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Pituitary apoplexy is a rare surgical emergency. This condition involves the rapid progression, which can threaten patients’ life and is caused by haemorrhage or infarction in the pituitary gland. In most cases, a pituitary apoplexy occurs on a pre-existing pituitary tumor. The patient presents with a clinical syndrome of headache, visual deficits, ophthalmoplegia, and altered mental status and hormonal dysfunction. We report a 28-year-old male patient with no previous history of pituitary gland disease. There was a sudden onset and rapid progression, and the patient underwent emergency endoscopic nasal surgery. After surgery, the patient's neurological function was improved and stable.

Waste-derived biogas and third-generation algal biodiesel are attractive alternative fuels to substitute fossil diesel in a diesel engine. However, the use of biodiesel as pilot liquid fuel and biogas as the main fuel in a diesel engine is a complex and extremely non-linear process. The current research aims to forecast and optimize the combustion and exhaust emission parameters of a variable compression dual-fuel combustion engine. Experiment data were collected at multiple engine loads, compression ratio, pilot fuel injection pressure, and timings. Using the experimental data, a multi-layer perceptron network was used to create an Artificial Neural Network (ANN) based prognostic model. Brake thermal efficiency, flow rates of biogas, peak in-cylinder pressure, carbon dioxide, unburnt hydrocarbons, oxides of nitrogen, and carbon monoxidewere all predicted using the established prognostic model. The predictive model's robustness is demonstrated by statistical metrics such as R (0.9723 – 0.988) and R2 (0.9453 – 0.9761), Nash-Sutcliffe model efficiency (94% – 97%), and mean absolute percentage error (0.013 – 0.128), Kling-Gupta efficiency (0.9548 – 0.9836), Theil's U2 model uncertainty (0.162 – 0.368) were used to validate the generated model, demonstrating good model quality. The Multi-Output Response Surface Methodology (RSM) was used to optimize the parameters of dual-fuel combustion. Using the desirability technique, the trade-off analysis between emission and efficiency showed that 84% engine load, 244 bar of fuel injection pressure, 28 oCA bTDC of injection timing, and 17.5 of compression ratio are the best operation conditions. The RSM research results were confirmed using an experimental investigation, and errors were less than 9%. It was revealed that ANN-linked RSM is a good hybrid method for modeling, prediction, and optimization of a dual- fuel engine's performance.

Multiple intracranial meningiomas refer to the presence of multiple meningiomas in multiple intracranial locations in the same patient without signs of neurofibromatosis. The incidence varies from 1% to 10%. Despite the diversity, the prognosis of multiple intracranial meningiomas has no difference from that of benign solitary meningioma. However, malignant tumors of different grades are observed to occur simultaneously in one-third of multiple meningiomas. Surgery is still the best choice for the treatment of symptomatic lesions. Our case review aims to introduce and discuss a 50-year-old female patient diagnosed with multiple intracranial meningiomas, and to describe its clinical, radiological, and histological characteristics. It also emphasizes that the patient had four tumors, underwent surgery, and had a good long-term overcome.

Objectives: To evaluate clinical and preclinical characteristics and results of microsurgery of meningioma under preoperative selective embolization. Subjects and methods: A descriptive research on 9 patients with meningioma who experienced selective embolization preoperation and microsurgery in Military Hospital 103 from January 2016 to July 2021. Evaluating the tumor extent of resection by Simpson, surgery result by Ojemann. Results: Clinical characteristics include consciousness disorder 11.1%, increased intracranial pressure 88.9%, epilepsy 33.3%, movement disorder 33.3% often in the parietial-temporal lobe, psychosis 11.1% often in the frontal lobe. 100% of patients under total resection, medium duration was 155.56 ± 33.58 minutes. Blood transfusion was 0.33 ± 0.5 units. None of the patients had surgery complications postoperation. The good result was 100%. Conclusion: Symptomatic meningioma depends on the situation. Preoperative selective embolization enables to decline the surgery duration, blood transfusion, to remove tumor totally, and to have good results post-operation.

Nowadays, the problem of oil pollution is becoming a big challenge for the environment. Oil pollution threatens the survival of life on land as well as aquatic life. Aware of the seriousness of oil pollution, there have been many scientific studies on solutions to oil spill treatment. The methods can be mentioned as mechanical treatment, microbiological treatment, chemical treatment, absorbent material treatment. Each method has its advantages and disadvantages. In this short review, recent research activities related to the selection of oil-absorbing absorbents and their application in oil absorption are presented. Then, an extensive list of different oil-absorbing materials from the literature, including polymeric materials, porous inorganic materials, and biomass materials, was provided along with their characteristics. Furthermore, the oil adsorption capacity of such materials for different oils and organic solvents has also been discussed to highlight different factors involved in the selection of adsorbent adsorbents. Oil has been tested to separate oil in oil-water mixtures. Finally, some future trends and prospects for oil-absorbing materials are outlined.

Pressure on alternative fuels and strict environmental regulations are driving a strategic shift in the efficient use of renewable biofuels. One of the promising biofuel candidates recently interested by scholars is a biological or organic additive that is added into diesel or biodiesel fuel to improve engine performance and reduce pollutant emissions. With efforts to improve efficiency and combustion quality in cylinders, combustion characteristics, flame structure and emission formation mechanism in compression ignition (CI) engines using blended fuel with organic additives have been studied on the effect of additive properties on the combustion behaviour. In this review, the physicochemical properties of typical organic additives such as ethers compounds and their effects on engine performance and emission characteristics have been discussed and evaluated based on conclusions of recent relevant literature. The results of the analysis revealed the prospect of using ether additives to improve combustion in cylinders and reduce pollutant emissions from CI engines. Obviously, the presence of higher oxygen content, lower viscosity and density, and higher cetane number resulted in a positive change in the combustion dynamics as well as a chain of mechanisms for the formation of pollutant precursors in the cylinder. Therefore, ether additives have a significant contribution to the sustainable energy strategy of the transportation sector in the next period when internal combustion engines still dominate in the competition for energy system choices equipped on vehicles.

Energy is the lifeblood of modern economies as the latter is fueled by the energy demand for everyday life production and consumption. Dubbed as the period of “green economic development,” the 21st...

Energy plays an important role in economic growth and environmental protection, is an important input of many manufacturing industries, and one of the essential commodities of households. The proce...

Always, oil spills do cause serious and dire consequences for the environment, nature, and society that it consumes much time and socio-economic resources to overcome such consequences. Oil spills, hence, posed a big challenge in searching the advanced technologies and devices to recover spilled oil rapidly and efficiently. Indeed, sorbents have been found to play an extremely critical role in the spilled-oil remediation processes. Recently, a large number of various advanced sorbents and sorbent-based oil-collecting devices/technologies have been developed to enhance the oil-recovery capacity. Therefore, it is necessary to have a comprehensive assessment of the application of sorbent-based oil-collecting devices/technologies in recovering spilled oil. Due to this reason, this paper aims to provide a comprehensive review of the advanced technologies of the combination of sorbents and oil-collecting devices in the oil cleanup strategies. Two main oil-collecting devices such as booms and skimmers that could conjunct with sorbents were critically evaluated on the basis of the applicability and technological features, indicating that the capacity of oil spill recovery could achieve 90%. Moreover, oil-storage and oil-collecting devices were also completely mentioned. Last but not least, technical directions, concerns over the application of sorbents in oil recovery, and existing challenges relating to storage, transport, and disposal of used sorbents were discussed in detail. In the future, the automatic process of spilled oil recovery with the conjunction between advanced devices and environmentally friendly high-efficiency sorbents should be further investigated to minimize the environmental impacts, reduce the cost, as well as maximize the collected oil spill.

During the COVID-19 pandemic, lockdowns at city-to-nation levels were enforced in many places in the world aiming to restrict the spread rate of COVID-19. Due to the forced restrictions, many human...

Recently, advances in sensor technologies, data communication paradigms, and data processing algorithms all affect the feasibilities of the bridges structural health monitoring and deterioration detection, and other implementations of monitoring operations. The paper proposes a method to design an irregularity detection and monitoring system for road bridges that combines internet of things (IoT) and artificial intelligence (AI) technologies. Raspberry Pi 4 embedded computer integrating IoT and AI technology with convolutional neural network (CNN) is employed to simultaneously monitor remote bridges on websites and apps via Google Firebase cloud database. The first step of successful testing in the laboratory showed that the system can work stably and coincide with the proposed goals.

Demands for the decline of CO2 emissions resulted in a significant transformation of the energy systems working on carbon sources towards more sustainable, clean, and renewable characteristics. Hydrogen is emerging as a secondary energy vector with ever-increasing importance in the decarbonisation progress. Indeed, hydrogen, a green and renewable energy source, could be produced from steam gasification of plant- originated lignocellulosic biomass. In this current review, key factors affect the hydrogen production yield from steam gasification of plant- originated lignocellulosic biomass, including the design of the gasifier, temperature, pressure, and steam-to-biomass ratio, steam flow rate, moisture and particle size of fed biomass, and catalysts were thoroughly analysed. Moreover, the effects of the abovementioned factors on the reduction of tar formation, which is also a key parameter towards ensuring the trouble-free operation of the reactor, were critically evaluated. More importantly, the separation of produced hydrogen from steam gasification of biomass and challenges over technological, environmental, and economic aspects of biomass gasification were also presented in detail. In addition, this paper is also profiling the prospect of Vietnam in fulfilling its hydrogen economy potential because Vietnam has vast biomass due to its tropical weather and availability of arable land, providing abundant lignocellulosic biomass with 45% of agricultural waste, 30% of firewood, and 25% of other sources. Besides, some primary factors hindering the broad application of biomass for hydrogen production were indicated. Finally, some solutions for implementing the hydrogenization strategy in Vietnam have also been discussed.

The present work compares the biofuel production efficiency of Padina tetrastromatica and Sargassum swartzii macro algae biomass by fermentation with Saccharomyces cerevisiae and Zymomonas Mobilis. The optimal pretreatment factors were identified by studying the effect of temperature, pH, and enzyme concentration on the conversion of macroalgae biomass to fermentable reducing sugars. The Low concentration of enzyme did not help conversion of biomass to reducing sugars even after 15 h of treatment with enzyme, but when the enzyme concentration was increased, the desired conversion was completed within 4h of enzyme treatment. Both Padina tetrastromatica and Sargassum swartzii had an ethanol yield of above 80% irrespective of the difference in the species used for the fermentation. The highest possible ethanol yield (95.12%) was achieved for Padina tetrastromatica biomass when it was fermented with Zymomonas Mobilis. From the above results, it is clear that both Padina tetrastromatica and Sargassum swartzii have the potential to be used as reliable feedstock for biofuel production. The spent biomass after the fermentation process was used for the lipid extraction process and the extracted lipid was used for biodiesel production. The percentage of biodiesel yield obtained by means of the Soxhlet extraction process from Padina tetrastromatica and Sargassum swartzii macro algae with the conventional NaOH catalyst was found to be 84 % and 89 % respectively. MgO.La2O3 was synthesized by means of the co- precipitation method. With the introduction of MgO.La2O3 Nano catalyst biodiesel yield was improved up to 88 % and 92 % for Padina tetrastromatica and Sargassum swartzii macro algae, respectively.

In recent years, searching for efficient solutions to improve the emission and performance characteristics of diesel engines is considered as one of the essential and urgent work. Metal nanoparticles with a large surface area and high heat transfer coefficient could provide the impressive additive ability to the fuel reactivity and atomization. Therefore, the critical role of metal nanoparticles in the support of diesel engine behaviors using biodiesel and diesel is thoroughly evaluated in this current review. Indeed, preparation methods and critical properties of metal nanoparticles and metal nanoparticles-laden fuels are fully introduced. More importantly, the performance, combustion, emission characteristics, and tribology behaviors of diesel engines running on metal nanoparticles- laden biodiesel are compared to diesel fuel in detail. Generally, metal nanoparticles-included biodiesel facilitates the formation of a more homogeneous oxygen-containing mixture of fuel-air, resulting in a more complete combustion process than that of diesel fuel. As a result, the use of biodiesel with the presence of metal nanoparticles is considered as the potential strategy for promoting spay and atomization, enhancing the combustion process, increasing brake thermal efficiency (BTE), reducing toxic emissions (including carbon monoxide (CO), unburnt hydrocarbon (HC), and smoke), and improving tribology characteristics. However, some drawbacks are also indicated, such as increased NOx emission and brake-specific fuel consumption. In addition, it is also concluded that studies on other environmental impacts (such as PM emission), the stable properties of metal nanoparticles, and economic aspects should be made more extensively before commercial applications of metal nanoparticles in the real world.

International audience; The use of a cheap and effective adsorption approach based on biomass-activated carbon (AC) to remediate heavy metal contamination is clearly desirable for developing countries that are economically disadvantaged yet have abundant biomass. Therefore, this review provides an update of recent works utilizing biomass waste-AC to adsorb commonly-encountered adsorbates like Cr, Pb, Cu, Cd, Hg, and As. Various biomass wastes were employed in synthesizing AC via two-steps processing; oxygen-free carbonization followed by activation. In recent works related to the activation step, the microwave technique is growing in popularity compared to the more conventional physical/chemical activation method because the microwave technique can ensure a more uniform energy distribution in the solid adsorbent, resulting in enhanced surface area. Nonetheless, chemical activation is still generally preferred for its ease of operation, lower cost, and shorter preparation time. Several mechanisms related to heavy metal adsorption on biomass wastes-AC were also discussed in detail, such as (i) - physical adsorption/deposition of metals, (ii) - ion-exchange between protonated oxygen-containing functional groups (–OH, –COOH) and divalent metal cations (M2+), (iii) - electrostatic interaction between oppositely-charged ions, (iv) - surface complexation between functional groups (−OH, O2−, −CO–NH-, and –COOH) and heavy metal ions/complexes, and (v) - precipitation/co-precipitation technique. Additionally, key parameters affecting the adsorption performance were scrutinized. In general, this review offers a comprehensive insight into the production of AC from lignocellulosic biomass and its application in treating heavy metals-polluted water, showing that biomass-originated AC could bring great benefits to the environment, economy, and sustainability

The development of renewable energy resources is strongly urged to recoup the shortage of fossil-based energy and its associated pollution issues. Energy production from carbohydrate materials has recently been of great interest due to the availability, reliability, and abundance of carbohydrate sources. Significantly, the catalytic transformation of waste carbohydrates into furan-based biofuels, specifically 2,5-dimethylfuran (DMF), appears to be an attractive solution to the aforementioned energy and environmental issues. The potential of DMF as a renewable fuel is prospective, with its physicochemical properties that are similar to those of fossil fuels. Therefore, the current work focuses on the production of DMF, with the important aspects for enhanced DMF yield being summarized herein. Notably, the significant catalysts derived from zeolite, noble-metal, non-noble-metal, metal–organic framework, and electrocatalytic materials are discussed, alongside their effects in deriving carbohydrates to DMF. Furthermore, the mechanisms of DMF production were clarified too, followed by the scrutinization of the effects from reaction conditions, solvents, and hydrogen donors onto the DMF yield. Finally, the purification process, commercialization potential, and economic feasibility of DMF production were incorporated too, with insightful future directions being identified at the end of our review. This review is expected to advocate DMF production from carbohydrate materials, which could alleviate the energy and environmental problems encountered presently.

The current study aims to investigate the effects of advanced injection timing combined with dual-fuel mode on the diesel engine's overall performance, emission, and combustion characteristics under various loading conditions. In this study, blends of waste oil methyl ester (WOME) at 10%, 20%, and 30% v/v concentration and diesel fuel were used as injected fuel, while biogas was the inducted gaseous fuel through the inlet manifold with a flow rate of 0.8 kg/h. Experimentations were carried out on a 4-stroke single-cylinder water-cooled diesel engine, in which engine speed, injection pressure, and compression ratio were fixed at 1500 rpm, 220 bar, and 17.5:1, respectively. Based on experimental data, dual-fuel mode of WOME20-biogas combined with advanced injection timing to 24°bTDC depicted the most positive results. Indeed, the higher brake thermal efficiency (2.40%), lower exhaust gas temperature (15.77%), but increased brake-specific fuel consumption (3.12%) and brake-specific energy consumption (1.85%) compared to diesel fuel were found at the highest load. Furthermore, increasing trends of in-cylinder pressure (7.48%) and heat release rate (4.71%), but diminished ignition delay (6.96%) as opposed to diesel fuel at higher loads were also reported. For emission analysis, a significant reduction of unburnt hydrocarbon (44.5%), carbon monoxide (61.72%), oxide of nitrogen (64.13%), and smoke intensity (47.42%) was obtained in comparison to conventional diesel fuel. Generally, the test diesel engine working on dual-fuel mode of WOME20-biogas combined with advanced injection timing of 24°bTDC would be helpful to enhance the overall efficiency and emission characteristics.

The concentrations of heavy metal ions found in waterways near industrial zones are often exceed the prescribed limits, posing a continued danger to the environment and public health. Therefore, greater attention has been devoted into finding the efficient solutions for adsorbing heavy metal ions. This review paper focuses on the synthesis of carbon nanotubes (CNTs) from biomass and their application in the removal of heavy metals from aqueous solutions. Techniques to produce CNTs, benefits of modification with various functional groups to enhance sorption uptake, effects of operating parameters, and adsorption mechanisms are reviewed. Adsorption occurs via physical adsorption, electrostatic interaction, surface complexation, and interaction between functional groups and heavy metal ions. Moreover, factors such as pH level, CNTs dosage, duration, temperature, ionic strength, and surface property of adsorbents have been identified as the common factors influencing the adsorption of heavy metals. The oxygenated functional groups initially present on the surface of the modified CNTs are responsible towards the adsorption enhancement of commonlyencountered heavy metals such as Pb 2+ , Cu 2+ , Cd 2+ , Co 2+ , Zn 2+ , Ni 2+ , Hg 2+ , and Cr 6+ . Despite the recent advances in the application of CNTs in environmental clean-up and pollution treatment have been demonstrated, major obstacles of CNTs such as high synthesis cost, the agglomeration in the post-treated solutions and the secondary pollution from chemicals in the surface modification, should be critically addressed in the future studies for successful large-scale applications of CNTs.

The maritime sector has been searching for efficient solutions to change energy consumptions patterns of ports and ships to ensure the sustainable operation and to reduce CO 2 emissions to support sustainable transport in line with International Maritime Organization (IMO) policy guidelines. Therefore, pursuing smart strategies by utilizing the renewable energy sources, clean fuels, smart grid as well as measures of efficient-energy use are beneficial towards attaining the core goals of the IMO, specifically CO 2 emission reduction in the future. This work reviews the main methods and criteria for monitoring CO 2 emission from ports and ships are meticulously presented. Advanced renewable energy technologies connected with sources such as solar, wind, tidal, wave, and alternative fuels and their application in ports to reduce CO 2 were thoroughly were examined. In addition, energy- saving technique and strategies for alternative power and fuels in ships were comprehensively evaluated. The key finding is that port-to-ship interactions such as using zero-emission energy sources or nearly zero-emission approaches were found to offer significant benefits for CO 2 emission reduction. Finally, it is recommended that smart approaches associated with efficient and clean energy use for the port-to-ship pathways to generate net zero-CO 2 emissions for the maritime shipping sector need further urgent investigation.

Nanofluids have gained significant popularity in the field of sustainable and renewable energy systems. The heat transfer capacity of the working fluid has a huge impact on the efficiency of the renewable energy system. The addition of a small amount of high thermal conductivity solid nanoparticles to a base fluid improves heat transfer. Even though a large amount of research data is available in the literature, some results are contradictory. Many influencing factors, as well as nonlinearity and refutations, make nanofluid research highly challenging and obstruct its potentially valuable uses. On the other hand, data-driven machine learning techniques would be very useful in nanofluid research for forecasting thermophysical features and heat transfer rate, identifying the most influential factors, and assessing the efficiencies of different renewable energy systems. The primary aim of this review study is to look at the features and applications of different machine learning techniques employed in the nanofluid-based renewable energy system, as well as to reveal new developments in machine learning research. A variety of modern machine learning algorithms for nanofluid-based heat transfer studies in renewable and sustainable energy systems are examined, along with their advantages and disadvantages. Artificial neural networks-based model prediction using contemporary commercial software is simple to develop and the most popular. The prognostic capacity may be further improved by combining a marine predator algorithm, genetic algorithm, swarm intelligence optimization, and other intelligent optimization approaches. In addition to the well-known neural networks and fuzzy- and gene-based machine learning techniques, newer ensemble machine learning techniques such as Boosted regression techniques, K-means, K-nearest neighbor (KNN), CatBoost, and XGBoost are gaining popularity due to their improved architectures and adaptabilities to diverse data types. The regularly used neural networks and fuzzy-based algorithms are mostly black-box methods, with the user having little or no understanding of how they function. This is the reason for concern, and ethical artificial intelligence is required.

Biodiesel has been emerging as a potential and promising biofuel for the strategy of reducing toxic emissions and improving engine performance. Computational methods aiming to offer numerical solutions were inevitable as a study methodology which was sometimes considered the only practical method. Artificial neural networks (ANN) were data-processing systems, which were used to tackle many issues in engineering and science, especially in some fields where there was a failure of the conventional modeling approaches. Thus, it was believed that the best choice was the development of a novel approach like the ANN model to anticipate engine performance and exhaust emissions with high accuracy. In this review paper, the structure and applicability of the ANN model were comprehensively evaluated. More importantly, the use of ANN with trained, tested, and validated data was introduced to determine the performance and emission characteristics of a diesel engine fueled with biodiesel-based fuel. In general, the ANN model could supply a relatively high determination coefficient as compared between predicted results and experimental data, showing that the ANN model could have a good ability to predict the engine behaviors with an accuracy higher than 95%.

Anaerobic digestion (AD) is a viable and cost-effective method for converting organic waste into usable renewable energy. The efficiency of organic waste digestion, nonetheless, is limited due to inhibition and instability. Accordingly, biochar is an effective method for improving the efficiency of AD by adsorbing inhibitors, promoting biogas generation and methane concentration, maintaining process stability, colonizing microorganisms selectively, and mitigating the inhibition of volatile fatty acids and ammonia. This paper reviews the features of crop waste-derived biochar and its application in AD systems. Four critical roles of biochar in AD systems were identified: maintaining pH stability, promoting hydrolysis, enhancing the direct interspecies electron transfer pathway, and supporting microbial development. This work also highlights that the interaction between biochar dose, amount of organic component in the substrate, and inoculum-to-substrate ratio should be the focus of future research before deploying commercial applications.

Every day, a large amount of food waste (FW) is released into the environment, causing financial loss and unpredictable consequences in the world, highlighting the urgency of finding a suitable approach to treating FW. As moisture content makes up 75% of the FW, hydrothermal carbonization (HTC) is a beneficial process for the treatment of FW since it does not require extensive drying. Moreover, the process is considered favorable for carbon sequestration to mitigate climate change in comparison with other processes because the majority of the carbon in FW is integrated into hydrochar. In this work, the reaction mechanism and factors affecting the HTC of FW are scrutinized. Moreover, the physicochemical properties of products after the HTC of FW are critically presented. In general, HTC of FW is considered a promising approach aiming to attain simultaneously-two core benefits on economy and energy in the sustainable development strategy.