This PDF file contains the front matter associated with SPIE Proceedings Volume 12758, including the Title Page, Copyright information, Table of Contents, and Conference Committee information.

Poly(Lactic-co-glycolic) acid (PLGA) is a biopolymer with numerous opportunities for medical science and environmental application. Tailoring the surface behavior of hydrophobic PLGA is important for many of their applications. Carbon nanotubes are graphene derivatives that have superior thermal, mechanical, electrical, and optical properties. Much research has been devoted to enhancing the properties of polymers using nanomaterials. In this research, composites of PLGA and multiwall carbon nanotube (MWNT) were prepared by using the solution cast technique with different MWNT contents. These composites are processed using microwave radiation to modify the surface behavior. The effects of processing are investigated using different techniques such as Contact angle measurement, Fourier transform infrared spectroscopy, and bacterial interactions. It is observed that microwave radiation modifies the surface behavior without introducing any additional surface functionalities. This is clearly observed from the bacterial investigation where microwave radiation increased bacterial growth in PLGA composites with 1% MWNT compared to pure polymer and 5% PLGA/MWNT composites. This demonstrates the use of microwave radiation as a promising tool for material modification that can be used to tailor surface characteristics for biomedical applications such as bioscaffolds.

Selective dissolution of copper from waste printed circuit boards (WPCBs) using atmospheric, microwave, and pressure leaching techniques has been investigated. A critical comparison of these three different methods was analyzed based on their leaching efficiency of the copper. The hydrothermal autoclave reactor was used for pressure leaching of printed circuit boards (PCBs) powder and also organic solvent treated PCBs were utilized instead of Parr high pressure reactor. Dimethylacetamide (DMAc) and Dimethylformamide (DMF) were used for organic swelling of 1 cm × 1 cm PCBs. DMAc at optimum conditions (temperature: 140 ºC, S/L ratio: 300 g/L, time: 6 h) displayed better dissolution of epoxy resins than that of DMF and facilitates the easy separation of metallic parts from non-metallic parts of PCBs. The percentage of copper in PCBs powder, DMF and DMAc treated PCBs was found to be 21, 46.02 and 78.75 % respectively. Pressure leaching of copper was carried out using two different oxidizing agents such as nitric acid and hydrogen peroxide. It has been identified that HNO3 found to be better oxidizing agent at 140 ºC in an autoclave as compared to H2O2. The Optimized conditions for pressure leaching of PCBs powder were temperature of 140 ºC with S/L ratio of 50 g/L using 15% HNO3 oxidizing agent and 3M H2SO4 concentration in time of 90 min. The leaching of copper from metal clads obtained after organic swelling with DMAc showed that the leaching efficiency is 96.96% with 5% HNO3 along with 3M H2SO4, S/L ratio of 50 g/L and time of 90 min at 140 ºC. The amount of oxidizing agent required for pressure leaching of DMAc treated PCBs is less when compared to pressure leaching of PCB powder.

In this article, we have observed the Bianchi type-III anisotropic cosmological model in the presence of cloud strings in context of electro- magnetic field in general theory of relativity. With the aid of the constant decelerating parameter and the shear scalar's relationship to scalar expansion that is derived from variation law of Hubble parameter [1] exact solutions of field equations have been obtained. Graphical representations of the parameters have been made out for the analysis of the dynamics and significance of the physical parameters of the model. The physical and kinematical properties found in the model demonstrate acceleration in the expansion of the universe, showcasing a compatibility with present day cosmological observations.

In this paper, an EV battery-based energy storage microgrid is controlled by the fuzzy logic controller, which we use as the backbone of an intelligent energy management system (EMS). Plug-in electric vehicles (EVs) can join the microgrid via a DC rapid charging station. Fuzzy logic controllers are used for each EV's estimated departure time, battery charge level, and rated capacity to calculate how much power of each EV can provide toV2G (vehicle-to-grid) and G2V (grid-to-vehicle) services. An array of solar panels and a battery attached to the Microgridthrough a bidirectional dime converter and a boost converter are the core components of the PVDCM. Both positive and negative currents can move from the power source tothe load whether the PV panels are set up for Maximum power point tracking (MPPT) or maximum voltage operation. To maximize efficiency in the faceof high input current and low input voltage, a new design for a solar the DC/DC converter is givenin this paper. However, thehigh DC/DC converter output power means that a big value of the input current is to be expected, which will possess adetrimental impact on the circuit design and the system's stability. In addition to being able to accept a wide variety of input voltage while maintaining a constant output voltage, the DC/DC converter is protecting the battery from being exposed to an output current, and improves the battery's useful life. Inverter current must be tracked and converted from abc to dq0 for this method to work (Clarke and Park transformation). Here the, two orthogonal phase variables for a Fuzzy controller are carried out by the Park transformation (DQ) on a single-phase inverter.

A common man is haunted by the thoughts of being infected by an unknown virus or bacteria or some microorganism, like severe acute respiratory syndrome corona virus -2 (SARS-Cov-2). To predict the vulnerability level of a person to infectious agents due to their exposure. A model is designed in this article using Fuzzy Inference system-Mamdani Type, based on the example of COVID cases considering a person’s visit to different places like professional visits, exposure in residential area, location of the office and many more other factors. Henceforth analyze our daily schedule to estimate the level of vulnerability to a virus such as SARS-Cov-2.

Covid19 pandemic teaches the inevitability of innovations in teaching and learning experience, especially in English communication competencies. This research investigates the possibility of teaching English communication skills, especially speaking skills applying integrated simulation activities. Creating a naturalistic environment through technology in English pedagogy was in demand. The learning aligns with integrating graphics-based strategies and optimizing instruction time through innovative techniques and resources. The researcher employed a quasi-experimental study which involved 180 teenage girls and boys between 17 and 19 ages from B tech. II semester from VIIT. Total sampling technique used to collect data through questionnaires, discussions, and semi-structured interviews. The researcher determined the pronunciation accuracy level of participants through Rosetta stone language learning software in pre-test. Virtual Reality and simulation activities through Rosetta stone software employed to train the experimental group. The post-test findings designate that participants‟ overall progression is remarkable in speaking subskills, i.e., intonation, vocabulary, the assortment of expressions, and grammar, especially pronunciation. There is a correlation between the training through simulation activities and pronunciation accuracy (p<0.05).

The present study focused on exploring the impact of Artificial Intelligence (AI) tools on Technical students’ ESL (English as Second language) Oral Communication skills. The researcher used preposttest results and speaking rubrics as research methodology. The samples of the study were 60 technical engineering students at VFSTR University, India. The study was designed with pre-posttest and a self-reflection questionnaire for selected samples as quasi experimental study. The aim of the study is enhancing the students’ accuracy and Fluency levels in Oral Communication skills through mobile applications based on AI (Artificial Intelligence). The analysis of the study revealed the significant difference of mean score of the speaking skills pre-post test of the selected group in favour of the post-test results. The study results showed that Artificial Intelligence based mobile applications can develop the students’ Speaking skills in the area of Accuracy and Fluency. The present study concluded with further recommendations related to mobile applications based on AI (Artificial Intelligence) for enhancing Writing skills of the Professional students.