Hasil untuk "Rural industries"

Xuedong Hu, Jiaqi Hu, Zicheng Wang et al.

As land use performance undergoes abrupt shifts due to the transition from growth-centric to ecology-focused development, traditional evaluation methods often overlook the catastrophe characteristics of urban complex functions in the process of system evolution, resulting in land governance strategies being unable to adjust rapidly to adapt to regional transformation. To address this limitation, this study develops an ecological priority-oriented performance evaluation system for land use Production–Living–Ecological (PLE) Functions and introduces the Entropy–Catastrophe Progression model to conduct comprehensive measurement and obstacle diagnosis of land use PLE function performance in the Yangtze River Economic Belt of Hubei Province, a typical region, thereby proposing differentiated control strategies. The results show the following: (1) The Entropy–Catastrophe Progression Model can accurately measure the spatiotemporal evolution of land use PLE function performance during the development transition period. (2) The average value of land use PLE function performance presents a fluctuating upward trend, increasing from 0.812 (Poor level) in 2014 to 0.924 (Good level) in 2023. (3) Significant spatial disparities are observed, exhibiting a gradient decrease from provincial capital centers, provincial sub-centers, and ecological economic belts to metropolitan areas. (4) The key obstacles restricting performance improvement include a weak foundation for high-quality tertiary industries, insufficient intensity in environmental purification, and an inadequate supply of high-level living services. These can be addressed by dividing high-quality service optimization zones, green industry enhancement zones, and ecology–economy synergy zones, and establishing differentiated governance mechanisms to improve land use PLE function performance. This study provides theoretical guidance and empirical support for optimizing pathways for urban–rural land use and management.

Kohinur Akter, Monirul Islam, Md. Rakibul Hasan et al.

The study reveals the development and quality evaluation of biscuits that enriched with galactagogue effects for lactating mothers. Natural galactagogue mix was formulated using food ingredients like moringa leaf (10 %), moringa pod (40 %), black cumin seed (10 %), and cashew nuts (40 %). Composite flour of wheat and galactagogue mix powder were blended ( %, w/w) at ratios of 100:0, 95:5, 90:10, 85:15, and 80:20, where 100:0 ratio refers to as control. Incorporation of galactagogue mix into wheat flour significantly (p < 0.05) increased protein, fat, fiber, and ash while decreased moisture content and carbohydrates than wheat flour. In addition, significant increases in water absorption capacity ( %), emulsion capacity %, and emulsion stability ( %) was observed, while oil absorption capacity ( %), foaming capacity ( %), foaming stability ( %), swelling capacity, and density of mix were significantly (p < 0.05) decreased. The thermal stability of the mix was higher than that of wheat flour, but lower than the composite flour. FTIR spectroscopy revealed the presence of lactogenic compounds in the mix, including saponins and phytoestrogens, which were partially retained in composite flour and biscuits. The biscuits were also analyzed for some physical properties, antioxidant activity, phenolic content, and sensory attributes. Biscuits fortified with composite flour significantly (p < 0.05) increased the amount of protein (9.01 % to 13.78 %), antioxidant activity (1.77 % to 2.65 %), and total phenol content (4.74 mg GAE/g to 9.92 mg GAE/g). Sensory evaluation indicated that biscuits with 10 % galactagogue mix were most acceptable. This study indicated the potential of developing functional foods for lactating mothers.

Nasim Katebi, Mohammad Ahmad, Mohsen Motie-Shirazi et al.

Perinatal complications, defined as conditions that arise during pregnancy, childbirth, and the immediate postpartum period, represent a significant burden on maternal and neonatal health worldwide. Factors contributing to these disparities include limited access to quality healthcare, socioeconomic inequalities, and variations in healthcare infrastructure. Addressing these issues is crucial for improving health outcomes for mothers and newborns, particularly in underserved communities. To mitigate these challenges, we have developed an AI-enabled smartphone application designed to provide decision support at the point-of-care. This tool aims to enhance health monitoring during pregnancy by leveraging machine learning (ML) techniques. The intended use of this application is to assist midwives during routine home visits by offering real-time analysis and providing feedback based on collected data. The application integrates TensorFlow Lite (TFLite) and other Python-based algorithms within a Kotlin framework to process data in real-time. It is designed for use in low-resource settings, where traditional healthcare infrastructure may be lacking. The intended patient population includes pregnant women and new mothers in underserved areas and the developed system was piloted in rural Guatemala. This ML-based solution addresses the critical need for accessible and quality perinatal care by empowering healthcare providers with decision support tools to improve maternal and neonatal health outcomes.

Lorelay Mendoza Grijalva, Allisa G. Hastie, Meili Gong et al.

Safe sanitation access is commonly believed to be ubiquitous in high-income countries; however, researchers and community advocates have exposed a glaring lack of access for many low-income communities and communities of color across the U.S. While this disparity has been identified and quantified at a high level, local and household-level implications of sanitation failures remain ill-defined. We develop a set of user-based and environmental measures to assess the performance of centralized wastewater systems, septic systems, and straight-piped systems in Lowndes County, Alabama. We combine qualitative, survey, and environmental sampled data to holistically compare user experiences across infrastructure types. This integrated approach reveals new routes of exposure to wastewater through informal household maintenance and system backups and provides evidence for the spread of wastewater-like contamination throughout the community. This work elucidates the severity of sanitation failures in one rural U.S. community and provides a framework to assess sanitation quality in other contexts with limited sanitation access in high-income countries.

Somnath Buriuly, Leena Vachhani, Sivapragasam Ravitharan et al.

The Rural Postman Problem with Temporal Unavailability (RPP-TU) is a variant of the Rural Postman Problem (RPP) specified for multi-agent planning over directed graphs with temporal constraints. These temporal constraints represent the unavailable time intervals for each arc during which agents cannot traverse the arc. Such arc unavailability scenarios occur in routing and scheduling of the instrumented wagons for inspection of railway tracks without disturbing the train schedules, i.e. the scheduled trains prohibit access to the signal blocks (sections of railway track separated by signals) for some finite interval of time. A three-index formulation for the RPP-TU is adopted from the literature. The three-index formulation has binary variables for describing the route information of the agents, and continuous non-negative variables to describe the schedules at pre-defined locations. A relaxation of the three-index formulation for RPP-TRU, referred to as Cascaded Graph Formulation (CGF), is investigated in this work. The CGF has attributes that simplify the polyhedral study of time-dependent arc routing problems like RPP-TRU. A novel branch-and-cut algorithm is proposed to solve the RPP-TU, where branching is performed over the service arcs. A family of facet-defining inequalities, derived from the polyhedral study, is used as cutting planes in the proposed branch-and-cut algorithm to reduce the computation time by up to $48\%$. Finally, an application of this work is showcased using a simulation case study of a railway inspection scheduling problem based on Kurla-Vashi-Thane suburban network in Mumbai, India. An improvement of $93\%$ is observed when compared to a Benders' decomposition based MILP solver from the literature.

Md Bokhtiar Al Zami, Shaba Shaon, Vu Khanh Quy et al.

Industrial networks are undergoing rapid transformation driven by the convergence of emerging technologies that are revolutionizing conventional workflows, enhancing operational efficiency, and fundamentally redefining the industrial landscape across diverse sectors. Amidst this revolution, Digital Twin (DT) emerges as a transformative innovation that seamlessly integrates real-world systems with their virtual counterparts, bridging the physical and digital realms. In this article, we present a comprehensive survey of the emerging DT-enabled services and applications across industries, beginning with an overview of DT fundamentals and its components to a discussion of key enabling technologies for DT. Different from literature works, we investigate and analyze the capabilities of DT across a wide range of industrial services, including data sharing, data offloading, integrated sensing and communication, content caching, resource allocation, wireless networking, and metaverse. In particular, we present an in-depth technical discussion of the roles of DT in industrial applications across various domains, including manufacturing, healthcare, transportation, energy, agriculture, space, oil and gas, as well as robotics. Throughout the technical analysis, we delve into real-time data communications between physical and virtual platforms to enable industrial DT networking. Subsequently, we extensively explore and analyze a wide range of major privacy and security issues in DT-based industry. Taxonomy tables and the key research findings from the survey are also given, emphasizing important insights into the significance of DT in industries. Finally, we point out future research directions to spur further research in this promising area.

Xiao Wang, Yutong Wang, Jing Yang et al.

As the concept of Industries 5.0 develops, industrial metaverses are expected to operate in parallel with the actual industrial processes to offer ``Human-Centric" Safe, Secure, Sustainable, Sensitive, Service, and Smartness ``6S" manufacturing solutions. Industrial metaverses not only visualize the process of productivity in a dynamic and evolutional way, but also provide an immersive laboratory experimental environment for optimizing and remodeling the process. Besides, the customized user needs that are hidden in social media data can be discovered by social computing technologies, which introduces an input channel for building the whole social manufacturing process including industrial metaverses. This makes the fusion of multi-source data cross Cyber-Physical-Social Systems (CPSS) the foundational and key challenge. This work firstly proposes a multi-source-data-fusion-driven operational architecture for industrial metaverses on the basis of conducting a comprehensive literature review on the state-of-the-art multi-source data fusion methods. The advantages and disadvantages of each type of method are analyzed by considering the fusion mechanisms and application scenarios. Especially, we combine the strengths of deep learning and knowledge graphs in scalability and parallel computation to enable our proposed framework the ability of prescriptive optimization and evolution. This integration can address the shortcomings of deep learning in terms of explainability and fact fabrication, as well as overcoming the incompleteness and the challenges of construction and maintenance inherent in knowledge graphs. The effectiveness of the proposed architecture is validated through a parallel weaving case study. In the end, we discuss the challenges and future directions of multi-source data fusion cross CPSS for industrial metaverses and social manufacturing in Industries 5.0.

Neave O'Clery, Juan Chaparro, Andres Gomez-Lievano et al.

What drives formal employment creation in developing cities? We find that larger cities, home to an abundant set of complex industries, employ a larger share of their working age population in formal jobs. We propose a hypothesis to explain this pattern, arguing that it is the organised nature of formal firms, whereby workers with complementary skills are coordinated in teams, that enables larger cities to create more formal employment. From this perspective, the growth of formal employment is dependent on the ability of a city to build on existing skills to enter new complex industries. To test our hypothesis, we construct a variable which captures the skill-proximity of cities' current industrial base to new complex industries, termed 'complexity potential'. Our main result is that complexity potential is robustly associated with subsequent growth of the formal employment rate in Colombian cities.

Simon Kloker, Alex Cedric Luyima, Matthew Bazanya

This paper introduces WASHtsApp, a WhatsApp-based chatbot designed to educate rural African communities on clean water access, sanitation, and hygiene (WASH) principles. WASHtsApp leverages a Retrieval-Augmented Generation (RAG) approach to address the limitations of previous approaches with limited reach or missing contextualization. The paper details the development process, employing Design Science Research Methodology. The evaluation consisted of two phases: content validation by four WASH experts and community validation by potential users. Content validation confirmed WASHtsApp's ability to provide accurate and relevant WASH-related information. Community validation indicated high user acceptance and perceived usefulness of the chatbot. The paper concludes by discussing the potential for further development, including incorporating local languages and user data analysis for targeted interventions. It also proposes future research cycles focused on wider deployment and leveraging user data for educational purposes.

Carolina Allendes-Muñoz, Marcelo Miranda-Cavallieri, Camilo Matus-Olivares et al.

Wetland salt works with handcrafted production are scarce in Chile. This activity is the base of the maintenance of some local communities’ economy, establishing small rural groups and helping in the conservation of the cultural traditions. These wetlands provide an important habitat for southern hemisphere swan species. Salt workers point out that among the most laborious tasks to keep the salt pans running, is the removal of macrophytes from their production systems. We evaluated the behaviour of two threatened swan species in these wetlands to check if they provide an ecosystem service to salt workers. Our results showed that the main behaviour recorded was the activity of feeding, where the swans spend more than 45% of their time. Considering that each individual can ingest approx. 12-16 kg of food daily, it is shown that swans could provide an ecosystem service through the removal of macrophytes. There were no significant differences in behaviors between species, but between sampling sites, in behaviors such as self-maintenance, which was related to the degree of disturbance of these. Our findings are novelty evidence of the role of swans as ecosystem services providers for salt workers. These results highlight that the maintenance of traditional industries could be a win-win strategy for bird conservation.

Manikandan Dhayalan, Sheikdawood Parveen, Sathiyapriya Thirumalaisamy et al.

Herbal plants have been used, in light of their responsiveness and wide availability, for the construction of a pioneering nanomaterial. In this study, a colloidal suspension of gold nanoparticles (GNPs) was synthesized from an extract of Madhuca longifolia (ML) using chloroauric acid.  For biomedical applications, Madhuca longifolia (ML) was used as a bioreductant as well as a capping agent The formed ML-GNPs were analyzed using different analytical techniques, antioxidant assays, and thiazolyl blue formazan assay against A549 cell lines to evaluate clinical relevance. They were further evaluated for their influence on antimicrobial activity using a disc diffusion test against two different microorganisms, Proteus vulgaris and Micrococcus luteus. The ML-GNPs produced had good antioxidant, antibacterial, and anticancer activities. The conformation of the XRD spectra with prominent characteristic planes was indexed to the face-centered cubic (fcc)-structured GNPs. Surface morphology analysis was used to determine the particle size of the GNPs. Fourier transform infrared spectra of the samples were used to determine the analogs for strong H bonding. The MIC values of biogenic GNPs against both strains of Proteus vulgaris and Micrococcus luteus was calculated as 0.29 and 0.96 g/mL, respectively, and triclosan was considered as 0.4 and 2 g/mL, respectively. The findings of this study will be beneficial for future studies of the therapeutic potential of ML-GNPs. Actively, ML-GNPs can be a capable material for formulating nanomedicines after subsequent clinical experiments.

Szilárd Erhart, Kornél Erhart

Abstract We present a methodology to develop the integrated toxicity and climate change risk assessment of Europe based facilities, industries and regions. There is an increasingly important need for large scale sustainability measurement solutions for company reporting with high granularity. In this paper we measure key aspects of Sustainable Development Goals in terms of human, cancer and non-cancer toxicity, ecotoxicity together with global warming impact potentials from point source pollutant releases of more than 10,000 companies and their 33,000 facilities in Europe from 2001 to 2017, by using the European Pollutant Release and Transfer Register. For our assessment, we deploy a scientific consensus model, USEtox for characterizing human and ecotoxicological impacts of chemicals and the global warming potential values from the Intergovernmental Panel on Climate Change. We discuss water and air emissions of dozens of pollutants in urban, rural, coastal and inland areas. Companies in the electricity production sector are estimated to have the largest human toxicity impact potential (46% of total) and the largest global warming impact potential (50%), while companies in the sewerage sector have the largest ecotoxicity impact potential (50%). In the overall economy, the correlation between facilities’ global warming and toxicity impact potentials is positive, however, not very strong. Therefore, we argue that carbon footprint of industrial organizations can be only used as a climate change risk indicator, but not as an overall environmental performance indicator. We confirm impact potentials of major pollutants in previous research papers (Hg accounting for 76% of the total human toxicity and Zn accounting for 68% of total ecotoxicity), although we draw the attention to the limitations of USEtox in case of metals. From 2001 to 2017 total human toxicity dropped by 28%, although the downward trend reversed in 2016. Ecotoxicity and global warming impact potentials remained unchanged in the same period. Finally, we show that the European pollutant release monitoring data quality could be further improved, as only three quarters of the toxic releases are measured in the Member States of the European Union, and a high share of toxic pollutant releases are only estimated in some countries. Of the measured or calculated toxic releases, only one third is reported according to the most robust CEN/ISO standards and about one fifth according to the least preferred other methods, like engineering judgements.

Maria Afroz Toma, Md. Hasibur Rahman, Md. Saydar Rahman et al.

Natural pigments and colorants have seen a substantial increase in use over the last few decades due to their eco-friendly and safe properties. Currently, customer preferences for more natural products are driving the substitution of natural pigments for synthetic colorants. Filamentous fungi, particularly ascomycetous fungi (<i>Monascus</i>, <i>Fusarium</i>, <i>Penicillium</i>, and <i>Aspergillus</i>), have been shown to produce secondary metabolites containing a wide variety of pigments, including β-carotene, melanins, azaphilones, quinones, flavins, ankaflavin, monascin, anthraquinone, and naphthoquinone. These pigments produce a variety of colors and tints, including yellow, orange, red, green, purple, brown, and blue. Additionally, these pigments have a broad spectrum of pharmacological activities, including immunomodulatory, anticancer, antioxidant, antibacterial, and antiproliferative activities. This review provides an in-depth overview of fungi gathered from diverse sources and lists several probable fungi capable of producing a variety of color hues. The second section discusses how to classify coloring compounds according to their chemical structure, characteristics, biosynthetic processes, application, and present state. Once again, we investigate the possibility of employing fungal polyketide pigments as food coloring, as well as the toxicity and carcinogenicity of particular pigments. This review explores how advanced technologies such as metabolic engineering and nanotechnology can be employed to overcome obstacles associated with the manufacture of mycotoxin-free, food-grade fungal pigments.

Jay Lee, Hanqi Su

The recent emergence of large language models (LLMs) demonstrates the potential for artificial general intelligence, revealing new opportunities in Industry 4.0 and smart manufacturing. However, a notable gap exists in applying these LLMs in industry, primarily due to their training on general knowledge rather than domain-specific knowledge. Such specialized domain knowledge is vital for effectively addressing the complex needs of industrial applications. To bridge this gap, this paper proposes a unified industrial large knowledge model (ILKM) framework, emphasizing its potential to revolutionize future industries. In addition, ILKMs and LLMs are compared from eight perspectives. Finally, the "6S Principle" is proposed as the guideline for ILKM development, and several potential opportunities are highlighted for ILKM deployment in Industry 4.0 and smart manufacturing.

Maksim Papenkov, Chris Meredith, Claire Noel et al.

Accurate industry classification is a critical tool for many asset management applications. While the current industry gold-standard GICS (Global Industry Classification Standard) has proven to be reliable and robust in many settings, it has limitations that cannot be ignored. Fundamentally, GICS is a single-industry model, in which every firm is assigned to exactly one group - regardless of how diversified that firm may be. This approach breaks down for large conglomerates like Amazon, which have risk exposure spread out across multiple sectors. We attempt to overcome these limitations by developing MIS (Multi-Industry Simplex), a probabilistic model that can flexibly assign a firm to as many industries as can be supported by the data. In particular, we utilize topic modeling, an natural language processing approach that utilizes business descriptions to extract and identify corresponding industries. Each identified industry comes with a relevance probability, allowing for high interpretability and easy auditing, circumventing the black-box nature of alternative machine learning approaches. We describe this model in detail and provide two use-cases that are relevant to asset management - thematic portfolios and nearest neighbor identification. While our approach has limitations of its own, we demonstrate the viability of probabilistic industry classification and hope to inspire future research in this field.

R. Carmona-Cabezas, J. Gomez-Gomez, A. B. Ariza-Villaverde et al.

Tropospheric ozone (O3) time series have been converted into complex networks through the recent so-called Visibility Graph (VG), using the data from air quality stations located in the western part of Andalusia (Spain). The aim is to apply this novel method to differentiate the behavior between rural and urban regions when it comes to the ozone dynamics. To do so, some centrality parameters of the resulting complex networks have been investigated: the degree, betweenness and shortest path. Some of them are expected to corroborate previous works in order to support the use of this technique; while others to supply new information. Results coincide when describing the difference that tropospheric ozone exhibits seasonally and geographically. It is seen that ozone behavior is fractal, in accordance to previous works. Also, it has been demonstrated that this methodology is able to characterize the divergence encountered between measurements in urban environments and countryside. In addition to that, the promising outcomes of this technique support the use of complex networks for the study of air pollutants dynamics. Particularly, new nuances are offered such as the identification and description of singularities in the signal.

M. Gislason, L. Galway, Chris G Buse et al.

ABSTRACT This paper explores how climate change communication is understood and enacted in Canada’s Provincial North (CPN), with a focus on the role that local climate champions play in regions characterized by rurality, remoteness, and a high degree of reliance on natural resource industries. Drawing from 24 in-depth interviews with individuals increasing local attention to climate in Northern British Columbia and Ontario, this research identifies communication challenges and opportunities arising in these contexts. Existing literature inadequately addresses the challenges of advancing climate change initiatives in rural and remote communities. Confirming and extending existing research on place-based communication, CPN climate champions underscored that messages must be place-based, community-informed, reflect local realities, and address the role of industry in regional economies. This paper offers an important set of insights that is relevant to climate change communication in other rural and remote settings in high-income countries.

Brooke P. A. Kennedy, Nick Boyle, Peter J. S. Fleming et al.

The One Welfare concept is proposed to guide humans in the ethical treatment of non-human animals, each other and the environment. One Welfare was conceptualized for veterinarians but could be a foundational concept through which to promote the ethical treatment of animals that are outside of direct human care and responsibility. However, wild-living animals raise additional ethical conundrums because of their multifarious values and roles, and relationships that humans have with them. At an open facilitated forum, the 2018 Robert Dixon Memorial Animal Welfare Symposium, a panel of five experts from different fields shared their perspectives on “loving and hating animals in the wild” and responded to unscripted questions from the audience. The Symposium’s objectives were to elucidate views on the ethical treatment of the native and invasive animals of Australia and to identify some of the resultant dilemmas facing conservationists, educators, veterinarians and society. Here, we document the presented views and case studies and synthesize common themes in a One Welfare framework. Additionally, we identified points of contention that can guide further discourse. With this guide in place, the identification and discussion of those disparate views was a first step toward practical resolutions on how to manage wild-living Australian fauna ethically. We concluded that there was great utility in the One Welfare approach for any discourse about wild animal welfare. It requires attention to each element of the triple bottom line and ensures that advocacy for one party does not vanquish the voices from other sectors. We argue that, by facilitating a focus on the ecology in the context of wild animal issues, One Welfare is more useful in this context than the veterinary context for which it was originally developed.

Min LI, Qinhao LIU, Guan ZHAO et al.

With the continuous deepening of rural modernization, modern rural diversified industries such as rural planting, animal husbandry, and agricultural product processing industries are booming. Therefore，on the basis of rural diversified industries，this paper proposes a planning model of rural multi-energy system that includes rural diversified industries，waste disposal and renewable energy power generation. First，based on the study of waste treatment and energy output characteristics of the rural animal husbandry industry manure gas production facilities and waste pyrolysis gasification power generation facilities, and the electricity，gas，and thermal energy supply models was established for rural waste treatment facilities；second，study of the rural multi-energy and the demand characteristics of multiple types of energy loads such as electricity，heat and gas in the multi-industrial complex，and considering the synergy between the multi-industry, an energy demand model for the rural multi-energy complex was established. Finally，a large-scale village in the north was selected to simulate and verify the proposed method. The results show that the method in this paper has realized the full utilization of rural resources and the synergy of rural multiple industries，and improved economic benefits.

Albert Tchey Agbenyegah, Luther-King Junior Zogli , Bongani Dlamini et al.

The current study illustrates the influence of restaurant ambient conditions on customers satisfaction in the tourism and hospitality industries through cluster and simple random techniques. The primary objective was to ascertain the relationship between the restaurant ambient conditions and customer satisfaction in rural restaurants. A closedended questionnaires with varying options were designed to collect primary data from randomly selected customers from 11 restaurants from the study settings. Primary data was analysed via the SPSS software based on statistical tools of regression analysis to determine the relationship between the dependent and independent variables. Final outcomes indicated significant relationship between the dependent and independent variables. The restaurant ambient conditions have significant relationship with customer satisfaction. Based on the findings, this study recommends that owner-managers of restaurants in rural areas need to improve the bulk of the ambient situations to attract more customers. This empirical study contributes to existing literature on the tourism and hospitality industry with specific reference to the restaurant businesses.