Search

Abstract Air travel has an important role in the spread of viral acute respiratory infections (ARIs). Aircraft offer an ideal setting for the transmission of ARI because of a closed environment, crowded conditions, and close-contact setting. Numerous studies have shown that influenza and COVID-19 spread readily in an aircraft with one virus-positive symptomatic or asymptomatic index case. The numbers of secondary cases differ markedly in different studies most probably because of the wide variation of the infectiousness of the infector as well as the susceptibility of the infectees. The primary risk factor is sitting within two rows of an infectious passenger. Elite athletes travel frequently and are thus prone to contracting an ARI during travel. It is anecdotally known in the sport and exercise medicine community that athletes often contract ARI during air travel. The degree to which athletes are infected in an aircraft by respiratory viruses is unclear. Two recent studies suggest that 8% of Team Finland members traveling to major winter sports events contracted the common cold most probably during air travel. Further prospective clinical studies with viral diagnostics are needed to understand the transmission dynamics and to develop effective and socially acceptable preventive measures during air travel.

This study aims to investigate the Joule effect, thermal radiation, and Coriolis effects in unsteady magnetohydrodynamics (MHD) micropolar flow over a 3-D unstable sheet. A magnetic field is typically applied to the surface; additionally, it is assumed that the fluid is conducting electricity. Other micro-rotations are also considered. The physical issue is resolved with the help of the fundamental equations, and the issue's complexity is reduced with the use of similarity variables. In the present approach, the homotopy analysis method (HAM) is employed. The heat, skin's friction factor, temperature, micro movements, and velocity associated with the emerging parameters and transfer rates are considered. The boundary layer thickness is increased as the parameter of vorticity increases. When the magnitude of the magnetic field increases, the skin friction coefficient decreases. The state variables are approximated up to six decimal places numerically. The numerical values of −f″(0) and −θ′(0) are computed to higher decimal places and compared with the available literature to validate the results. The outcomes obtained are compared with the available literature; the results here are corroborated, and the performance of the HAM is demonstrated.

Abstract Background Dengue fever caused by dengue virus is a tropical disease and is among the deadliest vector-borne diseases. The humid and hot summers of Pakistan support the probation of the vectors responsible for the transmission of viral and other parasitic diseases. Methodology A retrospective study, from 2012- 2019, of dengue infected individuals from the Punjab province of Pakistan was carried out to analyze epidemiology, clinical and laboratory findings of subjects with dengue virus infection. Data was derived from National Institute of Health (NIH) followed by Dengue control program of Pakistan, covering the incidence rate in 36 districts of Punjab and Islamabad Capital Territory (ICT) respectively. Patients data including the presence of dengue specific antigen or/and antibodies such as NS1 and IgG/IgM were observed. The study also included the analysis of demographic data, geographic data, and the month-wise distribution of dengue cases to examine seasonal trends. Results We analyzed 25,682 dengue infected individuals. The statistical analysis revealed a significant association between genders in which male population was more affected by dengue than females. It was also noted that the middle age group was the most affected age group while the highest number of cases were reported in October. Rawalpindi and Lahore were the most affected cities in Punjab province while Islamabad represented the highest number of cases during the recent outbreak in 2019. The IgM and IgG antibodies were highly prevalent among the infected patients. Conclusion Dengue is endemic in Pakistan, circulating throughout the year. Highest number of cases were observed in the month of October, September and November respectively. Association between climate change and vector-borne diseases need to be investigated in Pakistan as they significantly influence the timing and intensity of dengue and other disease outbreaks. Further exploration of hematological parameters is required to better diagnose and treat the disease. For the effective control of dengue outbreaks, awareness campaigns on sewage management and vector control along with social factors are strongly recommended for better control and eradication of the disease.

Objective: Hemodialysis patients with chronic kidney disease often exhibit inflammation characterized by elevated levels of C-reactive protein, Interleukin 6 and tumor necrosis factor-alpha, and they are shown to be associated with cardiovascular impairment and enhanced renal failure. This study aims to assess the impact of fish oil intake on inflammation indicators in adult hemodialysis patients. Methods: From the inception to December 2023, the datasets Cochrane Central, Google Scholar, Science Direct, Embase, and Pubmed were examined. Two authors independently searched, selected, and screened the literature. The pooled results are represented by weighted mean difference (WMD) with 95% confidence intervals. To investigate the causes of heterogeneity, subgroup analysis was done. Sensitivity analysis was then used to evaluate the validity of the combined findings. Results: Thirteen randomized control trials studies were included. The pooled results showed that fish oil supplementation caused a significant reduction of the C-reactive protein level (WMD, −2.92 mg/L; 95% Confidence interval, −5.23, to −0.61; p = 0.01; I 2 = 99%), especially in patients with baseline C-reactive protein ⩾5 mg/L (WMD, −4.39 mg/L; 95% Confidence interval, −5.93 to 2.85; p 5 mg/L, responded to fish oil supplementation to reduce their C-reactive protein level; however, Interleukin 6 and tumor necrosis factor-alpha levels did not appear to be affected.

Bionanofluids containing biological nanoparticles suspended in base fluids exhibit altered dynamics due to coupled effects between the nanoparticles and fluid properties. More efficient cooling can enhance medical technology performance, reduce energy usage, and provide safer, more sustainable healthcare solutions. This work overcomes previous research limitations by elucidating the combined impacts of microorganisms and couple stress properties on the behavior of water-based bionanofluids containing copper nanoparticles, under inclined magnetic fields. Governing equations for momentum, energy, concentration, and microorganisms are transformed into ordinary differential equations (ODEs) via similarity methods. The resulting ODE system is then solved semi-analytically using the Homotopy Analysis Method, revealing distinct profile behaviors. Additionally, quantitative indicators including skin friction for different values of M, λ,β, and Nr increased by 7.19%, 62.81%, 31.27%, and 21.32% respectively. Similarly Nusselt number for different values Qe , Ec, and Df decrease by 3.502 %, 2.5705%, and 2.447% respectively. Furthermore, Sherwood Numbers for different values of Sc, Kc, increased by 16.41%, and 4.133% respectively. Finally, Microorganisms for different values of Lb, Pe, and σ1 increase by 2.934%, 2.61%, and 1.172% respectively.

Objective: To determine one-month mortality in patients with ischemic stroke using Score for Early Ischemic Stroke Mortality. Study Design: Prospective longitudinal study. Place and Duration of Study: Combined Military Hospital, Jhelum Pakistan, from Jan 2020 to May 2021. Methodology: All patients with acute ischemic stroke, aged more than 18 years, of either gender, were consecutively enrolled. Mortality at 1 month in patients with ischemic stroke was noted along with the demographic and clinical characteristics (comorbidities, smoking status, clinical stroke at admission, and cause of the stroke). Mortality at 1 month was predicted by using Predicting Early Mortality of Ischemic Stroke score. Additionally, National Institutes of Health Stroke Scale, Glasgow Coma Scale, and previous Modified Ranking Scale at admission was also recorded. Results: Among 160 patients, the Mean age was 66.07±9.92 years. 121(75.6%) patients were males and 39(24.4%) were females. Mortality at 1 month was observed in 26(16.3%) patients. A significant association of mortality at 1 month was observed with age (p

This research reports on the combined effects of heat and mass transfer (HMT) under the influences of the Soret and Dufour in natural convection steady 2D magnetohydrodynamic flow through the boundary layer in a porous vertical tube or duct. The current study is motivated by the significant applications of HMT in engineering processes such as casting and welding. The goal of this framework is to explore the assisting and opposing movements with HMT above a vertical porous channel under the influence of invariant suction and fluid dissipation which have not been reported in the earlier studies. The governing flow equations in terms of partial differential equations (PDEs) are altered to dimensionless ordinary differential equations (ODEs) by using dimensionless variables. Employing the BVP4C approach, the leading equations are solved numerically. The dual nature of solutions has been observed due to suction. Stability exploration has been provided to confirm a stable solution. A comparison between published and current studies shows outstanding agreement. Key parameter effects on flow characteristics are visually offered using graphs as well as tables. It is noteworthy that the influence of Soret effects becomes apparent in a suspended mixture of particles and fluids. These phenomena can be attributed to temperature differences, whereby the motion of fluid particles in the warmest region with the maximum energy level causes the particles to migrate towards the coldest region. Notably, the flow speed rate at the left plate is initially high and slowly diminishes near the right plate.

ABSTRACT The selection of an appropriate production system plays a crucial role in ensuring the health, welfare, and productivity of American Pekin ducks. The aim of this study was to investigate the influence of various rearing production systems on the performance of American Pekin Ducks. A total of 180 straight run ducklings (10 days old) were randomly allocated into three experimental groups: intensive production system (IPS), free-range production system (FRPS), and pool with yard production system (PYPS). The distribution was carried out following a completely randomized design. We investigated the morphological parameters, growth performance, serum chemistry, meat cholesterol and triacylglycerol, cellular immunity, intestinal morphology, and carcass traits of Pekin ducks. The results indicate that PYPS birds exhibited significantly better morphometric parameters compared to IPS and FRPS ones. Ducks raised in PYPS had the highest growth rate till the 75th day as compared to those reared in IPS and FRPS. Triacylglycerol, total lipids, blood and meat fat and triacylglycerol were higher in IPS; whereas albumin, AG ratio, total proteins, glucose, and globulin were higher in PYPS. Similarly, cellular immunity (phagocytic activity, eosinophils, basophils, and monocytes) was increased in PYPS. Intestinal morphology and overall carcass traits were better in birds reared under PYPS than in those of IPS and FRPS. American Pekin ducks raised in PYPS showed improved growth, serum chemistry, cellular immunity, and carcass traits. These results suggest that the PYPS could be a promising production system for raising ducks in sub-tropical regions.

Metal induced artefacts in computed tomography (CT) images are primarily caused by beam hardening, scatter effects, and photon starvation. These artefacts impede the characterization of fine anatomical structures and compromise the diagnostic value of the CT images. We aim to develop an innovative machine learning-based technique called residual dense U-Net (RDU-Net), specifically for spectral photon-counting CT (SPCCT), to mitigate metal artefacts across all energy bins. The proposed model was quantitatively evaluated, with and without the metal artefact reduction (MAR) algorithm, using line profiles, histogram analysis, signal-to-noise ratio (SNR), root mean squared error (RMSE), and structural similarity index measure (SSIM). The results show significant improvements with the average SNR increasing from 3.37 to 17.40 across the five energy bins after the application of the MAR algorithm. The average RMSE decreased from 0.016 to 0.001, and the average SSIM increased by 34.9%. The study also evaluated material density images of hydroxyapatite (HA) and iodine, with and without the MAR algorithm, using the receiver operating characteristic (ROC) paradigm. The results show improved accuracy in the material identification for HA (86% to 91%) and iodine (84% to 93%) after MAR. Overall, the evaluation of the model show promising results and the potential to significantly decrease the metal artefacts in all the parameters used in the energy analysis at p < 0.0001, while preserving the attenuation profile of SPCCT images.

Stroke rehabilitation faces challenges in attaining enduring improvements in hand motor function and is frequently constrained by interventional limitations. This research aims to present an innovative approach to the integration of cognitive engagement within visual feedback incorporated into fully immersive virtual reality (VR) based games to achieve enduring improvements. These innovative aspects of interaction provide more functional advantages beyond motivation to efficiently execute repeatedly hand motor tasks. The effectiveness of virtual reality games incorporated with innovative aspects has been investigated for improvements in hand motor functions. A randomized controlled trial was conducted, a total of (n=56) subacute stroke patients were assessed for eligibility and (n=52) patients fulfilled the inclusion criteria. (n=26) patients were assigned to the experimental group and (n=26) patients were assigned to the control group. VR intervention involves four VR based games, developed based on hand movements including flexion/extension, close/open, supination/pronation and pinch. All patients got therapy of 24 sessions, lasting 4 days/week for a total of 6 weeks. Five clinical outcome measures were Fugl- Meyer Assessment-Upper Extremity, Action Research Arm Test, Box and Block Test, Modified Barthel Index, and Stroke-Specific Quality of Life were assessed to evaluate patients’ performance. Results revealed that after therapy there was significant improvement between the groups (p

The inclusion of nanoparticles has the potential to improve the thermal efficiency of the base fluid. The field of nanofluid (NF) dynamics has attracted important attention due to its extensive range of practical uses like fuel cells, solar energy, medication administration, heat transfer, microfabrication, coolant applications, and other related domains. The aim of this study is to scrutinize the impact of Lorentz force, thermal energy, joule heating, heat source and injection parameters, and Brownian and thermoporetic diffusions on the hybrid nanofluid over the moving wedge. The stability inquiry is reported for the existing work in order to confirm the stable solutions that make the study unique. Novelty of the existing work is to investigate the hybrid nanofluid flow and its stability. The nanoparticles MoS2 and Ag are suspended in ethylene glycol and water used as host fluids. The numerical solution is obtained from the dimensionless first-order differential equations, which are achieved from the basic flow phenomena through similarity alteration variables. The influence of emerging factors on flow phenomena is reported via graphs. The positive eigenvalues report stable solutions, while the negative eigenvalues designate unstable solutions. It is perceived that due to Lorentz force, the rate of the fluid declines while the temperature inside the flow channel enhances. The velocity profile decreases while the temperature and concentration increase with increasing quantities of permeable factors. Similarly, the Forchheimer number causes to enhance the flow rate and decrease the heat and concentration outlines. The current analysis is validated by the published work.

Amputation can have varying impacts on amputees depending on the extent of residual muscles left. Commercial prosthetics prioritize functional movements, neglecting patient-specific gestures related to the amputation type. Therefore, examining user-specific non-functional movements is pivotal. Rather than training on innumerable motions, prioritizing efficiently identifiable movements enhances prosthetic user-specificity. We examined 16 distinct wrist and finger motions using five classifiers (Wide Neural Networks, Ensemble Bagged Trees, Cubic SVM, Fine KNN, Logistic Regression Kernel). One-Way Anova testing ( $\text{p} < 0.05$ ) revealed significant classifier differences, with Wilcoxon signed-rank tests ( $\text{p} < 0.05$ ) distinguishing finger and wrist gestures. Ensemble Bagged Trees excelled ( $\text{p} < 0.05$ ) for finger (98.2% ± 0.81) and wrist (99% ± 0.73) movements; Fine KNN and Cubic SVM scored up to 96.3% ± 0.81 and 95.9% ± 1.43, respectively. Notably, Abduction of thumb and flexion of others consistently showed high accuracies for finger gestures. Wrist Radial Deviation (Clockwise) and Wrist Extension emerged as top wrist movements. Our study addresses the oversight of non-functional movements in myoelectric control. Our innovative approach focuses on selecting optimal finger and wrist movements for accurate gesture recognition, a departure from prior research neglecting these critical movements. By pinpointing these movements’ significance and performance, we provide a solution to enhance personalized prosthetic development. Our findings mark a pioneering step in leveraging accurate finger and wrist gestures to craft more effective and personalized myoelectric control systems. These insights bridge the gap in existing research and pave the way for improved prosthetic device design.

Abstract Deep neural networks (DNNs) have demonstrated higher performance results when compared to traditional approaches for implementing robust myoelectric control (MEC) systems. However, the delay induced by optimising a MEC remains a concern for real-time applications. As a result, an optimised DNN architecture based on fine-tuned hyperparameters is required. This study investigates the optimal configuration of convolutional neural network (CNN)-based MEC by proposing an effective data segmentation technique and a generalised set of hyperparameters. Firstly, two segmentation strategies (disjoint and overlap) and various segment and overlap sizes were studied to optimise segmentation parameters. Secondly, to address the challenge of optimising the hyperparameters of a DNN-based MEC system, the problem has been abstracted as an optimisation problem, and Bayesian optimisation has been used to solve it. From 20 healthy people, ten surface electromyography (sEMG) grasping movements abstracted from daily life were chosen as the target gesture set. With an ideal segment size of 200 ms and an overlap size of 80%, the results show that the overlap segmentation technique outperforms the disjoint segmentation technique (p-value

Subvocal voice recognition is important in rehabilitation because it allows people with speech issues to communicate in an alternate manner. Capturing and interpreting subtle muscular movements during subvocalization can improve the rehabilitation process, allowing patients to have more autonomy and a higher quality of life. The scarcity of research on subvocal voice recognition, as well as the use of IMU (accelerometer and gyroscope) signals for speech activity detection, are significant challenges. The study focuses on the amalgamation of spectrotemporal feature extraction techniques for classification and IMU data for speech activity detection. The study carries out the classification of an isolated word vocabulary sets of 70 words corresponding to 6 subjects and 96 isolated words for subjects. A feature extraction algorithm was used utilizing Variational Mode Decomposition. The results demonstrated maximum accuracy rates of 98.6% for the 70-word set and 92% for the 96-word set. Automatic speech activity detection (ADSAS) was developed using only IMU data and was independent of the EMG data. The comparison was carried out by using a previously proposed EMG activity detection method based on Teager Kaiser Operator and morphological operations, The IMU based detection technique achieved a lowest error of 0.09 compared to 0.21 for the EMG based detection technique. The results proved that IMU based methods perform better than EMG based methods for detection of speech activity. Statistical analysis was carried out using paired t-test and resulted in a significant difference between the two techniques (p-value< 0.05).