Efficient Resource Utilization Research Articles

A Method for Predicting High-Resolution 3D Variations in Temperature and Salinity Fields Using Multi-Source Ocean Data

High-resolution three-dimensional (3D) variations in ocean temperature and salinity fields are of great significance for ocean environment monitoring. Currently, AI-based 3D temperature and salinity field predictions rely on expensive 3D data, and as the prediction period increases, the stacking of high-resolution 3D data greatly increases the difficulty of model training. This paper transforms the prediction of 3D temperature and salinity into the prediction of sea surface elements and the inversion of subsurface temperature and salinity using sea surface elements, by leveraging the relationship between sea surface factors and subsurface temperature and salinity. This method comprehensively utilizes multi-source ocean data to avoid the issue of data volume caused by stacking high-resolution historical data. Specifically, the model first utilizes 1/4° low-resolution satellite remote sensing data to construct prediction models for sea surface temperature (SST) and sea level anomaly (SLA), and then uses 1/12° high-resolution temperature and salinity data as labels to build an inversion model of subsurface temperature and salinity based on SST and SLA. The prediction model and inversion model are integrated to obtain the final high-resolution 3D temperature and salinity prediction model. Experimental results show that the 20-day prediction results in the two sea areas of the coastal waters of China and the Northwest Pacific show good performance, accurately predicting ocean temperature and salinity in the vast majority of layers, and demonstrate higher resource utilization efficiency.

Review on the Impact of Corporate ESG Practices on China's Economy and Society

ESG has become a popular topic in the current international community, and it is also an important direction and perspective for academic research at home and abroad. There are many empirical studies on ESG, but few review literatures. Based on the methods of literature research, comparative analysis, and historical research, this paper sorts out and summarizes the existing Chinese literature on ESG and its connotation, corporate performance, corporate governance, macroeconomic transformation, and ESG localization. The results show that ESG practices positively correlate with corporate financial performance, and good corporate governance helps improve corporate management. In addition, ESG is conducive to improving corporate resource utilization efficiency, promoting corporate green transformation, helping enterprises cope with economic transformation challenges, promoting China's social transformation, and building a localized ESG system.

The effect of an innovative payment method on inpatient volume and bed resources and their regional distribution: the case of a central province in China

BackgroundSince 2020, China has piloted an innovative payment method known as the Diagnosis-Intervention Packet (DIP). This study aimed to assess the impact of the DIP on inpatient volume and bed allocation and their regional distribution. This study investigated whether the DIP affects the efficiency of regional health resource utilization and contributes to disparities in health equity among regions.MethodsWe collected data from a central province in China from 2019 to 2022. The treatment group included 508 hospitals in the pilot area (Region A, where the DIP was implemented in 2021), whereas the control group consisted of 3,728 hospitals from non-pilot areas within the same province. We employed the difference-in-differences method to analyze inpatient volume and bed resources. Additionally, we conducted a stratified analysis to examine whether the effects of DIP implementation varied across urban and rural areas or hospitals of different levels.ResultsCompared with the non-pilot regions, Region A experienced a statistically significant reduction in inpatient volume of 14.3% (95% CI 0.061–0.224) and a notable decrease of 9.1% in actual available bed days (95% CI 0.041–0.141) after DIP implementation. The study revealed no evidence of patient consultations shifting from inpatient to outpatient services due to the reduction in hospital admissions in Region A after DIP implementation. Stratified analysis revealed that inpatient volume decreased by 12.4% (95% CI 0.006–0.243) in the urban areas and 14.7% in the rural areas of Region A (95% CI 0.051–0.243). At the hospital level, primary hospitals experienced the greatest impact, with a 19.0% (95% CI 0.093–0.287) decline in inpatient volume. Furthermore, primary and tertiary hospitals experienced significant reductions of 11.0% (95% CI 0.052–0.169) and 8.2% (95% CI 0.002–0.161), respectively, in actual available bed days.ConclusionsDespite efforts to curb excessive medical service expansion in the region following DIP implementation, large hospitals continue to attract a large number of patients from primary hospitals. This weakening of primary hospitals and the subsequent influx of patients to urban areas may further limit rural patients’ access to medical services. The implementation of the DIP may raise concerns about its impact on health care equality and accessibility, particularly for underserved rural populations.

Ionic Liquid-Catalyzed CO2 Conversion for Valuable Chemicals.

CO2 is not only the main gas that causes the greenhouse effect but also a resource with abundant reserves, low price, and low toxicity. It is expected to become an important "carbon source" to replace oil and natural gas in the future. The efficient and clean resource utilization of CO2 has shown important scientific and economic value. Making full use of abundant CO2 resources is in line with the development direction of green chemistry and has attracted the attention of scientists. Environmentally friendly ionic liquids show unique advantages in the capture and conversion of CO2 due to their non-volatilization, designable structure, and good solubility, and show broad application prospects. The purpose of this paper is to discuss the research on the use of an ionic liquid as a catalyst to promote the synthesis of various value-added chemicals in CO2, hoping to make full use of CO2 resources while avoiding the defects of the traditional synthesis route, such as the use of highly toxic raw materials, complicated operation, or harsh reaction conditions. The purpose of this paper is to provide reference for the application and development of ionic liquids in CO2 capture and conversion.

Natural resources and economic growth: Examining the role of globalization, financial development, and digitalization in India

Natural resources are considered vital for economic growth, laying the foundations for various industries. Therefore, the present study aims to examine the importance of natural resources, globalization, financial development, and digitalization in India's economic performance from 1970 to 2020. The study utilizes the Auto-regressive distributed lag (ARDL) techniques with structural breaks and the Granger causality test to detect the direction of causality. Further, Fully Modified Ordinary Least Square (FMOLS) and Dynamic Ordinary Least Square (DOLS) were used to check the robustness of the long-run coefficients. The finding supports the “Resource curse hypothesis” in India. Globalization and financial development drive the long-run growth performance. In the short run, digitalization and globalization enhance growth performance. The Granger causality result unfolds a bidirectional causal relationship between economic growth and digitalization and unidirectional causation from financial development and globalization to economic growth. The study's outcomes have notable policy implications that emphasize the need to induce financial development, integrate digital technology into core sectors of the economy, and encourage market openness and efficient utilization and management of natural resources for sustainable economic growth.

Selective lithium recovery from lithium precipitation mother liquor by using a diketone-based solvent

Lithium recovery from lithium precipitation mother liquor is an important point for improving lithium resource utilization efficiency. In this study, a modified β-diketone based organic solvent was developed. DBM was selected as extractant, which has the advantage of low cost compared to fluor-diketones. Organic phosphate TBP was used instead of traditional alkylphosphine oxide as co-extractant. The results show that TBP has the ability to inhabit the extraction of sodium so that it is positive for separation factor of lithium to sodium. Simultaneously, TBP plays the role of diluent, thus improving two-phase separation performance significantly. The phase separation time is only tens of seconds, which is much less than that of alkylphosphine oxide co-extraction system. Besides, low cost and low viscosity properties of TBP avoid the limitation of additive amount, which means that it has the industrial feasibility to improve the extraction performance by increasing TBP concentration. The developed extraction solvent has the combination sequence of H+ > > Li+ > > Na+. By using optimized solvent of 0.4 mol/L DBM and 1.2 mol/L TBP dissolved in sulfonated kerosene, single-stage lithium extraction rate is 99.96 % and separation factor of lithium to sodium reaches >160,000 at the O/A phase ratio of 1:1.

Impacts of economic development, globalization, and gross capital formation on natural resources rents: Evidence from India

Natural resources are a country's wealth, and resources economics and policy literature has extensively researched how to utilize this richness as a determinant of the country's growth. However, the primary challenges reside in establishing economic development as a driver for natural resource rents. Given this context, this study explores the association between economic development, globalization, gross capital formation, and natural resources rents in India. For the empirical research, the study employed Dynamic Auto-Regressive Distributive Lag (DARDL) simulation and Kernel-based Regularized Least Squares (KRLS) approaches on yearly data from 1990 to 2020. The present research used a unit root test to ascertain the stationary state across all variables, establishing their long-term cointegration connection. Results suggest that capital formation and economic development positively impact rents derived from natural resources in India, while globalization negatively affects natural resources rents. Unidirectional causation of economic development, globalization, and gross capital creation to natural resources rents has been established in this study using the Toda-Yamamoto causality model. Our findings have important policy implications and support the idea that sustainable economic growth models inherently rely on factors like the efficient utilization of natural resources and globalization.

Multi-Agent Deep Reinforcement Learning Based Dynamic Task Offloading in a Device-to-Device Mobile-Edge Computing Network to Minimize Average Task Delay with Deadline Constraints.

Device-to-device (D2D) is a pivotal technology in the next generation of communication, allowing for direct task offloading between mobile devices (MDs) to improve the efficient utilization of idle resources. This paper proposes a novel algorithm for dynamic task offloading between the active MDs and the idle MDs in a D2D-MEC (mobile edge computing) system by deploying multi-agent deep reinforcement learning (DRL) to minimize the long-term average delay of delay-sensitive tasks under deadline constraints. Our core innovation is a dynamic partitioning scheme for idle and active devices in the D2D-MEC system, accounting for stochastic task arrivals and multi-time-slot task execution, which has been insufficiently explored in the existing literature. We adopt a queue-based system to formulate a dynamic task offloading optimization problem. To address the challenges of large action space and the coupling of actions across time slots, we model the problem as a Markov decision process (MDP) and perform multi-agent DRL through multi-agent proximal policy optimization (MAPPO). We employ a centralized training with decentralized execution (CTDE) framework to enable each MD to make offloading decisions solely based on its local system state. Extensive simulations demonstrate the efficiency and fast convergence of our algorithm. In comparison to the existing sub-optimal results deploying single-agent DRL, our algorithm reduces the average task completion delay by 11.0% and the ratio of dropped tasks by 17.0%. Our proposed algorithm is particularly pertinent to sensor networks, where mobile devices equipped with sensors generate a substantial volume of data that requires timely processing to ensure quality of experience (QoE) and meet the service-level agreements (SLAs) of delay-sensitive applications.

Shallow tillage mitigates plant competition by increasing diversity and altering plant community assembly process.

Understanding how human activities affect biodiversity is needed to inform systemic policies and targets for achieving sustainable development goals. Shallow tillage to remove Artemisia ordosica is commonly conducted in the Mu Us Desert. However, the impacts of shallow tillage on plant community species diversity, phylogenetic structure, and community assembly processes remain poorly understood. This study explores the effects of shallow tillage on species diversity including three a-diversity and two b-diversity indicators, as well as phylogenetic structure [phylogenetic diversity (PD), net relatedness index (NRI), and nearest taxon index (NTI)]. Additionally, this research analyzes the effects of shallow tillage on the community assembly process. The results showed that the a-diversity index, b-diversity index, and PD of the shallow tillage (ST) communities were significantly higher than those of the non-shallow tillage (NT) communities, and the phylogenetic structures of both the ST and NT communities tended to be differentiated, with competitive exclusion being the main mechanism of plant assembly. However, shallow tillage increased the relative importance of the stochastic processes dominated by dispersal limitation, mitigating plant competition in the communities. This conclusion was supported by the Raup-Crick difference index-based analysis. Therefore, for the ecological restoration of the Mu Us Desert, species with adaptability and low niche overlap should be selected to increase the utilization efficiency of the environmental resources. The results of this study provide a foundation for policy development for ecosystem management and restoration in the Mu Us Desert.

Quality evaluation of selected expired fluoroquinolones medicines obtained from the public hospitals in Jimma zone, Oromia regional state, Ethiopia.

The problem of medicine expiration presents a notable obstacle, resulting in considerable financial losses. Nevertheless, there is currently limited data indicating that certain medications do not experience a significant decrease in effectiveness after their expiration date. Therefore, the aim of the study was to assess the physico-chemical quality of expired fluoroquinolone antibiotics. The expired samples of fluoroquinolone antibiotics were purposively collected from public hospitals in the Jimma zone of the Oromia regional state, Ethiopia. A World Health Organization quality evaluation sampling strategy was employed. Then, simple random sampling techniques were utilized for the selection of tablets for the laboratory quality control test. The assay, identification, and dissolution were performed in accordance with the United States Pharmacopeia (USP) guidelines, as well as failure mode and effect analysis (FMEA) techniques. The finding revealed that about 100% (7/7) expired samples passed pharmacopeia quality specifications for identity and assay tests. However, of the seven expired brands, about 14.3% (1/7) of the sample (Code-002) was unable to release its API content within the USP criteria of 30 min. The risk-based quality evaluation revealed that assay was the most critical quality attributed to ciprofloxacin tablets (RPN = 189), followed by identity (RPN = 100). Assay was also the most critical quality attribute (RPN = 378), followed by identity (RPN = 100) for Norfloxacin tablets. The risk-based desirability function approach showed that 75% (3/4) of ciprofloxacin products were of good quality, and 25% (1) were found to be of acceptable quality, while the desirability function of norfloxacin tablets was found to be excellent 1 (33.3%), good 1 (33.3%), and acceptable 1 (33.3%). The study revealed that medications can maintain their quality beyond their labeled expiration date. By combining pharmacopeial standards with risk-based approaches like failure mode and effect analysis (FMEA), the study provides a comprehensive evaluation framework. This approach not only confirms the continued effectiveness of expired fluoroquinolone antibiotics but also underscores the potential waste reduction and cost-saving benefits. This could significantly contribute to addressing healthcare challenges in low-resource settings, promoting more efficient pharmaceutical resource utilization.

Preparation and Characterization of Bio-Asphalt Based on Sludge-Derived Heavy Oil

To achieve the efficient resource utilization of municipal sludge and promote the sustainability of pavement materials, this study employed liquefaction technology to process municipal sludge. The resulting liquefied-sludge-derived heavy oil was blended with 50# asphalt to prepare a bio-asphalt that can replace petroleum asphalt. Firstly, orthogonal experiments were conducted to analyze the effects of the solid–liquid ratio (dried sludge:anhydrous ethanol), liquefaction temperature, and reaction time on the yield of the sludge-derived heavy oil. Then, the basic characteristics of the sludge-derived heavy oil were studied using an elemental analyzer, gel permeation chromatography, thermal analysis, gas chromatography–mass spectrometry, and Fourier transform infrared spectroscopy, and the differences between the sludge-derived heavy oil and petroleum asphalt were compared. Finally, to determine the appropriate content range of sludge-derived heavy oil in bio-asphalt, a comprehensive evaluation of the three major indicators, aging resistance, storage stability, low-temperature performance, and high-temperature performance was carried out for the prepared bio-asphalts. The results indicated that the optimal preparation process for liquefied sludge oil involves a liquefaction temperature of 275 °C, a solid–liquid ratio of 1:15, and a reaction time of 1 h, resulting in an oil production rate of 22.36%. The sludge-derived heavy oil demonstrated good thermal stability, with its primary components being aliphatic compounds (carboxylic acids, ketones, aldehydes, alcohols, alkanes, esters, etc.), with esters being the most abundant. Furthermore, the sludge-derived heavy oil was highly compatible with 50# asphalt, but no chemical reaction occurred between them. When the sludge-derived heavy oil content ranged from 5% to 20%, bio-asphalt showed favorable aging resistance and storage stability. As the content of the sludge-derived heavy oil increased, its low-temperature performance improved, but there was a slight decrease in high-temperature performance. Additionally, correlation analysis highlighted that the influence of sludge-derived heavy oil content on the high-temperature performance of bio-asphalt was notably greater than on other properties. Therefore, the recommended dosage of sludge-derived heavy oil should be between 5% and 10%.

An ecological population study of lampreys in the Lotka-Volterra tertiary trophic level based on sex differences

This study examines the adaptive changes in sex ratio on animal populations and its effects on ecosystem stability and interactions. The effects of sex ratio dynamics on the ecosystem were analyzed through mathematical modeling using lampreys as the study population. In this study, a two-stage tertiary trophic Lotka-Volterra mathematical model of ecological dynamics was developed, taking into account food preferences, ecological roles, and sex interactions of lampreys. The simulation results showed that a rapid adjustment in sex ratio led to a reduction in environmental loads, which triggered an early rebound increase in lampreys and predator populations. To assess the ability of lampreys populations to adjust sex ratios, this study used a combination of fuzzy integrated evaluation and hierarchical analysis methods. The results of the study revealed the importance of sex-adaptive traits for population development, including increased resource utilization efficiency and population fitness, as well as decreased reproductive success and reduced genetic diversity. Based on the RRT (resistance, resilience and temporal stability) method, this study constructed an ecosystem stability assessment model and investigated the effects of changes in the sex ratio of lampreys on ecosystem stability. The experimental results showed that ecosystem stability was highest when the sex ratio was 0.6 and lowest when the sex ratio was 0.2. Variation in sex ratio may affect the behavior and abundance of lampreys, thereby directly influencing their interactions with other species. Variability in sex ratio provides more resources for predators and parasites of lampreys, promotes their growth, and positively affects ecosystem balance. Simulation results showed that the model was highly stable under different interactions. In summary, this study reveals the important effects of sex ratio on ecosystem stability and interactions, and provides important insights into the understanding of adaptive evolutionary traits of species, ecosystem stability and ecological interactions.

Integrating Perishables into Closed-Loop Supply Chains: A Comprehensive Review

In an era where sustainability and efficient resource utilization are paramount, the closed-loop supply chain (CLSC) emerges as a critical approach, particularly in the context of perishable goods. The perishability of products adds a layer of complexity to supply chain management, necessitating innovative strategies for maximizing product life and minimizing waste. This comprehensive review article delves into the integration of perishable products within the framework of CLSC. The study thoroughly examines existing research to identify gaps and outline future research directions. It emphasizes the unique challenges and complexities of managing perishable goods, a crucial but often overlooked component in sustainable supply chain practices. The review highlights the balance between efficiency and sustainability, underscoring the importance of reverse logistics and circular economy principles in enhancing supply chain resilience. By synthesizing various methodologies and findings, the article presents a holistic view of the current state of perishable product management in CLSCs, offering valuable insights for academia and industry practitioners. The study not only contributes to the theoretical understanding of CLSCs, but also proposes practical approaches for their optimization, aligning with broader sustainability goals.

Separation Study of Magnesium–Lithium from Low‐Mg/Li Brine

The lithium present in salt lakes constitutes a significant and valuable resource. There are various methods for extracting lithium from salt lake brine, but currently, they all face challenges such as high energy consumption and low utilization efficiency of lithium resources. One prominent issue is the composition of feedstock during lithium extraction, specifically determining the optimal concentration ratio (nMg/nLi value). This constitutes a critical aspect in the later stages of the extraction process, influencing the cost and efficiency of lithium extraction processes. The fundamental reason for this prominent issue is the effective control of the evaporation and concentration process of lithium‐containing brines, which is caused by the disconnection between the evaporation process and the subsequent processing and extraction stages. Therefore, considering the concentration variation patterns of Li+ and Mg2+ in brine during the evaporation process, paper employs a combination of experimental research and computational simulation. It investigates the variation of Li‐Mg concentrations and their interactions during the natural evaporation enrichment process. The research investigates changes in lithium and magnesium concentrations and their interactions during natural evaporation enrichment process of salt lake. Elucidates the mechanism of lithium migration and proposes a new lithium extraction process ‐ the ‘3 Steps 2 Units’.

Calcium oxide enhances the anaerobic co-digestion of excess sludge and plant waste: performance and mechanism.

The study investigates the effect of the oxidant calcium oxide (CaO) on the codigestion of excess sludge (ES) and plant waste (PW) under mesophilic anaerobic conditions to enhance methane production. The findings indicate that CaO significantly elevated methane yield in the codigestion system, with an optimum CaO addition of 6% resulting in a maximum methane production of 461 mL/g volatile solids, which is approximately 1.3 times that of the control group. Mechanistic exploration revealed that CaO facilitated the disintegration of organic matter, enhanced the release of soluble chemical oxygen demand, and increased the concentrations of soluble proteins and polysaccharides within the codigestion substrate. The presence of CaO was conducive to the generation and biological transformation of volatile fatty acids, with a notable accumulation of acetic acid, a smaller carboxylic acid within the VFAs. The proportion of acetate in the CaO-amended group increased to 32.6-36.9%. Enzymatic analysis disclosed that CaO enhanced the activity of hydrolytic and acidogenic enzymes associated with the ES and PW codigestion process but suppressed the activity of coenzyme F420. Moreover, CaO augmented the nutrient load in the fermentation liquid. The study provides an alternative scheme for the efficient resource utilization of ES and PW.

Low-toxicity natural pyrite on electro-Fenton catalytic reaction in a wide pH range

The resource utilization of natural pyrite not only reduces secondary pollution but also brings certain environmental benefits. However, the green and efficient use of pyrite presents certain challenges. In this study, a novel electro-Fenton (EF) system was constructed utilizing copper modified graphite felt (GF/Cu) as cathode and natural pyrite (com-FeS2) as catalyst. The results demonstrated that the system exhibited a remarkable stability over an extensive pH range (3.0–10.0) and remained effective even under adverse environmental conditions, such as high salinity or elevated antibiotic concentration. After optimizing the reaction conditions, 0.2 mM sulfamerazine (SMZ) was almost completely degraded within 1.5 h. The results highlighted the catalytic role of Fe(II) on the com-FeS2 surface. Combined with quenching experiments and quantitative analysis of reactive oxygen species (ROS), the removal of SMZ was primarily attributed to the generation of •OH, ordered by 1O2 > •O2− > •OHads, a possible degradation pathway was proposed by HR-LC-MS. The biological toxicity after the reaction was detected, and the introduction of polyvinylpyrrolidone (PVP) was beneficial to reduce the biological toxicity of iron dissolution. This work provides new insights into the green and efficient resource utilization of natural pyrite and significantly expands the pH applicability range of the Fenton process, demonstrating the large-scale industrial application potential of pyrite.

A Review of Drip Irrigation’s Effect on Water, Carbon Fluxes, and Crop Growth in Farmland

The substantial depletion of freshwater reserves in many pivotal agricultural regions, attributable to the dual pressures of global climate change and the excessive extraction of water resources, has sparked considerable apprehension regarding the sustainability of future food and water security. Drip irrigation, as an efficient and precise irrigation method, reduces water loss caused by deep percolation, soil evaporation, and runoff by controlling the irrigation dosage and frequency, thus improving the efficiency of water resource utilization. Studies have shown that compared with traditional irrigation methods, drip irrigation can significantly decrease water consumption, optimize the water–energy relationship by reducing soil evaporation, increase the leaf area index, and promote crop growth, thereby enhancing plant transpiration. Although more wet and dry soil cycles from drip irrigation may increase soil CO2 emissions, it also enhances crop photosynthesis and improves crop net ecosystem productivity (NEP) by creating more favorable soil moisture conditions, indicating greater carbon sequestration potential. The advantages of drip irrigation, such as a short irrigation cycle, moderate soil moisture, and obvious dry and wet interfaces, can improve a crop’s leaf area index and biomass accumulation, improve root dynamics, promote the distribution of photosynthetic products to the aboveground parts, and thus enhance crop yields. This study highlights the potential for the application of drip irrigation in arid regions where resource optimization is sought, providing strong technical support for the achievement of sustainable agricultural development. Future research needs to consider specific agricultural practices, soil types, and environmental conditions to further optimize the implementation and effectiveness of drip irrigation.

A Combination of Transcriptome and Enzyme Activity Analysis Unveils Key Genes and Patterns of Corncob Lignocellulose Degradation by Auricularia heimuer under Cultivation Conditions.

The cultivation of Auricularia heimuer, a species of edible mushroom, heavily relies on the availability of wood resources serving as substrate for the growth of the species. To ensure the sustainable development of the A. heimuer industry and optimize the utilization of corncob as a substrate, this study sought to investigate the potential use of corncob as a substrate for the cultivation of A. heimuer. The purpose of this study was to explore the utilization of corncob lignocellulose by A. heimuer at the mycelium, primordium, and fruiting stages, by specifically examining the expression profiles of both carbohydrate-active enzymes (CAZymes) and the transcriptome of differentially expressed genes (DEGs) relevant to corncob biomass degradation. The results revealed 10,979, 10,630, and 11,061 DEGs at the mycelium, primordium, and fruiting stages, respectively, while 639 DGEs were identified as carbohydrate-active enzymes. Of particular interest were 46 differentially expressed CAZymes genes that were associated directly with lignocellulose degradation. Furthermore, the study found that A. heimuer exhibited adaptive changes that enabled it to effectively utilize the cellulose present in the corncob. These changes were observed primarily at the primordium and fruiting stages. Key genes involved in lignocellulose degradation were also identified, including g6952, g8349, g12487, and g2976 at the mycelium stage, g5775, g2857, g3018, and g11016 at the primordium stage, and g10290, g2857, g12385, g7656, and g8953 at the fruiting stage. This study found that lytic polysaccharide monooxygenase (LPMO) played a crucial role in the degradation of corncob cellulose, further highlighting the complexity of the molecular mechanisms involved in the degradation of lignocellulose biomass by A. heimuer. The study sheds light on the molecular mechanisms underlying the ability of A. heimuer to degrade corncob biomass, with implications for the efficient utilization of lignocellulose resources. The findings from this study may facilitate the development of innovative biotechnologies for the transformation of corncob biomass into useful products.

Application of Machine Learning in 3D Bioprinting: Focus on Development of Big Data and Digital Twin.

The application of machine learning (ML) in bioprinting has attracted considerable attention recently. Many have focused on the benefits and potential of ML, but a clear overview of how ML shapes the future of three-dimensional (3D) bioprinting is still lacking. Here, it is proposed that two missing links, Big Data and Digital Twin, are the key to articulate the vision of future 3D bioprinting. Creating training databases from Big Data curation and building digital twins of human organs with cellular resolution and properties are the most important and urgent challenges. With these missing links, it is envisioned that future 3D bioprinting will become more digital and in silico, and eventually strike a balance between virtual and physical experiments toward the most efficient utilization of bioprinting resources. Furthermore, the virtual component of bioprinting and biofabrication, namely, digital bioprinting, will become a new growth point for digital industry and information technology in future.

Cubature Kalman fusion filtering under stochastic communication protocol: Tackling dynamical bias, scheduling probability and channel noise

The paper addresses the problem of cubature Kalman fusion filtering (CKFF) for nonlinear systems subject to dynamical bias and stochastic communication protocol (SCP). To account for the engineering practice of networked environment, the channels from sensors to filters, affected by Gaussian channel noise, are considered in the system model incorporating dynamical bias. With the purpose of reducing communication load and enhancing resource utilization efficiency, the SCP is adopted for information transmissions, where the scheduling probability is allowed to deviate within bounds from its designated value owing to possible implementation errors. The objective of this paper is to design a CKFF algorithm in spite of the presence of dynamical bias, channel noise and SCP with uncertain scheduling probability. Specifically, the local filter is constructed such that an upper bound on the filtering error covariance (FEC) is calculated through the resolution of matrix difference equations, and the filter gain is subsequently designed to minimize this upper bound. Then, the local filters are fused by utilizing the inverse covariance intersection fusion rule. Moreover, the boundedness of the FEC’s upper bound is also investigated using the matrix theory. The feasibility and effectiveness of the proposed CKFF approach are demonstrated through two simulation experiments.