Diagnostic Imaging and Radiation Therapy in the Arab World: A New Model of Advanced Practice

This study aimed at suggesting a new model for advanced practice in the diagnostic imaging and radiation therapy in the Arab World by presenting a comparative study between the different medical imaging techniques, the concepts, benefits, risks and medical applications of these techniques has been presented with details. Attempting For building a new model of advanced practice for the diagnostic role of  imaging and radiation therapy in the Arab World; by analyzing the current status of the imaging and radiation therapy in the Arab World, and then surveying the different medical imaging techniques. Then  to suggest a model of best practices upon the outcomes of the study

Improving the melting performance in a triple-pipe latent heat storage system using hemispherical and quarter-spherical fins with a staggered arrangement

This study aims to evaluate the melting characteristics of a phase change material (PCM) in a latent heat storage system equipped with hemispherical and quarter-spherical fins. A vertical triple-pipe heat exchanger is used as the PCM-based heat storage unit to improve the melting performance compared with a double-pipe system. Furthermore, the fins are arranged in inline and staggered configurations to improve heat transfer performance. For the quarter-spherical fins, both upward and downward directions are examined. The results of the system equipped with novel fins are compared with those without fins. Moreover, a fin is added to the heat exchanger’s base to compensate for the natural convection effect at the bottom of the heat exchanger. Considering similar fin volumes, the results show that the system equipped with four hemispherical fins on the side walls and an added fin on the bottom wall has the best performance compared with the other cases with hemispherical fins. The staggered arrangement of the fins results in a higher heat transfer rate. The downward quarter-spherical fins with a staggered configuration show the highest performance among all the studied cases. Compared with the case without fins, the heat storage rate improves by almost 78% (from 35.6 to 63.5 W), reducing the melting time by 45%

Numerical analysis of the energy-storage performance of a PCM-based triplex-tube containment system equipped with arc-shaped fins

This study numerically intends to evaluate the effects of arc-shaped fins on the melting capability of a triplex-tube confinement system filled with phase-change materials (PCMs). In contrast to situations with no fins, where PCM exhibits relatively poor heat response, in this study, the thermal performance is modified using novel arc-shaped fins with various circular angles and orientations compared with traditional rectangular fins. Several inline and staggered layouts are also assessed to maximize the fin’s efficacy. The effect of the nearby natural convection is further investigated by adding a fin to the bottom of the heat-storage domain. Additionally, the Reynolds number and temperature of the heat-transfer fluid (HTF) are evaluated. The outcomes showed that the arc-shaped fins could greatly enhance the PCMs’ melting rate and the associated heat-storage properties. The melting rate is 17% and 93.1% greater for the case fitted with an inline distribution of the fins with a circular angle of 90° and an upward direction, respectively, than the cases with uniform rectangular fins and no fins, which corresponded to the shorter melting time of 14.5% and 50.4%. For the case with arc-shaped fins with a 90° circular angle, the melting rate increases by 9% using a staggered distribution. Compared to the staggered fin distribution, adding an extra fin to the bottom of the domain indicates adverse effects. The charging time reduces by 5.8% and 9.2% when the Reynolds number (Re) rises from 500 to 1000 and 1500, respectively, while the heat-storage rate increases by 6.3% and 10.3%. When the fluid inlet temperature is 55°C or 50°C, compared with 45°C, the overall charging time increases by 98% and 47%, respectively

Encapsulated deep eutectic solvent for esterification of free fatty acid

A novel encapsulated deep eutectic solvent (DES) was introduced for biodiesel production via a two-step process. The DES was encapsulated in medical capsules and were used to reduce the free fatty acid (FFA) content of acidic crude palm oil (ACPO) to the minimum acceptable level (< 1%). The DES was synthesized from methyltriphenylphosphonium bromide (MTPB) and p-toluenesulfonic acid (PTSA). The effects pertaining to different operating conditions such as capsule dosage, reaction time, molar ratio, and reaction temperature were optimized. The FFA content of ACPO was reduced from existing 9.61% to less than 1% under optimum operating conditions. This indicated that encapsulated MTPB-DES performed high catalytic activity in FFA esterification reaction and showed considerable activity even after four consecutive recycling runs. The produced biodiesel after acid esterification and alkaline transesterification met the EN14214 international biodiesel standard specifications. To our best knowledge, this is the first study to introduce an acidic catalyst in capsule form. This method presents a new route for the safe storage of new materials to be used for biofuel production. Conductor-like screening model for real solvents (COSMO-RS) representation of the DES using σ-profile and σ-potential graphs indicated that MTPB and PTSA is a compatible combination due to the balanced presence and affinity towards hydrogen bond donor and hydrogen bond acceptor in each constituent

The development and validation of a scoring tool to predict the operative duration of elective laparoscopic cholecystectomy

Background: The ability to accurately predict operative duration has the potential to optimise theatre efficiency and utilisation, thus reducing costs and increasing staff and patient satisfaction. With laparoscopic cholecystectomy being one of the most commonly performed procedures worldwide, a tool to predict operative duration could be extremely beneficial to healthcare organisations. Methods: Data collected from the CholeS study on patients undergoing cholecystectomy in UK and Irish hospitals between 04/2014 and 05/2014 were used to study operative duration. A multivariable binary logistic regression model was produced in order to identify significant independent predictors of long (> 90 min) operations. The resulting model was converted to a risk score, which was subsequently validated on second cohort of patients using ROC curves. Results: After exclusions, data were available for 7227 patients in the derivation (CholeS) cohort. The median operative duration was 60 min (interquartile range 45–85), with 17.7% of operations lasting longer than 90 min. Ten factors were found to be significant independent predictors of operative durations > 90 min, including ASA, age, previous surgical admissions, BMI, gallbladder wall thickness and CBD diameter. A risk score was then produced from these factors, and applied to a cohort of 2405 patients from a tertiary centre for external validation. This returned an area under the ROC curve of 0.708 (SE = 0.013, p  90 min increasing more than eightfold from 5.1 to 41.8% in the extremes of the score. Conclusion: The scoring tool produced in this study was found to be significantly predictive of long operative durations on validation in an external cohort. As such, the tool may have the potential to enable organisations to better organise theatre lists and deliver greater efficiencies in care

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Pinless friction stir spot welding of aluminium alloy with copper interlayer

Spot welding joints of Al-Mg-Si alloy (AA6061-T6) were produced with and without the addition of copper interlayer using pinless friction stir spot welding (P-FSSW). To investigate the effects of welding parameters on the metallurgical and mechanical properties of the weldment, various tool plunge depth and dwell time were used. Optical microscopy, scanning electron microscopy, and energy-dispersive X-ray spectroscopy (EDS) have been used for microstructural characterisation.Meanwhile, the mechanical characterisation of the welded joints was evaluated by tensile-shear test. The experimental results showed that a larger bonding area and sound joint were achieved with the addition of Cu interlayer due to the improvement in thermal distribution. Also, an alloying reaction took place between the aluminium substrate and Cu interlayer during P-FSSW, forming intermetallic compounds layer in the interface through the diffusion process. The increasing of dwell time and plunge depth to some extent were beneficial to the formation of the joint and diffusion process, and thus increasing the tensile-shear load of the joints. The observed fracture mode of the joint was either completely shear off in the interface or complete nugget pullout

Imagined Speech Classification Using EEG and Deep Learning

In this paper, we propose an imagined speech-based brain wave pattern recognition using deep learning. Multiple features were extracted concurrently from eight-channel electroencephalography (EEG) signals. To obtain classifiable EEG data with fewer sensors, we placed the EEG sensors on carefully selected spots on the scalp. To decrease the dimensions and complexity of the EEG dataset and to avoid overfitting during the deep learning algorithm, we utilized the wavelet scattering transformation. A low-cost 8-channel EEG headset was used with MATLAB 2023a to acquire the EEG data. The long-short term memory recurrent neural network (LSTM-RNN) was used to decode the identified EEG signals into four audio commands: up, down, left, and right. Wavelet scattering transformation was applied to extract the most stable features by passing the EEG dataset through a series of filtration processes. Filtration was implemented for each individual command in the EEG datasets. The proposed imagined speech-based brain wave pattern recognition approach achieved a 92.50% overall classification accuracy. This accuracy is promising for designing a trustworthy imagined speech-based brain–computer interface (BCI) future real-time systems. For better evaluation of the classification performance, other metrics were considered, and we obtained 92.74%, 92.50%, and 92.62% for precision, recall, and F1-score, respectively

Synthesis of dimethyl carbonate for enhancement of gasoline performance

This study aimed to investigate the preparation and application of a green chemical (i.e., dimethyl carbonate (DMC)) as an anti-knocking agent for gasoline. Another objective was to study the usage of wastes of eggs as a heterogeneous catalyst in the process. Results of Brunauer–Emmett–Teller method showed that both the surface area and pore volume of calcined eggshell and pure CaO were of the same order. Results showed that calcined eggshell and pure CaO have almost the same X-ray diffraction images confirming the suitability of eggshell wastes as a heterogeneous catalyst for the preparation of DMC. SEM analysis revealed that the morphology of the CaO nano-particles are spherical shape for the Nanoparticles (NPs) and CaO was determined to be ∼63 nm in size. FTIR (Fourier-transform infrared spectroscopy) spectra of reaction mixture proved the presence of dimethyl carbamate in the resulting sample. Experimental results indicated that optimum operating parameters for an 80.4% yield of DMC were 9:1 ratio of methanol-to propylene carbonate, 0.8 wt% catalyst, and 2 h of operating time. The blending of DMC with pool gasoline showed a noticeable increase in the octane number compared with other conventional toxic additives. Keywords: Green chemicals, Eggshell wastes, Pool gasoline, Selective additive, Anti-knocking characteristic