Search Results (2,889)

Sustainable agricultural practices need to be continuously sought after so that a greater number of producers can adopt them, taking into account, above all, the food security scenario, land use efficiency, and climate change. Intercropping—a cultivation system in which two or more species are grown in close proximity in the same field—is one strategy to increase diversity in the agroecosystem. However, for intercropping systems to be adopted, their productive and economic advantages over monoculture must be clearly demonstrated. Banana (Musa sp.) growers are interested in crop diversification as a potential strategy to increase production yields and, consequently, economic income. The management of banana crops can be facilitated by intercropping, as this system plays an important role in increasing biodiversity and reducing the need for weed control in the crop rows, promoting better land use efficiency. However, this system should be evaluated alongside other indicators. Banana intercropping has significant potential and many benefits, but success depends on the interaction between the component species, appropriate management practices, and favorable environmental conditions. This review aims to provide an overview of recent studies on banana intercropping systems, focusing on the contextualization of land use, monoculture and intercropping, and evaluating intercropping indicators, as well as the benefits, risks, and disadvantages discussed in the literature, and the main outcomes of banana-based intercropping systems. The main findings relate to the possibility of using intercrops with aromatic species and the preliminary reports on the contributions of intercrops to the suppression of Fusarium wilt disease. Full article

Aluminum-activated malate transporter (ALMT) genes play an important role in aluminum ion (Al³⁺) tolerance, fruit acidity, and stomatal movement. Although decades of research have been carried out in many plants, there is little knowledge about the roles of ALMT in Orchidaceae. In this study, 34 ALMT genes were identified in the genomes of four orchid species. Specifically, ten ALMT genes were found in Dendrobium chrysotoxum and D. catenatum, and seven were found in Apostasia shenzhenica and Phalaenopsis equestris. These ALMT genes were further categorized into four clades (clades 1–4) based on phylogenetic relationships. Sequence alignment and conserved motif analysis revealed that most orchid ALMT proteins contain conserved regions (TM1, GABA binding motif, and WEP motif). We also discovered a unique motif (19) belonging to clade 1, which can serve as a specifically identified characteristic. Comparison with the gene structure of AtALMT genes (Arabidopsis thaliana) showed that the gene structure of ALMT was conserved across species, but the introns were longer in orchids. The promoters of orchid ALMT genes contain many light-responsive and hormone-responsive elements, suggesting that their expression may be regulated by light and phytohormones. Chromosomal localization and collinear analysis of D. chrysotoxum indicated that tandem duplication (TD) is the main reason for the difference in the number of ALMT genes in these orchids. D. catenatum was chosen for the RT-qPCR experiment, and the results showed that the DcaALMT gene expression pattern varied in different tissues. The expression of DcaALMT1-9 was significantly changed after ABA treatment. Combining the circadian CO₂ uptake rate, titratable total acid, and RT-qPCR data analysis, most DcaALMT genes were highly expressed at night and around dawn. The result revealed that DcaALMT genes might be involved in photosynthate accumulation. The above study provides more comprehensive information for the ALMT gene family in Orchidaceae and a basis for subsequent functional analysis. Full article

Nowadays, the microgrid system is characterized by a diversification of power factors and a complex network structure. Existing studies on microgrid fault diagnosis and troubleshooting mostly focus on the fault detection and operation optimization of a single power device. However, for increasingly complex microgrid systems, it becomes increasingly challenging to effectively contain faults within a specific spatiotemporal range. This can lead to the spread of power faults, posing great harm to the safety of the microgrid. The topology optimization of the microgrid based on deep reinforcement learning proposed in this paper starts from the overall power grid and aims to minimize the overall failure rate of the microgrid by optimizing the topology of the power grid. This approach can limit internal faults within a small range, greatly improving the safety and reliability of microgrid operation. The method proposed in this paper can optimize the network topology for the single node fault and multi-node fault, reducing the influence range of the node fault by 21% and 58%, respectively. Full article

The fragile environment of the Himalayan region is prone to natural hazards, which are intensified by climate change, leading to food and livelihood insecurity for inhabitants. Therefore, building resilience in the most dominant livelihood sector, i.e., the agricultural sector, has become a priority in development and planning. To assess the perils induced by climate change on the agriculture sector in the ecologically fragile region of Kashmir Valley, a study has been conducted to evaluate the risk using the Intergovernmental Panel on Climate Change (IPCC) framework. The risk index has been derived based on socioeconomic and ecological indicators for risk determinants, i.e., vulnerability, hazard, and exposure. Furthermore, the study also evaluated the future risk to the agriculture sector under changing climatic conditions using Shared Socioeconomic Pathways (SSPs) for SSP2-4.5 and SSP5-8.5 at mid- and late-century timescales. It was observed that districts such as Bandipora (0.59), Kulgam (0.56), Ganderbal (0.56), and Kupwara (0.54) are most vulnerable due to drivers like low per capita income, yield variability, and areas with >30% slope. Shopian and Srinagar were found to be the least vulnerable due to adaptive capacity factors like livelihood diversification, crop diversification, percentage of tree crops, and percentage of agriculture labor. In terms of the Risk index, the districts found to be at high risk are Baramulla (0.19), Pulwama (0.16), Kupwara (0.15), and Budgam (0.13). In addition, the findings suggested that the region would experience a higher risk of natural hazards by the mid- (MC) and end-century (EC) due to the projected increase in temperature with decreasing precipitation, which would have an impact on crop yields and the livelihoods of farmers in the region. Full article

We used cluster analysis on 200-year-old tree-ring chronologies to examine the patterns that emerge from self-organization, driven by environmental heterogeneity, that might drive diversification in ponderosa pine (Pinus ponderosa). We determined the natural patterns on the landscape and then tested these groups against historically separated varieties within this species that could be evidence of diversification. We used 178 previously collected tree-ring chronologies from the western United States that were archived in the International Tree-Ring Databank. We explored a variety of clustering techniques, settling on Ward’s clustering with Euclidian distance measures as the most reasonable clustering process. These techniques identified two (p = 0.005) to ten (p = 0.01) potential natural clusters in the ponderosa pine chronologies. No matter the number of clusters, we found that the ponderosa pine varieties ponderosa and benthamiana always cluster together. The variety scopulorum differentiates clearly on its own, but brachyptera is a mix of diverse groups, based on the environmental driving factors that control tree-ring chronology variability. Cluster analysis is a useful tool to examine natural grouping on the landscape using long-term tree-ring chronologies, enabling the researcher to examine the patterns of environmental heterogeneity that should lead to speciation. From this analysis, we suggest that the brachyptera variety should be more varied genetically. Full article

The face of corporate governance is changing as new technologies in the scope of artificial intelligence and data analytics are used to make better future-oriented decisions on performance management. This study attempts to provide empirical results to analyze when the impact of diversity on the board of directors is most evident through the multi-breaks model and artificial neural networks. The input data for the simulation includes 853 electronic companies listed on the Taiwan Stock Exchange from 2000 to 2021. The empirical results show that the higher the percentage of female board members, the more influential the company’s performance is, which is only evident when the company is in good business condition. By integrating ANNs with multi-breakpoint regression, this study introduces a novel approach to management research, providing a detailed perspective on how board diversity impacts firm performance across different conditions. The ANN results show that using the number of business board members for predicting Return on Assets yields the highest accuracy, with female board members following closely in predictive effectiveness. The presence of women on the board contributes positively to ROA, particularly when the company is experiencing favorable business conditions and high profitability. Our analysis also reveals that a higher percentage of male board members improves company performance, but this benefit is observed only in highly favorable and unfavorable business conditions. Conversely, a higher percentage of business members tends to affect performance during periods of high profitability negatively. The power of the board of directors and significant shareholders is positively correlated with performance, whereas CEO power positively impacts performance only when it is not extremely low. Independent board members generally do not have a significant effect on profits. Additionally, the company’s asset value positively influences performance primarily when the return on assets is high, and increased financial leverage is associated with reduced profitability. Full article

Given the overexploitation of fisheries and the growing consumption of sea products, aquaculture is emerging as an alternative to meet the demand for protein at regional, national, and global levels. In northern Chile, the foothills of the Andes offer an opportunity for sustainable economic diversification. In this study, results of a rainbow trout (Oncorhynchus mykiss) culture in a recirculation system are presented, analyzing its growth and performance under altitude conditions. The research was carried out in Copaquilla, a small area in the foothills of northern Chile, 3000 m above sea level. Five thousand 15 g juvenile trout were acquired and transported by land from the Rio Blanco fish farm, successfully traveling more than 2100 km. During the 20-month-long culture, several growth parameters were evaluated, including specific growth rate, percentage of weight growth, feed conversion factor, survival, and Fulton’s condition factor. All these parameters were within the normal growth range for trout, evidencing good-quality growth of the organisms. The results offer evidence that rainbow trout farming at 3000 m above sea level is viable and presents a viable performance, opening new opportunities for aquaculture in northern Chile. Full article

Exploring the low-carbon transition in China can offer profound guidance for governments to develop relevant environmental policies and regulations within the context of the 2060 carbon neutrality target. Previous studies have extensively explored the promotion of low-carbon development in China, yet no studies have completely explained the mechanisms of the low-carbon transition in China from the perspective of per capita carbon emissions (PCEs). Based on the statistics and carbon emissions data of 367 prefecture level cities in China from 2000 to 2020, this study employed markov chain, kernel density analysis, hotspots analysis, and spatial regression models to reveal the spatiotemporal distribution patterns, future trends, and driving factors of PCEs in China. The results showed that China’s PCEs in 2000, 2010, and 2020 were 0.72 ton/persons, 1.72 ton/persons, and 1.91 ton/persons, respectively, exhibiting a continuous upward trend, with evident regional heterogeneity. PCEs in northern China and the eastern coastal region were higher than those of southern China and the central and southwestern regions. The PCEs in China showed obvious spatial clustering, with hot spots mainly concentrated in Inner Mongolia and Xinjiang, while cold spots were mainly in some provinces in southern China. The transition of PCEs in China exhibited a strong stability and a ‘club convergence’ phenomenon. A regression analysis revealed that the urbanization level and latitude had negative effects on PCEs, while the regional economic development level, average elevation, average slope, and longitude showed positive effects on PCEs. These findings have important implications for the promotion of the low-carbon transition and the effective achievement of the “dual carbon” goal. Full article

Transposable elements (TEs) significantly contribute to the evolution and diversity of plant genomes. In this study, we explored the roles of TEs in the genomes of Citrus and Citrus-related genera by constructing a pan-genome TE library from 20 published genomes of Citrus and Citrus-related accessions. Our results revealed an increase in TE content and the number of TE types compared to the original annotations, as well as a decrease in the content of unclassified TEs. The average length of TEs per assembly was approximately 194.23 Mb, representing 41.76% (Murraya paniculata) to 64.76% (Citrus gilletiana) of the genomes, with a mean value of 56.95%. A significant positive correlation was found between genome size and both the number of TE types and TE content. Consistent with the difference in mean whole-genome size (39.83 Mb) between Citrus and Citrus-related genera, Citrus genomes contained an average of 34.36 Mb more TE sequences than Citrus-related genomes. Analysis of the estimated insertion time and half-life of long terminal repeat retrotransposons (LTR-RTs) suggested that TE removal was not the primary factor contributing to the differences among genomes. These findings collectively indicate that TEs are the primary determinants of genome size and play a major role in shaping genome structures. Principal coordinate analysis (PCoA) of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) identifiers revealed that the fragmented TEs were predominantly derived from ancestral genomes, while intact TEs were crucial in the recent evolutionary diversification of Citrus. Moreover, the presence or absence of intact TEs near the AdhE superfamily was closely associated with the bitterness trait in the Citrus species. Overall, this study enhances TE annotation in Citrus and Citrus-related genomes and provides valuable data for future genetic breeding and agronomic trait research in Citrus. Full article

Hyperuricemia, a major worldwide burden on public hygiene, is closely connected with dietary habits. However, few studies have evaluated the association of dietary diversity with hyperuricemia. To preliminarily reveal the status of a diversified diet in preventing hyperuricemia based on a neighborhood-based, massive-scale cohort in China, a total of 43,493 participants aged 20–74 years old, with no history of hyperuricemia at baseline, were enrolled in the research from April 2016 to December 2019. The Dietary Diversity Score (DDS) was utilized to evaluate the dietary variety and split the participants into the low-, medium-, and high-DDS groups. Information on participants was connected to regional health information systems that acquired data on hyperuricemia instances up to 28 February 2023. Hazard ratios (HRs) and 95% confidence intervals (CIs) were computed by Cox proportional hazards models. Restricted cubic splines (RCS) were implemented to analyze dose–response correlation. A total of 1460 individuals with newly diagnosed hyperuricemia were observed over a median follow-up period of 5.59 years. Compared to the low-DDS group, HRs for the medium- and high-DDS groups were 0.87 (95% CI 0.76–0.99) and 0.80 (95% CI 0.70–0.91) in the fully adjusted model, respectively. The risk of hyperuricemia incidence was reduced by 5% for each 1 unit of DDS increase. A linear correlation of DDS with hyperuricemia emerged and further revealed that the intake of 8–10 broad categories of food could decrease the incidence of hyperuricemia. Our results validate the dietary principle of “food diversification” recommended in guidelines. Conclusions should be applied with caution considering the paucity of related evidence in additional nations. Full article

This study explores the relationship between the entrepreneurship ecosystem and decent work in digital entrepreneurship, raising essential questions about the roles of economic growth and socioeconomic status. By examining this relationship, the research aims to clarify how these factors influence opportunities, inclusivity, and sustainable development in the digital entrepreneurship landscape. It investigates both the direct impacts of the entrepreneurship ecosystem and decent work and the moderating effects of economic growth and socioeconomic disparities on digital entrepreneurship. These moderating factors are crucial for understanding how broader economic conditions can enhance or limit the entrepreneurship ecosystem’s effectiveness. Data were collected from 624 entrepreneurs in the Kingdom of Saudi Arabia (KSA) to empirically test this model, providing a solid foundation for the proposed hypotheses. The findings significantly affect knowledge advancement and policymaking, particularly concerning KSA Vision 2030. The results confirm the vital roles of a well-developed entrepreneurship ecosystem and the promotion of decent work in supporting digital entrepreneurship. Moreover, the moderating effects of economic growth and socioeconomic status indicate that policy interventions should consider these broader contextual factors to be effective. For policymakers, this study emphasizes the need to foster an environment that strengthens the entrepreneurship ecosystem while addressing economic inequalities and promoting sustained growth. Aligning these initiatives with KSA Vision 2030 could advance digital entrepreneurship as a pivotal element of the country’s economic diversification and development strategies. Ultimately, the study aims to inform policies that enhance inclusivity and sustainability in the digital entrepreneurship sector, ensuring that the advantages of digital innovation are widely accessible across society. Full article

In this study, we apply a novel approach of portfolio diversification—the robust maximum diversified (RMD)—to a small and developing economy’s stock market. Using monthly returns data from August 2019 to May 2024 of 18/19 stocks listed on Fiji’s South Pacific Stock Exchange (SPX), we construct the RMD portfolio and simulate with additional constraints. To implement the RMD portfolio, we replace the covariance matrix with a matrix comprising unexplained variations. The RMD procedure diversifies weights, and not risks, hence we need to run a pairwise regression between two assets (stocks) and extract the R-square to create a P-matrix. We compute each asset’s beta using the market-weighted price index, and the CAPM to calculate market-adjusted returns. Next, together with other benchmark portfolios (1/N, minimum variance, market portfolio, semi-variance, maximum skewness, and the most diversified portfolio), we examine the expected returns against the risk-free (RF) rate. From the simulations, in terms of expected return, we note that eight portfolios perform up to the RF rate. Specifically, for returns between 4 and 5%, we find that max. RMD with positive Sharpe and Sortino (as constraints) and the most diversified portfolio offer comparable returns, although the latter has slightly lower standard deviation and downside volatility and contains 94% of all the stocks. Portfolios with returns between 5% and the RF rate are the minimum-variance, the semi-variance, and the max. RMD with positive Sharpe; the latter coincides with the RF rate and contains the most (94%) stocks compared to the other two. An investor with a diversification objective, some risk tolerance and return preference up to the RF rate can consider the max. RMD with positive Sharpe. However, depending on the level of risk-averseness, the minimum-variance or the semi-variance portfolio can be considered, with the latter having lower downside volatility. Two portfolios offer returns above the RF rate—the market portfolio (max. Sharpe) and the maximum Sortino. Although the latter has the highest return, this portfolio is the least diversified and has the largest standard deviation and downside volatility. To achieve diversification and returns above the RF rate, the market portfolio should be considered. Full article

The family Bondarzewiaceae is an important and diverse group of macrofungi associated with wood as white rotting fungi, and some species are forest tree pathogens. Currently, there are nine genera and approximately 89 species in the family, distributed in tropical, subtropical, and temperate climates. To address the phylogenetic relationships among the genera, a combined ITS-28S dataset was subjected to maximum likelihood (ML), Bayesian inference (BI), and time divergence analyses using the BEAST package. Both ML and BI analyses revealed two major clades, where one major clade consisted of Amylosporus, Stecchericium, and Wrightoporia austrosinensisa. The second major clade is composed of Bondarzewia, Heterobasidion, Gloiodon, Laurilia, Lauriliella, and Wrightoporia, indicating that these genera are phylogenetically similar. Wrightoporia austrosinensisa recovered outside of Wrightoporia, indicating that this species is phylogenetically different from the rest of the species of the genus. Similarly, time divergence analyses suggest that Bondarzewiaceae diversified around 114 million years ago (mya), possibly during the Early Cretaceous Epoch. The genus Amylosporus is well resolved within the family, with an estimated stem age of divergent around 62 mya, possibly during the Eocene Epoch. Further, the species of the genus are recovered in two sister clades. One sister clade consists of species with pileate basidiomata and generative hyphae with clamp connections, corresponding to the proposed section Amylosporus sect. Amylosporus. The other consists of species having resupinate basidiomata and generative hyphae without clamps, which is treated here as Amylosporus sect. Resupinati. We provided the key taxonomic characters, known distribution, number of species, and stem age of diversification of each section. Furthermore, we also described a new species, Amylosporus wadinaheezicus, from Oman, based on morphological characters of basidiomata and multigene sequence data of ITS, 28S, and Tef1-α. With pileate basidiomata and phylogenetic placement, the new species is classified under the proposed A. sect. Amylosporus. An identification key to the known species of Amylosporus is presented. Ecology and distribution of species of the genera in the family are discussed. Full article

With the increasing complexity of mechanical equipment and diversification of deep learning models, vibration signals collected from such equipment are susceptible to noise interference. Moreover, traditional neural network models struggle to be effectively deployed in production environments with limited computational resources, severely impacting the accurate extraction and effective diagnosis of FK fault characteristics. In response to this challenge, this study proposes a fault diagnosis method for rolling bearings, integrating a lightweight ShuffleNetV2 network with variational mode decomposition (VMD) and the fast kurtogram (FK) algorithm. Initially, this paper introduces an enhanced FK method where the VMD algorithm is employed for data denoising, extracting FK post-denoising. These feature maps not only preserve critical signal information but also simplify data complexity. Subsequently, these feature maps are utilized to train and test the ShuffleNetV2 model, facilitating effective fault identification and classification. Ultimately, by conducting experimental comparisons with several mainstream lightweight network models, such as MobileNet and SqueezeNet, as well as traditional convolutional neural network models, this study validates the effectiveness of the proposed method in extracting fault characteristics from vibration signals, demonstrating superior diagnostic accuracy and computational efficiency. This provides a novel technical approach for health monitoring and fault diagnosis of industrial bearings and offers theoretical and experimental support for the deployment of lightweight networks in industrial applications. Full article

With the rapid expansion of global trade, the complexity and diversification of supply chains have become increasingly significant. In particular, the supply chain for hazardous materials, involving chemicals and explosives, requires stringent regulation. Managing the flow of these high-risk goods necessitates a reliable access control system to ensure safety and compliance. Traditional supply chain management systems often rely on centralized databases and record-keeping systems, which are prone to tampering and single points of failure, making them inadequate for current high-security demands. This paper combines blockchain technology with a hazardous materials supply chain model. In the blockchain network, our innovation lies in the introduction of a transaction coordinator to create transaction sets for each supply chain entity along with smart contracts to implement access control for these transaction sets. We also propose a new hazardous materials supply chain model architecture and conduct experimental verification using simulated hazardous materials supply chain data. Our experimental results show that the proposed method performs excellently in throughput and latency tests, demonstrating the potential to enhance the efficiency and security of supply chain management. Full article