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We have developed a simple yet effective transform function to convert 3D point-source seismic data to equivalent 2D line-source data, which is required when applying efficient 2D migration and full-waveform inversion to field data collected along a line. By numerically comparing the 3D and corresponding 2D Green’s tensors in various media, the phase shift approximately 45° and the offset amplitude compensation factor, as well as small fluctuations of the amplitude ratios, are observed in all nonzero components of the wave-equation solutions. Based on these observations, we derive a transform function consisting of (1) a simple filter for compensating amplitude and phase shift and (2) stretching scalars for scaling amplitude differences for different components. We use the 3D and 2D analytical wave solutions in various homogeneous media to demonstrate the accuracy of our transform function, and then apply it to a heterogeneous viscoelastic anisotropic model and a modified Marmousi model. All of these results indicate that our transform function is applicable for the conversion of point-source data to equivalent line-source data for imaging 2D subsurface structure.

Background: Most primary Health Care Centers (PHCCs) in Iraq have a referral system records; however, this mechanism does not function well because of the lack of other requirements for an efficient referral system. Objective: To assess the practice & opinion of doctors in PHCs toward the referral system, and to determine the doctors in PHC's commitment to referral system instructions and guidelines. Subjects and methods: A cross-sectional study with analytic elements was conducted in nine health directorates in Iraq, from the 1st October 2018 – 30th June 2019.One PHC was selected randomly form each sector in every governorate, A questionnaire was used to collect the required information. SPSS version 24 analysis was used for the statistical analysis. Results: sixty-three doctors were working in PHCs had participated in the current study, the mean age (40.03 ±10.24), 58.7%were female, 46% were general practitioner, 30.2% of the participated doctors had 300 and less patient/month; 31.7% of doctors had ≤10 Patients referred/month, emergencies was the main cause for referral (46.03%), and 37(58.37%) of doctors announced that the referred-form not retrained to the PHC, and ever retrained-forms had no feedback 29(46%), 28(44%)of the participated doctors agreed that the current referral-system was effective and seven of them strongly agreed, 59(93.7%) believe in the importance of hospital-feedback, with a significant relationship between their attitude about the effective-current-referral system & Refer cases Percentage, while no significant-relation with their Patients examined/month. Loaded crowded and hospital doctors shortage as possible causes and suggest to referral-system activation especially the hospital -part". Conclusions: there was inadequate knowledge of referral-policies and lack of coordination or/and clear feedback-expectations and PHCs-hospitals collaboration and lack of referral-system integrated within an electronic-health-record.

In a magnetic field, two-dimensional (2D) mixed convection is investigated within a zigzagged trapezoidal chamber. The lower side of the trapezoidal chamber is irregular, in particular, a zigzagged wall with different zigzag numbers N. The fluid particles move in the room due to the motion of the upper wall, while the porosity-enthalpy approach represents the melting process. The thermal parameters of the fluid are enhanced by what is called a nano-encapsulated phase change material (NEPCM) consisting of polyurethane as the shell and a nonadecane as the core, while water is used as the base fluid. In order to treat the governing equations, the well-known Galerkin finite element method (GFEM) is applied. In addition, the heat transfer (HT) irreversibility and the fluid friction (FF) irreversibility are compared in terms of the average Bejan number. The main results show that the melt band curve behaves parabolically at smaller values of Reynolds number (Re) and larger values of Hartmann number (Ha). Moreover, minimizing the wave number is better in order to obtain a higher heat transfer rate.

Recently, phase change materials (PCMs) have gained great attention from engineers and researchers due to their exceptional properties for thermal energy storing, which would effectively aid in reducing carbon footprint and support the global transition of using renewable energy. The current research attempts to enhance the thermal performance of a shell-and-tube heat exchanger by means of using PCM and a modified tube design. The enthalpy–porosity method is employed for modelling the phase change. Paraffin wax is treated as PCM and poured within the annulus; the annulus comprises a circular shell and a fined wavy (trefoil-shaped) tube. In addition, copper nanoparticles are incorporated with the base PCM to enhance the thermal conductivity and melting rate. Effects of many factors, including nanoparticle concentration, the orientation of the interior wavy tube, and the fin length, were examined. Results obtained from the current model imply that Cu nanoparticles added to PCM materials improve thermal and melting properties while reducing entropy formation. The highest results (27% decrease in melting time) are obtained when a concentration of nanoparticles of 8% is used. Additionally, the fins’ location is critical because fins with 45° inclination could achieve a 50% expedition in the melting process.

Energy saving has always been a topic of great interest. The usage of nano-enhanced phase change material NePCM is one of the energy-saving methods that has gained increasing interest. In the current report, we intend to simulate the natural convection flow of NePCM inside an inverse T-shaped enclosure. The complex nature of the flow results from the following factors: the enclosure contains a hot trapezoidal fin on the bottom wall, the enclosure is saturated with pours media, and it is exposed to a magnetic field. The governing equations of the studied system are numerically addressed by the higher order Galerkin finite element method (GFEM). The impacts of the Darcy number (Da = 10−2–10−5), Rayleigh number (Ra = 103–106), nanoparticle volume fraction (φ = 0–0.08), and Hartmann number (Ha = 0–100) are analyzed. The results indicate that both local and average Nusselt numbers were considerably affected by Ra and Da values, while the influence of other parameters was negligible. Increasing Ra (increasing buoyancy force) from 103 to 106 enhanced the maximum average Nusselt number by 740%, while increasing Da (increasing the permeability) from 10−5 to 10−2 enhanced both the maximum average Nusselt number and the maximum local Nusselt number by the same rate (360%).

BackgroundNon-alcoholic fatty liver disease (NAFLD) is an overlooked complication of type 2 diabetes (T2D). Current recommendations for the management of NAFLD are mainly focused on weight reduction, overlooking the role of macronutrient composition. Although dietary carbohydrates play a major role in intrahepatic fat synthesis, their association with the progression of liver steatosis has not been fully investigated in patients with T2D.AimTo investigate the association between higher carbohydrate intake and the presence of liver steatosis in patients with T2D.MethodsThis cross-sectional study included men and women aged 18–60 years diagnosed with T2D. Anthropometric measurements, hepatic steatosis assessment using the controlled attenuation parameter (CAP), blood samples, and dietary data were analyzed. Participants were divided into two groups: NAFLD and NAFLD-free. A two-sample t-test was used to evaluate the differences between the two groups. Stepwise multiple linear regression models adjusted for potential confounders were used to determine the association between CAP values and higher carbohydrate intake.ResultsIn total, 358 participants were included. NAFLD was present in 79.3% of the participants. Body mass index, waist circumference, ALT, HbA1c, and triglycerides showed direct, while HDL-Cholesterol revealed inverse associations with CAP values. No significant relationship was found between carbohydrate intake and steatosis in the total study sample; however, multiple linear regression analysis revealed a significant relationship between carbohydrate intake and CAP values in patients aged ≤50 years.ConclusionIn patients with T2D, higher carbohydrate intake was associated with liver steatosis in those aged 50 years and below. Further studies are required to confirm the causality between carbohydrate intake and liver steatosis.

In frequency-domain seismic wave modeling, absorbing artificial reflections is crucial to obtain accurate numerical solutions. We have determined that, in viscoelastic anisotropic media (VEAM), the most popular absorbing boundary techniques, such as the perfectly matched layer and the generalized stiffness reduction method (GSRM), fail. Then, we develop a new version of the GSRM and incorporate it into a 2D/2.5D spectral element method. We find with extensive nontrivial numerical experiments that the new GSRM exhibits excellent features of simple and efficient implementation, while handling free-surface and subsurface interface topography. Furthermore, we find that sampling the positive wavenumber range is an efficient strategy to compute the 3D wavefield in arbitrary 2D VEAM, and the new version takes full advantage of the symmetry/antisymmetry of the wavefield. The new GSRM removes artificial reflections by damping the real and imaginary viscoelastic moduli in different ways. The wavefields in two vertically transverse isotropic and one orthorhombic viscoelastic homogeneous models are compared with the corresponding analytical solutions to show the high accuracy performance of the new GSRM. Finally, a complex 2D geologic model with irregular free-surface and subinterface is considered to present the modeling technique and its adaptation capacity for complex 2D VEAM.

Sodium-ion batteries are making inroads toward better acceptance by both research and industry communities as promising electrochemical energy storage systems for stationary battery applications. The extreme dedication to lithium-ion batteries, since the early 90s, has eclipsed any significant development around room temperature Na-ion batteries, despite the materials availability advantage the latter have over the Li-ion battery counterparts. Benefiting from the substantial knowledge accumulated on Li-ion batteries, tremendous progress rapidly occurred with focus on solving the fundamental issues encountered at the component, system and cost levels in Na-ion batteries. In this review, we discuss the key aspects that make Na-ion batteries enable the research of a wide spectrum of sodium-based materials and electrolytes, which further catalyzes the development of plethora of energy storage systems.

Mobile learning (m-learning) adoption has increased and shall be demonstrated superior performance by implementing related computing paradigms, such as IoT, edge, mobile edge, fog, AI, and 5G. Mobile cloud architectures (MCAs) enable m-learning with several benefits and face limitations while executing real-time applications. This study investigates the state-of-the-art m-learning architectures, determines a layered m-learning-MCA obtaining numerous benefits of related computing paradigms, and expands m-learning functional structure. It evaluates m-learning performance across the four physical layer’s MCAs—distance cloud, cloudlet, operator-centric cloud, ad hoc cloud, and emerging computing architectures. Surprisingly, only distance-cloud MCA is adopted for developing m-learning systems by ignoring the other three. Performance evaluation shows m-learning gets terrific benefits and users QoE in related computing paradigms. Mobile edge computing offers ultralow latency, whereas the current architecture improves task execution time (1.87, 2.01, 2.63, and 3.97) for the resource-intensive application (i.e., 4.2 MB). Fog using AI algorithms is exceptional for more complex learning objects, IoT is superior for intelligent learning tools, and 5G ultrawideband services are more significant for intelligent video analytics. These findings help learners, educators, and institutions adopt an appropriate model for achieving their academic objectives across educational disciplines. The presented approach enables future research to design innovative architectures considering resource-intensive m-learning application execution requirements, such as video content analytics and virtual reality learning models.

In this paper, we present new nonlinear contractions based on altering distances and prove the existence and uniqueness of fixed points for cyclic operators. We prove here very interesting fixed point theorems in which we combine and extend the contractive conditions of Banach, Kannan, Chatterjea, and of many others. Our results shall serve as generalized versions of many fixed point results proved in the literature. Examples and application to integral equations that exploits Jensen inequality are given to illustrate the analysis and theory and validate our proved results. Publisher's Version

One of the largest spontaneous adverse events reporting databases in the world is the Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS). Unfortunately, researchers face many obstacles in analyzing data from the FAERS database. One of the major obstacles is the unstructured entry of drug names into the FAERS, as reporters might use generic names or trade names with different naming structures from all over the world and, in some cases, with typographical errors. Moreover, report duplication is a known problem in spontaneous adverse event-reporting systems, including the FAERS database. Hence, thorough text processing for database entries, especially drug name entries, coupled with a practical case-deduplication logic, is a prerequisite to analyze the database, which is a time- and resource-consuming procedure. In this study, we provide a clean, deduplicated, and ready-to-import dataset into any relational database management software of the FAERS database up to September 2021. Drug names are standardized to the RxNorm vocabulary and normalized to the single active ingredient level. Moreover, a pre-calculated disproportionate analysis is provided, which includes the reporting odds ratio (ROR), proportional reporting ratio (PRR), Chi-squared analysis with Yates correction (x2), and information component (IC) for each drug-adverse event pair in the database.

The authors have requested that this preprint be removed from Research Square.

The Schwarz waveform relaxation (SWR) algorithms have many favorable properties and are extensively studied and investigated for solving time dependent problems mainly at a continuous level. In this paper, we consider a semi-discrete level analysis and we investigate the convergence behavior of what so-called semi-discrete SWR algorithms combined with discrete transmission conditions instead of the continuous ones. We shall target here the hyperbolic problems but not the parabolic problems that are usually considered by most of the researchers in general when investigating the properties of the SWR methods. We first present the classical overlapping semi-discrete SWR algorithms with different partitioning choices and show that they converge very slow. We then introduce optimal, optimized, and quasi optimized overlapping semi-discrete SWR algorithms using new transmission conditions also with different partitioning choices. We show that the new algorithms lead to a much better convergence through using discrete transmission conditions associated with the optimized SWR algorithms at the semi-discrete level. In the performed semi-discrete level analysis, we also demonstrate the fact that as the ratio between the overlap size and the spatial discretization size gets bigger, the convergence factor gets smaller which results in a better convergence. Numerical results and experiments are presented in order to confirm the theoretical aspects of the proposed algorithms and providing an evidence of their usefulness and their accuracy.

Fresh water is scarce, making it a worldwide issue. In order to address global freshwater demand, a filtration technique is needed. Solar distillation (SD) that purifies brackish and subterranean water has been proven to be a promising green technology. It produces distilled water which can be used as potable water for drinking and other purposes. The designs, operations, and configurations of several inverted solar stills are thoroughly examined in this article. All techniques for solar water distillation to separate saltwater from freshwater have the same fundamental idea. It has been demonstrated that for a specified mass of water in the top basin, the daily output of an inverted absorber double-basin solar still (IASS) grows with increasing water depth in the bottom basin. Nevertheless, as the water depth in the bottom basin rises from 1 cm to 5 cm, the output of an inverted absorber double-basin solar system falls by about 27%. At water depths of 4, 6, and 8 cm, the daily yields from inverted absorber solar stills paired with a refrigeration cycle (RIASS) were 6.4, 10.08, and 9.5 L/day, respectively. The results also showed a substantial rise in water temperature in the inverted absorber solar still as a result of lower bottom heat loss and larger absorptivity. In this study, the emphasis on energy, efficiency, and environmental concerns remains with the modified multi-wick basin-type inverted absorber solar panel. The performance of the inverted trickling solar still was assessed with a 60 ppm average salinity under various sun radiation, feed water flow rate, and existence conditions for natural convection. It was found that the still could produce 2.55 L/day m2 of fresh water, a 15% increase. Brackish water with a salinity of 6000 ppm was used to test the still in November at tilt angles of 47° and 32°. Condensate production at the specified angles was 2.8 and 2 L/d, respectively. A total output of 6.907, 5.681, and 4.650 kg/m2/day was also generated using the modified multi-wick basin-type inverted absorber solar still (MMWBIASS) at water depths of 1, 2, and 3 cm, respectively. With black cotton wicks, the MMWBIASS had a total thermal efficiency of 34.04%, 28.17%, and 23.61%.

Nicergoline (NIC) is a semisynthetic ergot alkaloid derivative applied for treatment of dementia and other cerebrovascular disorders. The efficacy of sesame oil to slow and reverse the symptoms of neurodegenerative cognitive disorders has been proven. This work aimed to formulate and optimize sesame oil-based NIC-nanostructured lipid carriers (NIC–NLCs) for intranasal (IN) delivery with expected synergistic and augmented neuroprotective properties. The NIC–NLC were prepared using sesame oil as a liquid lipid. A three-level, three-factor Box–Behnken design was applied to statistically optimize the effect of sesame oil (%) of the total lipid, surfactant concentration, and sonication time on particle size, zeta potential, and entrapment efficacy as responses. Solid-state characterization, release profile, and ex vivo nasal permeation in comparison to NIC solution (NIC–SOL) was studied. In vivo bioavailability from optimized NIC–NLC and NIC–SOL following IN and IV administration was evaluated and compared. The optimized NIC–NLC formula showed an average particle size of 111.18 nm, zeta potential of −15.4 mV, 95.11% entrapment efficacy (%), and 4.6% loading capacity. The NIC–NLC formula showed a biphasic, extended-release profile (72% after 48 h). Permeation of the NIC–NLC formula showed a 2.3 enhancement ratio. Bioavailability studies showed a 1.67 and 4.57 fold increase in plasma and brain following IN administration. The results also indicated efficient direct nose-to-brain targeting properties with the brain-targeting efficiency (BTE%) and direct transport percentage (DTP%) of 187.3% and 56.6%, respectively, after IN administration. Thus, sesame oil-based NIC–NLC can be considered as a promising IN delivery system for direct and efficient brain targeting with improved bioavailability and expected augmented neuroprotective action for the treatment of dementia.