Route discovery schemes in Mobile Ad hoc Networks with variable-range transmission power

Broadcasting in MANETs is important for route discovery but consumes significant amounts of power that is difficult to renew for devices that rely heavily on batteries. Most existing routing protocols make use of a broadcast scheme known as simple flooding. In such an on-demand routing protocol (e.g. AODV) the source node originates a Route Request (RREQ) packet that is blindly rebroadcast via neighbouring nodes to all nodes in the network. Simple flooding leads to serious redundancy, together with contention, and collisions, which is often called the broadcast storm problem. This thesis proposes two improvement strategies: topology control (adjusting transmission power) and reduced retransmissions (reducing redundant rebroadcasts) to reduce energy consumption. For energy efficient route discovery the main idea is to reduce the energy consumed per broadcast during route discovery. An Energy Efficient Adaptive Forwarding Algorithm (called EEAFA) is proposed to reduce the impact of RREQ packet flooding in on-demand routing protocols. The algorithm operates in two phases: 1) Topology construction phase, which establishes a more scalable and energy efficient network structure where nodes can adjust their transmission power range dynamically, based on their local density. 2) A Forwarding Node Determination phase, that utilises network information provided by the constructed topology, where nodes independently decide to forward a RREQ packet or not without relying on GPS or any distance calculations. A further Enhanced EEAFA (called E-EEAFA) algorithm is also proposed, which combines two techniques: graph colouring and sectoring techniques. Graph colouring increases awareness at network nodes to improve the determination of a forwarding node, while the sectoring technique divides neighbours into different forwarding sectors. This helps to reduce overlap between forwarding nodes and select suitable nodes in each sector to forward RREQ packets. These techniques are employed in a distributed manner and collaborate to reduce the number of forwarding nodes, which thus reduces the volume of RREQ packets populating the network. These algorithms have been validated as effective by NS2 simulation studies that are detailed in the thesis

New insight into strategies used to develop long-acting G-CSF biologics for neutropenia therapy

Over the last 20 years, granulocyte colony-stimulating factors (G-CSFs) have become the major therapeutic option for the treatment of patients with neutropenia. Most of the current G-CSFs require daily injections, which are inconvenient and expensive for patients. Increased understanding of G-CSFs’ structure, expression, and mechanism of clearance has been very instrumental in the development of new generations of long-acting G-CSFs with improved efficacy. Several approaches to reducing G-CSF clearance via conjugation techniques have been investigated. PEGylation, glycosylation, polysialylation, or conjugation with immunoglobulins or albumins have successfully increased G-CSFs’ half-lives. Pegfilgrastim (Neulasta) has been successfully approved and marketed for the treatment of patients with neutropenia. The rapidly expanding market for G-CSFs has increased demand for G-CSF biosimilars. Therefore, the importance of this review is to highlight the principle, elimination’s route, half-life, clearance, safety, benefits, and limitations of different strategies and techniques used to increase the half-life of biotherapeutic G-CSFs. Understanding these strategies will allow for a new treatment with more competitive manufacturing and lower unit costs compared with that of Neulasta

Genomics-assisted breeding in four major pulse crops of developing countries: present status and prospects

The global population is continuously increasing and is expected to reach nine billion by 2050. This huge population pressure will lead to severe shortage of food, natural resources and arable land. Such an alarming situation is most likely to arise in developing countries due to increase in the proportion of people suffering from protein and micronutrient malnutrition. Pulses being a primary and affordable source of proteins and minerals play a key role in alleviating the protein calorie malnutrition, micronutrient deficiencies and other undernourishment-related issues. Additionally, pulses are a vital source of livelihood generation for millions of resource-poor farmers practising agriculture in the semi-arid and sub-tropical regions. Limited success achieved through conventional breeding so far in most of the pulse crops will not be enough to feed the ever increasing population. In this context, genomics-assisted breeding (GAB) holds promise in enhancing the genetic gains. Though pulses have long been considered as orphan crops, recent advances in the area of pulse genomics are noteworthy, e.g. discovery of genome-wide genetic markers, high-throughput genotyping and sequencing platforms, high-density genetic linkage/QTL maps and, more importantly, the availability of whole-genome sequence. With genome sequence in hand, there is a great scope to apply genome-wide methods for trait mapping using association studies and to choose desirable genotypes via genomic selection. It is anticipated that GAB will speed up the progress of genetic improvement of pulses, leading to the rapid development of cultivars with higher yield, enhanced stress tolerance and wider adaptability

Improving the Power Efficiency of a High-Density Cluster in MANETs

A mobile ad hoc network (MANET) is a set of different mobile nodes that organises a temporary network in the absence of any fixed infrastructure. Due to the node power limit, prolonging the network lifetime is challenging. Clustering schemes offer a practical way of providing power efficiency when dealing with high density networks. In this paper we propose a developing routing algorithm to transmit packets in an energy-efficient manner. The proposed algorithm can significantly reduce both power consumption and interference. This can be achieved by optimising one of the cluster members as a cluster head child (selected by the cluster head). Cluster head child selection is based on the weight value of the cluster nodes. This cluster head child communicates with the cluster head and acts as a temporary base station within its cluster members (neighbours). It also inherits routing and cluster information from the cluster head, thus allowing the network to be more efficient, and reliable. Additionally, in the high dense region of the cluster the algorithm dynamically adjusts the transmission power of the cluster members within the range of the cluster head child

Improving the Power Efficiency of a High-Density Cluster in MANETs

A mobile ad hoc network (MANET) is a set of different mobile nodes that organises a temporary network in the absence of any fixed infrastructure. Due to the node power limit, prolonging the network lifetime is challenging. Clustering schemes offer a practical way of providing power efficiency when dealing with high density networks. In this paper we propose a developing routing algorithm to transmit packets in an energy-efficient manner. The proposed algorithm can significantly reduce both power consumption and interference. This can be achieved by optimising one of the cluster members as a cluster head child (selected by the cluster head). Cluster head child selection is based on the weight value of the cluster nodes. This cluster head child communicates with the cluster head and acts as a temporary base station within its cluster members (neighbours). It also inherits routing and cluster information from the cluster head, thus allowing the network to be more efficient, and reliable. Additionally, in the high dense region of the cluster the algorithm dynamically adjusts the transmission power of the cluster members within the range of the cluster head child

Social anxiety in E-Learning: Scale validation and socio-demographic correlation study

During the ongoing coronavirus disease 2019 pandemic, over 1.5 billion students worldwide have been deprived of access to traditional learning. This situation has necessitated the use of social distancing-based educational methods; consequently, a tremendous shift towards e-learning has been observed. This study assesses medical students' social anxiety levels in e-learning environments. The study was conducted in two phases. In the first phase, the original Turkish Social Anxiety Scale for E-Learning Environments (SASE) was adapted in English and tested for validity and reliability. This instrument has two subscales: social anxiety in learner-learner interaction and in learner-instructor interaction. In the second stage, we explored the associations of gender, age, and perceived academic performance with medical students' social anxiety levels in e-learning environments. A total of 325 responses were analysed. Consistent with the original version, the adapted scale is a reliable and valid measure of social anxiety in e-learning. Social anxiety in e-learning was related to gender (p = 0.008) and age (p = 0.013). Social anxiety levels were higher in students with lower perceived performance during e-learning compared to students with enhanced performance, but the difference was not significant. The SASE is a useful instrument for evaluating social anxiety in e-learning environments across English educational frameworks. Considering the shift in social interaction environments, efforts are required to reduce medical students' social anxiety levels and enhance learning