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Water can be sustainably and ecologically converted by electrocatalysts into hydrogen and oxygen, which, in turn, can be converted into energy. However, the advancement of using water as green energy is hampered by limitations in the study of high-performance catalysts. The purpose of this study was to construct an electrocatalyst by anchoring well-dispersed multiwalled carbon nanotubes (MWCNTs) on nickel–copper (NiCu-MOF) nanoblocks through a simple solvothermal method. The synthesis of NiCu-MOF@MWCNTs demonstrated exceptional electrocatalytic performance for the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) in an alkaline medium. At 10 mA cm–2in 1.0 M KOH, the OER and HER performance of the catalyst displays a relatively low overpotential, with only 220 and 78 mV, respectively. Furthermore, the catalytic activity remained unchanged for 24 h in 1.0 M KOH. This performance was superior to the majority of electrocatalysts that have been reported. This was achieved by utilizing the strong synergy that exists between MWCNTs and bimetallic (Ni–Cu) nano blocks present in the metal–organic framework. The enhanced electrocatalytic activity of the nanocomposite can be attributed to the synergistic impact caused by its various components.

Royal jelly is an anti-inflammatory, antioxidant, and neuroprotective bee product. There are several sources for royal jelly and one of them is Indian Royal Jelly (IRJ). However, the neuroprotective actions of IRJ and the underlying molecular mechanisms involved are not well known.

Background The prevalence of obesity is rising worldwide. Due to the side effects associated with modern drugs, there is a need for an alternative treatment for obesity management. Triphala(TP), a polyherbal formulation from Ayurveda, is used by Ayurvedic physicians for weight loss.Purpose This study was designed to evaluate the effects of TP on obesity at the biochemical, histological, and molecular levels.Materials and Methods Male Wistar rats (125–150 g, 6–7 weeks old) were fed with a high-fat diet (HFD) for total of 48 days. From day 24 to day 48, along with HFD, rats were given an aqueous extract of TP (50, 100, and 200 mg/kg/day) or atorvastatin (1.2 mg/kg/day). Biochemical parameters were estimated in serum. Histopathology was done for the liver and adipose tissue. Levels of the genes involved in lipid metabolism were determined by quantitative real-time polymerase chain reaction (qRT-PCR). Monoamine levels were estimated from the brain tissue.Results At the end of the study (day 48), compared to only HFD receiving group (DC), all TP-treated groups showed a significant decrease in body weight, serum glucose, total cholesterol, triglycerides, leptin, interleukin-6, C-reactive protein, malondialdehyde, and noradrenaline levels. High-density lipoprotein, adiponectin, superoxide dismutase, serotonin, and dopamine levels were found to be increased compared to DC rats. Expression of various genes involved in lipid metabolism was found to be down regulated only in TP 100 group compared with DC. Additionally, all TP groups showed a reduction in adipocyte size and restored monoamine levels.Conclusion The aqueous extract of TP had shown an anti-obesity effect as demonstrated by lowering inflammation and oxidative stress, adipocyte size, and modulation of expression of genes involved in lipid metabolism.

Well-performing organic–inorganic halide perovskites are susceptible to poor efficiency and instability due to their various defects at the interphases, grain boundaries (GBs), and surfaces. In this study, an in situ method is utilized for effectively passivating the under-coordinated Pb2+defects of perovskite with new non-fullerene acceptors (NFAs) (INXBCDT; X = H, Cl, and Br) through their carbonyl and cyano functional groups during the antisolvent dripping process. It reveals that the bicyclopentadithiophene (BCDT) core with highly electron-withdrawing end-capping groups passivates GBs and boosts perovskite grain growth. This effective defect passivation decreases the trap density to increase the carrier recombination lifetime of the perovskite film. As a result, bromo-substituted dicyanomethylene indanone (INBr)-end-capped BCDT (INBrBCDT-b8; 3a)-passivated devices exhibit the highest power conversion efficiency (PCE) of 22.20% (vs those of 18.09% obtained for perovskite films without passivation) upon an optimized film preparation process. Note that devices treated with more soluble 2-ethylhexyl-substituted compounds (1a, 2a, and 3a) exhibit higher PCE than those treated with less soluble octyl-substituted compounds (1b, 2b, and 3b). It is also worth noting that BCDT is a cost-effective six-ring core that is easier to synthesize with a higher yield and therefore much cheaper than those with highly fused-ring cores. In addition, a long-term stability test in a glovebox for 1500 h reveals that the perovskite solar cells (PSCs) based on a perovskite absorber treated with compound 3amaintain ∼90% of their initial PCE. This is the first example of the simplest high-conjugation additive for perovskite film to achieve a PCE greater than 22% of the corresponding lead-based PSCs.

Smart grid (SG) engages bidirectional energy and data flow with advanced metering infrastructure (AMI) and lures attackers to exploit vulnerabilities in the critical infrastructure. Of the existing cyber threats, one of the major attacks is a man-in-the-middle (MITM) attack which eavesdrops and interrupts the communication between smart meter (SM) and data concentrator (DC) thereby paving the way for other cyber threats. Though many research works dealt with the solution to this attack, the majority of them are either simulation based or not intended for AMI. Hence, the proposal aims to develop a robust machine learning (ML) based intrusion detection system (IDS) to detect the attack in the real-time infrastructure. To attain this, AMI is setup using lamp loads, resistive loads, sensors, AtMega controller, Raspberry Pi, and a Server using the communication protocols namely Modbus TCP/IP and message queuing telemetry transport (MQTT). Then, the attack is emulated using Ettercap in a real-time testbed. The packets are captured with Wireshark and processed using preprocessing methods in Python. Furthermore, a pool of ML algorithms is extensively trained and validated on the practical testbed to identify suitable intrusion detection models. The results exhibit that the random forest (RF) algorithm outperforms the rest of the algorithms. Furthermore, to optimize its performance, the conventional RF algorithm is blended with a modified hybrid bat algorithm (HBA). The performance metrics of the hybrid model exhibit its supremacy over its counterparts. Proposed model video link: https://drive.google.com/file/d/1Yq6nuNlr98klaoy07k83m4ega SHOJIM0/view?usp = drive_link.

Ba3Ca2Ti2O9doped with Dy3+ions is cultured by single step Solid state synthesis approach. The structural, optical and absorption properties are assessed from UV-Vis spectroscopy, photoluminescence spectroscopy (PL) and X-ray diffraction (XRD) characteristic studies, respectively. The 4F9/2→6H15/2transition of Dy3+ion effect strong emission in the visible region is observed under 328 nm excitation. The visible light-emitting phosphorescence originating from the characteristic transitions in Dy3+rare earth elements is inferred from the photoluminescence spectra. The developed phosphor composition demonstrates promising luminescence properties on account of the efficient energy transfer from the host matrix to the luminescence center. It is also surmised that the color coordinates of the sample material formed in the blue region attribute to the CIE color coordinates and color purity. The resultant outcome is suggestive that the studied compounds are promising material for the visible light-emitting diodes and solid state laser applications.

A decade of significant research has led to the emergence of photovoltaic solar cells based on perovskites that have achieved an exceptionally high‐power conversion efficiency of 26.08%. A key breakthrough in perovskite solar cells (PSCs) occurred when solid hole‐transporting materials (HTMs) replaced liquid electrolytes in dye‐sensitized solar cells (DSSCs), because HTMs play a crucial role in improving photovoltaic performance as well as cell stability. This review is mainly focused on the HTMs that are responsible for hole transport and extraction in PSCs, which is one of the crucial components for efficient devices. Here, we have reviewed small molecular as well as polymeric HTMs that have been reported in the last two years and discussed their performance based on the analysis of their molecular architectures. Finally, we include a perspective on the molecular engineering of new functional HTMs for highly efficient stable PSCs. The properties of ideal hole transporting materials (HTMs) in perovskite solar cell should include facile synthesis and purification, good solubility, photochemical and thermal stability, tunable energy levels, and excellent hole mobility.

This review highlights our recent efforts in the development of organic semiconductors based on anthradithiophene (ADT), dithienothiophene (DTT), tetrathienoacene (TTA), benzothienodithiophene (BTDT), benzothienothiophene (BTT), chalcogen‐planarized BT, and some quinoidal oligothiophenes for the application of organic thin‐film transistors (OTFTs). We visualized various strategies that have been employed in molecular architecture to improve the stability as well as solubility, and the energy levels are tuned for efficient hole/electron injection, thus leading to high‐performance solution processable OTFTs. The obtained mobility was correlated with the molecular stacking pattern and film morphology/microstructure of the semiconductors. Overall, this review presents information that aids reliable OTFT data analysis and provide guidelines for the development of next‐generation organic semiconductors. At present, the p‐type and n‐type OTFTs developed by our group are able to reach the mobilities of over 4.01 and 2.5 cm2V−1s−1, respectively. In addition, we also demonstrated the utilization of these conjugated moieties in development of high performance dye‐sensitized solar cells (DSSCs) and hole transporting materials (HTM) as well as non‐fullerene acceptor (NFA) for perovskite solar cells (PSCs). This review examines strategies employed in molecular architecture to increase stability and solubility, and the energy levels used to optimize hole/electron injection, leading to high‐performance solution‐processable OTFTs.

A facile synthesis of a bimetallic metal–organic framework (MOF) codoped with carbon nanodots (CNDs) (Co/Mn@CNDs-MOF) via solvothermal treatment is reported. In this study, we prepared a composite material with nanofusiform-like structures as an efficient earth-abundant oxygen evolution reaction (OER) electrocatalyst, its morphology was confirmed by high-resolution transmission electron microscopy, and the calculated average particle size of the Co/Mn@CNDs-MOF was 10.5 nm. Electrochemical methods were performed to examine the catalytic OER of the Co/Mn@CNDs-MOF electrode. The MOF composite revealed high current densities of 50 and 100 mA/cm2at 280 and 320 mV overpotentials, respectively, with a low Tafel slope of 140 mV dec–1in a 1 M KOH aqueous electrolyte toward OER. Here, the incorporation of CNDs into a bimetallic MOF increases the surface area, active sites, and moreover the electrocatalytic activity of the composite, revealing almost equal properties when compared to a commercial catalyst, ruthenium oxide (RuO2). This research provides an outstanding avenue to realize multifunctional electrocatalysts.

Multiport converters gain prominent importance in electric vehicle (EV) and DC micro-grid applications for their capability to integrate multiple renewable power sources and energy storage systems. The stored energy in the battery balances the load demand during intermittent power generation from the photovoltaic (PV) source. However, charging the drained battery in the complete absence of PV power interrupts the overall operation of the system. Hence, a modified dual-input three-port isolated bidirectional converter is proposed to handle bidirectional power transfer in the output port and to utilize available power for battery charging. Implementation of a mode selection logic controller with optimal maximum power point tracking and pulse width modulated controllers improves the reliability of the converter. The equivalent circuit of the proposed topology and its mathematical model help evaluate the loss of components at different conduction intervals. The computed device losses, inductor and capacitor equivalent series resistance losses, and other losses clearly depict the effect on the performance of the proposed converter. Thus, the predicted efficiency is validated by the experimental data of the laboratory prototype, substantiating the performance of the converter.

Among the optimistic areas of research, is the creation of novel C−C, C−N, and C−O bonds by replacing toxic and waste‐generating chemicals with alcohols as more sustainable and greener reagents. The co‐existence of molecular oxygen and TBHP was admired by its capacity to oxidize and cyclize to form biologically active acridine‐1,8‐dione derivatives from alcohol, aniline and dimedone without any metal catalyst. The decomposition of TBHP and aeration of molecular oxygen on the surface of water was the key factor for effective catalytic outcome. The current method exhibits tolerance for diverse substrates to afford acridine‐1,8‐dione derivatives (18 compounds) with high yield (up to 95 %). Additionally, the photophysical properties of the acridine‐1,8‐dione derivatives were also studied, and found that few of the acridine‐1,8‐dione derivatives have shown appreciable Aggregation Induced Emission Enhancement (AIEE) behaviour. A metal, ligand, and additive‐free aerobic oxidative annulation strategy was employed to synthesize fluorescent acridine‐1,8‐diones using TBHP in water. Various acridine‐1,8‐diones were prepared from readily available benzyl alcohol, 1,3‐diketone, and aniline under mild conditions, further, photophysical properties of acridine‐1,8‐dione derivatives were analyzed using acetonitrile unfolding good deep blue emission and AIEE behaviour.

Though copper is a capable electrocatalyst for the CO2reduction reaction (CO2RR), it rapidly deactivates to produce mostly hydrogen. A current hypothesis as to why this occurs is that potential-induced morphological restructuring takes place, leading to a redistribution of the facets at the interface resulting in a shift in the catalytic activity to favor the hydrogen evolution reaction over CO2RR. Here, we investigate the veracity of this hypothesis by studying the changes in the voltammetry of various copper surfaces, specifically the three principal orientations and a polycrystalline surface, after being subjected to strongly cathodic conditions. The basal planes were chosen as model catalysts, while polycrystalline copper was included as a means of investigating the overall behavior of defect-rich facets with many low coordination steps and kink sites. We found that all surfaces exhibited (perhaps surprisingly) high stability when subjected to strongly cathodic potentials in a concentrated alkaline electrolyte (10 M NaOH). Proof for morphological stability under CO2RR-representative conditions (60 min at −0.75 V in 0.5 M KHCO3) was obtained from identical location scanning electron microscopy, where the mesoscopic morphology for a nanoparticle-covered copper surface was found unchanged to within the instrument accuracy. Observed changes in voltammetry under such conditions, we found, were not indicative of a redistribution of surface sites but of electrode fouling. Besides impurities, we show that (brief) exposure to oxygen or oxidizing conditions (i.e., 1 min) leads to copper exhibiting changing morphology upon cathodic treatment which, we posit, is ultimately the reason why many groups report the evolution of copper morphology during CO2RR: accidental oxidation/reduction cycles.

Purpose: In this study, the main objectives are to show the performance of deep convolutional neural network in identifying individual pig and investigate the accuracy level of CNN using four datasets made with pig’s face in different growing period. Methods: Firstly, the datasets were captured in an experimental pig barn at a different time. Secondly, the datasets were filtered similar images using the structural similarity index measure (SSIM) for data preparation. Finally, face image classification is performed by employing a deep convolutional neural network (DCNN) namely ZFNet model. Results: The results have shown that individual pig identification is outperformed while using the same age dataset in training and testing stage with an accuracy rate above 97%. Conclusions: The model performed better in a combined dataset which is a combination of all individual data. For future recommendation, it would be beneficial to perform the effectiveness on a large scale of pigs, and a network model should be considered unsupervised learning in case of ageing classification.

Kerala Ayurveda Ostoact Tablet (OAT) is a traditional Ayurvedic preparation that might use for the management of joint pain, bone pain and arthritis. The goal of present research was to evaluate the activity of OAT in improving postmenopausal osteoporosis (PMO) in ovariectomized (OVX) rats.

The pressing need to meet sustainability and climate objectives has prompted a call for expanding the use of renewable energy sources, improving the intelligence and flexibility of electricity grids, and increasing the adoption of electric vehicles and other electricity-powered products. In light of their numerous benefits, widespread electrification and digital technologies can form the basis of energy and climate policy. This research presents an innovative biased transformer and digital twin battery model to support the wind energy based electric vehicle battery charging system. During periods of low and moderate wind, the biased transformer is utilized to increase the voltage for charging electric vehicles. A digital twin of the battery system creates a window into battery charging and aging levels by evaluating the data gathered based on internal resistance. Furthermore, the State of Charge estimation model and different internal resistance estimation algorithms are also exploited. A novel method for precise State of Charge (SOC) estimation in third-gen battery models is presented, integrating Collaborative Gradient Boosting and Adaptive Extended Kalman Filter (AEKF). This approach, implemented in MATLAB Simulink, combines machine learning and adaptive filtering, enhancing accuracy and adaptability for efficient battery management. The functionalities and resilience of both hardware and software of the proposed system are validated under field operation.

Addressing the challenge of cost-effectively synthesizing stable thermal barrier coating materials has been a significant hurdle. This study describes the bulk synthesis of stannate-based pyrochlore compounds, specifically erbium tin oxide (Er2Sn2O7) and yttrium tin oxide (Y2Sn2O7). These synthesized pyrochlore oxides and commercially available yttria-stabilized zirconia (YSZ) were coated onto nickel super alloy. The coated specimens were subjected to thermal oxidation kinetics studies at 900 ± 5°C for 200 h, and alterations in physico-chemical characteristics, modifications in surface morphology, and variations in the composition of thermal barrier coating (TBCs) before and after exposure to oxidation conditions were evaluated. Oxidation kinetics results demonstrate that Er2Sn2O7pyrochlore oxide has better performance than other Y2Sn2O7and commercial YSZ TBC materials in high-temperature thermal barrier systems.

The 3,5-dithiooctyl dithienothiophene based small molecular semiconductor DDTT-DSDTT(1), end functionalized with fused dithienothiophene (DTT) units, was synthesized and characterized for organic field effect transistors (OFET). The thermal, optical, electrochemical, and computed electronic structural properties of 1were investigated and contrasted. The single crystal structure of 1reveals the presence of intramolecular locks between S(alkyl)···S(thiophene), with a very short S–S distance of 3.10 Å, and a planar core. When measured in an OFET device compound 1exhibits a hole mobility of 3.19 cm2V–1s–1, when the semiconductor layer is processed by a solution-shearing deposition method and using environmentally acceptable anisole as the solvent. This is the highest value reported to date for an all-thiophene based molecular semiconductor. In addition, solution-processed small molecule/insulating polymer (1/PαMS) blend films and devices were investigated. Morphological analysis reveals a nanoscopic vertical phase separation with the PαMS layer preferentially contacting the dielectric and 1located on top of the stack. The OFET based on the blend comprising 50% weight of 1exhibits a hole mobility of 2.44 cm2V–1s–1and a very smaller threshold voltage shift under gate bias stress.

In this work, we investigate gold surface dissolution under cathodic potentials as a function of crystal orientation using cyclic voltammetry, scanning electron microscopy, and atomic force microscopy to determine to what extent cathodic corrosion is anisotropic in nature. Additional experiments were performed to gain insights into the effect of the presence of CO on cathodic corrosion. Carbon monoxide experiments were conducted to investigate the effect of more realistic reaction conditions on cathodic corrosion as they might be found in gold-driven CO2electrolyzers, although the effects of the presence of CO2(reactant) and carbonate salts (typically present in the reaction medium) were excluded from this study. It was found that cathodic corrosion of gold is strongly anisotropic, with stepped surfaces and the {110} plane being most susceptible to dissolution, whereas the {111} and {100} planes were much more resilient to dissolution. On these more stable surfaces, nanocrystallite growth was observed instead, which we hypothesize originates from redeposition of the gold that dissolves from the more corrosive, more open, and/or defective facets. Finally, the presence of carbon monoxide was found to slightly enhance the rate of surface change, as evidenced by increases in charge in cyclic voltammograms after corrosion and an earlier onset of crystallite growth on the {111} and {100} planes, which we ascribe to enhanced gold mobility due to the strong bond formed between CO and gold in alkaline media.

ABSTRACTThe effects of fuel injection strategies on the characteristics of common rail diesel injection engine using mahua methyl ester (MME20) blend have been investigated. Fuel injection strategies such as fuel pressure and split injection have been implemented on a test engine. When MME20 was used as the fuel on mechanical injection at an injection pressure of 22 MPa, specific fuel consumption and NOxemission were found to be increased and brake thermal efficiency (BTE) decreased. In the first phase, in order to optimise the utilisation of the mahua methyl ester blend, fuel injection pressure was increased from 20 to 50 MPa with an increment of 10 MPa. The experimental observation reveals that high fuel injection pressure (50 MPa) exhibits higher BTE and better combustion characteristics when compared with decremented injection pressures. HC, CO and smoke level decreased with an increase in injection pressure due to better-atomised spray and mixture formation. In the second phase, implementation of spilt injection 5% MME20 as pilot injection at 5°, 10° and 15° CA before main injection was identified with the decrease of HC, CO, NOxand smoke emission with marginal sacrifice of BTE compared with diesel fuel.

Effluent from paper industry was oxygenated till saturation using Lark Hygiene Fermenter at 25°C under real time environment. Time, speed, and feed concentration were selected as dominant input factors to determine the dissolved oxygen (DO) under response surface methodology (RSM) based Box–Behnken design to provide 17 experimental runs. The experimental results were optimized using RSM and artificial neural networks (ANN). From RSM analysis, a second-order quadratic representation for single objective optimization was successfully fitted which produced R2= 99.07 and R2adj= 97.87. Analysis of variance results shows that time and feed concentration were the most significant parameters than the speed, influencing the DO. Another single objective optimization tool ANN produced R2= 96.27 and R2adj= 94.06. Validation analysis provided the predicted values by RSM and ANN were close to the validation values, whereas RSM showed a better prediction than the ANN with the lowest deviation. Hence, the optimal condition predicted by RSM was taken to conduct the confirmatory experiment. The confirmatory experimental condition of time at 6 min, speed of 142 rpm with 90% concentration produced the minimal DO of 5.38 ppm. The error percentage of the predicted with confirmatory experimental and theoretical equations results were 1.11% and 0.035%, respectively, which validates the predicted model.

ABSTRACTAn experiment was conducted to evaluate modelling relationships between pig’s body surface temperature and ambient environment including inside and outside of pig barn. For this purpose, four different artificial neural network (ANN), including Feed Forward Back-propagation (FFB), Layer recurrent (LR), Elman (EL) and Cascade Forward Back-propagation (CFB) with different learning algorithms, transfer functions, hidden layers and neuron in each layer, and multi-linear regression (MLR) models have been performed to predict body temperature of pig. Six two-month-old pigs were studied over a period of 92 days during two years (2017–2018) to develop and evaluate the ANN and MLR models. The performance of the models in predicting pig’s body temperature was determined using statistical quality parameters, including coefficient of determination (R2), root mean square error (RMSE) and mean absolute percentage error (MAPE). The FFB model with the Levenberg-Marquardt training function, Gradient descent weight and bias learning function, Log-sigmoid transfer function and two hidden layers with 20 neurons was found as the best model. Sensitivity analysis indicated that the temperature-humidity index (THI) inside the room is the most influential factor in predicting pig’s body temperature in the MLR/ANN models.

Background: Hepatitis B virus (HBV) has affected over 300 million people worldwide which causes to induce mostly liver disease and liver cancer. It is a member of the family Hepadnaviridae which is a small DNA virus with unusual characters like retroviruses. Generally, hepatoprotective drugs provoke some side effects in human beings. For the reason, this study aims to identify alternative drug molecules from the natural source of medicinal plants with smaller quantity of side effects than those conventional drugs in treating HBV. Methods: We developed computational methods for calculating drug and target binding resemblance using the Maestro v10.2 of Schrodinger suite. The target and ligand molecules were obtained from recognized databases. Ligand molecules of 40 phytoconstituents were retrieved from variety of plants after we executed crucial analyses such as molecular docking and absorption, distribution, metabolism, and excretion (ADME) analysis. Results: In the docking analysis, the natural analogues repandusinic acid showed better docking scores of −14.768 with good binding contacts. The remaining bioactive molecules corilagin, furosin, nirurin, iso-quercetin and gallocatechin also showed better docking scores. Conclusion: This computational analysis reveals that repandusinic acid is a suitable drug candidate for HBV. Therefore, we recommend that this analogue is suitable in further exploration using in vitrostudies.

Hepatitis B virus (HBV) has affected over 300 million people worldwide which causes to induce mostly liver disease and liver cancer. It is a member of the family Hepadnaviridae which is a small DNA virus with unusual characters like retroviruses. Generally, hepatoprotective drugs provoke some side effects in human beings. For the reason, this study aims to identify alternative drug molecules from the natural source of medicinal plants with smaller quantity of side effects than those conventional drugs in treating HBV. We developed computational methods for calculating drug and target binding resemblance using the Maestro v10.2 of Schrodinger suite. The target and ligand molecules were obtained from recognized databases. Ligand molecules of 40 phytoconstituents were retrieved from variety of plants after we executed crucial analyses such as molecular docking and absorption, distribution, metabolism, and excretion (ADME) analysis. In the docking analysis, the natural analogues repandusinic acid showed better docking scores of –14.768 with good binding contacts. The remaining bioactive molecules corilagin, furosin, nirurin, iso‐quercetin and gallocatechin also showed better docking scores. This computational analysis reveals that repandusinic acid is a suitable drug candidate for HBV. Therefore, we recommend that this analogue is suitable in further exploration using in vitrostudies. Author summary:Hepatitis B virus affects the human beings due to the virus replication. The conventional drugs of hepatitis B virus have side effects on human and few are not responsible for that diseases complication. Hence, present computational studies found a few effective phytocompounds for hepatitis B virus which are identified based on their mode of interactions with hepatitis B viral protein molecule. Among the molecules, repandusinic acid has a better docking score and it was shown good binding affinities with the target. In vitroand in vivoevaluation will be essential and we hope this study will be helpful to proceed further with the effective drug development.

•Computational investigations of the interaction of neurotransmitter and metal cluster (Pt3) with gas phase and different phase are investigated.•The adsorption energies of neurotransmitter with platinum metal cluster (gas phase) are the highest absorption energy.•The studies ELF, LOL and ALIE confirm the electron delocalization energies and RDG study confirm the non-covalent interactions.•The electrophilic and nucleophilic attractions of the neurotransmitter with Pt3 metal clusters are revealed by the MEP investigation, while the FMO analysis reveals very low energy gap values.•Non-covalent interaction studies showed that the molecules interacted strongly with the metal clusters.

•Electronic properties were analysed using five different solvents.•Electrophilic and nucleophilic attacking sites are confirmed.•The active sites were determined using molecular electrostatic potential, ELF, LOL, ALIE and RDG.•Condensed Fukui function, natural bond orbital (NBO) and NLO property were discussed.•Docking study was done against 7WCL protein.

Purpose: During tillage operations, draft force contributes hugely to the operational cost. Accurate knowledge of draft force (DF) requirement for tillage implements is a useful tool for machinery selection, matching of implements to tractor, etc. The goal of this research was to measure the draft force of a compact disc harrow and analyze the effect of soil moisture content (SMC) and machine speed on draft force. Also, another aim is to develop a model equation to predict draft force requirement of compact disc harrow. Methods: A EWX 10000F winch was used to provide the draft (pull) force which was powered by a 24 V DC battery. The draft force was measured using a load cell which transmitted the measured values to an AND ad 4532B indicator. The draft force of the compact disc harrow was measured at three different levels of SMC: low SMC (5–7%, 9–11%, 13–15%); medium SMC (25–27%, 29–31%, 33–35%); and High SMC (40–42%, 44–46%, 48–50%) with machine speed (MS) of 0.06 m/s, 0.09 m/s, and 0.12 m/s. Results: The results obtained were statistically analyzed and it showed that the lowest draft force occurred at 26% SMC with a force of about 658 N. A multi-variable regression equation was developed after the regression analysis. The regression equation DF= 466.91 + 6.25*(SMC) + 2952.1*(MS) was selected as the best model for predicting draft force. This equation was verified using the Bland–Altman plot, the ttest analysis, and the standard error analysis. Conclusion: The results of the verification methods proved that the suggested model can be used for predicting draft force requirement of a compact disc harrow.