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Efficient hybrid heuristic adopted deep learning framework for diagnosing breast cancer using thermography images
Abstract The most dangerous form of cancer is breast cancer. This disease is life-threatening because of its aggressive nature and high death rates. Therefore, early discovery increases the patient’s survival. Mammography has recently been recommended as diagnosis technique. Mammography, is expensive and exposure the person to radioactivity. Thermography is a less invasive and affordable technique that is becoming increasingly popular. Considering this, a recent deep learning-based breast cancer diagnosis approach is executed by thermography images. Initially, thermography images are chosen from online sources. The collected thermography images are being preprocessed by Contrast Limited Adaptive Histogram Equalization (CLAHE) and contrasting enhancement methods to improve the quality and brightness of the images. Then, the optimal binary thresholding is done to segment the preprocessed images, where optimized the thresholding value using developed Rock Hyraxes Dandelion Algorithm Optimization (RHDAO). A newly implemented deep learning structure StackVRDNet is used for further processing breast cancer diagnosing using thermography images. The segmented images are fed to the StackVRDNet framework, where the Visual Geometry Group (VGG16), Resnet, and DenseNet are employed for constructing this model. The relevant features are extracted usingVGG16, Resnet, and DenseNet, and then obtain stacked weighted feature pool from the extracted features, where the weight optimization is done with the help of RHDAO. The final classification is performed using StackVRDNet, and the diagnosis results are obtained at the final layer of VGG16, Resnet, and DenseNet. A higher scoring method is rated for ensuring final diagnosis results. Here, the parameters present within the VGG16, Resnet, and DenseNet are optimized via the RHDAO to improve the diagnosis results. The simulation outcomes of the developed model achieve 97.05% and 86.86% in terms of accuracy and precision, respectively. The effectiveness of the designed methd is being analyzed via the conventional breast cancer diagnosis models in terms of various performance measures.
RETRACTED ARTICLE: Sentimental analysis based federated learning privacy detection in fake web recommendations using blockchain model
Combined use of 1,3-dichloropropene with dimethyl disulfide and chloropicrin for managing potato powdery scab and weed
The evolutionary history and timeline of mites in ancient soils
The impact of air pollution on the settlement intention of the floating population——Empirical evidence from China
Race- and sex-specific differences in the risk of incident hearing loss and associated factors
Development and external validation of a machine learning model to predict bronchopulmonary dysplasia using dynamic factors
Determinants of retinopathy and short-term neurological outcomes after cerebral malaria
Abstract Neurological abnormalities are frequent after cerebral malaria (CM) resolves. The identification of survivors that should be prioritized during follow-up after CM is necessary for post-hospitalization care. We analysed social, clinical, and immune determinants of malarial retinopathy (MR) and short-term neurological outcomes after CM. Children aged 24 to 71 months with CM were prospectively followed-up until 28 days after admission at two hospitals in Benin. Direct ophthalmoscopy was performed shortly after admission. Plasma biomarkers were measured at admission. A neurocognitive deficit screener was administered at discharge and 21–28 days after admission. Of 70 children, 20 died before discharge (28.6%). Neurological deficits decreased from 100% on admission to 48.9% at discharge, and to 16.7% at 21–28 days after admission. MR was found in 58% of children. In multivariate analysis, factors associated with MR were a traditional consultation before admission and study site. In addition, neurological deficits were associated with MR (Odds Ratio 5.54 95% CI (1.30–23.54)). In univariate analysis, higher plasma levels of angiopoietin-2 were associated with neurological deficit at discharge and at days 21–28 post-admission. Therefore, MR and endothelium activation may be markers of neurological deficit, the former at hospital discharge and the latter at discharge and at D21–D28 post-admission.
Global burden trends and forecasts for MAFLD in adolescents and young adults from 1990 to 2021
PVTE system performance improvement via numerical optimization of heat sink design and fluid working conditions
A new auxiliary variables-based estimator for population distribution function under stratified random sampling and non-response
Effects of functional electrical stimulation on cognition rate and gait in neurological patients during single- and dual-task walking
Abstract People with neurological disorders and foot drop may suffer from cognitive-motor interference during walking. Functional Electrical Stimulation (FES) targets foot drop during gait but its effects on cognition remain underexplored. Fifteen individuals (4 males, 11 females; mean age 35.5 ± 12.5 years) with various neurological disorders, who had been using FES for at least three months, were recruited from our outpatient clinic. Subjects were assessed during walking with and without FES (FES CONDITION) and under single- and dual-task walking (TASK). The dual-task consisted of counting backwards from a number near 100 in steps of seven while walking. Cognition rate served as outcome parameter, with high values indicating subjects could efficiently maintain both cognitive task performance and walking speed. A linear mixed model analysis was conducted with FES CONDITION and TASK as fixed and SUBJECTS as random effects. The cognition rate during dual-task walking was significantly better with FES vs. without. FES showed minor effects on dorsiflexion in swing but larger effects on overall gait, as reflected in walking speed, step length and step width. While dual-task led to inferior results in gait, FES counteracted this effect and improved cognition rate. These findings suggest that FES not only addresses gait pattern and stability but also frees cognitive resources for walking. This shift in focus may enhance environmental awareness, social interaction or multitasking and thereby improving overall independence and quality of life, which is particularly relevant for patients with neurological disorders and an increased risk of falls.
A comparison between adsorption and photocatalytic degradation for the management of sulfamethoxazole in water
Abstract Sulfamethoxazole (SMX) is one of the majority of vital antibiotic medications and is widely employed for the treatment of bacterial infections. This pharmaceutical residue has been detected in surface water and sewage wastewater treatment plants (WWTP). Moreover, it has negative impacts on humans and ecosystems. The main aim of this work is to remediate water from SMX using two different water treatment techniques i.e. adsorption and photocatalytic degradation by using silver phosphate (Ag 3 PO 4 ). The materials were characterized using structural (e.g. elemental dispersive X-ray spectroscopy (EDX), Fourier-transform infrared spectroscopy (FTIR), and X-ray diffraction (XRD), and morphological (Brunauer–Emmett–Teller (BET), and scanning electron microscopy (SEM)) analytical methods. The percentage of elimination of SMX at optimum solution pH, adsorbent dose, initial drug concentration and equilibrium time, was 95.15% by adsorption which corresponds to a maximum adsorption capacity (Q max ) of 1299.7 mgg −1 and the removal percentage of SMX was 98.2% according to the photocatalytic degradation. Fritz-Schlunder model is the best to describe the adsorption of SMX onto Ag 3 PO 4 . Ag 3 PO 4 can be efficiently recycled as an adsorbent using distilled water up to 4 cycles followed by ethanol 70% and turmeric extract. For the recycling of Ag 3 PO 4 as a photocatalyst, 0.1 M NaOH is the best solvent followed by water, ethanol 70%.
Development of paper based colorimetric method using pigment from red dragon fruit for determination of Cu and Fe
Abstract Betalain, a natural pigment found in red dragon fruit, has been proposed as a natural reagent for metal detection. In the present study, this pigment was extracted and used as a colorimetric reagent for Cu and Fe on a paper-based analytical device (PAD) and then applied to water samples. The extract was stable at 5 ± 3 °C for 16 weeks. In a solution with a pH of 4–5, the betalain extract changed color from pink to light orange (Cu) and yellow (Fe) and was selective against Na, K, Ca, Ba, Al, Mg, Zn, Hg, Ni, and Pb. The color change was caused by a metal–betalain complex with an estimated ratio of 1:2 (Cu–betalain) and 1:9 (Fe–betalain). Betalain PAD was produced under optimal conditions using Whatman CF1 paper containing 20 µL of 100 mg/mL betalain extract at pH 4–5. This process resulted in a limit of quantification of 3.133 mg/L (Cu) and 4.736 mg/L (Fe) and a limit of detection of 1.034 mg/L (Cu) and 1.563 mg/L (Fe). Based on these findings, betalain PAD made from red dragon fruit could be a viable alternative for the on-site detection of Cu and Fe in water. Ultimately, betalain PAD is a toxic waste-free, portable, fast, and prospective on-site tool for metal detection.
Dual-enzyme activated theranostic nanoparticles for image-guided glioblastoma therapy
Impact of economic growth patterns on carbon quota allocation by industry in China: extensive or intensive
Innovative approach in the treatment of comminuted proximal phalanx fractures in horses based on biomechanical modelling
Abstract Proximal phalanx (P1) fractures in horses are relatively common, and present significant treatment challenges, especially when the fractures are comminuted or infected. An innovative treatment approach includes attaching an external fixator to the third metacarpal bone (MC III), the healthy bone above fracture, to offload the injured P1 and protect it from load–bearing forces, particularly during post–surgical standing up. This study aims to develop the favourable mathematical and numerical models for screws configuration in this external fixator. Nine configurations (I-IX), varying in screw alignment and number, were investigated based on the experimental data from computed tomography and simulations of compression tests. Cortical and trabecular tissues were modelled as a nonlinear viscoelastic continuum, with material constants identified through uniaxial compression and stress relaxation tests. The best attachment of the external fixator was analysed in terms of stresses and strains in both trabecular and cortical bone, as well as stresses in screws. Configuration II (1 diaphysis screw, 4 distal metaphysis screws at 7°) and III (1 diaphysis screw, 4 distal metaphysis screws at 14°) were identified as mostly biomechanically favourable. This external stabilization approach could potentially reduce the rate of post–surgical failure often leading to horse euthanasia.