使用热分析方法研究化学改性剂对淀粉性质的影响

经过化学改性后的玉米淀粉应用范围很广,目前主要应用在制药及食品行业。本研究中,对从玉米淀粉中提取出的直链淀粉和支链淀粉做了阳离子化改性处理,即使用季铵盐处理原淀粉得到不同的改性产品,并将这些阳离子化改性淀粉与未改性的原淀粉做了比较。同时本实验也研究了原淀粉及改性淀粉的热力学行为,同时使用TG-DTA及DSC测试手段对该改性淀粉的热降解行为进行表达,本文的一个目的也是将这些原淀粉进行表面阳离子化处理,进而制定一套对改性淀粉及未改性淀粉的分析测试方法。     

A Review of Transmission Rate over Wireless Fading Channels: Classifications,Applications, and Challenges

To address the explosive traffic demands, the capacity of the fading channel is increasingly becoming a prime concern in the designing of the wireless communication system. The channel capacity is an extremely important quantity, since it allows the transmission of the data through the channel with an arbitrarily small probability of error. In other words, capacity dictates the maximum rate of information transmission, called as ‘capacity’ of channel, determined by the intrinsic properties of the channel and is independent of the content of the transmitted information. In this paper, we present a comprehensive survey of the existing work related to the channel capacity model over various fading channels. With an elaborated explanation of the theory of channel capacity, definitions of channel capacity based on the channel state information are reviewed. To compliment this, review of the technique to enhance the channel capacity is discussed and reviewed. An effective capacity model to overcome the channel capacity limitation is also explained. Furthermore, as the secure transmission of data is of utmost importance, to address this physical layer security model is also reviewed. We also summarize the work related to channel capacity in various types of wireless networks. We finally cover the future research directions, including less explored aspects of the channel capacity that can be studied to design efficient communication systems.

     

Application Layer Scheduling in Cloud: Fundamentals,Review and Research Directions

The cloud computing paradigm facilitates a finite pool of on-demand virtualized resources on a pay-per-use basis. For large-scale heterogeneous distributed systems like a cloud, scheduling is an essential component of resource management at the application layer as well as at the virtualization layer in order to deliver the optimal Quality of Services (QoS). The cloud scheduling, in general, is an NP-hard problem due to large solution space, thus, it is difficult to find an optimal solution within a reasonable time. In application layer scheduling, the tasks are mapped to logical resources (i.e., virtual machines), aiming to optimize one or more QoS parameters, and conforming to several constraints. Various algorithms have been proposed in the literature for application layer scheduling, where each of them is based on some fundamental design techniques like simple heuristics, meta-heuristics, and most recently hybrid heuristics. Although ample literature survey exists for cloud scheduling algorithms, none of them present their study exclusively for the application layer. In this survey paper, we present a study on task scheduling algorithms used only at the application layer of the cloud. We classify our study according to various fundamental techniques used in designing such scheduling algorithms. One of the main features of our study is that it covers numerous application type e.g., a set of independent tasks, simple workflow, scientific workflow, and MapReduce jobs. We also provide a comparative analysis of existing algorithms on various parameters like makespan, cost, resource utilization, etc. In the end, research directions for future work have been provided.     

Lightweight Cryptography: A Solution to Secure IoT

In Internet of Things (IoT), the massive connectivity of devices and enormous data on the air have made information susceptible to different type of attacks. Cryptographic algorithms are used to provide confidentiality and maintain the integrity of the information. But small size, limited computational capability, limited memory, and power resources of the devices make it difficult to use the resource intensive traditional cryptographic algorithms for information security. In this scenario it becomes impertinent to develop lightweight security schemes for IoT. A thorough study on the lightweight cryptography as a solution to the security problem of resource-constrained devices in IoT has been presented in this work. This paper is a comprehensive attempt to provide an in-depth and state of the art survey of available lightweight cryptographic primitives till 2019. In this paper 21 lightweight block ciphers, 19 lightweight stream ciphers, 9 lightweight hash functions and 5 variants of elliptic curve cryptography (ECC) has been discussed i.e. in total 54 LWC primitives are compared in their respective classes. The comparison of the ciphers has been carried out in terms of chip area, energy and power, hardware and software efficiency, throughput, latency and figure of merit (FoM). Based on the findings it can be observed that AES and ECC are the most suitable for used lightweight cryptographic primitives. Several open research problems in the field of lightweight cryptography have also been identified.

     

Isolation of High Oleate Recombinants in Peanut by Near Infra‐Red Spectroscopy and Confirmation With Allele Specific Polymerase Chain Reaction Marker

Near infrared (NIR) spectrophotometer offers rapid, noninvasive, nondestructive, and high‐throughput phenotyping of seed samples for use in agriculture and industry. In this study, a reflectance‐based NIR spectrophotometer was calibrated and used for the isolation of desirable higher‐oleic‐acid peanut recombinants from single‐seed‐derived segregating populations at F₇ and F₈ generations. A calibration model was developed through partial least‐square regression using wet chemistry data from 158 peanut genotypes. Desirable prediction for oil, palmitic acid, oleic acid, and linoleic acid in intact seed was obtained based on this calibration. It detected significant high correlations (r) and coefficient of determination (R²) between the actual gas chromatography values and NIR predicted values of fatty acid profile in another 123 peanut genotypes that were generated from crosses involving a high‐oleate mutant and Spanish bunch varieties with early maturity. From this recombinant single‐seed‐derived progenies, 15 higher‐oleate recombinants were isolated and later genotyped through an in‐house developed polymerase chain reaction‐based allele specific marker. The present study has generated high‐oleate peanut recombinants with early maturity in Spanish bunch background. The breeding materials generated here will be evaluated for yield attributing traits at different locations in future.     

Modeling and performance analysis of VI‐CRA: A congestion control algorithm for vehicular networks

This study proposes a Vehicle ID‐based CAM Rate Adaptation (VI‐CRA) algorithm for beacon messages in the vehicular network. Foremost, an improved vehicle ID–based analytical model is proposed at the MAC layer of vehicular network. The model weighs the random back‐off number chosen by vehicles participating in the back‐off process, with the vehicle ID incorporated in their respective CAMs. This eventually leads to the selection of a vehicle ID–based random back‐off number, minimizing the probability of collision due to same back‐off number selection. It is worth noting that the improved analytical model outperforms the existing works in terms of average packet delay since only one fourth of the contention window size is used throughout the simulation. To enhance the performance of the analytical model, the paper incorporates a congestion control algorithm, by adapting the rate of CAM broadcast over the control channel. The algorithm is designed considering a wide range of scenarios, ranging from nonsaturated to extremely saturated network (in terms of collision probability) and sparsely distributed to teemed network (in terms of vehicular density). For better analyses of simulation results, the algorithm is applied over different vehicle ID–based back‐off numbers. Simulation results for all the back‐off numbers show that vehicle ID–based CAM rate adaptation algorithm performs better than the traditional fixed CAM rate IEEE 802.11p, even at high vehicular density.     

Lamellar phase supported synthesis of colloidal gold nanoparticles, nanoclusters, and nanowires

Gold nanoparticles (Au NP) have been synthesized in aqueous phase under ambient conditions in the presence of a series of various cationic double chain as well as dimeric (gemini) surfactants. The spacer chain and twin tail length of these surfactants has been systematically varied to see the effect of hydrophobicity on their capping ability. It has been observed that the increase in the length of spacer chain (from 12-2-12 to 12-6-12) and twin tails (from 10-2-10 to 14-2-14) significantly increases the lamellar phase formation and which in return acts as a wonderful template to accommodate the NP in the form of nanoclusters and nanowires. The lamellar phase practically facilitates the nucleation of Au degrees and produces large NP (15 +/- 2 nm). All reactions have also been carried out in the presence of beta-cyclodextrin (CYC) which has strong ability to complex with surfactant tail. The presence of CYC induces a tendency to form nanowire and it is more prominent in the case of surfactants with longer spacer group.