Estimates of daily oxygen consumption,carbon dioxide and methane emissions,and heat production for beef and dairy cattle using spot gas sampling

A simulation study was conducted to examine accuracy of estimating daily O₂ consumption, CO₂ and CH₄ emissions, and heat production (HP) using a spot sampling technique and to determine optimal spot sampling frequency (FQ). Data were obtained from 3 experiments where daily O₂ consumption, emissions of CO₂ and CH₄, and HP were measured using indirect calorimetry (respiration chamber or headbox system). Experiment 1 used 8 beef heifers (ad libitum feeding; gaseous exchanges measured every 30 min over 3 d in respiration chambers); Experiment 2 used 56 lactating Holstein-Friesian cows (restricted feeding; gaseous exchanges measured every 12 min over 3 d in respiration chambers); Experiment 3 used 12 lactating Jersey cows (ad libitum feeding; gaseous exchanges measured every hour for 1 d using headbox style chambers). Within experiment, averages of all measurements (FQALL) and averages of measurements selected at time points with 12, 8, 6, or 4 spot sampling FQ (i.e., sampling every 2, 3, 4, and 6 h in a 24-h cycle, respectively; FQ12, FQ8, FQ6, and FQ4, respectively) were compared. Within study a mixed model was used to compare gaseous exchanges and HP among FQALL, FQ12, FQ8, FQ6, and FQ4, and an interaction of dietary treatment by FQ was examined. A regression model was used to evaluate accuracy of spot sampling within study [i.e., FQALL (observed) vs. FQ12, FQ8, FQ6, or FQ4 (estimated)]. No interaction of diet by FQ was observed for any variables except for CH₄ production in experiment 1. No FQ effect was observed for gaseous exchanges and HP except in experiment 2 where CO₂ production was less (5,411 vs. 5,563 L/d) for FQ4 compared with FQALL, FQ12, and FQ8. A regression analysis between FQALL and each FQ within study showed that slopes and intercepts became farther from 1 and 0, respectively, for almost all variables as FQ decreased. Most variables for FQ12 and FQ8 had root mean square prediction error (RMSPE) less than 10% of the mean and concordance correlation coefficient (CCC) greater than 0.80, and RMSPE increased and CCC decreased as FQ decreased. When a regression analysis was conducted with combined data from the 3 experiments (mixed model with study as a random effect), results agreed with those from the analysis for the individual studies. Prediction errors increased and CCC decreased as FQ decreased. Generally, all the estimates from FQ12, FQ8, FQ6, and FQ4 had RMSPE less than 10% of the means and CCC greater than 0.90 except for FQ6 and FQ4 for O₂ consumption and CH₄ production. In conclusion, the spot sampling simulation with 3 indirect calorimetry experiments indicated that FQ of at least 8 samples (every 3 h in a 24-h cycle) was required to estimate daily O₂ consumption, CO₂ and CH₄ production, and HP and to detect changes in those in response to dietary treatments. This sampling FQ may be considered when using techniques that measure spot gas exchanges such as the GreenFeed and face mask systems.     

High lithium storage of Co3O4 enabled by integrating hollow and porous carbon scaffolds

The Co₃O₄, as a potential anode of lithium-ion batteries, has gained considerable attention because of high theoretical capacity. However, the Co₃O₄ is suffering from serious structure deterioration and rapid capacity fading due to its bulky volume change during cyclic charge/discharge process. Herein, to stabilize the lithium storage performance of the Co₃O₄ nanoparticles, a characteristic carbon scaffold (HPC) integrating hollow and porous structures has been fabricated by a well-designed method for the first time. The ultrafine Co₃O₄ nanoparticles are cleverly anchored on the HPC (HPC@Co₃O₄) and hence achieve significantly improved electrochemical properties including high capacity, improved reaction kinetics and outstanding cycle stability, showing high capacity of 1084.7 mAh g^-1 after 200 cycles at 200 mA g^-1 as well as 681.4 mAh g^-1 after 300 cycles at 1000 mA g^-1. The HPC@Co₃O₄ therefore shows good promising for application in advanced lithium-ion battery anodes. The results of the systematically material and electrochemical characterizations indicate that the synergistic effects of ultrafine Co₃O₄ nanoparticles and well-designed HPC scaffolds are responsible for the outstand performance of the HPC@Co₃O₄ anode. Moreover, this work can enrich the understanding and development of stable and high-performance metal oxide-based lithium-ion battery anodes for advanced lithium storage.     

空间曲线的特征识别与高质量非均匀采样

为避免传统均匀采样方法因忽视曲线重要特征而生成不理想的采样结果,获得给定数量且由特征点和辅助点组成的采样点序列,提出基于特征识别的高质量空间曲线非均匀采样方法.首先使用抛物线插值法得到曲线上所有曲率极大值点和挠率极大值点的近似位置,经筛选后产生特征点,以更好地抓住空间曲线的轮廓特征.然后定义基于弧长、曲率和挠率加权组合的特征函数,并以此自适应地选取曲线上的辅助点.与3种主流采样方法比较的实验结果表明,该方法能够获得更高质量的采样结果且具有更好的实用性,从而进一步改善空间曲线的B样条拟合效果.     

Real time power management strategy for fuel cell hybrid electric bus based on Lyapunov stability theorem

The fuel cell/battery durability and hybrid system stability are major considerations for the power management of fuel cell hybrid electric bus (FCHEB) operating on complicated driving conditions. In this paper, a real time nonlinear adaptive control (NAC) with stability analyze is formulated for power management of FCHEB. Firstly, the mathematical model of hybrid power system is analyzed, which is established for control-oriented design. Furthermore, the NAC-based strategy with quadratic Lyapunov function is set up to guarantee the stability of closed-loop power system, and the power split between fuel cell and battery is controlled with the durability consideration. Finally, two real-time power management strategies, state machine control (SMC) and fuzzy logic control (FLC), are implemented to evaluate the performance of NAC-based strategy, and the simulation results suggest that the guaranteed stability of NAC-based strategy can efficiently prolong fuel cell/battery lifespan and provide better fuel consumption economy for FCHEB.     

计算机网络办公自动化及安全策略探究

互联网通讯采取标准化模式主要以TCP/IP协议为载体,通讯的优越特性体现在同时具备便捷性与开放性,为办公提供很大的便利,但基于网络系统也会入侵病毒、也会给信息数据与办公体系安全性造成威胁,直接影响企业综合稳定发展。据此,为保障办公工作的顺利开展,本文对计算机网络办公自动化及安全策略进行详细分析。     

Automatic design for shop scheduling strategies based on hyper-heuristics: A systematic review

Against the background of smart manufacturing and Industry 4.0, how to achieve real-time scheduling has become a problem to be solved. In this regard, automatic design for shop scheduling based on hyper-heuristics has been widely studied, and a number of reviews and scheduling algorithms have been presented. Few studies, however, have specifically discussed the technical points involved in algorithm development. This study, therefore, constructs a general framework for automatic design for shop scheduling strategies based on hyper-heuristics, and various state-of-the-art technical points in the development process are summarized. First, we summarize the existing types of shop scheduling strategies and classify them using a new classification method. Second, we summarize an automatic design algorithm for shop scheduling. Then, we investigate surrogate-assisted methods that are popular in the current algorithm field. Finally, current problems and challenges are discussed, and potential directions for future research are proposed.     

Superswelling Microneedle Arrays for Dermal Interstitial Fluid (Prote)Omics

The noninvasive sampling of dermal interstitial fluid (ISF) for the monitoring of clinical biomarkers is a greatly appealing area of research. The identification of molecular biomarkers in biological fluids has been accelerated with -omics analyses but remains limited in ISF because of its time-consuming and complex extraction process. Here, the generation of microneedle (MN) patches made of superabsorbent acrylate-based hydrogels for the rapid sampling of dermal ISF is described to explore its proteome. In depth, iterative optimization allows the identification of novel acrylate-based compositions with the required chemical, mechanical, and biocompatibility properties allowing proteomic analysis of the extracted ISF for the first time after sampling with swelling MNs. The generated MN arrays show no cytotoxic effect, successfully cross the stratum corneum, and can collect up to 6 µL of dermal ISF in 10 min in vivo. Proteomics lead to the detection of 176 clinically relevant biomarkers in the collected samples validating the use of ISF as a relevant bodily fluid for disease monitoring and diagnostic. Importantly, it is discovered that extraction fingerprint is strongly dependent on the MNs chemistry, and thus specific biomarkers could be selectively extracted by tuning the composition of the patch, making the system versatile and specific.     

A novel adaptive sampling based methodology for feasible region identification of compute intensive models using artificial neural network

Identification of feasible region of operations in multivariate processes is a problem of interest in several fields. This is particularly challenging when the process model is black-box in nature and/or is computationally expensive, as analytical solutions are not available and the number of possible model evaluations is limited. An efficient methodology is required to identify samples where the model is evaluated for developing a computationally efficient surrogate model. In this work, an artificial neural network based surrogate model is proposed which is integrated with a statistical-based approach (Jack-knifing) to estimate the variance of the surrogate model prediction. This allows implementation of an adaptive sampling approach where new samples are identified close to the feasible region boundary or in regions of high prediction uncertainty. The proposed approach performs better than a previously published kriging based method for different dimensionality case studies.     

Anticancer activity of flavonoids accompanied by redox state modulation and the potential for a chemotherapeutic strategy

Since researchers began studying the mechanism of flavonoids’ anticancer activity, little attention has been focused on the modulation of redox state in cells as a potential chemotherapeutic strategy. However, recent studies have begun identifying that the anticancer effect of flavonoids occurs both in their antioxidative activity which scavenges ROS and their prooxidative activity which generates ROS. Against this backdrop, this study attempts to achieve a comprehensive analysis of the individual and separate study findings regarding flavonoids’ modulation of redox state in cancer cells. It focuses on the mechanism behind the anticancer effect, and mostly on the modulation of redox potential by flavonoids such as quercetin, hesperetin, apigenin, genistein, epigallocatechin-3-gallate (EGCG), luteolin and kaempferol in both in vitro and animal models. In addition, the clinical applications of and bioavailability of flavonoids were reviewed to help build a treatment strategy based on flavonoids’ prooxidative potential.     

Distributed two‐stage state estimation with event‐triggered strategy for multirate sensor networks

This paper investigates the state estimation issue for a class of wireless sensor networks (WSNs) with the consideration of limited energy resources. First, a multirate estimation model is established, and then, a new event‐triggered two‐stage information fusion algorithm is developed based on the optimal fusion criterion weighted by matrices. Compared with the existing methods, the presented fusion algorithm can significantly reduce the communication cost in WSNs and save energy resources of sensors efficiently. Furthermore, by presetting a desired containment probability over the interval [0,1] with the developed event‐triggered mechanism, one can obtain a suitable compromise between the communication cost and the estimation accuracy. Finally, a numerical simulation for the WSN tracking system is given to demonstrate the effectiveness of the proposed method.