以猪小肠黏膜提取物作为α-葡萄糖苷酶和二肽基肽酶IV的酶活力分析体系的建立

α-葡萄糖苷酶和二肽基肽酶IV（dipeptidyl peptidase 4,DPP-4）是II型糖尿病治疗中2 种重要的靶向酶。这两种商品化酶价格昂贵且主要来源于微生物,难以有效用于两种酶抑制剂的筛选,而这两种酶均普遍存在哺乳动物的小肠中。为了获得经济有效、来源于哺乳动物体内的α-葡萄糖苷酶和DPP-4,本研究收集新鲜的猪小肠黏膜分泌物及上皮细胞,对比分析了猪小肠不同部位黏膜提取物的α-葡萄糖苷酶和DPP-4的活力。以猪小肠黏膜提取物作为α-葡萄糖苷酶和DPP-4的酶反应体系,并且利用这两种酶的阳性药（阿卡波糖和抑二肽素A（diprotin A,IPI））分别进行了抑制率验证和评价。阿卡波糖对商品和猪回肠源α-葡萄糖苷酶的半数有效抑制质量浓度（median inhibition concentration,IC50）分别是1.102 4、0.244 7 mg/mL;IPI对商品和猪回肠源DPP-4的IC50分别为19.119 7、41.268 4 μg/mL。通过比较发现,猪回肠黏膜提取物的α-葡萄糖苷酶和DPP-4比活力分别为0.084 1、0.053 4 U/mg,在3 种黏膜提取物中均为最高,因此选择猪回肠黏膜提取物作为商品化α-葡萄糖苷酶和DPP-4的替代物进行抑制剂的筛选。     

Elliptical slot based polarization insensitive compact and flexible chipless RFID tag

A miniaturized, polarization insensitive, and fully passive chipless radio frequency identification tag is proposed in this research article. The realized tag is based on slotted elliptical structures in a nested loop fashion with identical lengths and widths of slot resonators. Alteration of data sequence is accomplished by addition and elimination of nested resonators in the geometric structure. The tag is capable to encode 10 bits of data and covers spectral range from 3.6 to 15.6 GHz. The formulated structure demonstrates polarization insensitive characteristic. The data encoding structure is analyzed and optimized for different substrates that are, Rogers RT/duroid/5880, Rogers RT/duroid/5870, and Taconic TLX‐0 over the miniaturized footprint of 22.8 × 16 mm². The presented tag is robust, novel, compact, and flexible exhibiting a stable response to impinging electromagnetic waves at various angles of incidence.     

Modeling and operation optimization of RE integrated microgrids considering economic,energy, and environmental aspects

Microgrids provide promising solution for integration of renewable energy sources in the electrical grid. To exploit the key benefits, achieving the economical operation of renewable aided microgrids has become necessary and is a challenging task. This paper presents an efficient optimization model to minimize the operational cost of a solar integrated microgrid. We formulate a joint optimization mixed integer problem for appropriate modeling of the system under various practical constraints. An efficient solution is obtained with a distributed approach such that the original problem is solved in two stages. Dual decomposition approach is adopted for cost, emissions, and solar share optimization. Lagrange relaxation, Lambda iteration method, and binary integer programming are employed to obtain the joint optimization solution. Finally, the performance of the proposed model is validated through simulations that show that an overall cost reduction of 4.2070e+04 $ and emission reduction of 7.2001e+03 kg are achieved with the proposed model.     

An effective back‐off selection technique for reliable beacon reception in VANETs

In safety‐critical scenarios, reliable reception of beacons transmitted by a subject vehicle is critical to avoid vehicle collision. According to the employed contention window sizes in IEEE 802.11p, beacons are transmitted with a small contention window size. As a result, multiple vehicles contend for the shared channel access by selecting the same back‐off slot. This is a perfect recipe for synchronous collisions wherein reliable beacon delivery cannot be guaranteed for any vehicle. We consider the problem of selecting the back‐off slots from the current contention window to provide reliable delivery of beacons transmitted by a subject vehicle to its neighbors. Given a safety scenario, we propose a Pseudo‐Random Number Generator (PRNG)‐inspired back‐off selection (PBS) technique. The proposed technique works on the hypothesis that synchronous collisions of beacons transmitted by a subject vehicle can be reduced if all its neighbors select different back‐off slots (ie, not the back‐off slot selected by the subject vehicle). The discrete‐event simulations demonstrate that PBS can increase the overall message reception from a subject vehicle, in comparison with the uniform random probability back‐off selection in IEEE 802.11p.     

From Arteries to Capillaries: Approaches to Engineering Human Vasculature

From microscaled capillaries to millimeter‐sized vessels, human vasculature spans multiple scales and cell types. The convergence of bioengineering, materials science, and stem cell biology has enabled tissue engineers to recreate the structure and function of different hierarchical levels of the vascular tree. Engineering large‐scale vessels aims to replace damaged arteries, arterioles, and venules and their routine application in the clinic may become a reality in the near future. Strategies to engineer meso‐ and microvasculature are extensively explored to generate models for studying vascular biology, drug transport, and disease progression as well as for vascularizing engineered tissues for regenerative medicine. However, bioengineering tissues for transplantation has failed to result in clinical translation due to the lack of proper integrated vasculature for effective oxygen and nutrient delivery. The development of strategies to generate multiscale vascular networks and their direct anastomosis to host vasculature would greatly benefit this formidable goal. In this review, design considerations and technologies for engineering millimeter‐, meso‐, and microscale vessels are discussed. Examples of recent state‐of‐the‐art strategies to engineer multiscale vasculature are also provided. Finally, key challenges limiting the translation of vascularized tissues are identified and perspectives on future directions for exploration are presented.     

Recent progress in the modification of carbon materials and their application in composites for electromagnetic interference shielding

With the development in the modern technologies such as telecommunication instruments and scientific electronic devices, large amount of the electromagnetic radiations are produced, which lead to harmful effect on the highly sensitive electronic devices as well as on the health of human beings. To minimize the effect of electromagnetic radiations produced by different technologies, more efficient shielding materials are required which must be cost-effective, lightweight and good corrosion resistive. In this review, we focused on the shielding materials based on composites of carbon nanotubes and graphene. The typical surface modification of carbon nanotubes and graphene to optimize their interactions with polymers matrix has also summarized. It was found that the composites based on these carbon fillers were more efficient for electromagnetic interference shielding due to their unique properties (i.e., superior electrical, mechanical and thermal) together with lightweight, easy processing. Hence, the carbon nanotubes and graphene-based composites are excellent shielding materials against the electromagnetic radiations.     

Controlling the material removal and roughness of Inconel 718 in laser machining

Nickel alloys including Inconel 718 are considered as challenging materials for machining. Laser beam machining could be a promising choice to deal with such materials for simple to complex machining features. The machining accuracy is mainly dependent on the rate of material removal per laser scan. Because of the involvement of many laser parameters and complexity of the machining mechanism it is not always simple to achieve machining with desired accuracy. Actual machining depth extremely varies from very low to aggressively high values with reference to the designed depth. Thus, a research is needed to be carried out to control the process parameters to get actual material removal rate (MRR_act) equals to the theoretical material removal rate (MRR_th) with minimum surface roughness (SR) of the machined surfaces. In this study, five important laser parameters have been used to investigate their effects on MRR and SR. Statistical analysis are performed to identify the significant parameters with their strength of effects. Mathematical models have been developed and validated to predict the machining responses. Optimal set of laser parameters have also been proposed and confirmed to achieve the actual MRR close to the designed MRR (MRR_% = 100.1%) with minimum surface roughness (R_a = 2.67 µm).     

WEDM of layered composite: analyzing material removal and cut quality issues

The use of cladded bimaterial composites has grown in the recent past as they offer a combination of properties at low cost. But the heterogeneity which is the inherent attribute of these composites makes it challenging to accurately cut via conventional means. Therefore, thermal cutting is commonly employed for their cutting which not only produce poor cut quality and deeper heat affected zones but also demand subsequent finishing operations. Wire electric discharge cutting (WEDM) is a proficient alternate but low material removal (MRR) and widen kerf slot (KW) due to sideways sparking limit its application. Moreover, both layers of material have different thermoelectric properties and are subjected to simultaneous cutting by a single moving wire electrode which lead to produce different spark strength against both layers. In this regard, the present study aims to investigate the cutting potential of WEDM for cladded bimaterial with a prior focus on both the aforesaid issues, i.e. MRR and KW. Considering the thermoelectric nature of the WEDM, workpiece-related parameters like orientation of work surface and layer thickness of each layer are taken as control variables in addition to the WEDM process parameters. Experimental results are thoroughly analyzed using statistical and SEM analysis.     

Novel Analytical Thermal Performance Rate Analysis in ZnO-SAE50 Nanolubricant: Nonlinear Mathematical Model

The investigation of local thermal transport rate in the nanolubricants is significant. These lubricants are broadly used in environmental pollution, mechanical engineering and in the paint industry due to high thermal performance rate. Therefore, thermal transport in ZnO-SAE50 nanolubricant under the impacts of heat generation/absorption is conducted. The colloidal suspension is flowing between parallel stretching disks in which the lower disk is positioned at z = 0 and upper disk apart from distance d. The problem is transformed in dimensionless version via described similarity transforms. In the next stage, an analytical technique (VPM) is implemented for the solution purpose. The graphical results against multiple flow parameters were furnished over the region of interest and explained comprehensively. It is imperative to mention that the results are plotted for ZnO-SAE50 and conventional liquid as well. Further, rapid motion of the fluid is perceived against high Reynolds and γ parameters. The wall shear stresses at the upper end rises for multiple Reynolds and γ while; decrement is detected at the lower end. The significant contribution of an internal heat source is noted for thermal performance rate at the upper end. Foremost, the local heat transport rate declines at the lower disk. By altering Reynolds number, prompt heat transfer rate is gained at the upper disk and increasing behavior of the local heat transport rate is slow at the lower disk. From the study, it is concluded that the nanolubricants have high thermal characteristics. Therefore, such fluids are reliable to use in above stated areas.     

A New Hybrid SARFIMA-ANN Model for Tourism Forecasting

Many countries developed and increased greenery in their country sights to attract international tourists. This planning is now significantly contributing to their economy. The next task is to facilitate the tourists by sufficient arrangements and providing a green and clean environment; it is only possible if an upcoming number of tourists’ arrivals are accurately predicted. But accurate prediction is not easy as empirical evidence shows that the tourists’ arrival data often contains linear, nonlinear, and seasonal patterns. The traditional model, like the seasonal autoregressive fractional integrated moving average (SARFIMA), handles seasonal trends with seasonality. In contrast, the artificial neural network (ANN) model deals better with nonlinear time series. To get a better forecasting result, this study combines the merits of the SARFIMA and the ANN models and the purpose of the hybrid SARFIMA-ANN model. Then, we have used the proposed model to predict the tourists’ arrival in New Zealand, Australia, and London. Empirical results showed that the proposed hybrid model outperforms in predicting tourists’ arrival compared to the traditional SARFIMA and ANN models. Moreover, these results can be generalized to predict tourists’ arrival in any country or region with a complicated data pattern.