Search Results (38)

The prevalence of probiotic-labeled products with no evidence of improved health outcomes associated with their consumption has perturbed both the trust of clinicians and the public perception of microbial therapeutics. While probiotics are clearly defined as live microorganisms that, when administered in adequate amounts, confer a health benefit on the host, it is often ignored in the microbial marketplace. Many products including household cleaners, cosmetics, and pet foods attach probiotic to their labels without supplying viable strains, clinically effective doses, or proven outcomes. Evidence from metagenomic studies and compositional analyses suggest that many probiotics on the market are mischaracterized or mislabeled, a problem that is only exacerbated by weak regulatory standards. In contrast, there are a limited collection of strain-specific interventions such as Lactobacillus rhamnosus GG, L. rhamnosus GR1, Saccharomyces boulardii, and Escherichia coli Nissle 1917 that have demonstrated beneficial effects in randomized clinical trials. Considering that the consumption of commercial probiotics often lacks measurable health benefits, it is unreasonable to group proven microbial therapeutics under the same umbrella term of “probiotic”. This paper proposes a strict enforcement of semantic distinction: reserving “probiotics” for less regulated microbial-rich products whereas microbe-containing products that have demonstrated clinical benefit following robust regulatory oversight should be considered for reclassification. Full article

The electric power industry is not only facing the pressure from the reduction of industrial and commercial electricity prices to stimulate the significant growth of demand, but also facing the increasingly serious pressure of unreasonable consumption caused by cross-subsidies; the cross-subsidy mitigation effect and energy-saving effect of the current tiered electricity price policy have basically disappeared. This article examines the main variables that affect the electricity demand and carbon emissions in order to develop a better tiered electricity pricing scheme that can effectively manage cross-subsidies in electricity prices while simultaneously saving energy and lowering carbon emissions. The China Statistical Yearbook’s electricity balance sheets for 2013–2020 are used in this article, along with pertinent data from the State Grid Corporation of China and the China Statistical Yearbook for 2006–2016. It builds an electricity demand model for classified users by using the time series analysis method and multiple statistical regression method. The variables are then subjected to a Granger causality test and a cointegration test in this article. The analysis shows that the adjustment of the electricity price policy has a significant impact on energy-saving and carbon reduction, and for residential electricity consumption, the income variable is the main factor affecting the electricity demand. We take residents’ affordability as the constraint condition for dividing the range of electricity and determining the beneficiary group, take the carbon emission responsibility target and the cross-subsidy degree alleviation target as constraints in determining the tiered price difference, propose an improvement scheme for the tiered electricity price, and carry out the sensitivity analysis of the influence between the parameters. The results show that the optimization improves the precision of the cross-subsidy treatment and significantly improves the effects of energy conservation and emission reduction. Full article

With the rapid growth of Internet applications and network traffic, existing routing algorithms are usually difficult to guarantee the quality of service (QoS) indicators such as delay, bandwidth, and packet loss rate as well as network energy consumption for various data flows with business characteristics. They have problems such as unbalanced traffic scheduling and unreasonable network resource allocation. Aiming at the above problems, this paper proposes a QoS-oriented energy-saving routing algorithm A3C-R in the software-defined network (SDN) environment. Based on the asynchronous update advantages of the asynchronous advantage Actor-Critic (A3C) algorithm and the advantages of independent interaction between multiple agents and the environment, the A3C-R algorithm can effectively improve the convergence of the routing algorithm. The process of the A3C-R algorithm first takes QoS indicators such as delay, bandwidth, and packet loss rate and the network energy consumption of the link as input. Then, it creates multiple agents to start asynchronous training, through the continuous updating of Actors and Critics in each agent and periodically synchronizes the model parameters to the global model. After the algorithm training converges, it can output the link weights of the network topology to facilitate the calculation of intelligent routing strategies that meet QoS requirements and lower network energy consumption. The experimental results indicate that the A3C-R algorithm, compared to the baseline algorithms ECMP, I-DQN, and DDPG-EEFS, reduces delay by approximately 9.4%, increases throughput by approximately 7.0%, decreases the packet loss rate by approximately 9.5%, and improves energy-saving percentage by approximately 10.8%. Full article

The unreasonable parameters of mill liner lifter bars will not only decrease the operating rate of the mill and increase electricity consumption but, also, seriously restrict the production capacity of the mill. Therefore, optimizing the parameters of liner lifter bars is helpful to save energy, improve its production capacity, and increase benefits for enterprises. Given the unreasonable parameters of the lifter bars of the semi-autogenous grinding (SAG) mill in a beneficiation plant in Yunnan (China), the distinct element method (DEM) with orthogonal tests was used to conduct simulation, the simulation results demonstrating that the three parameters all had significant influence on the collision energy, with the order of group numbers > angles > heights by the analysis of range and variance, and the optimal parameters combination, with angles of 20°, groups of 12, and heights of 210 mm, was obtained. Then, the lifer bars optimized were applied in industrial tests to verify their effect, and the results illustrated that all of the service life of lifter bars, the operating rate, production capacity, and electricity consumption were significantly improved at 159 days, 92.32%, 54.37 t/h, and 21.45 kW·h/t, respectively. This paper proposes a reference for the similar design and optimization of lifter bars for the other beneficiation plants. Full article

Based on the panel data of 283 prefecture-level cities in China from 2010 to 2021, this paper takes the pilot policy of “Broadband China” as a natural experiment to evaluate the impact of digital infrastructure construction on urban ecological welfare performance and its mechanism by using a progressive difference–difference model. The results show that China’s digital infrastructure construction will significantly reduce the performance of urban ecological welfare. Through the analysis of input and output, it is found that the construction of digital infrastructure can significantly reduce resource consumption and increase welfare output, especially economic welfare, but at the level of environmental pollution, it will significantly increase the discharge of industrial wastewater, which may be the main reason for the negative effect of digital infrastructure construction. Through the group analysis, it is found that the overall negative impact of digital infrastructure construction on ecological welfare performance may be caused by the ecologically fragile western region and the unreasonable industrial structure. Through the adjustment model, it is found that innovation investment can positively regulate the negative impact of digital infrastructure on ecological welfare performance. The grey model (GM) is further used to forecast the data for 2022–2025, and it is found that while the negative impact of digital infrastructure is decreasing, it is still significant. This study provides empirical evidence for accurately understanding the effect and mechanism of digital infrastructure construction on ecological welfare performance. Full article

The power consumption data in buildings can be viewed as a time series, where outliers indicate unreasonable energy usage patterns. Accurately detecting these outliers and improving energy management methods based on the findings can lead to energy savings. To detect outliers, an anomaly detection model based on time-series reconstruction, AF-GS-RandomForest, is proposed. This model comprises two modules: prediction and detection. The prediction module uses the Autoformer algorithm to build an accurate and robust predictive model for unstable nonlinear sequences, and calculates the model residuals based on the prediction results. Points with large residuals are considered outliers, as they significantly differ from the normal pattern. The detection module employs a random forest algorithm optimized by grid search to detect residuals and ultimately identify outliers. The algorithm’s accuracy and robustness were tested on public datasets, and it was applied to a power consumption dataset of an office building. Compared with commonly used algorithms, the proposed algorithm improved precision by 2.2%, recall by 12.1%, and F1 score by 7.7%, outperforming conventional anomaly detection algorithms. Full article

Water resource shortage and unreasonable application of nitrogen (N) fertilizer have been problems in wheat production of northern China. However, the interaction effects of water regimes and N practices on wheat root growth, grain yield, soil water, and inorganic N changes as well as water-N use efficiency are still unclear under drip irrigation. A field experiment was conducted during the 2020–2021 and 2021–2022 winter wheat (Triticum aestivum) growing seasons. In this study, three irrigation schedules (i.e., irrigation was applied up to 80% [D1], 75% [D2], and 70% [D3] as soon as the soil water content decreased to 65%, 60% or 55% of field capacity) and two N practices (i.e., N applied at the base, jointing, booting stages were 90, 72, 48 kg ha⁻¹ [N1], and the base, jointing, booting, filling stages were 90, 40, 40, 40 kg ha⁻¹ [N2], respectively) were considered. The decease in irrigation water amount was offset by the increase in soil water consumption. In addition, N practices significantly interacted with irrigation on soil NO₃⁻–N accumulation (2021–2022), NH₄⁺–N accumulation, SPAD value (2020–2021), N content in stems and grains at maturity, and average root length and weight density at the flowering stage. Irrigation, rather than N practices, significantly affected grain yield, total N uptake, crop N transformations (NT), the contribution of NT to grain (NTPC), water and N productivity, in which, for the value of these two seasons, D2 increased total N uptake by 18.1% (p < 0.05), and NT by 39.4% (p < 0.05) under N1 as compared to D3. Additionally, the highest WUE and ANUE were found in D2 during 2021–2022. Heavy irrigation water amount caused high a LAI; further analysis proved that the LAI was the key factor affecting grain yield, and positively and significantly correlated to yield. However, no significant difference in the LAI between D1 and D2 was found. N1 was beneficial to prevent N leaching and increase water and N use efficiency, biomass, and N transformation amount. This study recommends that D2 + N1 might be a promising system for manipulating irrigation and fertilization practices under sub-surface drip irrigation systems to improve water and N use efficiency and grain yields in semi-arid regions. Full article

A water diversion system (WDS) with cascade pumping stations (CPSs) plays an important role in the application of water resources. However, high energy consumption is reported due to unreasonable scheduling schemes and long decision times. Herein, this paper presents a new method to achieve optimal scheduling schemes effectively, including the head allocation of CPSs, the number of running pumps, and pump blade angles. A double-layer mathematical model for a WDS was established with the goal of achieving minimal energy consumption, considering the constraints of flow rate, water level, and the characteristics of pump units. The inner-layer model was used to obtain scheduling schemes of single-stage pumping stations, as well as the water levels and flow rates of water channels, while the outer-layer model was used to optimize inter-stage head allocation. An improved wolf-pack algorithm (IWPA) was proposed to solve the model, using a Halton sequence to obtain the uniform initial population distribution and introducing simulated annealing (SA) to improve the global searchability. Moreover, an idea for a pre-established scheme library was suggested for inner-layer models to obtain the solutions in real time with less calculation workload. Taking an actual project as a case, in contrast with the actual schemes, the optimal scheduling method could result in energy savings of 14.37–20.39%, a CO₂ emission reduction of 13–32 tons per day, and water savings of 0.14–18.34%. Moreover, the time complexity decreased to square order, and the CPU time of the optimal method was about 1% that of the traditional method. This study provides an efficient method for the high-value utilization of energy and water resources for a WDS. Full article

Mine ventilation is crucial for ensuring safe production in mines, as it is integral to the entire underground mining process. This study addresses the issues of high energy consumption, regulation difficulties, and unreasonable regulation schemes in mine ventilation systems. To this end, we construct an optimization model for mine ventilation network regulation using mixed-integer nonlinear programming (MINLP), focusing on objectives such as minimizing energy consumption, optimal regulation locations and modes, and minimizing the number of regulators. We analyze the construction methods of the mathematical optimization model for both selected and unselected fans. To handle high-order terms in the MINLP model, we propose a variable discretization strategy that introduces 0-1 binary variables to discretize fan branches’ air quantity and frequency regulation ratios. This transformation converts high-order terms in the constraints of fan frequency regulation into quadratic terms, making the model suitable for solvers based on globally accurate algorithms. Example analysis demonstrate that the proposed method can find the optimal solution in all cases, confirming its effectiveness. Finally, we apply the optimization method of ventilation network regulation based on MINLP to a coal mine ventilation network. The results indicate that the power of the main fan after frequency regulation is 71.84 kW, achieving a significant energy savings rate of 65.60% compared to before optimization power levels. Notably, ventilation network can be regulated without adding new regulators, thereby reducing management and maintenance costs. This optimization method provides a solid foundation for the implementation of intelligent ventilation systems. Full article

Traditional multi-agent path planning algorithms often lead to path overlap and excessive energy consumption when dealing with cooperative tasks due to the single-agent-single-task configuration. For this reason, the “many-to-one” cooperative planning method has been proposed, which, although improved, still faces challenges in the vast search space for meeting points and unreasonable task handover locations. This paper proposes the Cooperative Dynamic Priority Safe Interval Path Planning with a multi-meeting-point and single-meeting-point solving mode switching (Co-${\mathrm{D}\mathrm{P}\mathrm{S}\mathrm{I}\mathrm{P}\mathrm{P}}_{\mathrm{m}\mathrm{s}}$) algorithm to achieve multi-agent path planning with task handovers at multiple or single meeting points. First, the initial priority is set based on the positional relationships among agents within the cooperative group, and the improved Fermat point method is used to locate multiple meeting points quickly. Second, considering that agents must pick up sub-tasks or conduct task handovers midway, a segmented path planning strategy is proposed to ensure that cooperative agents can efficiently and accurately complete task handovers. Finally, an automatic switching strategy between multi-meeting-point and single-meeting-point solving modes is designed to ensure the algorithm’s success rate. Tests show that Co-${\mathrm{D}\mathrm{P}\mathrm{S}\mathrm{I}\mathrm{P}\mathrm{P}}_{\mathrm{m}\mathrm{s}}$ outperforms existing algorithms in 1-to-1 and m-to-1 cooperative tasks, demonstrating its efficiency and practicality. Full article

The artificial potential field method has efficient obstacle avoidance ability, but this traditional method suffers from local minima, unreasonable paths, and sudden changes in heading angles during obstacle avoidance, leading to rough paths and increased energy consumption. To enable autonomous mobile robots (AMR) to escape from local minimum traps and move along reasonable, smooth paths while reducing travel time and energy consumption, in this paper, an artificial potential field method based on subareas is proposed. First, the optimal virtual subgoal was obtained around the obstacles based on the relationship between the AMR, obstacles, and goal points in the local environment. This was done according to the virtual subgoal benefit function to solve the local minima problem and select a reasonable path. Secondly, when AMR encountered an obstacle, the subarea-potential field model was utilized to solve problems such as path zigzagging and increased energy consumption due to excessive changes in the turning angle; this helped to smooth its planning path. Through simulations and actual testing, the algorithm in this paper demonstrated smoother heading angle changes, reduced energy consumption, and a 10.95% average reduction in movement time when facing a complex environment. This proves the feasibility of the algorithm. Full article

Newer buildings have a lower but smoother profile of indoor temperature, while older buildings are less energy efficient. Sometimes, the indoor temperature is unreasonably high, being 25–30 °C. There are buildings where the indoor temperature does not correlate with the outdoor one. Correction factors adjusting convective heat transfer coefficients are suggested. Energy demand is defined using the rate of heat loss and internal heat gains for the given building construction and design consumption profile. We suggest adjusting the setpoints of the secondary supply temperature to keep indoor and return temperatures lower. Correcting a traditional approach when designing a building may minimize energy consumption by 23.3% and increase the annual performance by up to 14.1%. The reductions of thermal peak resulting from a new type of controller adjustment (for instance, discrete) compared to the traditional operation range from roughly 10 to 30%, respectively. A better understanding of the system operation is a necessary step to switch to fourth-generation district heating (4GDH). This methodology is especially helpful in shaving daily peaks of heat demand. Building envelopes ease the charging, maximum storage capacity, and balance of the given generation and demand profiles, which are key factors in achieving the reduction in greenhouse gas (GHG) emissions. Once the heat demand is covered according to the maximum storage capacity for the given generation and demand profile, fewer efforts to modernize a district heating network are required. Full article

Limited by the influence of network topology and other factors, the theory of carbon emission flow is unreasonable in the allocation of carbon responsibility on the user side, which leads to the low enthusiasm of users to respond to emission mitigation. The emergence of bilateral transactions provides users with the freedom to choose the type of power supply which is of great significance to exploring the potential of users to reduce emissions and promote the consumption of new energy. For this reason, this paper proposes a bi-level emission reduction model of the hybrid electricity market considering carbon emission flow and source–load coordination. The upper level aims to maximize the revenue of wind, photovoltaic, and thermal power generators and establishes a market-clearing model based on the trading rules of the hybrid electricity market to obtain the bid-winning power of each generator and the hybrid market electricity price. After the market is cleared, the carbon emission liability of the user side is calculated by using the carbon emission flow theory. The lower level takes the minimum cost of electricity consumption as the target and uses electricity price and carbon responsibility as incentives to establish a decision-making model for users to purchase electricity and guide users to actively choose green energy for consumption. The results of the example show that compared with the single pool market trading model the carbon emissions of the system are reduced by 11.9% while the income of the new energy power generations is increased by 9.84% and the electricity cost of the user is reduced by 21.2%, which underlines a mutually beneficial outcome for all stakeholders in the market. Full article

The obstacle avoidance system of a drone affects the quality of its flight path. The artificial potential field method can react quickly when facing obstacles; however, the traditional artificial potential field method lacks consideration of the position information between drones and obstacles during flight, issues including local minima, unreachable targets, and unreasonable obstacle avoidance techniques that lengthen flight times and consume more energy get encountered. Therefore, an improved artificial potential field method is proposed. First, a collision risk assessment mechanism was introduced to avoid unreasonable obstacle avoidance actions and reduce the length of unmanned aerial vehicle flight paths. Then, to solve the problem of local minimum values and unreachable targets, a virtual sub-target was set up and the traditional artificial potential field model was modified to enable the drone to avoid obstacles and reach the target point. At the same time, a virtual sub-target evaluation factor was set up to determine the reasonable virtual sub-target, to achieve a reasonable obstacle avoidance path compared to the traditional artificial potential field method. The proposed algorithm can plan a reasonable path, reduce energy consumption during flight, reduce drone turning angle changes in the path, make the path smoother, and can also be applied in complex environments. Full article

Dynamic mesh atomizers have been widely used in various fields because of their compact structure, low energy consumption, and low production costs. The finite element method is an important technique to analyze the factors affecting the atomization performance of dynamic mesh atomizers. However, at present, there is a lack of decisive solutions to the basic problems of boundary setting in terms of the simulation and vibration displacement characteristics of atomizers under different vibration modes. In this paper, two errors were found in the Vibration Analysis of a Piezoelectric Ultrasonic Atomizer to Control Atomization Rate paper written by Esteban Guerra-Bravo et al. in 2021. First, in the finite element analysis, the boundary condition of the atomizing sheet was set to be fixed, which is inconsistent with the actual support situation and seriously affects the vibration of the atomizing sheet. Second, in the simulation result, from the first mode to the third mode, the growth rate of the maximum displacement at the center of the atomizing sheet was as high as 77.12%, even up to 221.05%, which is inconsistent with the existing vibration theory. In view of these errors, in this paper, the working principle of dynamic mesh atomizers is analyzed and the vibration equation of the atomizing sheet under peripheral simple support is derived. Through comparison with the literature, it was proven that the boundary setting and vibration displacement of the atomizing sheet in the original paper are unreasonable. By measuring the atomizing rate of the atomizing sheet under different boundary conditions, it was proven that the peripheral freedom of the atomizing sheet should be greater than or equal to 1, namely, peripheral freedom or peripheral simply supported. The vibration displacement theory was used for the simulation, and the relationship between the vibration displacement and resonant frequency of the atomizing sheet under peripheral simple support was measured. It was found that with the increase in the resonance frequency, the maximum displacement of vibration modes with only nodal circles was larger than that of the other vibration modes, and the maximum displacement increased slightly with the increase in the number of nodal circles by about 0.98%. Full article