Search Results (60,124)

Histone acetylation is an important epigenetic mechanism that has been shown to play a role in diapause regulation. To explore the physiological and molecular mechanisms of histone deacetylase in the diapause process, LC-MS/MS analysis was used to perform TMT proteomic and metabolomic analysis on non-diapause (ND), pre-diapause (PreD), diapause (D), cold treatment (CT), and post-diapause (RD) stages of the meadow moth. A total of 5367 proteins were identified by proteomics, including 1179 differentially expressed proteins. We found 975 (602 up-regulated and 373 down-regulated), 997 (608 up-regulated and 389 down-regulated), 1119 (726 up-regulated and 393 down-regulated), 1179 (630 up-regulated and 549 down-regulated), 94 (51 up-regulated and 43 down-regulated), 111 (63 up-regulated and 48 down-regulated), 533 (243 up-regulated and 290 down-regulated), 58 (31 up-regulated and 27 down-regulated), and 516 (228 up-regulated and 288 down-regulated) proteins in ND and PreD, ND and D, ND and CT, ND and RD, PreD and D, PreD and CT, PreD and RD, D and CT, D and RD, and CT and RD stages, respectively. A total of 1255 differentially expressed metabolites were annotated by metabolomics. Through KEGG analysis and time series analysis of differentially expressed metabolites, we found that phospholipids were annotated in significantly different modules, demonstrating their important role in the diapause process of the meadow moth. Using phospholipids as an indicator for weighted gene co-expression network analysis, we analyzed the most relevant differentially expressed proteins in the module and found that ribosomal 40s and 60s subunits were the most relevant proteins for diapause. Because there have been studies that have shown that histone deacetylase is associated with the diapause of meadow moths, we believe that histone deacetylase regulates the 40s and 60s subunits of ribosomes, which in turn affects the diapause of meadow moths. This finding expands our understanding of the regulation of meadow moth diapause and provides new insights into its control mechanism. Full article

Glacial Lake Outburst Flood (GLOF) events, particularly prevalent in Asia’s High Mountain regions, pose a significant threat to downstream regions. However, limited understanding of triggering mechanisms and inadequate observations pose significant barriers for early warnings of impending GLOFs. The 2018 Nyalam GLOF event in southern Tibet offers a valuable opportunity for retrospective analysis. By combining optical and radar remote sensing images, meteorological data, and seismicity catalogs, we examined the spatiotemporal evolution, triggering factors, and the outburst mechanism of this event. Our analysis reveals a progressive retreat of 400–800 m for the parent glaciers between 1991 and 2018, increasing the runoff areas at glacier termini by 167% from 2015 to 2018 and contributing abundant meltwater to the glacial lake. In contrast, the lake size shrunk, potentially due to a weakening moraine dam confirmed by SAR interferometry, which detected continuous subsidence with a maximum line-of-sight (LOS) rate of ~120 mm/a over the preceding ~2.5 years. Additionally, temperature and precipitation in 2018 exceeded the prior decade’s average. Notably, no major earthquakes preceded the event. Based on these observations, we propose a likely joint mechanism involving high temperatures, heavy precipitation, and dam instability. An elevated temperature and precipitation accelerated glacial melt, increasing lake water volume and seepage through the moraine dam. This ultimately compromised dam stability and led to its failure between 3 August 2018 and 6 August 2018. Our findings demonstrate the existence of precursory signs for impending GLOFs. By monitoring the spatiotemporal evolution of environmental factors and deformation, it is possible to evaluate glacial lake risk levels. This work contributes to a more comprehensive understanding of GLOF mechanisms and is of significant importance for future glacial lake risk assessments. Full article

Facility Management (FM) has increasingly focused on integrating Building Information Modeling (BIM) with the Internet of Things (IoT), known as digital twins, in large-scale development projects. Effective BIM integration in FM requires improved cooperation among participants across various project stages. This digital revolution aims to enhance planning, construction, and asset management efficiency, benefiting all parties. However, BIM utilization in FM is limited by incomplete owner understanding, insufficient data accessibility, and stakeholders’ unfamiliarity with BIM procedures and standards. Despite recognizing BIM’s significance, the FM industry faces significant implementation challenges. Facility managers often lack a comprehensive understanding of BIM’s benefits in streamlining operations and enhancing cost efficiency, as well as the necessary skills for its use. Addressing these barriers requires developing an Employer’s Information Requirements (EIR) document at a project’s outset, providing a strategic plan and vision for all involved parties. BIM and IoT are pivotal technologies for transitioning to efficient building operations and crucial for reducing time, costs, and operational challenges throughout any project. This research aims to establish a digital trio workflow, integrating BIM, EIR, and IoT to maximize stakeholder benefits. It explores how preparing the EIR through stakeholder communication can improve design processes, sustainability, efficiency, cost, and time, especially for megaprojects. Full article

In Romania, rural communities grapple with decades of depopulation and economic decline, endangering the natural and cultural richness of their landscapes. The implementation of Romania’s 2030 sustainable development plan presents an opportunity to reverse these trends by merging economic and community development with cultural preservation. This paper examines the potential for creating new livelihood opportunities through a program that integrates sustainable agrotourism with culturally appropriate vernacular architecture in Romania’s distinct rural regions. Focusing on two such regions characterized by significant rural population decline yet endowed with ecological services capable of supporting a diverse rural economy, we collaborated with an architect and landscape engineer to devise three specific and detailed agritourist housing scenarios. These scenarios draw upon local architectural forms harmonious with the vernacular landscape, providing accommodations for agrotourism guests and facilitating craft workshops for visitors interested in rural crafts and traditions. We evaluated the cultural appropriateness of the architectural designs through a social survey and assessed the broader social utility of the development plan via an expansive cost–benefit analysis, treating the project’s sustainability features as quasi-public goods. Such interdisciplinary endeavours are essential for effectively bridging conceptually driven social analysis with pragmatic design and planning strategies, essential for achieving sustainable futures for rural communities and landscapes, as exemplified by rural Romania. Full article

Logistics, distribution models, and landscapes of food production strongly influence the space of our cities and territories. In addition to the network of large-scale retail distribution that is diffused in urban and non-urban areas, with this contribution, we study the presence of new forms of the local and sustainable distribution of food (such as Alternative Food Networks, and community-supported agriculture). Studying and understanding how these distribution models can support and be integrated within a landscape planning and design approach is explored through the Analytic Hierarchy Process (AHP), a multi-criteria decision analysis method. Through the specific focus of a Food Hub localization, the aim is to demonstrate how distribution models can not only support but also integrate into landscape planning and design. The fundamental objectives for structuring and locating a Food Hub can be organized under three strategic objectives: pursuing the benefit of people, the planet, and profit. The choice of one distribution method over others, or what is the best location and condition for distribution centers, is the question we have tested with the collaboration of “L’Ortazzo” Association. The case study is a solidarity purchasing group located in the upper Valsugana valley area (Trentino Region, Italy), a supra-municipality reality involving about a hundred families that, currently, do not have a physical distribution center. Full article

The reliance on rainfed agriculture exposes southern Africa to low agricultural productivity and food and nutritional insecurity; yet, the region is endowed with vast irrigation potential. Extreme weather events including drought, floods, and heatwaves exacerbate the existing challenges, underscoring the need to improve agricultural water management as a climate change adaptation strategy. This mixed-methods review followed the Search, Appraisal, Synthesis, and Analysis (SALSA) framework to explore the irrigation opportunities and challenges in southern Africa by critically analysing the drivers and constraints of irrigation systems in southern Africa. The premise is to understand the reasons behind the abandonment of some of the areas equipped for irrigation. In cases where irrigation systems are present, the study assesses whether such technologies are effectively being used to generate the expected agricultural productivity gains, and what factors, in cases where that is not the case, constrain farmers from fully using the existing infrastructure. The review further discusses the enabling environment supporting irrigated agriculture and the role of gender in irrigation development. An assessment of the role of women in agriculture on the share of land equipped for irrigation to total cultivated land area, as well as on the proportion of the area equipped for irrigation versus the area that is actually irrigated is conducted. The review found a divergence between countries’ land areas equipped for irrigation and actually irrigated areas. Specific to irrigation expansion, the review rebuts the notion that increasing the irrigated area increases crop production and ensures food security. This may not always be true as irrigation development needs to consider the impacts on other closely linked water and energy sectors through transformative approaches like the water–energy–food (WEF) nexus and scenario planning. If well-planned and implemented, sustainable irrigated agriculture could be catalytic to transforming southern Africa’s food system to be inclusive, equitable, socially just, and resilient, benefiting people and the planet. Full article

Autonomous vehicles are rapidly advancing and have the potential to revolutionize transportation in the future. This paper primarily focuses on vehicle motion trajectory planning algorithms, examining the methods for estimating collision risks based on sensed environmental information and approaches for achieving user-aligned trajectory planning results. It investigates the different categories of planning algorithms within the scope of local trajectory planning applications for autonomous driving, discussing and differentiating their properties in detail through a review of the recent studies. The risk estimation methods are classified and introduced based on their descriptions of the sensed collision risks in traffic environments and their integration with trajectory planning algorithms. Additionally, various user experience-oriented methods, which utilize human data to enhance the trajectory planning performance and generate human-like trajectories, are explored. The paper provides comparative analyses of these algorithms and methods from different perspectives, revealing the interconnections between these topics. The current challenges and future prospects of the trajectory planning tasks in autonomous vehicles are also discussed. Full article

Malnutrition rates in Advanced Liver Disease (ALD) are significantly higher than those in well-compensated liver disease. In addition to its physiological impact, malnutrition is detrimental for quality of life and social, emotional, and psychological well-being. Studies within oncology and renal supportive care have identified the influence of non-physiological factors on malnutrition risk. Integrating similar factors into malnutrition screening for ALD could improve identification of at-risk patients to optimize treatment planning. This qualitative study aimed to understand the holistic factors influencing nutritional status in the ALD population. Semi-structured interviews with 21 patients, carers, and clinicians explored the experiences of malnutrition in ALD. Thematic analysis revealed five key themes: (i) appropriateness of healthcare delivery; (ii) health- and food-related factors; (iii) high symptom burden, (iv) social support impacting well-being, and (v) physical and structural supports. Current screening methods do not adequately capture all potential drivers of malnutrition in the ALD population. Adopting a more supportive approach including both physiological and non-physiological factors in ALD malnutrition screening may promote more timely and comprehensive nutritional interventions that address the complex and holistic needs of patients living with ALD. Full article

In addressing the complex challenges of path planning in multi-robot systems, this paper proposes a novel Hybrid Decentralized and Centralized Training and Execution (DCTE) Strategy, aimed at optimizing computational efficiency and system performance. The strategy solves the prevalent issues of collision and coordination through a tiered optimization process. The DCTE strategy commences with an initial decentralized path planning step based on Deep Q-Network (DQN), where each robot independently formulates its path. This is followed by a centralized collision detection the analysis of which serves to identify potential intersections or collision risks. Paths confirmed as non-intersecting are used for execution, while those in collision areas prompt a dynamic re-planning step using DQN. Robots treat each other as dynamic obstacles to circumnavigate, ensuring continuous operation without disruptions. The final step involves linking the newly optimized paths with the original safe paths to form a complete and secure execution route. This paper demonstrates how this structured strategy not only mitigates collision risks but also significantly improves the computational efficiency of multi-robot systems. The reinforcement learning time was significantly shorter, with the DCTE strategy requiring only 3 min and 36 s compared to 5 min and 33 s in the comparison results of the simulation section. The improvement underscores the advantages of the proposed method in enhancing the effectiveness and efficiency of multi-robot systems. Full article

While aspiring to become internationally valued producers of high-quality wines, certain Romanian wineries recently turned towards wine tourism. Given the increasing role of smart devices and online-based information in holiday selection and planning, the main objective of the paper is to evaluate the online presence, informational content and effectiveness of Romanian wineries’ websites for the promotion of wine tourism. This evaluation comprised 53 features tested in previous research and organized into four categories: main website characteristics, wine tourism, marketing, and education. Based on content analysis conducted on 154 websites of wineries identified in all Romanian regions, scores were computed and, subsequently, wineries were classified, mapped, and evaluated. The findings show that certain basic features are overall available, while exclusive features that could positively influence tourist preferences and experiences are insufficient in terms of design, education, and marketing characteristics. Less than 50% of the analysed websites inform about wine tasting activities, less than 35% specify visiting hours, and less than 20% mention tourist amenities. The websites that indicate other local wineries, allied industries or tourist attractions represent exceptions. This study underlines the importance of leveraging digital tools within the marketing strategy of wineries and the need to enhance networking among regional stakeholders as prerequisite for sustainable development. Full article

Complex event processing (CEP) systems have gained significant importance in various domains, such as finance, logistics, and security, where the real-time analysis of event streams is crucial. However, as the volume and complexity of event data continue to grow, optimizing the performance of CEP systems becomes a critical challenge. This paper investigates the impact of indexing strategies on the performance of databases handling complex event processing. We propose a novel indexing technique, called Hierarchical Temporal Indexing (HTI), specifically designed for the efficient processing of complex event queries. HTI leverages the temporal nature of event data and employs a multi-level indexing approach to optimize query execution. By combining temporal indexing with spatial- and attribute-based indexing, HTI aims to accelerate the retrieval and processing of relevant events, thereby improving overall query performance. In this study, we evaluate the effectiveness of HTI by implementing complex event queries on various CEP systems with different indexing strategies. We conduct a comprehensive performance analysis, measuring the query execution times and resource utilization (CPU, memory, etc.), and analyzing the execution plans and query optimization techniques employed by each system. Our experimental results demonstrate that the proposed HTI indexing strategy outperforms traditional indexing approaches, particularly for complex event queries involving temporal constraints and multi-dimensional event attributes. We provide insights into the strengths and weaknesses of each indexing strategy, identifying the factors that influence performance, such as data volume, query complexity, and event characteristics. Furthermore, we discuss the implications of our findings for the design and optimization of CEP systems, offering recommendations for indexing strategy selection based on the specific requirements and workload characteristics. Finally, we outline the potential limitations of our study and suggest future research directions in this domain. Full article

The objective of this research was to examine the determinants of farmer participation and shallot-farming development in search of effective farm management practices. The study used structural equation modeling data analysis. The primary data were collected from direct structural interviews with 150 randomly chosen shallot farmers in Bantaeng Regency, Indonesia. It was found that the latent variables of Physical Aspects of Land, System of Economy Peasant Society, and System of Political Peasant Society were fundamental factors that exerted a positive and significant influence on the latent variable of Farmer Participation. Therefore, improvements in the physical aspects of the land, the economic framework, and the political structure of agricultural communities could promote farmer participation. Furthermore, the latent variable of Farmer Participation and System of Political Peasant Society had a positive and significant impact on shallot-farming development. Thus, by increasing the influence of government officials and community leaders, shallot farming can be promoted. The farmers can then enhance their participation in shallot-farming plan formulation and implementation, providing the continued development of shallot farming. The findings of this study contribute significantly to the body of knowledge by validating previous research and proposing different ways to improve effective farm management practices in shallot farming. Full article

Rurality is an important indicator to reflect the development of villages and reveal internal differences in rural areas. The unbalanced development of transportation infrastructure in the current period of rapid urbanization has become one of the principal elements triggering spatial differences in rurality and changes in rural territorial characteristics. However, there are few studies on the impact of transportation infrastructure accessibility on the multidimensional characteristics of rurality from the perspective of heterogeneity. This paper analyzed the spatio-temporal characteristics of transport accessibility (TA) and the county rurality index (CRI) in Guangdong in 2005, 2010, 2015 and 2020 using an accessibility model and the rurality index and explored the clustering characteristics and interactions of TA and the CRI through exploratory spatial data analysis (ESDA) and geographic weighted regression (GWR) modeling. The findings showed that (1) TA and the CRI in Guangdong were significantly unbalanced in terms of space. The CRI showed a weakening trend in general, forming a distribution pattern of “high in the north and low in the south, high in the west and low in the east”, while TA was on the rise, maintaining a stable pattern of “high in the middle and low in the periphery”. (2) Both TA and the CRI in Guangdong had a Moran’s I value greater than 0.6 during the study period, exhibiting strong spatial agglomeration, while the two showed a significant spatial negative correlation. (3) The influence of TA on the CRI in different dimensions showed dynamic changes in stages, with TA having a higher intensity of effect on society rurality and land rurality in 2005, while on society rurality and industry rurality in 2020. (4) This paper grouped 77 counties in Guangdong into four types of policy zonings—coordination types, lagged types of accessibility, lagged types of rurality and double lagged types—and put forward corresponding development recommendations. The study conducted in this paper contributes to an in-depth understanding of the impact of transportation infrastructure development on the multidimensional characteristics of rurality and provides a basis for policy formulation for coordinated urban–rural development and sustainable rural development. Full article

Alluvial fans have been proven to have great utilisation potential in QTP, but to what extent they are suitable for agricultural development is unknown. Therefore, using the alluvial fan in the Lhasa River Basin (LRB) as a case study, this paper established an evaluation system of land suitability for agriculture (LSA). Principal component analysis (PCA) and the exhaustive method (EM) were used to define the minimum dataset (MDS) and then the LSA of the alluvial fan in the LRB was evaluated using a comprehensive index of LSA. Two scientific approaches were implemented to improve the LSA using a scenario simulation. The results showed that the MDS assessed by the EA was more representative compared to the PCA. Alluvial fans with suitable grades are mainly distributed in the Lhasa River’s middle and lower reaches. Developing facility agriculture and repairing roads accessing the alluvial fans are effective approaches to improve the LSA, which can increase the suitable-grade area from 58.62% to 97.82% and 63.85%, respectively. Therefore, most alluvial fans in the LRB are suitable for developing agriculture, and under the influence of human activities, there will be more alluvial fans suitable for developing agriculture. Our research provides scientific methods for the sustainable development of land in alpine regions. Full article

Cables are vital load-bearing components of cable-stayed bridges. Surface defects can lead to internal corrosion and fracturing, significantly impacting the stability of the bridge structure. The detection of surface defects from bridge cable images faces numerous challenges, including shadow disturbances due to uneven lighting and difficulties in addressing multiscale defect features. To address these challenges, this paper proposes a novel and cost-effective deep learning segmentation network, named Trans-DCN, to detect defects in the surface of the bridge cable. The network leverages an efficient Transformer-based encoder and integrates multiscale features to overcome the limitations associated with local feature inadequacy. The decoder implements an atrous Deformable Convolution (DCN) pyramid and dynamically fuses low-level feature information to perceive the complex distribution of defects. The effectiveness of Trans-DCN is evaluated by comparing it with state-of-the-art segmentation baseline models using a dataset comprising cable bridge defect images. Experimental results demonstrate that our network outperforms the state-of-the-art network SegFormer, achieving a 27.1% reduction in GFLOPs, a 1.2% increase in mean Intersection over Union, and a 1.5% increase in the F1 score. Ablation experiments confirmed the effectiveness of each module within our network, further substantiating the significant validity and advantages of Trans-DCN in the task of bridge cable defect segmentation. The network proposed in this paper provides an effective solution for downstream cable bridge image analysis. Full article