3D indoor modeling and game theory based navigation for pre and post COVID-19 situation.

The COVID-19 pandemic has greatly affected human behavior, creating a need for individuals to be more cautious about health and safety protocols. People are becoming more aware of their surroundings and the importance of minimizing the risk of exposure to potential sources of infection. This shift in mindset is particularly important in indoor environments, especially hospitals, where there is a greater risk of virus transmission. The implementation of route planning in these areas, aimed at minimizing interaction and exposure, is crucial for positively influencing individual behavior. Accurate maps of buildings help provide location-based services, prepare for emergencies, and manage infrastructural facilities. There aren't any maps available for most installations, and there are no proven techniques to categorize features within indoor areas to provide location-based services. During a pandemic like COVID-19, the direct connection between the masses is one of the significant preventive steps. Hospitals are the main stakeholders in managing such situations. This study presents a novel method to create an adaptive 3D model of an indoor space to be used for localization and routing purposes. The proposed method infuses LiDAR-based data-driven methodology with a Quantum Geographic Information System (QGIS) model-driven process using game theory. The game theory determines the object localization and optimal path for COVID-19 patients in a real-time scenario using Nash equilibrium. Using the proposed method, comprehensive simulations and model experiments were done using QGIS to identify an optimized route. Dijkstra algorithm is used to determine the path assessment score after obtaining several path plans using dynamic programming. Additionally, Game theory generates path ordering based on the custom scenarios and user preference in the input path. In comparison to other approaches, the suggested way can minimize time and avoid congestion. It is demonstrated that the suggested technique satisfies the actual technical requirements in real-time. As we look forward to the post-COVID era, the tactics and insights gained during the pandemic hold significant value. The techniques used to improve indoor navigation and reduce interpersonal contact within healthcare facilities can be applied to maintain a continued emphasis on safety, hygiene, and effective space management in the long term. The use of three-dimensional (3D) modeling and optimization methodologies in the long-term planning and design of indoor spaces promotes resilience and flexibility, encouraging the adoption of sustainable and safe practices that extend beyond the current pandemic.

Unleashing the visible light-exposed photocatalytic potential of V2O5/g-C3N4 nanocomposites for dye industries wastewater cleaner production.

Dealing harmful dye-containing effluent from the textile sector significantly contributes to water contamination. The persistence of these dyes in wastewater complicates traditional treatment approaches, emphasizing the necessity for efficient photocatalytic materials for dye pollution degradation. Due to its unique features, V2O5/g-C3N4 nanocomposites are discovered as promising photocatalysts in this area. The V205 nanoparticles act as electron acceptors, while g-C3N4 acts as electron donors, thus encouraging charge separation and increasing photocatalytic activity. The V2O5/g-C3N4 nanocomposites are characterized using XRD, FTIR spectroscopy, SEM, TEM, XPS, and UV-DRS. Cationic dyes, anionic dyes and mix dyes (1:1 mixture of cationic and anionic dyes) are used to test the photocatalytic activity of the nanocomposites. Photocatalytic activity shows that V2O5/g-C3N4 nanocomposites are more active than their precursors. The V5G-2 nanocomposite degrades anionic (Rose Bengal (85.1%) and Xylenol Orange (77.6%), cationic (Auramine O (75% and Crystal Violet (79.5%), and mixed dyes (81%), after 120 min of irradiation. This study introduces a novel technique for synthesizing V2O5/g-C3N4 nanocomposites using solvothermal and ultrasonic processes. The findings of this research provide significant knowledge for the development of photocatalysts with enhanced efficiency in the degradation of dye pollutants.

Reactive Centre Loop Mutagenesis of SerpinB3 to Target TMPRSS2 and Furin: Inhibition of SARS-CoV-2 Cell Entry and Replication.

The SARS-CoV-2 virus can utilize host cell proteases to facilitate cell entry, whereby the Spike (S) protein is cleaved at two specific sites to enable membrane fusion. Furin, transmembrane protease serine 2 (TMPRSS2), and cathepsin L (CatL) are the major proteases implicated, and are thus targets for anti-viral therapy. The human serpin (serine protease inhibitor) alpha-1 antitrypsin (A1AT) shows inhibitory activity for TMPRSS2, and has previously been found to suppress cell infection with SARS-CoV-2. Here, we have generated modified serpin inhibitors with increased specificity for these cellular proteases. Using SerpinB3 (SCCA-1), a cross-class inhibitor of CatL, as a scaffold, we have designed and produced reactive centre loop (RCL) variants to more specifically target both furin and TMPRSS2. Two further variants were generated by substituting the RCL P7-P1 with the spike protein S1/S2 cleavage site from either SARS-CoV-2 alpha or delta (P681R) sequences. Altered inhibitory specificity of purified recombinant proteins was verified in protease assays, with attenuated CatL inhibition and gain of furin or TMPRSS2 inhibition, as predicted, and modified serpins were shown to block S protein cleavage in vitro. Furthermore, the serpin variants were able to inhibit S-pseudoparticle entry into A549-ACE2-TMPRSS2 cells and suppress SARS-CoV-2 replication in Vero E6 cells expressing TMPRSS2. The construct designed to inhibit TMPRSS2 (B3-TMP) was most potent. It was more effective than A1AT for TMPRSS2 enzyme inhibition (with an eighteen-fold improvement in the second order inhibition rate constant) and for blocking SARS-CoV-2 viral replication. These findings advance the potential for serpin RCL mutagenesis to generate new inhibitors, and may lead to novel anti-viral biological molecules.

Recent advancements in urea biosensors for biomedical applications.

The quick progress in health care technology as a recurrent measurement of biochemical factors such as blood components leads to advance development and growth in biosensor technology necessary for effectual patient concern. The review wok of authors present a concise information and brief discussion on the development made in the progress of potentiometric, field effect transistor, graphene, electrochemical, optical, polymeric, nanoparticles and nanocomposites based urea biosensors in the past two decades. The work of authors is also centred on different procedures/methods for detection of urea by using amperometric, potentiometric, conductometric and optical processes, where graphene, polymer etc. are utilised as an immobilised material for the fabrication of biosensors. Further, a comparative revision has been accomplished on various procedures of urea analysis using different materials-based biosensors, and it discloses that electrochemical and potentiometric biosensor is the most promise one among all, in terms of rapid response time, extensive shelf life and resourceful design.