Search Results (33)

This article studies the chain’s service area size in biomethane recovery from municipal organic waste, with a model created to study the energy generated, which may be applied to determine the optimal allocation of waste and location of the digester. This paper critically addresses the transportation energy losses, which are related to the transport distance and to the technology used for transportation. The collection and transportation of organic waste to the transfer station are studied, with us first considering the use of a 10-ton-payload truck, and the transportation to the digester then studied considering the use of trucks with different payloads: 9, 18 and 27 tons. The results show that depending on the availability of organic waste and the distances to travel, a positive impact may be derived from having many digesters in the area rather than the most common scenario today of a single digester. The results also demonstrate that in less populated regions, the energy differences created by the location of the digester are less significant than those in more populated regions. This paper presents a real-life case study in the province of Québec, Canada. However, this approach can be used in other territories and provides insights for urban planners or policymakers considering the sustainability of waste management in their territory. The novelty of this paper is the study of energy recovery based on the location of the digester and the availability of organic waste in the region. When using only one digestor in the municipality, the total energy losses in the transportation between a transfer station and the digester are between 9.8 and 13%, but when using two digesters in the municipality, the total loss from transportation is reduced to 6.6%. Full article

Peanut is Kenya’s second most important legume after beans, primarily grown in the Nyanza and Western regions. This study maps the peanut value chain in Kenya, aiming to identify key actors, quantify costs and value addition, and outline constraints and opportunities, with a view to upgrading the chain. A cross-sectional survey was conducted among value chain actors in Karachuonyo and Nyakach sub-counties, complemented by secondary data sources. Descriptive statistics were used to analyze socio-economic characteristics, production volumes, pricing, demand trends, and policy-related factors. The findings indicate a predominance of female farmers (68%) in peanut production, though few use improved technologies; only 26% were aware of improved seed varieties, and just 1.5% reported using them. Fertilizer usage was absent, attributed to high costs, soil conditions, and limited knowledge. The wholesale and processing segments are male-dominated, largely due to capital intensity and travel requirements, while female traders dominate the retail sector. Strengths Weaknesses Opportunity and Threats (SWOT) analysis highlighted the significant potential of favorable production ecologies, processing options, and robust demand in local and international markets. Key constraints identified include limited seed availability, high fertilizer costs, pest issues, and declining soil fertility. Policy implications include increasing access to affordable inputs, promoting gender-inclusive programs, investing in agricultural research and infrastructure, supporting sustainable farming practices, and fostering public-private partnerships to expand processing and market access. Full article

With the vast majority of global trade volume and value reliant on maritime transport, accurate prediction of vessel estimated time of arrival (ETA) is crucial for optimizing supply chain efficiency and managing logistical complexities in port operations. This review paper systematically examines the current state of research and practices in the field of vessel ETA prediction, highlighting significant trends, methodologies, and technologies. It explores various approaches, including classical methods, machine learning and deep learning algorithms, and hybrid methods, developed to enhance the accuracy and reliability of vessel travel time and arrival time predictions. Additionally, this paper categorizes key influencing factors and metrics, and identifies open issues and challenges within current prediction models. Concluding with proposed future research directions aimed at addressing the identified gaps and leveraging technological advancements, this review emphasizes the importance of fostering innovation in maritime ETA prediction systems, particularly within the framework of Intelligent Transportation Systems (ITSs) and maritime logistics. By applying a systematic literature review (SLR) methodology and conducting an in-depth evaluation, the results provide a comprehensive overview of vessel ETA prediction for researchers, practitioners, and policy makers involved in maritime transport and logistics, and offer insights into the potential for improved efficiency, safety, and environmental sustainability in waterway networks. Full article

The hospitality business model has undergone profound changes influenced by successive waves of technological advances and platforms. This paper explores how different waves of technologies and platforms are shaping the evolution of the hospitality business model. Employing a systematic literature review, this research analyzes how platform innovation has driven significant shifts in the industry. The analysis yielded four key findings. Firstly, the incorporation of digital technologies resulted in a radical transformation of conventional business models, prompting substantial alterations in marketing strategies, distribution processes, and consumer behavior patterns. Secondly, the industry has undergone five significant technological revolutions, evolving from steam-powered transportation to the integration of artificial intelligence (AI) and the Internet of Things (IoT), thereby driving a shift towards innovation-centric business models. Thirdly, the advent of digital platforms, most notably online travel agencies (OTAs), posed a challenge to traditional hospitality models by introducing personalized experiences and disrupting established market norms. While digital platforms offer advantages such as enhanced convenience and customization, they also present challenges, including intensified competition and declining profit margins. Nonetheless, technological advancements such as AI, virtual reality (VR), and augmented reality (AR) present a potential avenue for redefining value propositions and enhancing customer experiences. Fourth, the future of the hospitality business model is poised for further disruption, influenced by the emergence of new virtual platforms and services. This could potentially result in a reshaping of the industry’s value chain and value proposition. Full article

The paper highlights the potential of cross-docking to reduce storage time and costs. The study addresses evolving market demands that push logistics providers to adopt new technologies for operational efficiency, emphasizing the often-overlooked importance of optimizing cross-docking layouts. The research, conducted in two phases, first analyzed the current warehouse layout (Variant I) to identify inefficiencies and then designed a new layout (Variant II) that was simulated using FlexSim 2022 software. The results showed significant improvements with the new layout, including a 35% increase in deliveries and a 3.23% reduction in forklift travel distances, leading to lower operational costs. Even minor adjustments in the warehouse design proved to enhance logistics efficiency, particularly during peak demand periods like holidays. The study demonstrates how FlexSim software can be applied in cold chain logistics to optimize warehouse operations, underscoring the benefits of cross-docking for cost-effective logistics management. Full article

For the sake of realizing the safety detection of natural gas and petroleum pipeline welds, this paper designs a ferromagnetic pipeline weld magnetic flux leakage detector based on the calculation of the magnetic circuit of the detection probe, with the magnetization direction perpendicular to the traveling direction. The traditional pipeline magnetic flux leakage detection device uses a detection system mode in which the magnetization direction is parallel to the direction of travel. However, due to the structural characteristics of the weld, the traditional detection system mode is not applicable. Since the weld magnetic flux leakage detector needs to travel along the direction of the weld, the detector designed in this paper rotates the magnetizer 90 degrees along the direction of the weld seam so that the magnetization direction is perpendicular to the direction of travel, breaking through the technical barrier that make traditional magnetic flux leakage detection devices unsuitable for weld detection. The detection device includes a magnetizing structure, a data sampling device, and a driving and traveling device. The magnetic flux leakage signal collected by the detector is converted into a digital image in the form of a grayscale matrix. Using mathematical morphology and chain code algorithms in image processing technology, a pipeline weld defect inversion software system is developed, and a preliminary quantitative analysis of pipeline weld defects is achieved. The application of this technology enables the inspection and protection of oil and gas pipeline welds throughout their life cycle, broadens the scope of existing inspection objects, and is of great safety significance for ensuring national public security. Full article

Background: Business continuity entails the potential negative consequences of uncertainty on a firm’s ability to achieve strategic objectives. The COVID-19 pandemic significantly impacted business continuity due to lockdowns, travel restrictions, and social distancing measures. Consequently, firms adopted specific supply chain (SC) practices to effectively navigate this global crisis. Methods: This research adopted a stochastic approach based on Bayesian Networks to evaluate the implications of business continuity on firms’ decisions to embrace SC practices, focusing on omnichannel strategies, SC coordination, and technologies such as artificial intelligence systems, big data and machine learning, and mobile applications. Results: Our findings revealed that firms facing disruption in a single performance area can apply specific strategies to maintain resilience. However, multiple areas of underperformance necessitate a varied approach. Conclusions: According to our empirical analysis, omnichannel strategies are critical when disruptions simultaneously impact quality, inventory, sales, and ROI, particularly during major disruptions such as the COVID-19 pandemic. AI and big data become vital when multiple risks coalesce, enhancing areas such as customer service and supply chain visibility. Moreover, supply chain coordination and mobile app adoption are effective against individual performance risks, proving crucial in mitigating disruption impacts across various business aspects. These findings help policy-makers and business owners to have a better understanding of how business continuity based on performance resistance to disruptions pushes companies to adopt different practices including new technologies and supply chain coordination. Accordingly, they can use the outputs of this study to devise strategies for improving resilience considering their supply chain vulnerabilities. Full article

Conveying and baling are two important links in the mechanized harvesting of ramie, in the face of ramie cutting and baling harvesting technology research gaps, low stalk conveying rate, high breaking rate and other problems. In this paper, according to the technical requirements of ramie harvesting, we designed a conveying and baling device, the hand-held ramie cutter. First, the key mechanism of the conveying and baling device of the equipment was designed. Then, we analyzed the location of stem clogging and the reasons for the breaking problem during the conveying and baling process. The field harvesting experiments were carried out according to the principles of Box–Behnken experimental design. Taking the machine travelling speed, conveying speed and ramie raking frequency as the test factors and using the Design-Expert V8.0.6.1 to process the data, we established a regression model for each experimental factor on the conveying rate and breaking rate. The order of influence of several factors on the breaking rate is: X₂ > X₁ > X₃; and the effects of the three factors on the conveying rate were X₃ > X₂ > X₁. Through response surface analysis (RSA), the effects of the factors on the indicators were explained, as was the impact of the factors on the indicators. Finally, the parameter optimization was carried out with the delivery rate as the core index. The best combination of motion parameters was obtained as follows: the travelling speed was 0.37 m/s, the chain conveying speed was 1.1 m/s, and the raking frequency was 144 times/min. With the combination of parameters under the field test verification, the results show that compared with the original work quality, the stalk delivery rate increased from 85.2% to 93% (an increase of 7.8%), the stalk breaking rate fell from 31.1% to 20.4% (a decrease of 10.7%). The performance of ramie harvesting and baling was greatly improved, and we achieved relatively satisfactory results. Full article

This paper surveys urban courier routing, pointing out the learning process of the generalized travel cost enhanced by using innovations related to the introduction of emerging information and communication technologies (ICTs, i.e., the internet of things, big data, block chain and artificial intelligence), considering a smart city. Couriers, when planning in advance or choosing the routes in real time for delivering to citizens as well as to business users (including retailers), need to consider both the driving and walking routes (i.e., from the delivery bay to the customers) to optimize their activities. A two-layer literature optimization model is recalled, and the main scientific people-centered challenges that need to be addressed under the light of emerging ICTs are identified and explored, which are the learning process of routing attributes, as well as the opportunity to book on-street delivery bays in advance or in real time. Then, after a literature review on modeling courier activities, a unitary formulation is presented that combines old and real-time network data. In addition, integration with new telematics solutions (i.e., delivery bay booking) is pointed out. Finally, discussions on innovations and cost optimization are presented. Full article

(1) Objective: To explore the neurobiological effects of terahertz (THz) radiation on zebrafish larvae using calcium (Ca²⁺) imaging technology. (2) Methods: Zebrafish larvae at 7 days post fertilization (dpf) were exposed to THz radiation for 10 or 20 min; the frequency was 2.52 THz and the amplitude 50 mW/cm². The behavioral experiments, neural Ca²⁺ imaging, and quantitative polymerase chain reaction (qPCR) of the dopamine-related genes were conducted following the irradiation. (3) Results: Compared with the control group, the behavioral experiments demonstrated that THz radiation significantly increased the distance travelled and speed of zebrafish larvae. In addition, the maximum acceleration and motion frequency were elevated in the 20 min radiation group. The neural Ca²⁺ imaging results indicated a substantial increase in zebrafish neuronal activity. qPCR experiments revealed a significant upregulation of dopamine-related genes, such as drd2b, drd4a, slc6a3 and th. (4) Conclusion: THz radiation (2.52 THz, 50 mW/cm², 20 min) upregulated dopamine-related genes and significantly enhanced neuronal excitability, and the neurobiological effect of THz radiation can be visualized using neural Ca²⁺ imaging in vivo. Full article

The travel-goods industry is an essential part of the larger travel and tourism sector, but it allegedly creates significant environmental impacts due to resource and energy consumption. This study investigates the potential of the product-service system (PSS) models to promote the transition to a sustainable travel industry in the future. It explores the drivers and barriers to PSS adoption within the luggage industry from a theoretical perspective and identifies opportunities for value creation using both consumer and luggage industry viewpoints. Four hypothetical PSS models are developed to highlight different pathways to PSS adoption, underpinned with empirical data collected via a consumer survey and semi-structured interviews with industry experts. Even though the analysis revealed shifting consumer attitudes towards servitisation concepts within the travel-goods market, at present, the widespread adoption of PSS is hindered by the fragmented nature of global supply chains and entrenched ownership values. Addressing supply chain issues in a way that empowers end-of-life systems to sustainably manage products beyond their functional obsolescence is critical. In parallel, product-oriented PSS models are more likely to increase, driven by a burgeoning resale market and supported by digital technologies, which in turn can lead to greater prospects for use-oriented PSS adoption in the long-term that would eventually promote sustainability. Full article

The valorisation of biomass by synthesising a multi-biomass corridor can be an optimistic pathway to solving the growing waste management problem. However, the supply chain problem usually involves a massive number of variables, including the connectivity of the sink source and the selection of a technology pathway. In this work, a “Decomposition Approach” was utilised, wherein a P-graph was incorporated with a conventional mathematical model to reduce the number of variables. Although this type of approach is well established with respect to solving biomass supply chain problems, no previous works have comprehensively considered the effect of the maximum allowable travel distance (MATD) on a supply chain model. A case study in Peninsular Malaysia involving oil palm, paddy, and coconut biomass was conducted using the proposed approach. Moreover, a multiple linear regression (MLR) tool for formulating the cost-correlated function based on the best technology pathway obtained from a P-Graph was incorporated. As a result, the net profit of the biomass corridor was estimated to be USD 0.87 billion, with 1.45 × 10⁷ tonnes per year of biomass being sent to 39 processing hubs over a 20-year lifespan. Furthermore, a sensitivity analysis was also conducted to investigate the impact of several cost-related parameters on the net profit. Full article

Charging load mobility evaluation becomes one of the main concerns for charging services and power system stability due to the stochastic nature of electrical vehicles (EVs) and is critical for the robust scheduling of economic operations at different intervals. Therefore, the EV spatial–temporal approach for load mobility forecasting is presented in this article. Furthermore, the reliability indicators of large-scale EV distribution network penetration are analyzed. The Markov decision process (MDP) theory and Monte Carlo simulation are applied to efficiently forecast the charging load and stochastic path planning. A spatial–temporal model is established to robustly forecast the load demand, stochastic path planning, traffic conditions, and temperatures under different scenarios to evaluate the charging load mobility and EV drivers’ behavior. In addition, the distribution network performance indicators are explicitly evaluated. A Monte Carlo simulation is adopted to examine system stability considering various charging scenarios. Urban coupled traffic-distribution networks comprising 30-node transportation and 33-bus distribution networks are considered as a test case to illustrate the proposed study. The results analysis reveals that the proposed method can robustly estimate the charging load mobility. Furthermore, significant EV penetrations, weather, and traffic congestion further adversely affect the performance of the power system. Full article

In order to quickly dry the peanut pods and effectively reduce the mildew on peanut pods in rainy weather, this paper analyzed the research status of peanut digging and inverting technology in China and abroad, combined with the peanut two-stage harvesting mode. The orthogonal experiment was carried out by using the peanut digger-inverter to study the different forms of upright type, taking the rate of vines inverting, the rate of buried pods, and the rate of fallen pods as the evaluation indexes, and taking the traveling speed of the tractor A, the line speed of the conveyor chain B, and the line speed of the inverting roller C as the experimental factors. The results showed that, in the states of unpressed vines and pressed vines, the order of influence of the peanut digger-inverter on the evaluation indices was A > C > B. The optimal horizontal combination of unpressed vines was A₂C₃B₂, when the traveling speed of the tractor is 1.06 m/s, the line speed of the inverting roller is 2.12 m/s, and the line speed of the conveyor chain is 1.02 m/s; the rate of vines inverting was 71.07%, the rate of buried pods was 0.2%, and the rate of fallen pods was 0.22%. Under the condition of vines pressing, the best horizontal combination is A₂C₂B₂, when the travelling speed of the tractor is 1.01 m/s, the line speed of the inverting roller is 1.88 m/s, and the line speed of the conveyor chain is 1.02 m/s; the rate of vines inverting was 74.29%, the rate of buried pods was 0.14%, and the rate of fallen pods was 0.33%. The paired t-test was carried out by the peanut digger-inverter under the state of pressed and unpressed vines. There was little difference in the influence of each factor on the rate of fallen pods and the rate of buried pods, but there was a significant difference in the influence on the rate of vines inverting. The rate of inversion of vines under the state of pressed vines was higher than that under the state of unpressed vines. The research results will provide certain technical support for the late optimization of the peanut digger-inverter and create a hardware foundation for the intelligence and information harvesting of peanuts. Full article

In recent years, applications of Blockchain technology (BCT) have been progressing at a galloping rate in miscellaneous fields, such as finance, education, travel, healthcare, and insurance. However, BCT has gained much popularity in the construction industry, especially in developed nations worldwide, as it can solve real-world problems, including poor payments, inadequate cooperation and collaboration, inappropriate data sharing among stakeholders, and poor efficiency. The current research employs a bibliometric and systematic literature review (SLR) on utilizing BCT in the construction industry. Using co-occurrence and co-citation studies, network visualization and other methodologies concerning the Web of Science (WOS) database and the research contacts’ patterns were investigated in 482 academic papers. Notable publications, conferences, significant writers, nations, organizations, and funding organizations have been acknowledged. Our research reveals that the primary study topics are BCT in the construction industry, supply chain management, smart contracts, sustainability, building information modeling (BIM), the Internet of Things (IoT) and energy efficiency. Several possible fields for further research are mentioned, including the use of BCT in: (i) circular economy, (ii) risk management, (iii) smart villages, and (iv) infrastructure construction projects. Full article