Optimization of NiFe2O4/rGO composite electrode for lithium-ion batteries

The combination of carbon compositing and the proper choice of binders in one system offer an effective strategy for improving electrode performance for lithium ion batteries (LIBs). Here, we focus on the optimization of reduced graphene oxide content in NiFeO/reduced graphene oxide (abbreviated to NiFeO/rGO) composites and the proper choice of binders to enhance the cycling stability of the NiFeO electrode. The NiFeO/rGO composites were fabricated by a hydrothermal-annealing method, in which the mean size of spinel NiFeO nanoparticles was approximately 20\ua0nm. When tested as anode materials for LIBs, the NiFeO/rGO electrodes with carboxymethylcellulose (CMC) binder exhibited excellent lithium-storage performance including high reversible capacity, good cycling durability and high-rate capability. The capacity could be retained as high as 1105\ua0mAh\ua0g at a current density of 100\ua0mA\ua0g for over 50 cycles, even cycled at higher current density of 1000\ua0mA\ua0g, a capacity of 800\ua0mAh\ua0gcan be obtained, whereas the electrode with the polyvinylidene fluoride (PVDF) binder suffered from rapid capacity decay under the same test conditions. As a result, the NiFeO/rGO composites with CMC binder electrode in this work are promising as anodes for high-performance LIBs, resulting from the synergistic effect of optimal graphene content and proper choice of binder

Effects of yeast culture and oxalic acid supplementation on in vitro nutrient disappearance, rumen fermentation, and bacterial community composition

Hemicellulose is an important polysaccharide in ruminant nutrition, but it has not been studied as thoroughly as cellulose. Further research is needed to explore supplements that can improve its digestibility and ruminal buffering effects. Our previous research demonstrated the efficacy of oxalic acid (OA) as an essential nutrient in yeast culture (YC) for improving rumen fermentation performance. Consequently, we conducted in vitro rumen digestion experiments to examine the effects of YC and OA on rumen fermentation and bacterial composition. Two diets containing different levels of hemicellulose were formulated: diet 1 with 10.3% and diet 2 with 17% hemicellulose. Three levels of YC (0.00, 0.625, and 1.25 g/kg) and three doses of OA (0.0, 0.4, and 0.8 g/kg, DM) were added into each diet with a 3 × 3 factorial design. A comprehensive assessment was conducted on a total of 18 experimental treatments at fermentation periods of 0, 6, 12, 24, and 48 h. In the first experiment (diet 1), the supplementation of YC, OA, and their interaction significantly increased in vitro DM disappearance (IVDMD) and NDF disappearance (IVNDFD; p < 0.001). In the second experiment (diet 2), the supplementation of OA and the interaction between YC and OA (p < 0.001) increased IVDMD and IVCPD, but had no significant effects on IVNDFD. The interactions of YC and OA significantly increased ammonia nitrogen (p < 0.001). The production of acetic acid, propionic acid, and total volatile fatty acids (TVFA), and pH levels were significantly higher in treatments supplemented with YC and OA (p < 0.001). YC and OA in both diets significantly altered the rumen bacterial community leading to increased Shannon and Simpson diversity indices (p < 0.001). In both diets, OA supplementation significantly increased the relative abundance of the phylum Bacteroidetes and Prevotella genus. The result also showed a positive correlation between the Prevotella and Selenomonas genera with IVDMD, IVNDFD, propionic acid, and TVFA production, suggesting that these dominant bacteria enhanced nutrient disappearance in the rumen. In conclusion, adding YC and OA resulted in modifications to the bacterial community’s composition and diversity, and improved nutrient disappearance. These changes indicate improved rumen fermentation efficiency, which is promising for future in vivo studies

Mechanistic insights into inositol-mediated rumen function promotion and metabolic alteration using in vitro and in vivo models

Inositol is a bioactive factor that is widely found in nature; however, there are few studies on its use in ruminant nutrition. This study investigated the effects of different inositol doses and fermentation times on rumen fermentation and microbial diversity, as well as the levels of rumen and blood metabolites in sheep. Rumen fermentation parameters, microbial diversity, and metabolites after different inositol doses were determined in vitro. According to the in vitro results, six small-tailed Han sheep fitted with permanent rumen fistulas were used in a 3 × 3 Latin square feeding experiment where inositol was injected into the rumen twice a day and rumen fluid and blood samples were collected. The in vitro results showed that inositol could increase in vitro dry matter digestibility, in vitro crude protein digestibility, NH3-N, acetic acid, propionic acid, and rumen microbial diversity and affect rumen metabolic pathways (p < 0.05). The feeding experiment results showed that inositol increased the blood concentration of high-density lipoprotein and IgG, IgM, and IL-4 levels. The rumen microbial composition was significantly affected (p < 0.05). Differential metabolites in the rumen were mainly involved in ABC transporters, biotin metabolism, and phenylalanine metabolism, whereas those in the blood were mainly involved in arginine biosynthesis and glutathione and tyrosine metabolism. In conclusion, inositol improves rumen function, affects rumen microorganisms and rumen and blood metabolites and may reduce inflammation, improving animal health

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Using Blockly to Create Simple Sensor & Actuator Based Applications on the SensibleThings Platform

Research at Miun investigates the so called “Internet of Things”. The research has so far produced components for sharing sensor and actuator information on the Internet, most notably the Sensible Things platform. The Sensible Things platform can run on many different devices such as smart phones, raspberry Pi devices, and desktop computers. However, programming applications based on the Sensible Things platform and deploying it on the hardware require knowledge of the Java programming language and the API of the platform. Today, many novice and first time programmers learn to program using the Blockly programming method, which include connecting blocks together to form simple procedures. Therefore, we have applied the Blocky method to ease the development of simple applications on the Sensible Things platform. After the work was done, the general users are now able to create entry level Sensible Things Applications

Study on water stability of asphalt binder with medium weathered igneous rock

Aiming at the problems of weak acidity of medium weathered igneous rock around Nairobi, Kenya, poor adhesion with asphalt and poor water stability of asphalt binder, the article studied the use of anti-stripping agent, cement, hydrated Lime and other technical measures to improve the water stability of asphalt binder with medium weathered igneous rock. The results showed that the 48h Marshall residual stability of the benchmark asphalt binder without any measures was 78.5%, which did not meet the standard requirements. The Marshall residual stability of medium weathered igneous rock can be significantly improved by adding anti stripping agent, cement and hydrated Lime. After freeze-thaw cycles, the splitting tensile strength of the asphalt binder with medium weathered igneous rock decreased obviously, and the TSR values of the asphalt binder with anti-spalling measures from small to large were K-4, K-3, K-2, K-6 and K-5. The water stability of the medium weathered igneous rock asphalt binder mixed with anti-stripping agent alone had relatively poor durability, and the medium weathered igneous rock asphalt binder mixed with cement and anti-stripping agent had the strongest ability to resist deformation when immersed in water

Practical polarization maintaining optical fibre temperature sensor for harsh environment application

Abstract A reflection spot temperature sensor was proposed based on the polarization mode interference in polarization maintaining optical fibre (PMF) and the phenomenon that the propagation constant difference of the two orthogonal polarization modes in stressing structures PMF is sensitive to temperature and the sensing equation was obtained. In this temperature sensor, a broadband source was used to suppress the drift due to polarization coupling in lead-in/lead-out PMF. A characteristic and performance investigation proved this sensor to be practical, flexible and precise. Experimental results fitted the theory model very well and the noise-limited minimum detectable temperature variation is less than 0.01 • C. The electric arc processing was investigated and the differential propagation constant modifying the PMF probe is performed. For the demand of field hot-spot monitoring of huge power transformers, a remote multi-channel temperature sensor prototype has been made and tested. Specially coated Panda PMF that can stand high temperatures up to 250 • C was fabricated and used as probe fibres. The sensor probes were sealed within thin quartz tubes that have high voltage insulation and can work in a hot oil and vapour environment. Test results show that the accuracy of the system is better than ±0.5 • C within 0 • C to 200 • C

Industrial Carbon Emission Efficiency of Cities in the Pearl River Basin: Spatiotemporal Dynamics and Driving Forces

In the context of green and high-quality development, effectively enhancing industrial carbon emission efficiency is critical for reducing carbon emissions and achieving sustainable economic growth. This study explored this research area using three models: the super-efficient SBM model was used to measure the industrial carbon emission efficiency of 48 cities in the Pearl River Basin from 2009 to 2017; the exploratory spatiotemporal data analysis method was used to reveal the spatiotemporal interaction characteristics of industrial carbon emission efficiency; and the geographical detectors and geographically weighted regression model were employed to explore the influencing factors. The results are as follows: (1) The Pearl River Basin’s industrial carbon emission efficiency steadily increased from 2009 to 2017, with an average annual growth rate of 0.18 percent, but the industrial carbon emission efficiency of some sites remains low; (2) The local spatiotemporal pattern of industrial carbon emission efficiency is solitary and spatially dependent; (3) The spatial variation of industrial carbon emission efficiency is influenced by a number of factors, including the industrialization level, openness to the outside world, the science and technology level, energy consumption intensity, and productivity level, with the productivity level, industrialization level, and openness to the outside world being the most important. Among these factors, the productivity level, science and technology level, openness to the outside world, and industrialization level all have a positive correlation with industrial carbon emission efficiency, but energy consumption intensity has a negative correlation. This study provides an integrated framework using exploratory spatiotemporal analysis and geographically weighted regression to examine carbon emission efficiency among cities. It can serve as a technical support for carbon reduction policies in cities within the Pearl River Basin, as well as a reference for industrial carbon emission studies of other regions of the world

Industrial Carbon Emission Efficiency of Cities in the Pearl River Basin: Spatiotemporal Dynamics and Driving Forces

In the context of green and high-quality development, effectively enhancing industrial carbon emission efficiency is critical for reducing carbon emissions and achieving sustainable economic growth. This study explored this research area using three models: the super-efficient SBM model was used to measure the industrial carbon emission efficiency of 48 cities in the Pearl River Basin from 2009 to 2017; the exploratory spatiotemporal data analysis method was used to reveal the spatiotemporal interaction characteristics of industrial carbon emission efficiency; and the geographical detectors and geographically weighted regression model were employed to explore the influencing factors. The results are as follows: (1) The Pearl River Basin’s industrial carbon emission efficiency steadily increased from 2009 to 2017, with an average annual growth rate of 0.18 percent, but the industrial carbon emission efficiency of some sites remains low; (2) The local spatiotemporal pattern of industrial carbon emission efficiency is solitary and spatially dependent; (3) The spatial variation of industrial carbon emission efficiency is influenced by a number of factors, including the industrialization level, openness to the outside world, the science and technology level, energy consumption intensity, and productivity level, with the productivity level, industrialization level, and openness to the outside world being the most important. Among these factors, the productivity level, science and technology level, openness to the outside world, and industrialization level all have a positive correlation with industrial carbon emission efficiency, but energy consumption intensity has a negative correlation. This study provides an integrated framework using exploratory spatiotemporal analysis and geographically weighted regression to examine carbon emission efficiency among cities. It can serve as a technical support for carbon reduction policies in cities within the Pearl River Basin, as well as a reference for industrial carbon emission studies of other regions of the world