Problem Of Shortage Research Articles

Ecohydrological investigation of cloud seeding effect on vegetation activity in the Boryeong Dam Basin, South Korea

Cloud seeding is well known to address water shortage problems caused by droughts by adding more precipitation and consequent runoff. Unlike previous studies, this study investigates another positive effect of cloud seeding on the activation of vegetation by integrating numerical cloud seeding simulations and processed-based modeling of various ecohydrological components. As the carbon cycle is closely related to the hydrological processes in ecosystems, we adopt the RHESSys ecohydrological modeling to synthetically simulate runoff and soil moisture along with primary productivity and vegetation respiration. Numerical simulations with and without cloud seeding are generated by the WRF-ARW model for the Boryeong Dam basin, one of the basins vulnerable to droughts, in 2021. The cloud seeding simulations of two cases are input into the RHESSys model to examine changes in hydrological and ecological components due to the added amount of precipitation. The results exhibit significant increases in annual precipitation (18 %) and runoff (22 %), and enhanced soil moisture stimulating the ecological components such as GPP and NPP, especially in spring. Cloud seeding can be considered to create optimal conditions for vegetation to absorb or sequester carbon from the atmosphere, thereby boosting vegetation growth. Additionally, the time-lagged correlations between cloud seeding and soil moisture, GPP, NPP, and respiration suggest that vegetation activity is highly dependent on antecedent 1–2 months occurrences of cloud seeding. This study implies that the cloud seeding effect on additional NPP can be considered as a countermeasure of the global average forest loss, which means that carbon emission rise in the global warming era can be partly alleviated by cloud seeding.

Glass-Blowing-Inspired Upcycling of Thermosetting Polymer to Neuron-Like Hierarchical Carbon for Microwave Absorption and Conversion.

Upgrading thermosetting polymer waste and harvesting unwanted electromagnetic energy are of great significance in solving environmental pollution and energy shortage problems. Herein, inspired by the glass-blowing art, a spontaneous, controllable, and scalable strategy is proposed to prepare hollow carbon materials by inner blowing and outside blocking. Specifically, hierarchically neuron-like hollow carbon materials (HCMSs) with various sizes are fabricated from melamine-formaldehyde sponge (MS) waste. Benefiting from the synergistic of the hollow "cell body" and the connected "protrusions" networks, HCMSs reveal superior electromagnetic absorption performance with a strong reflection loss of -54.9dB, electromagnetic-heat conversion ability with a high conversion efficiency of 34.4%, and efficient energy storage performance in supercapacitor. Furthermore, a multifunctional device integrating electromagnetic-heat-electrical energy conversion is designed, and its feasibility is proved by experiments and theoretical calculations. The integrated device reveals an output voltage of 34.5mV and a maximum output power of 0.89 µW with electromagnetic radiation for 60s. This work provides a novel solution to recycle polymer waste, electromagnetic energy, and unwanted thermal energy.

Effects of Rice-Frog Co-Cropping on the Soil Microbial Community Structure in Reclaimed Paddy Fields.

Utilizing and improving the productivity of reclaimed land are highly significant for alleviating the problem of food production shortage in China, and the integrated rice-frog farming model can improve soil fertility. However, there are few studies on the use of integrated rice-frog farming technology to improve the fertility of reclaimed land and increase its efficiency in food production. Therefore, this study was conducted to evaluate the effects of the rice-frog co-cropping mode on the soil fertility and microbial diversity of reclaimed land. A rice monoculture group (SF), low-density rice-frog co-cropping group (SD, 5000 frogs/mu, corresponds to 8 frogs/m2), and high-density rice-frog co-cropping group (SG, 10,000 frogs/mu, corresponds to 15 frogs/m2) were established and tested. The contents of total nitrogen, soil organic matter, available potassium, and available phosphorus of the soil in the SG group were significantly higher than those in the SF group (p < 0.05) in the mature stage of rice. Compared with the SF group, the SD and SG groups improved the soil microbial diversity and changed the structure of the microbial community. This study indicates that compared with the rice monoculture mode, the rice-frog co-cropping pattern can improve the soil fertility, as well as microbial diversity, of reclaimed land.

The Hidden Reserve of Nurses in The Netherlands: A Spatial Analysis.

Worldwide, nurse shortages constitute a problem, including in the Netherlands. Every region in the country has a shortage of all types of nurses. At the same time, there are large hidden reserves: persons who have been trained as a nurse but do not work in the healthcare sector. The size of the hidden reserve exceeds the shortage of nurses. Until now, the literature has not paid much attention to spatial aspects of the nursing shortage problem. In this paper, we analyze the size of the hidden reserves and how they are distributed over the country, across large and smaller cities, and across different nurse categories. We find that especially densely populated areas have relatively small shares of trained nurses as well as large hidden reserves relative to their population. These areas are also facing the largest nurse shortages. As nurse labor markets are local, policies that are more focused on local situations are necessary to activate these hidden reserves.

Synthesis and photocatalytic properties of Cerium(IV) oxide graphene oxide composites

Semiconductor photocatalytic technology is a simple, efficient, and low-cost method for environmental pollution remediation. Cerium dioxide (CeO2), as a promising oxidative degradation photocatalyst, can solve the problems of energy shortage and environmental pollution. In this paper, cerium dioxide/graphene oxide composites were successfully synthesized by a one-pot hydrothermal method, achieving a degradation rate of 88.96 % for rose red dye in 150 min, and the introduction of reduced graphene oxide effectively improves the photocatalytic performance of pure cerium oxide.

Sponge City Development from the Perspective of Sustainability: A Case Study of China

Traditional urban construction methods often result in the inability of rainwater to penetrate and store effectively, increasing the risk of urban flooding disasters. At the same time, due to the rapid development of urbanization, the problem of water shortage has become increasingly prominent. The sponge city policy aims to transform the urban construction mode, make full use of natural resources and ecological means, realize the natural accumulation, infiltration and purification of rainwater, and improve the city's absorption, storage and release capacity of rainwater, so as to reduce urban flood disasters and alleviate the shortage of water resources. This paper takes China as an example to explore the construction of a sponge city from the perspective of sustainable development. This paper analyzes the current situation and existing problems of sponge cities development in China, and puts forward the development prospect of PPP model, in order to promote sponge cities construction and sustainable urban development.

Gate Assignment Algorithm for Airport Peak Time Based on Reinforcement Learning

In existing airport gate allocation studies, little consideration has been given to situations where gate resources are limited during peak periods. Under such circumstances, some flights may not be able to make regular stops. In this paper, the airport gate assignment problem under peak time is investigated. We propose a gate pre-assignment model to maximize the gate matching degree and the near gate passenger allocation rate. Besides, to minimize the pre-assignment gate change rate, we propose a dynamic reassignment model based on the pre-assignment model. By considering the non-deterministic polynomial hard (NP-hard) property of this problem, a gate assignment algorithm based on proximal policy optimization (GABPPO) is proposed. The simulation results show that the algorithm can effectively solve the gate shortage problem during the airport peak period. Compared with the adaptive parallel genetic, deep Q-network, and policy gradient algorithms, the target value of solutions obtained by the proposed algorithm in the near gate passenger allocation rate is increased by 5.7%, 3.6%, and 7.9%, respectively, and the target value in the gate matching degree is increased by 10.6%, 4.9%, and 11.5% respectively.

Self-supervised dynamic and static feature representation learning method for flotation monitoring

Froth flotation is a widely used beneficiation method in mineral processing. Accurate grade monitoring is crucial for efficient minerals separation. However, despite recent developments highlighting the potential of deep learning in flotation monitoring, these methods face limitations in application due to the lack of reliable feature extraction and the scarcity of large datasets related to target task. To address these issues, we propose a self-supervised dynamic and static feature collaborative representation learning method. It extracts the spatiotemporal information from froth videos based on a two-stream convolutional architecture and is trained on a video frame prediction task without labeled data until both appearance and motion constraints are satisfied. Experiments on industrial zinc flotation data demonstrate that the learned representations transfer well to downstream grade monitoring tasks. This approach not only solves the label shortage problem when training large-scale deep learning models but also outperforms the state-of-the-art methods in flotation monitoring.

ТЕХНІКО-ЕКОНОМІЧНЕ ОБҐРУНТУВАННЯ ДОЦІЛЬНОСТІ ЗАСТОСУВАННЯ АСФАЛЬТОБЕТОННИХ ШАРІВ ІЗ ЗОЛОЮ ВИНЕСЕННЯ

Introduction. The road construction industry is currently one of the strategic industries of Ukraine, and the issue of quality and availability of basic building materials for road construction is particularly topical, which is directly related to its high material intensity. The known reserves of high-quality raw materials that could be used as asphalt concrete components are constantly decreasing, so it is necessary to look for alternative sources of raw materials for construction materials and explore the possibility of their use. In this regard, the most efficient use of local raw materials is the use of industrial waste, which can be one of the solutions to the problem of shortage of raw materials of inorganic origin. Problem statement. In road construction, when repairing or arranging road pavement layers, in particular asphalt mixtures, the need for carbonate mineral fillers, which are scarce in some regions, is constantly growing. Industrial by-products can be an alternative. One of these materials is fly ash from thermal power plants, which can be used instead of mineral fillers in asphalt mixtures. Objective. To perform a feasibility study of the use of asphalt concrete layers with fly ash. Materials and Methods. Analysis of information sources and the materials market of Ukraine and calculation of the technical and economic efficiency of fly ash application in asphalt mixtures.

Blast resistance performance and failure modes of prestressed thin-walled aqueducts subjected to underwater contact explosion

To solve the problem of regional water resource shortage, water diversion projects have been built around the world. As an essential lifeline project, the prestressed aqueduct is commonly used in cross-regional water transfer and diversion projects. However, the prestressed aqueduct is inclined to damage and collapse under explosion loading due to its thin structure. The main purpose of this paper is to investigate the nonlinear dynamic performance and failure modes of the large prestressed U-shaped thin shell aqueduct to underwater contact explosion. The prestress application approach is validated by theoretical calculations. The reliability of the analysis method of underwater contact explosion for reinforced concrete structures is verified by the underwater contact explosion test. Damage cracking process and nonlinear dynamic response characteristics of prestressed aqueducts to the underwater contact explosion with different explosive weights are performed. Blast resistance performances of prestressed aqueducts are discussed in terms of the crack length, residual displacement, and prestressing force loss. The influence of prestress level on the damage modes of the prestressed aqueduct under the blast loading is discussed. The results indicate that thin-walled U-shaped structures are extremely vulnerable to localized damage from underwater contact explosions. The blast-resistance performance of the U-shaped thin shell aqueduct can be significantly improved by applying prestress.

Can Environmental Information Disclosure Improve Energy Efficiency in Manufacturing? Evidence from Chinese Enterprises

Improving the energy efficiency of enterprises is one of the key means to solve the problem of energy shortage. It is of great significance to investigate how environmental information disclosure (EDI) promotes the green total factor energy efficiency (GTFEE) of enterprises. Based on this, this study calculates the GTFEE of enterprises by combining the database of Chinese manufacturing and the pollutant emission of industrial enterprises and investigates the impact of EDI on the GTFEE of manufacturing industries by using a difference-in-difference model. The following is found: (1) EDI can significantly promote the manufacturing enterprises’ GTFEE, and the results are still valid after a series of robustness tests; (2) Mechanism analysis shows that EDI can improve the GTFEE of manufacturing enterprises by promoting technological innovation and optimizing energy structure; (3) The heterogeneity analysis shows that EID is more positive on firms’ GTFEE in the eastern than western regions. The positive impact is greater for non-state-owned, low-energy consumption, export, and polluting enterprises. The findings of this paper provide a theoretical basis and practical enlightenment for the government to promote the green development transformation of enterprises.

Iron-doped biochar, an agricultural and environmentally beneficial fertilizer.

The utilization of agricultural waste to create value-added goods has benefited waste management while resolving cost-effectiveness and food shortage problems. Returning biochar produced from agricultural waste to the agricultural field is a sustainable method of enhancing crop production while lowering the environmental effect of typical fertilizers. It also enhances soil condition by modulating pH, soil organic carbon, water retention capacity, and soil ion exchange potential. The current work concentrated on the production of iron oxide-loaded biochar from banana peels. Pyrolysis was carried out at temperatures ranging from 400 to 500°C. The co-precipitation technique was utilized to impregnate Fe3O4 nanoparticles on biochar, and it showed to be an effective and trustworthy method. Loading was done in situ. Characterization techniques such as XRD, FTIR, CHNS, and TGA were employed to characterize synthesized materials. Swelling ratio, water retention, absorbance, and equilibrium water content percentage were used to study the adsorption capabilities of Fe3O4-loaded biochar, soil, and raw biochar. As a consequence, Fe3O4-enriched biochar was shown to have better adsorption capability than raw biochar, which in turn showed better adsorption properties than soil. Iron-loaded biochar was employed as a fertilizer in Abelmoschus esculentus (Okra), and the results showed that it is a cost-effective, environmentally friendly fertilizer.

Recent advances in solid–liquid triboelectric nanogenerator technologies, affecting factors, and applications

Converting dispersed mechanical energy into electrical energy can effectively improve the global energy shortage problem. The dispersed mechanical energy generated by liquid flow has a good application prospect as one of the most widely used renewable energy sources. Solid–liquid triboelectric nanogenerator (S–L TENG) is an inspiring device that can convert dispersed mechanical energy of liquids into electrical energy. In order to promote the design and applications of S–L TENG, it is of vital importance to understand the underlying mechanisms of energy conversion and electrical energy output affecters. The current research mainly focuses on the selection of materials, structural characteristics, the liquid droplet type, and the working environment parameters, so as to obtain different power output and meet the power supply needs of diversified scenarios. There are also studies to construct a theoretical model of S–L TENG potential distribution mechanism through COMSOL software, as well as to obtain the adsorption status of different kinds of ions with functional groups on the surface of friction power generation layer through molecular dynamics simulation. In this review, we summarize the main factors affecting the power output from four perspectives: working environment, friction power generation layer, conductive part, and substrate shape. Also summarized are the latest applications of S–L TENG in energy capture, wearable devices, and medical applications. Ultimately, this review suggests the research directions that S–L TENG should focus on in the future to enhance electrical energy output, as well as to expand the diversity of application scenarios.

Thermo-mechanical Stability Analysis of Hollow Cellular Concrete Block Air Convection Embankments for Cold Regions

Crushed-rock air convection embankment (ACE), as a highly open-graded porous medium, has been used to mitigate the thaw settlement of pavement structures in permafrost regions. Previous studies have revealed that cellular concrete has significant potential as a cost-effective material for ACE to solve the problem of crushed rock shortage in interior Alaska and improved the thermal stability of pavement structures in cold climates. The design configurations of the hollow cellular concrete block ACE were further designed to maximize the performance benefits and facilitate future implementation and field construction. However, the mechanical behaviors of the proposed structures and ice-rich subgrade were still unknown. In this study, a thermo-mechanical coupling model was developed to evaluate the thermal effect on the long-term mechanical stability of the selected pavement structures and subgrade soils. The results indicated that the thermal stability of the proposed hollow cellular concrete block ACEs was superior to that of the conventional crushed-rock ACE. The maximum thaw settlement of the proposed hollow cellular concrete block ACE was only 13.4% that of the conventional crushed-rock ACE. Thermal and mechanical analyses showed that the proposed cellular concrete ACEs have a significant advantage over conventional crushed-rock ACE.

Comparative experimental study on photothermal conversion and shape memory properties of MF-based flexible composite phase change materials loaded with carbon nanotubes and polydopamine

Efficient use of solar energy can effectively alleviate the problem of energy shortages. Currently, extensive researches have been carried out on photothermal conversion materials. However, factors such as photothermal conversion and thermal conductivity limit the practical implementation of photothermal materials. In this research, a novel flexible composite phase change material (CPCM) with melamine foam (MF) as the supporting skeleton, carbon nanotube (MWCNT)/polydopamine (PDA) as the light-absorbing coating and polyethylene glycol (PEG) as the energy storage material was successfully prepared. The results show that the MF-based CPCMs have good shape stability with a leakage of only 0.9 %, and high phase change enthalpies, the melting enthalpy was above 172.0 J/g. In addition, the thermal conductivity was improved due to the introduction of light-absorbing coatings into the CPCMs. Compared with MF/PEG, MWCNT/MF/PEG, and PDA/MF/PEG, MWCNT/PDA/MF/PEG were improved by 35.21 %, 8.6 % and 29.46 %, respectively. Finally, the average charging efficiency of MWCNT/PDA/MF/PEG is 96.26 %, which is 62.33 % and 20.1 % higher than that of MWCNT/MF/PEG and PDA/MF/PEG respectively, indicating that MWCNT and PDA nanofillers played a synergistic role in enhancing the performance of CPCMs. This study provides new and innovative ways for the design of photothermal materials.

НОВЫЕ РОЛИ РАБОТНИКОВ В УСЛОВИЯХ ЦИФРОВОЙ ТРАНСФОРМАЦИИ ПРОМЫШЛЕННОСТИ

Global changes taking place in the economy under the influence of digitalization and automation are inevitable, and society needs to accept and take into account their positive and negative aspects. The research objective is to study the structure and specifics of the interaction between people and technology and the impact of new technologies on the work environment and process, highlighting the positive and negative aspects. The theoretical and methodological basis of the study is the work of domestic and foreign researchers devoted to issues of digitalization and automation in industry, opportunities and threats of the transition to Industry 5.0. Results. The main idea of the concept is human-centricity – people and artificial intelligence as a team. This will ensure sustainable and stable production, reducing costs in the future. The structure of this interaction between the two subsystems affects the productivity and efficiency of the entire system, as well as the health, motivation and satisfaction of employees and has a positive impact on future development. It is emphasized that collaboration between humans and machines is aimed at leveraging the unique strengths of each participant. Automation is not about replacing humans, but about expanding their capabilities. This is especially true for tasks that require creativity, critical thinking, and complex decision making – areas that require human intuition and ingenuity. The subject of the study of the Industry 5.0 concept was the new role of people in the production process. The human worker is more connected to information and less vulnerable to attack thanks to technology. The object of the study was digital technologies that help, first of all, to solve the main problem of labor shortages by transferring complex and tedious tasks to robots. This allows people to concentrate and develop more informed management decisions. Thanks to advanced analytics and artificial intelligence, manufacturers can understand the individual needs and preferences of customers. This data is then used to customize products during production, provi¬ding a level of personalization that was previously considered impractical at scale. Mass customization allows for a wider range of product types to be produced without huge amounts of waste and pollution because such customization can be done on the same production lines using reused materials and components. Conclusion. The article summarizes the advantages of Industry 5.0: reduced time and increased efficiency of processes, their visibility and transparency in real time, high customer satisfaction, better occupational safety and greater risk management capabilities, ergonomics and environmental sustainability. The biggest barriers to technology adoption are also highlighted: high investment costs, as well as integration and lack of qualified employees.

Dysregulation of Immune Tolerance to Autologous iPSCs and Their Differentiated Derivatives.

Induced pluripotent stem cells (iPSCs), capable of differentiating into any cell type, are a promising tool for solving the problem of donor organ shortage. In addition, reprogramming technology makes it possible to obtain a personalized, i.e., patient-specific, cell product transplantation of which should not cause problems related to histocompatibility of the transplanted tissues and organs. At the same time, inconsistent information about the main advantage of autologous iPSC-derivatives - lack of immunogenicity - still casts doubt on the possibility of using such cells beyond immunosuppressive therapy protocols. This review is devoted to immunogenic properties of the syngeneic and autologous iPSCs and their derivatives, as well as to the reasons for dysregulation of their immune tolerance.

Optimizing the model-prediction of date palm fronds-derived producer gas and third generation biodiesel powered dual-fuel engine by employing Bayesian-optimized Boosted Regression Trees for enhanced prognostics

The global issue concerning the dual problem of economic energy shortage as well as greenhouse gas emission needs urgent attention. Due to its abundance and carbon neutrality, waste biomass is a good energy conversion feedstock. This research suggests a unique method for using date palm frond waste biomass-derived producer gas and algal biodiesel as sustainable diesel engine fuels. The Bayesian-optimized neural networks and Bayesian-optimized Boosted Regression Trees were employed to optimize engine combustion and emission performance. This was further enhanced with the application of k-cross fold to prevent the model from overfitting during training. The working of dual-fuel engines is a complex phenomenon owing to the employment of two different types of fuel one is liquid (biodiesel + diesel) while the other one is gaseous (Producer gas). The present endeavor was undertaken to handle this with the application of advanced data learning methods. The engine was tested at different compression ratios, engine loads, and fuel injection pressures for brake thermal efficiency, diesel fuel substitution, and emission. Both the Bayesian-optimized neural networks and Bayesian-optimized Boosted Regression Trees could predict the engine output with good prediction efficiency with comparable performance, however, the Bayesian-optimized Boosted Regression Trees-based models were more robust with a coefficient of determination value in the range of 0.9617–0.9999 and mean squared errors as low as 0.001. The mean absolute percentage error was very low in the range of 0.0316–5.231. The Theil’s U2 values were in the range of 0.0029–0.0126.

Preparation of natural N/O/S co-doped biomass-derived carbon materials for supercapacitors using multistage gas self-exfoliation effect

High-value utilization of biomass provided a feasible way to solve the energy shortage and environmental problems. The preparation of micro-mesoporous composite carbon materials from biomass waste as feedstock using a multistage gas self-exfoliation mechanism (CH3COOK and Ca2(C2H5COO)2) was a feasible approach. Among them, the N, O and S co-doped carbon materials were obtained in this paper by using forestry waste (bamboo) as raw material, spiral algae as green heteroatom dopant, Ca2(C2H5COO)2 as multifunctional template agent, and CH3COOK as gentle activator. The results indicated that BC-SA-0.5CP exhibited 324.85 F/g at 0.5 A/g. The symmetric supercapacitor (BSC-0.5//BSC-0.5) achieved 96.02% capacitance retention after 10,000 cycles, indicating excellent rate performance and charge/discharge stability. At a power density of 162.5 W/kg, the BSC-0.5//BSC-0.5 had an energy density of 14.67 Wh/kg. In addition, it was deeply analyzed the growth mechanism of heteroatoms, the formation mechanism of porous carbon and the electron transfer routes, which provided a theoretical basis for the preparation of biomass-derived carbon materials. Overall, this study demonstrated that the multistage gas self-exfoliation mechanism was beneficial in promoting the formation of micro-mesoporous composite structures and the growth of heteroatom functional groups, which ultimately provided a new route for the synthesis of natural heteroatom-doped porous carbon.

Drug Classification and Repurposing Using Decision Tree Algorithm and Data Analysis

Abstract: Fundamentally, drugs are substances that exhibit the capacity to alter biological functions, often serving as interventions to mitigate ailments or enhance physiological processes. However, the landscape of drug development and usage is undergoing transformation, fueled by innovative strategies that hold the promise of revolutionizing healthcare solutions. This research paper explores drug classification and repurposing through the utilization of decision tree algorithms and data analysis. Specifically, the aim is to classify drugs into three distinct types: Drug X which is most used drugs, Drug Y which is less frequently used drugs, and Drug C includes drugs like narcotics. Decision tree algorithms are employed to discern the defining attributes that categorize drugs into these types. By analyzing comprehensive datasets encompassing drug properties, interactions, and clinical outcomes, the study harnesses decision tree models to predict drug classifications accurately. This approach holds the potential to accelerate drug discovery, optimize treatment strategies, and contribute to more efficient healthcare solutions. The proposed algorithm is compared with both Naïve Bayes and K - Nearest Neighbors algorithms to prove it is more accurate. Ultimately, the significance of this paper transcends the boundaries of conventional drug development paradigms and to overcome the problem of shortage of drugs.