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Iron Mineralization in Mycobacterial Ferritins: Impact of Protein Cage; Pores; and Phosphate
No full textIron is essential for the growth of almost all organisms including pathogens. Despite its importance, free Fe2+ can mediate cellular toxicity by generating reactive oxygen species. To maintain the balance between its essentiality and toxicity, appropriate cellular levels of iron are tightly regulated by a self-assembled spherical protein nanocage called ferritin, which synthesizes ferric oxyhydroxide mineral in its central cavity. These minerals in native ferritins are also associated with significant amount of phosphate (Fe/P ~ 1-2 in bacteria vs. >10 in animals). Like iron, phosphate also regulates the pathogenesis of Mycobacterium tuberculosis (Mtb), which expresses two types of ferritin: non-heme binding ferritin (BfrB) and heme binding bacterioferritin (BfrA). The mechanism of mineral core formation and the impact of phosphate towards its structure and reactivity in BfrB are not explored and thus investigated herein. The study confirms that phosphate alters the kinetics of iron oxidation and decreases the size/crystallinity of the mineral core. Iron mineralization commences with the rapid influx of Fe2+ via different pores, formed during self-assembly process. Investigation of these pores as Fe2+ uptake routes in ferritins remain a subject of intense research, in iron metabolism, toxicity and bacterial pathogenesis. As BfrA expression is upregulated during iron deprivation, its Fe2+ uptake/storage mechanism must be efficient and crucial for its survival and pathogenesis. Therefore, the electrostatics at/along its pores are altered to unravel the Fe2+ uptake pathways. While the 4-fold and B-pores are involved in rapid Fe2+ uptake/oxidation, alteration of 3-fold pores abolished the self-assembly process, thereby exhibiting impaired ferroxidase activity. The current dissertation helps to understand iron-phosphate solution chemistry occurring inside the ferritin nanocage and unravels the Fe2+ entry pathways along with the significance of self-assembly phenomena in Mtb ferritins; these findings may provide a future platform to engineer ferritin cage as nanosink/nanoreactor and regulate Mtb pathogenesis
Unravelling the Molecular Connection Between Pax9 and Autophagy To Regulate Oral Carcinogenesis
No full textPAired boX 9 (PAX9) gene belong to the PAX family, which encodes a family of metazoan transcription factors documented by a conserved DNA binding paired domain 128-amino- acids, critically essential for physiology and development. It has a significant role in maintaining squamous cell differentiation, and its deregulation is associated with tumor initiation and malignant transformation. Here, we have examined the mechanism of downregulation of PAX9 in oral carcinogenesis and its reactivation leading to lethal autophagy for potential cancer therapeutics in oral squamous cell carcinoma (OSCC). Our data showed that the expression of PAX9 was decreased in increasing grades of oral cancer and DMBA-induced hamster model of oral carcinogenesis. The downregulation of PAX9 is through promoter hypermethylation in exposure to alcohol and arecoline consumption was observed. Further, we showed that PAX9 inhibits proliferation and triggers apoptosis in OSCC. Interestingly, PAX9 activates lethal autophagy to degrade the EGFR signaling leading to cell death, establishing the tumor-suppressive potential of PAX9 in oral cancer. In another study, we have identified PAX9 for cellular differentiation by inhibiting EMT and stemness in cancer stem cells of OSCC. Notably, we revealed that protective autophagy in oral cancer stem cells maintains stemness through lysosomal degradation of PAX9 in oral cancer. In this setting, we have identified procaine, a local anesthetic, as DNA methyltransferase (DNMT) inhibitor to increase the expression of PAX9 in oral cancer. Interestingly, the reactivation of PAX9 by procaine found to inhibit cell growth and trigger apoptosis in OSCC in vitro and in vivo. Likely, the enhanced PAX9 expression after exposure to procaine controls stemness and differentiation through the autophagy-dependent pathway in OSCC cells. In SCC cells, procaine improved anticancer drug sensitivity through PAX9, and its deficiency significantly blunted the anticancer drug sensitivity mediated by procaine. Further, procaine promoted antitumor activity in FaDu xenografts in athymic nude mice, and immunohistochemistry data showed that PAX9 expression was significantly enhanced in the procaine group compared to the vehicle control. In conclusion, the reactivation of PAX9 by the discovery of small molecule anticancer drugs or increasing PAX9 copy number through gene therapy could offer a promising clinical outcome for the treatment of OSCC patients
Elliptic PDEs with Concave and Convex Nonlinearities
No full textElliptic partial differential equations (PDEs) have applications in various fields of science and engineering such as conservation laws, reactiondiffusion problems, thin obstacle problem, phase transitions, crystal dislocation, soft thin films, elastic properties of fractal media and flow through fractal nonsmooth domains. It is also important in various fields of mathematics such as harmonic analysis, differential geometry and calculus of variations. In this thesis, the existence, multiplicity and regularity of solutions to some elliptic PDEs with concave and convex nonlinearities are considered. Existence of solutions are shown for elliptic problems defined on regular and fractal domains subject to different boundary conditions such as Dirichlet, Neumann or nonlinear boundary conditions. Some of the major techniques used in the thesis are: variational methods, weak convergence methods, Mountain pass theorem and its variants, method of subsuper solutions, critical point theory and the theory of monotone operators
Role of Defects on the Deformation Behavior and Mechanisms in Large-scale Nickel Nanowire Subjected to Different Loading Methods: A Molecular Dynamics Simulation Study
No full textMetallic nanowires (NWs) are one of the essential building blocks in electromechanical devices, interconnects, and other nanodevices due to their unique mechanical, electrical, optical, and magnetic properties. The reliability of these devices depends mainly on the mechanical response of the constituents. NWs have a large surface-to-volume ratio compared to bulk materials, and hence the free surfaces are expected to play an essential role in the plastic deformation at smaller length scales. Also, the plastic deformation is observed to be heterogeneous at small length scales characterized by localized strain. Experimental studies are expensive as it requires expensive setups to maintain high precision equipment. Also, there could be uncertainty in measurements that may arise from specific issues, such as the gripping of NWs and rotation of the NWs. Therefore, a numerical simulation study is an alternative to conducting experiments. A computational tool like molecular dynamics (MD) numerically solves the N-body problem of classical mechanics and has been widely used to gain insights into the deformation behavior and mechanisms of perfect and defect nanoscale materials. In the present study, large-scale MD simulations are carried out to investigate the effect of defects (linear and voids), defects interactions (linear-void), and temperature effect (10 K-1200 K) on the mechanical properties and deformation mechanisms in single crystal nickel (Ni) NW (~925625 atoms). The NWs are tested for different loading methods, i.e., tensile, bending, and torsion at different temperatures and loading rates. The microstructural evolution (dislocations, stacking faults, twins, and twin boundaries) is analyzed and correlated with the deformation behavior. Finally, an experimental study is carried out to correlate the deformation relief patterns with those observed in MD simulation studies. The experimental studies are carried out on Ni-28W (28 wt.%W) single crystal alloy, subjecting it to compression test at room temperature. The major findings from the above mentioned studies are discussed in the following paragraph. The MD simulation tensile deformation results at a temperature of 10 K and strain rate of 108 s-1 show that the defects lower the yield stress and is more prominent in the presence of internal void (~30 % decrease). Several intrinsic and extrinsic parallel stacking faults (SFs) are generated after yielding by slip occurring on {111} planes. Crack propagation and crack-defect (void) interactions studies carried out at a temperature of 10 K and strain rate of 109 s-1 on [010], [1-10], and [111] axial crystallographic orientations of Ni NW show that crack does not propagate in the [111] orientation. The crack velocity is 313 m/s in [010] orientation. With the decrease in crack-void spacing from 20 Å to 5 Å, the average crack velocities (207 m/s-120 m/s) decrease in [010] orientation due to crack tip blunting arising from the crack-void coalescence. The tensile and creep behavior of nickel NWs containing single and multiple-voids (void diameter = 30 Å) carried out in the strain rate range of 108 s-11010 s-1 and temperatures of 10 K 1200 K show that the load-bearing capacity, the elastic modulus of the NWs decrease with an increase in the number of voids and temperature. The stress exponent (n) estimated from the steady-state regions of the creep curves is in the range of 0.8 – 2.77, which confirms the diffusive mechanism. The activation energies for creep are estimated and found to be 42.5 kJ/mol for perfect NW, 40 kJ/mol for single void, and 38 kJ/mol for multi-void nickel NW. So, it can be concluded that multi-void NW is less creep resistant. In the torsion studies, the critical torsional angles are lower in the NWs containing defects as compared to the perfect NW. Finally, the experimental and simulated compressive stress-strain curves of Ni-28W (28 wt.%W) alloy show a qualitative similarity
Investigation of Various Factors Shaping the Hearing Organ of Drosophila: The Johnston’s Organ
No full textThis thesis deals with the investigation of the consequences of several internal and environmental factors on the Drosophila hearing organ, the Johnston’s organ (JO). JO is evolving as a potential model system to examine the hearing associated defects in vertebrates. Drosophila can be utilized as a model to investigate the effects of many parameters that may affect the hearing organ of the vertebrates. In the case of vertebrates, several studies suggest parameters like aminoglycosides, alteration of circadian rhythm (CR), excess noise, low pressure, and aging can affect hearing. The present study examines the oral toxicity of different types of aminoglycosides (gentamicin, kanamycin, neomycin) at a discrete concentration (50, 100,150, 200, 250 μg/ml) from the first instar larva onwards. The third instar larvae display defective sound avoidance behavior and crawling behavior (regulated by sensory motor neuron). The adult flies hatched after aminoglycoside treatment have lesser amounts of acetylcholine esterase, higher amounts of reactive oxygen species (ROS), and altered hearing-related behaviors. All the genes involved in the hearing associated behaviors such as nompC, inactive, nanchung, pyrexia, and serotonin were downregulated after aminoglycoside treatment. The effect of environmental factors like low pressure, noise, and altered circadian rhythm was investigated on Drosophila development from the embryonic stage onwards. In the environmentally challenged third instar larval antenna imaginal disc, cell death was detected. Flies hatched from the environmentally challenged larvae have increased amounts of antioxidant enzymes, reactive oxygen species, and fewer amounts of mitochondria. Altered hearing-related behaviors like climbing, aggression, and courtship suggest the antenna is defective. The effect of age was investigated on the JO of Drosophila. Perhaps with age, the climbing behavior declined and the antennae have less amount of catalase and contains more amounts of carbonyl. This suggests that there would be more accumulation of H2O2 and redox imbalance in the antennae. Superoxide dismutase (SOD) plays a key role in the redox balance within the body. Thus, SOD mutants were checked for hearing-related behaviors in different developmental stages. Adult flies have impaired climbing behavior. The third instar larva shows malformed startle, sound avoidance, and crawling behavior. Hearing or mechanosensory-related behaviors such as startle and sound avoidance, and larva crawling behavior were found to be affected in the SOD mutants. All these assays point that SOD flies have hearing defects. With the age, advanced glycosylated end products (AGE) get accumulated within the body. To induce aging, we fed the 1st instar larvae with age compounds. In AGE treated antennae, more autofluorescence was detected. AGE-treated flies have impaired climbing behavior. AGEcompound treated flies has more amount of carbonyl content, SOD level, and less catalase activity. This study signifies that age-related hearing defect in the Drosophila is due to redox imbalance and accumulation of AGE compound with age. This thesis finds that factors like aminoglycosides, noise, pressure, circadian rhythm (CR), and age can alter the behaviors associated with antennae in Drosophila
Identification of potential Therapeutic Targets and Investigating Piwi-interacting RNA (piRNA)Mediated Target Regulations Implicated in Oncogenesis and Drug Resistance of Sarcoma
No full textSarcomas are rare, and aggressive cancers of mesenchymal origin, with a survival rate ＜15% if metastasized. The molecular heterogeneity of this cancer complicates its diagnosis, prognosis, and treatment. Further, acquired chemoresistance remains a major clinical challenge, accounting for its treatment failure and tumor relapse. Therefore, it is critical to decrypt key regulators and the underlying molecular mechanisms of sarcomagenesis and drug resistance. The current study sought to identify key regulators of tumorigenesis and chemoresistance that could be modulated by PIWI-interacting RNA (piRNA), a class of small non-coding RNAs dysregulated in two types of sarcomas, soft tissue sarcoma (STS) and osteosarcoma (OS). Initially, we used omics analysis of STS clinical data, and found Ribonucleotide reductase regulatory subunit M2 (RRM2) as a potential oncogene, whose higher expression was found to be linked with STS prognosis, lower survival, and recurrence. In vitro studies revealed that overexpression of RRM2 in HT1080 fibrosarcoma cells, a type of STS induces proliferation, migration, invasion, and colony formation, whereas silencing arrests the cell cycle at the G0/G1 phase and induces apoptosis. Interestingly, we discovered that piR-39980, which is downregulated in HT1080 cells, regulates RRM2 expression by directly targeting its 3' UTR and modulates sarcomagenesis by acting as a tumor suppressor. Furthermore, we found that piR-39980 was very less expressed, while its targets, RRM2 and Cytochrome P450 Family 1 Subfamily A Member 2 (CYP1A2) are highly upregulated in doxorubicin (DOX)-resistant HT1080 (HT1080/DOX) cells compared to parental HT1080 cells. Our findings from several molecular assays revealed that RRM2 confers DOXresistance by rescuing DOX-induced DNA damage by promoting DNA repair, whereas CYP1A2 induces DOX-resistance by decreasing intracellular DOX-accumulation via its metabolism. Interestingly, overexpression of piR-39980 in HT1080/DOX cells significantly increased the DOX sensitivity by promoting intracellular DOX accumulation, DNA damage, and apoptosis, indicating that piR-39980 could reduce DOX resistance by modulating RRM2 and CYP1A2 expression. On the contrary, piR-39980 is significantly upregulated in OS and acts as an oncogene by targeting Serpin Family B Member 1 (SERPINB1), resulting in Matrix metalloproteinase-2 (MMP2) activation. In summary, this study discovered that piR 39980, through modulating key targets, play crucial roles in sarcoma oncogenesis and chemoresistance, and thus could be a promising RNA-based therapeutic agent, which needs to be studied further
Nanocarbon Containing Alumina-carbon Refractories
No full textThe functional refractories used in steel casting operations are usually made up of alumina- carbon based compositions due to their comprehensive properties. Conventionally, these refractories contain 25-30 wt% carbon, with graphite as the main carbon source, particularly to impart and improve corrosion and thermal shock resistance. The presence of alumina provides excellent mechanical and thermomechanical properties along with other conventional refractory properties. Owing to its low thermal expansion and superior thermal conductivity, carbon addition provides excellent thermal shock resistance. Because of its non-wetting nature, it avoids the adhesion of steel/slag melts on the refractory thereby improving corrosion resistance. As carbon imparts these two extremely important properties in the refractory compositions, the amount of graphite usage is considerably high for these refractories compared to other carbon-containing ones. However, the presence of high carbon encompasses several problems viz. a) higher heat loss due to the increased thermal conductivity of the refractory which increases the specific energy consumption per unit of steel production b) enhances the chances of carbon pick-up by steel, which affects the quality and properties of steel negatively c) oxidation of carbon causing a porous refractory structure which can be easily penetrated and corroded by steel/slag melts d) releases a higher amount of COx gases into the atmosphere. Considering these factors carbon content in the Al2O3-C refractories is to be reduced. However, minimizing the carbon content reduces the non-wetting behavior and also decreases the thermal conductivity of the refractory which causes an increase in thermal stress within the system, which damages their comprehensive properties and results in poor service life. Hence, the development of low-carbon Al2O3-C refractories without conceding any beneficial properties is a challenge to refractory technologists. Such a challenge is intended in the present work with the use of nanocarbon as a carbon source to reduce/replace graphite. Literature shows different studies are available to develop low carbon-containing Al2O3-C refractories using various carbon sources, replacing graphite partially or entirely, and further evaluation of the properties developed. But hardly any study is available on making low carbon Al2O3-C refractories with systematic optimization of nanocarbon and graphite content in the composition. Also, the comparison of developed properties of experimental compositions against conventional composition is done in the current work which is rarely found. In the present work, the variation in physical, mechanical, and thermo-mechanical properties with variation in the amount of nanocarbon in the composition is studied. Phase analysis and microstructural developments are also evaluated along with the oxidation resistance at different temperatures. Thermal shock resistance and corrosion resistance are also examined for optimized and selected batches. Nanocarbon possesses greater reactivity due to its high surface area in comparison to graphite and helps in the formation of in-situ ceramic phases like carbides. Formation of aluminum carbide in nanocarbon-containing compositions enhances strength. It can easily disperse in the gaps between coarse, medium, and fine alumina particles thereby reduces porosity and contributing to strength development. Well dispersed nanocarbon results in comparable corrosion properties even at much lower amounts than graphite. These nanocarbon particles can absorb and relieve stresses caused during thermal cycling, thereby improving thermal shock resistance
Novel Periocular Recognition under Non-cooperative Scenarios
No full textComponents of face, such as iris and ocular region, possess discriminating patterns, making it suitable to be considered as a biometric trait to identify an individual. However, it becomes difficult to recognize a person with a low and degraded quality of images. Sometimes, it fails to authenticate when face is partially occluded (nose, mouth covered). In these situations, periocular region can be used as a biometric trait as opposed to iris which requires user co-operation as well as high resolution images. The periocular region can also be a useful biometric trait to authenticate an individual even if the low-resolution, defocused, off-angle, and only partial face or iris image is available. The thesis first provides an outline of existing ocular biometric datasets and summarizes a guideline on which datasets are useful or can be potentially used for study of periocular biometric. This is essential as there is no dedicated dataset for periocular study. Iris and face datasets are suitably used for periocular study. This thesis further investigates the performance of periocular based biometric system in the following two aspects: (a) Eliminating redundancy through a small and properly selected subset of features obtained using non-overlapping block division approach, and (b) Simulating real-time scenarios by modeling image quality covariates associated with blur, low-resolution and bit-depth on the performance of periocular recognition. The extraction of binned histogram features encoded by an interpolated local binary pattern in a blockwise manner is proposed in the first study. Matching is done using the Canberra distance measure. Experiment results show that the proposed method can reduce feature size without affecting its accuracy. In the second study, four types of image quality covariates such as out-of-focus blurred version (modelled through Gaussian function), camera shake blurred version (modelled through linear motion), low spatial resolution version (modelled through inter-area interpolation) and low bit-depth acquisition (modelled through bit plane slicing) are subjected to recognition and performance is evaluated. A deep learning architecture is used to train models and performance is evaluated using k-fold cross validation. Experimental results show that the performance of periocular recognition is primarily affected by out-of-focus blur. At the same time, it is more robust to camera shake blur. These approaches can be used to speed up the recognition process and evaluate other biometric systems’ performance when surveillance is to be done in unconstrained scenarios
Detection and Mitigation of DDoS Attack in Software Defined Networks (SDN) using Statistical Approach
Get PDFSoftware-Defined Network (SDN) is a network management technology that makes the network efficient in performance and dynamic in nature. SDN attempts to centralize network intelligence in one network component by decoupling the data plane from the control plane. The SDN uses the OpenFlow protocol for communication with network layer components. The centralized behaviour has some vulnerabilities in terms of security, scalability, and elasticity, which are the primary security concerns of SDN. One of these critical issues is the impact of Distributed Denial of Service (DDoS) attack on SDN. In a DDoS attack, multiple targets are attacked with Trojans and target single or multiple victims’ on the network. The attacker uses numerous spoofed IPs for targeting the network. The attacker can cause significant damage to the entire network by bringing down the controller. The DDoS attack affects the switch and controller since the attacker sends the spoofed source IPs from different locations.The effectiveness of DDoS attacks in SDN appears faster and more significantly than the traditional networks. Therefore, it is vital to ensure the early detection method to prevent the DDoS attack in the SDN network. A generic DDoS detection approach is proposed in [1]. The existing method consists of flow collection, essential feature extraction, and self-organized maps (SOM) classification. The features for DDoS are 6-tuples entries, i.e., an average of packets per flow, an average of bytes per flow, an average of duration per flow, percentage of pair-flows, growth of single flowers, and growth of different Ports. The paper assumes that each attack packet received from an additional source should be a new flow entry, but it is always implementation-dependent. Also, various topology scenarios such as near to victim or near to attacker are not discussed. Due to the wide popularity of UDP flood attacks, many solutions have been proposed in the literature to counter such attacks in SDN networks. The solutions found in the literature are implemented on the edge switch at the data plane [2, 3]. The existing literature fails to achieve the best results for detecting the flooding attack in SDN. Hence. We proposed the Shannon entropy method to measure traffic’s randomness and compare the threshold with window entropy to detect the attacker source in the SDN data plane. The Shannon entropy is used to detect the DDoS flooding attack by comparing the window’s entropy with a threshold. If the entropy is less than the threshold, there is a possibility of attack. The first step is to detect the victim host followed by an attacker’s source. Once the targeted host is identified, mitigation can be performed by the rate-limiting method. Low rate DDoS attacks are a severe threat to SDN-based data centres’ data layer. It is very much essential to identify the attack before it happens. When a packet in event increases, it becomes a bottleneck for the controller, and the resources start depleting. The usual Shannon entropy is a less efficient method to detect the false alarm in such a situation. Hence, we have employed Renyi entropy (RE) as the information distance metric to discriminate between low rate DDoS attacks and regular traffic. Also, we have compared RE with other ID metrics like KLD, Hellinger, and Sibson distance. We have observed that this metric can identify attack traffic from legitimate traffic to a greater extent with an improved false-negative rate. DDoS attacks can be against the SDN controller or the flow table storage capacity in an OpenFlow switch. The increasing internet traffic poses a challenge to distinguish between legitimate and malicious traffic. Thus, a convolutional neural network (CNN) model detects the DDoS attack traffic in SDN using the standard dataset CICDDoS2017. It can identify malicious traffic using a two-level detection method. The first one is on entropy implemented by the controller to determine which switch the suspicious traffic entered the network from. The next is fine-grained packet-based deep detection distinguished DDoS attack traffic based on a convolutional neural network. This work is compared with SVM, DNN, and DT. The results are analyzed using various evaluation metrics like accuracy F1-score, precision, and recall with acceptable training time. The CNN model increases the accuracy for detecting the DDoS traffic and enhancing the network system’s security. The proposed model shows through emulation results that CNN model is capable of early detection and mitigation of the high-rate attack traffic at the edge switches itself. In the future, we will use this same model to detect DDoS attacks in multi-controller environments
Dynamical Behaviours of Size Dependant and Functionally Graded Beams via Numerical Solutions
No full textNanostructures have made significant advancements in the fields of science, and engineering because of their unique mechanical, electrical, and electronic properties. Due to these characteristics, nanomaterials such as nanowires, nanoparticles, nanoribbons, and nanotubes, etc., play a critical role in a variety of nanoelectromechanical systems, such as nanoprobes, nanotube resonators, and nanoactuators. In nanotechnology, non-classical models and nonlocal elasticity theories are essential due to the presence of small-scale effects at the nano or micro scale. Unlike classical theories, the nonlocal theories contain internal material length scale parameters that can capture size effects at the nano or micro scale and can predict the behavior of the nano-sized structures accurately. Hence, accurate prediction of their dynamical behaviors becomes essential for engineering design and manufacturing. On the other hand, Functionally Graded Materials (FGM) have gained enormous attention as heat-shielding advanced structural materials in various engineering applications and industrial sectors, such as aerospace, nuclear power, automobiles, aviation, space vehicles, biomedical, and steel. These are often inhomogeneous materials composed of ceramic-metal composites, with the composition or volume of constituents varying continuously in one or more specified directions. As a result, their properties vary continuously along one interface to the next in a predetermined mathematical pattern. The ceramic component withstands high temperatures due to its low thermal conductivity, making it appropriate for usage in high-temperature environments including nuclear reactors, chemical plants, and the production of high-speed vessels. The ductile metal component prevents fracture caused by high temperature gradient-induced strains. As a result, the mechanical strength of FGM substantially increases while reducing the weight of structure. As said above, the functionally graded materials have a variety of positive aspects as per requirements which enables the material to be more adaptable. Combining FGM concept with nano scaled effect produce materials with much-enhanced functionality specially in the development of devices and equipments, viz. nano-electro-mechanical systems, including thin shape memory alloy, atomic force microscopy, etc. Modelling and analysis of FG-Nano beams are challenging as nanoscale devices are built exploiting the characteristics of nanotubes, nanobeams, nanomembranes, and nanosheets. Further, the uncertainties or randomness of the material properties of structural components are of serious concern. Structural analysis is usually done by taking deterministic or crisp parameters, but the truth is quite diverse. The primary causes of the spread of uncertainty or randomness are defects in atomic configurations, measurement errors, environmental conditions, etc., which affect the behaviour of dynamical structures. As a matter of fact, these structural anomalies indicate that the materials may not have the capability to demonstrate their normal mechanical behaviors. The influence of uncertainties may become much more profound in case of nano and micro structures due to the small-scale effects. In fact, several nanoscale experiments and molecular dynamics study also support the claim of possible inclusion of randomness in various parameters. In view of the above, the objective of this thesis has been to develop dynamical models as well as study dynamical characteristics of nanobeams, microbeams, functionally graded beams, functionally graded nanobeams, and functionally graded microbeams considering various boundary conditions, complicating effects as well as with material or geometrical uncertainties by employing different efficient numerical or analytical methods where appropriate. In order to capture small scale effects of nano or microstructures, various non-classical continuum theories such as Eringen's nonlocal elasticity theory, nonlocal strain gradient theory, conformable fractional nonlocal elasticity theory, nonlocal elasticity theory with bi Helmholtz operator, modified couple stress theory, and a new nonlocal elasticity theory have been discussed. Several beam theories, such as Euler-Bernoulli beam theory, Timoshenko beam theory, one variable first-order shear deformation theory, and refined higher-order shear deformation theory, are considered. Further, various complicating effects, viz. Winkler-Pasternak elastic foundation, variable elastic foundation, Kerr elastic foundation, longitudinal magnetic field, electromagnetic field, hygroscopic environment, linear and nonlinear thermal environment, surface energy, surface residual stresses, porosity, etc., are taken into this investigation. Fuzzy concepts such as triangular fuzzy number, symmetric Gaussian fuzzy number, single and double parametric forms, etc., have also been attributed to deal with material uncertainties and their propagations. As such, differential quadrature method, differential transform method, Rayleigh-Ritz Method, Hermite-Ritz Method, shifted Chebyshev polynomials-based Rayleigh-Ritz methods, Navier's method, Galerkin weighted residual method, Monte Carlo simulation technique, and wavelet-based methods such as Haar wavelet and higher-order Haar wavelet methods have also been applied to solve the problems. Additionally, comprehensive studies have been conducted on all the scaling parameters to determine their effect on frequencies and buckling loads