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Natural fiber composites expected to be in great demand in the coming years due to increased consumer awareness to reduce the waste and environmental pollution. Bagasse fibers available in plenty as an agro-residue and bio composites derived from such renewable resources offer potential for scale-up and value addition. This review provides an insight on current research trends on development and characterization of bagasse-based composites. Various chemical treatment methods and processing techniques used to improve the mechanical, thermal, acoustic, and aging properties of sugarcane bagasse reinforced composites are summarized in the review.

Parkinson’s disease (PD) is a progressive neurodegenerative disorder characterized by motor and motor impairments. However, the conventional diagnostic approaches often struggle to identify subtle abnormal movements at its early stages. To address this issue, a novel video-based PAVE-GAN framework is proposed for PD detection. The patient video sequences are processed using Multi-scale Retinex (MSR) algorithm to improve the visual quality and Improved Sobel edge detector (ISED) is used to extract precise body contours. The Generative adversarial network (GAN) structure is designed with Pose-Activity sampling modules for estimating different body poses with fine details. The estimated feature subsets are processed in the Deep belief network (DBN) to classify the subjects as PD or normal. The proposed PAVE-GAN is evaluated with specific network metrices such as precision, recall, specificity, accuracy, Matthews Correlation Coefficient and F1 score. The experimental results reveal that the proposed PAVE-GAN attains the accuracy of 98.23% for PD detection based on clinical video datasets. Moreover, the proposed PAVE-GAN framework increases an accuracy range by 12.74%, 6.51%, 3.42% and 2.69% better than 3D-CAM model, Random Forest, DNN architecture and Hybrid machine learning classifiers respectively.

Hispanic persons living in the United States (U.S.) are at higher risk of infection and death from coronavirus disease 2019 (COVID-19) compared with non-Hispanic persons. Whether this disparity exists among critically ill patients with COVID-19 is unknown. To evaluate ethnic disparities in mortality among critically ill adults with COVID-19 enrolled in the Study of the Treatment and Outcomes in Critically Ill Patients with COVID-19 (STOP-COVID). Multicenter cohort study of adults with laboratory-confirmed COVID-19 admitted to intensive care units (ICU) at 67 U.S. hospitals from March 4 to May 9, 2020. Multilevel logistic regression was used to evaluate 28-day mortality across racial/ethnic groups. A total of 2153 patients were included (994 [46.2%] Hispanic and 1159 [53.8%] non-Hispanic White). The median (IQR) age was 62 (51-71) years (non-Hispanic White, 66 [57-74] years; Hispanic, 56 [46-67] years), and 1462 (67.9%) were men. Compared with non-Hispanic White patients, Hispanic patients were younger; were less likely to have hypertension, chronic obstructive pulmonary disease, coronary artery disease, or heart failure; and had longer duration of symptoms prior to ICU admission. During median (IQR) follow-up of 14 (7-24) days, 785 patients (36.5%) died. In analyses adjusted for age, sex, clinical characteristics, and hospital size, Hispanic patients had higher odds of death compared with non-Hispanic White patients (OR, 1.44; 95% CI, 1.12-1.84). Among critically ill adults with COVID-19, Hispanic patients were more likely to die than non-Hispanic White patients, even though they were younger and had lower comorbidity burden. This finding highlights the need to provide earlier access to care to Hispanic individuals with COVID-19, especially given our finding of longer duration of symptoms prior to ICU admission among Hispanic patients. In addition, there is a critical need to address ongoing disparities in post hospital discharge care for patients with COVID-19.

Artificial intelligence (AI) technologies, including machine learning (ML), deep learning, and large language models, are increasingly applied in medical diagnostics. In rhinology, these tools are being evaluated for tasks such as image interpretation, cytology classification, and clinical decision support. To systematically evaluate the application and diagnostic accuracy of AI technologies in rhinology, with a focus on clinical utility and implementation barriers. This review followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. Seventeen full-text studies were screened based on predefined eligibility criteria, focusing on AI applications with diagnostic metrics in rhinology. Data on AI type, diagnostic task, performance outcomes, and study quality were extracted and synthesized narratively. Twelve studies met the inclusion criteria. Image-based diagnostic tools using convolutional neural networks demonstrated high accuracy (81%-99%) in nasal polyp detection, cytology classification, and computed tomography (CT) scan interpretation. ML models using patient-reported data achieved accuracies of 74.5%-85.5% for chronic rhinosinusitis prediction. Large language models like ChatGPT and Gemini were evaluated for clinical question answering, with performance exceeding 80% in some domains. Risk of bias was moderate in most primary studies, and none reported clinical integration beyond prototype stages. AI exhibits promising diagnostic accuracy across several applications in rhinology. However, significant challenges persist, including limited validation, methodological heterogeneity, and lack of clinical implementation. Future research should focus on prospective trials, explainability, and regulatory frameworks to ensure safe integration into clinical workflows.

This work involves the synthesis of highly conducting, ultra-thin, mesoporous manganese dioxide, nanotubes and nanowires, using a sol–gel technique. This is a template-free method for preparing mesoporous (3.3 to 5.4 nm) nanotubes and nanowires of 10–15 nm radius with surface area (221.19 m2/g-102.09 m2/g). In the MnO2 lattice, oxygen and cationic vacancies are tailored by changing the reducing agent for improved energy storage. X-ray photoelectron spectroscopic studies are conducted to quantify the oxygen and cationic vacancies. The tailored one-dimensional δ-MnO2 is used as an electrode material for symmetric and asymmetric supercapacitor designs. A non-toxic, less volatile aqueous neutral electrolyte is used for the supercapacitive measurement, giving a specific capacitance of 460.75 F g−1 at 2 mV s−1 with symmetric mode at 1 V. With activated carbon, this material can also produce asymmetric supercapacitors with a specific capacitance of 107.38 F g−1 at 10 mV s−1 at 1.7 V.

The World Health Organization (WHO) global strategy to eliminate cervical cancer (CxCa) could result in >62 million lives saved by 2120 if strategy targets are reached and maintained: 90% of adolescent girls receiving prophylactic human papillomavirus (HPV) vaccine, 70% of women receiving twice-lifetime cervical cancer screening, and 90% of cervical pre-cancer lesions and invasive CxCa treated. However, the cost and complexity of CxCa screening and treatment approaches has hampered scale-up, particularly in low- and middle-income countries (LMICs), and new approaches are needed. Therapeutic HPV vaccines (TxV), which could clear persistent high-risk HPV infection and/or cause regression of pre-cancerous lesions, are in early clinical development and might offer one such approach. During October 2021 to March 2022, WHO, in collaboration with the Bill and Melinda Gates Foundation, convened a series of global expert consultations to lay the groundwork for understanding the potential value of TxV in the context of current CxCa prevention efforts and for defining WHO preferred product characteristics (PPCs) for TxV. WHO PPCs describe preferences for vaccine attributes that would help optimize vaccine value and use in meeting the global public health need. This paper reports on the main discussion points and findings from the expert consultations. Experts identified several ways in which TxV might address challenges in current CxCa prevention programmes, but emphasized that the potential value of TxV will depend on their degree of efficacy and how quickly they can be developed and implemented relative to ongoing scale-up of existing interventions. Consultation participants also discussed potential use-cases for TxV, important PPC considerations (e.g., vaccine indications, target populations, and delivery strategies), and critical modelling needs for predicting TxV impact and cost-effectiveness.

The concept of energy in graphs and matrices is frequently used in all application fields. The energy of a matrix is an extended version of the energy of a graph. The neutrosophic matrix energy concept needs to be more noticeable in multi-criteria decision-making environments. This study presents the concept of the energy of a multi-valued neutrosophic matrix. The upper and lower bounds of the proposed energy were determined. The connection between the neutrosophic hesitant matrix and the multi-valued neutrosophic matrix is provided. Since the parameters of the two matrices differ in truth, indeterminacy, and false entries, the matrix is converted into a single-valued form, and then the energy was calculated. The MCDM problem was addressed with the proposed energy, which is solved by a novel decision-making method. The task is to select a machine from a group of repaired machines in a particular industry that is in good condition. The final ranking values are calculated by the ranking energy formula that decides which is preferred. Then the comparative results were given to demonstrate the accuracy of the proposed energy outcomes.

Repeated obstruction and closure of the upper airway, sporadic hypoxic episodes, and sympathetic activity are symptoms of obstructive sleep apnea (OSA). Obstructive sleep apnoea is due to a combination of altered upper airway structure and muscular function, a low arousal threshold and increased loop gain. Although recurrent upper airway (UA) collapse during sleep is the most frequent clinical hallmark of OSA, the exact cause of this collapse is unknown. Furthermore, while continuous positive airway pressure aids in the management of OSA, many patients find it intolerable. As a result, a better knowledge of the causes of OSA may result in more effective treatments.We did a review of randomized controlled trials that were done in this regard in the last 10 years and whose full-text version is available on the PubMed database. A total of 20 articles were finalized for review after applying our criteria. The articles have proposed different theories regarding the anatomical basis responsible for obstructive sleep apnoea. The theories proposed by different studies in the last decade include reduced genioglossus and hypoglossal nerve activity, the pharyngeal muscles' failure to keep the airway open or tighten it, tonsils and adenoid hypertrophy, an oversensitive ventilatory control system and low respiratory arousal threshold, mandibular position, pharyngeal muscles' high sympathetic drive, cephalometric alterations such as mandibular and hyoid bone position and the length of the soft palate, obesity, and neck fat and fluid re-distribution in the body, from the lower to the upper parts while reclining.Given the diverse etiological characteristics of OSA patients and to increase our knowledge of the condition, additional study into this group is required. Filling any knowledge gaps that may exist in the anatomical basis of the onset of OSA is the main objective of this review paper.

The purpose of this paper is to investigate the effects of Cattaneo-Christov double diffusion on a steady, viscous, magnetohydrodynamic, incompressible, electrically conducting flow of an Oldroyd-B fluid flow over a stretched sheet with mixed convection account taken into consideration along with the presence of a magnetic field, nanofluid particles, thermal diffusion and diffusion thermoeffects. In addition, the characteristics of chemical processes, the Schmidt number, thermophoresis, the Prandtl number and Brownian motion effects are taken into consideration in this research. As a result of the present use of similarity variables, the scope of application for constitutive equations that deal to mass, energy and concentration has been expanded. Making use of the bvp4c solver, which is a computational platform that runs on MATLAB ® , in order to find answers for the problem of governing equations that has been presented. In order to get an accurate measurement of the shear stress as well as the rates of heat and mass transfer at the boundary, the Sherwood number, the Nusselt number and the skin-friction coefficients are used. Tables are a useful tool for doing accurate computations using numerical values. In order to undertake a comprehensive analysis of the dynamics of the problem, we carry out an in-depth research of the concrete repercussions that are caused by a number of different aspects. After then, we use graphic approaches to accentuate and show the implications that have resulted from the situation. In addition, to get a more thorough knowledge of the memory effects, it is beneficial to do a comparative assessment of the present results and the outcomes from the past.

COVID-associated rhino-orbito-cerebral Mucormycosis (CA-ROCM), henceforth referred to as Covid-Associated Mucormycosis (CAM), is a serious and fatal condition unless treated promptly and completely. The main treatment of the CAM is complete surgical debridement and administration of systemic antifungals. The first line antifungal recommended for CAM is Amphotericin-B. Since Amphotericin-B has systemic side effects mainly on the renal system, a timely decision to start and end Amphotericin-B therapy is very essential. Besides the Computed Tomography (CT) scan, serum levels of C-reactive protein (CRP) levels are a good indicator of CAM-associated inflammation levels in the patient's body. By monitoring the CRP levels, we can titrate amphotericin treatment to cause minimal harm to the kidneys. Our study was done to analyze the kinetics of C-reactive protein in patients of CAM admitted in a tertiary-care hospital and compare it with the CRP levels in COVID-associated non-Mucormycosis Sinusitis patients. Aim and objective To study the kinetics of serum C-reactive protein (CRP) levels among patients undergoing in-patient care for COVID-associated rhino-orbito-cerebral mucormycosis and compare with serum CRP levels in COVID-19 patients suffering from sinusitis without rhino-orbito-cerebral mucormycosis.  Materials and methods This was a retrospective cohort study. The source of data was post-COVID sinusitis patients who were admitted during 2nd wave of COVID-19 in India in our hospital whose medical records were accessed by the Medical Records Department. The subjects were recruited into the two study groups namely the Mucormycosis group and the non-Mucormycosis group based on the histopathological report of the nasal biopsy specimen. The medical records of each member of the two groups were studied for the levels of serum C-reactive protein measured at the time of admission and every 5(+1) days thereafter till the time of discharge. The kinetics of serum C-reactive protein levels, which is a marker of inflammation is studied in each of the two groups and compared using statistical methods. Results There was a significant difference between Mucormycosis and Non-Mucormycosis groups in CRP-level kinetics. However, there was no significant trend of decrease or increase over time in Mucormycosis as well as non-Mucormycosis cases. Conclusion CRP is an important biomarker in assessing the septic response to COVID-associated rhino-orbito-cerebral mucormycosis. Detection of raised CRP levels helps in prompt early initiation of anti-fungal treatment. Also, monitoring the levels of serum CRP will guide in deciding the time to stop the antifungals at an appropriate time. CRP monitoring is commonly available and affordable. Hence, we recommend CRP monitoring of in-patients of CAM.