Rapid Growth Research Articles

Development of alginate beads loaded with bioactive ingredients from Chlorella vulgaris cultivated in food industry wastewaters

Microalgae are increasingly recognized for their potential in the food sector due to their rapid growth and rich content in proteins, carbohydrates, and pigments. The extraction of pigments from microalgal biomass holds promise for their utilization as natural colorants and antioxidants. To address the economic challenges associated with microalgae cultivation, particularly high nutrient costs, this study focused on cultivating Chlorella vulgaris in a mixture of food industry wastewaters (brewery wastewater, expired orange juice and cheese whey). This resulted in a microalgae-bacteria consortium with a concentration of 2.2 g·L−1 dry weight after 5 days of cultivation. The wastewater bioremediation ranged between 23 and 77 %, and the produced microalgae biomass contained 21.68 ppm lutein, 36.47 ppm a-chlorophyll and 11.19 ppm b-chlorophyll. The extraction process employed a solvent screening strategy with food industry-accepted solvents used to extract high-value compounds efficiently. Ethanol was the most effective solvent, outperforming acetone, ethyl acetate, and hexane. An upscaled extraction process was conducted using 10 g lyophilized microalgae. After ethanol evaporation, the microalgal extract was re-diluted in sunflower oil and encapsulated in alginate beads, achieving an encapsulation yield of 93.3 %. Lutein, identified as one of the main compounds in the extract, exhibited a satisfactory encapsulation efficiency of 55 %. The efficient encapsulation of the microalgae components in alginate beads was verified by the alteration of the colorimetric parameters of these alginate beads compared to those loaded with pure sunflower oil as well as empty beads. These findings highlight the potential of microalgae as a valuable tool for transforming food industry wastewater into high-value products, especially when microalgal extract is encapsulated in alginate beads. This strategy presents substantial prospects for the food industry, merging effective wastewater valorization with biomass production and bioactive compound extraction. It exemplifies a circular bioeconomy, showcasing sustainable resource management and value creation.

Impact of adding waste polyethylene (PE) and silica fume (SF) on the engineering properties of cement mortar

Impact of adding waste polyethylene (PE) and silica fume (SF) on the engineering properties of cement mortar

Multiple faults detection in doubly-fed induction generator wind turbine using artificial neural network

The development of fault detection methods in wind turbine (WT), especially for single fault detection, is continuously increasing. However, the rapid growth of fault detection in WT leads to another challenge where multiple faults can occur. The single fault detection method in WT is no longer reliable, especially when multiple faults occur simultaneously. Therefore, multiple faults detection in doubly-fed induction generators (DFIG) WT was proposed using an artificial neural networks (ANN) model. These multiple faults include internal and external stator faults happening simultaneously. Internal stator faults cover inter-turn short circuit faults and open circuit faults, while external stator faults cover loss of excitation and external short circuit faults. The performance of the developed multiple faults detection model was measured using accuracy and the root mean square error (RMSE) value. The results show that the developed model performs well with high accuracy and a low RMSE value. Thus, the developed model can accurately detect the coexistence of multiple faults in DFIG WT.

Causes and Impacts of Water Pollution on Various water bodies in the State of Rajasthan, India: A Review

Water quality and water resources make an impression on the social, economic and political advancement of society. With the rapid growth of urbanization and industrialization linked with economic and social needs, the pollution of water has reached a level of no return. Water is defined as harmful for human and aquatic lives when it is become contaminated by unexpected substances such as heavy metals, agricultural and industrial chemicals, hydrocarbon fuels, radioactive materials, sewage, pharmaceutical drugs, and biologic agents such as bacteria, parasites, and viruses. This water is considered polluted or contaminated (Bagul et al. 2015), The problem of water pollution becomes more hazardous in a region where availability of water is critically less like the state of Rajasthan (Coyte et al. 2019). The situation of surface water pollution in arid and semi-arid areas of state is alarming. We know that every living being needs water for their survival. All living being intake water directly or indirectly from various water resources. Intake of polluted water would be harmful for them. Transport of bio-accumulative pollutants to food chain makes the situation more grievous. So, it is the need of the hour to examine the magnitude and range of water pollution in the water bodies, especially in the state like Rajasthan. In the present scenario we can’t prevent water to being polluted totally but the scaling down of pollution is imperative. It is high time to take some steps to educate and spread awareness to the people regarding this alarming issue.

Study of the modern reclamation and ecological state of soils in Azerbaijan

For many years in the Republic of Azerbaijan, numerous reclamation and ecological measures aimed at attracting agricultural lands of natural cenoses to use in agrocenoses were carried out. The soils of the studied territory are quite unique in terms of their soil-forming structure and ecological conditions, and they differ from other regions of the country in terms of irrigation water content. The article reflects some important results of soil and water studies conducted over the last years. Determining the qualitative composition of groundwater and irrigation water in different seasons of the year using modern methods is relevant from an environmental and reclamation point of view. Based on remote sensing and geographic information system (GIS) technologies, our research is based on the analysis of natural and anthropogenic landscape changes and changes in natural conditions as a result of agricultural development in the 20 km buffer zone along the banks of Kura and Araz rivers. As a result of the conducted research, it was determined that the rapid growth of the population has caused the reduction of the area of agro-landscapes, the salinization of the soil, the drying of the water in the water basins, the expansion of the construction areas. This has disrupted the natural balance.

An Efficient Lightweight Crypto Security Module for Protecting Data Transmission Through IOT Based Electronic Sensors

The Internet of Things (IoT) devices are advanced nanoelectronics devices which has recently witnessed an explosive expansion in the field of communication and electronics, becoming ubiquitous in various applications. However, the rapid growth of IoT applications makes them prone to security threats and data breaches. Hence, cryptographic techniques are developed to ensure data confidentiality and integrity in IoT and many of the applications from optoelectronics. However, the existing cryptographic algorithms face challenges in securing the data from threats during transmission, as they lack effective key management. Therefore, we proposed a novel optimized lightweight cryptography (LWC) to resolve this challenge using the combined benefits of Grey Wolf Optimization and Hyper Elliptic Curve Cryptography (GW-HECC). The proposed LWC algorithm protects the data from attacks during data exchange by optimizing the key management process and aims to deliver greater Quality of Service (QoS) in IoT networks. An IoT network was initially created with multiple sensor devices, IoT gateways, and data aggregators. The proposed framework includes a Quantum Neural Network (QNN)-based attack prediction module to predict the malicious data entry in the IoT network. The QNN learns the attack patterns from the historical IoT data and prevents incoming malicious data entries, ensuring that only normal data is transmitted to the cloud. For secure data transmission, the sensed data from the IoT network are encrypted using the proposed GW-HECC. The presented work was designed and implemented in Python software; the experimental results demonstrate that the proposed method offers greater data confidentiality of 97.9%, improved attack prediction accuracy of 99.8%, and a reduced delay of 0.37 s. Furthermore, a comparative analysis was made with existing cryptographic algorithms, manifesting that the proposed algorithm acquired improved results.

Performance Analysis: Object Detection System for Low Illumination

Abstract: Abnormal activity detection plays a very important role in surveillance applications. The existing research on surveillance for daytime has achieved better performance by detecting and tracking objects using deep learning algorithms. However, it is difficult to achieve the same performance for night vision mainly due to low illumination. Deep learning is a powerful machine learning technique in which the object detector automatically learns image features required for detection tasks. It is required to generate a model that detects objects under low illumination. The approach is to use thermal infrared images and detect external objects, if any, and classify whether it is human or animal in an isolation area. With the rapid growth of deep learning, more efficient techniques will be implemented to solve the problems of object detection using neural networks and deep learning

Influence of Build Height on Quality of Additively Manufactured Thermoplastic Polyurethane Parts

Due to geometrical degrees of freedom, low cost, and ease of realizing complex structures, polymer additive manufacturing (AM) has emerged exceptionally well. Even with rapid evolutionary growth, AM lacks sound quality mainly including inherent porosity and surface roughness compared to their counterparts (conventional manufacturing processes) due to the involvement of several printing parameters in AM processes. This quality‐based comparative assessment presents the influence of build/layer height on the porosity (using micro‐X‐ray computed tomography) and surface roughness (in build direction) of additively manufactured thermoplastic polyurethane (due to its versatile properties in applications like wearable electronics and biomedical) using three different polymer AM processes namely selective laser sintering, fused deposition modeling, and stereolithography. Along with porosity, an in‐depth pore characterization is also performed to understand the geometrical feature and severity of pores present in each sample of the AM process. Results are compared finally to make concluding remarks.

Interconnectivity disrupted by fading globalization: A network approach to recent international trade developments

Abstract The post-World War II decades experienced rapid growth in international trade, but recently a trend of weakening globalization has been consolidating. We construct an International Trade Network (ITN) using bilateral trade (2010 to 2022) to assess how interconnectedness has evolved in the face of recent developments. Our analysis reveals that while network connectivity initially improved, there was a shift towards a negative trend from 2018, coinciding with an increasingly unfavorable environment for international trade. We also document significant changes in the roles of countries within the ITN. While the USA remains the primary hub and China solidifies its second position, key countries like Germany, France, Great Britain, and Japan have notably lost relevance, whereas nations like India and the Republic of Korea are gaining prominence. Finally, employing an econometric model, we show that countries with large economies, significant manufacturing sector, lower inward foreign direct investment stock, and economic and geopolitical stability tend to occupy more central positions in the ITN.

New energy vehicle technology research - Charging technology

In recent years, Chinas economic development is becoming more and more rapid, leading to the increasingly serious pollution emission problem of traditional fuel vehicles. In order to solve the environmental problems, the transformation of automobiles has become an urgent problem. At the present stage, electric vehicles are also widely concerned by all sectors of society because of their low carbon emissions, energy saving and low use cost. With the rapid growth of electric vehicle sales, the demand for charging piles is rising, and the mainstream charging facilities for new energy vehicles are still in short supply. Therefore, we need to focus on efficient wireless charging to solve the major problems in the current electric vehicle industry. This paper analyzes the wireless dynamic energy transmission technology, extending the service life of the battery, how to reduce the cost, the optimization of coil parameters design, the offset of transmission coil and receiving coil, foreign body detection and overheating problems.

Upgrade and Performance Evaluation of G8+ Large-size Cast Mono-Si Ingot

With the rapid growth of CZ mono-Si solar cell technology in the global market, the development of cast mono-Si faces challenges in terms of crystal quality and cost. This study introduces the first preparation of a G8+ large-size casting furnace by upgrading a G7 furnace to enhance casting mono-Si's performance and economic benefits. The effects of the G8+ casting furnace on the preparation cost of mono-Si ingot, crystal quality and its impact on the performance of solar cells were thoroughly investigated. Modifying the thermal field and optimizing the seed pavement strategy increased the G8+ cast mono-Si ingot weight to 1600kg, raised the monocrystalline ratio to approximately 98%, and achieved an effective yield exceeding 50%. Solar cells made from G8+ cast mono-Si demonstrated electrical performance comparable to CZ mono-Si cells, achieving an average efficiency of 22.64% with only a 0.3% efficiency gap. Consequently, the upsizing of cast mono-Si ingots and adopting rigorous defect control strategies could significantly enhance the electrical performance and manufacturing productivity of cast mono-Si.

FULLY AUTOMATED SOLAR GRASS CUTTER

In present world grass cutter machines are becoming very popular . Rapid growth of different high-tech tools and equipment makes our jobs much easier . Nowadays we are facing issues of pollution and power failures in our daily life . As we know pollution is manmade, so there are solutions for this problems too .Earlier grass cutters contains IC engine and hence because of its environmental impact, pollution level rises .IC engines are costly and hence the grass cutter is also costly.This was one of the main disadvantage of old model grass cutters. Maintenance cost of this conventional machine is also high.In order to overcome these drawbacks , we have thought about the device, which performs its functions without causing such problems.The project aims at implementing a grass cutting machine system which runs on solar energy .This model is economical compared to the previous one .Solar power doesn’t release any green house gases.Hence it is safe and environmentally friendly. Also use of solar power reduces use of electricity .General principle of mowing were used in the designinig and developing of solar powered grass cutter .The designing of the project consists of solar panel,DC motor,motor driver,arduinoUNO,cutting blade,ultrasonic sensor.Arduino is used to control the entire system and hence the device is automated.Ultrasonic sensor is used for avoiding obstacles and the working of the same is also controlled by the microcontroller.The battery recharges by the solar charging controller and also less energy is required for cutting the grass.Hence the performance is more efficient than the conventional machine.Levelling of grasses in playgrounds,gardens etc.can be achieved by using this machine.The cutted grass left behind will also be collected along with the cutting operation by using grass collection technique.This is additionally inbuilted on the device.Since the device is fully automated no man power is needed and also skilled labourers are not neeeded to operate the device.Hence normal people can use this automated grass cutter without much efforts. Keywords-Solar,Grass cutter,Levelling,Economical,Pollution- Free

Etiological Subclassification of Stroke in Older People ≥80 Years Compared to Younger People: A Systematic Review and Meta-Analysis.

Due to the rapid growth of the world´s oldest population, the number of older persons with stroke is expected to rise. Knowledge of stroke etiology is essential to offer personalized and equal health care across age groups. The present systematic review aimed to investigate the prevalence of etiological subtypes of ischemic and hemorrhagic stroke in older compared to younger people. MEDLINE, Embase, Cochrane, Epistemonikos, and Cinahl were systematically searched for studies regarding etiological classification in people ≥80years compared to those <80years with ischemic or hemorrhagic stroke. Out of 28441 identified articles, eight met the inclusion criteria. In total, 8223 individuals were included in meta-analyses, of whom 2997 were 80years or older. We demonstrated a higher prevalence of cardioembolic stroke in people ≥80years OR 1.68 (95% CI, 1.12-2.53). Small vessel disease was significantly less common in older people OR .64 (95% CI, .50-.81). Regarding large vessel disease, no statistically significant difference between the two groups was shown OR 1.05 (95% CI, .77-1.43). In people ≥80years, cardioembolic stroke is more common, and small vessel disease less common compared to people <80years. Overall, the results have to be interpreted with caution due to few studies. Large studies using validated classification systems are needed.

Investigating Research Hotspots of Combat-related Spinal Injuries: A 30-year Bibliometric Analysis Study.

Spinal cord injuries often lead to significant motor and sensory deficits, as well as autonomic dysfunction. Compared with normal spinal injuries, combat-related spinal injuries (CRSIs) are usually more complex and challenging to treat because of multiple traumas, firing-line treatments, and arduous initial treatments on a battlefield. Yet numerous issues remain unresolved about clinical treatment and scientific research. The enhancement of CRSI diagnosis and treatment quality by military surgeons and nurses is imperative. The objective of this study is to identify the frontiers, hotspots, and trends among recent research, summarize the development process of clinical trials, and visualize them systematically. We collected publications from CRSI based on the Core Collection of Web of Science for 30 years from January 1, 1993 to May 1, 2023.Visualizations of the knowledge maps were produced using VOSviewer and CiteSpace software. We examined annual trends of publications and distribution patterns, the number of publications, as well as the research hotspots. Among 201 documents, it was found that there was a stable upward trend in publications. There were 2 rapid growth stages during the 30 years. Among all countries, the USA contributed the most publications, along with the highest influence and the most international cooperation. Military Medicine was the journal of the maximum publications, whereas the Spine journal was the most influential one. Keyword co-occurrence analysis and trend topics analysis revealed that these articles focused 5 distinct categories for CRSI. As the first bibliometric study focused on CRSI, we demonstrated the evolution of the field and provided future research directions. We summarized the hotspots and 5 clusters published. This would serve as a useful guide for clinicians and scientists regarding CRSI global impacts.

Tumor Growth Kinetics Based on Initial Tumor Volume Doubling Time in Active Surveillance of Low-Risk Papillary Thyroid Carcinoma.

During active surveillance (AS) of low-risk papillary thyroid carcinomas (PTCs), the majority remain stable, while some exhibit either increase or decrease in tumor diameter or tumor volume (TV). We aimed to evaluate the clinical outcomes and relevant parameters influencing tumor growth kinetics of low-risk PTCs. This retrospective cohort study evaluated clinical parameters of 402 patients with low-risk PTC sized <2 cm, with a follow-up duration over 3 years. Changes in maximum tumor diameter, TV, and initial TV doubling time (i-TVDT) calculated within 3-year were assessed. A significant change in TV was defined as a change of 75% or more. Of the 402 patients with low-risk PTC, 93.3% (375/402) were diagnosed with papillary thyroid microcarcinoma. During a median follow-up of 5 years, 3.4% (14/402) of patients developed new cervical lymph node (LN) metastasis, and 8.2% (33/402) experienced maximal diameter increase of ≥3 mm. The i-TVDT of <5 years emerged as an independent risk factor for both maximal diameter growth and new LN metastasis (p<0.001 and p=0.04, respectively). Based on TV changes and i-TVDT during AS, we identified four statistically significant tumor kinetic patterns (p<0.001): Stable (±75% change in TV), Rapid growth (TV increase >75% and i- TVDT <5 years), Slow growth (TV increase >75% and i-TVDT ≥5 years), and Shrinkage (TV decrease >75%). Most of the PTCs remained stable (67.7%), but 17.2% were rapidly growing, with a median onset of growth of 2.0 years. Slowly growing PTCs, comprising 10.9%, grew at a median of 4.3 years. A minority, 4.2%, exhibited shrinkage. In total, 115 (28.6%) patients underwent delayed surgery >12 months after initiating AS. The reasons for delayed surgery included patient preference (51/115, 44.3%), disease progression (31/115, 27.0%), and suspected disease progression, which was referred to as tumor growth not meeting the criteria of an increase of ≥3 mm in maximal tumor diameter (17/115, 14.8%). An i-TVDT of <5 years serve as an important prognostic indicator for disease progression, including tumor growth and new LN metastasis. The four tumor kinetic patterns based on TV changes and i-TVDT assist in guiding personalized decisions early in AS.

Integration of Smart Cities and Building Information Modeling (BIM) for a Sustainability Oriented Business Model to Address Sustainable Development Goals

The construction industry, business models, and smart cities are recognized as pivotal domains with profound implications for fostering sustainability, prompting extensive research endeavors. However, there remains a dearth of interdisciplinary integration within this sphere aimed at fostering sustainable development. Nevertheless, current studies suggest that research in this area could provide theoretical and practical guidance for the sustainable transformation of society and make a positive contribution to the realization of the Sustainable Development Goals (SDGs). Therefore, this paper aims to utilize an innovative mixed research approach combining macro-quantitative bibliometric analysis with subsequent micro-qualitative content examination based on the SDGs to explore the relationship between BIM and smart cities in promoting a sustainability-oriented business model, which provides a comprehensive understanding of the overall situation and development of research topics in the field and contributes to the improvement of the SDGs. The results show that, during the last 13 years (from the year 2011 to 2023), the period from the year 2011 to 2016 was the initial stage of the field, followed by a rapid growth after the year 2018, of which “BIM”, “Smart City”, “Business Model”, “Building Life Cycle”, “Urban Management”, and “Business Model Innovation” are the keywords representing the current research hotspots. The circular economy model that has been developed since 2021 has contributed to life cycle stages, including “briefing stages” and “procurement stages”. As such, the “whole life cycle”, “strategic urban planning frameworks”, and “sustainable business models” have become future research trends, whilst real-world applications such as “smart tourism”, “e-government”, and “green building” have emerged. Further, the key partnerships of “city managers”, “corporate enterprises”, and “public participation” for smart cities contribute to the achievement of SDGs 8 and 17 in terms of integrating urban information technology and urban infrastructure, policy regulation, knowledge-sharing, improving economic efficiency, and promoting sustainable economic growth.

Structural Changes in the Dynamics of China’s Exports and Imports

The economic policy pursued has turned China into a major trading power. In terms of GDP, the Chinese economy has been the first economy in the world for a number of recent years; China’s rapidly growing trade flows have made it the largest trading partner for many countries. Over the past twenty years there has been rapid growth in exports and imports. The article puts forward a hypothesis about the presence of structural instability in the dynamics of Chinese exports for the period from 2000 to 2020. The hypothesis was confirmed and two periods were identified in the dynamics of exports and imports with different natures of the main development trend: from 2000 to 2008 and from 2009 to 2020. For each stage, trend equations were selected that describe the dynamics of exports and imports and an interval forecast of indexes for 2021 was made. Materials and methods. During the work, dynamic, structural analysis of analytical and statistical information was used; methods of analytical, logical, systemic, correlation and regression analysis were used, as well as analysis of structural changes. The analysis was carried out using the Statistica 10.0 program.Results. A change in the value of the import coverage ratio by exports was revealed before and after structural changes in the dynamics of the main foreign economic indexes and an assessment of their statistical significance was given. An analysis of the influence of export dynamics on GDP dynamics was carried out and it was found that before structural changes, the influence of export dynamics on GDP dynamics was statistically insignificant, and after a structural change, export dynamics began to have a direct impact on changes in China’s GDP. Conclusion. Analysis of official statistical data on the main indexes of China’s foreign economic activity for the period from 2000 to 2020 allowed us to note that the volume of Chinese exports increased over the period 2010-2019 from $1.58 trillion in 2010 (10.34% of global exports), to $2.50 trillion in 2019 (12.81% of global exports). In 2019, China continued to rank first in terms of export value among all countries in the world. Despite the challenging year of 2020, China’s exports reached almost 2.6 trillion US dollars and increased by 4% compared to 2019.China also occupies a leading position in the export of high-tech goods - their volume is 731.9 billion US dollars, the share of exports in the global volume is 25%. At the same time, the dynamics of Chinese exports for the period from 2000 to 2020 was heterogeneous and characterized by structural instability. Two stages can be distinguished with different characteristics of the main development trend: from 2000 to 2008 and from 2009 to 2020. Based on this, the authors came to the conclusion that to describe the main trend in the development of export and import dynamics for the period from 2000 to 2008, the exponential model is best suited. To describe the main trend in the development of export and import dynamics in the period from 2009 to 2020 - logarithmic model. A study of the consistency of changes in export and import volumes showed that in the period from 2009 to 2020 was characterized by greater consistency in China’s main foreign trade flows than the period from 2000 to 2008. In the period before the structural change in the dynamics of exports and imports, the coverage ratio varied from 105.7% to 127.6%; in the period after the structural change, the coverage ratio changed from 108.9% to 135.4%.Checking the statistical significance of the differences in the coefficient of coverage of imports by exports before and after the structural change showed that the differences are not statistically significant. In the period from 2000 to 2008 the dynamics of China’s exports did not have a statistically significant impact on the dynamics of the country’s GDP. From 2009 to 2020 after structural changes in the nature of the dynamics of the main indexes of China’s foreign trade, changes in exports began to have a statistically significant impact on the dynamics of GDP. A 1% increase in China’s exports now results in a 0.25% increase in GDP.The practical significance of the paper is determined by the developed methodology for analyzing structural changes in the dynamics of exports and imports, examined using the example of China.

Navigating the nexus: unraveling technological innovation, economic growth, trade openness, ICT, and CO2 emissions through symmetric and asymmetric analysis

In Malaysia’s rapid economic growth and industrialization, environmental degradation and carbon emissions pose significant challenges. As urbanization continues to rise, there is a growing recognition of the imperative to tackle CO2 emissions. Trade openness and globalization drive economic activity but also heighten environmental pressures, including CO2 emissions from transportation and industry. Information communication technology (ICT) usage, shaped by infrastructure and regulations, can either improve energy efficiency or increase energy consumption. The study examines the impacts of economic growth (EG), trade openness (TON), technological innovation (TIN), and ICT on CO2 emissions in Malaysia, using both symmetric and asymmetric methods from 1985 to 2021. While many studies have explored environmental degradation, focusing on CO2 emissions and ecological footprint indicators, only a limited number have delved into the combined impact of sustainable EG, TON, ICT, and TIN on Malaysia’s CO2 emissions. Notably, these studies have often neglected the utilization of both symmetric and asymmetric methodologies. Hence, this study employed auto-regressive distributed lag (ARDL) and non-linear ARDL approaches to investigate the dynamic effects of the studied variables. The key findings from the symmetric analysis demonstrate that EG, TON, and ICT together take part in the increase of CO2 emissions in both the short and long run. Particularly, technological innovation plays a significant role in reducing CO2 emissions in the short term through the adoption of cleaner technologies. However, the results of the NARDL bound test reveal asymmetric long-term consequences of technological innovation, economic growth, and ICT on CO2 emissions. The study underscores the need for CO2 reduction policies in Malaysia, advocating for measures, such as incentivizing cleaner technologies and upgrading energy infrastructure. It also recommends implementing carbon pricing mechanisms for production and trade, alongside awareness campaigns to foster behavioral changes aimed at reducing emissions.

Detection of Urban Growth in Taiz City, Yemen, Between 1981 and 2022 by Using Google Earth™ and Geographical Information System Data

Rapid urbanization brought serious socio-economic and environmental problems in many cities around the world, particularly in developing countries like Yemen. Urban "sprawl", a synonym of rapid and unplanned urban growth, is considered an obstacle for sustainable development, which causes serious long- and short-term problems, such as extreme infrastructure expenses, economic inefficiency, environmental destruction, and social instability. This is the case of Taiz City, the third largest city in Yemen, which is facing a huge challenge to manage the spatial extension of its built-up area at the expense of the reduction of natural resources and environment. This study aims to investigate urban growth process in Taiz City, focusing on urban sprawl and agricultural land-use change during 1981–2022. The data used are high resolution geospatial data, which are the topographic map for 1981 and Google Earth (GE) images for 2003, 2012, and 2022. The methodology adopted was manual digitizing using Geographic Information System (GIS) software to extract urban land use features from the images of the different dates. Four land-use maps were produced and used for calculation the urban sprawl and land-use changes. The urban expansion rate and patterns were also identified in three phases: 1981–2003, 2003–2012, and 2012–2022. The results show that the built-up area increased six times from 6.2 km2 in 1981 to 34 km2 in 2022, while the agriculture area decreased by 77% from 18 km2 in 1981 to 4.2 km2 in 2022. The urban sprawl in Taiz covered about 75% of its municipal area and extended to the agricultural and rural areas. The sprawl index (USI) is measured to be 5.4%, indicating a high degree of sprawl in Taiz. There is no open space left for future development, and the water resources are at risk of population and depletion. The study demonstrated that informal and haphazard expansion must be controlled, a development strategy should be prepared, so that sustainable urban growth can be achieved. The results of this study could be used as a decision support tool for urban management activities. The vector layers produced by this study could provide the required input data for the future urban modeling of the city.

Towards Environmentally Sustainable Aviation: A Review on Operational Optimization

In recent years, the rapid growth of air traffic has intensified pressure on the air transport system, leading to congestion problems in airports and airspace. The projected increase in demand exacerbates these issues, necessitating immediate attention. Additionally, there is a growing concern regarding the environmental impact of the aviation sector. To tackle these challenges, the adoption of advanced methods and technologies shows promise in expanding current airspace capacity and improving its management. This paper presents an overview of sustainable aviation, drawing on publications from academia and industry. The emphasis is on optimizing both flight and ground operations. Specifically, the review delves into recent advancements in airline operations, airport operations, flight operations, and disruption management, analyzing their respective research objectives, problem formulations, methodologies, and computational experiments. Furthermore, the review identifies emerging trends, prevailing obstacles, and potential directions for future research.