Search Results (18)

In recent decades, the aviation industry has increasingly adopted composite materials for various aircraft components, due to their high strength-to-weight ratio and durability. To ensure the safety and reliability of these structures, Health and Usage Monitoring Systems (HUMSs) based on fiber optics (FO), particularly Fiber Bragg Grating (FBG) sensors, have been developed. However, both composite materials and optical fibers are susceptible to environmental factors such as moisture, in addition to the well-known effects of mechanical stress and thermal loads. Moisture absorption can lead to the degradation of mechanical properties, posing a risk to the structural integrity of aircraft components. This research aims to quantify and monitor the impact of moisture on composite materials. A new formulation of the Bragg equation is introduced, incorporating mechanical strain, thermal expansion, and hygroscopic swelling to accurately measure Bragg wavelength variations. Experimental validation was performed using both uncoated and polyimide-coated optical fibers subjected to controlled hygrothermal conditions in a climate chamber. The results demonstrate that uncoated fibers are insensitive to humidity, whereas coated fibers exhibit measurable wavelength shifts due to moisture absorption. The proposed model effectively predicts these shifts, with errors consistently below 2.6%. This approach is crucial for improving the performance and reliability of HUMSs in monitoring composite structures, ensuring long-term safety in extreme environmental conditions. Full article

Improving energy utilization efficiency is a crucial means to achieve energy conservation, emission reduction, and green development. At present, to establish a high-quality development framework and satisfy the growing need for a better life among all its people, China must steadfastly pursue the path of green development. Although China’s substantial economic scale and achievements in ecological civilization construction provide favorable conditions for green transformation, there remains a significant gap compared to developed countries in the application of green and clean technologies. Confronted with technological bottlenecks, leveraging emerging technologies such as industrial robots from the new round of scientific and technological revolutions to improve the green total factor energy efficiency (GTFEE) is of critical importance to China’s green development. This study explores the potential impact of industrial robots on enhancing China’s GTFEE. It begins by reviewing the current research landscape in this field, highlighting its shortcomings, and theorizing potential impact pathways of industrial robots. Subsequently, the paper analyzes data from 2010 to 2019 on the usage of industrial robots and GTFEE across 276 cities at the prefectural level or above in China. Through empirical regression models that incorporate control variables and interaction terms, the study investigates the specific impacts of industrial robots on energy efficiency and their mechanisms of action. The results indicate that industrial robots significantly enhance the GTFEE of Chinese cities, especially in the Northeastern region. Industrial robots notably improve the GTFEE in resource-based cities, old industrial bases, and low-carbon pilot cities. Additionally, robots indirectly boost GTFEE by increasing labor productivity. Enhanced levels of green innovation and environmental regulations also positively moderate the effectiveness of industrial robots in improving energy efficiency. The findings of this research can assist local government agencies in coordinating and implementing policies that are conducive to green development, making better use of industrial robots to serve the people, and are of significant importance for promoting the transformation of China’s economy and society towards high-quality development. Full article

This research explores the factors influencing bike-share usage durations in the Detroit Metropolitan Area over two years, focusing on spatial, temporal, and COVID-19-related variables. Using a fully parametric hazard-based duration model with random parameters, we address data heterogeneity and uncover how different conditions affect bike-share trips. Our findings reveal that (a) intense environmental factors such as high traffic stress, poor weather, and high COVID-19 risk levels are associated with shorter trip durations; (b) in contrast, supportive initiatives like memberships, an affordable USD 5 Access Pass, a free one-month pass during the pandemic, and the introduction of new stations are more likely to encourage longer rides; (c) variables like gym closures due to the pandemic, evening hours, and the addition of new stations, which were set as random variables in our model, exhibit both positive and negative relationships with ride durations. A key finding is the 20-minute mark in ride durations, which helps understand user behaviors and trip purposes. This insight aids urban planning by suggesting strategic bike station placements to enhance bike-share system efficiency and meet diverse community needs. Moreover, the pandemic and related policy responses have clearly impacted user behaviors, showing the necessity for adaptable urban transportation strategies in response to external crises. This study not only deepens our understanding of urban mobility dynamics but also underscores the effectiveness of adaptive strategies in promoting sustainable urban transportation. Full article

The global demand for energy is significantly impacted by the consumption patterns within the building sector. As such, the importance of energy simulation and prediction is growing exponentially. This research leverages Building Information Modelling (BIM) methodologies, creating a synergy between traditional software methods and algorithm-driven approaches for comprehensive energy analysis. The study also proposes a method for monitoring select energy management factors, a step that could potentially pave the way for the integration of digital twins in energy management systems. The research is grounded in a case study of a newly constructed educational building in New South Wales, Australia. The digital physical model of the building was created using Autodesk Revit, a conventional software for BIM methodology. EnergyPlus, facilitated by OpenStudio, was employed for the traditional software-based energy analysis. The energy analysis output was then used to develop preliminary algorithm models using regression strategies in Python. In this regression analysis, the temperature and relative humidity of each energy unit were used as independent variables, with their energy consumption being the dependent variable. The sigmoid algorithm model, known for its accuracy and interpretability, was employed for advanced energy simulation. This was combined with sensor data for real-time energy prediction. A basic digital twin (DT) example was created to simulate the dynamic control of air conditioning and lighting, showcasing the adaptability and effectiveness of the system. The study also explores the potential of machine learning, specifically reinforcement learning, in optimizing energy management in response to environmental changes and usage conditions. Despite the current limitations, the study identifies potential future research directions. These include enhancing model accuracy and developing complex algorithms to boost energy efficiency and reduce costs. Full article

The goal of increasing fuel efficiency and decreasing greenhouse gas (GHG) emissions has increased interest in the application of renewable energy sources and the usage of new technologies in the maritime industry. In order to implement the most suitable source, factors such as voyage duration, storage availability, and the condition of existing vessels as well as those that are still under construction should be taken into account. Propeller optimization is proposed as a long-term solution. This paper investigates the environmental aspects of propeller optimization, focusing on its potential to reduce ship vibrations fuel consumption, and, therefore, the ship’s carbon footprint. The case study presents propeller optimization on a Ro-Ro passenger ship. The data collected during sea trials before and after propeller optimization will be compared. Expected fuel oil consumption will be correlated to the CO₂ emission reduction. Besides propeller optimization, the paper performs a SWOT (strengths, weaknesses, opportunities, threats) analysis comparing it with solar and wind power applications on ships. Full article

The development of Xiongan New Area in Hebei Province, China, as a significant national choice, has considerable strategic significance for the integrated growth of Beijing, Tianjin, and Hebei. This paper proposes a cloud model for the suitability evaluation of the construction of Xiongan New Area based on entropy weight analysis, taking into account the geological conditions, groundwater environment, environmental geological problems, and other factors of the suitability of image city development. According to the research, the suitability evaluation findings for the project building employing the cloud model are in strong accord with those of the traditional model and have some application potential. The evaluation’s findings indicate that the project construction in Xiongan New Area is acceptable, with suitable and relatively suitable sites making up 81.4% of the total area and excellent circumstances for project development, construction, and usage. This study offers helpful direction for Xiongan New Area’s urban land-space design and serves as a useful point of comparison for studies looking at the viability of other deep Quaternary Plain region engineering buildings. Full article

Antibiotic usage and resistance are major health concerns. Antibiotic resistance occurs when bacteria evolve to resist the effects of antibiotics, making it impossible to treat infections. The overuse and misuse of antibiotics are the main contributing factors, while environmental stress (such as heavy metals accumulation), unhygienic conditions, illiteracy, and unawareness also contribute to antibiotic resistance. The slow and costly development of new antibiotics has lagged behind the emergence of antibiotic-resistant bacteria, and the overuse of antibiotics leads to negative consequences. The current study used different literature resources to generate an opinion and find a possible solution to antibiotic barriers. Different scientific approaches have been reported to overcome antibiotic resistance. The most useful approach among these is nanotechnology. Nanoparticles can be engineered to disrupt bacterial cell walls or membranes, effectively eliminating resistant strains. Additionally, nanoscale devices enable the real-time monitoring of bacterial populations, allowing for the early detection of resistance emergence. Nanotechnology, along with evolutionary theory offers promising avenues in combating antibiotic resistance. Evolutionary theory helps us understand the mechanisms by which bacteria develop resistance, allowing us to anticipate and counteract their adaptive strategies. By studying the selective pressures that drive resistance, we can therefore design more effective interventions or traps. The synergy between the evolutionary theory and nanotechnology presents a powerful approach to combat antibiotic resistance, offering new avenues for the development of effective treatments and the preservation of our antibiotic arsenal. Full article

Transporting materials and mine staff is a vital link necessary to the production process in underground mines. Deteriorating climatic conditions, mainly due to the increasingly deep mining and the usage of machines, force us to look for solutions to improve the underground mine environmental situation. Another essential factor responsible for deteriorating working conditions is harmful substances and exhaust fumes emitted from diesel engines. Supplying the workplaces with air quantity exceeding requirements such as the minimum velocity of air movement or gas and climatic conditions will allow for maintaining the gas concentration at the appropriate level. One possible way to solve the problems mentioned above is to replace suspended monorails powered by internal combustion engines with new solutions of electrically battery-powered monorails. Electric monorails are not yet widely used in mines; nevertheless, they have many advantages. This article analyzes the exhaust gas parameters from monorail locomotives operating in a hard coal mine and determines the required airflow to maintain permissible concentrations of harmful gases. It also focuses on a comparative analysis of climatic conditions in the development heading, considering the roadway’s functioning with and without using diesel or electric monorail. The study consists of the methodology for predicting climate conditions. Based on the performed analysis, it was shown that using electric monorails could significantly improve working conditions. Full article

The current research aimed to solve the environmental pollution of mature coconut water by Lipomyces starkeyi and provide a study of its high value utilization. The innovation firstly investigated the rheological properties and interface behavior of a crude exopolysaccharide and provided a technical support for its application in food. A response surface methodology was performed to ameliorate the fermentation factors of the new exopolysaccharide with mature coconut water as a substrate, and the consequences suggested that the maximum yield was 7.76 g/L under optimal conditions. Rotary shear measurements were used to study the influence of four variables on the viscosity of the exopolysaccharide solution. The results illustrated that the exopolysaccharide solution demonstrated a shear-thinning behavior and satisfactory thermal stability within the test range. The viscosity of the exopolysaccharide solution was significantly affected by ionic strength and pH; it reached the peak viscosity when the concentration of NaCl was 0.1 mol/L and the pH was neutral. The adsorption behavior of the exopolysaccharide at the medium chain triglyceride–water interface was investigated by a quartz crystal microbalance with a dissipation detector. The results demonstrated that the exopolysaccharide might form a multilayer adsorption layer, and the thickness of the adsorption layer was at its maximum at a concentration of 1.0%, while the interfacial film was the most rigid at a concentration of 0.4%. Overall, these results suggest that the exopolysaccharide produced by Lipomyces starkeyi is an excellent biomaterial for usage in drink, makeup and drug fabrications as a thickening and stabilizing agent. Full article

Recent tragic marine incidents indicate that more efficient safety procedures and emergency management systems are needed. During the 2014–2019 period, 320 accidents cost 496 lives, and 5424 accidents caused 6210 injuries. Ideally, we need historical data from real accident cases of ships to develop data-driven solutions. According to the literature, the most critical factor to the post-incident management phase is human error. However, no structured datasets record the crew’s actions during an incident and the human factors that contributed to its occurrence. To overcome the limitations mentioned above, we decided to utilise the unstructured information from accident reports conducted by governmental organisations to create a new, well-structured dataset of maritime accidents and provide intuitions for its usage. Our dataset contains all the information that the majority of the marine datasets include, such as the place, the date, and the conditions during the post-incident phase, e.g., weather data. Additionally, the proposed dataset contains attributes related to each incident’s environmental/financial impact, as well as a concise description of the post-incident events, highlighting the crew’s actions and the human factors that contributed to the incident. We utilise this dataset to predict the incident’s impact and provide data-driven directions regarding the improvement of the post-incident safety procedures for specific types of ships. Full article

Sensitive skin is characterized by symptoms of discomfort when exposed to environmental factors. Peptides are used in cosmetics for sensitive skin and stand out as active ingredients for their ability to interact with skin cells by multiple mechanisms, high potency at low dosage and the ability to penetrate the stratum corneum. This study aimed to analyze the composition of 88 facial cosmetics for sensitive skin from multinational brands regarding usage of peptides, reviewing their synthetic pathways and the scientific evidence that supports their efficacy. Peptides were found in 17% of the products analyzed, namely: acetyl dipeptide-1 cetyl ester, palmitoyl tripeptide-8, acetyl tetrapeptide-15, palmitoyl tripeptide-5, acetyl hexapeptide-49, palmitoyl tetrapeptide-7 and palmitoyl oligopeptide. Three out of seven peptides have a neurotransmitter-inhibiting mechanism of action, while another three are signal peptides. Only five peptides present evidence supporting their use in sensitive skin, with only one clinical study including volunteers having this condition. Noteworthy, the available data is mostly found in patents and supplier brochures, and not in randomized placebo-controlled studies. Peptides are useful active ingredients in cosmetics for sensitive skin. Knowing their efficacy and synthetic pathways provides meaningful insight for the development of new and more effective ingredients. Full article

Corrosion is an ever-present phenomena of material deterioration that affects all metal structures. Timely and accurate detection of corrosion is required for structural maintenance and effective management of structural components during their life cycle. The usage of aircraft materials has been primarily driven by the need for lighter, stronger, and more robust metal alloys, rather than mitigation of corrosion. As such, the overall cost of corrosion management and aircraft downtime remains high. To illustrate, $5.67 billion or 23.6% of total sustainment costs was spent on aircraft corrosion management, as well as 14.1% of total NAD for the US Air Force aviation and missiles in the fiscal year of 2018. The ability to detect and monitor corrosion will allow for a more efficient and cost-effective corrosion management strategy, and will therefore, minimize maintenance costs and downtime, and to avoid unexpected failure associated with corrosion. Conventional and commercial efforts in corrosion detection on aircrafts have focused on visual and other field detection approaches which are time- and usage-based rather than condition-based; they are also less effective in cases where the corroded area is inaccessible (e.g., fuel tank) or hidden (rivets). The ability to target and detect specific corrosion by-products associated with the metals/metal alloys (chloride ions, fluoride ions, iron oxides, aluminum chlorides etc.), corrosion environment (pH, wetness, temperature), along with conventional approaches for physical detection of corrosion can provide early corrosion detection as well as enhanced reliability of corrosion detection. The paper summarizes the state-of-art of corrosion sensing and measurement technologies for schedule-based inspection or continuous monitoring of physical, environmental and chemical presence associated with corrosion. The challenges are reviewed with regards to current gaps of corrosion detection and the complex task of corrosion management of an aircraft, with a focused overview of the corrosion factors and corrosion forms that are pertinent to the aviation industry. A comprehensive overview of thin film sensing techniques for corrosion detection and monitoring on aircrafts are being conducted. Particular attention is paid to innovative new materials, especially graphene-derived thin film sensors which rely on their ability to be configured as a conductor, semiconductor, or a functionally sensitive layer that responds to corrosion factors. Several thin film sensors have been detailed in this review as highly suited candidates for detecting corrosion through direct sensing of corrosion by-products in conjunction with the aforementioned physical and environmental corrosion parameters. The ability to print/pattern these thin film materials directly onto specific aircraft components, or deposit them onto rigid and flexible sensor surfaces and interfaces (fibre optics, microelectrode structures) makes them highly suited for corrosion monitoring applications. Full article

This study presents a methodology for forecasting the medium– and long–term real revenues of the automotive post–sales service sectors, assuming the automobile industry is nowadays undergoing a deep process of transformation. There are several conditioning factors, usage as well as environmental reasons, that makes past times an unreasonable guide for a future forecast. Firstly, we estimate, using regression models, the most important variables for the automobile sector that will affect the long–term forecasts of the automotive aftermarket’s revenues. Secondly, we apply participatory methods to quantify the impact of the new conditioning factors. This is a research tool used for the Spanish automotive aftermarket. Our results indicate how stakeholders’ perceptions modulate the forecasts for those economic sectors involved in a disrupted changing business model. Full article

With the rapid popularization of mobile Internet technology and smart terminal equipment in recent years, the volume and usage of dockless bikesharing (hereafter referred to as bikesharing), which is green, environmentally friendly and convenient, have grown rapidly, making it one of the China’s “new four major inventions.” The development of the bikesharing in China consists of a pre-sharing era and a post-sharing era. In the pre-sharing era, capital-driven vicious market competition and lack of precise control have led to the abuse of urban space. Since the post-sharing era, the industry structure has returned to rationality, and many participants have been forced out of the market. The bikesharing has formed an oligopoly market consisting of head players such as Hellobike, Mobike, and Ofo. Therefore, how to improve the level of refined operations, promote sustainable development, improve cyclist satisfaction, and contribute to China’s strength in transportation have become urgent problems for bikesharing companies and traffic management departments. From the perspective of the cyclist experience, the brand choice of the bikesharing is taken as the research object. An online revealed preference survey is used to collect data on cyclists’ socio-economic attributes and subjective evaluations on the bikesharing. The conditional Logit model is used to explore the important factors that influence cyclists on the choice of bikesharing brands. Research results include: (1) age, occupation type, after-tax monthly income of the faculty group, riding comfort, rent, picking up/returning convenience, word of mouth, and volume have a significant impact on cyclists’ bikesharing brand choices; (2) gender, educational background, monthly living expenses of the student group, appearance, deposit, deposit returning speed, rate of broken bikes, ease of use of software, and rent discount have no significant impact on cyclists’ bikesharing brand choices. The research results are of great significance for improving the service quality of bikesharing companies and promoting the healthy development of the shared economy in China. Based on the results of the study, policy recommendations are made on the improvement for riding comfort, human-centered design, and word of mouth, and the construction of shared facilities. Full article

The continuous growth of the number of Internet of Things (IoT) devices and their inclusion to public and private infrastructures has introduced new applciations to the market and our day-to-day life. At the same time, these devices create a potential threat to personal and public security. This may be easily understood either due to the sensitivity of the collected data, or by our dependability to the devices’ operation. Considering that most IoT devices are of low cost and are used for various tasks, such as monitoring people or controlling indoor environmental conditions, the security factor should be enhanced. This paper presents the exploitation of side-channel attack technique for protecting low-cost smart devices in an intuitive way. The work aims to extend the dataset provided to an Intrusion Detection Systems (IDS) in order to achieve a higher accuracy in anomaly detection. Thus, along with typical data provided to an IDS, such as network traffic, transmitted packets, CPU usage, etc., it is proposed to include information regarding the device’s physical state and behaviour such as its power consumption, the supply current, the emitted heat, etc. Awareness of the typical operation of a smart device in terms of operation and functionality may prove valuable, since any deviation may warn of an operational or functional anomaly. In this paper, the deviation (either increase or decrease) of the supply current is exploited for this reason. This work aimed to affect the intrusion detection process of IoT and proposes for consideration new inputs of interest with a collateral interest of study. In parallel, malfunction of the device is also detected, extending this work’s application to issues of reliability and maintainability. The results present 100% attack detection and this is the first time that a low-cost security solution suitable for every type of target devices is presented. Full article