Government of Gujarat

The application of radio detection and ranging in different places, such as military installations and commercial use, is done with the help of a RADAR SYSTEM, which uses electromagnetic waves for the detection of different physical components, such as distance, speed, position, range, direction, size, etc., which can be either fixed or in motion. The use of radar systems has greatly advanced, especially in navigation. In this research, we study existing navigation technologies and propose an Arduino-based radar system. It has an advantage over other radar systems, as the kit reduces power consumptionand connects to a wide range of Arduino boards and open-source code. The system consists of a basic ultrasonic sensor mounted on a servo motor that rotates to a specific angle and at a specific speed. This ultrasonic sensor is connected to Arduino digital input/output pins, and the servo motor is also connected to them. KEYWORDS- Arduino, Ultrasonic sensor, Servo motor, Simulation,

Computational advancement is the need of the present century and has played an important role in transforming the medical industry and health research. The application of engineering principles to biology using computational techniques has led to the development of in silico modeling and simulation. This chapter discusses the role of computational advancements in medical research and the importance of artificial intelligence and machine learning in modeling and simulation of diseases with personalized healthcare. In silico modeling and simulation provide precise predictions about the underlying signaling mechanisms involved in various diseases. This leads to early detection, as well as time-efficient and cost-effective solutions for healthcare practitioners. Computational techniques enhance targeted drug therapy in the pharmaceutical industry, facilitating drug design, development, and testing. Although in silico modeling and simulations are trending nowadays, challenges and limitations remain, such as the accuracy of the model, the depth of complex biological models, effective and efficient datasets, the lack of data availability, patient concerns, consent, and finally, the validation of the data as the model persists. Keeping the constraints in mind, the health informatics field has boosted the development and analysis of much more complex models like those related to cancer and diabetes. For advancing the medical industry, the impact of in silico models would bring a revolution in patient care. This chapter has attempted to cover everything, from significance to constraints and difficulties in in silico modeling.

With the increasing prevalence of type 1 and type 2 diabetes, management, particularly for those receiving insulin therapy, becomes a global health concern. Since the advancement of in silico models, diabetes treatment has greatly improved. Computer simulations forecast the insulin dosages needed for bolus and basal infusion based on real-time glucose dynamics. By replicating glucose-insulin dynamics and taking into account factors like age, activity, food intake, insulin resistance, and more, these models—like the UVA/PADOVA simulator—have completely changed the way people with diabetes are treated. These algorithms not only forecast insulin dosages but also help with medication customization, thereby improving patient outcomes. When factors like stress and physical activity are taken into account, in silico models offer vital information on the ideal basal and bolus insulin dosages. Additionally, even in the absence of exact insulin-to-carbohydrate ratios, reinforcement learning models have demonstrated potential in predicting bolus insulin doses, increasing the accuracy of insulin delivery. Despite improvements, data validation, device integration, and the requirement for individualized care continue to pose challenges to these models' ability to accurately forecast insulin dosages. Several in silico modeling techniques, their uses, and the significance of tailored care in maximizing diabetes management are covered in this research.

Objective: Quinoline-fused heterocycles demonstrate various biological activities, including antibacterial, antifungal, anticancer and anti-inflammatory. However, their therapeutic potential in the context of diabetes remains underexplored. This research focuses on evaluating the α-glucosidase inhibitory potential of benzo[g]quinoline derivatives. Methods: An efficient synthetic route was established to generate a series of 3-((E)-((E)-benzylidene)hydrazineylidene)methyl)-2-chlorobenzo[g]quinoline derivatives 6a–6o. Structural elucidation of the newly synthesized compounds was performed using 1H and 13C NMR spectroscopy, FT-IR spectroscopy, mass spectrometry, and elemental analysis. The compounds were subsequently evaluated for their α-glucosidase inhibitory activity in vitro. Results and Discussion: All synthesized compounds exhibited α-glucosidase inhibitory activity. Notably, derivatives 6c, 6g, and 6h demonstrated significantly higher potency, with IC50 values of 16.40 ± 0.60, 6.80 ± 0.20, and 9.60 ± 0.30 µM, respectively, compared to the standard drug acarbose (IC50 = 38.45 ± 0.80 µM). Conclusions: The findings highlight the promising therapeutic potential of benzo[g]quinoline derivatives as α-glucosidase inhibitors, warranting further investigation for the management of diabetes.

Agricultural residues, often burned openly pose environmental challenges but offers opportunities for valorization into functional materials. Converting such residues into biochar supports circular economy principles. Here, cotton stalk (CS) was converted into phosphate-modified biochar (PMCS) via pyrolysis at 350, 550, and 800°C. Response Surface Methodology (RSM) was applied to the adsorption process, treating pyrolysis temperature as a categorical factor in a rotatable CCD. PMCS was characterized by Brunauer-Emmett-Teller (BET), Scanning Electron Microscopy (SEM), and Fourier Transform Infrared Spectroscopy (FTIR), Point of Zero Charge while adsorption was evaluated through isotherm and kinetic modeling for synthetic textile wastewater containing Eriochrome Black T (EBT), starch, and salts. PCS800 exhibited a BET analysis of 750 m² per gram of biochar and achieved nearly 77% COD reduction at 33 min and 6.43 g/L for synthetic wastewater, while 60% with complete decolorization for real effluent. The optimum removal followed Langmuir behaviour (qmax=90.2 mg/g, KL= 0.049 L/mg) with pseudo-second-order kinetics, reflecting micropore filling by starch. Overall, this study establishes a circular economy pathway by valorizing CS into an efficient adsorbent, mitigating residue burning while offering scalable potential for textile wastewater treatment.

Cryopreservation has been a revolutionary tool of assisted reproductive techniques to preserve valuable germplasm. The study was performed to measure the cleavage rate and the effect of cryopreservation techniques (slow freezing and vitrification) on in vitro produced buffalo embryos. Cumulus oocytes complexes were recovered by manual aspiration method. In vitro maturation (IVM), fertilization (IVF), and culture (IVC) were performed using commercially available Vitrogen (Brazil) media in benchtop incubator having 5% O2, 5% CO2, and optimum N2 with 90% humidity. Total 29 sessions were performed during November 2022 to June 2023 and 655 (23 ± 1.21 ovaries/session) ovaries were processed. Total 2515 follicles were observed including 1387 (55.15; 48.0 ± 1.81; 55.15%) small, 982 (34.0 ± 1.27; 39.05%) medium and 146 (5.0 ± 2.25; 5.8%) large follicles. Total 1679 COCs were recovered from 2515 follicles with recovery rate of 66.75%. Total 1640 COCs were used for IVM, IVF and IVC. After 72 h of the IVC 63.1 % (1015/1640) cleavage rate were observed and on day six after IVC 20 % (295/1640) blastocyst rate were observed. Blastocysts of grade I & II were randomly assigned either fresh, vitrified and slow freezing group. The re-expansion rate in frozen-thaw and vitrified-devitrified group blastocysts were observed at different time intervals. The total re-expansion rate of frozen-thawed BLs was 91.46%, which was significantly lower than 96% of vitrified-devitrified BLs. Further to study the hatching rate fresh (control) group was included and hatching were observed at 2, 12, and 24 hrs. Apoptosis rate were assessed using the TUNEL assay. TUNEL assay revealed a significant apoptosis in frozen-thaw blastocysts compared to vitrified-devitrified group (13.73 ± 0.67 vs 8.99 ± 0.71). Hence, vitrification is more competent method for cryopreservation of in vitro produced transferable buffalo embryos.

Pregnancy requires maternal immune tolerance of the semi-allogeneic fetus without compromising host defense. Myeloid-derived suppressor cells (MDSCs) have emerged as key regulators of maternal fetal tolerance, but their role in early miscarriage (EM), recurrent pregnancy loss (RPL), and recurrent implantation failure (RIF) remains incompletely defined. To systematically evaluate the role of MDSCs in EM, RPL, and RIF and assess their potential as biomarkers and therapeutic targets in implantation failure and pregnancy loss. A systematic review in accordance with PRISMA guidelines. Searches were conducted in Google Scholar up to April 13, 2025, using the terms "Myeloid Derived Suppressor Cells," "in vitro fertilization," "early miscarriage," "pregnancy loss," and "implantation failure." Studies were eligible if they quantified MDSCs in peripheral blood or endometrial samples of women with EM, RPL, or RIF and animal-only studies. Reviews, abstracts, and inaccessible full texts were excluded. Of 70 records identified, 11 met inclusion criteria (seven human, five murine, one has included human samples and murine models). In human studies, reduced granulocytic MDSCs (G-MDSCs) were strongly associated with EM and RPL, correlating with low estradiol/progesterone, impaired STAT3 signaling, and a Th1-dominant cytokine milieu. Findings in RIF were heterogeneous: some reported decreased polymorphonuclear MDSCs with functional impairment, while others observed elevated monocytic MDSCs (M-MDSCs) with diminished suppressive capacity, suggesting dysfunctional or compensatory expansion. Placental enrichment of G-MDSCs demonstrated their tolerogenic role in situ, promoting Treg induction and macrophage polarization. Murine models confirmed it as the cause since MDSC depletion abolished pregnancy, while progesterone-STAT3-ROS signaling supported their expansion and suppressive function. Adoptive MDSC transfer partially rescued fetal resorption in abortion-prone models. MDSCs are central to maternal fetal tolerance, and their dysregulation contributes to EM, RPL, and RIF. Human and animal data support their potential as predictive biomarkers and therapeutic targets in implantation failure. Standardization of MDSC phenotyping and mechanistic studies of subset-specific functions are warranted to advance clinical translation.