Unveiling the potential of aluminum-decorated 3D phosphorus graphdiyne as a catalyst for N2O reduction.

Interest in single-atom catalysts (SACs) has surged due to their potential to mitigate greenhouse N2O gas from the environment. In this study, we explore the potential of N2O reduction using porous 3D phosphorus graphdiyne decorated with an Al atom (3D-Al/PGDYN) through density functional theory. Results confirm the energetic stability of Al decorations on 3D-PGDYN and indicate that the Al atom plays an active role in catalysis. The N2O molecule undergoes spontaneous dissociation on the surface of the 3D-Al/PGDYN, initiating from the O-end, with a dissociation energy of -2.93 eV. In parallel, N2O dissociation through the N-end involves chemisorption onto the 3D-Al/PGDYN surface, with an adsorption energy (Ead) of -1.74 eV. The negative Ead values (-2.47 and -2.64 eV) indicate that CO and O2 species chemisorb onto the 3D-Al/PGDYN surface, but these energies are lower than that of N2O, suggesting that CO and O2 molecules do not hinder the N2O reduction process. Furthermore, the reaction CO + O* → CO2, which is vital for catalyst regeneration, proceeds swiftly on the 3D-Al/PGDYN catalyst with a low energy barrier of 0.11 eV, highlighting the catalyst's exceptional reactivity. This work holds significance in the design of catalysts and could be instrumental in developing new and efficient solutions for effectively removing harmful N2O from the environment.

A bromide substituted 2D additive for stable and efficient perovskite photovoltaics.

In this article, a bromide substituted 2D layered perovskite having a repeated vertical orientation and coexisting with the bulk of a 3D perovskite is reported for the first time. This novel structure is obtained through controlled compositional engineering of the perovskite precursor solution. The photovoltaic performance of this novel 2D/3D perovskite was higher than that of 3D MAPbI3 and a maximum photoconversion efficiency (PCE) of 17.4% was achieved. The devices fabricated using this perovskite heterostructure were stable and retained their initial PCE up to 20 days when kept open in a laboratory environment with 40% relative humidity.

Spatial spillover impact of determinants on child mortality in Pakistan: evidence from Spatial Durbin Model.

BACKGROUND: Child mortality is a major challenge to public health in Pakistan and other developing countries. Reduction of the child mortality rate would improve public health and enhance human well-being and prosperity. This study recognizes the spatial clusters of child mortality across districts of Pakistan and identifies the direct and spatial spillover effects of determinants on the Child Mortality Rate (CMR). METHOD: Data of the multiple indicators cluster survey (MICS) conducted by the United Nations International Children's Emergency Fund (UNICEF) was used to study the CMR. We used spatial univariate autocorrelation to test the spatial dependence between contiguous districts concerning CMR. We also applied the Spatial Durbin Model (SDM) to measure the spatial spillover effects of factors on CMR. RESULTS: The study results showed 31% significant spatial association across the districts and identified a cluster of hot spots characterized by the high-high CMR in the districts of Punjab province. The empirical analysis of the SDM confirmed that the direct and spatial spillover effect of the poorest wealth quintile and MPI vulnerability on CMR is positive whereas access to postnatal care to the newly born child and improved drinking water has negatively (directly and indirectly) determined the CMR in Pakistan. CONCLUSION: The instant results concluded that spatial dependence and significant spatial spillover effects concerning CMR exist across districts. Prioritization of the hot spot districts characterized by higher CMR can significantly reduce the CMR with improvement in financial statuses of households from the poorest quintile and MPI vulnerability as well as improvement in accessibility to postnatal care services and safe drinking water.

Synthesis, molecular structure and urease inhibitory activity of novel bis-Schiff bases of benzyl phenyl ketone: A combined theoretical and experimental approach.

Background: Urease belongs to the family of amid hydrolases with two nickel atoms in their core structure. On the basis of literature survey, this research work is mainly focused on the study of bis-Schiff base derivatives of benzyl phenyl ketone nucleus. Objective: Synthesis of benzyl phenyl ketone based bis-Schiff bases in search of potent urease inhibitors. Method: In the current work, bis-Schiff bases were synthesized through two steps reaction by reacting benzyl phenyl ketone with excess of hydrazine hydrate in ethanol solvent in the first step to get the desired hydrazone. In last, different substituted aromatic aldehydes were refluxed in catalytic amount of acetic acid with the desired hydrazone to obtain bis-Schiff base derivatives in tremendous yields. Using various spectroscopic techniques including FTIR, HR-ESI-MS, and 1H NMR spectroscopy were used to clarify the structures of the created bis-Schiff base derivatives. Results: The prepared compounds were finally screened for their in-vitro urease inhibition activity. All the synthesized derivatives (3-9) showed excellent to less inhibitory activity when compared with standard thiourea (IC50 = 21.15 ± 0.32 µM). Compounds 3 (IC50 = 22.21 ± 0.42 µM), 4 (IC50 = 26.11 ± 0.22 µM) and 6 (IC50 = 28.11 ± 0.22 µM) were found the most active urease inhibitors near to standard thiourea among the synthesized series. Similarly, compound 5 having IC50 value of 34.32 ± 0.65 µM showed significant inhibitory activity against urease enzyme. Furthermore, three compounds 7, 8, and 9 exhibited less activity with IC50 values of 45.91 ± 0.14, 47.91 ± 0.14, and 48.33 ± 0.72 µM respectively. DFT used to calculate frontier molecular orbitals including; HOMO and LUMO to indicate the charge transfer from molecule to biological transfer, and MEP map to indicate the chemically reactive zone suitable for drug action. The electron localization function (ELF), non-bonding orbitals, AIM charges are also calculated. The docking study contributed to the analysis of urease protein binding.

A Scheduling Mechanism Based on Optimization Using IoT-Tasks Orchestration for Efficient Patient Health Monitoring.

Over the past years, numerous Internet of Things (IoT)-based healthcare systems have been developed to monitor patient health conditions, but these traditional systems do not adapt to constraints imposed by revolutionized IoT technology. IoT-based healthcare systems are considered mission-critical applications whose missing deadlines cause critical situations. For example, in patients with chronic diseases or other fatal diseases, a missed task could lead to fatalities. This study presents a smart patient health monitoring system (PHMS) based on an optimized scheduling mechanism using IoT-tasks orchestration architecture to monitor vital signs data of remote patients. The proposed smart PHMS consists of two core modules: a healthcare task scheduling based on optimization and optimization of healthcare services using a real-time IoT-based task orchestration architecture. First, an optimized time-constraint-aware scheduling mechanism using a real-time IoT-based task orchestration architecture is developed to generate autonomous healthcare tasks and effectively handle the deployment of emergent healthcare tasks. Second, an optimization module is developed to optimize the services of the e-Health industry based on objective functions. Furthermore, our study uses Libelium e-Health toolkit to monitors the physiological data of remote patients continuously. The experimental results reveal that an optimized scheduling mechanism reduces the tasks starvation by 14% and tasks failure by 17% compared to a conventional fair emergency first (FEF) scheduling mechanism. The performance analysis results demonstrate the effectiveness of the proposed system, and it suggests that the proposed solution can be an effective and sustainable solution towards monitoring patient's vital signs data in the IoT-based e-Health domain.

Physiological, Biochemical and Defense System Responses of Roadside Vegetation to Auto-Exhaust Pollution.

This study determined the effects of traffic pollutants on plants (Nerium oleander and Ricinus communis) growing along Faisalabad to Okara (R-1) and Okara to Lahore (R-2) roads in Pakistan. The photosynthetic pigments, photosynthetic rate, transpiration rate and total soluble proteins of roadside vegetation were significantly lower than control plants (50 m away from road). The average decrease in photosynthetic rate of Nerium oleander and Ricinus communis was 33.90% and 27.94% along R-1 and 41.85% and 32.409% along R-2 road, respectively. The decreased photosynthesis in roadside flora resulted in higher water use efficiency and substomatal CO2 concentration. However, higher antioxidant activity and free amino acid contents were noted in roadside plants that might be due to their defensive response to traffic pollutants. N. oleander was more affected by traffic pollutants and R. communis showed more resistance. Thus, N. oleander could be used for biomonitoring and R. communis for phytoremediation of vehicular pollution.

Tunable relativistic quasiparticle electronic and excitonic behavior of the FAPb(I1-xBrx)3 alloy.

We study the structural, electronic, and excitonic properties of mixed FAPb(I1-xBrx)3 0 ≤x≤ 1 alloys by first-principles density functional theory as well as quasiparticle GW and Bethe Salpeter equation (BSE) approaches with the inclusion of relativistic effects through spin orbit coupling. Our results show that the system volume decreases with increasing Br content. The quasiparticle band gaps vary from 1.47 eV for pure α-FAPbI3 to 2.20 eV for Br-rich α-FAPbBr3 and show stronger correlation with the structural changes. The optical property analysis reveals that the overall excitonic peaks are blue shifted with the Br fraction. Our results further reveal strong Br concentration dependence of the variation in the exciton binding energy (from 74 to 112 meV) and the carrier effective masses as well as the high frequency dielectric constants. These findings provide a way to tune the carrier transport properties of the material by doping, which could be utilized to improve the short circuit currents and power conversion efficiencies in multijunction solar cell devices.

Preliminary screening of rhizobacteria for biocontrol of little seed canary grass (Phalaris minor Retz.) and wild oat (Avena fatua L.) in wheat.

Conventional weed control methods often have environmental impact. The present study was conducted to screen selected accessions of Pseudomonas for both potential biocontrol of Phalaris minor and Avena fatua and potential concurrent growth promotion of wheat. The four Pseudomonas strains (B11, T19, T24, and T75) were found positive for cyanide production, siderophore production, phosphorus solubilization, oxidase activity, catalase activity, and ACC deaminase activity in vitro. These strains were phytotoxic, causing up to 73.3% mortality in the lettuce seedling bioassay. Consortia of compatible Pseudomonas strains increased A. fatua and P. minor seedling mortality up to 50.0% and 56.7%, respectively, and reduced root length up to 73.8% and 53.9%, respectively, as compared with the uninoculated control. Consortia of compatible Pseudomonas strains increased wheat shoot length, root length, fresh biomass, dry biomass, and leaf greenness up to 41.6%, 100%, 79.9%, 81.5%, and 21.1%, respectively, over the uninoculated control. Four of the 11 Pseudomonas consortia tested expressed good weed suppression and wheat growth promotion capacity and deserve further experimentation. The findings from this study may lead to the formulation of bioherbicides that will improve human and environmental health.

Synthesis and Characterization of Functionalized Nanosilica for Zinc Ion Mitigation; Experimental and Computational Investigations.

Zinc is an essential trace metal and its concentration above 4ppm reduces the aesthetic value of water. This study explores the possibility of using functionalized nanohybrids as Zn(II) ion scavengers from aqueous solution. Functionalized nanohybrids were synthesized by the attachment of thiosemicarbazide to silica. The material was characterized by TGA, SEM, FTIR, EDX, and BET analysis, which revealed ligand bonding to silica. The functionalized silica was employed as Zn(II) ion extractant in batch experiments and removed about 94.5% of the Zn(II) ions at pH 7, near zero point charge (6.5) in 30 min. Kinetics investigations revealed that zinc adsorption follows an intra particle diffusion mechanism and first-order kinetics (K = 0.1020 min-1). The data were fitted to Freundlich, Dubinin-Radushkevich, and Langmuir models and useful ion exchange parameters were determined. The impact of co-existing ions on Zn(II) ion sequestration was also studied and it was found that the adsorbent can be used for selective removal of zinc with various ions in the matrix. Quantum mechanical investigations revealed that the Zn(II) ion adsorption on ZnBS1 is more favorable, having higher binding energy (BE) (-178.1 kcal/mol) and ∆H (-169.8), and making tridentate complex with the N and S sites of the chelating ligand. The negative ∆G and BE values suggest highly spontaneous Zn(II) adsorption on the modified silica even at low temperatures.

Spatial and Temporal Heterogeneity of Metal Contaminants in Soils Along Two Major Roads.

The concentrations of zinc, copper, lead and cadmium owing to vehicles were analyzed in roadside soils during all the four seasons from Faisalabad-Gojra road (M-4) and Gojra-Jhang road (GJR) in the Punjab, Pakistan. Results indicated that all the polluted sites along the roadside had comparatively higher metal concentrations as compared to control, nevertheless, spatio-temporal variations in metal concentrations were apparent in different soil samples. The spatial differences in metal concentrations were strongly associated with vehicle density at the Gojra Interchange site and Forest Park site along M-4 and GJR roads, respectively. Among seasons, metal ions exhibited the following order: summer > autumn > spring > winter, indicating that high temperature might have released more metal ions. The metals were recorded in contaminated soil in the order of Zn > Cu > Pb > Cd along both roads. This investigation emphasizes the need for proper environmental management particularly the improvement of roads and proper checking of vehicles running on these regards.

Game Theoretic Solution for Power Management in IoT-Based Wireless Sensor Networks.

Internet of things (IoT) is a very important research area, having many applications such as smart cities, intelligent transportation system, tracing, and smart homes. The underlying technology for IoT are wireless sensor networks (WSN). The selection of cluster head (CH) is significant as a part of the WSN's optimization in the context of energy consumption. In WSNs, the nodes operate on a very limited energy source, therefore, the routing protocols designed must meet the optimal utilization of energy consumption in such networks. Evolutionary games can be designed to meet this aspect by providing an adequately efficient CH selection mechanism. In such types of mechanisms, the network nodes are considered intelligent and independent to select their own strategies. However, the existing mechanisms do not consider a combination of many possible parameters associated with the smart nodes in WSNs, such as remaining energy, selfishness, hop-level, density, and degree of connectivity. In our work, we designed an evolutionary game-based approach for CH selection, combined with some vital parameters associated with sensor nodes and the entire networks. The nodes are assumed to be smart, therefore, the aspect of being selfish is also addressed in this work. The simulation results indicate that our work performs much better than typical evolutionary game-based approaches.

Lead Concentrations in Soils and Some Wild Plant Species Along Two Busy Roads in Pakistan.

This study assessed the level of Pb in soil and five wild plant species (Calotropis procera, Datura alba, Parthenium hysterophorus, Cenchrus ciliaris and Ricinus communis) during all the four seasons. Two busy roads varying in age and traffic volume were selected i.e., Faisalabad-Sargodha road (FSR) and Pindi Bhattian to Lillah (M-2) in the Punjab, Pakistan. Results showed raised levels of Pb in both plants and soil samples along both roads. The range of Pb concentration in plants was 0.08-3.98 and 1.95-4.74 mg kg- 1 for soil. Higher Pb contamination was recorded along FSR road as compared to M-2. Among seasons, the higher Pb concentration was found during summer, probably due to very high temperature. Among all the plants studied, Calotropis procera accumulated the highest level (3.98 mg kg- 1 dry wt.) of Pb; Thus, it can be used as good biomonitor/phytoremediator at Pb contaminated areas.

Selenium (Se) improves drought tolerance in crop plants--a myth or fact?

Climate change has emerged as one of the most complex challenges of the 21st century and has become an area of interest in the past few decades. Many countries of the world have become extremely vulnerable to the impacts of climate change. The scarcity of water is a serious concern for food security of these countries and climate change has aggravated the risks of extreme events like drought. Oxidative stress, caused by a variety of active oxygen species formed under drought stress, damages many cellular constituents, such as carbohydrates, lipids, nucleic acids and proteins, which ultimately reduces plant growth, respiration and photosynthesis. Se has become an element of interest to many biologists owing to its physiological and toxicological importance. It plays a beneficial role in plants by enhancing growth, reducing damage caused by oxidative stress, enhancing chlorophyll content under light stress, stimulating senesce to produce antioxidants and improving plant tolerance to drought stress by regulating water status. Researchers have adopted different strategies to evaluate the role of selenium in plants under drought stress. Some of the relevant work available regarding the role of Se in alleviating adverse effect of drought stress is discussed in this paper.

High-risk lead removal by planned sequential transvenous laser extraction and minimally invasive right thoracotomy.

INTRODUCTION: Transvenous pacemaker or implantable cardioverter defibrillator (ICD) lead extraction via mechanical or excimer laser sheath is typically safe and effective. Longer duration from implant, presence of large vegetations or thrombi, fractured leads, and prior failed extraction are risk factors predicting higher complication rates or incomplete or failed lead removal. Techniques developed for minimally invasive valve surgery were used in conjunction with laser extraction to refine a "hybrid" technique for lead extraction. We assessed the outcomes of high-risk lead extraction using this hybrid lead extraction technique. METHODS AND RESULTS: Retrospective assessment of clinical parameters and procedural outcomes in patients undergoing planned hybrid lead extraction from February 2008 to September 2012 was performed. We report 8 cases of hybrid lead extraction performed at our institution. We extracted 21 leads with average lead age of 13.8 years since implant. All leads were removed with complete clinical and radiographic success. There were no intraprocedure complications. One patient died of continued sepsis and 1 other had symptoms consistent with pulmonary embolism. CONCLUSIONS: Hybrid lead extraction using this technique is a safe and effective approach for removal of high-risk chronic pacemaker or ICD leads. This method extends the range of approachable leads resulting in complete removal without median sternotomy. Hybrid lead extraction can be scheduled electively facilitating complete lead removal with a low complication rate and short postoperative recovery time, mitigating the risks inherent in midline sternotomy or emergent cardiac surgical rescue.

Etomidate use and postoperative outcomes among cardiac surgery patients.

BACKGROUND: Although a single dose of etomidate can cause relative adrenal insufficiency, the impact of etomidate exposure on postoperative outcomes is unknown. The objective of this study was to examine the association between a single induction dose of etomidate and clinically important postoperative outcomes after cardiac surgery. METHODS: The authors retrospectively examined the association between etomidate exposure during induction of anesthesia and postoperative outcomes in patients undergoing cardiac surgery from January 2007 to December 2009 by using multivariate logistic regression analyses and Cox proportional hazards regression analyses. Postoperative outcomes of interest were severe hypotension, mechanical ventilation hours, hospital length of stay, and in-hospital mortality. RESULTS: Sixty-two percent of 3,127 patients received etomidate. Etomidate recipients had a higher incidence of preoperative congestive heart failure (23.0 vs. 18.3%; P = 0.002) and a lower incidence of preoperative cardiogenic shock (1.3 vs. 4.0%; P < 0.001). The adjusted odds ratio for severe hypotension and in-hospital mortality associated with receiving etomidate was 0.80 (95% CI, 0.58-1.09) and 0.75 (95% CI, 0.45-1.24), respectively, and the adjusted hazard ratio for time to mechanical ventilation removal and time to hospital discharge was 1.10 (95% CI, 1.00-1.21) and 1.07 (95% CI, 0.97-1.18), respectively. Propensity score analysis did not change the association between etomidate use and postoperative outcomes. CONCLUSIONS: In this study, there was no evidence to suggest that etomidate exposure was associated with severe hypotension, longer mechanical ventilation hours, longer length of hospital stay, or in-hospital mortality. Etomidate should remain an option for induction of anesthesia in cardiac surgery patients.

Implementing goal-directed protocols reduces length of stay after cardiac surgery.

OBJECTIVE: To test the effect of a high reliability organization (HRO) intervention on patient lengths of stay in the CVICU and hospital. The authors proposed that (1) higher safety related evidence based protocol (SREBP) team compliance scores and (2) lower SREBP milestone scores are associated with shorter lengths of CVICU and hospital stay. DESIGN: A prospective, longitudinal observational evaluation was used to assess the effects of SREBP-focused rounding processes and a milestone-tracking tool. SETTING: United States, university academic medical center's 27-bed CVICU. PARTICIPANTS: Six hundred sixty-five adult cardiac surgery patients and the CVICU care team (100 registered nurses and 16 clinical providers) participated. MEASUREMENTS AND MAIN RESULTS: Team compliance was the proportion of SREBP-related team behaviors exhibited during daily rounds. Patients' milestone scores were the cumulative difference between actual and expected times for 4 SREBP milestones over 48 hours. Milestones achieved earlier than expected indicated reduced complication risk, and milestones achieved later than expected indicated increased risk. As team compliance increased, CVICU length of stay decreased 0.66 (95% CI: -0.04 to 1.28; p = 0.08) days; hospital stay decreased 0.89 times (95% CI: 0.77-1.03; p = 0.008). As the mean milestone scores increased from -7 to 12, length of ICU stay increased 2.63 (95% CI: 1.66-3.59; p<0.001) days; hospital length of stay increased 1.44 times (95% CI: 1.23-1.7; p = 0.05). CONCLUSIONS: A milestone-driven pathway supported by team rounding was associated with decreased lengths of CVICU and hospital stay. However, tracking patient trajectories by milestones suggests a more complex relationship than anticipated and presents new opportunities for SREBP implementation and research.

Efficient detection of nitric oxide a biomarker associated with COVID19 via N, P co-doped C60 fullerene: a computational study.

CONTEXT: Coronavirus (COVID-19) is a novel respiratory viral infection, causing a relatively large number of deaths especially in people who underly lung diseases such as chronic obstructive pulmonary and asthma, and humans are still suffering from the limited testing capacity. In this article, a solution is proposed for the detection of COVID-19 viral infections through the analysis of exhaled breath gasses, i.e., nitric oxide, a prominent biomarker released by respiratory epithelial, as a non-invasive and time-saving approach. Here, we designed a novel and low-cost N and P co-doped C60 fullerene-based breathalyzer for the detection of NO gas exhaled from the respiratory epithelial cells. This breathalyzer shows a quick response to the detection of NO gas by directly converting NO to NO2 without passing any energy barrier (0 kcal/mol activation energy). The recovery time of breathalyzer is very short (0.98 × 103 s), whereas it is highly selective for NO sensing in the mixture of CO2 and H2O gasses. The study provides an idea for the synthesis of low-cost (compared to previously reported Au atom decorated nanostructure and metal-based breathalyzer), efficient, and highly selective N and P co-doped C60 fullerene-based breathalyzer for COVID-19 detection. METHODS: The geometries of N and P-doped systems and gas molecules are simulated using spin-polarized density functional theory calculations.

Systematic surface bowing in 2D III-nitride monolayers.

In this article we report novel composite materials of bucky ball (C60 fullerene) and III-nitrides (BN, AlN, GaN, InN). The experimental feasibility of the novel composite materials is confirmed through negative binding energies and molecular dynamics simulations performed at 500 K. The structural properties of the novel composites are explored through density functional theory. An unusual phenomenon of surface bowing is observed in the 2D structure of the III-nitride monolayers due to the C60 sticking. This surface bowing systematically increases as one proceeds from BN → AlN → GaN → InN. The electron density difference and Hirshfeld charge density analysis show smaller charge transfer during the complexation, which is probably due to weak van der Waal's forces. The presence of van der Waal's forces is also confirmed by the Atom in Molecule analysis, Reduced Density Gradient Technique and Non-covalent Interaction analysis. This work provides a foundation for further theoretical and experimental studies of the novel phenomenon of systematic bowing in the 2D structure of III-nitride monolayers.

Fog-assisted de-duplicated data exchange in distributed edge computing networks.

The Internet of Things (IoT) generates substantial data through sensors for diverse applications, such as healthcare services. This article addresses the challenge of efficiently utilizing resources in resource-scarce IoT-enabled sensors to enhance data collection, transmission, and storage. Redundant data transmission from sensors covering overlapping areas incurs additional communication and storage costs. Existing schemes, namely Asymmetric Extremum (AE) and Rapid Asymmetric Maximum (RAM), employ fixed and variable-sized windows during chunking. However, these schemes face issues while selecting the index value to decide the variable window size, which may remain zero or very low, resulting in poor deduplication. This article resolves this issue in the proposed Controlled Cut-point Identification Algorithm (CCIA), designed to restrict the variable-sized window to a certain threshold. The index value for deciding the threshold will always be larger than the half size of the fixed window. It helps to find more duplicates, but the upper limit offset is also applied to avoid the unnecessarily large-sized window, which may cause extensive computation costs. The extensive simulations are performed by deploying Windows Communication Foundation services in the Azure cloud. The results demonstrate the superiority of CCIA in various metrics, including chunk number, average chunk size, minimum and maximum chunk number, variable chunking size, and probability of failure for cut point identification. In comparison to its competitors, RAM and AE, CCIA exhibits better performance across key parameters. Specifically, CCIA outperforms in total number of chunks (6.81%, 14.17%), average number of chunks (4.39%, 18.45%), and minimum chunk size (153%, 190%). These results highlight the effectiveness of CCIA in optimizing data transmission and storage within IoT systems, showcasing its potential for improved resource utilization and reduced operational costs.

An intelligent diabetes classification and perception framework based on ensemble and deep learning method.

Sugar in the blood can harm individuals and their vital organs, potentially leading to blindness, renal illness, as well as kidney and heart diseases. Globally, diabetic patients face an average annual mortality rate of 38%. This study employs Chi-square, mutual information, and sequential feature selection (SFS) to choose features for training multiple classifiers. These classifiers include an artificial neural network (ANN), a random forest (RF), a gradient boosting (GB) algorithm, Tab-Net, and a support vector machine (SVM). The goal is to predict the onset of diabetes at an earlier age. The classifier, developed based on the selected features, aims to enable early diagnosis of diabetes. The PIMA and early-risk diabetes datasets serve as test subjects for the developed system. The feature selection technique is then applied to focus on the most important and relevant features for model training. The experiment findings conclude that the ANN exhibited a spectacular performance in terms of accuracy on the PIMA dataset, achieving a remarkable accuracy rate of 99.35%. The second experiment, conducted on the early diabetes risk dataset using selected features, revealed that RF achieved an accuracy of 99.36%. Based on our experimental results, it can be concluded that our suggested method significantly outperformed baseline machine learning algorithms already employed for diabetes prediction on both datasets.