Abstract-Under a multirate network scenario, the IEEE 802.11 DCF MAC fails to provide airtime fairness for all competing stations since the protocol is designed for ensuring max-min throughput fairness. As such, the maximum achievable throughput by any station gets bounded by the slowest transmitting peer. In this paper, we present an analytical model to study the delay and throughput characteristics of such networks so that the rate anomaly problem of IEEE DCF multirate networks could be mitigated. We call our proposal Time Fair CSMA (TFCSMA) which utilizes an interesting baseline property for estimating a target throughput for each competing station so that its minimum contention window could be adjusted in a distributed manner. As opposed to the previous work in this area, TFCSMA is ideally suited for practical scenarios where stations frequently adapt their data rates to changing channel conditions. In addition, TFCSMA also accounts for packet errors due to the time varying properties of the wireless channel. We thoroughly compare the performance of our proposed protocol with IEEE 802.11 and other existing protocols under different network scenarios and traffic conditions. Our comprehensive simulations validate the efficacy of our method toward providing high throughput and time fair channel allocation.

The outbreak of SARS-CoV-2 and deaths caused by it all over the world have imposed great concern on the scientific community to develop potential drugs to combat Coronavirus disease-19 (COVID-19). In this regard, lichen metabolites may offer a vast reservoir for the discovery of antiviral drug candidates. Therefore, to find novel compounds against COVID-19, we created a library of 412 lichen compounds and subjected to virtual screening against the SARS-CoV-2 Main protease (Mpro). All the ligands were virtually screened, and 27 compounds were found to have high affinity with Mpro. These compounds were assessed for drug-likeness analysis where two compounds were found to fit well for redocking studies. Molecular docking, drug-likeness, X-Score, and toxicity analysis resulting in two lichen compounds, Calycin and Rhizocarpic acid with Mpro-inhibiting activity. These compounds were finally subjected to molecular dynamics simulation to compare the dynamics behavior and stability of the Mpro after ligand binding. The binding energy was calculated by MM-PBSA method to determine the intermolecular protein-ligand interactions. Our results showed that two compounds; Calycin and Rhizocarpic acid had the binding free energy of − 42.42 kJ mol/1 and − 57.85 kJ mol/1 respectively as compared to reference X77 (− 91.78 kJ mol/1). We concluded that Calycin and Rhizocarpic acid show considerable structural and pharmacological properties and they can be used as hit compounds to develop potential antiviral agents against SARS-CoV-2. These lichen compounds may be a suitable candidate for further experimental analysis.

The whole world is facing a great challenging time due to Coronavirus disease (COVID-19) caused by SARS-CoV-2. Globally, more than 14.6 M people have been diagnosed and more than 595 K deaths are reported. Currently, no effective vaccine or drugs are available to combat COVID-19. Therefore, the whole world is looking for new drug candidates that can treat the COVID-19. In this study, we conducted a virtual screening of natural compounds using a deep-learning method. A deep-learning algorithm was used for the predictive modeling of a CHEMBL3927 dataset of inhibitors of Main protease (Mpro). Several predictive models were developed and evaluated based on R 2 , MAE MSE, RMSE, and Loss. The best model with R 2 ¼0.83, MAE ¼ 1.06, MSE ¼ 1.5, RMSE ¼ 1.2, and loss ¼ 1.5 was deployed on the Selleck database containing 1611 natural compounds for virtual screening. The model predicted 500 hits showing the value score between 6.9 and 3.8. The screened compounds were further enriched by molecular docking resulting in 39 compounds based on comparison with the reference (X77). Out of them, only four compounds were found to be drug-like and three were non-toxic. The complexes of compounds and Mpro were finally subjected to Molecular dynamic (MD) simulation for 100 ns. The MMPBSA result showed that two compounds Palmatine and Sauchinone formed very stable complex with Mpro and had free energy of À71.47 kJ mol À1 and À71.68 kJ mol À1 respectively as compared to X77 (À69.58 kJ mol À1). From this study, we can suggest that the identified natural compounds may be considered for therapeutic development against the SARS-CoV-2.

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Cutting force and torque are important factors in the success of the bone drilling process. In the recent past, many attempts have been made to reduce the cutting force and torque in the bone drilling process. In this work, drilling on human cadaver bones has been performed using rotary ultrasonic bone drilling process to investigate the effect of drilling parameters on cutting force and torque. The experimental work was carried on a recently developed rotary ultrasonic bone drilling machine for surgical operations. The experimental work was performed in two phases. The first phase includes a comparative study between rotary ultrasonic bone drilling and conventional surgical bone drilling, to study the influence of various drilling parameters (rotational speed, drill diameter, and drilling tool feed rate) on the cutting force and torque. The results revealed that the cutting force and torque produced during drilling operations in rotary ultrasonic bone drilling were lesser (30%–40%) than conventional surgical bone drilling. In the second phase, response surface methodology was used to perform the statistical modeling of cutting force and torque in rotary ultrasonic bone drilling process. Analysis of variance was performed at a confidence interval of 95% to analyze the significant contribution ( p < 0.05) of process parameters (drilling speed, feed rate, drill diameter, and abrasive particle size) on the responses (cutting force and torque). The confirmatory experiments were performed to validate the developed statistical models. It was found that both cutting force and torque decrease with increase in drilling speed and increases with the increasing drill diameter, feed rate, and abrasive particle size.

We address the problem of estimating the structure and motion of a smooth curved object from its silhouettes observed over time by a trinocular stereo rig under perspective projection. We first construct a model for the local structure along the silhouette for each frame in the temporal sequence. The local models are then integrated into a global surface description by estimating the motion between successive time instants. The algorithm tracks certain surface features (parabolic points) and image features (silhouette inflections and frontier points) which are used to bootstrap the motion estimation process. The entire silhouettes along with the reconstructed local structure are then used to refine the initial motion estimate. We have implemented the proposed approach and report results on real images.

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