Search

This article presents a comprehensive review of the studies in the domain of Solid Oxide Fuel Cells (SOFC) and Electrolysers, highlighting their integral role in promoting green hydrogen production. Over the past three decades, SOFC technology has seen profound advancements, transitioning from its initial phases to the cusp of commercialisation. The progression of this technology is illuminated through the systematic evolution of international symposia dedicated to SOFCs. These events have chronicled pivotal breakthroughs in materials innovation, a deepened understanding of electrode reactions, intricate chemical interactions, and the design and efficacy of SOFC configurations, from individual cells to complex multi-cell assemblies and integrated power systems. Concurrently, the studies shed light on the potential of solid oxide electrolyser technology in addressing the challenges posed by the intermittent nature of renewable energy sources, such as solar and wind. Operating at temperatures surpassing 600°C, these electrolysers adeptly decompose water and/or carbon dioxide into chemical fuels, capitalising on both thermodynamic and kinetic advantages. The review concludes with the findings of the exploration of nuclear power’s capability in championing high-temperature steam electrolysis for sustainable hydrogen production, encompassing a thorough analysis of material innovations, degradation mechanisms, and strategies to offset such deteriorations.

According to the future emphasis on the smart grid, renewable energy is vital to the revolution in power generation. A microgrid will be able to maintain itself in the next years without substantially relying on fossil fuel sources thanks to the noticeable increase in the penetration of renewable energy sources, notably solar energy. If not effectively controlled, power quality issues resulting from these interconnections might seriously impair the grid and distribution assets. The distribution system’s harmonics are removed from it by the HAPF management, which is caused by nonlinear loads and micro inverters. The longest daylight hours are when the PV-powered HAPF system performs at its best. To examine the harmonic distortion on the output waveforms, simulation and experiment data are combined.

Compositional tuning of magnetic properties to provide technologically useful results is in the forefront of research in complex oxides. Taking advantage of the highly sensitive nature of magnetism in 6H barium ruthenates (Ba3MRu2O9, M = transition metals or rare earth ions) to composition, we have carried out M-site dual doping by 50% each of Co and Mn. The high pressure and high temperature synthesized sample of 6H Ba3Co0.5Mn0.5Ru2O9 shows giant exchange bias (5.71 kOe at 5 K and 50 kOe cooling field) and huge coercivity (9.42 kOe at 5 K) at low temperature along with Griffiths phase like behavior in the 136 K < T < 260 K temperature range. The presence of ferromagnetic (FM) clusters in a non-collinear antiferromagnetic (AFM) background for temperature below 136 K is assumed. These FM clusters extend above 136 K to persist until 260 K, and the system finally reaches the paramagnetic (PM) state closer to room temperature. The exchange bias phenomena diminish above 20 K and this could be correlated with the peculiar nature of magnetic isotherms above and below this temperature. The transition at 136 K is regarded as AFM short-range ordering from ac and dc magnetization studies and heat capacity measurement. The presence of short-range interactions at temperatures until the PM region forms the basis of Griffiths phase like behavior in this sample. [ABSTRACT FROM AUTHOR]

In recent times, considerable attention has been given to examining the impact of micro/nanostructure on the thermoelectric characteristics of nonstoichiometric AgSbTe2. The present investigation employed direct melting of elements that produced p-type AgSbTe2 with spontaneous nanostructuring due to cation ordering. The product predominantly features an Ag-deficient Ag0.927Sb1.07Te2.005 phase with monoclinic Ag2Te nanoprecipitates and exhibits a degenerate semiconductor-like behavior with an energy band gap of 0.15 eV. A Seebeck coefficient of 251 μV K−1 and a power factor of 741 μW m−1 K−2 at near ambient temperature are attained with this composition. The variable range hopping (VRH) and linear magnetoresistance (LMR) confirmed that the low-temperature transport followed a VRH between the localized states. The composition also exhibited glass like thermal conductivity of 0.2 W m−1 K−1 arising from phonon scattering at all-scale hierarchical structures that led to a high ZT of 1.1 at room temperature. The direct melted ingots show a high relative density of ∼97%, Vickers hardness Hv of ∼108.5 kgf mm−2, and excellent thermal stability, making them an attractive choice for TEGs. [ABSTRACT FROM AUTHOR]

This study addresses the gap in the comprehensive literature on the intersection of readiness technology and changes in the manufacturing sector. This study employs a hybrid review (bibliometric analysis and conceptual framework) to offer a panoramic overview of the field. We scrutinised 77 publications from peer-reviewed journals, from 2005 to 2023, using methodological lenses such as keyword co-occurrence networks and thematic maps. The review reveals the major contributors (publication trends, themes, and topics) to integrating 3D printing, additive manufacturing, Tech Competition and Lifecycle Assessment in Manufacturing, and Smart Manufacturing Strategies. Based on these insights, we advocate a focused research agenda to expand scholarly contributions to this field. We introduce a framework that offers a theoretically robust tool for scholars and practitioners studying the impact of technology readiness in the manufacturing sector. Consequently, this study not only distils the existing literature, but also sets the stage for future research. This study places significant emphasis on the implementation of technological solutions as a means to improve production operations. Additionally, this research emphasises the significance of ensuring that investment strategies follow the organisation’s technological preparedness. An additional crucial implication concerns the cybersecurity protocols. This is consistent with the research’s emphasis on investigating cybersecurity concerns in the manufacturing industry.

Abstract This paper aims to find out if a score-based investment strategy could be developed using different scales. To achieve this objective several academic sources have been used and it is found that score-based investment not only outperforms the market but also protects the investors from the risks arising out of avoidable poor investments in the market. The project is a summary of bibliographic outcome of several scholars who have attempted to find out the impact of score-based investments in their respective markets. Score-based investments are typically dependent on accounting parameters and changes in these parameters signal that a firm’s performance is geared up for a change. The study has been done using a systematic literature review. Several research papers in peer-reviewed journals were referred starting from 1934 to 2021. Various equity-based scores like F-score, G score, L score and C score and debt-based scores like Z score, O score and M score are used for the construction of portfolios. It has been found that across geographies the use of score-based investing is known to give superior returns as compared to the market. Several pieces of literature provide the evidence. Developed countries like USA, UK, Australia, and Canada have a large concentration of literary sources that point to the evidence of score-based investing. At the same time, it is also pertinent to note that the performance of such techniques works relatively better in markets that are not efficient and where asymmetry in information flow is evident.

Introduction: Acute encephalitis syndrome (AES) is one of the important causes of mortality among children in India. Active management of the cases, followed by addressing the cause of AES, is the key strategy for preventing mortality. Lack of laboratory facility and difficulty of sampling blood and cerebrospinal fluid (CSF) for assessing causes is one of the important barriers to early initiation of treatment. The main objective of the study is to validate the Scrub Typhus Encephalitis Assessment Tool (SEAT) for the management of AES. Methods: The study is a continuation of a study conducted in a tertiary care hospital in Eastern Uttar Pradesh. A machine learning (LightGBM) model was built to predict the probability of scrub typhus diagnosis among patients with acute encephalitis. Three models were built: one with sociodemographic characters, the second with Model 1 variables and blood parameters, and the third with Model 2 variables and CSF parameters. Results: The sensitivity of diagnosing the scrub typhus case was 71%, 77.5%, and 83% in Model 1, Model 2, and Model 3, respectively, and specificity was 61.5%, 75.5%, and 76.3%, respectively, in the models. In Model 1 fever duration, in Models 2 and 3, neutrophil/lymphocyte ratio was the most important predictor for differentiating the scrub and nonscrub cases. Conclusion: With the available sensitivity and specificity of the tool, the SEAT can be a valuable tool for the prediction of scrub typhus as a cause of AES cases in remote areas.

Introduction Acute encephalitis syndrome (AES) poses a significant health challenge to children across India. Late arrival at tertiary care hospitals is a primary contributor to disease severity and poor outcomes. This study identifies the determinants of delayed health seeking and disease severity in AES cases.Methods We interviewed the parents/guardians/caregivers of 242 patients with AES admitted at a tertiary care centre. Multivariable analyses identified factors for delayed health seeking, defined as >3 days spent at home after symptom onset; and disease severity on admission, defined as need for oxygen support. 131 patients were evaluated for long-term outcomes after 3 years using the Liverpool Outcome Score.Results 90 (37.2%) patients had delayed health seeking and 202 (83.5%) had severe disease on admission. Lack of awareness about AES was a significant risk factor (OR 2.4, 95% CI 1.2 to 5.0, p=0.01) for delayed health seeking. Disease severity was associated with seeking treatment from uncertified medical practitioners (UMPs) (OR 7.3, 95% CI 2.7 to 19.8, p

Acute respiratory infections (ARIs) are a leading cause of death in children under five globally. The seasonal trends and profiles of respiratory viruses vary by region and season. Due to limited information and the population’s vulnerability, we conducted the hospital-based surveillance of respiratory viruses in Eastern Uttar Pradesh. Throat and nasal swabs were collected from outpatients and inpatients in the Department of Paediatrics, Baba Raghav Das (BRD) Medical College, Gorakhpur, between May 2022 and April 2023. A total of 943 samples from children aged 1 to 60 months were tested using multiplex real-time PCR for respiratory viruses in cases of ARI and SARI. Out of 943 samples tested, the highest positivity was found for parainfluenza virus [105 (11.13%) PIV-1 (79), PIV-2 (18), PIV-4 (18)], followed by adenovirus [82 (8.7%), RSV-B, [68 (7.21%)], influenza-A [46(4.9%): H1N1 = 29, H3N2 = 14), SARS CoV-2 [28 (3%)], hMPV [13(1.4%), RSV-A [4 (0.42%), and influenza-B (Victoria lineage) 1 (0.10%). The maximum positivity of respiratory viruses was seen in children between 1 to 12 months. The wide variation in prevalence of these respiratory viruses was seen in different seasons. This study enhances understanding of the seasonal and clinical trends of respiratory virus circulation and co-infections in Eastern Uttar Pradesh. The findings highlight the importance of targeted interventions to reduce the burden of respiratory infections in this region.

Lentil (Lens culinaris) and soybean (Glycine max) are proteinaceous legumes susceptible to salinity stress. This study aimed to evaluate the fertigating potential of silica nanoparticles (SiNPs) in improving the physiochemical status, yield parameters, and seed nutritional qualities of the legumes exposed to salinity stress. Characterization of the synthesized SiNPs revealed amorphous, round-shaped particles, a size of 15–40 nm, and a surface charge of −6.18 mV. Different concentrations of SiNPs (0, 1, 5, 10 g/L) were applied to the plants in combination with four different concentrations of NaCl (0, 200, 400, 600 mM) during the reproductive phase of plants. The results indicated that the SiNPs (especially 10 g/L) efficiently reduced the negative impacts of salinity by improving the physiochemical parameters (growth, pigments, primary metabolites, antioxidant enzymes). Similarly, the improvement in yield parameters (pods per plant, pod length, seeds/10 pods, etc.) and seed nutritional attributes (protein, sugar, free amino acids, free fatty acid, polyphenol contents, etc.) were observed irrespective of the NaCl concentrations. Specifically, applying 10 g/L SiNPs enhanced the total pod numbers by 1.70, and 1.57 folds; and the total number of seeds/10 pods by 1.44, and 1.65 in lentil and soybean plants, respectively, compared to the control set (600 mM NaCl). Moreover, the seed protein content was augmented by 3.29, and 1.30 folds compared to the 600 mM NaCl stressed plants (lentil and soybean, respectively) when treated with 10 g/L SiNPs. Therefore, it can be concluded that SiNPs can be used sustainably to improve yield and nutritional attributes under stressed conditions.

Abstract Background Eu is a lesser-known and traditional millet-based fermented brew of the Toto tribe from West Bengal, India. The starter culture used in this brew consists of diverse microflora. Identifying those microbes will not only help us gain a deeper understanding of the brew, but also quantify the impacts of this brew on the human system after consumption. Due to the progress in Illumina sequencing technology, the meta-profiling of 16S rRNA has emerged as a valuable resource for exploring the microbiome of any sample. We have utilised this tool (V3–V4 region) to study the microbiome population of Eu. Results The microbial diversity present in the brew was mainly constituted of probiotic and fermenting bacteria. The nutrient profiling of Eu estimated the amount of protein, carbohydrate, free amino acid, and free fatty acid. The nutritional substance present in the brew probably supports the growth of the probiotic microflora. Reverse ecology-based network analysis revealed considerable complementary interaction between humans and the microflora present in the Eu. GC–MS outlining enlisted thirteen potent compounds from Eu, and a comprehensive network pharmacological study on those compounds revealed the anti-cancerous properties of Eu, especially against gastrointestinal malignancy, by reducing the proliferation of malignant cells and forming pro-inflammatory cytokines. Conclusions The current study focuses on the meta-profiling and nutritional characteristics of Eu, which highlight the beverage’s potential as a probiotic health drink. Reverse ecology analysis demonstrated that the probiotic microflora competes strongly against pathogenic bacteria. Additionally, in silico network pharmacological research identified the drink as a potentially health-promoting and anti-cancer beverage.

Abstract Mental stress is found to be strongly connected with human cognition and wellbeing. As the complexities of human life increase, the effects of mental stress have impacted human health and cognitive performance across the globe. This highlights the need for effective non-invasive stress detection methods. In this work, we introduce a novel, artificial spiking neural network model called Online Neuroplasticity Spiking Neural Network (O-NSNN) that utilizes a repertoire of learning concepts inspired by the brain to classify mental stress using Electroencephalogram (EEG) data. These models are personalized and tested on EEG data recorded during sessions in which participants listen to different types of audio comments designed to induce acute stress. Our O-NSNN models learn on the fly producing an average accuracy of 90.76% (σ = 2.09) when classifying EEG signals of brain states associated with these audio comments. The brain-inspired nature of the individual models makes them robust and efficient and has the potential to be integrated into wearable technology. Furthermore, this article presents an exploratory analysis of trained O-NSNNs to discover links between perceived and acute mental stress. The O-NSNN algorithm proved to be better for personalized stress recognition in terms of accuracy, efficiency, and model interpretability.

Abstract Background Positron emission tomography (PET) images of head and neck squamous cell carcinoma (HNSCC) patients can assess the functional and biochemical processes at cellular levels. Therefore, PET radiomics‐based prediction and prognostic models have the potentials to understand tumour heterogeneity and assist clinicians with diagnosis, prognosis and management of the disease. We conducted a systematic review of published modelling information to evaluate the usefulness of PET radiomics in the prediction and prognosis of HNSCC patients. Methods We searched bibliographic databases (MEDLINE, Embase, Web of Science) from 2010 to 2021 and considered 31 studies with pre‐defined inclusion criteria. We followed the CHARMS checklist for data extraction and performed quality assessment using the PROBAST tool. We conducted a meta‐analysis to estimate the accuracy of the prediction and prognostic models using the diagnostic odds ratio (DOR) and average C‐statistic, respectively. Results Manual segmentation method followed by 40% of the maximum standardised uptake value (SUVmax) thresholding is a commonly used approach. The area under the receiver operating curves of externally validated prediction models ranged between 0.60–0.87, 0.65–0.86 and 0.62–0.75 for overall survival, distant metastasis and recurrence, respectively. Most studies highlighted an overall high risk of bias (outcome definition, statistical methodologies and external validation of models) and high unclear concern in terms of applicability. The meta‐analysis showed the estimated pooled DOR of 6.75 (95% CI: 4.45, 10.23) for prediction models and the C‐statistic of 0.71 (95% CI: 0.67, 0.74) for prognostic models. Conclusions Both prediction and prognostic models using clinical variables and PET radiomics demonstrated reliable accuracy for detecting adverse outcomes in HNSCC, suggesting the prospect of PET radiomics in clinical settings for diagnosis, prognosis and management of HNSCC patients. Future studies of prediction and prognostic models should emphasise the quality of reporting, external model validation, generalisability to real clinical scenarios and enhanced reproducibility of results.

Large language models (LLMs) have received considerable interest in the field of natural language processing (NLP) owing to their remarkable ability to generate clear, consistent, and contextually relevant materials. Among the numerous LLMs, ChatGPT (Generative Pre-trained Transformer for Chatbots) is emerging as a prominent prospective tool for developing conversational agents such as chatbots. However, there is a need for a clear conceptual understanding of ChatGPT's potential implications for the industry and its role in marketing. This study explores the adoption of ChatGPT in marketing and examines theories that may influence its adoption by marketers and consumers, as well as its implications for marketers. This study discusses how ChatGPT may allow for more personalized and engaging content, better customer experience, and improved ROI. However, adoption also brings challenges, including ethical considerations and the need for new skill development. This study also discusses future research opportunities for the adoption of ChatGPT and other generative artificial intelligence technologies in marketing. The goal is to provide insights for organizations that consider implementing these technologies, and to contribute to the literature on the adoption of Artificial Intelligence (AI) and the use of Generative AI in marketing.

Background: High levels of stress among pregnant women have been reported during the coronavirus disease 2019 (COVID-19) pandemic because of various infection-related and lockdown measures. Concerns about safe delivery, breastfeeding, and child care may increase the risk of depression in vulnerable women during the perinatal period. Aim: To study the perceptions regarding child care and prevalence of perinatal depression during the COVID-19 pandemic. Materials and Methods: A cross-sectional community-based survey was conducted among 750 lactating mothers post delivery between September 2020 and February 2021 in 51 districts of Uttar Pradesh. A convenient purposive sampling technique was used. A semi-structured questionnaire was used to collect the socio-demographic details and perceptions regarding child care during the COVID-19 pandemic. Assessment of depression symptoms was performed with the help of patient health questionnaire 9 (PHQ-9). Results: A total of 440 participants were suffering from some form of depression symptoms; the majority had mild depression. Depression was found to be higher among homemakers and young mothers (age

Background: Vaccines are a key strategy to stop the COVID19 pandemic. The present study was conducted to assess the incidence of Adverse Drug Reactions to the Covishield vaccine among healthcare workers. Materials and Methods: A cross-sectional, observational, questionnaire-based study was carried out on healthcare workers of R.U.H.S. College of Medical Sciences, Jaipur, Rajasthan. The study tool consisted of a digital questionnaire. Results: The present study was carried out among 316 healthcare workers who received the first dose of the Covishield vaccine. 83 (26.26%) participants complained of side effects after receiving the first dose of the Covishield vaccine. Fatigue (64), fever (52), body ache (40), swelling at the vaccination site (35), headache (25), and pain in the limb (18) were the most prevalent symptoms. Most post-vaccination symptoms were found to be mild. 67 participants showed side effects of vaccination within 24 hours while 16 showed side effects after 24 hours. Conclusion: This study reflects that one fourth of participants complained of side effects after receiving the first dose of the Covishield vaccine. These side effects are not severe and should not be an obstacle to the successful control of the Covid-19 pandemic in India.

In this study, sol gel technique is used to fabricate manganese (Mn) doped ZnO thin films and further utilize them as a platform for uric acid biosensors. The objective was to introduce manganese into the ZnO matrix to enhance its redox properties, capitalizing on the multivalent nature of manganese. The Mn-doped thin films of concentrations varying from 3 %,5 %,7 % and 10 % were prepared and further characterized using UV–vis spectroscopy, X-ray diffraction (XRD) spectroscopy, Fourier transform infrared spectroscopy (FTIR), field emission scanning electron microscopy (FESEM) and cyclic voltammetry (CV) measurements. The ZnO thin films with 7 % doping of Mn exhibited improved redox behaviour, as evident by the distinct redox peaks. In order to immobilise the uricase enzyme, the 7 % Mn doped composition was used, creating a highly sensitive and focused uric acid detection platform. The fabricated biosensor exhibits excellent performance in terms of sensitivity (40 µAmM-1cm-2), selectivity with 12 weeks, enabling precise and sensitive uric acid detection. This study brings to light an alternate approach in developing point of care biosensors using transition metal doped ZnO thin films.

The Internet of Things is a resource-constrained device that demands lightweight cryptographic solutions to achieve high performance and optimal security. In lightweight ciphers Substitution Box (S-box) plays an important role as it enables confusion property. However, it is one of the costlier operations. The design and construction of such S-boxes for Internet of Things (IoT) devices are crucial..Hence, we propose a 4-bit, highly Nonlinear, Bijective, Balanced S-box called Feather S-box to enable confusion in lightweight ciphers. The hardware performance of Feather S-Box is analysed in terms of Area and Critical Path-Delay cost. While examining the Area Delay-Product and Power-Delay Product, it shows 23% and 19% lower than PRESENT cipher and 12% lesser than GIFT and KATAN ciphers. The security analysis of the proposed S-Box is also done in terms of Nonlinearity, Bijective, Balanced, Global Avalanche characteristics, resistance to Algebraic attack, Side-channel attacks, Differential and Linear Cryptanalysis. The Feather S-box also exhibts good cryptographic properties such as Nonlinearity and immunity against Algebraic attacks. Moreover, it offers good resistance against Side-channel attack, Differential and Linear Cryptanalysis. We also observed that the Feather S-box has the highest immunity against Differential and Linear Cryptanalysis except for the SKINNY cipher.

This case report is about a rural 39 years old female of Asian origin and laborer by profession who developed Toxic Epidermal Necrolysis (TEN) with lamotrigine. She was a known case of Bipolar Affective Disorder Type 1 with psychosis on treatment with quetiapine, duloxetine, escitalopram, and etizolam for the last one and a half years and had no history of adverse effects with those drugs. Recently Lamotrigine was added to her regimen at a dose of 50 mg/day. She developed Stevens-Johnson syndrome (SJ syndrome) within two weeks of adding lamotrigine which progressed to Toxic Epidermal Necrolysis (TEN), SCORTEN scores 3, in the next 3-4 days. The sequence of events, reports of laboratory investigations, and management of TEN have been elaborated in this case report. On the Naranjo scale of causality, the suspected adverse drug reaction was established as ‘probable’ because the suspected culprit drug discontinuation led to improvement in the patient’s condition but a re-challenge was not tried.

Abstract In recent times, nanotechnology has emerged as an efficient tool to manage the adverse effect of environmental stresses on plants. In this connection, carbon-nanodots (CNDs) have been reported to ameliorate the negative impacts of salinity stress. Further, surface modification of CNDs is believed to augment their stress-alleviating potential, however, very little has been known about the potential of surface-functionalized CNDs. In this purview, two sugar (trehalose and glucose) terminated CNDs (CNPT and CNPG) have been synthesized and assessed for their stress-alleviating effects on Vigna radiata (a salt-sensitive legume) seedlings subjected to different concentrations of NaCl (0, 50, and 100 mM). The synthesized CNDs (CNPT and CNPG) exhibited a hydrodynamic size of 20–40 nm and zeta potential of up to − 22 mV with a 5–10 nm core. These water-soluble nanomaterials exhibited characteristic fluorescence emission properties viz. orange and greenish-yellow for CNPT and CNPG respectively. The successful functionalization of the sugar molecules on the CND cores was further confirmed using FTIR, XRD, and AFM. The results indicated that the application of both the CNDs improved seed germination, growth, pigment content, ionic and osmotic balance, and most importantly, the antioxidant defense which decreased ROS accumulation. At the same time, CNPT and CNPG exhibited no toxicity in the Allium cepa root tip bioassay. Therefore, it can be concluded that sugar-terminated CNDs improved the plant responses to salinity stress by facilitating sugar uptake to the aerial part of the seedlings.

Not Available

In addition to their role in cellular energy production, mitochondria are increasingly recognized as regulators of the innate immune response of phagocytes. Here, we demonstrate that altering expression levels of the mitochondria-associated enzyme, cytidine monophosphate kinase 2 (CMPK2), disrupts mitochondrial physiology and significantly deregulates the resting immune homeostasis of macrophages. Both CMPK2 silenced and constitutively overexpressing macrophage lines portray mitochondrial stress with marked depolarization of their membrane potential, enhanced reactive oxygen species (ROS), and disturbed architecture culminating in the enhanced expression of the pro-inflammatory genes IL1β, TNFα, and IL8. Interestingly, the long-term modulation of CMPK2 expression resulted in an increased glycolytic flux of macrophages akin to the altered physiological state of activated M1 macrophages. While infection-induced inflammation for restricting pathogens is regulated, our observation of a total dysregulation of basal inflammation by bidirectional alteration of CMPK2 expression only highlights the critical role of this gene in mitochondria-mediated control of inflammation.

Objective To determine the Japanese encephalitis (JE)-associated long-term functional and neurological outcomes, the extent of reduced social participation and predictors of poor outcomes among paediatric JE survivors.Design A retrospective cohort study.Setting Laboratory-confirmed JE-positive paediatric cases (

Scrub typhus infections caused by Orientiatsutsugamushi (OT), continue to remain underdiagnosed globally, due to the lack of distinctive symptoms. The elusive nature of the Acute Encephalitis Syndrome (AES) outbreak in Gorakhpur, Uttar Pradesh that claimed numerous pediatric lives was the driving force of this study which involved serological diagnosis (IgM–ELISA), isolation of OT in cell culture, confirmation by PCR, and characterization by Sanger sequencing. In total, 12 out of 36 patients were seropositive, of which 4 were positive by PCR. Upon enrichment in cell culture, additional 3 patients (including two seronegative) were detected positive by PCR. In total, three of these 7 patients were found to be infected with two strains of OT. Taken together, this study for the first time reports the occurrence of dual infections in addition to three circulating OT genotypes (Gilliam, Kato, and Karp-like) and highlights the significance of enriching OT in cell culture systems for efficient molecular detection.

Structural Plasticity (SP) in the brain is a process that allows structural neuronal changes, in response to learning. Spiking Neural Networks (SNN) are an emerging form of artificial neural networks that use brain-inspired techniques to learn. However, the application of SP in SNNs, its impact on overall learning, and network behaviour is rarely explored. In the present study, we use an SNN with a single hidden layer, to apply SP in classifying Electroencephalography (EEG) signals of two publicly available datasets. We considered classification accuracy as the learning capability and applied metaheuristics to derive the optimised number of neurons for the hidden layer along with other hyperparameters of the network. The optimised structure was then compared with overgrown and undergrown structures to compare the accuracy, stability, and behaviour of the network properties. Networks with SP yielded ~94% and ~92% accuracies in classifying wrist positions and mental states(stressed vs relaxed) respectively. The same SNN developed for mental stress classification produced ~77% and ~73% accuracies in classifying arousal and valence states. Moreover, the networks with SP demonstrated superior performance stability during iterative random initiations. Interestingly, these networks had a smaller number of inactive neurons and a preference for lowered neuron firing thresholds. This research highlights the importance of systematically selecting the hidden layer neurons over arbitrary settings, particularly for SNNs using Spike Time Dependent Plasticity learning and provides potential findings that may lead to the development of SP learning algorithms for SNNs.

IntroductionAcute encephalitis syndrome (AES) is a major public health enigma in India and the world. Uttar Pradesh (UP) is witnessing recurrent and extensive seasonal AES outbreaks since 1978. Government of India and UP state government have devised various mitigation measures to reduce AES burden and AES associated mortality, morbidity and disability in Uttar Pradesh. The aim of this study was to describe the public health measures taken in order to control seasonal outbreaks of AES in UP between 1978 and 2020.MethodsWe used literature review as a method of analysis, including the Indian government policy documents. This review utilized search engines such as PubMed, Google Scholar, Research Gate, Cochrane, Medline to retrieve articles and information using strategic keywords related to Acute Encephalitis Syndrome. Data was also collected from progress reports of government schemes and websites of Indian Council of Medical Research (ICMR), National Vector Borne Disease Control Programme (NVBDCP) and Integrated Disease Surveillance Programmes (IDSP).ResultsThe incidence of AES cases in UP have declined from 18.2 per million population during 2005-2009 to 15 per million population during 2015-2019 [CI 12.6–20.6, P-value < 0.001] and case fatality rate (CFR) reduced from 33% during 1980-1984 to 12.6% during 2015-2019 [CI 17.4–30.98, P-value < 0.001]. AES incidence was 9 (2019) and 7 (2020) cases per million populations respectively and CFR was 5.8% (2019) and 5% (2020). This decline was likely due to active surveillance programs identifying aetiological agents and risk factors of AES cases. The identified etiologies of AES include Japanese encephalitis virus (5–20%), Enterovirus (0.1–33%), Orientia tsutsugamushi (45–60%) and other viral (0.2–4.2%), bacterial (0–5%) and Rickettsial (0.5–2%) causes. The aggressive immunization programs against Japanese encephalitis with vaccination coverage of 72.3% in UP helped in declining of JE cases in the region. The presumptive treatment of febrile cases with empirical Doxycycline and Azithromycin (EDA) caused decline in Scrub Typhus-AES cases. Decrease in incidence of vector borne diseases (Malaria, Dengue, Japanese Encephalitis and Kala Azar) i.e., 39.6/100,000 population in 2010 to 18/100,000 population in 2017 is highlighting the impact of vector control interventions. Strengthening healthcare infrastructure in BRD medical college and establishment of Encephalitis Treatment Centre (ETC) at peripheral health centres and emergency ambulance services (Dial 108) reduced the referral time and helped in early treatment and management of AES cases. The AES admissions increased at ETC centres to 60% and overall case fatality rate of AES declined to 3%. Under clean India mission and Jal Jeevan mission, proportion of population with clean drinking water increased from 74.3% in 1992 to 98.7% in 2020. The proportion of household having toilet facilities increased from 22.9% in 1992 to 67.4% in 2020. Provisions for better nutritional status under state and national nutrition mission helped in reducing the burden of stunting (52%) and wasting (53.4%) among under five children in 1992 to 38.8% (stunting) and 36.8% (wasting) in year 2018. These factors have all likely contributed to steady AES decline observed in UP.ConclusionThere is a recent steady decline in AES incidence and CFR since implementation of intensive AES surveillance system and JE immunization campaigns which is highlighting the success of interventions made by central and state government to control seasonal AES outbreaks in UP. Currently, AES incidence is 9 cases per million population (in year 2019) and mortality is 5.8%.

The selection of an appropriate vehicle in a semi-solid topical product is of utmost importance since the vehicle composition and microstructure can potentially cause changes in drug–vehicle or vehicle–skin interactions and affect drug release and subsequent permeation into and across skin. Hence, the aim of this study was to evaluate different semi-solid formulations containing diclofenac sodium for the physicochemical and structural performance of excipients used and various physiological factors governing permeation of drugs applied to skin. The formulations (emulsion, emulgel, gel, and ointment) were prepared using conventional excipients and were found to be homogenous and stable. Rheological analysis demonstrated characteristic shear-thinning and viscoelastic behavior of formulations. The mean release rate of the gel formulation (380.42 ± 3.05 µg/cm2/h0.5) was statistically higher compared to all other formulations. In vitro permeation using human skin showed a significantly greater extent of drug permeation and retention for the emulgel formulation (23.61 ± 1.03 µg/cm2 and 47.95 ± 2.47 µg/cm2, respectively). The results demonstrated that the different formulations influenced product performance due to their inherent properties. The findings of this study demonstrated that a comprehensive physicochemical and structural evaluation is required to optimize the in vitro performance for dermatological formulations depending on the intended therapeutic effect.

Objective: To assess sleep and quality of life among chronic obstructive airway disease patients. Materials and Methods: Patients with primary, mild-to-moderate, stable chronic obstructive airways disease [asthma and chronic obstructive pulmonary disease (COPD)] on treatment visiting outpatient department of a government hospital were interviewed using a predesigned, pretested, semi-structure schedule. The patients were then administered standardized Pittsburgh sleep quality index (PSQI), St. George’s respiratory questionnaire (SGRQ), and Epworth sleepiness scale (ESS) questionnaires. Patients with any other known chronic disease, chest deformity, or long-term oxygen therapy were excluded. Using purposive sampling frame, 120 chest patients (asthma and COPD) and in addition, 30 ambulatory patients without having any underlying chronic respiratory diseases were also recruited for comparison purpose. Results: Mean age was 50.2 years. Mean duration of sleep during night was 5.40 h [±1.6; 95% confidence interval (CI) = 4.98–5.82] for patients with COPD; 5.53 h (±1.6; 95% CI = 5.11–5.95) for patients with asthma, and 6.97 h (±1.0; 95% CI = 6.57–7.36) for control patients (P < 0.001). It was noticed that 63.3% of control patients had at least 6 h of night sleep in comparison to 23.3% of chest patients (P < 0.01). Good PSQI score (up to 5 points) was found in 86.6% of control patients while it was found only in 35.0% of chest patients (P < 0.01); mean PSQI score among asthma was 8.08, 8.06 (COPD), and 3.46 among control patients, respectively. All the control patients (100%) reported good score for quality of life while chest patients reported good score for SGRQ (activity, impact, and symptoms) as 64.1, 83.3, and 82.5%, respectively (P < 0.01). Based on ESS, none of the patients complained of daytime sleepiness. To conclude, poor sleep was noticed in our study sample.

Background. There are many patient decision aids (DAs) available, yet there is limited evidence on comparative effectiveness of different tools. Objective. To examine feasibility of a study protocol and gather preliminary data on comparative effectiveness. Methods. Adult patients seeing a surgeon to discuss treatment for hip or knee osteoarthritis were randomized to hip and knee DAs from two vendors. Pre-visit survey included Hip/Knee Decision Quality Instrument, DA usage, health literacy, and quality of life (EQ-5D). Surgical status was ascertained 6 months post-visit. We examined response rates, eligibility, and compared the two DAs on amount of use, knowledge scores, and receipt of preferred treatment. Results. Overall response rate was 58/74 (78%) and did not differ by study arm. More patients in DA-A group reported reviewing all the DAs (64.5% DA-A v. 24.0% DA-B, P = 0.003). Knowledge scores were similar across arms (55.2% DA-A v. 48.8% DA-B, P = 0.4). For DA-B, knowledge scores were higher for those who reviewed all the DAs compared with those who did not (80% knowledge v. 39% knowledge, respectively, P = 0.004), while scores for DA-A did not vary by usage (62% knowledge v. 53% knowledge, respectively, P = 0.3). A similar percentage of each group received their preferred treatment (77% v. 73%, P = 0.8). Patients who were unsure about preferred treatment at baseline were more likely to have surgery in the DA-A arm compared with the DA-B arm (55% v. 20%, P = 0.1). Limitations. Small sample; patients were only surveyed pre-visit. Conclusion. Despite having different content and formats, the two DAs had similar overall effectiveness. Patients were more likely to review all of DA-A; however, patients who reviewed all of DA-B had the highest knowledge scores.

Circular Manufacturing (CM) is a manufacturing process that employs strategies such as remanufacturing and closed-loop supply chains to improve sustainability (Delpla, Kenné, & Hof, 2022). This process employs circular economic principles. The adoption of CM has been impeded by a lack of financial support, inadequate consumer awareness, and insufficient government support. This review aims to facilitate a broader understanding of the adoption of government policies in implementing circular manufacturing strategies, which will help in advancing our knowledge about how nations compete to create and capture value. To provide a comprehensive and global perspective, the review included 524 studies from the Scopus Database, covering studies between 1990 and May 2024. The review contributes to (a) outlining three thematic clusters of shared scholarly interest, (b) the conceptual framework, and (c) highlighting several areas for future research. Ineffective management and sharing of information are significant challenges that impede organisational knowledge and decision-making administration. The transition to CM is facilitated by identifying essential data and technologies through an integrative review (bibliometric analysis and conceptual framework).

Outbreaks of acute encephalitis syndrome (AES) have been occurring in Gorakhpur Division, Uttar Pradesh, India, for several years. In 2016, we conducted a case–control study. Our findings revealed a high proportion of AES cases with Orientia tsutsugamushi IgM and IgG, indicating that scrub typhus is a cause of AES.

Usher's syndrome is a heterogeneous autosomal recessive disorder characterized by dual sensory impairment in the form of profound congenital hearing loss and progressive visual loss due to retinal degeneration. There are only a few reports describing patients with Usher's syndrome presenting with psychotic features, and the exact etiology of its psychiatric manifestation is not clearly known. Herein, the authors report a case of Usher's syndrome with psychotic symptoms. Furthermore, the authors discuss the possible etiologies of psychotic symptoms in such cases and the challenges faced while assessing these symptoms in patients with sensory impairment.