Distance based Modelling and Optimization of Wireless Sensor Network Energy Consumption with Adaptive Clustering using Genetic Algorithm

Wireless sensor network (WSN), as one of the most important technologies due to its wide variety of applications, consists of various densely deployed sensor nodes inside or very near to application area. WSNs work with several limitations related to resources like battery power, bandwidth, memory and etc. and hence node goes out of energy where it's impossible to recharge or replace the battery of nodes. It has been proved that, long communication distance between sensor nodes and base station (BS) can drain the energy. This paper proposes an approach to optimize the WSN energy consumption of nodes via optimizing the number of clusters that minimizes the transmission distance, for maximizing network lifetime. A genetic algorithm is proposed for sensor nodes clustering to find the optimal number of cluster heads that reduces the energy consumption. The proposed solution considers the communication distance, as a main factor, which is formulated as an objective function to be optimized for the mathematical model constrained by the number of cluster heads. The results were conducted using the proposed GA for different instances with different settings such as the population size, number of cluster-heads, and number of generations. The experimental results show that the algorithm achieved good results and it converges toward the optimal solution through the generations for the different instances. Moreover, the proposed approach reduces the energy consumption more efficient when compared with hierarchical clustering algorithm on minimizing the communicating distance. It is recommended to scale the algorithm to consider a trade-off between the total intra-cluster communication distance and total distance of cluster-heads to BS as a future work

Ventilatory mechanics in thoracic surgery

This thesis proved that chest wall motion analysis technology could be used in thoracic surgery to answer a number of clinical and physiological questions. We used it either as a diagnostic tool or for the evaluation of an intervention outcome. We divided its use as a diagnostic tool into two categories; 1- diagnosis before surgery and 2- diagnosis after surgery. In the evaluation of an intervention outcome, we divided its use after a number of interventions: 1. Cosmetic Surgery: Chapter 5: The Effect of Pectus Carinatum (Pigeon Chest) Repair on Chest Wall Mechanics 2. Prognostic Surgery: a) Chapter 4: The Effect of Chest Wall Reconstruction on Chest Wall Mechanics b) Chapter 10: Late Changes in Chest Wall Mechanics Post Lung Resection: The Effect of Lung Cancer Resection In COPD patients 3. Palliative Surgery: a) Chapter 6: The Effect of Lung Volume Reduction Surgery on Chest Wall Mechanics b) Chapter 3: The Effect of Diaphragmatic Plication (Fixation) on Chest Wall Mechanics 4. Post-operative Intervention: Chapter 8: The Effect of Thoracic Nerve Blocks on Chest Wall Mechanic

Structural Characterization and Physical Properties of Syzygium cumini Flowering Plant

ABSTRACT: In this study, the flowering plant of syzygium cumini was used. X-ray fluorescence (XRF) and X-ray diffraction (XRD) were used to investigate the structure of the leaves and barks of syzygium cumini. The XRD results were indicated that the structures of both leaves and bark were amorphous. The XRF results indicated that both leaves and barks contained Potassium (K), Calcium (Ca), (Ti), and Magnesium (Mn), Iron (Fe), Copper (Cu), Zinc (Zn), Zernike (As), Lead (Pb), Barium (Br), Strontium (Sr). The optical properties of syzygium cumini were carried out using Fourier Transformation infrared spectroscopy (FTIR) and Ultra violet spectroscopy (UV). The FTIR spectra showed a broad and strong absorption band in the range (685-1638) cm -1 , and these absorptions were assigned to the different stretching vibrations. The absorption for bark and leave was found to be 2.45 and 2.52 a u, while the wave length was found to be 277.4 and 277.5 nm, respectively. The energy band gap is calculated and found to be 5.017 and 4.67 eV, for bark and leave, respectively

Study on prevalence of internal parasites in semi- intensive dairy production system of Sudan

A cross sectional study was conducted in the dairy cattle of Al-Rodwan dairy project in Omdurman town during the three different seasons of the year. The results of the faecal examinations (n-290) showed that the prevalence of the internal parasites was 16, 8.42, and 7.36% for dry cool, dry hot, and wet hot season, respectively. The prevalence of coccidiosis was found to be 13, 4.21, and 2.10% for dry cool, dry hot, and wet hot season, respectively, while the prevalence of Fasciolosis was 1, 4.21, and 4.21% for dry cool, dry hot, and wet hot season, respectively. Statistically, no association between season and the prevalence of internal parasites (P> 0.05). A positive association (P< 0.01) between the milk yield and the occurrence of internal parasites was observed (infection with internal parasite reduce milk yield of the animal). Similarly, an association was recorded for the breed and age of the animal with infection of internal parasites (P< 0.05). Application of odds ratio (OR) indicated that breed was considered to be a protective factor (OR = 0.294), while age of the animal was considered to be a risk factor (OR = 3.638) for presence of internal parasites

Identification of novel differentially expressed genes in type 1 diabetes mellitus complications using transcriptomic profiling of UAE patients: a multicenter study

Type 1 diabetes mellitus (T1DM) is a chronic metabolic disorder that mainly affects children and young adults. It is associated with debilitating and long-life complications. Therefore, understanding the factors that lead to the onset and development of these complications is crucial. To our knowledge this is the first study that attempts to identify the common differentially expressed genes (DEGs) in T1DM complications using whole transcriptomic profiling in United Arab Emirates (UAE) patients. The present multicenter study was conducted in different hospitals in UAE including University Hospital Sharjah, Dubai Hospital and Rashid Hospital. A total of fifty-eight Emirati participants aged above 18 years and with a BMI < 25 kg/m2 were recruited and forty-five of these participants had a confirmed diagnosis of T1DM. Five groups of complications associated with the latter were identified including hyperlipidemia, neuropathy, ketoacidosis, hypothyroidism and polycystic ovary syndrome (PCOS). A comprehensive whole transcriptomic analysis using NGS was conducted. The outcomes of the study revealed the common DEGs between T1DM without complications and T1DM with different complications. The results revealed seven common candidate DEGs, SPINK9, TRDN, PVRL4, MYO3A, PDLIM1, KIAA1614 and GRP were upregulated in T1DM complications with significant increase in expression of SPINK9 (Fold change: 5.28, 3.79, 5.20, 3.79, 5.20) and MYO3A (Fold change: 4.14, 6.11, 2.60, 4.33, 4.49) in hyperlipidemia, neuropathy, ketoacidosis, hypothyroidism and PCOS, respectively. In addition, functional pathways of ion transport, mineral absorption and cytosolic calcium concentration were involved in regulation of candidate upregulated genes related to neuropathy, ketoacidosis and PCOS, respectively. The findings of this study represent a novel reference warranting further studies to shed light on the causative genetic factors that are involved in the onset and development of T1DM complications