting the information of the 31 traits. Q-type cluster analysis grouped the 213 Lycium ruthenicum germplasm resources into six clusters, each with distinct phenotypic characteristics. This analysis also identified the trait characteristics and breeding value of each cluster. The results of this study provide valuable information on the genetic improvement, conservation, and evaluation of Lycium ruthenicum germplasm resources. Full article