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In this work, we propose a cost-effective procedure to obtain magnetic single cotton yarns by employing commercially available magnetic powders and adhesives. Two different indirect magnetization methods are used on the yarns coated with several mixtures containing barium hexaferrite (BaFe12O19) as hard magnetic powder. The BH mass percentage is varied between 10% and 50%. Specific textile coating binders such as polyurethane and polyvinyl acetate are used as adhesives. A constant amount of 5% glycerol is employed as plasticizer agent. An in-house developed laboratory equipment is used to produce the magnetic cotton yarns. The equipment allows primary orientation of the magnetic particles along external field lines and subsequent magnetization until saturation. Our studies show that the diameter of the coated yarns is directly dependent on the amount of magnetic powder in the coating solution. Thus, the magnetic yarn diameter increases by 30% when compared to the 356µm diameter of the reference (uncoated) yarn for a barium hexaferrite mass percentage of 50%. Also, our studies reveal that increasing the magnetic properties (residual magnetism and coercive field intensity) of the composite yarns is possible only by increasing the mass percentage of the magnetic powder content. The highest values of the magnetic properties have been measured when neodymium permanent magnets (NdFeB) were used for the magnetization instead of a toroidal coil. The residual magnetization and saturation increase with the amount of barium hexaferrite embedded in the textile yarn. However, the increase in mass percentage is limited by the degradation of the yarn properties which allow them to be used for textile applications. SEM images of the coated yarns reveal a relatively uniform deposition of magnetic layer on the reference cotton yarn. publishedVersion

Control theory has seen recently impactful applications in network science, especially in connections with applications in network medicine. A key topic of research is that of finding minimal external interventions that offer control over the dynamics of a given network, a problem known as network controllability. We propose in this article a new solution for this problem based on genetic algorithms. We tailor our solution for applications in computational drug repurposing, seeking to maximize its use of FDA-approved drug targets in a given disease-specific protein-protein interaction network. We show how our algorithm identifies a number of potentially efficient drugs for breast, ovarian, and pancreatic cancer. We demonstrate our algorithm on several benchmark networks from cancer medicine, social networks, electronic circuits, and several random networks with their edges distributed according to the Erdös-Rényi, the scale-free, and the small world properties. Overall, we show that our new algorithm is more efficient in identifying relevant drug targets in a disease network, advancing the computational solutions needed for new therapeutic and drug repurposing approaches.

Recently, a few computational methodologies and algorithms have been developed to simulate the microstructure evolution in powder bed fusion (PBF) additive manufacturing (AM) processes. However, none of these have attempted to simulate the grain structure evolution in multitrack, multilayer AM components in a fully 3D transient mode and for the entire AM geometry. In this work, a multiscale model, which consists of coupling a transient, discrete-source 3D AM process model with a 3D stochastic solidification structure model, was applied to quickly, efficiently, and accurately predict the grain structure evolution of IN625 alloys during Laser Powder Bed Fusion (LPBF). The capabilities of this model include studying the effects of process parameters and part geometry on solidification conditions and their impact on the grain structure formation within multicomponent alloy parts processed via AM. Validation was accomplished based on single-layer LPBF IN625 benchmark experiments, previously performed and analyzed at the National Institute of Standards and Technology (NIST), USA. This modeling approach can also be used to quantitatively predict the solidification structure of Ti-6Al-4V alloys in electron beam AM processes.

A 3D transient CFD–reaction coupled model is developed to predict the slag–metal reaction and desulphurization kinetics in ladle furnace with both molten slag and air layers considered. The coupled...

Characterization of unsteady loads is critical for the development of control systems for next-generation air vehicles. Both Direct Numerical Simulation (DNS) and Large Eddy Simulation (LES) methods are prohibitively expensive, and existing Reynolds-Averaged Navier-Stokes (RANS) approaches have been shown to be inadequate in predicting both mean and unsteady loads. In recent years, scale-resolving methods, such as Partially Averaged Navier-Stokes (PANS) and Detached Eddy Simulation (DES), have been gaining acceptance and filling the gap between RANS and LES. In this study, we focus on a new variant of the PANS method, namely blended PANS or BPANS, which was shown to perform well in the incompressible regime for both wall-bounded and free shear flows. In this paper, we extend BPANS to compressible supersonic flows by adding a compressibility correction, leading to a new model called BPANS CC. The new model is tested using a well-known supersonic mixing layer case, and the results show good agreement with experimental data. The model is then used on a complex supersonic retropropulsion case and the results are in good agreement with experimental data.

In this work, synthesis and optical properties of a new composite based on poly(o-phenylenediamine) (POPD) fiber like structures, poly(vinylidene fluoride) (PVDF) spheres and double-walled carbon nanotubes (DWNTs) are reported. As increasing the PVDF weight in the mixture of the chemical polymerization reaction of o-phenylenediamine, the presence of the PVDF spheres onto the POPD fibers surface is highlighted by scanning electron microscopy (SEM). The down-shift of the Raman line from 1421 cm−1 to 1415 cm−1 proves the covalent functionalization of DWNTs with the POPD-PVDF blends. The changes in the absorbance of the IR bands peaked around 840, 881, 1240 and 1402 cm−1 indicate hindrance steric effects induced of DWNTs to the POPD fiber like structures and the PVDF spheres, as a consequence of the functionalization process of carbon nanotubes with macromolecular compounds. The presence of the PVDF spheres onto the POPD fiber like structures surface induces a POPD photoluminescence (PL) quenching process. An additional PL quenching process of the POPD-PVDF blends is reported to be induced in the presence of DWNTs. The studies of anisotropic PL highlight a change of the angle of the binding of the PVDF spheres onto the POPD fiber like structures surface from 50.2° to 38° when the carbon nanotubes concentration increases in the POPD-PVDF/DWNTs composites mass up to 2 wt.%.

Background:Diabetic ketoacidosis is an acute major life-threatening complication of diabetes, characterized by hyperglycemia, ketoacidosis and ketonuria, which can be life threatening if it is not promptly recognized and treated. This occurs mainly in patients with type 1 diabetes, but stressors like trauma and infection can increase the risk of ketoacidosis in other forms of diabetes such as type 2 diabetes. Type 2 diabetes mellitus is a complex metabolic disorder of heterogeneous etiology with behavioral, social, and environmental risk factors that unmask the effects of genetic susceptibility. Recent studies indicate an increasing prevalence of type 2 diabetes mellitus in children and adolescents around the world in all ethnicities. C-peptide is a useful and widely used method of assessing pancreatic beta cell function given his structure: part of proinsulin which is cleaved prior to co-secretion with insulin from pancreatic beta cells. This is used as a tool in the differentiation of type 1 diabetes from type 2 but also other types of diabetes. We present a 12-year-old previously healthy male who was hospitalized in our clinic for polydipsia, polyuria, weight loss and emesis, with symptom onset 10 days prior to admission. On the admission day, he presented to the emergency room for progressively increasing somnolence, apathy, decreased muscle tone and urinary incontinence. Physical examination was significant for grade I obesity [height 168 cm and weight 90 kg, yielding a body index mass (BMI) of 31.78 kg/m2, percentile >97%], lethargy, slurred speech, high blood pressure (145/90 mmHg), tachycardia (145 beats per minute) and acanthosis nigricans. Considering his physical examination, laboratory tests and clinical evolution, he was diagnosed with type 2 diabetes mellitus complicated with hyperosmolar hyperglycemic state and diabetic ketoacidosis. Diabetic ketoacidosis should be considered in the differential diagnosis of metabolic decompensation in all types of diabetes. Although type 2 diabetes mellitus seems to be still rare in childhood and adolescence, prevention and treatment of type 2 diabetes mellitus should become public awareness and public health intervention programs. The particularity of this case was the unusual onset of diabetes mellitus type 2 in a male child with metabolic syndrome.

This paper addresses the experimental and numerical dynamic analysis of curved bars used as percussion musical instruments. These structures are known as triangles, being made of various metal materials. The study was based on the experimental analysis of the dynamic response over time and the frequency of three types of triangles, different in material and size. Subsequently, finite element analysis of the same structures modeled with the SimCenter 12 program was performed. The results were compared, highlighting the contribution of material type and geometry in obtaining vibration modes, frequency spectrum, and structural damping coefficient. Between the experimental and the numerical analysis, the obtained errors were below 2.2% in terms of their natural frequencies. The study also highlights the complementarity of the two methods in understanding the vibration modes of triangles.

We live in an environment where it is debated whether there is a causality between pollution and climate change, which has a negative impact on both human health and nature. Because of this, determining and improving air quality has become a priority in today's society. Combustion of fossil fuels, industrialization or meteorological factors play a significant role in air pollution. Consequently, the society becomes interested in the existence of an application that provides a real-time air quality index of a certain geographical area, as well as a forecast on this air quality index for a few hours or days. Therefore, this paper proposes a practical solution for a faster adaptation of the human user by creating a database with information about polluted areas in the city. As a result, a person will be able to know the air quality both in the area where he finds himself, as well as in another location where he wants to move.