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This work evaluated an anaerobic sequencing batch membrane bioreactor (AnSBR-MBR) equipped with waste-based ceramic membranes for treating low-strength real drain wastewater. Two feeding regimes, viz. settled feed (Phase 1) and mixed feed (Phase 2) were compared. The biological performance (chemical oxygen demand (COD) and phosphate (PO43-) removal) and filtration performance (total suspended solids (TSS) removal and membrane fouling) were investigated. The reactor characteristics in terms of solids content, sludge settling behaviour, and extracellular polymeric substances (EPS) were also assessed. In Phase 1, the settled feed (with the absence of particulate organic matter) resulted in low volatile suspended solids (VSS; 0.23 ± 0.15 g/L), causing low COD removal (28.38 ± 8.14%). In the mixed feed regime in Phase 2, VSS increased (1.82 ± 0.60 g/L) due to the organic content in the particulate matter, which gave microorganisms additional food, resulting in increased COD removal (47.42 ± 2.81%); this phase was also characterised by lower membrane fouling because of the lower EPS content. Marginally higher TSS removal was obtained as well in Phase 2 (96.72 ± 3.26%) than in Phase 1 (90.48 ± 8.14%). This work demonstrates that AnSBR-MBR performance is superior with mixed drain wastewater containing suspended solids and thus pre-settling is not recommended. HIGHLIGHTS Feeding strategies are important in the anaerobic treatment of dilute drain wastewater.; Mixed wastewater containing organic particulate matter is recommended as an influent.; Mixed wastewater resulted in higher COD removal and lower membrane fouling.; Waste-based ceramic membranes were successfully field tested.;

Abstract The COVID-19 pandemic came with many setbacks, be it to a country’s economy or the global missions of organizations like WHO, UNICEF or GTFCC. One of the setbacks is the rise in cholera cases in developing countries due to the lack of cholera vaccination. This model suggested a solution by introducing another public intervention, such as adding Chlorine to water bodies and vaccination. A novel delay differential model of fractional order was recommended, with two different delays, one representing the latent period of the disease and the other being the delay in adding a disinfectant to the aquatic environment. This model also takes into account the population that will receive a vaccination. This study utilized sensitivity analysis of reproduction number to analytically prove the effectiveness of control measures in preventing the spread of the disease. This analysis provided the mathematical evidence for adding disinfectants in water bodies and inoculating susceptible individuals. The stability of the equilibrium points has been discussed. The existence of stability switching curves is determined. Numerical simulation showed the effect of delay, resulting in fluctuations in some compartments. It also depicted the impact of the order of derivative on the oscillations.

Abstract The present study was aimed at showing the importance of HPV DNA status and the clinical history of the patients required by the cytologist for accurate reporting. A total of 1250 symptomatic women who attended the gynaecology outpatient department of the Mahavir Cancer Sansthan and Nalanda Medical College, Patna, for pap smear examinations were screened and recruited for the study. Due to highly clinical symptoms out of the negative with inflammatory smears reported, one hundred and ten patients were randomly advised for biopsy and HPV 16/18 DNA analysis by a gynaecologist to correlate negative smears included in the study. Pap smear reports revealed that 1178 (94.24%) were negative for intraepithelial lesions (NILM) with inflammatory smears, 23 (1.84%) smears showed low-grade squamous intraepithelial lesions (LSIL), 12 (0.96%) smears showed high-grade squamous intraepithelial lesions, and 37 (2.96%) smears showed an atypical squamous cell of undetermined significance (ASC-US). A biopsy of 110 out of 1178 (NILM) patients revealed that 15 (13.63%) women had cervical cancer, 29 women had CIN I, 17 women had CIN II + CIN III, 35 women had benign cervical changes, and 14 women had haemorrhages. On the other hand, HPV 16/18 DNA was detected as positive in 87 out of 110. The high positivity of HPV in biopsied cases where frank cervical cancer and at-risk cancer were also observed in the negative smear-screened patients reveals that the HPV status and clinical history of the patients will be quite helpful to the cytologist for accurate reporting, and suggests that a negative HPV DNA result may be a stronger predictor of cervical cancer risk than a negative Pap test.

Abstract In this paper, a compact low-profile dual-band wearable textile antenna is proposed for on-body and off-body communications. The presented antenna works efficiently in the 5G n79 frequency band (4.4 − 5 GHz) and the ISM band (5.725 − 5.875 GHz). The designed antenna has an ultra-wide impedance bandwidth of 2.01 GHz and peak realized gains of 10.5 dBi and 12 dBi at 4.5 GHz and 5.8 GHz, respectively. The antenna has a small footprint (π × 0.3λ 0 2), which is inspired by circular fractal geometry. The performance of the presented wearable antenna is evaluated at various body parts, including the arm, wrist, and chest. The link margin is evaluated in the on-body and off-body communication scenarios, i.e., communication with the implantable antenna and the outside-body antenna, which is 80 dB and 65 dB at 4.5 GHz and 5.8 GHz, respectively. The 1 gm/10 gm specific absorption rate values at 4.5 GHz and 5.8 GHz are 0.12/0.098 and 0.11/0.082, respectively, which are significantly lower than the standard values, making the proposed antenna suitable for modern wearable applications.

Abstract The extracellular matrix (ECM) is a dynamic and complex microenvironment that modulates cell behavior and cell fate. Changes in ECM composition and architecture have been correlated with development, differentiation, and disease progression in various pathologies, including breast cancer [1]. Studies have shown that aligned fibers drive a pro-metastatic microenvironment, promoting the transformation of mammary epithelial cells into invasive ductal carcinoma via the epithelial-to-mesenchymal transition (EMT) [2]. The impact of ECM orientation on breast cancer metabolism, however, is largely unknown. Here, we employ two non-invasive imaging techniques, fluorescence-lifetime imaging microscopy (FLIM) and intensity-based multiphoton microscopy, to assess the metabolic states of cancer cells cultured on ECM-mimicking nanofibers in a random and aligned orientation. By tracking the changes in the intrinsic fluorescence of nicotinamide adenine dinucleotide and flavin adenine dinucleotide, as well as expression levels of metastatic markers, we reveal how ECM fiber orientation alters cancer metabolism and EMT progression. Our study indicates that aligned cellular microenvironments play a key role in promoting metastatic phenotypes of breast cancer as evidenced by a more glycolytic metabolic signature on nanofiber scaffolds of aligned orientation compared to scaffolds of random orientation. This finding is particularly relevant for subsets of breast cancer marked by high levels of collagen remodeling (e.g. pregnancy associated breast cancer), and may serve as a platform for predicting clinical outcomes within these subsets [3–6].

Abstract Background Dental caries (DC) is a multifaceted oral condition influenced by genetic and environmental factors. Recent advancements in genotyping and sequencing technologies, such as Genome-Wide Association Studies (GWAS) have helped researchers to identify numerous genetic variants associated with DC, but their prevalence and significance across diverse global populations remain poorly understood as most of the studies were conducted in European populations, and very few were conducted in Asians specifically in Indians. Aim This study aimed to evaluate the genetic affinity of effect alleles associated with DC to understand the genetic relationship between global populations with respect to the Indian context. Methodology This present study used an empirical approach in which variants associated with DC susceptibility were selected. These variants were identified and annotated using the GWAS summary. The genetic affinity was evaluated using Fst. Results The effect of allele frequencies among different populations was examined, revealing variations in allele distribution. African populations exhibited higher frequencies of specific risk alleles, whereas East Asian and European populations displayed distinct profiles. South Asian populations showed a unique genetic cluster. Conclusion Our study emphasises the complex genetic landscape of DC and highlights the need for population-specific research as well as validation of GWAS-identified markers in Indians before defining them as established candidate genes.

The intricate molecular landscape of cancer pathogenesis continues to captivate researchers worldwide, with Circular RNAs (circRNAs) emerging as pivotal players in the dynamic regulation of biological functions. The study investigates the elusive link between circRNAs and the Transforming Growth Factor-β (TGF-β) signalling pathway, exploring their collective influence on cancer progression and metastasis. Our comprehensive investigation begins by profiling circRNA expression patterns in diverse cancer types, revealing a repertoire of circRNAs intricately linked to the TGF-β pathway. Through integrated bioinformatics analyses and functional experiments, we elucidate the specific circRNA-mRNA interactions that modulate TGF-β signalling, unveiling the regulatory controls governing this crucial pathway. Furthermore, we provide compelling evidence of the impact of circRNA-mediated TGF-β modulation on key cellular processes, including epithelial-mesenchymal transition (EMT), migration, and cell proliferation. In addition to their mechanistic roles, circRNAs have shown promise as diagnostic and prognostic biomarkers, as well as potential molecular targets for cancer therapy. Their ability to modulate critical pathways, such as the TGF-β signalling axis, underscores their significance in cancer biology and clinical applications. The intricate interplay between circRNAs and TGF-β is dissected, uncovering novel regulatory circuits that contribute to the complexity of cancer biology. This review unravels a previously unexplored dimension of carcinogenesis, emphasizing the crucial role of circRNAs in shaping the TGF-β signalling landscape.

Background: Volitionally modifying respiration leads to changes in middle cerebral arterial (MCA) blood flow. The effect of changes in breath rate on MCA blood flow has not been reported. Aims and Objectives: To determine the effect of slow (bumblebee yoga breathing) and fast (high frequency yoga breathing) yoga breathing techniques on MCA blood flow and vagally mediated heart rate variability. Materials and Methods: Thirty participants (mean age ± standard deviation, 27.3 ± 4.2 years) were assessed on 2 separate days practicing either high frequency yoga breathing (HFYB, breath frequency 54.2/min) or slow frequency bumblebee yoga breathing (BBYB, breath frequency 3.8/min) in random order to determine the effects of changes in breath frequency on MCA hemodynamics. Assessments included transcranial Doppler sonography, vagally mediated heart rate variability (VmHRV), and respiration. Results: Both HFYB and BBYB (i) reduced MCA flow velocities, i.e., peak systolic, end diastolic, and mean flow velocities, and (ii) increased MCA pulsatility indices. There was an increase in VmHRV during BBYB based on increased power in high frequency (HF) and low frequency (LF). LF reflects VmHRV for slow breath frequencies. In BBYB the average breath rate was 3.8 breaths/min. In contrast, VmHRV decreased during HFYB (based on reduced HF power; repeated measures analysis of variance, P < 0.05, all cases). Conclusion: Hence, irrespective of the differences in breath frequency, both HFYB and BBYB appear to reduce MCA flow velocities and increase the resistance to blood flow bilaterally, although the VmHRV changed in opposite directions. MCA velocity and pulsatility changes are speculated to be associated with low global neural activity during yoga breathing.

Basically, non-communicable diseases (NCDs) are lifestyle diseases. They cannot be transmitted from one person to another person. Instead, our lifestyle, genetics, and environment influence our susceptibility to various diseases. In India, non-communicable illnesses and injuries are responsible for 52% of fatalities. The burden of non-communicable diseases and the resultant mortality are predicted to increase if the government does not take significant steps to prevent and control NCDs and related risk factors. According to the currently available research, the top causes of illness, disability, and death in India include hypertension, cardiovascular diseases, cancer, diabetes, lung disease, chronic renal disease, trauma, stroke, and chronic obstructive and mental disorders. Since 1980s, the Government of India has assisted the states through several vertical programs to prevent and control NCDs. However, efforts to prevent and control NCDs significantly increased under the 11th plan. New programs were launched on a small scale in a select few districts. The financial burden of NCDs has mostly stayed the same, though based on past experiences, reducing exposure to risk factors requires focusing on health promotion and preventative actions. The public healthcare system must have the tools and talents needed for effective management, early diagnosis, and screening. Effective monitoring systems, integrated management, and public awareness campaigns are required to successfully implement the program and make services available to all national citizens.

Objective: Tuberculosis (TB) is among the most frequent causes of infectious-disease-related mortality. Despite being treatable by antibiotics, tuberculosis often goes misdiagnosed and untreated, especially in rural and low-resource areas. Chest X-rays are frequently used to aid diagnosis; however, this presents additional challenges because of the possibility of abnormal radiological appearance and a lack of radiologists in areas where the infection is most prevalent. Implementing deep-learning-based imaging techniques for computer-aided diagnosis has the potential to enable accurate diagnoses and lessen the burden on medical specialists. In the present work, we aimed to develop deep-learning-based segmentation and classification models for accurate and precise detection of tuberculosis in chest X-ray images, with visualization of infection using gradient-weighted class activation mapping (Grad-CAM) heatmaps. Methods: First, we trained the UNet segmentation model using 704 chest X-ray radiographs taken from the Montgomery County and Shenzhen Hospital datasets. Next, we implemented the trained UNet model on 1,400 tuberculosis and control chest X-ray scans to segment the lung region. The images were taken from the National Institute of Allergy and Infectious Diseases (NIAID) TB portal program dataset. Then, we applied the deep learning Xception model to classify the segmented lung region into tuberculosis and normal classes. We further investigated the visualization capabilities of the model using Grad-CAM to view tuberculosis abnormalities in chest X-rays and discuss them from radiological perspectives. Results: For segmentation by the UNet model, we achieved accuracy, Jaccard index, Dice coefficient, and area under the curve (AUC) values of 96.35%, 90.38%, 94.88%, and 0.99, respectively. For classification by the Xception model, we achieved classification accuracy, precision, recall, F1-score, and AUC values of 99.29%, 99.30%, 99.29%, 99.29%, and 0.999, respectively. The Grad-CAM heatmap images from the tuberculosis class showed similar heatmap patterns, where lesions were primarily present in the upper part of the lungs. Conclusion: The findings may verify our system's efficacy and superiority to clinician precision in tuberculosis diagnosis using chest X-rays and raise the possibility of a valuable setup, particularly in environments with a scarcity of radiological expertise.

Abstract Background Rice bean (Vigna umbellata), an underrated legume, adapts to diverse climatic conditions with the potential to support food and nutritional security worldwide. It is used as a vegetable, minor food crop and a fodder crop, being a rich source of proteins, minerals, and essential fatty acids. However, little effort has been made to decipher the genetic and molecular basis of various useful traits in this crop. Therefore, we considered three economically important traits i.e., flowering, maturity and seed weight of rice bean and identified the associated candidate genes employing an associative transcriptomics approach on 100 diverse genotypes out of 1800 evaluated rice bean accessions from the Indian National Genebank. Results The transcriptomics-based genotyping of one-hundred diverse rice bean cultivars followed by pre-processing of genotypic data resulted in 49,271 filtered markers. The STRUCTURE, PCA and Neighbor-Joining clustering of 100 genotypes revealed three putative sub-populations. The marker-trait association analysis involving various genome-wide association study (GWAS) models revealed significant association of 82 markers on 48 transcripts for flowering, 26 markers on 22 transcripts for maturity and 22 markers on 21 transcripts for seed weight. The transcript annotation provided information on the putative candidate genes for the considered traits. The candidate genes identified for flowering include HSC80, P-II PsbX, phospholipid-transporting-ATPase-9, pectin-acetylesterase-8 and E3-ubiquitin-protein-ligase-RHG1A. Further, the WRKY1 and DEAD-box-RH27 were found to be associated with seed weight. Furthermore, the associations of PIF3 and pentatricopeptide-repeat-containing-gene with maturity and seed weight, and aldo–keto-reductase with flowering and maturity were revealed. Conclusion This study offers insights into the genetic basis of key agronomic traits in rice bean, including flowering, maturity, and seed weight. The identified markers and associated candidate genes provide valuable resources for future exploration and targeted breeding, aiming to enhance the agronomic performance of rice bean cultivars. Notably, this research represents the first transcriptome-wide association study in pulse crop, uncovering the candidate genes for agronomically useful traits.

Abstract The challenge of developing an Android malware detection framework that can identify malware in real-world apps is difficult for academicians and researchers. The vulnerability lies in the permission model of Android. Therefore, it has attracted the attention of various researchers to develop an Android malware detection model using permission or a set of permissions. Academicians and researchers have used all extracted features in previous studies, resulting in overburdening while creating malware detection models. But, the effectiveness of the machine learning model depends on the relevant features, which help in reducing the value of misclassification errors and have excellent discriminative power. A feature selection framework is proposed in this research paper that helps in selecting the relevant features. In the first stage of the proposed framework, t-test, and univariate logistic regression are implemented on our collected feature data set to classify their capacity for detecting malware. Multivariate linear regression stepwise forward selection and correlation analysis are implemented in the second stage to evaluate the correctness of the features selected in the first stage. Furthermore, the resulting features are used as input in the development of malware detection models using three ensemble methods and a neural network with six different machine-learning algorithms. The developed models’ performance is compared using two performance parameters: F-measure and Accuracy. The experiment is performed by using half a million different Android apps. The empirical findings reveal that malware detection model developed using features selected by implementing proposed feature selection framework achieved higher detection rate as compared to the model developed using all extracted features data set. Further, when compared to previously developed frameworks or methodologies, the experimental results indicates that model developed in this study achieved an accuracy of 98.8%.

Cancer poses intricate challenges to treatment due to its complexity and diversity. Ferroptosis and circular RNAs (circRNAs) are emerging as innovative therapeutic avenues amid the evolving landscape of cancer therapy. Extensive investigations into circRNAs reveal their diverse roles, ranging from molecular regulators to pivotal influencers of ferroptosis in cancer cell lines. The results underscore the significance of circRNAs in modulating molecular pathways that impact crucial aspects of cancer development, including cell survival, proliferation, and metastasis. A detailed analysis delineates these pathways, shedding light on the molecular mechanisms through which circRNAs influence ferroptosis. Building upon recent experimental findings, the study evaluates the therapeutic potential of targeting circRNAs to induce ferroptosis. By identifying specific circRNAs associated with the etiology of cancer, this analysis paves the way for the development of targeted therapeutics that exploit vulnerabilities in cancer cells. This review consolidates the existing understanding of ferroptosis and circRNAs, emphasizing their role in cancer therapy and providing impetus for ongoing research in this dynamic field.

Due to the complex functioning of Smart Healthcare Systems (SHS), many security concerns have been raised in the past. It provisions the attackers to hamper the working of SHS in a variety of ways, e.g., injection of false data to replace vital signs, tampering of medical devices to prevent informing critical situations, etc. In this work, a novel ML-based framework, i.e., SmartHealth is proposed to secure IoMT devices in SHS. SmartHealth watches the vital signs gathered through different IoMT to analyze the change in various body activities to differentiate between normal activities and dangerous security attacks. The performance of the SmartHealth is also analyzed for three different dangerous attacks. During performance analysis, it has been observed that SmartHealth can identify wicked activities in IoMT 92% times accurately with an F1-score of 90%.

Abstract Breast cancer, a global health concern predominantly affecting women, recorded 2.3 million new cases and 685,000 deaths in 2020. Alarmingly, projections suggest that by 2040, there could be over 3 million new cases and 1 million deaths. To assess breast cancer prevalence in 24 rural villages within a 60 km radius of NIMS Hospital, Tala Mod, Jaipur, Rajasthan, North India 303,121. A study involving 2023 participants conducted initial screenings, and positive cases underwent further tests, including ultrasound, mammography, and biopsy. SPSSv28 analysed collected data. Among 2023 subjects, 3 screened positive for breast lumps. Subsequent clinical examination and biopsy identified 1 normal case and 2 with breast cancer, resulting in a prevalence proportion of 0.0009 or 98 per 100,000. This study helps fill gap in breast cancer prevalence data for rural Rajasthan. The results highlight a concerning prevalence of breast cancer in the rural area near NIMS hospital, emphasizing the urgent need for increased awareness, early detection, and better healthcare access. Challenges like limited resources, awareness programs, and delayed diagnosis contribute to this high incidence. To address this, comprehensive approach is necessary, including improved screening programs and healthcare facilities in rural areas. Prioritizing rural healthcare and evidence-based strategies can reduce the burden of breast cancer and improve health outcomes.

Abstract The present study was conducted to assess the impact of non-encapsulated, air-dried microencapsulated, and lyophilized microencapsulated probiotics in indigenous cattle calves (Bos indicus). Twenty-four (5–7 days old) indigenous cattle calves were selected and assigned into four groups, with six calves in each as follows: control (CON), fed milk and basal diet alone, and treatment groups supplemented with non-encapsulated (NEC), air-dried microencapsulated (AEC) and lyophilized microencapsulated (LEC) probiotic L. reuteri SW23 at 108 CFU/head/day in skim milk as a carrier provided for 60 days. The animals were divided into four groups, adopting a complete randomized design, and the effects were considered significant at p ≤ 0.05. Probiotics supplementation increased (p

Abstract This paper proposes a circularly polarized ultra-thin flexible antenna with a flexible rectifier and power management unit (PMU) for smartwatch/wristband applications. The flexible antenna is compact (0.17λ 0 × 0.20λ 0 × 0.0004λ 0) and has a stepped ground plane. A parasitic element is used at the substrate bottom to reduce the specific absorption rate (SAR) and enhance the gain up to 3.2 dBi, at the resonating frequency of WLAN/Wi-Fi (2.45 GHz). The SAR of the proposed design is also analysed at the resonating frequency, and it satisfies the guidelines of the International Commission on Non-Ionizing Radiation Protection (ICNIRP) and IEEE C95.1–2019 human safety standards. An impedance matching circuit is used between the antenna and the RF energy harvester to improve conversion efficiency. Polarization mismatch is avoided with the help of circular polarization, achieved by tuning stubs of size 0.02λ 0 × 0.044λ 0. The integration of the antenna and rectenna results in a good conversion efficiency of 78.2% at − 5 dBm of input power with a load resistance of 2 KΩ. The availability of RF signals allows the user to charge the smartwatch/wristband by connecting the PMU circuit with the RF energy harvester.

Abstract We present a temporary keyword search over sensitive and confidential health data in a cloud environment. The cloud constitutes a semi-trusted domain, making it necessary for data owners to secure their data before outsourcing it through techniques like encryption. Attribute-based keyword search techniques tend to perform a search operation using a search token generated by an authorized user. These search tokens can lead to serious privacy threats, as they can extract all ciphertexts that may have been generated along with their keyword. Therefore, restricting search tokens to extract ciphertexts generated within a time interval is a more promising solution. In this paper, we present a novel ciphertext policy fine-grained temporary keyword that prevents the misuse of these search tokens. Further, it mitigates the risk of insider threats within healthcare organizations by limiting the window of opportunity for unauthorized access to minimum. To assess the security, our proposed scheme is formally proven to be secure against Selectively Chosen Keyword Attacks in the generic bilinear group model. Additionally, we demonstrate that the encryption algorithm’s complexity is linear in relation to the number of attributes. Our scheme’s significance and practicality are revealed by the performance evaluation.

The biotic and abiotic stresses cause a significant decline in the yield and fruit quality traits, including antioxidants and minerals, of bitter gourd when grown in open fields. Protected cultivation technology has emerged to minimize such stresses. We investigated the effect of diverse environments (hi-tech greenhouse, naturally ventilated polyhouse, insect-proof net-house, and open field) and breeding lines on earliness, yield potential, antioxidant activities, and dietary nutrients. In the GYT analysis, 12 treatment combinations involving four growing environments and three breeding lines of bitter gourd were examined. The 3-year study suggested that the cultivation of bitter gourd crops in an insect-proof net house (NH) showed superior performance in earliness, yield-attributing traits, antioxidant activities, and dietary nutrients, followed by a naturally ventilated polyhouse (NP). However, NH was on par with NP and significantly better than the open-field-grown crop. The GYT biplot analysis highlighted that the combinations of NH and Pusa Rasdar outperformed and were the most stable treatments for all the traits investigated, followed by NH in conjunction with S32 and S57 lines. This study suggests that growing bitter gourd in protected environments is the optimal strategy to achieve early market prices and improve the yield and nutritional quality of the fruits.

Asynchronous interconnection is essential for integrating AC networks operating at different frequencies, typically 50 Hz and 60 Hz. This need arises from distributed power generation methods, including offshore renewable sources and diverse regional grid configurations. Advanced strategies are required to overcome these frequency differences and ensure uninterrupted power transfer.High-Voltage Direct Current (HVDC) transmission systems facilitate efficient power exchange, enhancing grid reliability and stability. This study focuses on optimizing the Proportional-plus-Integral (PI) controller parameters within a 20 MVA Voltage Source Converters (VSC)-based HVDC system to enable asynchronous interconnection between offshore and onshore AC networks. The offshore VSC regulates active and reactive power, while the onshore VSC controls DC voltage and reactive power. A vector control approach with symmetric optimum PI tuning is proposed for a comprehensive performance assessment of the VSC-based HVDC transmission system.The effectiveness of the tuned PI controller parameters is evaluated through four test cases using MATLAB/Simulink for offline simulation and Typhoon HIL604 for real-time validation. These cases involve abrupt changes in reference active and reactive power for the offshore VSC; and in reference reactive power and DC voltage for the onshore VSC. Results demonstrate rapid and satisfactory dynamic performance across all test cases, as evidenced by offline simulations and real-time validation.The validation highlights the effectiveness of the proposed control design with symmetric optimum PI tuning, confirming its ability to enhance the overall performance of the HVDC transmission system for efficient asynchronous interconnection.

This study aimed to improve the stability and prolonged gefitinib release from the nanoliposomes. Nanoliposomes were prepared by reverse-phase evaporation and optimized using Box-Behnken design to investigate the influence of sonication time (X1), tween 80 / soya phosphatidylcholine ratio (X2), and cholesterol / soya phosphatidylcholine ratio (X3) on nanoliposomes. Optimized nanoliposomes were quasi-spherical shaped, with a mean dimension of 93.2 nm and an encapsulation efficiency of 87.56±0.17 %. Surface decoration of the optimized batch was done using different concentrations of chitosan. The optimal chitosan concentration required to adorn the surface of nanoliposomes was 0.01 %. In comparison to unadorned nanoliposomes (82.16±0.65 %), adorned nanoliposomes (78.04±0.35 %) released the drug consistently over 24 h via Fickian diffusion. The IC50 values for surface-adorned nanoliposomes in A549 and H1299 cells were 6.53±0.75 and 4.73±0.46 µM, respectively. Cytotoxicity of the surface-decorated nanoliposomes may be due to their higher zeta potential and prolonged drug release. At 4°C, adorned and unadorned nanoliposomes are most stable. In conclusion, the developed nanoliposomes may offer a new path for melanoma clinics.

Summary: Mitochondrial ribosomes (mitoribosomes) have undergone substantial evolutionary structural remodeling accompanied by loss of ribosomal RNA, while acquiring unique protein subunits located on the periphery. We generated CRISPR-mediated knockouts of all 14 unique (mitochondria-specific/supernumerary) human mitoribosomal proteins (snMRPs) in the small subunit to study the effect on mitoribosome assembly and protein synthesis, each leading to a unique mitoribosome assembly defect with variable impact on mitochondrial protein synthesis. Surprisingly, the stability of mS37 was reduced in all our snMRP knockouts of the small and large ribosomal subunits and patient-derived lines with mitoribosome assembly defects. A redox-regulated CX9C motif in mS37 was essential for protein stability, suggesting a potential mechanism to regulate mitochondrial protein synthesis. Together, our findings support a modular assembly of the human mitochondrial small ribosomal subunit mediated by essential supernumerary subunits and identify a redox regulatory role involving mS37 in mitochondrial protein synthesis in health and disease.

Small cell lung cancer (SCLC) is characterized by early metastatic dissemination and rapid emergence of chemoresistance resulting in a very dismal prognosis. SCLC tumors are characterized by nearly universal biallelic inactivation of TP53 and RB1 genes and are classified into four molecular subtypes based on the expression of lineage-specific transcription factors. The integration of information encoded by the coding and non-coding genome has significantly improved our understanding of the contribution of various non-coding RNAs (ncRNAs), such as long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs), in the pathogenesis of SCLC. This has led to the concept of competing endogenous RNAs (ceRNAs) where the presence of the same miRNA response elements in one or more coding and ncRNAs may result in them competing for the same miRNA. Several studies have looked at the role of lncRNAs and circRNAs as ceRNAs by constructing ceRNA regulatory networks (ceRNETs). In this review, we discuss the role of ceRNETs in regulating various cancer hallmarks, including cell proliferation, invasion, migration, EMT, apoptosis, and chemoresistance of SCLC cells. We also discuss the potential of lncRNAs and circRNAs as biomarkers for diagnosis, prognosis, and predicting chemoresistance of SCLC.

In this work, the closed-form analytical solutions have been generated for the complex coupled Higgs field equation through newly two efficient techniques, namely the auxiliary equation method and the extended Sinh-Gordon expansion approach. The equation under consideration introduces a quantum field, often referred to as the Higgs field, to elucidate the mechanism responsible for generating mass in gauge bosons. The approaches used achieve an extensive variety of solutions, including rational functions, hyperbolic functions, exponential functions, trigonometric functions, and Jacobian elliptical functions. Moreover, to understand the properties of the attained solutions, combined 3D-graphics and contour plots are demonstrated for specified parametric values. In particular, it has been extensively discussed that wave position and category changes with respect to different parameters for some solutions. Various attractive soliton-like solutions have been extracted, such as bell-shaped, travelling waves, periodic solitary waves, singular kink-shaped solitons, and many others. All derived solutions are substituted into the original model to ensure their accuracy. The derived solitons can be employed to investigate numerous complex phenomena associated with this model. Soliton-like solutions and travelling waves are incredible phenomena seen in a variety of domains of physics, including nonlinear waves, nonlinear optics, nonlinear dynamics, quantum physics, dusty plasma physics, engineering physics, and other nonlinear sciences fields.

Implementing the Montreal Protocol has limited the use of conventional refrigerants and has led industries to find optimal or economical eco-friendly refrigerants to reduce environmental hazards. The present study analyzes an N2O-based cascade refrigeration system for achieving ultralow cooling temperatures using different eco-friendly refrigerants with low GWP and ODP in a high-temperature cycle. 3E (Energy, Exergy, and Economy) analysis of a cascade refrigeration system using eco-friendly refrigerants such as R290, R1270, RE170, R600, R600a, HFE7100, and HFE7000 in the upper cycle and N2O in the lower cycle was conducted. The R744A/R600 pair performed best among the other refrigerant pairs due to its lower discharge pressure and compression ratio. The refrigerant pair R744A/R600 results in a higher cascade cycle COP of approximately 0.87, with 48 % exergetic efficiency, while the refrigerant pair R41/HFE7100 has the lowest COP (0.68) and lowest exergetic efficiency (42 %). The minimal operational cost varies from 73006 to 76907 USD per annum for refrigerant pair R744A/R600, while for the other pairs, the cost varies from 98625 USD to 114674 USD. The R744A/R600 refrigerant pair provides COP values that are 1.38–5.38 % greater than the others, with a 1.01–3.45 % variation in exergy efficiency.

Pyrolysis conversion offers the advantages of significant waste reduction and potential energy recovery. This work examined the potential of combining plastic and agricultural wastes as pyrolysis feedstocks. The mixture of waste low-density polyethylene and Pongamia pinnata seeds was analysed using differential and thermogravimetric methods. In addition to the Coats-Redfern (CR) method, Kissinger-Akahira-Sunose (KAS), Flynn-Wall-Ozawa (FWO), Friedman (FRM), and Kissinger (KN) model-free methods were also applied to calculate the kinetic parameters. The apparent activation energy (Ea) calculation demonstrated that the co-pyrolysis conversion required Ea values of 125–154 kJ mol−1. The artificial neural network (ANN) model was considered to validate thermogravimetric data. The R2 values were near unity in training, validation, and testing conditions, with the minimum possible value for mean square error obtained for the considered heating rates. The Pongamia pinnata seeds and waste plastic mixture could surely be utilized to lessen environmental degradation, add value to leftover seeds and waste low-density polyethylene by extracting fuel for transportation and other commercial activities, and produce industrial chemicals, as found through the kinetic modelling, thermodynamic parameters, and ANN modelling.

This research paper investigates the Kadomtsev-Petviashvii-Benjamin-Bona-Mahony equation. The new Kudryashov and generalized Arnous methods are employed to obtain the generalized solitary wave solution. The phase plane theory examines the bifurcation analysis and illustrates phase portraits. Finally, the external perturbation terms are considered to reveal its chaotic behavior. These findings contribute to a deeper understanding of the dynamics of the Kadomtsev-Petviashvii-Benjamin-Bona-Mahony wave equation and its applications in real-world phenomena.

Abstract Nanotechnology appears to be a promising tool to redefine crop nutrition in the coming decades. However, the crucial interactions of nanomaterials with abiotic components of the environment like soil organic matter (SOM) and carbon‒sequestration may hold the key to sustainable crop nutrition, fortification, and climate change. Here, we investigated the use of sugar press mud (PM) mediated ZnO nanosynthesis for soil amendment and nutrient mobilisation under moderately alkaline conditions. The positively charged (+ 7.61 mv) ZnO sheet-like nanoparticles (~ 17 nm) from zinc sulphate at the optimum dose of (75 mg/kg blended with PM (1.4% w/w) were used in reinforcing the soil matrix for wheat growth. The results demonstrated improved agronomic parameters with (~ 24%) and (~ 19%) relative increases in yield and plant Zn content. Also, the soil solution phase interactions of the ZnO nanoparticles with the PM-induced soil colloidal carbon (− 27.9 mv and diameter 0.4864 μm) along with its other components have influenced the soil nutrient dynamics and mineral ecology at large. Interestingly, one such interaction seems to have reversed the known Zn-P interaction from negative to positive. Thus, the study offers a fresh insight into the possible correlations between nutrient interactions and soil carbon sequestration for climate-resilient crop productivity.

This review delves into the pivotal role of the long non-coding RNA NEAT1 in cancer biology, particularly in lung cancer (LC). It emphasizes NEAT1's unique subcellular localization and active involvement in gene regulation and chromatin remodeling. The review highlights NEAT1's impact on LC development and progression, including cell processes such as proliferation, migration, invasion, and resistance to therapy, positioning it as a potential diagnostic marker and therapeutic target. The complex web of NEAT1's regulatory interactions with proteins and microRNAs is explored, alongside challenges in targeting it therapeutically. The review concludes optimistically, suggesting future avenues for research and personalized LC therapies, shedding light on NEAT1's crucial role in LC.

Introduction: Access to oral healthcare is limited in rural areas, resulting in disparities in oral health services. Primary health centers (PHCs) are essential for providing integrated oral healthcare to rural populations. This study examines the patterns, barriers, and utilization of oral healthcare at PHCs in Rohtak district, Haryana. Materials and Methods: In this 6-month household cross-sectional study, data were collected from a sample of 600 participants residing in rural areas under the jurisdiction of three randomly selected PHCs in Rohtak district. The study employed multistage cluster systematic random sampling procedures. Data collection included structured questionnaires and clinical oral examinations following the type-III ADA classification. Participants' oral health status was evaluated using the WHO oral health assessment form for adults (2013). Descriptive and analytical statistics were used for data analysis. Results and Discussion: Dental caries and periodontal diseases were more common in older age groups. Barriers to oral healthcare among the elderly include fear of dental procedures and low dental literacy. Proximity to PHCs influenced dental service utilization, with higher rates among participants living near a PHC, that is, within 5 km of a PHC. Conclusion: Age, gender, proximity to PHCs, household size, and socioeconomic status play crucial roles in the utilization of oral health services among the rural population. Addressing these factors is essential for improving oral healthcare and overcoming barriers. It is crucial to enhance the accessibility, affordability, and availability of oral health services at PHCs to promote better oral health and overall well-being in rural areas.

Power electronics converters (PECs) are responsible for efficiently converting electrical energy between power generators, storage systems and power consumers/loads. The PECs are subjected to complicated power loading factors throughout their operations and, thus, are proven to have issues regarding lifetime. Therefore, according to the original equipment manufacturers and suppliers, the reliability of the PECs is a key priority in order to be widely used and accepted in the industries. In this context, this review article aims to provide a comprehensive overview of reliability assessment strategies and testing protocols for ensuring the lifetime requirements of PECs. In addition, the paper conducts a thorough investigation of various strategies that are employed to enhance reliability during the design and useful life phase, including the analysis of different types of failure mechanisms, identification of factors contributing to failures, and assessment of techniques for estimating and regulating junction temperatures to prolong the lifetime of the system under real-life operating conditions. Furthermore, the article highlights the challenges encountered in monitoring and predicting component degradation and outlines the crucial steps for conducting a functional safety analysis. Particular emphasis is provided on summarizing the different accelerated aging tests for power electronics converters used in automotive applications, as these tests have yet to be fully covered in previous literature. This study provides an overview and guidelines for understanding the reliability of PECs and identifying potential areas for future research. Finally, the paper concludes most of the ongoing research and innovations in this area and provides insights into the future trends and challenges in enhancing the reliability of power electronics converters.

As communication technology advances, high-gain antennas are being investigated for a variety of long-distance applications. One such high gain antenna is reflectarray, it has combined advantageous characteristics of a reflector and phased array antennas. However, to design the reflectarray antenna its phase range, bandwidth, gain, cross polarization and the side lobe levels must be in optimal range to meet the requirements for distant applications. In this article, we have reviewed various research works of reflectarray antenna and highlighted the techniques to develop an efficient high gain reflectarry antenna. Recently, for high gain applications, as per end user requirement, there is a need to vary the frequency and radiation characteristics in a controlled manner. This can be achieved by using reconfigurable reflectarray antennas. In this article, reconfigurable mechanisms and active elements used for reconfiguration are reviewed in detail. In the end of this survey, some of the works on reflectarray antenna which were published by the research society are compared, summarizing the important parameters such as operating frequency, phase range, gain bandwidth, peak gain, cross polarization levels, and side lobes.

Abstract This review article explores the dynamic field of radiopharmaceuticals, where innovative developments arise from combining radioisotopes and pharmaceuticals, opening up exciting therapeutic possibilities. The in-depth exploration covers targeted drug delivery, delving into passive targeting through enhanced permeability and retention, as well as active targeting using ligand-receptor strategies. The article also discusses stimulus-responsive release systems, which orchestrate controlled release, enhancing precision and therapeutic effectiveness. A significant focus is placed on the crucial role of radiopharmaceuticals in medical imaging and theranostics, highlighting their contribution to diagnostic accuracy and image-guided curative interventions. The review emphasizes safety considerations and strategies for mitigating side effects, providing valuable insights into addressing challenges and achieving precise drug delivery. Looking ahead, the article discusses nanoparticle formulations as cutting-edge innovations in next-generation radiopharmaceuticals, showcasing their potential applications. Real-world examples are presented through case studies, including the use of radiolabelled antibodies for solid tumors, peptide receptor radionuclide therapy for neuroendocrine tumors, and the intricate management of bone metastases. The concluding perspective envisions the future trajectory of radiopharmaceuticals, anticipating a harmonious integration of precision medicine and artificial intelligence. This vision foresees an era where therapeutic precision aligns seamlessly with scientific advancements, ushering in a new epoch marked by the fusion of therapeutic resonance and visionary progress. Graphical Abstract

Abstract The Nipah virus, a highly pathogenic zoonotic pathogen, has once again surfaced in the state of Kerala, India, with recent cases reported in 2023. This article delves into the epidemiological details of these cases, shedding light on the two fatalities that occurred in September 2023 and August 2023 as well as the suspected cases that have undergone testing. Nipah virus, known for its severe neurological and respiratory disease manifestations, remains a formidable health threat due to the lack of specific treatments or vaccines. The government’s response to these recent cases, including mass testing and quarantine measures, is discussed, drawing lessons from past outbreaks in the region. Kerala has experienced multiple Nipah virus outbreaks since 2018, prompting a closer examination of environmental factors, such as deforestation and urbanization, which increase the risk of zoonotic transmission. This article underscores the global implications of Nipah virus resurgence in Kerala and emphasizes the importance of preparedness and vigilance in the face of emerging infectious diseases. The lessons learned from Kerala’s experience with Nipah virus outbreaks provide valuable insights for public health professionals and policymakers worldwide.

Background: The recent re-emergence of the monkeypox (mpox) epidemic in nonendemic regions has raised concerns regarding a potential global outbreak. The mpox virus (MPV) is a smallpox-like virus belonging to the genus Orthopoxvirus (family: Poxviridae). Although studies suggest that MPV infection suppresses the Toll-like receptor-3- and tumor necrosis factor-α-related signaling pathways, whether MPV regulates other immune-related pathways remains unclear. Methods: In this study, two distinct temporal patterns were used for establishing an MPV-infected human immortal epithelial cancer cell line (HeLa). These two durations 2 and 12 h of incubation were selected to identify the coregulated genes and pathways affected by MPV infection. Results: The use of the Gene Ontology framework, Kyoto Encyclopedia of Genes and Genome database, and MetaCore software yielded valuable insights. Specifically, various pathways were found to be enriched in HeLa cells infected with MPV for 2 and 12 h. These pathways included Notch, CD40, CD95, hypoxia-inducible factor-1-α, interleukin (IL)− 1, IL-6, phosphoinositide 3-kinase, nuclear factor-κB, mitogen-activated protein kinase, and oxidative stress–induced signalling pathways. Clusters and pathways of metabolism and viral replication cycles were significantly associated with the 2-hour infection group. This association was identified based on the regulation of genes such as HSPG2, RHPN2, MYL1, ASPHD2, CA9, VIPR1, SNX12, MGC2752, SLC25A1, PEX19, and AREG. Furthermore, clusters and pathways related to immunity and cell movement were found to be associated with the 12-hour infection group. This association was identified based on the regulation of genes such as C1orf21, C19orf48, HRK, IL8, GULP1, SCAND2, ATP5C1, FEZ1, SGSH, TACC2, CYP4X1, MMP1, CPB1, P2RY13, WDR27, PRPF4, and ENDOD1. Conclusions: This study can improve our understanding of the mechanisms underlying the pathophysiology and post-infection sequelae of mpox. Our findings provide valuable insights into the various modes of MPV infection.

Introduction: University students’ motivators and preferences for yoga as their course of study can influence their future as yoga instructors and therapists. Materials and Methods: Six hundred and thirty-six students of both genders (251:385, male: female) from four North Indian universities offering graduate and postgraduate courses in yoga were the respondents to a convenience sampling survey about their preferences and motivators. Results: The three most common reasons why students chose to study yoga were (i) “I can help many people through knowledge of yoga” (32.2%), (ii) “I will become a better person by studying yoga” (21.9%), and (iii) “I find yoga interesting” (18.9%). After completion of the course, most students wished (i) “to study another course in yoga” (28.8%), (ii) “to work in yoga and education in a university” (17.5%), and (iii) “to work in yoga and research” (14.3%). Students appreciated positive effects which they attributed to yoga (e.g. good health, feeling peaceful, and positive behavior changes). Conclusion: Students did not like regulations such as early wakening and dietary restrictions. The available information about the scope, benefits, safety considerations, and requirements of yoga can help student aspirants make an informed choice about their future careers. Students of yoga can be further motivated by evidence informed interactive sessions.

Abstract Background SARS-CoV-2 infections caused mild-to-moderate illness. However, a sizable portion of infected people experience a rapid progression of hyper-inflammatory and hypoxic respiratory illness that necessitates an effective and safer remedy to combat COVID-19. Methods A total of 150 COVID-19-positive patients with no to mild symptoms, between the age groups 19–65 years were enrolled in this randomized, open-labeled three-armed clinical trial. Among them, 136 patients completed the study with RT-PCR negative reports. The patients received herbal drugs orally (Group A (Adhatoda vasica; AV; 500 mg; n = 50); Group B (Tinospora cordifolia; TC; 500 mg; n = 43), and Group C (AV + TC; 250 mg each; n = 43)) for 14 days. Clinical symptoms, vital parameters, and viral clearance were taken as primary outcomes, and biochemical, hematological parameters, cytokines, and biomarkers were evaluated at three time points as secondary outcomes. Results We found that the mean viral clearance time was 13.92 days (95% confidence interval [CI] 12.85–14.99) in Group A, 13.44 days (95% confidence interval [CI] 12.14–14.74) in Group B, and 11.86 days (95% confidence interval [CI] 10.62–13.11) days in Group C. Over a period of 14 days, the mean temperature in Groups A, and B significantly decreased linearly. In Group A, during the trial period, eosinophils, and PT/INR increased significantly, while monocytes, SGOT, globulin, serum ferritin, and HIF-1α, a marker of hypoxia reduced significantly. On the other hand, in Group B hsCRP decreased at mid-treatment. Eosinophil levels increased in Group C during the treatment, while MCP-3 levels were significantly reduced. Conclusions All the patients of the three-armed interventions recovered from COVID-19 and none of them reported any adverse effects from the drugs. Group C patients (AV + TC) resulted in a quicker viral clearance as compared to the other two groups. We provide the first clinical report of AV herbal extract acting as a modifier of HIF-1α in COVID-19 patients along with a reduction in levels of ferritin, VEGF, and PT/INR as the markers of hypoxia, inflammation, and thrombosis highlighting the potential use in progression stages, whereas the TC group showed immunomodulatory effects. Trial registration Clinical Trials Database -India (ICMR-NIMS), CTRI/2020/09/028043. Registered 24th September 2020, https://www.ctri.nic.in/Clinicaltrials/pdf_generate.php?trialid=47443&EncHid=&modid=&compid=%27,%2747443det%27 Graphical Abstract

AbstractBackground India recorded the first outbreak of African swine fever (ASF) in North-eastern region (NER) in the year 2020.Aim The current study was undertaken to investigate the transmission of African swine fever virus (ASFV) in the wild boars of Northeast India, particularly of Assam.Material and Methods ASF suspected mortal tissue remains and blood samples of wild boars collected from different locations of Assam were screened for molecular detection of swine viruses which includes Classical swine fever virus, Porcine Circovirus 2, Porcine reproductive and respiratory syndrome virus and ASFV.Results One sample each from Manas and Nameri National Parks was detected positive for ASFV. Besides this, one of the samples was positive for CSFV and one of the ASFV positive samples was also positive for PCV2. Several striking gross and microscopic alterations were noticed in different organs of ASFV infected animals. Sequencing and phylogenetic analysis of B646L gene confirmed the presence of ASFV genotype-II in wild boars. Circulation of similar genotype in domestic pigs of NER in the contemporary period as well as locations near to the aforementioned national parks indicates the transmission of ASFV from domestic to wild boars.Clinical Relevance The detection of ASFV in the wild boars of Assam is alarming as it is an impending threat to pig population and other endangered species (particularly Pygmy hog), making it increasingly daunting to control the disease.Conclusion Chances are high for ASFV to become endemic in Assam region if stringent measures are not taken at proper time.

Emission and performance parameters of a 4-stroke CI engine operated on a blend of catalytic co-pyrolysis oil with pure diesel, produced through Azadirachta indica seed, waste LDPE (low-density polyethylene), and aluminium oxide (Al2O3) as a catalyst, are modelled in the current work using an Artificial Neural Network (ANN). At 500°C temperature, the highest oil output obtained was 93.91 wt%. The produced liquid fuel possessed similar physical features to that of pure diesel, including density (794 kg/m3) and heating value (44.42 MJ/kg), but lower flash and fire points that would assist in a better and complete combustion of the fuel blend resulting in a better performance and combustion characteristics. Using inputs including brake mean effective pressure, load, brake power, and torque, a developed ANN model was applied to forecast the performance (Brake Thermal Efficiency and Brake Specific Fuel Consumption) along with emission characteristics (Smoke and NOx). The Levenberg-Marquardt back-propagation training technique was applied for emissions and performance characteristics prediction having the best accuracy. Regression coefficients (R2) for predicting BTE, BSFC, NOx, and smoke were all very near to 1: 0.99801, 0.9983, 0.95753, and 0.97467. The study determines that the proposed alternative fuel could be utilized in blend with the pure diesel to in an unmodified diesel engine. It has also been found that artificial neural networks (ANN) could prove to be useful to model and forecast the performance or emissions of renewable fuels in diesel engines, with the potential for these fuels to be employed in transportation.

Load Frequency Control (LFC) and Voltage Control (VC) are critical aspects of hybrid generation systems. In this work, the performance comparison of three different control approaches for LFC and VC: Genetics Algorithm (GA)-tuned Proportional Integral Differentiator (PID), Particle Swarm Optimization (PSO)-PID, and a conventional PID controller is presented. Especially, the performance is assessed and analyzed for convergence speed and computational complexity for each approach. Mathematical framework for each approach is discussed, including the required equations for hybrid generation system. It is reported that the traditional PID controller exhibits fast convergence due to its direct adjustment of control parameters. Simulation results reveal that it requires manual tuning and has low computational complexity. In contrast, the GA-PID utilizes a GA optimization process which automatically tunes the PID gains. Although, it may require multiple generations to converge to the optimal solution, however, it offers better control performance. Moreso, it comes at the cost of higher computational complexity compared to the traditional PID controller. In contrast, the PSO-PID employs an algorithm for parameter optimization. It converges faster than the GA-PID but still requires more iterations than the traditional PID controller. Similar to the GA-PID, it has higher computational complexity due to fitness function evaluation and particle updates. The optimization results provide insights into the convergence speed and computational complexity trade-offs between the three control approaches. Practitioners in the field of hybrid energy systems can utilize the outcomes to make informed decisions based on their specific requirements and available computational resources.

Bakelite, a thermosetting plastic, is harder to recycle as compared to than thermoplastic polymers through thermal method due to its inherent property to harden on application of heat. This study co-pyrolyzes waste bakelite with polypropylene (PP), high-density polyethylene (HDPE), polystyrene (PS), and polymethyl methacrylate (PMMA) in a conventional semi-batch pyrolysis reactor and microwave pyrolysis reactor to determine how the reactor type and thermoplastic blending affect product distribution, yield, and composition of condensable fraction. The blending of thermoplastics and pyrolysis reactor types greatly affects product distribution. Bakelite, on pyrolysis, produces 39.12 wt% condensable product, which increased to 45.42 wt%, 58.76 wt%, 61.53 wt%, and 66.76 wt% in conventional pyrolysis and 49.87 wt%, 61.26 wt%, 66.51 wt%, and 72.88 wt% in microwave pyrolysis by blending HDPE, PP, PMMA, and PS respectively. The composition analysis through Gas chromatography-mass spectrometry and Fourier-transformed infrared spectroscopy confirms the formation of alkanes, cycloalkanes, alkenes, cycloalkenes, aromatics, and oxygenated compounds, from both pyrolysis processes. However, their percentage differ significantly in both processes. Microwave-assisted pyrolysis with activated carbon yields superior oil in both quantity and composition compared to conventional pyrolysis, effectively transforming waste plastics into valuable products.

The lignocellulose reinforced composites are commonly used sustainable materials with good mechanical and physical properties. Aiming to properly dispose and recover the potential value of discarded lignocellulose reinforced composites, the pyrolysis behaviour and kinetics of reed straw processing residual/polylactic acid (RSPR/PLA) composites, a typical 3D printing material, was investigated. Based on the TG-FTIR results, the synergistic effects between RSPR and PLA during the pyrolysis process were clarified. Compared with the FTIR spectra of PLA, the absorption peaks of CO and CO2 disappear in the FTIR spectra of RSPR/PLA composite, which indicates RSPR provides additional free radicals for the free radical reaction of PLA, and further promoting the decomposition. The apparent activation energy of the RSPR/PLA composite pyrolysis was calculated by two iso-conversional methods including Flynn-Wall-Ozawa (FWO) and Kissinger-Akahira-Sunose (KAS). The average Ea of the RSPR/PLA composite (122.6 kJ mol−1 (FWO) and 117.9 kJ mol−1 (KAS)) was lower than that of solo pyrolysis of RSPR (138.5 kJ mol−1 (FWO) and 135.4 kJ mol−1 (KAS)) and the pure PLA (197.0 kJ mol−1 (FWO) and 196.6 kJ mol−1 (KAS)). The master plot method results suggested the pyrolysis of RSPR/PLA composite followed the one-dimensional (D1) diffusion model. This work provides an environmentally friendly strategy to effective thermo-chemical upgrading of the value of discarded lignocellulose reinforced composite material.

Abstract The pandemic and other environmental conditions have increased the use of masks as a precautionary measure. It is an effective way to protect ourselves from viruses/pollution/ and other health-affecting environmental factors. However, for smart devices such as smartphones with face locks, attendance systems, and smart surveillance cameras with enabled face recognition, these masks raised another challenge of masked face recognition. Masked face recognition is an increased subset challenge of the standard face recognition problem as they lack facial features. The masked images are occluded, making the structure and the facial features of the non-occluded region of importance. This paper presents a novel two-fold approach KInsight (K Nearest Neighbor-based Insight Face algorithm) for masked face detection using antelopev2, which uses a RetinaFace detection algorithm and a ResNet100 Convolutional Neural Network for face detection and embedding generation. Further, we propose to use a KNN classifier for masked face recognition. Several experiments have compared the proposed scheme’s performance with important research contributions. Experimental results show that the scheme significantly outperforms several benchmark approaches with an accuracy of around 98.5%.