Evolution of structural and magnetic properties in Ta/Ni_81Fe_(19) multilayer thin films

The interdiffusion kinetics in short period (12.8 nm) Ta/Ni81Fe19 polycrystalline multilayer films has been investigated and related to the evolution of soft magnetic properties upon thermal annealing in the temperature range 300-600-degrees-C. Small angle x-ray diffraction and transmission electron microscopy were used to estimate the multilayer period. Interdiffusion in the multilayers was directly computed from the decay of the satellites near (000) in a small angle x-ray diffraction spectrum. A kinetic analysis of interdiffusion suggests that grain growth is concurrent with grain boundary diffusion of Ta in Ni81Fe19. The evolution of soft magnetic properties of Ni81Fe19, i.e., lowering of 4piM(s) and increase in coercivity H(c), also lend support to the above analysis

Photon signature analysis using template matching

We describe an approach to detect improvised explosive devices (IEDs) by using a template matching procedure. This approach relies on the signature due to backstreaming ? photons from various targets. In this work we have simulated cylindrical targets of aluminum, iron, copper, water and ammonium nitrate (nitrogen-rich fertilizer). We simulate 3.5 MeV source photons distributed on a plane inside a shielded area using Monte Carlo N-Particle (MCNP TM) code version 5 (V5). The 3.5 MeV source gamma rays yield 511 keV peaks due to pair production and scattered gamma rays. In this work, we simulate capture of those photons that backstream, after impinging on the target element, toward a NaI detector. The captured backstreamed photons are expected to produce a unique spectrum that will become part of a simple signal processing recognition system based on the template matching method. Different elements were simulated using different sets of random numbers in the Monte Carlo simulation. To date, the sum of absolute differences (SAD) method has been used to match the template. In the examples investigated, template matching was found to detect all elements correctly

Resistivity network and structural model of the oxide cathode for CRT application

In this paper, the electrical properties of oxide cathode and oxide cathode plus, supplied by LG Philips Displays, have been investigated in relation to different cathode activation regimes and methods. Oxide cathode activation treatment for different durations has been investigated. The formations of the compounds associated to the diffusion of reducing elements (Mg, Al, and W) to the Ni cap surface of oxide cathode were studied by a new suggestion method. Scanning electron microscopy (SEM) coupled with energy dispersive X-ray spectroscopy (EDX) was used as analytical techniques. Al, W, and Mg doping elements take place during heating to 1080 K (Ni-Brightness) under a rich controlled Ba–SrO atmosphere through an acceleration life test. The chemical transport of these elements was occurred mainly by the Ni cap grain boundary mechanism with significant pile-up of Mg compounds. Al and W show a superficial concentrations and distribution. A new structural and resistivity network model of oxide cathode plus are suggested. The new structural model shows a number of metallic and metallic oxide pathways are exist at the interface or extended through the oxide coating. The effective values of the resistances and the type of the equivalent circuit in the resistivity network model are temperature and activation time dependent.</p

The non-standard finite difference scheme for linear fractional PDEs in fluid mechanics

AbstractA non-standard finite difference scheme is developed to solve the linear partial differential equations with time- and space-fractional derivatives. The Grunwald–Letnikov method is used to approximate the fractional derivatives. Numerical illustrations that include the linear inhomogeneous time-fractional equation, linear space-fractional telegraph equation, linear inhomogeneous fractional Burgers equation and the fractional wave equation are investigated to show the pertinent features of the technique. Numerical results are presented graphically and reveal that the non-standard finite difference scheme is very effective and convenient for solving linear partial differential equations of fractional order

Post COVID-19 effect on medical staff and doctors' productivity analysed by machine learning

The COVID-19 pandemic has profoundly affected the healthcare sector and the productivity of medical staff and doctors. This study employs machine learning to analyze the post-COVID-19 impact on the productivity of medical staff and doctors across various specialties. A cross-sectional study was conducted on 960 participants from different specialties between June 1, 2022, and April 5, 2023. The study collected demographic data, including age, gender, and socioeconomic status, as well as information on participants' sleeping habits and any COVID-19 complications they experienced. The findings indicate a significant decline in the productivity of medical staff and doctors, with an average reduction of 23% during the post-COVID-19 period. These results reflect the overall impact observed following the entire course of the COVID-19 pandemic and are not specific to a particular wave. The analysis revealed that older participants experienced a more pronounced decline in productivity, with a mean decrease of 35% compared to younger participants. Female participants, on average, had a 28% decrease in productivity compared to their male counterparts. Moreover, individuals with lower socioeconomic status exhibited a substantial decline in productivity, experiencing an average decrease of 40% compared to those with higher socioeconomic status. Similarly, participants who slept for fewer hours per night had a significant decline in productivity, with an average decrease of 33% compared to those who had sufficient sleep. The machine learning analysis identified age, specialty, COVID-19 complications, socioeconomic status, and sleeping time as crucial predictors of productivity score. The study highlights the significant impact of post-COVID-19 on the productivity of medical staff and doctors in Iraq. The findings can aid healthcare organizations in devising strategies to mitigate the negative consequences of COVID-19 on medical staff and doctors' productivity

Impact of diabetes mellitus on clinical presentation and treatment response of smear positive pulmonary tuberculosis patients

Background: Diabetes mellitus (DM) is a known risk factor for tuberculosis (TB). The aim of this study was to evaluate the effect of DM on clinical presentation and treatment response of sputum positive pulmonary tuberculosis patients.Methods: The present retrospective study was carried out in department of Pulmonary Medicine, Sree Gokulam Medical College and Research Foundation, Trivandrum, between January 2014 to December 2016.Results: Out of 205 subjects enrolled for this study, 73 were diagnosed with DM and 132 patients had no history of DM and were having HbA1c less than 6.5%. Mean HbA1c in DM group at presentation was 10.5 and in patients without DM group was 5.6. Low BMI was more in DM patients. Clinical characteristics at presentation were similar in both the groups. Patients with DM presented after long duration of symptoms (>8 weeks duration) and also with more atypical symptoms. On radiological examination, lower zone involvement and cavity lesions were more in patients with DM which was statistically significant. Clinical picture at the end of 6 months showed improvement in both the groups but radiological improvement was more in patients without DM compared to the other group.Conclusions: Uncontrolled DM is associated with high prevalence of Tuberculosis. Atypical symptoms and atypical radiological findings are more common in DM patients which lead to delayed presentation. Strategies are needed to ensure that optimal care is provided to patients with both diseases.

Does Consumers’ Demographic Profile influence Online Shopping?: an Examination using Fishbein’s Theory

Using questionnaire survey, this study examines whether demographic profile could influence the consumers’ attitude towards online shopping behavior. Five demographic profile variables that could be linked to attitude were chosen: gender, age, job designation, marital status and salary. The results show that all variables are important determinants to online shopping behavior. Such results support Fishbein’s attitude theory that states demographic profile as important variable in influencing attitude towards an object. The findings of this study provide some understanding to the service providers and the government on the effect of demographic profile on online shopping. Of consequence, such understanding would help them in finding and implementing suitable strategies to enhance online shopping. Keywords: online shopping; part-time students; Fishbein’s attitude theor

Nutrient content in rice husk ash of some malaysian rice varieties

Analysis performed on more than 60 samples of 10 different paddy varieties showed 21.33% of the rough rice comprised rice husk, while 13% of the husk constituted rice husk ash. The nutrient content of rice husk ash was 80.26% silica, 0.38% phosphorus, 1.28% potassium, 0.21% magnesium and 0.56% calcium. Statistically, nutrient composition is significantly influenced by varietal differences. As a potential material for fertilizer use, the estimates of total nutrient supplementation available from rice husk ash per annum are discussed

Imaging Tumor Acidity: pH-Low Insertion Peptide Probe for Optoacoustic Tomography

Optoacoustic tomography has been used for the detection of pancreatic ductal adenocarcinoma targeted by pH-Low Insertion Peptide (pHLIP) conjugated to near infrared fluorescent dye. It was proved that tumor targeting is a pH-dependent. The approach could have major implication for detection and monitoring of pancreatic and other cancers