High Expenses Research Articles

Precutting endoscopic band ligation-assisted resection versus endoscopic submucosal dissection in patients with small gastric submucosal tumors originating from the muscularis propria: study protocol of a randomized controlled trial

BackgroundThe management of small gastric submucosal tumors (SMTs) originating from the muscularis propria layer (SMT-MPs) remains a subject of debate. Endoscopic submucosal dissection (ESD) is currently considered the optimal treatment for resection. However, high expenses, complex procedures, and the risk of complications have limited its application. Our previously proposed novel operation, precutting endoscopic band ligation (precutting EBL), has been demonstrated in a long-term, single-arm study to be an effective and safe technique for removing small gastric SMTs. However, the absence of a pathological examination and the potential for delayed perforation have raised concerns. Thus, we modified the precutting EBL by adding endoscopic resection to the snare after ligation and closure, yielding the precutting endoscopic band ligation-assisted resection (precutting EBLR). Moreover, the initial pilot study confirmed the safety and efficacy of the proposed approach and we planned a randomized controlled trial (RCT) to further validate its clinical feasibility.MethodsThis was a prospective, single-center, open-label, parallel group, and randomized controlled trial. Approximately 40 patients with SMT-MPs will be included in this trial. The patients included were allocated to two groups: ESD and precutting EBLR. The basic clinical data of the patients were collected in detail. To better quantify the difference between ESD and precutting EBLR, the primary outcome was set as the operation duration. The secondary outcomes included total operation cost and hospitalization, intraoperative adverse events, and postoperative recurrence. The primary outcome was tested for superiority, while the secondary outcomes were tested for noninferiority. SPSS is commonly used for statistical analysis.DiscussionThis study was designed to validate the feasibility of a novel operation for removing gastric SMT-MPs. To intuitively assess this phenomenon, the operation durations of precutting EBLR and ESD were compared, and other outcomes were also recorded comprehensively.Trial registrationChinese Clinical Trial Registry ChiCTR2200065473. Registered on November 5, 2022.

Multi-Dimensional Modeling of Cerebral Hemodynamics: A Systematic Review.

The Circle of Willis (CoW) describes the arterial system in the human brain enabling the neurovascular blood supply. Neurovascular diseases like intracranial aneurysms (IAs) can occur within the CoW and carry the risk of rupture, which can lead to subarachnoid hemorrhage. The assessment of hemodynamic information in these pathologies is crucial for their understanding regarding detection, diagnosis and treatment. Multi-dimensional in silico approaches exist to evaluate these hemodynamics based on patient-specific input data. The approaches comprise low-scale (zero-dimensional, one-dimensional) and high-scale (three-dimensional) models as well as multi-scale coupled models. The input data can be derived from medical imaging, numerical models, literature-based assumptions or from measurements within healthy subjects. Thus, the most realistic description of neurovascular hemodynamics is still controversial. Within this systematic review, first, the models of the three scales (0D, 1D, 3D) and second, the multi-scale models, which are coupled versions of the three scales, were discussed. Current best practices in describing neurovascular hemodynamics most realistically and their clinical applicablility were elucidated. The performance of 3D simulation entails high computational expenses, which could be reduced by analyzing solely the region of interest in detail. Medical imaging to establish patient-specific boundary conditions is usually rare, and thus, lower dimensional models provide a realistic mimicking of the surrounding hemodynamics. Multi-scale coupling, however, is computationally expensive as well, especially when taking all dimensions into account. In conclusion, the 0D-1D-3D multi-scale approach provides the most realistic outcome; nevertheless, it is least applicable. A 1D-3D multi-scale model can be considered regarding a beneficial trade-off between realistic results and applicable performance.

An Improved Deep Learning Model for Detecting Rice Diseases

Early detection of rice plant diseases could help to quickly eradicate numerous diseases, such as fungi, viruses, and bacteria, consequently increasing rice yield. Traditional techniques for performing this task may not be the best because they take a long time, require experienced personnel, and are susceptible to a variety of infections. As a result, machine learning and deep learning approaches have recently been utilized to overcome these issues and present a more accurate model for detecting rice plant diseases. However, the current machine learning (ML) and deep learning (DL) models for this task produce unsatisfactory results due to many constraints, including high computational expenses and overfitting. To address these limitations and obtain more accurate disease detection for rice plants, we present a hybrid model of MobileNet and DNN (HMobileNetDNN). The small size of MobileNet minimizes computing costs, while the depth and complexity of DNN improve the model's capacity to capture complicated features, yielding satisfying results. Furthermore, the proposed HMobileNetDNN is also compared to four transfer learning-based DL models, namely ResNetV2, InceptionV3, MobilenetV2, and DensNet121, using the Paddy Doctor dataset. We employ several performance metrics to assess the effectiveness and efficiency of the models, like accuracy, precision, recall, F1 score, and area under the curve. The proposed model outperformed the comparing models, achieving values of 0.918, 0.918, 0.907, 0.912, and 0.949 for accuracy, precision, recall, F1 score, and area under the curve, respectively.

Redefining Luxury Electric Cars: A Comprehensive Analysis of Faraday Future Inc.

The global automotive industry is experiencing a seismic shift towards sustainability, with electric vehicles (EVs) leading the way. Among the new entrants in this arena, Faraday Future Inc. (FF) stands out with its vision to redefine luxury electric cars. This article presents a comprehensive analysis of FF's approach, comparing it to established luxury car brands and examining the novel luxury values it introduces. FF has strategically positioned itself to cater to the growing demand for eco-friendly, technologically advanced, and luxurious EVs. The result is a holistic reimagining of the luxury EV. Key competitive advantages for FF include its team of industry experts, advanced EV technology, and savvy marketing. Furthermore, founder YT Jia's potential influence, particularly in the Chinese market, adds a powerful dimension to the company's prospects. Nonetheless, FF faces immediate financial challenges, evident in its lack of revenue juxtaposed with high operational expenses. To realize its ambitions, FF must secure substantial funding, a task complicated by YT Jia's unresolved credit issues. Despite these hurdles, FF's diverse product portfolio offers immense potential. However, the risk of delayed product launches looms in a fast-paced industry. In summary, this article explores FF's mission to redefine luxury electric cars, emphasizing its unique value propositions, competitive strengths, and financial obstacles. FF's innovative approach positions it as a promising contender in the EV market, poised to make a lasting impact on the luxury EV segment while advancing the global shift towards sustainable transportation solutions.

Репродуктивное здоровье трансгендерных людей: серия случаев из Восточной Европы и Центральной Азии

Objective: Collection of data on psychological, social, legal, and economic barriers faced by transgender (TG) and non-binary (NB) individuals when approaching reproductive healthcare in Eastern Europe and Central Asia.Semi-structured interviews were conducted with TGL and NB who had experiences in reproductive healthcare.Six interviews were conducted with respondents who had experiences of pregnancy (an undisclosed country in Central Asia), oocyte retrieval for impregnation of the partner (Russia), abortion (Kazakhstan), postponing hormone therapy to conceive a child in the future (Russia), endometrial ablation to stop menses (Georgia), and artificial insemination (Russia). TG with a male gender in identification documents and masculine appearance face difficulties when trying to make an appointment for gynecological procedures, as well as the lack of understanding on behalf of other patients. In order to avoid bureaucratic barriers and intolerant treatment, TG and NB have to turn to private clinics, resulting in high financial expenses. TG who have a male gender marker and gave birth cannot be designated as a father in the birth certificate. None of the respondents suffered from gender dysphoria because of stopping/postponing hormone therapy. One experienced gender dysphoria after treatment with feminizing hormone therapy.Conclusion. The aforementioned legal barriers can be reduced by providing access to gynecological procedures for all patients irrespective of their gender marker. Clinical practice guidelines on reproductive health should be supplemented with information on TG and NB

Solving the Vehicle Routing Problem with Multiple Trips and Simultaneous Delivery-Pickup for Drinking Water Distribution Company

Transportation is a crucial factor in distribution, as it can save up to 50% of the overall costs. The Vehicle Routing Problem with Multiple Trips and Simultaneous Delivery-Pickup (VRPMTSDP) has become one of the most important areas of logistic management. This problem is an extension of the Vehicle Routing Problem (VRP), including the following characteristics: multiple trips and simultaneous delivery-pickup. A set of homogenous vehicles is available at the depot to deliver and pick up customer’s goods. The route of each vehicle in serving customers can cover more than one trip. This research helps to solve the problems faced by the Drinking Water Distribution Company in Bandung. Currently, they face high delivery costs and frequent driver overtime when returning to the depot, resulting in high overtime expenses. This problem can be classified as VRPMTSDP, with the aim of minimizing delivery costs. We propose a Tabu Search with the initial solution obtained using Saving Matrix and Nearest Neighbor. The results show that the proposed route by the Tabu Search algorithm saves delivery costs of 11.22% rather than the company’s current route. Sensitivity analyses are presented to understand the impact of various Tabu Search operators on the delivery cost of VRPMTSDP.

Object detection and state analysis of pigs by deep learning in pig breeding

Introduction: Attack behavior is common in intensive pig breeding, where the hard conditions of the piggery can lead to illness or even death for the pigs. High labor expenses will result from manually observing and recognizing pig attack behaviors in intensive porcine breeding operations. Objective: This study aims to employ deep learning techniques to identify and classify various aggressive behaviors in pigs, enhancing monitoring efficiency in breeding facilities. Methods: A novel ladybug beetle-optimized adaptive convolutional neural network (LBO-ACNN) was proposed to recognizepig behavior in pig breeding. Pigs' object detection dataset was gathered for this investigation. The data preprocessed using discrete wavelet transform (DWT) eliminates noise from each frequency component by breaking down the image into its elements. The proposed method is implemented using Python software. The proposed method is compared to other algorithms. Result:The investigational outcome shows that the suggestedstrategy accurately identifies pig behaviors, achieving a high F1-score (93.31%), recall (92.51%), precision (94.17%), and accuracy (94.78%) demonstrating its effectiveness in monitoring and classifying behaviors in breeding facilities

Benchtop-AFP: An Exploration of Democratised Automated Fibre Placement

This paper outlines the creation and evaluation of Benchtop-AFP, an innovative approach to producing composite materials akin to Automated Fibre Placement (AFP) but without the high capital expenses typical of traditional AFP methods. This unique technique, with further refinement, could serve as a valuable tool for research and development in automated fibre placement. As a world first, it aims to democratise AFP research, particularly for institutions where access to full-scale AFP facilities is unavailable and limited due to financial, skills, or safety constraints. This article presents the new method and provides examples of samples generated using this technique.

Optimizing Waste Collection Efficiency by NodeMCU enabled Ultrasonic Trash Can Surveillance and ThingSpeak Dashboards

The use of inflexible route schedules for garbage collection results in inadequate waste disposal, posing environmental risks and incurring high operational expenses, including fuel costs and landfill fees, even when the waste containers are not completely full. This study utilizes a cost-effective Internet of Things (IoT) monitoring system to facilitate dynamic routing. The aim is to enhance the efficiency and frequency of waste collection by optimizing it based on real-time fill levels, rather than following fixed cycles. The prototype employs an ultrasonic distance sensor in conjunction with a NodeMCU ESP8266 micro-controller to detect the fill level of a trash can. The collected data is then transmitted to the ThingSpeak cloud platform. Real-time visualization dashboards display live data on waste levels in different containers, providing guidance for collection scheduling. The estimated scope entails conducting circuit simulation using Proteus, optimizing PCB layout, and developing an integrated IoT prototype connected to ThingSpeak for IoT analytics. Ultimately, integrating cost-effective IoT edge sensors such as ultrasonic ranging with cloud analytics dashboards greatly enhances effectiveness, sustainability, and intelligent allocation of resources in public trash collection. This results in economic and environmental advantages by reducing landfill overflow through the digitalization of smart cities.

Review of Mixing Mechanism and Performance of Natural Rubber with Bituminous Materials

Road degradation is a common problem in Malaysia which caused by weather changes, expanding loads as well as the effects of ageing, moisture and temperature results in high maintenance expenses on conventional bitumen pavement. Therefore, it has been recommended on the modification of bitumen as a substitute technique to address this issue and extend the pavement’s lifespan. This study addresses the inadequacy of existing solutions by focusing on the direct mixing approach and the use of pre-treatment using chemical solvent and some additives specifically on epoxidized natural rubber, natural rubber latex and cup lump natural rubber (CLNR). Additionally, this study intends to give a brief summary of how bitumen performance is improved by the inclusion of additives or modifiers by emphasizing the key attributes of modified bitumen after the addition of modifiers. Further information is also provided on the quantity and application method of each addition in order to determine the ideal value for different applications. This study will examine the use of several additives based on past research, such as polyphosphoric acid, Zychotherm, as well as the use of toluene and xylene to maintain the homogeneity of the rubberized bitumen. Studies on the usage of cup lump natural rubber (CLNR) are not common, thus future study should investigate more closely at CLNR and its mixing technique. This research contributes to the field by providing insights into the practical application of modified bitumen for sustainable road construction, especially in regions with a significant rubber industry.

Immunological studies on the effects of toltrazuril and neem extract in broiler chickens suffering from coccidiosis.

The prevalence of avian coccidiosis in the poultry industry has grown, resulting in substantial financial losses from high mortality, stunted growth, reduced productivity, and expensive medical expenses. The purpose of the current study was to assess the immunological effects of neem leaf extract and toltrazuril on broilers that had contracted coccidiosis. In this investigation, 100 one-day-old Cobb broiler chicks without sexes were employed. The chicks were divided into five equal groups, with 20 birds in each. On the 14th day of life, the birds in groups 2, 3, 4, and 5 received an oral inoculation with 1 × 105 sporulated oocysts of Eimeria tenella (E. tenella) (field isolate). The first group (Gp), which consists of 20 healthy broilers, served as a negative control. Gp (2) contains experimentally infected broilers and nontreated (served as a positive control). Gp (3) contains experimentally infected broilers treated with toltrazuril (1 ml/l drinking water) for two consecutive days. Gp (4) contains experimentally infected broilers treated with neem leaf extract 4% (50 ml/l drinking water) for 5 successive days, and Gp (5) contains experimentally infected broilers treated with toltrazuril (1 ml/l drinking water) and a half dose of neem leaves extract 4% (25 ml/l drinking water) for 5 successive days. For the purpose of estimating body weight growth and feed conversion ratio, each broiler was weighed separately at the start of the trial and again on the 1st and 10th day after treatment. In addition to obtaining intestinal samples for immunohistochemistry, blood samples were also obtained for immunological examination. As compared to the negative control group, the experimentally infested broilers with E. tenella showed significant decreases in serum nitric oxide, lysosome, phagocytic percent, and phagocytic index, along with significant increases in white blood cells (WBCs), lymphocyte, heterophilis, eosinophilis, basophilis, monocyte, serum total protein, γ globulin, fibrinogen, and haptoglobin. When compared to the control positive group, experimentally infested broilers treated with either neem or toltrazuril alone or in combination demonstrated significant increases in serum total protein, nitric oxide, lysozyme, phagocytic percent, and phagocytic index, but significant decreases in WBCs, lymphocytes, heterophile, eosinophile, basophile, and monocyte. The intestinal peroxidase stain of broilers infected with E. tenella exhibited a significant positive expression for CD4, but the infected broilers treated with toltrazuril and half a dosage of neem displayed a negative expression for CD4, identical to the negative control. The broiler chickens infested with E. tenella may have a variety of negative impacts on their immune systems and immunohistopathological findings. Nonetheless, toltrazuril and neem extract, either separately or in combination, function as anticoccidial medications that may enhance the broiler chicks' immune state.

Advances in CCU Methods: Handling Release of Carbon for the Impact of Climate Change

The escalating atmospheric concentrations of carbon dioxide (CO2) due to human pursuit which includes fossil fuel combustion, deforestation, and industrial production make contributions considerably to international warming and climate change. Carbon capture and storage (CCS) and carbon capture and usage (CCU) technology provide viable solutions for mitigating those emissions. This paper critiques various CCS and CCU techniques that specialize of their ability applications, stressful situations, and environmental impacts. While CCS technologies provide promising consequences in decreasing international warming capability, they're associated with better acidification and human toxicity in comparison to standard techniques. Alternatively, CCU technologies present an opportunity to convert CO2 into valuable products, thereby imparting a sustainable approach to greenhouse gas reduction. But, these technology face challenges consisting of high expenses, energy consequences, and the need for social recognition. This study provides a comprehensive assessment of modern CCS and CCU technologies, evaluates their environmental affects, and discusses future prospects for their implementation in reducing industrial CO2 emissions.

Prevalence of Musculoskeletal Pain among Chefs Working in Restaurants of Sialkot

Musculoskeletal pain is a pain coming from the structures such as bones, muscles, joints, tendons, and ligaments, clearly becoming more and more common. In addition to having a detrimental effect on a person's life quality, MSK pain's high healthcare expenses and concomitant loss of productivity have placed a heavy financial burden on societies. Objective: To find the prevalence of musculoskeletal pain among the chefs working in restaurants in Sialkot. Methods: The cross-sectional/observational survey study was conducted for 4 months and convenient sampling technique was used on chefs working in restaurants of Sialkot. Results: This study assessed prevalence and level of pain among chefs of different restaurants in Sialkot. This study included 178 participants with age range varied from 25 to 50 years. 61.2% of participants aged 25-29 years. 63.5% of participants were among those having 8 to 10 working hours. 24.7% of the participants had weight ranging from 55 to 59 kg. 58.4% of participants had mild pain. Duration of job of most of participants (40.4%) was 2 to 6 years. Most participants (20.8%) were having trouble in ankle/feet, (16.3%) had trouble in knees and lower back. Conclusions: We found that muscle and skeletal pain in chefs working in different restaurants of Sialkot most probably in ankles/feet, knees and low back. The pain was found to be mild on Numeric Pain Rating Scale (NPRS) mostly in male chefs of middle age with ideal weight.

RETROFITTING OUTDATED PYRANOMETER FOR IoT INTEGRATION TOWARDS A CIRCULAR ECONOMY MODEL

An innovative way of applying the circular economy concept in the obsolete research equipment domain is by repairing and upgrading critical subcomponents of the initial equipment, for reuse purposes. Thus, a large percentage of environmental waste is reduced, resulting from the whole process of manufacturing a brand new modern one, along with the implied purchasing costs, while serving its intended purpose simultaneously. The whole re-engineering process produces increased overall cost efficiency, by massively reducing the raw material requirements, the electrical energy consumption for design and manufacture, and the resulting waste material. In this respect, the article addresses the inherent issues in retrofitting an old model analog signal pyranometer, designed in the ‘90s. The upgrade initiative aims to massively increase the digital processing speed, the quality, and the quantity of the data acquisition, while also providing an integrated local storage solution and wireless access through a designated IP address using a web interface, for data interrogation in real-time. All these are done at low costs, with market-available materials, to avoid any high expenses related to acquiring new ones.

Smart contract applications in the built environment: How prepared are Nigerian construction stakeholders?

Studies have demonstrated that advanced technology, such as smart contract applications, can enhance both pre- and post-contract administration within the built environment sector. Smart contract technology, exemplifying blockchain technologies, has the potential to improve transparency, trust, and the security of data transactions within this sector. However, there is a dearth of academic literature concerning smart contract applications within the construction industries of developing countries, with a specific focus on Nigeria. Consequently, this study seeks to explore the relevance of smart contract technology and address the challenges impeding its adoption, offering strategies to mitigate the obstacles faced by smart contract applications. To investigate the stakeholders, this research conducted 14 virtual interview sessions to achieve data saturation. The interviewees encompassed project management practitioners, senior management personnel from construction companies, experts in construction dispute resolution, professionals in construction software, and representatives from government construction agencies. The data obtained from these interviews underwent thorough analysis employing a thematic approach. The study duly recognizes the significance of smart contract applications within the sector. Among the 12 identified barriers, issues such as identity theft and data leakage, communication and synchronization challenges, high computational expenses, lack of driving impetus, excessive electricity consumption, intricate implementation processes, absence of a universally applicable legal framework, and the lack of a localized legal framework were recurrent impediments affecting the adoption of smart contract applications within the sector. The study also delves into comprehensive measures to mitigate these barriers. In conclusion, this study critically evaluates the relevance of smart contract applications within the built environment, with a specific focus on promoting their usage. It may serve as a pioneering effort, especially within the context of Nigeria.

IoT sensor nodes for air pollution monitoring: A review

Air quality is an important environmental concern, as it is strictly related to human health risks and adverse eff ects on it. Monitoring air pollutants and diff erent ancillary parameters is a feasible and crucial approach to address this challenge. This task typically involves high expenses in case measurements are carried out by using conventi onal measurement instruments and human operators. However, uti lizing measurement systems with low-cost sensors can reduce the overall implementati on eff ort. The aim of this paper is to describe the sensor node architecture applicable to a general monitoring system and based on this structure, review diff erent current low-cost measurement system proposals for outdoor air quality monitoring.

The importance and political and economic position (Silk Road) of China (review, goals, obstacles and challenges)

Today, as a vast continent, Asia is facing new developments and various actors have presented plans to achieve their goals in its various regions. China is one of these emerging players that have proposed the plan to revive the Silk Road in order to become a world power. This route represents a fundamental element of China's foreign policy strategy aimed at extending its sphere of influence to diverse regions. Revealed by the head of state of China in September 2013, this initiative encompasses around 4.4 billion individuals, constituting 65 percent of the global population, and involves a substantial portion of the world's gross production, totaling 21 trillion and it consists of two parts of the Economic Belt and Road. "New" "Maritime Silk Road" has been formed. China's effort and interest in promoting such grand projects, apart from the fact that it can have new economic and political effects for this country, can also expand more and more in China's foreign policy. Qash should have a more active area. The competition between China and America in the international economy shows the increasing influence of China in the Asian economy and the spectacular growth of China's economic and commercial activities in Africa compared to other powers, especially the United States. By revitalizing the silk road and drawing an economic belt, China will have access to world roads. Facilitation and expansion of an international and reliable transport corridor with affordable costs has been developed in the direction of its national interests. Based on this, the authors of this article raise their question as to whether China's innovations, despite what the Beijing authorities have said, can appear in practice, or whether the obstacles on the way of these plans prevent them from coming to fruition. Will you come? Our conjecture is that owing to the excessively high expenses, China's plans and the disruptions that the United States may create in competition with Beijing, and also due to some environmental problems and lack of support. The likelihood of success for these plans appears doubtful, at least in the foreseeable future.

Empirical analysis of tree-based classification models for customer churn prediction

Customer churn is a vital and reoccurring problem facing most business industries, particularly the telecommunications industry. Considering the fierce competition among telecommunications firms and the high expenses of attracting and gaining new subscribers, keeping existing loyal subscribers becomes crucial. Early prediction of disgruntled subscribers can assist telecommunications firms in identifying the reasons for churn and in deploying applicable innovative policies to boost productivity, maintain market competitiveness, and reduce monetary damages. Controlling customer churn through the development of efficient and dependable customer churn prediction (CCP) solutions is imperative to attaining this goal. According to the outcomes of current CCP research, several strategies, including rule-based and machine-learning (ML) processes, have been proposed to handle the CCP phenomenon. However, the lack of flexibility and robustness of rule based CCP solutions is a fundamental shortcoming, and the lopsided distribution of churn datasets is deleterious to the efficacy of most traditional ML techniques in CCP. Regardless, ML-based CCP solutions have been reported to be more effective than other forms of CCP solutions. Unlike linear-based, instance-based, and function-based ML classifiers, tree-based ML classifiers are known to generate predictive models with high accuracy, high stability, and ease of interpretation. However, the deployment of tree-based classifiers for CCP is limited in most cases to the decision tree (DT) and random forest (RF). Hence, this research investigated the effectiveness of tree-based classifiers with diverse computational properties in CCP. Specifically, the CCP performances of diverse tree-based classifiers such as the single, ensemble, enhanced, and hybrid tree-based classifiers are investigated. Also, the effects of data quality problems such as the class imbalance problem (CIP) on the predictive performances of tree-based classifiers and their homogeneous ensemble variants on CCP were assessed. From the experimental results, it was observed that the investigated tree-based classifiers outperformed other forms of classifiers such as linear-based (Support Vector Machine (SVM)), instance-based (K-Nearest Neighbour (KNN)), Bayesian-based (Naïve Bayes (NB)) and function-based (MultiLayer Perceptron (MLP)) classifiers in most cases with or without the CIP. Also, it was observed that the CIP has a significant effect on the CCP performances of investigated tree-based classifiers, but the combination of a data sampling technique and a homogeneous ensemble method can be an effective solution to CIP and also generate efficient CCP models.

Compact, efficient, and affordable absorption Carnot battery for long-term renewable energy storage

The growing penetration of renewable energy poses significant challenges to the stability of the power grid, necessitating the development of advanced energy storage systems to facilitate power grid decarbonization with enhanced flexibility. Nonetheless, current energy storage technologies face obstacles including geographical constraints, high expenses, and short lifespans. In this work, a novel Carnot battery (power-heat-power conversion) based on absorption-desorption processes of hygroscopic salt solutions, absorption Carnot battery (ACB), is proposed for large-scale renewable energy storage with remarkable energy storage density (ESD), competitive round-trip efficiency (RTE), and negligible self-discharging rate (SDR). Through the integration of heat-generation, heat-storage, and power-generation sub-cycles into a single compact system, the ACB can save space and cost compared to previous Carnot batteries. A dynamic model is established with high accuracies to explore the characteristics of the proposed system. The dynamic temperatures, pressures, concentrations, mass flow rates, powers, and efficiencies of the ACB are analyzed to elucidate its energy conversion/storage mechanism. Based on the multi-objective optimization, the optimum operating concentration range of [45%, 60%] is determined, demonstrating the best comprehensive performance with an RTE of 45.80% and an ESD of 16.26 kWh/m3. Compared to the existing energy storage systems, the ACB stands out due to the competitive RTEs (30.5%–48.4%) and higher ESDs (7.6–21.8 kWh/m3). Even during an 80-day standby period, the ACB exhibits a small SDR of only 0.74%, which is significantly lower than that of Rankine pumped thermal energy storage (RPTES) at 33.01%. Despite the ACB yields a higher initial cost, it demonstrates a markedly lower levelized cost of storage (0.342 $/kWh) compared to the RPTES (0.749 $/kWh) because of its higher ESD, thus confirming the economic feasibility of the proposed system.

Generation of Green Carbon Nanomaterials from Biomass Pyrolysis for the Production of Biofuel and Bioenergy

The need to find a Renewable Energy Resource (RER) with significant potential has been brought to light by the fact that petroleum and natural gas are being used up to their full capacity, reducing the amount of energy produced globally. The issues relating to the preparation, hydrolysis with enzymes, and biomass culture processes that must be completed before bioenergy may be produced are still being addressed via ongoing initiatives. Because nanotechnology offers unique active areas for multiple responses and operations, it can overcome the difficulties posed by these biomass sources. Pyrolysis may be used to produce chemicals and RER from biomass sustainably. However, the process's high production expenses prevent it from being widely used. This approach's long-term reliability and financial viability may be greatly increased by fabricating high-quality, active carbon nanoparticles using waste heat and renewable progenitors. This paper suggests using Biomass Pyrolysis to Generate Green Carbon Nanomaterials (BP-GGCN) for biofuel and bioenergy production. The suggested method makes the most of biomass pyrolysis's financial gains and sustainability by producing superior Three-Dimensional Graphene Bubbles (3DGBs) using residual pyrolysis gases and thermal waste. The resultant 3DGBs work well in energy storage and ecologically sensitive applications. According to a life-cycle study, the current approach has less overall effect than the traditional Chemical Vapour Deposition (CVD) technique on human well-being, environmental systems, and resources. The specific qualities of this GGCN help biofuels, biodiesel, enzymes, and microbial fuel cells work better.