一种有效的除臭物质—脱乙酰壳多糖(英)

阐述了脱乙酰壳多糖使用于除臭剂配方中能提供良好的感觉和效果 ,不产生白色残留物和皮肤刺激性 ,且解释了其原因。     

Oil Palm Fibre Reinforced Phenol Formaldehyde Composites: Influence of Fibre Surface Modifications on the Mechanical Performance

Oil palm fibres have been used as reinforcement in phenol formaldehyde resin. In order to improve the interfacial properties, the fibres were subjected to different chemical modifications such as mercerisation, acrylonitrile grafting, acrylation, latex coating, permanganate treatment, acetylation, and peroxide treatment. The effect of fibre coating on the interface properties has also been investigated. Morphological and structural changes of the fibres were investigated using scanning electron microscopy and IR spectroscopy. Mechanical properties of untreated and treated fibres were studied. Changes in stress–strain characteristics, tensile strength, tensile modulus and elongation at break of the fibres upon various modifications were studied and compared. The incorporation of the modified fibres resulted in composites having excellent impact resistance. Fibre coating enhanced the impact strength of untreated composite by a factor of four. Tensile and flexural performance of the composites were also investigated. Finally, inorder to have an insight into the failure behaviour, the tensile and impact fracture surfaces of the composites were analysed using scanning electron microscope.     

Dynamical mechanical analysis of sisal/oil palm hybrid fiber‐reinforced natural rubber composites

Natural rubber was reinforced with sisal and oil palm fibers and was subjected to dynamic mechanical analysis to determine the dynamic properties as a function of temperature. The storage modulus E′ was found to increase with weight fraction of fiber. This is due to the increased stiffness imparted by the natural fibers. Loss modulus increased with loading while the damping property was found to decrease. The fibers were subjected to alkali treatment of different concentrations namely 0.5, 1, 2, and 4% and the dynamic properties were studied. In the case of composites containing chemically modified fibers, storage modulus and loss modulus were found to increase. Scanning electron micrographs of tensile fracture surfaces of treated and untreated composites demonstrated better fiber–matrix bonding in the case of the former. POLYM. COMPOS., 27: 671–680, 2006. © 2006 Society of Plastics Engineers     

Performance analysis and optimization design of an axial‐flow vane separator for supercritical CO2 (sCO2)‐water mixtures from geothermal reservoirs

Supercritical CO₂ (sCO₂) has been proven to be a promising working fluid for geothermal heat mining, and the produced hot sCO₂ can be directly used for power generation. However, the sCO₂ produced from a brine‐based reservoir may contain a certain amount of water, preventing direct power‐cycle utilization. In this paper, an axial vane separator was designed to address the separation problem of sCO₂ and water produced from geothermal reservoirs. First, the influences of operational and structural parameters on the separation performance were analyzed through numerical simulations. Five factors were selected to develop separation performance regression models by the response‐surface method (RSM). Finally, geometrical parameter optimization was applied to these RSM models. The results show that the guide vane area and the exhaust inlet are the main locations impacting the system pressure drop. The separation performance can be affected by many factors, including the guide blade outlet angle, number of vanes, hub diameter, length of the vortex tube, droplet size, and inlet velocity. The water‐droplet size and the number of vanes are the most critical factors affecting the separation efficiency. The inlet velocity, the number of vanes, and the hub diameter have a larger influence on the pressure drop of the separator. The optimization results indicate that the separation efficiency can reach 100% under certain operating conditions with a pressure drop no greater than 100 kPa.     

On‐line estimation of switched reluctance motor parameters

This paper addresses the problem of on‐line parameter estimation of switched reluctance motors and provides, to the best of the authors' knowledge, the first result that takes into account the dynamics of both electrical and mechanical subsystems. Based on a widely‐used standard model of the motor and establishing a reasonable structure for modeling the unknown load torque, a linear parametric model is derived and a 2‐stage identification scheme is proposed and implemented with the recursive least‐squares algorithm with forgetting factor. It is assumed that stator voltages and currents and rotor position and speed are available through measurements. Numerical simulations and experimental tests are included for a 3‐phase 12/8 switched reluctance motor. The results show a good performance of the proposed methodology, and the estimated parameters are validated through their use in a closed‐loop control scheme. Key features of the proposed solution are that it does not rely on locked‐rotor tests nor does it assume previous knowledge of the magnetization curves of the motor. The estimation scheme is intended to improve the performance and efficiency of currently available control algorithms, and it is potentially useful for the design of selfcommissioning switched reluctance drives, ie, drives that can automatically adjust the controller parameters for a wide range of motors and loads.     

Dual-Mechanism Quenched Fluorogenic Probe Provides Selective and Rapid Detection of Cathepsin L Activity**

Cathepsin L (CTL) is a cysteine protease demonstrating upregulated activity in many disease states. Overlapping substrate specificity makes selective detection of CTL activity difficult to parse from that of its close homologue CTV and the ubiquitous CTB. Current probes of CTL activity have limited applications due to either poor contrast or extra assay steps required to achieve selectivity. We have developed a fluorogenic probe, CTLAP, that displays good selectivity for CTL over CTB and CTV while exhibiting low background fluorescence attributed to dual quenching mechanisms. CTLAP achieves optimum CTL selectivity in the first 10 min of incubation, thus suggesting that it is amenable for rapid detection of CTL, even in the presence of competing cathepsins.     

Performance Evaluation of Best Feature Subsets for Crop Yield Prediction Using Machine Learning Algorithms

The rapid innovations and liberalized market economy in agriculture demand accuracy in Crop Yield Prediction (CYP). In accurate prediction, machine learning (ML) algorithms and the selected features play a major role. The performance of any ML algorithm may improve with the utilization of a distinct set of features in the same training dataset. This research work evaluates the most needed features for accurate CYP. The ML algorithms, namely, Artificial Neural Network, Support Vector Regression, K-Nearest Neighbour and Random Forest (RF) are proposed for better accuracy. Agricultural dataset consists of 745 instances; 70% of data are randomly selected and are used to train the model and 30% are used for testing the model to assess the predictive ability. The results show that the RF algorithm reaches the highest accuracy by means of its error analysis values for all the distinct feature subsets using the same training agricultural data.     

Economic and epidemiological impact of different intervention strategies for clinical contagious mastitis

The overall aim of this study was to compare different intervention strategies for clinical intramammary infections (IMI). We conducted a simulation study to represent a Danish dairy cattle herd with IMI caused mostly by Staphylococcus aureus and 9 different intervention strategies for clinical IMI. A standard intervention of 3 d of treatment consisting of intramammary injections for all clinical cases was used. Two of the strategies reflected the use of more antibiotics and 6 strategies reflected cow-specific treatment or culling decisions. For these strategies, we assessed the cost and effectiveness of culling as an IMI intervention. Our results showed that nearly all strategies could reduce the number of IMI cases [e.g., a median of 37 clinical cases with the extended intramammary treatment over 5 d strategy (Basic5) and 30 clinical cases with the cow culled with recovery probability below 50% (Before50)] compared with the standard intervention (median of 42 clinical cases). This happened alongside either increased antibiotic usage (e.g., from a median of 123 treatment days up to 179 treatment days with strategy Basic5) or an increased number of cows culled in relation to IMI (e.g., from a median of 16 up to 24 cows with strategy Before50). Strategies with more antibiotics or reactive culling had a slightly higher net income (e.g., €190,014 median net income with strategy Basic5 or €196,995 with strategy Before50 compared with €187,666 with the standard strategy). This shows that a cow-specific clinical intervention approach can be cost-effective in reducing IMI incidence.