An enhanced synchronized multi-channel MAC scheme to improve throughput in VANET

The development of autonomous driving and intelligent transportation demands, fast, reliable and efficient data transmission for various applications in vehicular ad hoc network (VANET). This poses great challenges to the design of a media access control (MAC) protocol that can adapt to the frequent topological shifts. IEEE 1609.4 defines the multi-channel MAC layer implementation in VANET. The multi-channel operation works on a fixed synchronization interval that alternates between a control channel and service channels. The fixed interval leads to poor utilization of limited spectrum resources. In this paper, a multi-channel reliable MAC protocol (MCRMAC), that uses both the control channel and service channel irrespective of the interval to ensure proper and efficient throughput utilization in VANET is proposed. The simulations reveal the performance of the proposed scheme and it outperforms IEEE 1609.4 in terms of throughput

Quantitative Susceptibility Mapping in Cognitive Decline: A Review of Technical Aspects and Applications

In the human brain, essential iron molecules for proper neurological functioning exist in transferrin (tf) and ferritin (Fe3) forms. However, its unusual increment manifests iron overload, which reacts with hydrogen peroxide. This reaction will generate hydroxyl radicals, and irons higher oxidation states. Further, this reaction causes tissue damage or cognitive decline in the brain and also leads to neurodegenerative diseases. The susceptibility difference due to iron overload within the volume of interest (VOI) responsible for field perturbation of MRI and can benefit in estimating the neural disorder. The quantitative susceptibility mapping (QSM) technique can estimate susceptibility alteration and assist in quantifying the local tissue susceptibility differences. It has attracted many researchers and clinicians to diagnose and detect neural disorders such as Parkinsons, Alzheimers, Multiple Sclerosis, and aging. The paper presents a systematic review illustrating QSM fundamentals and its processing steps, including phase unwrapping, background field removal, and susceptibility inversion. Using QSM, the present work delivers novel predictive biomarkers for various neural disorders. It can strengthen new researchers fundamental knowledge and provides insight into its applicability for cognitive decline disclosure. The paper discusses the future scope of QSM processing stages and their applications in identifying new biomarkers for neural disorders

Broad-tailed force distributions and velocity ordering in a heterogeneous membrane model for collective cell migration

Correlated velocity patterns and associated large length-scale transmission of traction forces have been observed in collective live cell migration as a response to a "wound". We argue that a simple physical model of a force-driven heterogeneous elastic membrane sliding over a viscous substrate can qualitatively explain a few experimentally observed facts: (i) the growth of velocity ordering which spreads from the wound boundary to the interior, (ii) the exponential tails of the traction force distributions, and (iii) the swirling pattern of velocities in the interior of the tissue.Comment: 7 pages and 5 figure

Lightweight 3D Convolutional Neural Network for Schizophrenia diagnosis using MRI Images and Ensemble Bagging Classifier

Structural alterations have been thoroughly investigated in the brain during the early onset of schizophrenia (SCZ) with the development of neuroimaging methods. The objective of the paper is an efficient classification of SCZ in 2 different classes: Cognitive Normal (CN), and SCZ using magnetic resonance imaging (MRI) images. This paper proposed a lightweight 3D convolutional neural network (CNN) based framework for SCZ diagnosis using MRI images. In the proposed model, lightweight 3D CNN is used to extract both spatial and spectral features simultaneously from 3D volume MRI scans, and classification is done using an ensemble bagging classifier. Ensemble bagging classifier contributes to preventing overfitting, reduces variance, and improves the model's accuracy. The proposed algorithm is tested on datasets taken from three benchmark databases available as open-source: MCICShare, COBRE, and fBRINPhase-II. These datasets have undergone preprocessing steps to register all the MRI images to the standard template and reduce the artifacts. The model achieves the highest accuracy 92.22%, sensitivity 94.44%, specificity 90%, precision 90.43%, recall 94.44%, F1-score 92.39% and G-mean 92.19% as compared to the current state-of-the-art techniques. The performance metrics evidenced the use of this model to assist the clinicians for automatic accurate diagnosis of SCZ

Identifying metalloproteins through X-ray fluorescence mapping and mass spectrometry

Metals are critical and dynamic components of biochemistry. To understand their roles, we greatly need tools to identify the ligands that bind them within the complexity of natural systems. This work describes the development of methods that not only detect and distinguish metals, but also characterize the proteins that bind them. We describe an approach to expose, identify and quantify metalloproteins in complex mixtures by sequential non-denaturing 2D-gel electrophoresis (2D GE)/X-ray Fluorescence (XRF) and tandem mass spectrometry (MS/MS) in the same spot of a sample. We first apply the development of 2D GE/XRF to Shewanella oneidensis MR-1, a well-studied system, and verify our electrophoretic approach. Then, we identified a novel periplasmic zinc protein in Pseudomonas aeruginosa PAO1 through 2D GE/XRF followed by MS/MS. The identity and function of this protein was verified through a gene mutation experiment.Fil: Raimunda, Daniel Cesar. Worcester Polytechnic Institute; Estados UnidosFil: Khare, Tripti. Argonne National Laboratory; Estados UnidosFil: Giometti, Carol. Argonne National Laboratory; Estados UnidosFil: Vogt, Stefan. Argonne National Laboratory; Estados UnidosFil: Argüello, José M.. Worcester Polytechnic Institute; Estados UnidosFil: Finney, Lydia. Argonne National Laboratory; Estados Unido

Transcriptional and Proteomic Analysis of a Ferric Uptake Regulator (Fur) Mutant of Shewanella oneidensis: Possible Involvement of Fur in Energy Metabolism, Transcriptional Regulation, and Oxidative Stress

The iron-directed, coordinate regulation of genes depends on the fur (ferric uptake regulator) gene product, which acts as an iron-responsive, transcriptional repressor protein. To investigate the biological function of a fur homolog in the dissimilatory metal-reducing bacterium Shewanella oneidensis MR-1, a fur knockout strain (FUR1) was generated by suicide plasmid integration into this gene and characterized using phenotype assays, DNA microarrays containing 691 arrayed genes, and two-dimensional polyacrylamide gel electrophoresis. Physiological studies indicated that FUR1 was similar to the wild-type strain when they were compared for anaerobic growth and reduction of various electron acceptors. Transcription profiling, however, revealed that genes with predicted functions in electron transport, energy metabolism, transcriptional regulation, and oxidative stress protection were either repressed (ccoNQ, etrA, cytochrome b and c maturation-encoding genes, qor, yiaY, sodB, rpoH, phoB, and chvI) or induced (yggW, pdhC, prpC, aceE, fdhD, and ppc) in the fur mutant. Disruption of fur also resulted in derepression of genes (hxuC, alcC, fhuA, hemR, irgA, and ompW) putatively involved in iron uptake. This agreed with the finding that the fur mutant produced threefold-higher levels of siderophore than the wild-type strain under conditions of sufficient iron. Analysis of a subset of the FUR1 proteome (i.e., primarily soluble cytoplasmic and periplasmic proteins) indicated that 11 major protein species reproducibly showed significant (P < 0.05) differences in abundance relative to the wild type. Protein identification using mass spectrometry indicated that the expression of two of these proteins (SodB and AlcC) correlated with the microarray data. These results suggest a possible regulatory role of S. oneidensis MR-1 Fur in energy metabolism that extends the traditional model of Fur as a negative regulator of iron acquisition systems

Amaranthus Biochar-Based Microbial Cell Composites for Alleviation of Drought and Cadmium Stress: A Novel Bioremediation Approach

Metal contamination coupled with aridity is a major challenge for remediation of abiotic stressed soils throughout the world. Both biochar and beneficial bacteria showed a significant effect in bioremediation; however, their conjugate study needs more exploration. Two rhizobacteria strains Serratia sp. FV34b and Pseudomonas sp. ASe42b isolated from multi-metal and drought stressed sites showed multiple plant-growth-promoting attributes (phosphate solubilization, indole-3-acetic acid, siderophore, and ammonia production). Both strains were able to tolerate a high concentration of Cd along with being resistant to drought (−0.05 to −0.73 MPa). The seldom studied biomass of Amaranthus caudatus L. was used for biochar preparation by pyrolyzing it at 470 °C for 160 min under limited oxygen and then using it for the preparation of biochar-based microbial cell composites (BMC)s. To check the efficiency of BMC under Cd stress (21 mg kg−1 soil) and drought, a pot-scale study was conducted using Brassica napus L. for 47 days. Both the BMC5 (Biochar + Serratia sp. FV43b) and BMC9 (Biochar + Pseudomonas sp. ASe42b) improved the seed germination, plant biometrical (shoot and root biomass, length of organs) and physiological (photosynthetic pigments, proline, malondialdehyde, and relative water content) parameters under drought (exerted until it reaches up to 50% of field capacity) and Cd-spiked soil. However, for most of them, no or few significant differences were observed for BMC9 before and after drought. Moreover, BMC9 maximized the Cd accumulation in root and meager transfer to shoot, making it a best bioformulation for sustainable bioremediation of Cd and drought stressed soils using rapeseed plant. © 2023 by the authors.Russian Science Foundation, RSF: 21-76-00011The research was funded by the Russian Science Foundation Grant No. 21-76-00011, https://rscf.ru/project/21-76-00011

RNA polymerase motors: dwell time distribution, velocity and dynamical phases

Polymerization of RNA from a template DNA is carried out by a molecular machine called RNA polymerase (RNAP). It also uses the template as a track on which it moves as a motor utilizing chemical energy input. The time it spends at each successive monomer of DNA is random; we derive the exact distribution of these "dwell times" in our model. The inverse of the mean dwell time satisfies a Michaelis-Menten-like equation and is also consistent with a general formula derived earlier by Fisher and Kolomeisky for molecular motors with unbranched mechano-chemical cycles. Often many RNAP motors move simultaneously on the same track. Incorporating the steric interactions among the RNAPs in our model, we also plot the three-dimensional phase diagram of our model for RNAP traffic using an extremum current hypothesis.Comment: 6 pages, 7 figure