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Function approximation is an important task in many different fields like economics, engineering, computing, classification, and forecasting. From a finite data set, the basic task of a function approximation method is to find a suitable relationship between variables and their corresponding responses. In the recent past, the improved neural networks including intuitive, interpretable correlated-contours fuzzy rules for classification tasks were proposed. However, the acquired data set can contain large volume of data and noise that degrades the classification ability of the model and increases the computational time. Thus, it is important to consider this problem which was not focused on recent existing works. Furthermore, there are also some neuron regularization issues in the second layer. To solve this issue in this proposed system Bat optimization based feature selection is proposed for optimal selection of features from the available dataset. Then classification is done by using enhanced neural network including intuitive and interpretable correlated-contours fuzzy rules (EC-FR). According to fuzzy rules extraction, an appropriate framework is built-in which similarity-based directional component of data partitioning and also a model to form cloud data is presented. Neurons weight and bias values are computed by adapting wavelet functions. Finally, parameters of the fuzzy neural networks are fine-tuned using the hybrid ant colony particle swarm optimization (HASO). Performance is evaluated primarily in accordance with the subsequent metrics like precision, recall, accuracy, and error rate.

Utilizing eggshells to synthesize a value added product like nanocrystalline hydroxyapatite (HA) has received a lot of attention from researchers since they are composed of CaCO3 with biologically essential trace elements such as Mg, Si, etc. Different biomedical applications need HA with appropriate nanoscale characteristics like crystallinity, particle size, morphology, surface area, mesoporous nature, etc. The same can be achieved by tuning the reaction parameters, choosing a suitable mode of preparation and utilizing organic modifiers. Here, we report the rapid synthesis of eggshell derived HA in the presence different organic modifiers using a custom built microwave reactor employing the previously optimized parameters. The synthesis process is relatively rapid and gets completed in 5 min. The absence of an organic modifier yielded inhomogeneous size nanorods in the range of 40 – 600 nm. Ethylenediaminetetraacetic acid (EDTA) assisted synthesis resulted in a flower like 1.67 ± 0.12 μm sized HA. Whereas polyethylene glycol 6000 (PEG) and cetyltrimethylammonium bromide (CTAB) assisted synthesis produced aggregated nanorods of length 31 ± 8 and 68 ± 20 nm, respectively. While the synthesis with trisodium citrate dihydrate (TSC) resulted in needles of HA with typical length of 32 ± 8 nm. Presence of Na, Mg and Si trace elements are confirmed from the composition analysis. All the samples are found to be mesoporous in nature. The in vitro cell culture experiment carried out using fibroblast NIH 3T3 cell line clearly revealed equal or higher cell viability for the samples synthesized in presence of organic modifiers as compared to sample produced without organic modifier. Thus, from the present study we find that the synthesis of eggshell derived HA using different organic modifiers via a custom built microwave reactor can be a potential approach for the rapid preparation of precursor materials with suitable nanoscale characteristics for developing bone fillers, drug/protein delivery carriers, tissue engineering scaffolds, etc.

We developed an improved hexagonal wurtzite ZnO and ZnO/C microflowers through the facile hydrothermal technique. The obtained nanostructures were characterized using X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), Transmission electron microscopy (TEM), Energy-dispersive X-ray spectroscopy (EDX) and UV–visible diffuse reflectance spectroscopy (UV–Vis DRS). The formation of flower-like material is confirmed using SEM and TEM analysis with an average diameter of about 2 µm composed of several plate-like nanostructures. The optical analysis results show that the presence of carbon particles with ZnO structures has significantly increased the light absorption ability of nanocomposite. The photocatalytic degradation ability of prepared nanostructures was examined using methylene blue as a model pollutant. The obtained results show that the photocatalytic degradation ability of ZnO/C nanostructures is approximately two times higher than the pristine ZnO microflowers. Based on the investigation, an enhancement of the photocatalytic ability of ZnO/C nanocomposite is achieved due to the synergistic effect between carbon particles and flower-like ZnO nanostructures.

The optimization of mining vehicle rear axle weld joints is a complex procedure. The designs for low-cycle fatigue with peak loads were analyzed using computational models and rig testing. On-road ...

The effect of g-C3N4 on the structural, optical, and photocatalytic properties of ZnO microcrystals under hydrothermal conditions was investigated in this research. The addition of g-C3N4 changed not only the phase composition, but also affect the growth of ZnO crystals, changing the lattice parameter and the transformation of hexagonal cylinder-like twinned ZnO microcrystals (1–2 μm length and 0.5–1 μm diameter) to g-C3N4 amalgamated rice-like ZnO nanostructure (500 nm length and 100 diameter) with type II heterojunction. The optical bandgap was found to be 3.27 and 3.21 eV for pristine ZnO and g-C3N4@ZnO, respectively. Owing to the narrow bandgap (2.7 eV) of g-C3N4, a red shift towards the visible region in optical absorption and a substantial reduction in the optical bandgap was observed for g-C3N4@ZnO heterostructure. Besides, it is also found that g-C3N4@ZnO has significantly higher photocatalytic effect (93 %) on RhB dye degradation than pristine ZnO (70 %) and g-C3N4 (68 %), because it produce a large number of reactive species (·OH and O2•− radicals) by hold-up the recombination of charge carriers via type II heterojunction. This research may be one of the most realistic approaches to developing effective photocatalysts for environmental remediation.

In this study, we synthesized the visible-light-driven photocatalytic activity of CdO nanowires and g-C3N4/CdO hybrid nanostructure by the hydrothermal method. X-ray diffraction, transmission electron microscopy, X-ray photoelectron spectrometry, and UV–Vis diffuse reflectance spectroscopy studies were carried out to compare the structural, morphological, and optical properties of CdO nanowires and g-C3N4/CdO hybrid nanostructure. Also, we investigated how CdO nanowires and g-C3N4/CdO hybrid nanostructure function as photocatalysts in the photocatalytic oxidation of RhB under visible light illumination, which revealed that g-C3N4/CdO hybrid nanostructure exhibits better photocatalytic oxidation on RhB than CdO nanowires with the first-order degradation kinetics. The prepared g-C3N4/CdO hybrid nanostructure can provide hybridized conduction band or valence band, which facilitates better charge transport and reduces recombination electron-hole charge carriers leading to higher photocatalytic performance. Hence, making hybrid nanostructures such as g-C3N4/CdO can be a potential approach to develop effective photocatalysts for treating effluents discharged from textile and dyeing industries.

We report the synthesis of silver-integrated silica nanostructures using rice hulls and silver chloride through a facile thermal combustion process. The formation of mesoporous silica nanomatrix embedded with silver nanoparticles (SiO2:Ag 5 wt% and SiO2:Ag 10 wt%) was confirmed by XRD, FTIR, EDX, BET, and TEM analysis. Also, the obtained results from the above studies revealed that the concentration of silver ions significantly increases the particle size and number of silver nanoparticles formed in the silica matrix. The electrochemical performance was studied using silver-integrated silica nanostructures as a working electrode in KOH electrolyte. The maximum specific capacitance of SiO2:Ag 5 wt%- and SiO2:Ag 10 wt%-coated electrode was found to be 517 and 580 F/g at current density of 1 A/g. It was also found that SiO2:Ag 10 wt% electrode exhibit an excellent stability with the capacitance retention of 94% than SiO2:Ag 5 wt% (capacitance retention of 85%) after 1000 cycles at a current density of 1 A/g. These results may be attributed to the inherent characteristic of more silver nanoparticles present in the silica nanomatrix in SiO2:Ag 10 wt%. The intrinsic characteristic of rice hull-derived silica nanostructures such as high surface area and mesoporous structure along with the advantage of silver nanoparticles (conductivity) can facilitate the Faradic redox processes at electrode surface which are responsible for the supercapacitive behavior of the prepared silver-integrated silica nanostructures.

Nonlinearity is a major constraint in analysing and controlling power systems. The behaviour of the nonlinear systems will vary drastically with changing operating conditions. Hence a detailed study of the response of the power system with nonlinearities is necessary especially at frequencies closer to natural resonant frequencies of machines where the system may jump into the chaos. This paper attempt such a study of a single machine to infinite bus power system by modelling it as a Duffing equation with softening spring. Using the method of multiple scales, an approximate analytical expression which describes the variation of load angle is derived. The phase portraits generated from the slow flow equations, closer to the jump, display two stable equilibria (centers) and an unstable fixed point (saddle). From the analysis, it is observed that even for a combination of parameters for which the system exhibits jump resonance, the system will remain stable if the variation of load angle is within a bounded region.

Mandible is the only mobile facial jaw bone and it aides in various functions such as phonation and mastication. Therefore, management of mandible fracture becomes inevitable due to its functional and anatomical importance. Fracture fixation methods and techniques have steadily evolved with various osteosynthesis systems. In this article, we discuss the management of mandible fracture using a newly designed two-dimensional (2D) hybrid V-shaped plate. In this paper, we have evaluated the efficacy of the newly developed 2D V-shaped locking plate in the management of mandibular fractures. We have assessed 12 cases of different mandibular fractures ranging from symphysis, parasymphysis, angle and subcondylar region. Treatment outcome was assessed both clinically and radiologically at regular intervals with various intraoperative and postoperative parameters. Results of this study suggest that fixation of mandible fracture with the 2D hybrid V-shaped plate facilitates anatomic reduction and functional stability and carries a low morbidity and infection rate. The 2D anatomic hybrid V-shaped plate can be a suitable alternative to conventional miniplate and 3D plates as it offers satisfactory anatomic reduction and functional stability. Positioning the plate in relation to the mental nerve and plate adaptation along the angle region are much easier.

The objective of this study is to analyse the movement of nitrates and dissolved oxygen under the effect of denitrification in a fracture–matrix (F–M) system with skin formation. An implicit finite difference scheme is developed to model the coupled nonlinear partial differential equations. A varying grid is considered at the fracture–skin interface to handle the mass transfer from the fracture to the skin. Bacterial growth is taken into account in the fracture. The growth is affected by the presence of electron donor and electron acceptor. Sensitivity analysis is performed for various fluid flow velocities, skin diffusion coefficients, facture dispersion coefficients, skin porosities (S-P), fracture apertures and rock–matrix (R–M) porosities. Outcomes of this study indicate that the occurrence of skin enriches the transport of nitrates as compared to the absence of skin when denitrification process exists in the system. The low fluid velocity (0.5 m/day) reduces the transport of nitrates to a distance of 5 m, whereas a high fluid velocity (5.0 m/day) triggers up to a distance of 30 m from the fracture inlet. The higher skin diffusion coefficient enhances the migration of nitrates and dissolved oxygen compared to the lower skin diffusion coefficients. The fracture aperture variation from 100 to 500 μm increases the movement of nitrates and dissolved oxygen in fracture from 4 to 10 m, respectively. The variation of S-P from 25 to 75% also follows the same trend. Variation in R–M porosity has an insignificant effect on the movement of nitrates and dissolved oxygen.

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The novel Coronavirus (COVID-19) pandemic has become a real challenge for healthcare providers around the world. Recently, it has been recorded that among all the health care professionals dentists, dental assistants, and dental hygienists are at high risk as they are in close contact with patients and are exposed to body fluids of patients. To assess the knowledge and create awareness of changes in the practice of emergency and non – emergency dental procedures during COVID-19 among dental interns. A cross-sectional study was conducted among 100dental interns. As the study was conducted during the pandemic time, a web-based survey was created using google form which composed of a set of 12 structured custom- made questions. The answers were collected and subjected to statistics.It was seen that more than 80% of the dental interns were aware of the guidelines issued by various dental associations regarding changes in dental procedures during COVID-19 pandemic situation. Most of the students were also aware of the term ‘Tele dentistry’ and telecommunications for dental care, consultation and education. Adaptations and adjustments in the dental procedures need to be done to avoid the spread of the disease. Hence, it is important and mandatory for dental professionals and students to be aware of the precautions to be taken when performing emergency as well as non-emergency procedures during this pandemic situation.

The high demand for synthetic hydroxyapatite for biomedical applications is on the rise day by day at the same time, there is a pressing need for producing hydroxyapatite (HA) at an economically viable cost to make the treatment affordable to everyone. In order to meet this objective, recycling of waste to value added products and cost effective methods suitable for scaling up the process are being attempted by researchers. In this report, an attempt has been made to optimize the parameters for the synthesis of nano HA from eggshell biowaste using well explored microwave method by employing a lab scale and pilot scale microwave reactors. Several parameters such as pH, organic modifier concentration and microwave power against volume of the reaction mixture has been studied from the view point of enhancing the yield of the product. The preliminary experiments done using lab scale reactor helped the optimization of pH and EDTA concentration. From the lab scale experiments, we found that the yield was directly proportional to the microwave power. The parameters optimized in the lab scale has been carried over to the pilot scale reactor. The results from pilot scale reactor revealed that although the microwave power from pilot scale reactor is considerably higher than that of the maximum power (900 W) of the lab scale reactor there is no significant difference in the yield of the product but the microwave irradiation time has reduced considerably which is almost in proportion to the power of the reactor. Parameters optimized from these batch processes will be useful for devising new scaling up process such as continuous flow methods.

Certain materials that are used in industries to manufacture parts, components and sub-assemblies are difficult to machine using traditional machining processes. Abrasive water jet machining is a viable solution to such a problem, and its use is sought where precision is the requirement. The process involves many input controllable parameters that influence the performance characteristics of the process such as MRR, surface finish and kerf width. Inconel-625 is one such hard-to-machine material that finds many applications in industries. The objective of the present work is set to ascertain experimentally the influence of three input parameters on the three responses mentioned above through ANOVA. WASPAS and MOORA are two powerful techniques that are used for multi-objective optimization, and the ranks of both the MCDM methods were observed to be same. Traverse speed and abrasive mass flow rate are proven to be statistically significant on MRR and surface finish, whereas standoff distance along with the above two parameters is also significant on the response kerf width. Machined surface morphology is studied using scanning electron microscopy. From the SEM morphology, it was confirmed that the higher abrasive flow rate obtained rough surface finish.

Silica nanoparticles have received great interest in biomedicine due to their high biocompatibility. In this study, we report the preparation of rare-earth ions integrated silica nanoparticles using rice husk biomass through a rapid and simple microwave-assisted combustion technique for making cost-effective bioimaging contrast agents. X-ray diffraction, energy-dispersive X-ray spectroscopy, and transmission electron microscope studies indicated that rare earth (europium/gadolinium) ions were strongly integrated with silica matrix via electrostatic interaction with environmental oxygen atoms. Europium-integrated silica nanoparticles showed a strong red fluorescence imaging capability that was attributed to 5D0→7F1 and 5D0→7F2 transitions of europium ions in the silica host matrix whereas gadolinium-integrated silica nanoparticles showed paramagnetism with T1-weighted magnetic resonance (MR) imaging capability that was ascribed to magnetic moment originated from a spin-orbit coupling of partially filled 4f electrons of gadolinium in the silica host matrix. In vivo toxicity evaluation using zebrafish embryos indicated that the rare-earth ions integrated silica nanoparticles are non-toxic. In view of these results, the prepared rare-earth ions integrated silica nanoparticles may be considered as potential materials in developing new bioimaging contrast agents at low cost.

In this study, a combination of “Cordia Dichotoma” natural fiber and “granite powder” as filler has been reinforced into epoxy resin making a hybrid composite. In this study, unused industrial wast...

Understanding the heat transfer mechanism in the subsurface is essential for designing geothermal heat extraction system as well as oil extraction system in petroleum reservoirs. Due to the inherent variability in thermal diffusivity in the rock matrix–fracture system, this interface can either act as a source or sink for temperature. The main objective of this study is to investigate the influence of considering the heat transfer term either as a source or a sink at the fissure–matrix interface while describing the spatial and temporal distribution of temperature in a fractured reservoir at the scale of a single fissure. A numerical model is developed using implicit finite difference method to forecast the spatial and temporal propagation of the thermal front and to analyse the sensitivity of various coupling terms at the fissure–matrix interface. Following the numerical treatment, the velocity of thermal front as well as the degree of thermal dispersion encountered within the high-permeable fissure was computed using the method of spatial moments (first and second, respectively). Numerical results indicate that the mobile fluids within the fissure could reflect the exchange of stored heat energy from the rock-matrix quite efficiently for the cases with the heat gain term in the fissure equation. An enhanced mixing effect was observed for the cases having an explicit heat loss term for the matrix in the absence of any source/sink in the fissure equation. However, the thermal mixing regime remained insignificant for the cases having an explicit heat gain term in the fissure.

Classification generally assigns objects to enormous predefined categories and it is pervasive crisis that covers various application. Preparing the data for Classification and Prediction is the major problem in classification. In order to rectify this issue, an approximate function is proposed using Interpretable intuitive and Correlated-contours Fuzzy Neural Network (IC-FNN). For acquiring cor- related fuzzy rules and non-separable rules that comes under proper optimization problem. The extracted fuzzy rule’s parameter was fine-tuned sourced on hierarchical Levenberg Marquardt (LM) learning method for enhancing performance. But here parameters of fuzzy rules aren’t tuned per- fectly. Hybridization of Ant Colony Optimization Genetic Algorithm (HACOGA) is proposed here to rectify these issues. It tunes the parameters of the extracted fuzzy rules. Hybridization is enforced to certain factors and ACO and GA variables that share same characteristics in the computation. Experimental results shows that proposed HACOGA assist in enhancing the performance of FNN with recall, precision, accuracy and F -measure for the Abalone age prediction dataset.

Rate of Penetration (ROP) is one of the important factors influencing the drilling efficiency. Since cost recovery is an important bottom line in the drilling industry, optimizing ROP is essential to minimize the drilling operational cost and capital cost. Traditional the empirical models are not adaptive to new lithology changes and hence the predictive accuracy is low and subjective. With advancement in big data technologies, real- time data storage cost is lowered, and the availability of real-time data is enhanced. In this study, it is shown that optimization methods together with data models has immense potential in predicting ROP based on real time measurements on the rig. A machine learning based data model is developed by utilizing the offset vertical wells’ real time operational parameters while drilling. Data pre-processing methods and feature engineering methods modify the raw data into a processed data so that the model learns effectively from the inputs. A multi – layer back propagation neural network is developed, cross-validated and compared with field measurements and empirical models.

Discrete groundwater level datasets are interpolated often using kriging group of models to produce a spatially continuous groundwater level map. There is always some level of uncertainty associated with different interpolation methods. Therefore, we developed a new trend function with the mean groundwater level as a drift variable in the regression kriging approach to predict the groundwater levels at the unvisited locations. Groundwater level data for 29 observation wells in Adyar River Basin were used to assess the performance of the developed regression kriging models. The cross-validation results shows that the proposed regression kriging method in the spatial domain outperforms other physical and kriging-based methods with R2 values of 0.96 and 0.98 during pre-monsoon and post-monsoon seasons, respectively.

Studies on mass transfer and transport of dissolved contaminants through heterogeneous hydrogeology rely on realistic expressions of their functional parameters. Hydrodynamic dispersion is one such parameter inheriting significant ambiguities in its estimation when subjected to heterogeneous flow conditions. In this study, a numerical model has been developed to explicitly evaluate the variability of dispersion coefficient on time-based and space-based scales for simulating contaminant transport mechanism in saturated porous media under nonlinear sorption mass transfer. Four types of inlet (solute source) conditions, viz., constant continuous, pulsating, exponentially decaying and sinusoidal varying were considered, and the resulting concentration profiles were compared. The governing partial differential equations were solved using an implicit finite difference technique. The results from sensitivity analysis suggest that the magnitude of the fluid velocity was influenced by the type of dispersion coefficient for different inlet boundary conditions. However, sorption partition coefficients and porosities were generally insensitive to the nature of dispersion under these boundary conditions. When time-dependent dispersion coefficient was adopted, an asymptotic increase in retained solute mass was observed for increased fluid velocity irrespective of the boundary conditions. The behavior of the concentration profile obtained using distance-dependent dispersion coefficient was unique when sinusoidal decaying solute boundary condition was used. The study rightly emphasizes the need for simultaneously updating mass transfer and transport parameters while accounting for the variation in solute inlet conditions.

Supercapacitors are emerged as leading energy storage device and developing new electrode materials for supercapacitors has received much scientific interest from the researchers. In this study, we have synthesized tin oxide-decorated amorphous silica (SnO2@RH-SiO2) nanostructures using rice husk template as a silica source via simple microwave combustion method for supercapacitor applications. XRD, FT-IR, and EDX studies obviously characterize that silica is present in amorphous form along with crystalline SnO2 having a rutile tetragonal structure in the prepared SnO2@RH-SiO2 sample. Further, TEM observation indicates that prepared sample is consisting of amorphous silica nanospheres decorated with agglomerated tin oxide nanoparticles having size of 5–10 nm. Cyclic voltammetry and galvanostatic charge/discharge studies characterize the supercapacitive behavior of working electrode fabricated from prepared SnO2@RH-SiO2 nanostructure. The specific capacitances of SnO2@RH-SiO2 nanostructure are about 448, 330, 275, 240, 225, and 200 F/g with the current density value of 1, 2, 4, 6, 8, and 10 A/g, respectively. The presence SnO2 species in SnO2@RH-SiO2 nanostructure can provide reactive surfaces for the adsorption/desorption charges and it facilitates the charge storage at the surface of sample. The above results suggested that the prepared SnO2@RH-SiO2 nanostructure has potential application for making electrochemical supercapacitors.

The formation of phase pure magnetically separable α-Fe

In this paper, we consider homogeneous and non-homogeneous system of first order linear fuzzy boundary value problems (SFOLBVPs) under granular differentiability. Using the concept of horizontal membership function, we introduced the notion of first order granular differentiability for n-dimensional fuzzy functions. We present granular integral and its properties. Theorems on the existence and uniqueness of solutions for homogeneous and non-homogeneous SFOLFBVPs are proved. We develop an algorithm for solution of non-homogeneous SFOLBVPs under granular differentiability. We provide some examples to illustrate the validity of the proposed algorithm.

We synthesized mesoporous SiO2 nanomatrix using rice husks as a precursor through a facile thermal combustion process. XRD, FTIR, EDX, and TEM analyses were used to validate the produced mesoporous SiO2 nanomatrix. Electrochemical measurements were used to determine the specific capacitance of mesoporous SiO2 nanomatrix, and the results showed that the specific capacitances are 216, 204, 182, 163, 152, 142, 135, 133, 124.4, 124 F/g at current densities of 0.5, 1, 2, 4, 6, 8, 10, 12, 14, and 16 A/g. The benefit of impurities, as well as the large surface area and mesoporous structure of rice husk derived SiO2 nanostructures, allow Faradaic redox reactions at the electrode surface and the resulting supercapacitive behavior. This research might lead to a low-cost technique of producing supercapacitor electrodes using rice husk-derived SiO2 as a precursor.

The present work investigates the ability of robust biochar from Gracilaria Rhodophyta red weeds collected from the deep sea waters of the Bay of Bengal, for sequential removal of silver and Brilliant Green (BG) dye from contaminated water. The impacting operating parameters viz contact time, the dosage of biochar, pH, and initial Ag+ concentration are optimized using 24 factorial central composite design (CCD)-based statistical modeling. The analysis of variance (ANOVA) projected an excellent history match of model data with experimental through high correlation coefficients. The sequential batch adsorption studies performed at a temperature of 303 K projected an uptake of 4.7 mg/g and 17.8 mg/g at the optimal operating conditions of pH 5–7 and 6, biochar dosage 1.0 and 0.5 g/100 mL, initial concentration 50 mg Ag+ ions and 100 mg BG dye per liter, and operating time 45 and 60 min, respectively, for Ag+ ions and BG dye. Further, the surface morphology, elemental compositions, functional groups, depositional, and structural characteristics of the biochar analyzed using FESEM, EDX, FTIR, BET, and XRD respectively confirmed its ability to successfully treating the contaminants. Moreover, the isothermal, thermodynamic, and kinetic analysis established the Langmuir model-based mono-layered homogeneous physisorption of Ag+ and BG dye with pseudo-second-order depositional characteristics at the solid-solution interface. The biochar is regenerative enough and could remove substantial amounts of Ag+ and BG dye from industrial contaminated water bodies. Moreover, the present work aids in promoting seaweed harvesting as an alternate occupation for littoral fisher societies.

We report the synthesis of hydroxyapatite (HAp)-based antibacterial biomaterials using a mussel shell as a calcium source and by the integration of silver ions via a wet precipitation method. The silver doping at 2 mol% can provide silver-doped carbonated HAp while at 10 mol% can offer silver-doped carbonated HAp/silver oxide nanocomposite. The synthesized Ag-integrated samples exhibit the H (263–903Mpa) and E (0.96–3.31GPa) almost similar to cancellous bone with good antibacterial inhibition on S. aureus (15 ± 02 mm) and E. coli (26 ± 02 mm) growth. Hence, they can be a potential precursor to make bone fillers for the treatment of bone infections.

As the number of COVID-19 cases increases day by day, the situation and livelihood of people throughout the world deteriorates. The goal of this study is to use machine learning models to identify disease and forecast whether or not a person is infected with the virus or another common illness. More articles about COVID-19 will be released starting in 2020, but we still do not have a reliable prediction mechanism to diagnose the disease with 100% accuracy. This comparison is done to see which model is the most effective in detecting and predicting disease. Despite the fact that we have immunizations, we require a best-prediction strategy to assist all humans in surviving. Researchers claimed that the supervised learning method predicts more accurately than the unsupervised learning method in the majority of studies. Supervised learning is the process of mapping inputs to derived outputs using a set of variables and created functions. This will also help us to optimize performance criteria using experience. It is further divided into two categories: classification and regression. According to recent studies, classification models are more accurate than other models.

The present study involved feeding of tender coconut water concentrate (TCW) and testa phenolic concentrate (PHE) to high fat fed animals. Analysis of serum showed increased HDL-C in concentrates treated group and therefore higher protection against atherogenesis compared to high fat fed group. Lesser fecal fat content and higher level of liver cholesterol were observed in high fat fed group, treatments with TCW and PHE ameliorated significantly. Fat content in the organs (liver, heart, kidney and adipose) of HFD group was high. Furthermore, certain fatty acids observed in the tissues were 14:0, 16:0, 18:0, 18:1, 18:2, 20:0, 20:3 and 20:4, among which 14:0, 16:0 & 18:0 are the major saturated fatty acids that increased significantly in high fat fed group when compared with starch fed group and ameliorated with TCW and PHE dose dependently. These results clearly indicate both the concentrates (TCW and PHE) restrict excess accumulation of lipids and altered composition of fatty acids in tissues as well as serum which are the risk factors for development of insulin resistance, hyperlipidemia, dyslipidemia etc., related to obesity. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13197-021-05178-2.