CNN and Rf based Early Detection of Brain Stroke Using Bio-Electrical Signals

The brain is a vital component of the body that is in control of involuntary and voluntary movements such as walking,   memory, and vision. Nowadays, some of the most prevalent brain disorders include Alzheimer's disease, brain tumors, and epilepsy (paralysis or stroke).  As a result, stroke has become a significant global health concern, with high rates of mortality and disability. Importantly, approximately two-thirds of all strokes occur in developing countries, highlighting the significant burden of this condition in these regions. Therefore, emphasizing the timely detection and appropriate treatment of brain tumors is crucial. Given the high potential for mortality or severe disability associated with stroke disease, prioritizing active primary prevention and early identification of prognostic symptoms is of paramount importance. Ischemic stroke and hemorrhagic stroke are the two primary classifications for stroke diseases. Each type calls for specific emergency treatments, such as the administration of thrombolytics or coagulants, tailored to their respective underlying mechanisms. However, to effectively manage stroke, it is crucial to promptly identify the precursor symptoms in real-time, as they can vary among individuals. Timely professional treatment within the appropriate treatment window is essential and should be provided by a medical institution. In contrast, prior research has primarily centered around the formulation of acute treatment strategies or clinical guidelines subsequent to the occurrence of a stroke, rather than giving sufficient attention to the early identification of prognostic symptoms. Specifically, recent research has extensively utilized image analysis techniques, such as computed tomography (CT) or magnetic resonance imaging (MRI), as a primary approach for detecting and predicting prognostic symptoms in stroke patients. Traditional methodologies not only encounter difficulties in achieving early real-time diagnosis but also exhibit limitations in terms of prolonged testing duration and high testing costs. In this study, we introduce a novel system that employs machine learning techniques to predict and semantically interpret prognostic symptoms of stroke. Our approach utilizes real-time measurement of multi-modal bio-signals, namely electrocardiogram (ECG) and photoplethysmography (PPG), with a specific focus on the elderly population. To facilitate real-time prediction of stroke disease during walking, we have developed a stroke disease prediction system that incorporates a hybrid ensemble architecture. This architecture synergistically combines Convolutional Neural Network (CNN) and Random Forest (RF) models, enabling accurate and timely prognostication of stroke disease. The suggested method prioritises the convenience of use of bio-signal sensors for the elderly by collecting bio-signals from three electrodes placed on the index finger. These signals include ECG and PPG, and they are obtained while the participants walk. The CNN-RF model delivers satisfactory prediction accuracy when using raw ECG and PPG data. F1-Score, Sensitivity, Specificity, and Accuracy were the performance parameters used to evaluated the model's performance

Evaluation of Trace Metal Content by ICP-MS Using Closed Vessel Microwave Digestion in Fresh Water Fish

The objective of the present study was to investigate trace metal levels of different varieties of fresh water fish using Inductively Coupled Plasma Mass Spectrophotometer after microwave digestion (MD-ICPMS). Fish samples were collected from the outlets of twin cities of Hyderabad and Secunderabad. The trace metal content in different varieties of analyzed fish were ranged from 0.24 to 1.68 mg/kg for Chromium in Cyprinus carpio and Masto symbollon, 0.20 to 7.52 mg/kg for Manganese in Labeo rohita and Masto symbollon, 0.006 to 0.07 mg/kg for Cobalt in Rastrelliger kanagurta and Pampus argenteus, 0.31 to 2.24 mg/kg for Copper in Labeo rohita and Penaeus monodon, 3.25 to 14.56 mg/kg for Zinc in Cyprinus carpio and Macrobrachium rosenbergii, and 0.01 to 2.05 mg/kg for Selenium in Rastrelliger kanagurta and Pampus argenteus, respectively. Proximate composition data for the different fishes were also tabulated. Since the available data for different trace elements for fish is scanty, here an effort is made to present a precise data for the same as estimated on ICP-MS. Results were in accordance with recommended daily intake allowance by WHO/FAO

Evaluation of trace metal content by ICP-MS using closed vessel microwave digestion in freshwater fish

The objective of the present study was to investigate trace metal levels of different varieties of fresh water fish using Inductively Coupled Plasma Mass Spectrophotometer after microwave digestion (MD-ICPMS). Fish samples were collected from the outlets of twin cities of Hyderabad and Secunderabad. The trace metal content in different varieties of analyzed fish were ranged from 0.24 to 1.68 mg/kg for Chromium in Cyprinus carpio and Masto symbollon, 0.20 to 7.52 mg/kg for Manganese in Labeo rohita and Masto symbollon, 0.006 to 0.07 mg/kg for Cobalt in Rastrelliger kanagurta and Pampus argenteus, 0.31 to 2.24 mg/kg for Copper in Labeo rohita and Penaeus monodon, 3.25 to 14.56 mg/kg for Zinc in Cyprinus carpio and Macrobrachium rosenbergii, and 0.01 to 2.05 mg/kg for Selenium in Rastrelliger kanagurta and Pampus argenteus, respectively. Proximate composition data for the different fishes were also tabulated. Since the available data for different trace elements for fish is scanty, here an effort is made to present a precise data for the same as estimated on ICP-MS. Results were in accordance with recommended daily intake allowance by WHO/FAO

Data S1: Raw data compilation

N-Acetyl-p-Aminophenol (APAP), also known as acetaminophen, is the most commonly used over-the counter analgesic and antipyretic medication. However, its overdose leads to both liver and kidney damage. APAP-induced toxicity is considered as one of the primary causes of acute liver failure; numerous scientific reports have focused majorly on APAP hepatotoxicity. Alternatively, not many works approach APAP nephrotoxicity focusing on both its mechanisms of action and therapeutic exploration. Moringa oleifera (MO) is pervasive in nature, is reported to possess a surplus amount of nutrients, and is enriched with several bioactive candidates including trace elements that act as curatives for various clinical conditions. In this study, we evaluated the nephro-protective potential of MO leaf extract against APAP nephrotoxicity in male Balb/c mice. A single-dose acute oral toxicity design was implemented in this study. Group 2, 3, 4 and 5 received a toxic dose of APAP (400 mg/kg of bw, i.p) and after an hour, these groups were administered with saline (10 mL/kg), silymarin—positive control (100 mg/kg of bw, i.p), MO leaf extract (100 mg/kg of bw, i.p), and MO leaf extract (200 mg/kg bw, i.p) respectively. Group 1 was administered saline (10 mL/kg) during both the sessions. APAP-treated mice exhibited a significant elevation of serum creatinine, blood urea nitrogen, sodium, potassium and chloride levels. A remarkable depletion of antioxidant enzymes such as SOD, CAT and GSH-Px with elevated MDA levels has been observed in APAP treated kidney tissues. They also exhibited a significant rise in pro-inflammatory cytokines (TNF-α, IL-1β, IL-6) and decreased anti-inflammatory (IL-10) cytokine level in the kidney tissues. Disorganized glomerulus and dilated tubules with inflammatory cell infiltration were clearly observed in the histology of APAP treated mice kidneys. All these pathological changes were reversed in a dose-dependent manner after MO leaf extract treatment. Therefore, MO leaf extract has demonstrated some therapeutic effectiveness against APAP-induced nephrotoxicity through enhancement of the endogenous antioxidant system and a modulatory effect on specific inflammatory cytokines in kidney tissues

Dynamic Behaviour of Buildings Resting on Sloppy Ground

The proper collection of seismic design forces for the architecture needs the specification of the exacted intensity of ground shaking that the structure will undergo throughout their existence. In line to get anticipation of the end of life and destruction of buildings due to the ground shake, it is essential to know the components of the ground motion. The common significant dynamic components of ground motion are (PGA)peak ground acceleration, duration and frequency content. The essential standard method used by many seismic codes is to use PGA as a particular measure of ground motion intensity. Despite, as more earthquake studies obtained, it enhanced that the use of a single design spectral shape scaled by peak site acceleration is inadequate to cover over all sites. Many recorded earthquake ground motions have response spectra dramatically distinct from the standard design spectrum. The earthquakes have different predominating frequency contents inherently low, medium, and high. The present study deals with the effect of the different dominating frequency contents of earthquakes on seismic behavior of R.C buildings resting on the sloppy ground.A linear time history analysis performed by using the relevant Finite Element Method (FEM) based software SAP2000 on sloppy ground buildings with three different ground motions of low, medium and high contents of the frequency with the same continuation and peak ground acceleration. The dynamic response of the R.C frame buildings due to the selected ground motions observed regarding storey displacement and base shear. It is found that low and intermediate frequency content ground motions had shown an essential impact on the seismic response of chosen R.C regular building frames and step-back building frames. Proceeding to the chosenR.C step back-setback building frames the medium and high-frequency content ground motions shown an essential impact on its seismic response. It is also observed that the end short columns in these buildings attract more-base shear compared to other columns. The base shear distribution among the columns is uneven this uneven distribution of base shear in columns leads to plastic hinge formation in the columns, which creates the profound impact in step-back and step-back–setback buildings

Preparation, surface functionalization, and characterization of carbon micro fibers for adsorption applications

In this study, the phenolic resin and viscose rayon precursor-based activated carbon fibers (ACFs) were prepared by carbonization and steam-activation. Prepared ACFs were surface-functionalized by hydrogen peroxide and applied as adsorbents in environmental remediation applications. Carbonization and activation conditions (temperature, time, and heating rate) were varied to prepare ACFs of different specific surface area and pore size distribution. At the activation temperature of 900°C, the specific surface area was found to be maximum (∼1,700 m2/g for the phenolic resin precursor- and ∼2,300 m2/g for the viscose rayon precursor-based ACFs). However, former precursor-based ACFs contained mostly micropores, whereas the latter contained both micropores and mesopores. Adsorption of methylene blue, the reagent used as a test adsorbate molecule, was found to be dependent on the surface area, pore volume, and pore size distribution of the prepared ACFs, and also on the surface oxygen functional groups incorporated therein. These surface characteristics were found to be controlled by carbonization and activation conditions. Rayon precursor-based ACFs were found to be superior to the phenolic resin-based ACFs for adsorbing methylene blue from aqueous solution, with ∼646 mg/g of the equilibrium ions loading observed in the former, in comparison to ∼540 mg/g in the latter

Assessment of metal levels and pollution indices of the Songor Wetland, Ghana

Sediment, soil and fish samples collected from the Songor Wetland were assessed for the spatial distributions of metal (Al, Fe, Zn, Cr, Ni, Cu, Pb, As, Cd and Hg) levels and contamination loads, using pollution indices and multivariate analysis. The samples were processed through microwave digestions (Soil and Sediment: [HNO3, HCl, HF, H2O2]; Fish: [HNO3, H2O2]), followed by the analysis of extracts using ICP-MS. The results displayed patchiness of metal levels in the sediment and soil samples, and in some cases, defying the established trend that levels of metals in sediments are generally higher than in soils. The differences in the results were ascribed to geological dominance and anthropogenic impacts. The finfish species displayed relatively higher bioaccumulation patterns of the metal levels than crustaceans. Aluminium (Al) and Zn levels were moderately enriched in sediment and soil samples. Overall enrichment factors ([EF {Al} and EF {Fe}]) suggested low to minimal enrichment except in a few cases. Pollution Load Index (PLI) based on Contamination Factor (CF) suggested that metal loads were less than baseline levels. On the other hand, Pearson Correlation Coefficient demonstrated that the metals present in the wetland were more lithogenic with remarkable inputs of biogenic and anthropogenic components. Principal Component Analysis revealed an association of Zn to the western section of the wetland, Cd, and Hg to the eastern part while the remaining metals were concentrated at the mid-section of the wetland. Lead (Pb) levels (1.10 ± 0.70 mg/kg) in finfishes exceeded the EU Regulation 1881/2006/EU (0.05 mg/kg) for fish tissues and could pose public health concerns