The effect of rice bran on physicochemical,textural and glycaemic properties of ready-to-eat extruded corn snacks

In this work, corn extruded snack products were enriched with rice bran (RB) at 10% and 15%. A co-rotating twin-screw extruder was used with a feed moisture content of 16 g 100 g⁻¹, a screw speed of 240 r.p.m. and four heating sections of the barrel (100, 140, 150 and 150 °C). The impact of RB inclusion on nutritional profile, starch digestion, physicochemical and textural properties of snack products was evaluated. RB-enriched extrudates showed a lower specific volume and hardness and higher crispness than control. RB at 15% gave a water-holding capacity lower than control. Rheology of extrudate dispersions indicated an increase in elastic interactions and solid-like behaviour with RB supplementation. Differences in rheological properties resulted in attenuation of predictive glycaemic response for RB-enriched snacks.     

Strain‐rate‐dependent mechanical properties of polypropylene separator for lithium‐ion batteries

The mechanical integrity of battery separators is critical for battery safety and durability. A comprehensive study of strain‐rate‐dependent tensile and puncture properties of a polypropylene lithium‐ion battery separator is presented here with a new model. Due to anisotropy of the polymeric membrane, tensile testing was conducted for different directions. Results showed that tensile strength and elastic modulus were increased 1000% and 500%, respectively, for different directions. It was also demonstrated that tensile strength changed 10 to 25% with strain rate (1.67 × 10^?4 to 1.67 × 10^?1 s^?1) for different directions. An equation was obtained for the first time for flow stress versus strain rate at varied tensile directions with respect to machine direction. Moreover, puncture testing was performed and it was shown that puncture strength was increased 140% with increasing strain rate from 0.25 to 250 mm min^?1. Two failure modes were also observed in puncture samples. Finally, Eyring's model was used to calculate activation enthalpy of the porous polypropylene separator. © 2020 Society of Chemical Industry     

Cit-CSP及其应用

介绍了Cit-CSP--Cit/E-commerce信息安全保障平台子系统，并阐述了它所提供的消息摘要、块加密、加密(公钥)、签名和MAC等功能和服务。     

Binders for jute-reinforced unsaturated polyester resin

Reinforcement of polyester resin with jute cloth under constant load is studied, The pretreatment of jute cloth with tetrahydrofuran and the effect of binding properties of poly(vinyl acetate) and acrylic acid and their effect on the impact, tensile, and water absorptions of jute cloth polyester composites are reported and their chemical reactions are discussed.     

An Insight View on Synthetic Protocol,Surface Activity,and Biological Aspects of Novel Biocompatible Quaternary Ammonium Cationic Gemini Surfactants

In this study, we prepared a novel series of diester-functionalized cationic gemini surfactants (C_m-E2O2-C_m) containing ethylene oxide as a spacer with varying alkyl chain lengths and characterized by ¹H NMR, FT-IR, elemental analysis, and ESI-MS. The physicochemical properties of the geminis were explored by tensiometry, fluorescence, dye solubilization, and Krafft point. These geminis acquire superior surface activity than the conventional surfactants. Fluorescence spectroscopy analysis affirmed that the micropolarity and aggregation number of micelles diminished with increase in the alkyl chain length. These geminis represent a new group of amphiphiles of considerably high biodegradability, better cleavability, and low toxicity as assessed by BOD test, FT-IR analysis, and HC₅₀ analysis, respectively. They also showed significant level of antimicrobial activity toward some specified bacterial strains of Gram-positive and Gram-negative by using agar well diffusion method. Furthermore, the thermogravimetric analysis provided information regarding thermal stabilities of the newly synthesized gemini surfactants.     

Analytical Modeling of Short-Channel Fully-Depleted Triple Work Function Metal Gate (TWFMG) SOI MESFET

Silicon - In this paper, a new structure: triple work function metal gate SOI MESFET, intended for integration into the deep-submicron CMOS technology, is proposed. The gate of the device consists...     

An Engineered sgsh Mutant Zebrafish Recapitulates Molecular and Behavioural Pathobiology of Sanfilippo Syndrome A/MPS IIIA

Mucopolysaccharidosis IIIA (MPS IIIA, Sanfilippo syndrome type A), a paediatric neurological lysosomal storage disease, is caused by impaired function of the enzyme N-sulfoglucosamine sulfohydrolase (SGSH) resulting in impaired catabolism of heparan sulfate glycosaminoglycan (HS GAG) and its accumulation in tissues. MPS IIIA represents a significant proportion of childhood dementias. This condition generally leads to patient death in the teenage years, yet no effective therapy exists for MPS IIIA and a complete understanding of the mechanisms of MPS IIIA pathogenesis is lacking. Here, we employ targeted CRISPR/Cas9 mutagenesis to generate a model of MPS IIIA in the zebrafish, a model organism with strong genetic tractability and amenity for high-throughput screening. The sgsh^Δex5−6 zebrafish mutant exhibits a complete absence of Sgsh enzymatic activity, leading to progressive accumulation of HS degradation products with age. sgsh^Δex5−6 zebrafish faithfully recapitulate diverse CNS-specific features of MPS IIIA, including neuronal lysosomal overabundance, complex behavioural phenotypes, and profound, lifelong neuroinflammation. We further demonstrate that neuroinflammation in sgsh^Δex5−6 zebrafish is largely dependent on interleukin-1β and can be attenuated via the pharmacological inhibition of Caspase-1, which partially rescues behavioural abnormalities in sgsh^Δex5−6 mutant larvae in a context-dependent manner. We expect the sgsh^Δex5−6 zebrafish mutant to be a valuable resource in gaining a better understanding of MPS IIIA pathobiology towards the development of timely and effective therapeutic interventions.     

Design and simulation of a novel metallic microgripper using vibration to release nano objects actively

In this study, we investigate a novel metallic microgripper which is able to grasp and transport nano particles (nano tubes/wires) and release them on desirable substrate by vibrating the gripper arms. This microgripper consists of a chevron actuator to grip nano object electrothermally and interdigited comb drive systems to generate vibration at the gripper arms electrostatically. Metallic (nickel) properties enable the chevron actuator to close the gap and pick the nano particle at low voltage and temperature. In order to reduce the out of plane bending during operation and also increase the gripping force, thickness of the nickel layer must be increased, hence electroplating process is proposed for deposition of nickel layer. To generate vibration at the end effectors, comb drive systems are stimulated by applying two voltage signals at desired resonant frequency to the stators. Practically, by sweeping the frequency of these signals around the resonant frequency the end effectors start vibrating. The vibration results in overcoming the adhesion forces due to inertial effects.     

Support vector regression methodology for prediction of input displacement of adaptive compliant robotic gripper

The prerequisite for new versatile grippers is the capability to locate and perceive protests in their surroundings. It is realized that automated controllers are profoundly nonlinear frameworks, and a faultless numerical model is hard to get, in this way making it troublesome to control utilizing tried and true procedure. Here, a design of an adaptive compliant gripper is presented. This design of the gripper has embedded sensors as part of its structure. The use of embedded sensors in a robot gripper gives the control system the ability to control input displacement of the gripper and to recognize specific shapes of the grasping objects. Since the conventional control strategy is a very challenging task, soft computing based controllers are considered as potential candidates for such an application. In this study, the polynomial and radial basis function (RBF) are applied as the kernel function of Support Vector Regression (SVR) to estimate and predict optimal inputs displacement of the gripper according to experimental tests and shapes of grasping objects. Instead of minimizing the observed training error, SVR _poly and SVR _rbf attempt to minimize the generalization error bound so as to achieve generalized performance. The experimental results show that an improvement in predictive accuracy and capability of generalization can be achieved by the SVR approach compared to other soft computing methodology.