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Underwater Wireless Sensor Networks (UWSNs) are established by Autonomous Underwater Vehicles (AUVs) or static Sensor Nodes (SN) that collect and transmit information over the underwater environment. Localization plays a vital role in the effective deployment, navigation and coordination of these nodes for many applications, namely underwater surveillance, underwater exploration, oceanographic data collection and environmental monitoring. Due to the unique characteristics of underwater transmission and acquisition, this is a fundamental challenge in underwater networks. However, localization in UWSNs is problematic due to the unique features of underwater transmission and the harsh underwater environment. To address these challenges, this paper presents an Improved Grey Wolf Optimization Based Node Localization Approach in UWSN (IGWONL-UWSN) technique. The presented IGWONL-UWSN technique is inspired by the hunting behavior of grey wolves with the Dimension Learning-based Hunting (DLH) search process. The proposed IGWONL-UWSN technique uses the Improved Grey Wolf Optimization Based (IGWO) algorithm to calculate the optimal location of the nodes in the UWSN. Moreover, the IGWONL-UWSN technique incorporates the DLH search process to improve the convergence and accuracy. The simulation results of the IGWONL-UWSN technique are validated using a set of performance measures. The simulation results show the improvements of the IGWONL-UWSN method over other approaches with respect to various metrics.

Abstract The Trust-Aware Aggregation Authentication Protocol for SIoT Networks is a security process intended for SIoT platforms. It concentrates on ensuring the reliability of communication and data aggregation between interrelated IoT devices. This protocol deploys authentication systems for verifying the identities of devices and integrates trust-aware mechanisms to estimate the trustworthiness of data exchanged from the social environment of SIoT. By establishing a trustworthy and secure communication structure, this protocol improves the entire integrity and security of SIoT networks, addressing potential vulnerabilities connected with social communications between IoT devices. Therefore, this study develops an enhanced Trust Management using Locally Weighted Salp Swarm Algorithm with Deep learning (ETM-LWSSADL) technique for SIoT Networks. The ETM-LWSSADL technique computes direct and indirect trust values and is assessed depending upon different weighing factors for maximizing the application performance and creating a secure data transmission process. During authentication process, when the SIoT device with total trust value (TTV)is not greater than the threshold value (THV) or authentication token is invalid, the gateways then disregard the node. Besides, bidirectional gated recurrent unit (BiGRU) model is applied to generate a THV on collected traffic data. Moreover, the ETM-LWSSADL technique exploits the LWSSA technique for optimum hyper parameter selection of the BiGRU algorithm. To highlight the enhanced performance of the ETM-LWSSADL methodology, an extensive range of simulations can be involved.

Body fluids carry several biomarkers and genetic material that enable the detection of carcinogenesis and tumor metastasis. Owing to this, liquid biopsy is gaining importance and entering clinical practice as an adjunct modality to the current standard of practice in cancer detection. Liquid biopsy involving specimens such as urine is non-invasive and has biomarkers reflecting the tumor microenvironment. We investigate the normal and altered levels of cellular metabolic by-products in liquid phantoms and demonstrate their photon-induced excited-state interaction behaviour for potential diagnostic applications. Short-span temporal analysis of metabolic by-products FAD and NADH in liquid phantoms with fiber optic fluorescence spectroscopy is carried out. The mixed liquid phantom of FAD and NADH, showed excited state interactions that manifested as simultaneous inverse variation in the fluorescence emission from FAD and NADH in varying pH environments. Linear discriminant analysis of the time-varying integrated fluorescence intensity resulted in a 100% accuracy in classifying liquid samples between high and low metabolite concentrations. An extension of application of the experiment model for analysis of body fluids such as urine is also discussed.

Recently, the Underwater Wireless Sensor Network (UWSN) with movable nodes has been launched because it has a lot of potential uses in aquatic science and is getting a lot of attention from researchers. Because there are so many more possible underwater uses, it is important to make sure that signals can get from one underwater point to another. Because of the long lags in signal transmission and the changing speed of sound underwater, it is hard and not possible to use the usual localization method in UWSN. Node localization (NL) in UWSN tries to figure out where new nodes are by using known nodes. The correctness of location can have a big effect on how well a UWSN works. UWSN has a lot of trouble with precise NL. When it comes to WSN, NL problems mean figuring out where unknown sensor nodes (SNs) are. This shows how important it is to have a perfect NL system. The Enhanced Dwarf Mongoose Optimization based Node Localization Scheme (EDMO-NLS) for UWSN is being worked on in this study. The scout group, the alpha group, and the babysitters are the three social groups of dwarf mongooses that were used in the suggested method. The family hunts as a unit, and the main female starts hunting. This sets the sleeping mounds, the road for hunting, and the distance that is covered. The EDMO-NLS method shown here finds nodes whose locations are unknown in UWSN. The modeling results showed that the proposed model worked better than existing methods. Based on the findings and the discussion, it is clear that the suggested method has shown the best localization success in UWSN.

Due to advancements in the technology, video transmission is a key feature in several applications. The transmission of the video from the source to the sink is quite different from the transmission of images-based data. The transmission of the video over the wireless sensor network is not an easy task with the available protocols. They have several disadvantages related to the energy efficiency and the reliability. Novel architecture namely high-quality video transmission architecture has been proposed in this paper. This is an energy efficient architecture. To conserve the energy during the transmission, this architecture does not support retransmission of the packets. But the dropping of the packets helps in improving the reliability and the life time of the network. This architecture majorly involves three layers namely the application layer, the network layer and the transport layer. The transmission of the data packets is based on the priority levels. Moving Picture Experts Group (MPEG - 2) technologies is used in the proposed work. Two different frames namely the key frame and the variant frame are used to prioritize the packets. The data packets with the highest priority from the variant frame is transmitted first and then followed by the data packets of the key frame. The data is segmented into smaller units and discrete cosine transform is applied over each unit. The inter link between the transport layer, application layer and the network layer is analysed by means of the state diagram. The results have been tabulated and depicted by means of graphical representations. Comparative analysis has been made between the proposed high quality video transmission architecture and the diversified architecture. The proposed method has been found to have produced comparatively better results and possesses a high quality video transmission with enhanced Peak Signal to Noise Ratio (PSNR) and reduces energy consumption.

Engagement and emotion are critical components that significantly influence a reader’s experience during a reading task. Despite the crucial role of engagement and emotions in shaping our reading experience, accurately tracking these dynamic states during actual reading remains a significant challenge. This study bridges this gap by detecting engagement and emotion levels during a reading task by leveraging the power of state-of-the-art deep learning models and investigating the correlations between the engagement levels and emotions. An experiment was conducted involving 18 university students reading 14 documents followed by a questionnaire to rate their levels of engagement, valence, and arousal after reading each document. A Tobii 4C eye-tracker with a pro license along with an Empatica E4 wristband were utilized to record behavioral and physiological data from the participants. A range of deep learning models were utilized for computing the engagement, valence, and arousal values, employing both user-independent and user-dependent methods. Our investigation revealed distinct yet complementary strengths in two deep learning models: Transformer excelled in user-independent detection of engagement and emotion with an accuracy of 80.38% (engagement), 71.28% (arousal) and 73.98% (valence) while ResNet shined in the user-dependent setting with an accuracy of 93.56% (engagement), 90.62% (arousal) and 88.70% (valence) which highlights the interplay between individual differences and reading dynamics. Intriguingly, we observed strong, document-specific correlations between engagement and emotion states, suggesting that different texts evoke unique affective responses. We developed an interactive dashboard visualizing predicted engagement and emotions, offering real-time feedback and personalized learning possibilities. The dashboard features an engagement gauge that displays the reader’s level of engagement based on predicted class probabilities, and an emotion emoji serving as a visual cue that illustrates the predicted emotional state of the reader. This technology can inform the design of dynamic interfaces that adjust to individual reading styles and emotional responses, potentially enhancing comprehension and involvement.

Abstract The sub-tropical, flat, peninsular region of Florida is subject to a unique climate with extreme weather events that impact agriculture, public health, and management of natural resources. Meteorological data at high temporal resolutions especially in tropical latitudes are essential to understand diurnal and semi-diurnal variations of climate, which are considered as the fundamental modes of climate variations of our Earth system. However, many meteorological datasets contain gaps that limit their use for validation of models and further detailed observational analysis. The objective of this paper is to apply a set of data gap filling strategies to develop a gap-free dataset with 15-minute observations for the sub-tropical region of Florida. Using data from the Florida Automated Weather Network (FAWN), methods of linear interpolation, trend continuation, reference to external sources, and nearest station substitution were applied to fill the data gaps depending on the extent of the gap. The outcome of this study provides continuous, publicly accessible surface meteorological observations for 30 FAWN stations at 15-minute intervals for years 2005–2020.

Abstract The use of nanotechnology has the potential to revolutionize the detection and treatment of cancer. Developments in protein engineering and materials science have led to the emergence of new nanoscale targeting techniques, which offer renewed hope for cancer patients. While several nanocarriers for medicinal purposes have been approved for human trials, only a few have been authorized for clinical use in targeting cancer cells. In this review, we analyze some of the authorized formulations and discuss the challenges of translating findings from the lab to the clinic. This study highlights the various nanocarriers and compounds that can be used for selective tumor targeting and the inherent difficulties in cancer therapy. Nanotechnology provides a promising platform for improving cancer detection and treatment in the future, but further research is needed to overcome the current limitations in clinical translation. Graphical Abstract

Aim: Photobiomodulation involves the use of low-level light therapy or near-infrared light therapy found to be useful in the treatment of a wide range of neurological diseases. Objective: The aim is to review the mechanism and clinical applications of photobiomodulation therapy (PBMT) in managing Alzheimer's disease. Methods: To ensure that the consensus statement accurately reflects both the experts' viewpoint and the most recent developments in the field, the expert opinions were recorded and thoroughly reviewed. Results: PBMT elicits reduction of beta-amyloid plaque, restoration of mitochondrial function, anti-inflammatory and antioxidant properties with a stimulation in ATP synthesis. Conclusion: The PBMT could be helpful in patients non-responsive to traditional pharmacological therapy providing significant aid in the management of Alzheimer's disease when introduced into the medical field.

Additive manufacturing (AM) technologies enable near-net-shape designs and demand-oriented material usage, which significantly minimizes waste. This points to a substantial opportunity for further optimization in material savings and process design. The current study delves into the advancement of sustainable manufacturing practices in the automotive industry, emphasizing the crucial role of lightweight construction concepts and AM technologies in enhancing resource efficiency and reducing greenhouse gas emissions. By exploring the integration of novel AM techniques such as selective laser melting (SLM) and laser metal deposition (LMD), the study aims to overcome existing limitations like slow build-up rates and limited component resolution. The study’s core objective revolves around the development and validation of a continuous process chain that synergizes different AM routes. In the current study, the continuous process chain for DMG MORI Lasertec 65 3D’s LMD system and the DMG MORI Lasertec 30 3D’s was demonstrated using 316L and 1.2709 steel materials. This integrated approach is designed to significantly curtail process times and minimize component costs, thus suggesting an industry-oriented process chain for future manufacturing paradigms. Additionally, the research investigates the production and material behavior of components under varying manufacturing processes, material combinations, and boundary layer materials. The culmination of this study is the validation of the proposed process route through a technology demonstrator, assessing its scalability and setting a benchmark for resource-efficient manufacturing in the automotive sector.

In this work, Er-doped BiVO4/BiFeO3 composites are prepared using the sonochemical process with a difference of rare earth loading compositions. The crystallinity and chemical and morphological structure of as-synthesized samples were investigated via X-ray diffraction, Raman scattering, and electron microscopy, respectively. The diffuse reflectance technique was used to extract the optical property and calculate the optical band gap of the composite sample. The piezo-photocatalytic performance was evaluated according to the decomposition of a Rhodamine B organic compound. The decomposition of the organic compound was achieved under ultrasonic bath irradiation combined with light exposure. The Er-doped BiVO4/BiFeO3 composite heterojunction material exhibited significant enhancement of the piezo-photocatalytic activity under both ultrasonic and light irradiation due to the improvement in charge generation and separation. The result indicates that Er dopant strongly affects the phase transformation, change in morphology, and alternation in optical band gap of the BiVO4 matrix. The incorporation of BiFeO3 in the composite form with BiVO4 doped with 1%Er can improve the photocatalytic performance of BiVO4 via piezo-induced charge separation and charge recombination retardment.

This study was conducted for the comparative analysis of antioxidant activity and untargeted metabolomics of dark- and light-colored sour cherry cultivars grown in Canada. Based on our previous study, we selected four cultivars—‘Heimann R’, ‘Gorsemska’, V70142, and ‘Montmorency’—to determine the untargeted metabolites and their role in antioxidant activities. A total of 473 metabolites were identified from four sour cherry genotypes using UPLC–ToF–MS. Untargeted metabolomics revealed the dominant chemical groups present in sour cherries. PCA showed that the diversity in sour cherry metabolites was due to the genotype differences indicating iditol, malic acid, chlorobenzene, 2-mercaptobenzothiazole, and pyroglutamic acid as the predominant contributors. The variable importance in the projection (VIP > 1.0) in partial least-squares–discriminant analysis described 20 biomarker metabolites representing the cherry metabolome profiles. A heatmap of Pearson’s correlation analysis between the 20 biomarker metabolites and antioxidant activities identified seven antioxidant determinants that displayed the highest correlations with different types of antioxidant activities. TPC and TAC were evaluated using the Folin–Ciocalteu method. The total antioxidant activity was performed using three different assays (ABTS, FRAP, and DPPH). This study of correlating metabolomics and antioxidant activities elucidated that the higher nutritional value and biological functions of sour cherry genotypes can be useful for the development of nutraceutical and functional foods.

Background: Advances in kidney transplantation and dialysis have helped millions of people with ESRD. However, cost involved in terms of initial investment, maintenance, training, skilled personnel, subsidies on consumables and drugs add to the long-term cost involved with treatment. Objectives: 1. To study the treatment expenditure, out of pocket expenditure and catastrophic expenditure during Haemodialysis. 2) To study sociodemographic characteristics of ESRD patients on Haemodialysis Methodology: It is a cross sectional study conducted in 2 government and 2 private hospitals among patients with chronic kidney disease who were undergoing haemodialysis for a minimum period of 1 month. Data was collected using preformed questionnaire containing data on socio-demographic variables, illness details, dialysis details, medications and other expenditures. Results: 65.7% of participant gave history of having insurance coverage or any assistance for dialysis. But majority of patients used their savings (69.7%), or gifts (60.2%), sold assets (51.2%), made unsecured loans (23.9%), mortgaged their lands (11.9%). In addition, 97.5% had catastrophic expenditure on dialysis. Out of pocket expenditure for dialysis per month was Rs.8,310 in government institutes and Rs.29,655 in private institute. Among private, it was Rs.11,297 rupees in ECHS patients and Rs.18,642 in other social insurance scheme Conclusion: There is a high out of pocket expenditure among dialysis patients for their session with public private disparity

A series of novel 1,5-diaryl pyrazole derivatives targeting the COX enzyme were designed by combined ligand and structure-based approach. The designed molecules were then further subjected to ADMET and molecular docking studies. Out of 34 designed compounds, the top-10 molecules from the computation studies were synthesized, characterized, and evaluated for COX-2 inhibition and anti-cancer activity. Initially, the target compounds were screened for the protein denaturation assay. The results of the top-five molecules T2, T3, T5, T6, and T9 were further subjected to in vitro COX-2 enzymatic assay and anti-cancer activity. As far as COX-2 inhibitory activity is considered, two compounds, T3 and T5, exhibited the half maximum inhibitory concentration (IC50) at 0.781 µM and 0.781 µM respectively. Further, the two compounds T3 and T5, when evaluated for COX-1 inhibition, exhibited excellent inhibitory activity with T3 IC50 of 4.655μM and T5 with IC50 of 5.596 μM. The compound T5 showed more significant human COX-2 inhibition, with a selectivity index of 7.16, when compared with T3, which had a selectivity index of 5.96. Further, in vitro anti-cancer activity was screened against two cancer cell lines in which compounds T2 and T3 were active against A549 cell lines and T6 was active against the HepG2 cell line. Stronger binding energy was found by comparing MM-PBSA simulations with molecular docking, which suggests that compounds T3 and T5 have a better possibility of being effective compounds, in which T5 showed higher binding affinity. The results suggest that these compounds have the potential to develop effective COX-2 inhibitors as anti-cancer agents.

Introduction: The clinical interview (CI) based diagnosis has more validity than the structured interview schedules based diagnosis. Hence, the epidemiological studies by clinician’s evaluation would be more valuable. To date, there is no clinical epidemiological studies by psychiatrists’ CIs of the primary care patients in India, especially for substance use and psychotic disorders. Objectives: To understand the prevalence of selected psychiatric disorders among patients of primary health centers (PHCs) based on the psychiatrist’s CI. Materials and Methods: Data collected from a file review of Telepsychiatric On-Consultation Training program (2016–2018) in which 73 in-service primary care doctors are trained in live general consultation of rural PHCs of Mandya district, Karnataka, India. Results: Prevalence of the psychiatric disorders among adult primary care patients was 47.5%. The common mental disorders (CMDs) (35.2%) were most common among them, followed by substance use (9.5%) and psychotic disorders (2.6%). Discussion: This is the first clinical epidemiological study from Indian rural primary health care based on a psychiatrist’s CI. Nearly half of the primary care patients were diagnosed with psychiatric disorders. This study demonstrated the feasibility of conducting such epidemiological studies with available time and resources. This study reported a higher prevalence of psychiatric disorders in rural PHCs.

A dual-band antenna is used for several wireless networks like ISM, WLAN, WiMAX, and WiFi. The antenna's uppermost element is a monopole shape with a rectangular protrusion. Antennas are created in CST. Using a 19-millimetre-wide by 31-millimetre-long FR4 substrate, the antenna is created in a design environment. Due to the SRR printing in the ground and the antenna's defective ground structure, the antenna is able to achieve dual resonance. A split ring resonator printed at the base also helps achieve a second resonance. With the help of a parameter analysis, we can pick the optimal proportions for the design. The antenna resonates at both 2.3 and 5.8 GHz. We construct and test the antenna. The results obtained through simulation are equivalent to those obtained from measurements in terms of s11, gain, and directivity, as well as E-plane and H-plane patterns. Because of its compact size, consistent radiation pattern, dual-band use, and excellent impedance matching and bandwidth, the suggested antenna is an excellent choice for use in ISM networks and other wireless applications.

Arterial lines are routinely used for hemodynamic monitoring and blood sampling in the operating room and in cardiac surgery intensive care unit. The complications related to arterial line insertion are very low; the knowledge of the relevant artery anatomy, skills and the experience of the operator and selection of a right size cannula plays a vital role in reducing morbidity related to arterial line insertion. We describe extensive superficial and deep necrosis of lower limb following arterial cannula insertion in a preterm neonate undergoing arterial switch procedure and discuss measures to prevent such a complication.

Interest in the context of reading holds special significance as it serves as a driving force for learning and education. By understanding and leveraging students’ interests, educators can create more effective and enjoyable learning environments that promote personalized learning experiences, enhanced comprehension, deep understanding, and motivation. A multimodal approach integrating gaze and physiological data could provide a more comprehensive and accurate assessment of interest levels. The goal of this study is to measure the level of interest experienced by users when reading newspaper articles by integrating gaze data and physiological responses. An experiment was conducted which recorded the gaze and physiological data from 13 university students reading 18 newspaper articles collected from the BBC news database. An SMI eye-tracker and an Empatica E4 wristband were used synchronously to capture the user’s eye movements and physiological data. To predict the interest levels of the participants, a manual feature extraction-based approach and a deep learning-based approach were employed. The interest levels were divided into four-class and binary based on the responses from the participants. A CNN-LSTM model using the gaze features outperformed other models in terms of accuracy and F1-score with 52.8% and 51.8 for four-class and 82.3% and 81.7 for binary classification using leave-one-document-out and leave-one-participant-out cross-validation, respectively.

Aim: To analyze the occurrence and correlation of oral manifestations of patients affected by gastro-esophageal reflux disease (GERD), especially with dental erosion. Materials and Methods: With a simple randomization method, a total of 120 patients, GERD-diagnosed patients (group 1, n = 60), based on complaints and reviewed by gastroenterologists through proper history, clinical pictures, and established investigations, and healthy individuals (group 2, n = 60), were enrolled in the study. Oral manifestations such as xerostomia, oral acid/burning sensation, subjective halitosis, dental sensitivity, and dental erosion were evaluated in both groups. The Chi-square test and continuous variables were compared by the Mann–Whitney test and the Kruskal–Wallis test (P value < 0.05, significant). Results: The Mann–Whitney U test on the distribution of the gastric complaints between two groups revealed a significant difference in all the variables. A significant difference was found in the distribution of all the oral manifestations except halitosis and dentinal hypersensitivity between both groups. The Chi-square test between the heartburn and dental erosions revealed a significant association (c2 = 293.761, df = 1, P < 0.001), whereas there was no significant association between heartburn and dentinal hypersensitivity. Conclusion: GERD and dental erosions had no significant correlation, whereas other oral manifestations and mucosal changes were found significant with GERD.

Purpose: This study was conducted to estimate the visual acuity improvement in patients with Leber hereditary optic neuropathy (LHON) with the help of low vision devices (LVDs) and to analyze the types of distant and near LVDs prescribed to the patients with LHON. Methods: A retrospective case review of 74 subjects with LHON who were referred to a low vision care clinic at a tertiary eye center from 2016 to 2019 were recruited. The reason for referral was assessed from the patients' electronic medical records (EMR). Demographic data of the patients, visual acuity status, type of LVD prescribed, and visual acuity improvement with LVD were documented. Results: Out of 74 patients, 91.9% (n = 68) were male, and the median age of patients was 21 (16) years. A 4× monocular telescope was prescribed for 2.7% of patients (n = 2) and SEETV binocular telescope for 1.4% (n = 1) was advised for distance. The most commonly prescribed near LVD was the 6× cutaway stand magnifier for 22 patients (29.7%). Four patients (5.4%) were prescribed with Notex, the most commonly prescribed non-optical LVD. Niki CCTV (12.2%, n=9) was the most commonly prescribed assistive device. The subjects were divided into three groups based on age: group I consisted of those 40 years for the interpretation of visual improvement. There was a statistically significant improvement (group I: P < 0.001, group II: P < 0.0001, group III: P < 0.003) in near vision with help of LVDs in all three groups. Conclusion: The use of LVDs and rehabilitation can help patients with LHON to lead a better life and will be more beneficial.

Black knot (BK) is a deadly disease of European (Prunus domestica) and Japanese (Prunus salicina) plums caused by the hemibiotrophic fungus Apiosporina morbosa. Generally, phytopathogens hamper the balance of primary defense phytohormones, such as salicylic acid (SA)–jasmonic acid (JA) balance, for disease progression. Thus, we quantified the important phytohormone titers in tissues of susceptible and resistant genotypes belonging to European and Japanese plums at five different time points. Our previous results suggested that auxin-cytokinins interplay driven by A. morbosa appeared to be vital in disease progression by hampering the plant defense system. Here, we further show that such hampering of disease progression is likely mediated by perturbance in SA, JA, and, to some extent, gibberellic acid. The results further indicate that SA and JA in plant defense are not always necessarily antagonistic as most of the studies suggest but can be different, especially in woody perennials. Together, our results suggest that the changes in phytohormone levels, especially in terms of SA and JA content due to BK infection and progression in plums, could be used as phytohormonal markers in the identification of BK-resistant cultivars.

Barium metaphosphate glasses (PBaLa) doped with erbium (Er3+) ions have been prepared by melt quenching method and studied their optical, structural characteristics by using FT-IR, absorption, radiative de-excitation spectra, decay curves and up-conversion measurements. Judd-Ofelt (Ωλ, λ = 2,4 and 6) parameters have been determined using the absorption transitions of the Er3+(1.0 mol %)-doped glasses which are in turn taken to predict the radiative characteristics that include branching ratio (βR), radiative emission probability (AR) and lifetime (τR) of some important fluorescent levels of Er3+:glasses. Visible emission spectra measured under 378 nm excitation reveals three emission transitions at 663 (4F9/2 → 4I15/2), 547 (4S3/2→ 4I15/2) and 524 nm (2H11/2 → 4I15/2) corresponding to Er3+ ions. Among these, the green emission at 547 nm is relatively intense. Near-Infrared emissions were measured by exciting at 980 nm which exhibits broad emission at 4I13/2→ 4I15/2 (1.53 µm). The stimulated emission cross-section (σemi), FWHM and gain bandwidth (σemi × FWHM) were predicted to be 13.58 × 10-21 cm−2, 59 nm and 801.2 cm3, respectively, for PBaLaEr1.0 glass. The lifetime of 4I13/2 level has been shortened from 2.53 to 0.8 ms with an increase in Er3+ ions concentration from 0.1 to 2 mol %. NIR to visible up-conversion has also been measured for various concentrations of Er3+-doped PBaLaEr glasses with 980 nm excitation. These findings indicate that the Er3+-doped PBaLaEr glasses can be considered for waveguide laser and optical amplifier applications at 1.53 µm.

Abstract Carrot processing industries produce 25–30% of waste in the form of carrot rejects, peels, and pomace which contain a large amount of high-value bioactive components. Green extraction of the bioactive components from carrot rejects with green solvents using closed-vessel energy-intensive microwave-assisted extraction was the objective of this work. In this work, three experimental studies were implemented. One uses 8 different green solvents for maximum yield of bioactive using green technology, and the other for the optimization of Microwave-assisted Extraction (MAE) parameters to enhance the bioactive components yield. Response Surface Methodology was employed to optimize the processing parameters including temperature, time, solid to solvent ratio, and solvent type. The optimized extraction conditions: treatment temperature of 50 °C for 5 min gave a significantly higher yield of total carotenoids (192.81 ± 0.32 mg carotenoids/100 g DW), total phenolic (78.12 ± 0.35 g GAE/100 g DW), and antioxidants by FRAP (5889.63 ± 0.47 mM TE/100 g DW), ABTS (1143.65 ± 0.81 mM TE/100 g DW), and DPPH (823.14 ± 0.54 mM TE/100 g DW) using a solvent combination of hexane and ethanol (1:3) with solid to solvent ratio of 1:40 (w/v). This green technology in combination with GRAS solvents promoted the best recovery of bioactive from carrot rejects. Moreover, the solid residue remained after the extraction of bioactive components exhibited higher carbon content (46.5%) and calorific value (16.32 MJ/kg), showcasing its potential to be used as an energy source.