Women Safety Night Patrolling Robot Using IOT

India's greatest threat is the safety of its women. Women do not feel safe in a variety of situations. This needs to be addressed as quickly as feasible. Technology evolves and develops on a daily basis, affecting how people live. As a result, the focus of this article is on modernising the technological framework in order to strengthen women's safety mechanisms. We introduce a new security method in this study to protect women during unusual behaviours. A new security technique based on a patrolling robot using the Raspberry Pi has been proposed. In this case, a night vision camera can be employed to secure any location. Various machine learning methods are applied to improve the classifier's accuracy. The findings suggest that the suggested method outperforms existing methods

Identification of Sickle Cell Anemia Using Deep Neural Networks

A molecule called hemoglobin is found in red blood cells that holds oxygen all over the body. Hemoglobin is elastic, round, and stable in a healthy human. This makes it possible to float across red blood cells. But the composition of hemoglobin is unhealthy if you have sickle cell disease. It refers to compact and bent red blood cells. The odd cells obstruct the flow of blood. It is dangerous and can result in severe discomfort, organ damage, heart strokes, and other symptoms. The human life expectancy can be shortened as well. The early identification of sickle calls will help people recognize signs that can assist antibiotics, supplements, blood transfusion, pain-relieving medications, and treatments etc. The manual assessment, diagnosis, and cell count are time consuming process and may result in misclassification and count since millions of red blood cells are in one spell. When utilizing data mining techniques such as the multilayer perceptron classifier algorithm, sickle cells can be effectively detected with high precision in the human body. The proposed approach tackles the limitations of manual research by implementing a powerful and efficient MLP (Multi-Layer Perceptron) classification algorithm that distinguishes Sickle Cell Anemia (SCA) into three classes: Normal (N), Sickle Cells(S) and Thalassemia (T) in red blood cells. This paper also presents the precision degree of the MLP classifier algorithm with other popular mining and machine learning algorithms on the dataset obtained from the Thalassemia and Sickle Cell Society (TSCS) located in Rajendra Nagar, Hyderabad, Telangana, India. Doi: 10.28991/esj-2021-01270 Full Text: PD

Lidar Observations of aerosol layers just below the tropopause level during IFP-INDOEX

A lidar system has been used at Gadanki (13.5º, 79.2ºE) to study the characteristics of aerosol layer (cloud) occurring just below the tropical tropopause. The preliminary results of the lidar observations indicate that the cloud occurs ~ 2 km below the tropopause. The top and bottom edges of the cloud have propensity for ice crystal presence with liquid droplets/ vapours in-between. The clouds show temporal fluctuations (in their backscattering ratio) with temporal scales of the order of 30–90 min

Multitargeted Imidazoles: Potential Therapeutic Leads for Alzheimer's and Other Neurodegenerative Diseases

Alzheimer’s disease (AD) is a complex, multifactorial disease in which different neuropathological mechanisms are likely involved, including those associated with pathological tau and Aβ species as well as neuroinflammation. In this context, the development of single multitargeted therapeutics directed against two or more disease mechanisms could be advantageous. Starting from a series of 1,5-diarylimidazoles with microtubule (MT)-stabilizing activity and structural similarities with known NSAIDs, we conducted structure−activity relationship studies that led to the identification of multitargeted prototypes with activities as MT-stabilizing agents and/or inhibitors of the cyclooxygenase (COX) and 5-lipoxygenase (5-LOX) pathways. Several examples are brain-penetrant and exhibit balanced multitargeted in vitro activity in the low μM range. As brain-penetrant MT-stabilizing agents have proven effective against tau-mediated neurodegeneration in animal models, and because COX- and 5-LOX-derived eicosanoids are thought to contribute to Aβ plaque deposition, these 1,5-diarylimidazoles provide tools to explore novel multitargeted strategies for AD and other neurodegenerative diseases

Analysis of strain and stacking faults in single nanowires using Bragg coherent diffraction imaging

Coherent diffraction imaging (CDI) on Bragg reflections is a promising technique for the study of three-dimensional (3D) composition and strain fields in nanostructures, which can be recovered directly from the coherent diffraction data recorded on single objects. In this article we report results obtained for single homogeneous and heterogeneous nanowires with a diameter smaller than 100 nm, for which we used CDI to retrieve information about deformation and faults existing in these wires. The article also discusses the influence of stacking faults, which can create artefacts during the reconstruction of the nanowire shape and deformation.Comment: 18 pages, 6 figures Submitted to New Journal of Physic

Synthesis, Characterization and Magnetic Susceptibility of the Heavy Fermion Transition Metal Oxide LiV_{2}O_{4}

The preparative method, characterization and magnetic susceptibility \chi measurements versus temperature T of the heavy fermion transition metal oxide LiV_{2}O_{4} are reported in detail. The intrinsic \chi(T) shows a nearly T-independent behavior below ~ 30 K with a shallow broad maximum at about 16 K, whereas Curie-Weiss-like behavior is observed above 50-100 K. Field-cooled and zero-field-cooled magnetization M measurements in applied magnetic fields H = 10 to 100 G from 1.8 to 50 K showed no evidence for spin-glass ordering. Crystalline electric field theory for an assumed cubic V point group symmetry is found insufficient to describe the observed temperature variation of the effective magnetic moment. The Kondo and Coqblin-Schrieffer models do not describe the magnitude and T dependence of \chi with realistic parameters. In the high T range, fits of \chi(T) by the predictions of high temperature series expansion calculations provide estimates of the V-V antiferromagnetic exchange coupling constant J/k_{B} ~ 20 K, g-factor g ~ 2 and the T-independent susceptibility. Other possible models to describe the \chi(T) are discussed. The paramagnetic impurities in the samples were characterized using isothermal M(H) measurements with 0 < H <= 5.5 Tesla at 2 to 6 K. These impurities are inferred to have spin S_{imp} ~ 3/2 to 4, g_{imp} ~ 2 and molar concentrations of 0.01 to 0.8 %, depending on the sample.Comment: 19 typeset RevTeX pages, 16 eps figures included, uses epsf; to be published in Phys. Rev.

Kondo effect in Ce(x)La(1-x)Cu(2.05)Si(2) intermetallics

The magnetic susceptibility and susceptibility anisotropy of the quasi-binary alloy system Ce(x)La(1-x)Cu(2.05)Si(2) have been studied for low concentration of Ce ions. The single-ion desc ription is found to be valid for x < 0.1. The experimental results are discussed in terms of t he degenerate Coqblin-Schrieffer model with a crystalline electric field splitting Delta = 330 K. The properties of the model, obtained by combining the lowest-order scaling and the pertur bation theory, provide a satisfactory description of the experimental data down to 30 K. The e xperimental results between 20 K and 2 K are explained by the exact solution of the Kondo mode l for an effective doublet.Comment: 11 pages, 13 Postscript figures, 1 tabl

Symmetric Anderson impurity model with a narrow band

The single channel Anderson impurity model is a standard model for the description of magnetic impurities in metallic systems. Usually, the bandwidth represents the largest energy scale of the problem. In this paper, we analyze the limit of a narrow band, which is relevant for the Mott-Hubbard transition in infinite dimensions. For the symmetric model we discuss two different effects: i) The impurity contribution to the density of states at the Fermi surface always turns out to be negative in such systems. This leads to a new crossover in the thermodynamic quantities that we investigate using the numerical renormalization group. ii) Using the Lanczos method, we calculate the impurity spectral function and demonstrate the breakdown of the skeleton expansion on an intermediate energy scale. Luttinger's theorem, as an example of the local Fermi liquid property of the model, is shown to still be valid.Comment: 4 pages RevTeX, 2 eps figures included, final versio

Collision-Induced Decay of Metastable Baby Skyrmions

Many extensions of the standard model predict heavy metastable particles which may be modeled as solitons (skyrmions of the Higgs field), relating their particle number to a winding number. Previous work has shown that the electroweak interactions admit processes in which these solitons decay, violating standard model baryon number. We motivate the hypothesis that baryon-number-violating decay is a generic outcome of collisions between these heavy particles. We do so by exploring a 2+1 dimensional theory which also possesses metastable skyrmions. We use relaxation techniques to determine the size, shape and energy of static solitons in their ground state. These solitons could decay by quantum mechanical tunneling. Classically, they are metastable: only a finite excitation energy is required to induce their decay. We attempt to induce soliton decay in a classical simulation by colliding pairs of solitons. We analyze the collision of solitons with varying inherent stabilities and varying incident velocities and orientations. Our results suggest that winding-number violating decay is a generic outcome of collisions. All that is required is sufficient (not necessarily very large) incident velocity; no fine-tuning of initial conditions is required.Comment: 24 pages, 7 figures, latex. Very small changes onl

Smart Contracts for Global Sourcing Arrangements

While global sourcing arrangements are highly complex and usually represent large value to the partners, little is known of the use of e-contracts or smart contracts and contract management systems to enhance the contract management process. In this paper we assess the potential of emerging technologies for global sourcing. We review current sourcing contract issues and evaluate three technologies that have been applied to enhance contracting processes. These are (1) semantic standardisation, (2) cognitive technologies and (3) smart contracts and blockchain. We discuss that each of these seem to have their merit for contract management and potentially can contribute to contract management in more complex and dynamic sourcing arrangements. The combination and configuration in which these three technologies will provide value to sourcing should be on the agenda for future research in sourcing contract management.</p