The novel coronavirus disease (COVID-19) pandemic has impacted health and wellbeing globally. To strengthen preventive and clinical care amid this pandemic, technological innovations like artificial intelligence (AI) are increasingly used in different contexts. This bibliometric study aimed to assess the current scholarly development and prominent research domains in applications of AI technologies in COVID-19 research. A total of 105 articles were retrieved from MEDLINE database that emphasized on the use of AI in the context of COVID-19. Most articles had multiple authors with a collaboration index of 7.18. Moreover, most of the articles were produced from the USA (22.86%) and China (21.9%), whereas developing countries were underrepresented among the contributing nations. Furthermore, several research domains were identified, including prevention and control, diagnostics, epidemiological characteristics, therapeutics, psychological conditions, and different areas of data sciences related to COVID-19. The current bibliometric evidence shows the early stage of development in this field, which necessitates equitable applications of AI in COVID-19 research emphasizing on health disparities, socio-legal issues, vaccine development, and applied public health research in this pandemic.

Chitosan nanoparticle delivery systems have potential for enhancing bone healing and addressing osteomyelitis. The objective was to deliver antimicrobial agents capable of preventing or treating osteomyelitis. Each formulation was optimized to achieve desired characteristics in terms of size (ranging from 100 to 400 nm), PDI (less than 0.5), zeta potential (typically negative), and in vitro release profiles for gentamicin. Entrapment percentages varied with gentamicin ranging from 10% to 65%. The chitosan nanoparticles exhibited substantial antimicrobial efficacy, particularly against both P. aeruginosa and MRSA, with zones of inhibition ranging from 13 to 24 mm and complete reduction in colony forming units observed between 3 to 24 hours. These chitosan nanoparticle formulations loaded with antimicrobials hold promise for addressing orthopedic complications.

Structural displacement is an important metric for assessing structural conditions because it has a direct relationship with the structural stiffness. Many bridge displacement measurement techniques have been developed, but most methods require fixed reference points in the vicinity of the target structure which limits field implementations. A promising alternative is to use reference-free measurement techniques that indirectly estimate the displacement by using measurements such as acceleration, and strain. This paper proposes novel reference-free bridge displacement estimation by the fusion of single acceleration with pseudo-static displacement derived from co-located strain measurements. First, we propose a conversion of the strain at the center of a beam into displacement based on the geometric relationship between strain and deflection curves with reference-free calibration. Second, an adaptive Kalman filter is proposed to fuse the displacement generated by strain with acceleration by recursively estimate the noise covariance of displacement from strain measurements which is vulnerable to measurement condition. Both numerical and experimental validations are presented to demonstrate the efficiency and robustness of the proposed approach.

The SARS (severe acute respiratory syndrome)-CoV (Coronavirus)-2 S(spike)-protein mRNA/cDNA currently being used as vaccines are antigenic but not antigens against SARS-CoV-2, that causes COVID (Coronavirus Disease) -19. Furthermore, the mRNA and cDNA antigenic vaccines also have potentials for homologous as well as heterologous recombination, primarily into the somatic cell DNA of the vaccine recipients. On the contrary, a SARS-CoV-2 RBD-protein antigen, a part of the S-protein, will directly stimulate antibody production against SARS-CoV-2. Hence, a vaccine composed of SARS-CoV-2 RBD-protein as a safer, fast acting, and effective vaccine against SARS-CoV-2 and thus against COVID-19. This is also useful for some immune compromised individuals.

Carbon dioxide (CO2), a major greenhouse gas, capture and separation has recently become a crucial technological solution to reduce atmospheric emissions from fossil fuel burning. Thereafter, many efforts have been put forwarded to reduce the burden on climate change by capturing and separating them especially from larger power plants by the utilization of different technologies. Those technologies have often suffered from high operating cost and huge energy consumption. On right side, physical process such as adsorption is very cost effective process which have been widely used to adsorb different contaminants including CO2. Henceforth, this review covers the overall efficacies of CO2 capture by the utilization of carbon based materials through adsorption technology. Subsequently, we also address the associated challenges and future opportunities of carbon based materials (CBMs). For CO2 capture, it was found that CBMs followed the order of carbon nanomaterials (i.e., graphene, graphene oxides, carbon nanotubes and their composites) < mesoporous -microporous or hierarchical porous carbons < biochar and activated biochar < activated carbons.

Coronary angiography, long considered the gold standard for coronary imaging, faces limitations in assessing coronary vessel wall anatomy and guiding percutaneous coronary intervention (PCI). Despite its prevalence, studies have demonstrated that it is suboptimal in estimating the severity of coronary disease and physiologic significance of stenosis. Intracoronary imaging techniques, such as intravascular ultrasound (IVUS) and optical coherence tomography (OCT), offer promising alternatives to overcome these limitations. This review delves into the nuances of IVUS and OCT, highlighting their strengths and limitations as adjuncts to PCI. IVUS, utilizing ultrasound technology, and OCT, based on near-infrared light, each provide unique insights into coronary pathology. They differ in terms of temporal and spatial resolution, influencing their capabilities in plaque characterization and vessel assessment. The discussion navigates their historical evolution, technical specifications, and clinical utility. Meta-analyses and adjusted observational studies suggest that both IVUS and OCT-guided PCI correlate with reduced cardiovascular risks compared to angiographic guidance alone. While IVUS has demonstrated consistent benefits in terms of clinical outcomes, the evidence supporting OCT is less robust. However, the utilization of these imaging modalities remains variable across regions, with increasing adoption in recent years, particularly in IVUS-guided PCIs. Intravascular ultrasound's journey from early motion detection to current high-resolution mechanical systems is traced, including improvements in catheter size and compatibility. On the other hand, optical coherence tomography has advanced significantly, utilizing near infrared light to achieve unparalleled resolutions, albeit requiring temporary blood clearance for optimal imaging. In conclusion, IVUS and OCT offer valuable insights into coronary pathophysiology and guide interventions with improved precision compared to traditional angiography. While IVUS remains more extensively utilized, OCT's growing potential is underscored by advancements in technology, culminating in enhanced imaging capabilities. Both modalities demonstrate comparable clinical outcomes, emphasizing the need for tailored imaging choices based on individual clinical scenarios. The continued refinement and broader integration of intravascular imaging are expected to play a pivotal role in optimizing coronary interventions and patient outcomes.

Additive manufacturing (AM) processes, including stereolithography (SL), can fabricate complex ceramic parts layer by layer using computer-aided design (CAD) models. A ceramic slurry with high solid loading is usually used in SL to fabricate the desired shape, which is further sintered to produce the final part. The traditional SL system utilizes a tank filled with printable material, known as a vat, which for ceramic slurry contributes several limitations and operational difficulties, and further renders it non-recyclable mainly due to its high viscosity and the fragility of the green state. In this study, we utilized a continuous film supply (CFS) printer integrated with a tape casting system using in-house-designed ceramic slurry to print standard prototype specimens. Various printing parameters, including viscosity, layer thickness control, and slurry recycling efficiency, were studied. In addition, post-processing optimizations of the prototype, characterizations, and the microhardness of sintered samples were studied to determine their properties and compare them with traditional methods. The effectiveness of slurry reusability was demonstrated by printing with original and recycled slurry to produce consistent densification of final parts. Post-processing was optimized to achieve a relative sinter density of 99.02% and microhardness of 12.59 GPa. This method provides new opportunities to realize dense complex ceramic features with final properties comparable to those produced by subtractive machining and traditional SL. Furthermore, slurry recycling helps to reduce the overall cost and material consumption.

Dengue virus (DENV) is spread by Aedes aegypti and causes significant global health risks. Alternative techniques are urgently needed because the current control mech-anisms are insufficient to reduce the transmission of DENV. Introducing Wolbachia pipientis into Ae. aegypti inhibits DENV transmission, however, the underlying mechanisms are still poorly understood. Innate immune effector upregulation, the regulation of autophagy, and intracellular competition between Wolbachia and DENV for lipids are among the theories for the mechanism of inhibition. Further-more, mainly three immune pathways Toll, IMD and JAK/STAT are involved in the host for the suppression of the virus. These pathways are activated by Wolbachia and DENV in the host and are responsible for the upregulation and downregulation of many genes in mosquitoes, which ultimately reduces the titer of the DENV in the host. The functioning of these immune pathways depends upon the Wolbachia, host and virus interaction. Here, we summarize the current understanding of DENV recognition by the Ae. aegypti’s immune system, aiming to create a comprehensive picture of our knowledge. Additionally, we investigated how Wolbachia regulates ac-tivation of multiple genes associated with the Toll and IMD pathway, for the reduc-tion of arboviruses.

Mitochondrial encephalomyopathy, lactic acidosis, and stroke-like episodes (MELAS) syndrome is one of the most frequent maternally inherited mitochondrial disorders.MELAS syndrome is a multi-organ disease that presents with a wide range of symptoms, such as dementia, epilepsy, lactic acidemia, myopathy, hearing loss, stroke-like episodes, diabetes, short stature, and myopathy. MELAS primarily affects tissue with high energy demands such as the brain, muscles, and heart. With 65–76% of affected people presenting at or before the age of 20, childhood is the typical age of onset. Genetic testing, imaging tests such as magnetic resonance imaging (MRI) scans, and other techniques, tests of blood, urine, and cerebrospinal fluid in addition to muscle biopsy (if necessary) may be used to diagnose MELAS syndrome. Management of MELAS remains largely supportive, focusing on symptom alleviation and metabolic stabilization. The long-term prognosis of MELAS is variable, influenced by factors such as age of onset, severity of symptoms, and presence of comorbidities. While some patients experience a relatively stable course with intermittent exacerbations, others may exhibit progressive neurological deterioration and multiorgan involvement. Early recognition, prompt intervention, and close monitoring are essential for optimizing outcomes and mitigating complications.Presenting here a case report of an occurrence of MELAS in a 31-year old male patient with chief complaints of perspiration, uneasiness and weight loss with increase in appetite and past history of bilateral hearing loss and vision loss in left eye.

Accurate and efficient medicinal plant image classification is of utmost importance as these plants produce a wide variety of bioactive compounds that offer therapeutic benefits. With a long history of medicinal plant usage, different parts of plants, such as flowers, leaves, and roots, have been recognized for their medicinal properties and are used for plant identification. However, leaf images are extensively used due to their convenient accessibility and are a major source of information. In recent years, transfer learning and fine-tuning, which use pre-trained deep convolutional networks to extract pertinent features, has emerged as an extremely effective approach for image identification problems. This study is leveraging the power of three component deep convolutional neural networks, namely VGG16, VGG19 and DenseNet201, to derive features from the input images of the medicinal plant dataset, containing leaf images of 30 classes. The models were compared and ensembled to make four hybrid models to enhance the predictive performance by utilizing the averaging and weighted averaging strategies. Quantitative experiments were carried out to evaluate the models on the Mendeley medicinal leaf dataset. The resultant ensemble of VGG19+DensNet201 with fine-tuning showcases enhanced capability in identifying medicinal plant images with an improvement of 7.43% and 5.8% compared with VGG19 and VGG16. Furthermore, VGG19+DensNet201 can outperform its standalone counterparts by achieving an accuracy of 99.12% on the test set. A thorough assessment with metrics such as accuracy, recall, precision, and f1-score firmly establishes the effectiveness of the ensemble strategy.

The significance of arts incorporated with culture inclusion makes the arts a matter of pressing interest. The arts are vital elements of a healthy society that benefits the nations even in difficult social and economic times. Based on the previous studies this research was conducted for the first time in Pakistan to explore the historical background of public art correlated with cultural and religious ethics. Though, Pakistan has a rich cultural history yet the role of modern public art is new and often used unintentionally. Our findings of different surveys conducted in Pakistan including oldest cities such as Lahore, Peshawar and newly developed, the capital city, Islamabad concluded that Public art has a rich cultural and historical background and the local community are enthusiastically connected to it. Different community groups prefer different types of public art in their surroundings depends on the city’s profile, cultural background, and religious mindset of the local community. Overall, the sculptures and depiction of animated beings are not considering right and debatable among the Pakistani societies. On the other hand, the cultural and historical monuments are highly appreciated and welcomed by the local community of Pakistan. This study may create scope for future estimation and development of public art in Pakistan in association with Islamic laws and cultural norms of the local society.

Scouring is the most common cause of bridge failure. This study was conducted to evaluate the efficiency of the Artificial Neural Networks (ANN) in determining scour depth around composite bridge piers. The experimental data, attained in different conditions and various pile cap locations, were used to obtain the ANN model and to compare the results of the model with most well-known empirical, HEC-18 and FDOT, methods. The data were divided into training and evaluation sets. The ANN models were trained using the experimental data, and their efficiency was evaluated using statistical test. The results showed that to estimate scour at the composite piers, feedforward propagation network with three neurons in the hidden layer and hyperbolic sigmoid tangent transfer function was with the highest accuracy. The results also indicated a better estimation of the scour depth by the proposed ANN than the empirical methods.

In the realm of digital transformation, effective leadership and motivation are pivotal for organisations navigating the complexities of today’s systems. This study explores the intersection of intrinsic motivation and mental well-being among mature students—an analogy that sheds light on strategies applicable to organisational contexts. In developed nations like the UK, mental health for mature students is increasingly recognised as a crucial component of their educational journey. Mature students, who typically enrol in higher education after an educational gap and upon turning 21, often face specific challenges that can impact their mental well-being while pursuing academic goals. The primary objective of our study was to assess the relationship between intrinsic motivation and the mental well-being of mature students. Our research revealed a significant positive correlation between these two variables. Confirmatory factor analysis (CFA) results supported a one-factor solution for the sample data from mature students. Additionally, we found that intrinsic motivation is a significant predictor of the mental well-being of mature students. Recognising and addressing the unique difficulties individuals encounter and providing appropriate support can enhance their well-being and contribute to the overall success of the higher education community.

Providing healthcare workers with cost information about the medications they prescribe can influence their decisions, particularly when that information is provided at the very moment they are faced with a prescribing decision. The current study aimed to analyse the impact of nudges that presented cost information to prescribers through their organisation's electronic prescribing system. The nudges were co-created by the research team (composed of behavioural scientists) and the lead hospital pharmacist. One nudge provided simple cost information (percentage difference between two brands of Mesalazine – Asacol and Octasa). The second nudge provided the potential annual cost-saving that could result if the cheaper medication was selected across the organisation. While the statistical analyses revealed that these nudges were not effective, several administrative barriers were overcome, which may inform future research. For example, presenting aggregated cost information to the prescribers is possible even when the actual cost of medicine is confidential and can not be displaced. In addition, future research could reveal more behavioural factors that facilitate medication optimisation.

This article explores the transformative role of neural networks in the realm of biology, particularly within microscopy image processing and illustrations. Neural networks have revolutionized cell segmentation and analysis, enabling precise delineation of cell boundaries and tracking of cellular behaviours. They excel in detecting subcellular structures, unravelling intricate organelle interactions. In 3D image reconstruction, neural networks navigate volumetric datasets, enhancing our understanding of spatial cellular architecture. These networks enhance disease diagnosis by identifying anomalies and irregularities, potentially revolutionizing early detection and classification. Moreover, neural networks restore and enhance microscopy images, unveiling hidden details. Lastly, they bridge art and science, fostering captivating biological art and enriching science communication. As neural networks evolve, they promise a future of limitless possibilities, weaving together technology, science, and art to illuminate the microscopic realm in unprecedented ways.

This research paper aims to examine the various aspects of cryptocurrencies, from their inception to their current status in the financial market, using a multidisciplinary approach that incorporates mathematical and psychological methods to explore the factors that contribute to the success of celebrity endorsements and the potential risks associated with them. The first section (1.1) of this research paper will provide an overview of cryptocurrencies, exploring their history, functionality, and impact on the global financial market. This will involve examining the technical details behind cryptocurrencies, such as blockchain technology, and the differences between various types of virtual assets. The research will also discuss the potential advantages and disadvantages of investing in cryptocurrencies, as well as the regulatory challenges they face. The second section (2.1) of the research paper will focus on the psychological aspect of cryptocurrency investing, analyzing the connection between personality traits and the likelihood of purchasing a cryptocurrency based on a celebrity endorsement. This will involve investigating Howard Gardner's theory of multiple intelligences to understand the qualities that make people more susceptible to investing in a cryptocurrency without prior knowledge (Gardner, 1983). The third section (3.1) of the research paper will delve into the mathematical side of cryptocurrency investing, examining the factors that contribute to the success of celebrity endorsements and the artificial growth of cryptocurrencies. This will involve developing software to calculate the artificial growth of a cryptocurrency over a 24-hour period and analyzing the data to understand the underlying factors driving its value. By taking a multidisciplinary approach, this research will shed light on the complexities of investing in virtual assets and help inform investors of the potential risks and benefits of investing in cryptocurrencies through qualitative and quantitative analyses and through the use of a Multi-Level Latent Class Analysis (LCA).

Neurology is a quickly evolving specialty that requires clinicians to make precise and prompt diagnoses and clinical decisions based on the latest evidence-based medicine practices. In all Neurology subspecialties, Stroke and Epilepsy in particular, clinical decisions affecting patient outcomes depend on neurologists accurately assessing patient disability. Artificial intelligence (AI) can predict the expected neurological impairment from an AIS (Acute Ischemic Stroke), the possibility of ICH (IntraCranial Hemorrhage) expansion, and the clinical outcomes of comatose patients. This review article informs readers of artificial intelligence principles and methods. The article introduces the basic terminology of artificial intelligence before reviewing current and developing AI applications in neurology practice. AI holds promise as a tool to ease a neurologist’s daily workflow and supply unique diagnostic insights by analyzing data simultaneously from several sources, including neurological history and examination, blood and CSF laboratory testing, CNS electrophysiologic evaluations, and CNS imaging studies. AI-based methods are poised to complement the other tools neurologists use to make prompt and precise decisions that lead to favorable patient outcomes.

In recent times, BERT based transformer models have become an inseparable part of the 'tech stack' of text processing models. Similar progress is being observed in the speech domain with a multitude of models observing state-of-the-art results by using audio transformer models to encode speech. This begs the question of what are these audio transformer models learning. Moreover, although the standard methodology is to choose the last layer embedding for any downstream task, but is it the optimal choice? We try to answer these questions for the two recent audio transformer models, Mockingjay and wave2vec2.0. We compare them on a comprehensive set of language delivery and structure features including audio, fluency and pronunciation features. Additionally, we probe the audio models' understanding of textual surface, syntax, and semantic features and compare them to BERT. We do this over exhaustive settings for native, non-native, synthetic, read and spontaneous speech datasets

A botnical survey was conducted in Kaptai reserve forests under Rangamati district in Bangladesh to study the flora of Karnaphuli range from May 2015 to October 2018. The survey was accompanied by a collection of voucher specimens enumerates 464 plant species belonging to 334 genera under 117 families from the forest range. The survey has confirmed 31 threatened forest species from this area along with many near threatened plant species.

A botnical survey was conducted in Kaptai reserve forests under Rangamati district in Bangladesh to study the flora of Karnaphuli range from May 2015 to October 2018. The survey was accompanied by a collection of voucher specimens enumerates 464 plant species belonging to 334 genera under 117 families from the forest range. The survey has confirmed 31 threatened forest species from this area along with many near threatened plant species.

The hybrid method proposed in the study, ANFIS-GWO, combines the Adaptive Neuro-Fuzzy Inference System (ANFIS) with Grey Wolf Optimization (GWO) for the diagnosis of liver disorders. ANFIS is a powerful tool that combines the advantages of neural networks and fuzzy logic to create a hybrid model capable of handling complex and uncertain data. GWO is a metaheuristic optimization algorithm inspired by the social behaviour of grey wolves. In the ANFIS-GWO method, the hyperparameters of ANFIS are optimized using GWO. This optimization process aims to fine-tune the ANFIS model based on the available dataset, which consists of 7 characteristic attributes and 354 samples related to liver diseases. By adopting the hyper-parameters, the ANFIS-GWO method enhances the overall performance and accuracy of the diagnostic system. To evaluate the effectiveness of the ANFIS-GWO intelligent medical system, the study employs classification accuracy, sensitivity, and specificity analysis. Classification accuracy measures the overall correctness of the system in predicting liver disease cases. Sensitivity refers to the system’s ability to correctly identify individuals with liver disorders, while specificity measures its ability to correctly identify those without liver disorders. Experimental results demonstrate that the performance of the ANFIS-GWO method surpasses that of traditional Fuzzy Inference Systems (FIS) and ANFIS models that do not undergo an optimization phase. This suggests that the integration of GWO optimization significantly improves the diagnostic accuracy of the ANFIS model for liver disease diagnosis.

Dissemination of resistant pathogens via food supply chains is a notable public health danger from farm to fork. The proposed work analysed the distribution of E. coli among various sources of animal-based food supply chain. Overall, 500 samples were heaped up from livestock, poultry sectors, environment, fisheries, and dairy. Standard microbiological procedures were used to isolate and identify E. coli. Further, isolates were confirmed by using MALDI-TOF and virulence associated genes (VAGs). The phenotypic resistance pattern of the isolates was determined by molecular identification of antibiotic resistance genes (ARGs) through PCR using specific primers. Shiga toxin producing E. coli (STEC) were subjected to PCR based O typing using specific primers against different O types. Overall results revealed that 154 (30.5%) samples were confirmed as E. coli, in which77 (50%) isolates were MDR E. coli. Among these, total 52 (67.53%) isolates showed array of VAGs in which 21 (40.38%) were confirmed as STEC based on stx1 and stx2. Furthermore, 12/52 (23.07%) isolates were detected as Non-O157 STEC co-harboring mcr-1 and blaNMD-1. Overall, O26 STEC was found to be the most prevalent among different non-O157 types. Herein, results proposed that detection of such STEC MDR E. coli causing serious public health consequences in developing countries.

Adequate knowledge about the development and operation of the components of water systems is of high importance in order to optimize them. For this reason, forecasting of future events becomes greatly significant due to making the appropriate decision. Moreover, operational river management severely depends on accurate and reliable flow forecasts. In this regard, current study inspects the accuracy of support vector regression (SVR), and SVR regulated with fruit fly optimization algorithm (FOASVR) and M5 model tree (M5), in river flow forecasting. Monthly data of river flow in two stations of the Lake Urmia Basin (Vaniar and Babarud stations on the Aji Chay and the Barandouz Rivers) were utilized in the current research. Additionally, the influence of periodicity (π) on the forecasting enactment was examined. To assess the performance of mentioned models, different statistical meters were implemented, including root mean squared error (RMSE), mean absolute error (MAE), correlation coefficient (R), and Bayesian information criterion (BIC). Results showed that the FOASVR with RMSE (4.36 and 6.33 m3/s), MAE (2.40 and 3.71 m3/s) and R (0.82 and 0.81) values had the best performances in forecasting river flows in Babarud and Vaniar stations, respectively. Also, regarding BIC parameters, Qt-1 and π were selected as parsimonious inputs for predicting river flow one month ahead. Overall findings indicated that, although both FOASVR and M5 predicted the river flows in suitable accordance with observed river flows, the performance of FOASVR was moderately better than the M5 and periodicity noticeably increased the performances of the models; consequently, FOASVR can be suggested as the accurate method for forecasting river flows.

Systemic amyloidosis is a multisystem illness characterized by fibrillary protein deposition, which causes dysfunction in the afflicted organ systems. Its diagnosis is frequently delayed since the disease's symptoms are unpredictable and non-specific. Its two main variants are light chain (AL) amyloidosis and transthyretin-related ATTR amyloidosis, which has both a sporadic (wildtype, ATTRwt) and hereditary (mutated, ATTRv) subtype. We discuss a case of Amyloidosis emerging in the kidneys and heart as a result of chronic inflammation caused by failure to treat TB, as well as its typical radiological characteristics, clinical presentation, imaging and instrumental evaluations, and therapeutic plan. This case report serves as a good reminder to medical personnel to ensure thorough patient follow-up in order to avoid extremely unusual and late complications resulting from treatment default.

Lyme disease, the leading vector-borne ailment in the U.S., annually affects an estimated 476,000 individuals, predominantly in the Northeast and Upper Midwest. Despite its increasing incidence, the evaluation of risk within U.S. cities, including natural public lands, remains inadequate. This study focuses on blacklegged tick occurrences and Borrelia burgdorferi infection prevalence in 24 Staten Island parks, aiming to assess Lyme disease exposure risk. Monthly acarological risk index (ARI) calculations from 2019 to 2022 revealed elevated values (0.16-0.53) in specific parks, notably Wolfe’s Pond Park, High Rock Park, Clay Pit Pond Park, Clove Lake Park, and Fair View Park. June (0.36) and November (0.21) consistently exhibited heightened ARIs, aligning with peak tick collection months. Despite stable yearly infection rates at 28.97%, tick densities varied significantly between parks and years. Identifying a high transmission risk in specific parks in Staten Island, a highly urbanized part of New York City, emphasizes the continuous necessity for Lyme disease risk management, even within the greenspaces of large cities.

Mitochondrial Ca2+ ([Ca2+]M) uptake through Ca2+ uniporter (MCU) is central to many cell functions such as bioenergetics, spatiotemporal organization of Ca2+ signals, and apoptosis. MCU activity is regulated by several intrinsic proteins including MICU1, MICU2, and EMRE. While significant details about the role of MICU1, MICU2, and EMRE in MCU function have emerged recently, a key challenge for the future experiments is to investigate how these regulatory proteins modulate mitochondrial Ca2+ influx through MCU in intact cells under pathophysiological conditions. This is further complicated by the fact that several variables affecting MCU function change dynamically as cell functions. To overcome this void, we develop a data-driven model that closely replicates the behavior of MCU under a wide range of cytosolic Ca2+ ([Ca2+]C), [Ca2+]M, and mitochondrial membrane potential values in WT, MICU1 knockout (KO), and MICU2 KO cells at the single mitochondrion and whole-cell levels. The model is extended to investigate how MICU1 or MICU2 KO affect mitochondrial function. Moreover, we show how Ca2+ buffering proteins, the separation between mitochondrion and Ca2+-releasing stores, and the duration of Ca2+-releasing channels affect mitochondrial function under different conditions. Finally, we demonstrate an easy extension of the model to single channel function of MCU.

Transposable elements (TEs) ubiquitously exist in the human genome, and some have the ability to copy and paste themselves to other locations, resulting in new insertions. Organisms have evolved with mechanisms and machineries to repress such activity. TEs are also co-opted for beneficial functions by the host and are thus maintained in the genome. During the lifetime of humans, aberrant TE activity might cause or contribute towards diseases including neurological conditions such as Alzheimers Disease (AD) and cancer. While inflammatory pathways linked to TEs may be a part of the disease pathology, on the other hand altered TE activity involving inflammatory pathways could be recognised by disease suppression mechanisms. For this reason, TEs could be targeted for therapeutic applications aiming to prevent TE activity or reduce initial inflammatory pathways as well as to activate disease suppression mechanisms. In this review, we describe the contributory and potential preventative roles of TEs in neurological conditions and cancer from a molecular and evolutionary perspective. Evolutionary paradigms both at the unicellular and organismal level aid understanding the role of TEs in disease. These observations could pave the way for the development of novel therapeutic approaches targeting TEs.

As the world endures the coronavirus disease 2019 (COVID-19) pandemic, conditions of 35 million vulnerable individuals struggling with substance use disorders (SUDs) worldwide have not received sufficient attention for their special health and medical needs. Many of these individuals are complicated by underlying health conditions, such as cardiovascular and lung diseases and undermined immune systems. During the pandemic, access to the healthcare systems and support groups is greatly diminished. Current research on COVID-19 has not addressed the unique challenges facing individuals with SUDs, including the heightened vulnerability and susceptibility to the disease. In this systematic review, we will discuss the pathogenesis and pathology of COVID-19, and highlight potential risk factors and complications to these individuals. We will also provide insights and considerations for COVID-19 treatment and prevention in patients with SUDs.

The software industry has adopted component-based software development (CBSD) to rapidly build and deploy large and complex software systems with significant savings at minimal engineering effort, cost, and time. However, CBSD encounters issues on security trust, mainly with respect to dependability attributes. A system is considered dependable when it can produce the outputs for which it was designed with no adverse effect on its intended environment. Dependability consists of several attributes that imply availability, confidentiality, integrity, reliability, safety, and maintainability. Dependability attributes must be embedded in a CBSD model to develop dependable component software. Motivated by the importance of these attributes, this paper pursues two objectives: to design a model for developing a dependable system that mitigates the vulnerabilities of software components, and to evaluate the proposed model. The model proposed in this study is labelled as developing dependable component-based software (2DCBS). To develop this model, the CBSD architectural phases and processes must be framed and the six dependability attributes embedded according to the best practice method. The expert opinion approach was applied to evaluate 2DCBS framing. In addition, the 2DCBS model was applied to the development of an information communication technology (ICT) portal through an empirical study method. Vulnerability assessment tools (VATs) were employed to verify the dependability attributes of the developed ICT portal. Results show that the 2DCBS model can be adopted to develop web application systems and to mitigate the vulnerabilities of the developed systems. This study contributes to CBSD and facilitates the specification and evaluation of dependability attributes throughout model development. Furthermore, the reliability of the dependable model can increase confidence in the use of CBSD for industries.

The use of Supplementary Cementitious Material (SCM) is widely used in production of sustainable concrete. Blended cements, incorporating SCM such as Pulverized Fly Ash (PFA) and Ground Granulated Blast Furnace Slag (GGBFS) have been widely used to reduce the cement contents and avoid adverse environmental impacts of CO2 produced during cement manufacturing. The analysis of various structural properties of concrete such as compressive strength, flexural strength and modulus of elasticity is important for its structural application. In this research, flexural strength of 100mmx100mmx500mm beams made from blended cement were tested under three curing conditions i.e. winter, summer and under water and the flexural strength was calculated using EN-12390-5 at the ages of 28 days and 56 days. For modulus of elasticity, concrete cylinders 150mmx300mm were tested as per procedure described in BS 1881-121(1983) at the age of 28 days. The compressive strength, flexural strength and modulus of elasticity for blended cement incorporating PFA and GGBFS has been increased under summer curing environment. The experimental values of Modulus of Elasticity are compared with the provision of BS 1881.

Crosstalk between the BMP and TGF-β signaling pathways regulates many complex developmental processes from the earliest stages of embryogenesis throughout adult life. In many situations, the two signaling pathways act reciprocally. For example, TGF-β signaling is generally pro-fibrotic whereas BMP signaling is anti-fibrotic and pro-calcific. Sex-specific differences occur in many diseases including cardiovascular pathologies. Differing ratios of fibrosis and calcification in stenotic valves suggests that BMP/TGF-β signaling may vary in men and women. In this review, we focus on the current understanding of the interplay between sex and BMP/TGF-β signaling and pose several unanswered questions.

Background: Thyroid nodules are common, affecting nearly 65% of the general population. While they are widespread, it's crucial to recognize that the majority of these nodules are not cancerous and can be effectively managed through careful monitoring. Thyroid ultrasound is commonly used to evaluate thyroid nodules owing to its low cost, wide availability and technical ease of application. In sonography, it's crucial to assess characteristics and vascular flow. Yet, conventional color and power Doppler ultrasound may not always effectively capture small vessels and low velocities due to their limitations. Superior Microvascular Imaging can display the blood flow of small vessels and low-velocity blood flow, which is difficult to visualize with conventional Doppler ultrasound. Meanwhile other thyroid scans, that utilize either [99mTc] pertechnetate or (18)F-fluorodeoxyglucose, can categorize nodules as hyperactive ('hot'), exhibiting normal activity ('warm'), or having reduced/no activity ('cold'). Thus, the main goal of screening and tracking thyroid nodules is to improve the management of potentially worrisome thyroid malignancies. Methodology: The study was conducted within the structural framework of a network meta-analysis, with the index tests being - SMI, Radionuclide Scanning and Color Doppler, and the general link between them being the reference gold standard. The data collection involved searching for all pertinent literature using PubMed, Google Scholar, and the Cochrane Library databases. The essential data was extracted following the application of specific inclusion and exclusion criteria.This meta-analysis included 7 RCTs with 1,152 patients for Radionuclide Scanning, 10 RCTs with 1,847 patients for SMI and 8 RCTs with 4,480 patients for Color Doppler. They were analyzed using the QualSyst tool and the risk of bias was evaluated by using QUADAS-2 analysis.The statistical software packages MetaDiSc 1.4, RevMan (Review Manager, version 5.3), SPSS (Statistical Package for the Social Sciences, version 20) and Excel in Stata 14 were used to perform the statistical analyses. Result: According to the findings, the sensitivity for Radionuclide Scanning is calculated as 0.79 (range: 0.76 to 0.81) and specificity as 0.55 (range: 0.50 to 0.60) with a 95% confidence interval. The overall diagnostic odds ratio (DOR) for Radionuclide Scanning Is 10.54.Additionally, with a 95% confidence interval, SMI exhibits a sensitivity of 0.82 (with a range of 0.79 to 0.84) and a specificity of 0.86 (with a range of 0.84 to 0.88), while the overall DOR is approximately 25.73. Color Doppler demonstrates a calculated sensitivity of 0.71 (ranging from 0.69 to 0.74) and specificity of 0.81 (ranging from 0.79 to 0.83) with a 95% confidence interval, while its DOR is 13.48.Conclusion: As evidenced by this meta-analysis, blood flow dependent imaging techniques are superior in their abilities to be used as diagnostic tests, especially in conjunction with their use in detecting thyroid nodules. This study offers a starting point for delving deeper into the utilization of Radionuclide Imaging, Superior Microvascular Imaging and Color Doppler in diagnosing thyroid nodules in a clinical setting. Key Words: - Thyroid Nodule, Radionuclide Scanning, Superior Microvascular Imaging, Color Doppler Diagnosis, Sensitivity, Specificity, Diagnostic imaging

The paper portrays predictive models for dissolved oxygen (DO) levels in an urban lake using common water quality parameters like Temperature, pH, Conductivity and ORP at a time. Data were sampled using three real-time, industry-standard sensors, OPTOD, CTZN, and PHEHT, and then interpolated using the ArcGIS kriging technique. Correlation studies were analyzed through the ML algorithm, the correlation study signified a highly positive correlation between DO and other water parameters and the model was corroborated by R-score in order to create the linear regression model. In addition, an artificial neural network- a machine learning method using the Levenberg-Marquardt algorithm was developed to build a model to predict the do as well. Then, the performance of the models was validated and also the R² accuracy was checked of the predicted data against the actual data. Thus, the appropriateness of the ANN model for the forecasting of investigated attributes is indicated by the fact that the discrepancy between the forecasted and real ANN model is significantly lesser than that of the regression model. However, the model can be used to reveal DO data from unknown urban lake water.

Hydrothermal /super critical processes are important process to synthesize materials which are otherwise difficult to form under normal conditions. A mathematical model is developed using standard transport equations to calculate the time for heating of hydrothermal reactor and computer simulation of the model was carried out in SOLIDWORKS® to validate it. The materials used to form reactor vessel were stainless steel (outer body) and TEFLON (PFA) (inner vessel). It was shown that composite wall, its geometry, construction & properties greatly affect the time and pattern of heat transfer. The time calculated and pattern generated were found to be in good agreement with experimental values.

Impervious surface area (ISA) is a crucial indicator for quantitative urban studies. It is also important for land use land cover classification, groundwater recharge, sustainable development, urban heat island effects, and more. Spectral ISA mapping suffers from mixed pixel problems, especially with bare soil. This study aims to develop an ISA index for spatiotemporal urban mapping from common multispectral bands by reducing soil signature better than in previous studies. This study proposed a global impervious surface area index (GISAI) enhancing ISA mapping accuracy using a temporal parameter of the remote sensing (RS) dataset. Bare soil spectral reflectance shows more fluctuation than urban ISA. Therefore, the study uses minimum composites of earlier urban indices to compile minimum soil signature. It is later improved by removing water, increasing the contrast between bare soil and urban ISA and reducing bright bare soil area. This study maps the ISA of all 12 megacities using the annual RS image collection from 2021. GISAI reduced the bare soil signature and achieved an overall accuracy of 87.29%, F1-score of 0.84, and Kappa coefficient of 0.75. However, it has some limitations with grey bare soil and barren hilly areas. By limiting bare soil signature, GISAI broadens the scope of inter-urban studies globally and lengthens potential urban time-series analysis using common multispectral bands.

This report elucidates a case of papillary carcinoma of the Thyroglossal Duct Cyst in a 19-year-old female. The swelling at presentation was suprahyoid, fixed and non-mobile with deglutition or tongue protrusion. Papillary carcinoma was diagnosed post-op through histopathological examination and a follow-up total thyroidectomy was planned. As the origin of TGDC papillary carcinoma is highly debated, no evidence-based guidelines yet exist as to the best line of treatment, however, Sistrunk’s procedure followed by total/near total thyroidectomy is widely considered the standard management practice in such cases.

This study investigates the pivotal areas where Artificial Intelligence (AI) integration in healthcare warrants further exploration, leveraging insights from Boston Specialists, a forefront healthcare provider in AI adoption. Employing a qualitative case study approach, enriched by in-depth interviews and comprehensive literature reviews, we identify three main domains for potential AI expansion: scheduling efficiency, clinical documentation, and AI-driven medical research. Our results underscore the substantial enhancements AI brings to operational workflows and patient care, notably through improved scheduling systems, accuracy in medical documentation, and the facilitation of data-driven research methodologies. These findings suggest a critical need for healthcare institutions to further invest in AI technologies, focusing on these key areas to harness AI's full potential in personalizing care, optimizing efficiency, and advancing medical knowledge. The study concludes with a call for continued investigation into AI's integration within healthcare settings, emphasizing the importance of a supportive organizational infrastructure, ethical considerations, and data security in realizing AI's transformative impact on healthcare delivery and patient outcomes.

Diabetes mellitus (DM) comprises a range of metabolic disorders characterized by high blood glucose levels caused by defects in insulin release, insulin action, or both. DM is a widespread condition that affects a substantial portion of the global population, causing high morbidity and mortality rates. The prevalence of this major public health crisis is predicted to increase in the forthcoming years. Although, several drugs are available to manage DM, these are associated with adverse side effects, which limits their use. In underdeveloped countries, where such drugs are often costly and not widely available, many people continue to rely on alternative traditional medicine, including medicinal plants. The latter serve as a source of primary healthcare and plant-based foods in many low and middle-income countries. Interestingly, many of the phytochemicals they contain have been demonstrated to possess antidiabetic activity such as lowering blood glucose levels, stimulating insulin secretion and alleviating diabetic complications. Therefore, such plants may provide protective effects that could be used in the management of DM. The purpose of this article was to review the medicinal plant-based foods traditionally used for the management of DM, including their therapeutic effects, pharmacologically-active phytoconstituents and antidiabetic mode of action at the molecular level. It also presents future avenues for research in this field.

This study was performed to evaluate the efficacy of nicotinic acid against Streptococcus pneumoniae biofilm. The experimental results indicate that S. pneumoniae forms biofilms, particularly at the liquid-air interface, as evidenced by the pellicle assay. Nicotinic acid demonstrated significant inhibition of S. pneumoniae biofilm formation at 6 h and 18 h, with higher concentrations leading to lower biofilm biomass, suggesting a concentration-dependent response. However, minimal biofilm inhibition was observed at 12 h. Treatment with nicotinic acid induced FTIR spectral changes in protein biomolecules of S. pneumoniae biofilm at 6 h and 18 h, evidenced by alterations in spectral peaks at 750 cm-1, 906 cm-1, 1540 cm-1, 1548 cm-1, and 1644 cm-1. Notably, no FTIR spectral changes were detected in 12 h S. pneumoniae biofilm following exposure to nicotinic acid. These findings suggest that nicotinic acid inhibits biofilm formation in a time and concentration-dependent manner, possibly by altering the structure of protein biomolecules within the biofilm.

Majority of published articles have talked about the challenges faced by students in learning online however, little has been talked about what the teachers have gone through especially during these times of the pandemic. This paper discusses the factors university teachers face when teaching online. These factors include accessibility to the internet, level of interaction between teachers and students, costs incurred, availability of training and academic policies kept in place to enhance effectiveness of teaching online. These are further divided into personal, social and economic factors where the teachers’ age, gender, remuneration, availability of resources, location and the economic status of the country is discussed in relation to the effectiveness of online learning. Upon carrying out a literature review on articles written on the effectiveness of online learning with the main focus being teachers, it was noted that the main factors affecting the effectiveness of online learning was the availability of internet connection and training provided to teachers. In Kenya, majority of the rural areas lack access to the internet and devices to learn online which makes it difficult for a teacher to teach effectively given the pandemic constraints. This study sheds light on the need for institutions and governments to take input from their teachers and train them on how to make online learning more effective. It also shows the status of universities in Kenya which had to shift to learning online due to the pandemic. Majority of them took time to adapt to this new change due to the discussed factors. Therefore it is recommended that the Government should train teachers and address the issue of lack of internet and electricity in Kenya.

The occurrence and ability of Salmonella typhimurium to withstand the effects of various antibiotics has been extensively recorded. This highlights the necessity for alternative methods to combat Salmonella infections. The current investigation aimed to ascertain the impact of benzoic acid on the extent of surface coverage and biomass of S. typhimurium biofilm after 48 and 72 hours. The findings indicated that all the different doses of benzoic acid (ranging from 3.125% to 50%) resulted in a decrease in the extent of biofilm surface coverage. Benzoic acid exhibited a substantial inhibitory effect on the biofilm biomass at all concentrations. Higher concentrations of benzoic acid led to a decrease in biofilm biomass, suggesting a concentration-dependent response. This finding implies that benzoic acid is effective in managing Salmonella infections.

Background: Appendicitis is a common cause of emergency department visits and appendectomies in the US, with 250,000 appendectomies performed annually. Current diagnostic methods, such as clinical findings, lead to inaccuracies and missed diagnoses, increasing morbidity and mortality. The only solution is surgery, but current hematological tests are not reliable and may lead to unnecessary surgery if the underlying etiology is self-limiting or requires medical treatment. This study explores the role of MRI as a diagnostic modality that can replace US/CT and supplement traditional clinical diagnostic signs while avoiding ionizing radiation and intravenous contrast medium. The purpose of this meta-analysis is to determine the accuracy of MRI as a diagnostic modality in diagnosing appendicitis, addressing concerns about diagnostic modalities and their adverse effects, and addressing the necessity and success of relevant interventions. Methods: Medical literature was comprehensively searched and reviewed without restrictions to particular study designs, or publication dates using PubMed, Cochrane Library, and Google Scholar databases for all relevant literature formulated in English. The extraction of necessary data proceeded after specific inclusion and exclusion criteria were applied. Meta Analysis was performed for 5206 patients, with 35 RCTs being selected. Analysis was done using the QualSyst tool, wherein two writers independently assessed the caliber of each study as well as the use of the Cochrane tool for bias risk apprehension. The statistical software packages RevMan (Review Manager, version 5.3), SPSS (Statistical Package for the Social Sciences, version 20), and Excel in Stata 14 were used to perform the statistical analyses along with other analytical software. Results: MRI had an overall sensitivity of over 95%, an overall specificity of 94.2% with a PPV of 0.875 in comparison to CT scan in the diagnosis and intervention regarding appendicitis. Conclusion: These findings strongly suggest that MRI is a reasonable alternative to CT for the diagnosis of appendicitis in hospitals with appropriate access to this technology for reasons about accuracy, reliability, and reproducibility as well as addressing safety concerns.

The study investigates the evolution of soil pore structure and shear strength deterioration in compacted clayey soil under controlled wetting and drying (wd) cycles, which are expected to become more frequent due to climate change. Thirty soil samples were compacted at optimal moisture content and 90% of maximum dry density. These samples were then subjected to 0, 1, 5, 10, and 15 controlled wd cycles from saturation to the wilting point, and volumetric changes were recorded during each cycle. After the wd treatment, the soil samples were scanned using X-ray Computed Tomography (CT) at 50 μm resolution and then sheared under unconsolidated-undrained and consolidated-undrained conditions in a triaxial test. Significant shrinkage and swelling of soil samples were observed during wd cycles, with average volumetric strain fluctuating between +12% at saturation and -5% at the wilting point. X-ray CT visualisation and analysis revealed higher porosity, more prominent pores and increased pore length in soil samples with increasing wd cycles. Both undrained and effective soil shear strength markedly decreased with increasing wd cycles. CT-derived macroporosity and pore length were significant predictors of the soil's undrained and effective shear strength when exposed to wd cycles. The findings emphasise the considerable impact of climate change, specifically wd cycles, on clayey soil, highlighting the need for consideration in the design of earth-based infrastructure.

In this study, we introduce the dynamics of a Hepatitis B virus (HBV) model with the class of asymptomatic carriers and conduct a comprehensive analysis to explore its theoretical aspects and examine the crossover effect within the HBV model. To investigate the crossover behavior of the operators, we divide the study interval into two subintervals. In the first interval, the classical derivative is employed to study the qualitative properties of the proposed system, while in the second interval, we utilize the ABC fractional differential operator. Consequently, the study is initiated using the piecewise Atangana-Baleanu derivative framework for the systems. The HBV model is then analyzed to determine the existence, Hyers-Ulam (HU) stability, and disease-free equilibrium point of the model. Moreover, we showcase the application of an Adams-type predictor-corrector (PC) technique for Atangana-Baleanu derivatives and an extended Adams-Bashforth-Moulton (ABM) method for Caputo derivatives through numerical results. Subsequently, we employ computational methods to numerically solve the models and visually present the obtained outcomes using different fractional-order values. This network is designed to provide more precise information for disease modeling, considering that communities often interact with one another, and the rate of disease spread is influenced by this factor.

Introduction: Biliary Atresia (BA) is a common cause of neonatal cholestatic jaundice which, if recognized and treated early, can be life-saving for the infant. If the liver biopsy suggests the presence of BA, exploratory laparotomy is then carried out to confirm the diagnosis, along with the Kasai procedure to provide drainage to the bile secreted by the liver. The purpose of this study is to get a deep dive into all the various imaging modalities that can diagnose BA more effectively and with absolute certitude, thus helping prevent several children from a grave prognosis.Methodology: For the collection of the data, a search was done by two individuals using PubMed, Google Scholar, and Cochrane Library databases for all relevant literature. Each qualifying paper was evaluated independently by two reviewers. Each article was analyzed for the number of patients, their age, procedure modality, complexity of ethology, and incidence of the pre-decided complications. The statistical software packages RevMan (Review Manager, version 5.3), SPSS (Statistical Package for the Social Sciences, version 20), Google Sheets, and Excel in Stata 14 were used to perform the statistical analyses. The data was obtained and entered into analytic software.Results: A total of 39 studies with 3,679 subjects were selected for the study, out of which 7 studies showed sensitivity above or equal to 95%, and an astounding 14 studies showed specificity above 95%. The value of True Positive (TP) was 1280, that of True Negative (TN) was 1817, that of False Positive (FP) was 239, and that of False Negative (FN) was 343. With a confidence interval of 95%, sensitivity, specificity, and positive predictive values were calculated. The sensitivity of Ultrasonography for Biliary Atresia is 0.79, with a CI of 95% in a range of 0.77 to 0.81. The specificity of Ultrasonography for Biliary Atresia is 0.88, with a CI of 95% in a range of 0.87 to 0.90. Conclusion: Even though several radiological techniques at present help to detect BA, USG of the abdomen proves to be an effective diagnostic and a modest screening test for the detection of BA.

Carrageenan (car-), used in the pharmaceutical as well as food industry, is marine sulfated polysaccharides. The carrageenan blends (CB) of kappa (κ-), iota (ι-), and lambda (λ-) of 50/50 weight by weight are multipurpose and biocompatible hydrophilic polymers. They were subjected to adsorption of copper (Cu2+) ions. The aim of the study was to conduct extensive rheological and mechanical studies rendering them suitable for biological purposes. The rheology was conducted at various temperatures using a frequency curve, frequency sweep, loss modulus, and storage modulus analysis. Models of rheology like Ostwald, Bingham, and Modified Bingham models were utilized. The rheological results demonstrated non-Newtonian/pseudo-plastic behavior at various temperatures. The models of rheology demonstrated good flow properties and rheological performance of these materials. These materials could be exploited for their application in pharmaceuticals, food, and cosmetics. Thus, our study reflects that these CB can be safely exploited in the healthcare, pharmaceutical, and food industry. However, further studies should be conducted to evaluate their effectiveness in clinical studies.

An increase in the use of smartphones has laid to the use of the internet and social media platforms. The most commonly used social media platforms are Twitter, Facebook, WhatsApp and Instagram. People are sharing their personal experiences, reviews, feedbacks on the web. The information which is available on the web is unstructured and enormous. Hence, there is a huge scope of research on understanding the sentiment of the data available on the web. Sentiment Analysis (SA) can be carried out on the reviews, feedbacks, discussions available on the web. There has been extensive research carried out on SA in the English language, but data on the web also contains different other languages which should be analyzed. This paper aims to analyze, review and discuss the approaches, algorithms, challenges faced by the researchers while carrying out the SA on Indigenous languages.

The aim of this work is to analyze and investigate the shape preserving properties of ternary 4-point non-stationary interpolating subdivision schemes constructed by Beccari et al. [1] with a tension parameter !k+1 which can reproducing exponential. Moreover, the conditions on the initial control points are developed that allow user to generate shape preserving limit curves after a nite number of subdivision steps and generalize these results in limiting case. Signicance of derived conditions are illustrated through graphs and the whole discussion is followed by examples.

ntroduction: Respiratory tract Infections are the greatest cause of death worldwide. Since its outbreak in 2019, the coronavirus pandemic (COVID-19) has been a challenge to humans in terms of treatment and prevention of this respiratory viral infection. The re-emergence of respiratory viral infections like influenza, pose a serious hazard to global public health because they occur seasonally. Creating broad-spectrum antiviral compounds for rapid action in the case of an outbreak crisis, as well as bioweapon defences, is critical. Human galectin-3 is found in high concentrations in activated T lymphocytes, epithelial and endothelial cells, and fibroblasts. ProLectin -I and ProLectin -M are both galectin antagonists. Blocking viral entry with a complex polysaccharide component "ProLectin-M" has downstream effects on viral reproduction enabling it to be used as a therapeutic tool and a safe alternative to conventional anti-viral medicines. Methods: In total, 3 cell based assays have been conducted to evaluate antiviral efficacy of ProLectin–I and ProLectin-M against SARS-CoV-2 virus, Influenza-A (H1N1), and human respiratory syncytial virus (hRSV) strain A2. ProLectin-M and ProLectin-I were evaluated for their anti-viral potency using SARS-CoV2 virus strain by viral RNA Extraction and qRT-PCR assays. The plaque assays were carried out to determine the antiviral activity of the test products (ProLectin-I and ProLectin-M) against ‘Influenza-A (H1N1)-A/PR/8/34 (TC adapted)’ and ‘Human respiratory syncytial virus (hRSV) strain A2’ in a cell based in vitro setting. As eference standard, "Oseltamivir Phosphate" and "Remdesivir" were used to determine antiviral activity of test products against H1N1 and hRSV strains respectively.Results: The IC_{50 of} ProLectin-M and ProLectin-I against SARS-CoV-2 virus was found to be 6248 ng/ml (6.2µg/ml) and 4207 ng/ml (4.2μg/ml) respectively. The CC₅₀ value was similar in both the test products i.e. >100 µg/ml. Against Influenza A (H1N1) strain, ProLectin-M exhibited 95 % reduction in the viral load at the test concentration of 21.8 µg/mL with an IC₅₀ value of 5.4 µg/mL whereas, ProLectin-I did not show any cytotoxicity till 250 µg/mL concentration. Against 'human respiratory syncytial virus (hRSV) strain A2, ProLectin-M exhibited 65 % reduction in the viral load at the test concentration of 43.75 µg/mL with an IC₅₀ value of 27.41 µg/mL whereas, ProLectin- I did not show any cytotoxicity till 250 µg/mL concentration. Conclusion: Both ProLectin-I and ProLectin-M have been reported to exhibit broad-spectrum antiviral activity in ‘in-vitro’ setting. ProLectin-M reducing influenza-A virus by 95% and hRSC strain A2 by 65%. To better understand broad spectrum antiviral activity of ProLectin-I and ProLectin-M, further pre-clinical research is warranted.

According to published descriptions, one of the most incapacitating forms of orofacial pain is trigeminal neuralgia (TN). At its core, trigeminal neuropathic pain (TN) is still a clinical diagnostic that has to be differentiated from other forms of TN and face pain linked to other neuralgias or headache disorders. Imaging can only help with the cause of the pain, whether it’s a vascular origin or not. It is becoming more and more evident that there is no one-size-fits-all medication or surgical procedure that can effectively treat every patient with trigeminal neuralgia (TN). This is probably because TN is a diverse collection of conditions that all present with face discomfort. Medical therapy using anticonvulsants like carbamazepine is still the first-line treatment for TN. If this doesn't work for the patient, surgical treatments are available. Microvascular decompression is often a safe, efficient operation with results that are both rapid and long-lasting. Patients who may benefit from percutaneous techniques such as radiofrequency ablation, glycerol ablation, balloon compression, or a combination, include those who cannot undergo general anesthesia or whose medical conditions prohibit a suboccipital craniectomy. Radiosurgery may be a great option for patients with bleeding diathesis brought on by blood-thinning medications who are not eligible for invasive procedures or who do not want to undergo open surgical procedures, as long as the patient is aware that achieving maximum pain relief may take several months. In conclusion, peripheral neurectomies persist in offering a low-cost and resource-saving substitute for pain management to those residing in areas with restricted financial and healthcare resources. In the end, developing a better understanding of the molecular processes behind trigeminal neuralgia will lead to new, less intrusive, and more effective treatments.

The natural and man-made landscape settings in the Khyber Pakhtunkhwa (KPK) province of Northern Pakistan have significantly changed in the last decade due to increasing demands of urbanized populace, migration, two major natural disasters, and climate change. The aim of this study is to analyze land possession, income and land-use diversification of KPK administered Charsadda district. Field data is collected through a sample survey. Furthermore, freely available Landsat 7 satellite images are used to classify land-use classes (e.g. vegetation, built-up) for two different years (e.g. 2005 and 2017) for cross-verification and comparison. The highest 45% of 80% land-owners occupy land-area between 1-10 hectares. Annually, the highest 57.5% of the total farmers / employed in-habitants of surveyed regions earn more than Rs. 100,000 or ~ $ 970 from agriculture activities. About 41.9% land-area covered by agricultural-land is transformed into built-up area since 2007, which is attributed to the increasing demand for buildings and commercial markets. The highest diversification is reported in Naguman area of Charsadda district followed by Rajjar and Niami. Population growth and huge migration of displaced persons from neighboring tribal areas are likely to be few factors which contributed to such a drastic change in land-use pattern since 2007 to 2017. Urgent attention of the policy makers, agricultural experts and society is required to minimize land degradation and to thwart further agricultural-land loss.

Artery of Percheron Infarct (AOP) is a rare congenital anatomical vascular variant supplying the paramedian thalamus and the rostral midbrain. It arises from either proximal segment of the posterior cerebral artery (P1). The symptoms of an AOP infarction might vary, although they typically manifest as memory loss, altered mental status, and supranuclear vertical gaze palsy. Most of the time, the initial CT scan fails to diagnose the AOP infarct. Most of these diagnoses are made when ischemic stroke patients are not eligible for thrombolytic therapy. We report a case of a 40-year-old female with a history of well-managed hypertension, who presented in the ER with chief complaints of altered behavior, altered gaze palsy, and drowsiness. Initially, the CT scan did not show pathological changes. The diagnosis was made the next hospital day by MRI. Our case presents an unusual presentation and the lack of evidence of AOP infarction on a CT scan does not exclude its diagnosis. An infarcted Percheron artery requires a thorough clinical and radiological examination.

Background. Nanotechnology is promising field for generating new applications. A green synthesis of nanoparticles through biological methods using plant extract have a reliable and ecofriendly approach to improve our global environment. Methods. Silver nanoparticles (AgNPs) were synthesized using aqueous extract of Anagalis arvensis L and silver nitrate and were physicochemically characterized. Results. The stability of AgNPs toward acidity, alkalinity, salinity and temperature showed that they remained stable at room temperature for more than two months. The SEM and TEM analysis of the AgNPs showed that they have a uniform spherical shape with an average size in the range of 40–78 nm. Further 1-Dibhenyl-2-Picrylhydrazl radical in Anagalis arvensis L.mediated AgNPs showed a maximum activity of 98% at concentration of 200μg/mL. Hydrogen peroxide scavenging assay in Anagalis arvensis L. mediated AgNPs showed a maximum activity of 85% at concentration of 200μg/mL. Reducing power of Anagalis arvensis L.Ag NPs exhibited a higher activity of 330 μg/mL at concentration of 200 μg/mL. These NPs have cytotoxic effects against brine shrimp (Artemia salina) nauplii with a value of 53% LD 178.04μg/mL. Conclusion. The AgNPs synthesized using Anagalis arvensis L. extract demonstrate a broad range of applications.

Water pollution is the main problem in the current scenario which is being faced by mankind due to the industrial and commercial effects. Industrial effluents contain heavy metals and inorganic ions like nitrates and phosphate ions. These ions are being included in waterways through industrial runoff. When the concentration of these hazardous pollutants increases in aquatic flora and fauna causes severe health problems. So remediation of these toxicants from water reserves is of chief importance. Conventional processes along with modern processes are being used for the treatment of industrial wastes. Photo-degradation is a modern method used for the degradation of inorganic ions due to its environmentally friendly nature and cost-effectiveness. In a recent study Aluminum oxide (Al2O3) nanoparticles were synthesized via a green approach at different pH by using Cymbopogan citratus (lemongrass) plant extract and these nanoparticles were used for the removal of inorganic ions from wastewater. The nanoparticles of different pH showed different % degradation of the inorganic ions in acidic medium removal of inorganic waste was less, in basic media % degradation was more as compared to acidic media but maximum % degradation was observed in neutral media like that average % degradation 91% and 81% was observed for nitrate and phosphate ions. The maximum absorbance occurred at 212nm and Al2O3 nanoparticles showed absorbance from 210nm-217nm. The R2 values of pseudo1st, 2nd, and BMG models were 0.956, 0.837, 0.7007 0.95, 0.896, and 0.756 for the nitrate and phosphate ions. Characterizations of synthesized particles were investigated by using UV-visible spectroscopy and other analytical methods like X-ray diffraction (XRD) and Fourier transform infrared spectroscopy (FTIR). The statistical analyses were done using Simple Linear regression (SLR).

The natural and man-made landscape settings in the Khyber Pakhtunkhwa (KPK) province of Northern Pakistan have significantly changed in the last decade due to increasing demands of urbanized populace, migration, two major natural disasters, and climate change. The aim of this study is to analyze land possession, income and land-use diversification of KPK administered Charsadda district. Field data is collected through a sample survey. Furthermore, freely available Landsat 7 satellite images are used to classify land-use classes (e.g., vegetation, built-up) for two different years (e.g., 2005 and 2017) for cross-verification and comparison. The highest 45% of 80% land-owners occupy land-area between 1–10 hectares. Annually, the highest 57.5% of the total farmers / employed in-habitants of surveyed regions earn more than Rs. 100,000 or ~$970 from agriculture activities. About 41.9% land-area covered by agricultural-land is transformed into built-up area since 2007, which is attributed to the increasing demand for buildings and commercial markets. The highest diversification is reported in Naguman area of Charsadda district followed by Rajjar and Niami. Population growth and huge migration of displaced persons from neighboring tribal areas are likely to be few factors which contributed to such a drastic change in land-use pattern since 2007 to 2017. Urgent attention of the policy makers, agricultural experts and society is required to minimize land degradation and to thwart further agricultural-land loss.

This comparative research paper examines the difference between sugarcane harvesting practices in Thailand and India. The objective of research was to investigate and compare current pattern of sugar harvesting and its impact of these approaches on labor health conditions in the sugarcane industry of both the countries as India and Thailand. Data were collected from target population groups (40 each) from study areas, namely Kanchanaburi and Saraburi provinces in Thailand and Beed District of Maharashtra state from India. The data showed that comparatively in Thailand, adoption of mechanized harvesting was seen more. However in India, mechanized harvesting was seen increasing but still people were largely involved in sugarcane harvesting and it had ill effects on the overall health of female workers specially. The result clearly indicated that there was drastic difference in harvesting system and labor health conditions in Thailand and India. The findings underscore the multifaceted impact of their occupation on various aspects of health including general well-being of female sugarcane cutters. The strenuous nature of sugarcane cutting, coupled with inadequate protective measures and limited access to healthcare has contributed to a range of health care challenges among female sugarcane cutters in India.

Presenting a case report on the occurrence of IgA nephropathy with hepatitis B infection in a 32-year-old male patient with main complaints of generalized weakness, easy fatigue, and bilateral swelling of the lower extremities. IgA nephropathy (IgAN), or Berger’s disease, is the most common primary glomerulonephritis worldwide. It is characterized by the formation of IgA1-containing circulating immune complexes and their deposition in the glomerular mesangium. Its etiology remains multifactorial and often idiopathic. IgA nephropathy alone does not have an infectious etiology; instead, it usually develops in conjunction with an infectious condition that triggers a dysregulated immune response. There is no proof that any particular infectious agent is the secondary cause of IgA nephropathy. Hepatitis B virus (HBV) infection is an infectious agent associated with renal complications, including IgA nephropathy. Symptoms include gross haematuria and mild proteinuria indicative of renal involvement. Laboratory investigations and serological tests are followed by imaging studies such as ultrasound and renal biopsy to confirm the diagnosis. The challenges encountered during the diagnostic process included overlapping symptoms and limitations of available diagnostic tests, highlighting the need for comprehensive diagnostic evaluation and multidisciplinary management approaches in similar cases. This case underscores the importance of recognizing and managing both conditions simultaneously to prevent long-term complications such as end-stage renal disease.

Increasing demand for electricity and modernization of power systems within competitive markets induce power systems to operate close to their stability limits. Therefore, a power system continuous monitoring and control by using voltage stability indices are known exigence. This is the first-ever effort, examined more than 40 voltage stability indices thorough an exhaustive study based in on their formulation, application, performance, and assessment measures. Which is conducted based on a logical and chronological order considering the most recent worldwide applied voltage stability indices. However, the generalizability of such an immense diversity of these indices in term of multivariable objectives subjects to a certain limitation to summate into a deciphered outcome. Despite all these obstacles, this study systematically reviews available indices in the literature within the past three decades to set out an integrated knowledge with an insight up-to-date exposition. That followed with a comparative analysis in term of their similarity, functionality, applicability, formulation, merit, demerit, and overall performances. Also, a broad categorization of voltage stability indices is addressed. This study with an immediate implication in practice as an exhaustive roadmap can be counted a planning and operation reference in the context of voltage stability for students, researchers, scholars, and practitioners.

The most important plastic resins used for wire coating are Polyvinyl Chloride (PVC), Nylon, Polysulfone and Low-high density polyethylene (LDPE / HDPE). In this article,the coating process is performed using elastic-viscous fluid as a coating material for wire coating in a pressure type coating die. The elastic-viscous fluid is electrically conducted in the presence of an applied magnetic field. The governing non-linear equations are modeled and then solved analytically by utilizing an Adomian decomposition method (ADM). The convergence of the series solution is established. The results are also verified by Optimal Homotopy Asymptotic Method (OHAM). The effect of different emerging parameters such as non-Newtonian parameters α and β, magnetic parameter M and the Brinkman number Br on solutions (velocity and temperature profiles) are discussed through several graphs. Additionally, the current result also compares with the published work already available in the literature.

An increasing number of studies have proposed that corporate social responsibility (CSR) performance depends on how companies apply their resources and capabilities to implement CSR. A firm’s ability to integrate, build, and reconfigure internal and external competencies to respond to environmental changes is its dynamic capability. Implementation of CSR at the strategic level will contribute to a firm’s sustainability. However, the research on strategic CSR is incipient. This study explores possible mechanisms to investigate how dynamic capability influences the performance of strategic CSR in China. By analyzing 134 Chinese listed companies in the period 2017–2019, in this study, we found that firms with a high level of dynamic capability were less likely to adopt strategic CSR practices, and had a low strategic CSR adoption performance. The results confirmed the loss aversion channel, indicating that firms with a high dynamic capability level were loss averse and that managers had a decreasing sensibility in decision-making and allocated fewer company resources in CSR projects. These results can help companies to better understand the dynamic capability and how dynamic capability contributes to the adoption of strategic CSR and performance over time. The policy implications of the study are also discussed.

Fertility preservation technologies have existed for decades, and the field is rapidly advancing; limited data exist regarding the use of these technologies by transgender patients. Many options are available for transgender patients who wish to preserve fertility before transitioning. These options include the cryopreservation of gametes, ovarian tissue, or embryos. Currently, ejaculated, or testicular sperm, immature oocytes, and ovarian tissue can be preserved for later use, but no such use option exists for immature testicular tissue. Many financial, sociological, and legal barriers and a lack of awareness among physicians and patients also hindered the utilization of these fertility preservation services. While options are abundant, usage rates are relatively low. The initial data regarding the successful use of preserved tissues appears promising, with birth rates not dissimilar to non-transgender patients. Further investigations into this area are needed. In addition, counseling regarding fertility preservation options should become a significant part of the provider-patient conversation before transitioning therapies.; fertility; transgender; reproductive technology.

Models of subsurface structures are important for successful deposit exploration but are challenged by the need to integrate data from different geophysical methods. In the present study, we evaluated a method of joint inversion in which audio-magnetotelluric (AMT) and dual frequency induced polarization (DFIP) data sets are inverted simultaneously to produce a consistent 2D resistivity model to show a clear image of subsurface structures. To achieve the objectives, we conducted AMT and DFIP surveys first on the same survey line within the Dongjun lead-zinc deposit in inner Mongolia by developing 31 AMT survey sites with an interstation separation of 40 m on a 1440 m survey track and operated in fifty-three frequencies in the range 1–10,400 Hz to record the resistivity distribution of subsurface to depths exceeding 800 m. The same survey setup up was applied to the DFIP method by utilizing the SQ-3C model with a pole-dipole array configuration and conducted measurements at frequencies of 4 Hz and 4/13 Hz. We first separately inverted AMT and DFIP measurements. The two-dimensional (2D) model obtained from AMT data revealed distinct low resistivity anomalies in the middle of the 2D inversion model. In contrast, the DFIP inversion model showed a high resistive body in the same region. In response to the discrepancies observed in the separate 2D inversion models, we implemented a joint inversion for both the AMT and DFIP datasets. The joint inversion resistivity model shows surficial conducting bodies and a high conductive body along the profile with relatively high Percent Frequency Effect (PEF) indicating high chargeability. The final joint inversion resistivity model clearly images the large silica alteration zone and the Pb-Zn mineralization. This study demonstrates the feasibility of a joint inversion methodology and highlights the value of integrating geophysical methods through joint inversion for enhanced characterization and exploration of lead-zinc ores.

Crystallization behavior of hexadecane (C₁₆H₃₄), octadecane (C₁₈H₃₈), eicosane (C₂₀H₄₂), and docosane (C₂₂H₄₆) dispersions of similar mean droplet diameter (x_50.2 ≈ 15 µm) was investigated in quiescent systems and compared to crystallization under mechanical stress. In quiescent systems, the required supercooling decreased with increasing chain length of the alkanes to initiate crystallization. Crystallization of alkane dispersions under mechanical stress resulted in similar onset crystallization supercooling, as during quiescent crystallization. Increase of mechanical stress did not affect the onset crystallization supercooling within alkane dispersions.

Abstract: Objective: To assess both individual and interactive effects of prenatal medical conditions depression and Diabetes, and health behaviors including smoking during pregnancy on infant birth defects. Methods: The data for this research study were collected by the Pregnancy Risk Assessment Monitoring System (PRAMS) in 2018. Birth certificate records were used in each participating jurisdiction to select a sample representative of all women who delivered a live-born infant. Complex sampling weights were used to analyze the data with a weighted sample size of 4,536,867. Descriptive statistics were performed to explore frequencies of the independent and dependent variables. Bivariate and multivariable analyses were conducted to examine associations among the independent and dependent variables. Results: The results indicate and significant interaction between the variables smoking and Depression and Depression and Diabetes (OR= 3.17; p-value <0.001 and OR= 3.13; p-value <0.001 respectively). Depression during pregnancy was found to be strongly associated with delivering an infant with a birth defect (OR= 1.31, P-value < 0.001). Conclusion: Depression during pregnancy and its interaction with smoking and Diabetes are vital in determining birth defects in infants. The results indicate that birth defects in the United States can be lowering Depression in pregnant women.

The field of program classification, a critical aspect of software engineering, facilitates understanding and categorization of code across various applications, including anomaly detection, and code quality assessment. The advancement of cross-language program classification opens up avenues for efficient code translation among different programming languages, significantly aiding developers in rapid coding and reducing development cycles. Existing research primarily focuses on semantic code analysis, with limited emphasis on cross-linguistic challenges. To address this, we introduce an innovative neural network model, CodeSemanticsNN, which leverages a refined Syntax Structure (SS) approach. This model consists of two integral mechanisms: first, it adopts a novel SS representation that combines sequential and graph-based SS structures, enhancing semantic feature capture. Second, it employs a 'unified vocabulary' strategy to bridge the gap between diverse programming languages, facilitating efficient cross-language classification. Additionally, we have compiled a comprehensive dataset of 20,000 files spanning five programming languages, serving as a benchmark for cross-language classification. Our experiments on this dataset demonstrate that CodeSemanticsNN surpasses existing models in four key metrics: Precision, Recall, F1-score, and Accuracy.

Building electric energy is characterized by a significant increase of its uses (e.g. vehicle charging), a rapidly declining cost of all related data collection and a proliferation of smart grid concepts, including diverse and flexible electricity pricing schemes. Not surprisingly, an increased number of approaches have been proposed for its modeling and forecasting. In this work, we place our emphasis on three forecasting related issues. First, on the forecasting explainability, i.e. the ability to understand and explain to the user what shapes the forecast. To this extent we rely on concepts and approaches that are inherently explainable, such as the evolutionary approach of genetic programming (GP) and its associated symbolic expressions, as well as the so-called SHAP (SHapley Additive eXplanations) values, which is a well established model agnostic approach for explainability, especially in terms of feature importance. Second, we investigate the impact of the training timeframe on the forecasting accuracy; this is driven by the realization that a fast training would allow for faster deployment of forecasting in real life solutions. And third, we explore the concept of counterfactual analysis on actionable features, i.e. features that the user can really act upon and which therefore present an inherent advantage when it comes to decision support. We have found that SHAP values can provide important insights into the model explainability. As for GP models, we have found comparable and in some cases superior accuracy when compared to its neural-network and time-series counterparts but a rather questionable potential to produce crisp and insightful symbolic expressions, allowing a better insight into the model performance. We have also found, and report here on an important potential especially for practical, decision support, solutions of counterfactuals built on actionable features and short training timeframes.

With the rise of powerful computational technologies, healthcare systems are going through a paradigm shift to the era of healthcare 5.0, also known as" smart healthcare". This new-age healthcare system not only enhances the life of patients but also aims to reduce healthcare costs significantly. People's health data collected through various means, including various Internet of Things (IoT) devices, is too sensitive to be regulated by particular organisations owing to increasing privacy and security threats. The sheer size of data makes it difficult for centralised bodies to regulate, due to which third-party involvement is introduced, which again poses threats to the privacy of the data holder. Motivated by the abovementioned gaps, we propose a decentralised approach using Ethereum blockchain technology and Oasis protocol. The patient-driven solution approach effectively solves the privacy problem by providing complete control of data to the owner. Along with this, byproducts such as fine-grained access control and on-chain data processing capabilities are also obtained.

Irrigation water management components evaluation is mandatory for sustainable irrigated agriculture production in the era of water scarcity. In this research spatio-temporal distribution of irrigation water components were evaluated at canal command area in Indus Basin Irrigation System (IBIS) using remote sensing based geo-informatics approach. Satellite derived MODIS product-based Surface Energy Balance Algorithm for Land (SEBAL) was used for the estimation of the Actual Evapotranspiration (ETa). Satellite derived SEBAL based ETa was calibrated and validated using the ground data-based advection aridity method (AA). Statistical analysis of the SEBAL based ETa and AA shows the mean 87.1 mm and 47.9 mm and, 100 mm and 77 mm, Standard deviation of 27.7 mm and 15.9 mm and, 34.9 mm and 16.1 mm, R of 0.93 and 0.94, NSE of 0.72 and 0.85, PBIASE -12.9 and -4.4, RMSE 34.9 and 5.76 for the Kharif and Rabi season, respectively. Rainfall data was acquired from the Tropical Rainfall Measuring Mission (TRMM). TRMM based rainfall was calibrated with the point observatory data of the Pakistan Metrological Department Stations. Canal water data was collected from the Punjab Irrigation department for the assessment of canal water availability. Water The water balance approach was applied in the unsaturated zone for the quantification of the gross and net Groundwater irrigation. Mmonthly variation of ETa with the minimum average value of 63.3 mm in January and the maximum average value of 110.6 mm in August was found. While, the average annual of four cropping years (2011-12 to 2014-15) ETa was found 899 mm. Average of the sum of Net Canal Water Use (NCWU) and Rainfall during the study period of four years was only 548 mm (36% of ETa) and this resulted the 739.6 mm of groundwater extraction. While the annual based variation in groundwater extraction of 632 mm and 780 mm was found. Seasonal analysis revealed 39% and 61% of groundwater extraction proportion during Rabi and Kharif season, respectively. The variation in four cropping year’s monthly groundwater extraction was found 28.7 mm to 120.3 mm. This variation was high in the 2011-12 to 2012-13 cropping year (0 mm to 148.7 mm), dependent upon the occurrence of rainfall and crop phenology. Net groundwater irrigation, estimated after incorporating the efficiencies was 503 mm year-1 on average for the four cropping years.

The study examines the relationship between corporate social responsibility (CSR) and the corporate life cycle (CLC) of the Chinese pharmaceutical listed companies for the duration of 2010 to 2018. The firm cash flow pattern is used as a proxy for the CLC. The study results indicate that the relationship between CSR and CLC is positive and linear in all the phases of the CLC including, the introduction, growth and maturity stage. Although the relationship is smaller and more significant at the maturity phase. The research further shows that investors incorporating social responsibilities values play a key role in the firm cash flow performance (CFP) across all the firm stages. Whilst, employees espousing social responsibility tenets can only improve CFP in the decline or shakeout stages. Likewise, embedding CSR into the customers group only improves CFP at the maturity stage. Applying the lag effects lead to the same study results. The finding for the bi-directional causality indicates that although CSR can positively influence CFP, CFP is ultimately more associated with the firm unobservable characteristics rather than performance attributed to CSR. On the whole, our study results point to positive causality between CSR and CFP across all the firm life stages and the CSR has a mediating effect on each life cycle.

This paper proposed a damping method for enhancing oscillatory stability performance of power systems with high penetration of renewable energy by a resilient wide-area multi-mode controller. The resilient wide-area multi-mode controller is used as an additional controller in a renewable energy system with a battery energy storage to enhance the damping of the critically weak modes. The weak modes are likely to be triggered in the event of line outages or any other disturbances, and the system may become unstable in the absence of proper corrective and preventive control. A firefly algorithm has been employed to design such a controller. Eigenvalue analysis and time-domain simulation are used to analyze the performance of the proposed controller in a realistic representative power system. From the simulation results, it is evident that the oscillatory stability performance of the renewable rich power system can be enhanced with the proposed control to keep the damping on critical modes to the industrial standards. Furthermore, renewable energy penetration can be increased significantly in the realistic representative system by introducing the proposed controller without disturbing the oscillatory stability margin.

This study assesses the impact of militarization, industrialization, technological innovation, and energy consumption on CO2 emissions in NATO countries, divided into "traditional" (Group 1) and "new member" states (Group 2), using data from 1985 to 2019. It identifies heterogeneity in effects and dependencies between the groups. Employing Pedroni and Kao panel cointegration tests, a long-term equilibrium relationship among the variables is confirmed. The analysis, using panel ARDL and GMM methods, reveals distinct outcomes for each group. In Group 1, military spending and energy consumption significantly increase CO2 emissions, while industrialization and technological innovation reduce them. Conversely, in Group 2, technological innovation and energy consumption raise emissions, whereas military spending and industrialization decrease them. The findings suggest Group 1 should strategize military expenditure and energy consumption to cut emissions, whereas Group 2 should focus on eco-friendly technology and efficient energy use to achieve environmental sustainability.

Chronic pancreatitis (CP) is an irreversible and progressive inflammation of the pancreas that can involve both pancreatic parenchyma and pancreatic duct. CP results in morphological change in the gland in the form of fibrosis and calcification along with functional impairment in the form of exocrine and endocrine insufficiency. Studies on the natural history of CP reveal the irreversibility of the condition and the resultant plethora of complications of which pancreatic adenocarcinoma is the most dreaded one. (1,2) In Japanese population-based studies by Otsuki and Fuzino et al, CP was clearly shown to reduce lifespan among males and females by 10.5 years and 16 years, respectively. (3) Most of these patients had occult pancreatic malignancies which were diagnosed late and were detected to be the commonest cause of mortality among these patients with a standardized mortality rate of 7.33. (3) This dismal prognosis is superadded with significant morbidity due to pain and poor quality of life rendering a significant burden on health and health-related infrastructure. These factors have led researchers to conceptualize early CP which theoretically is a reversible stage in the disease spectrum characterized by ongoing pancreatic injury with the presence of clinical symptoms and absence of classical imaging features of CP. Subsequently, the disease is thought to go through a compensated stage, a transitional stage, and culminating into decompensated stage with florid evidence of functional impairment of the gland. (4) In this focused review, we will discuss the definition and concept of early CP, risk factors and natural history of the development of CP, and the role of various modalities of EUS in the timely diagnosis of early CP.

The operating theatre represents a key contributor to healthcare-derived emissions. Here, we outline the carbon footprint of a lumbar microdiscectomy at our regional unit in Greater Manchester, with the use of AI technology. In doing so, we aim to define the extent of the environmental impact and identify carbon hotspots for sustainable change. Our unit of analysis covered the start of the patient journey into hospital through to the final outpatient appointment. Publicly available and locally sourced data was used. An inventory analysis of two lumbar microdiscectomies was conducted. Each item was categorised reconciled against our AI-powered ‘CO2 analysis’ database. Kilograms of carbon dioxide equivalent (kg CO2e) was chosen as the primary measure of impact. An average lumbar microdiscectomy at our trust generates 477.73kg CO2e. The operation (173.89kg CO2e, 36.40%) and the inpatient stay (144.67kg CO2e, 30.28%) constituted the biggest contributors. Single-use intraoperative equipment contributed to over three-quarters of the total emissions from the operation. By defining the environmental burden of elective spinal surgery, we have identified carbon hotspots to target for sustainable change. Substituting polluting elements for carbon-friendly alternatives and challenging the single-use culture, modern healthcare systems can help pave the way to a ‘net zero’ healthcare system.

This paper presents a framework to recognize the affective state of children with Autism Spectrum Disorder (ASD) in an in-the-wild setting using Heart Rate (HR) information. Our algorithm classifies a child’s emotion into positive, negative, or neutral states by analyzing the heart rate signal. The HR signal is obtained from a smartwatch in real-time using our smartwatch application. The heart rate data is acquired when the child learns to code a robot while interacting with an avatar that assists the child in communications skills and programming the robot. In this paper, we also present a comparison of using HR data for the classification of emotions with classification based on features extracted from HR signals using Discrete Wavelet Transform (DWT). Our experimental results show that the proposed method produces a comparable performance with the state-of-the-art HR-based emotion recognition techniques, despite the fact that our experiments are performed in an uncontrolled setting as opposed to a lab environment. This work contributes to real-world affect analysis of children with ASD using HR information.

Consumption is thus fundamentally related to sustainably because every decision pertaining to what to buy, what quantity the buy, how many to consume, or how to dispose of things has a direct influence on the natural world and the generations to come, and the overall impact of every single the customer's purchase is disastrous. A framework-based systematic literature review (SLR) was conducted to better comprehend the body of research on digital innovation and sustainability driving consumer behavior. This was done in order to acquire a deeper understanding of the studies that have already been done in this area. to provide (i) a comprehensive review of the current research landscape and (ii) a rich roadmap for future research. This study evaluated the literature especially in terms of theory, context, traits, and methodology. A total of 107 research articles published between 2013 and 2022 were found using scientific methods in the Scopus database. The findings showed that most research appears to have employed qualitative methodologies and was grounded in the setting of China and Italy. This review could help scholars better grasp the relationship between digital innovation and sustainability, opening the door for additional study and advancement in the field. Additionally, by extending the literature study and emphasizing the elements that can improve digital innovation and sustainability, practitioners will be given a better overall understanding of how to approach the problem.

Mesothelioma of the peritoneum is the second most prevalent type. The peritoneum, the membrane lining the abdomen and abdominal organs, is affected in this type of cancer. A common risk factor is exposure to asbestos. There isn’t a cure, but surgery, chemotherapy, and palliative care can improve your prognosis and quality of life. Here we present a case of a 47-year-old female with peritoneal mesothelioma.

Salmonella typhimurium is the predominant serovar identified in cases of salmonellosis. It is recognised for adhering to various surfaces and creating biofilm, leading to several foodborne outbreaks and antibiotic resistance. Actinomycetes are thought to possess a wide array of antibacterial characteristics that can combat different diseases. Currently, it is unclear whether it has antibiofilm properties against S. typhimurium. This study aimed to assess the antibiofilm efficacy of actinomycetes extracts against S. typhimurium ATCC 14028 by the Crystal Violet assay. Four actinomycetes isolates, EAS5, EAS7, EAA141, and EAA11, were obtained from BRIS soil in Terengganu. The actinomycetes isolates were extracted using ethyl acetate (EA). S. typhimurium was exposed to extracts for 6, 12, and 18 hours. The results showed that all EA extracts effectively prevented the S. typhimurium biofilm at 12 and 18 hours. EAAA11 was the most effective against the 12-hour biofilm, whereas EAS5 was the most effective against the 18-hour biofilm among these extracts. In conclusion, actinomycetes isolated from the BRIS soil in Terengganu show potential for controlling Salmonella infection.

Diabetic striatopathy (DS) is characterized by a hyperglycaemic state associated with chorea/ballism, and/or striatal hyper density on computed tomography, or hyperintensity on T1-weighted magnetic resonance imaging. To date, there have been only a few case series reported in the literature on this topic. We present an acute case of DS which delineates the clinical presentation, imaging and instrumental examinations, typical radiological findings, and therapeutic approach of this condition. The purpose of this case report is to to remind clinicians to consider DS when poor-controlled diabetic patients present with symptoms such as altered sensorium, sudden-onset choreiform and ballistic movements.

The vehicular ad hoc network (VANET) when augmented with internet is called internet of vehicles (IoV). In the IoV, vehicles have on board units (OBUs), use communication technologies and customized software to communicate with infrastructure around them. The vehicles can have permanent connectivity and global network awareness based on cloud computing. IoV technologies are still being assessed to ensure that the network is protected from attacks, supports a dynamic vehicular mobility scenarios and meets the low latency communication requirements between the vehicles and the surrounding infrastructure. To meet these strict Quality of Service (QoS) demands, Unmanned Aerial Vehicles (UAVs) play a vital role in IoV ecosystems. An UAV can serve as a mobile roadside unit (mRSU) to transmit data between vehicles, stationery RSUs and other UAVs. The UAVs have better line of sight (LOS) connections which result in better channel states and lower path loss than fixed RSUs. Although the inclusion of UAVs in vehicular networks has improved the system performance by providing better resource management and routing solutions, the traditional optimization techniques with their limitations are often not applicable. Therefore, in recent years, research community is integrating Artificial Intelligence (AI) and Machine Learning (ML) into UAV based IoV ecosystem to better manage resource allocation, routing and mobility management issues to optimize the overall network performance. In this survey paper we review the existing research done in AI/ML based UAV-IoV networks and communications with focus on resource management and routing from year 2019 to 2023. We have studied different AI techniques, their training attributes and architectures in various research works. The limitations of AI-based approaches in terms of required computational resources, availability of real world data and AI models’ complexity for the UAV-IoV environment are also discussed. Finally, the future directions for UAV-IoV research opportunities that can leverage the full potential of AI are presented.

In this part of the series of two papers, we extend the theorems discussed in part I for infinite series. We then use these theorems to develop distinct novel results involving the Hurwitz zeta function, Riemann zeta function, Polylogarithm and Fibonacci numbers. In continuation, we obtain some zeros of the newly developed zeta functions and explain their behaviour using plots in complex plane. Furthermore, we provide particular cases for the theorems and corollaries which show that our results generalise the currently available functions and series such as the Riemann zeta function and the geometric series. Finally, we provide four miscellaneous examples to showcase the vast scope of the developed theorems.

The Qiushuwan Cu-Mo deposit, located in the East Qinling molybdenum belt, which is a major mining site recognized for its enormous reserves of medium-sized molybdenum. In order to enhance our comprehension and ascertain supplementary mineral resources, it is critical to conduct an in-depth investigation of both the deep and peripheral regions. The primary goal of this study is to investigate the Qiushuwan Copper Molybdenum Mine, which is located in Zhenping County, Henan Province. The spread spectrum-induced polarization (SSIP) method is utilized as a means of conducting mining exploratory analysis. Significant findings have been obtained through the collection of SSIP data, geological analysis, and electrical parameter study of rock and ore samples along profile-80. By conducting a meticulous examination of the SSIP data at suitable frequencies, two prominent conductive ore bodies, specifically C2 and C4, have been successfully discovered. C2 exhibits a correlation with granite porphyry and molybdenum veins, while C4 is linked to a skarn deposit that contains a concentration of copper ore. The spatial differences in conductivity within the research area have been precisely characterized using resistivity models obtained from the SSIP data. The precision and dependability of our conclusions have been confirmed through the integration of borehole data and the matching of geological sections with inversion models. The recovered core samples show a diverse range of minerals, containing both valuable ores and minerals that have undergone alteration. Pyrite constantly appears with molybdenite in the majority of samples. The aforementioned results provide a strong foundation for future exploration initiatives and sustainable resource exploitation, enabling informed decision-making in the effective use and administration of natural resources. This study adds to the existing body of knowledge on the Qiushuwan Cu-Mo deposit and improves exploration methods in the region by utilizing the SSIP approach. The findings are a useful asset for geologists, mining experts, and stakeholders, offering essential knowledge for future exploration and sustainable utilization of resources.

We study the validity of quantum Fisher information (QFI) as a faithful quantum coherence and correlation quantier by drawing a comparison with subsystem's coherence measure, rst-order coherence (FOC) and the entanglement measure, Negativity to study the behavior of thermal quantum coherence and correlations in two qubit Heisenberg XXX model, placed in independently controllable magnetic eld by systematically varying the coupling parameter, magnetic eld and bath temperature for ferromagnetic and antiferromagnetic case. After carefully observing the prole of quantum coherence and correlation measures, we propose an inequality relations which shows that there may exist a quantitative relationship between QFI, Negativity and FOC in which, the equality exists at zero temperature. We identify QFI to be a more useful coherence quantier, as it quanties coherence of individual subsystems and correlations among the subsystems. On the other hand, FOC identies coherence present in the individual subsystems only. A reciprocal relationship between Negativity and FOC is also observed in dierent cases. We also observe the existence of entanglement in ferromagnetic case, in contrast to simple Heisenberg XXX model in uniform magnetic eld. We show that in the ferromagnetic case, a very small inhomogeneity in magnetic eld is capable of producing large values of thermal entanglement. This shows that the behavior of entanglement in the ferromagnetic Heisenberg system is highly unstable against inhomogeneity of magnetic elds, which is inevitably present in any solid state realization of qubits.

Background: Caregivers of asthmatic children have poor knowledge of proper asthma man-agement practices in Nigeria. The objective of this study was to examine the knowledge, attitudes, and practice behaviors of caregivers in the management of asthma in children under age 5 in Oyo State, Nigeria, using the Health Belief Model. Methods: While a mixed method was used in the original research, this brief describes the quantitative method used in this study to evaluate caregiver’s asthma management practices A 55-item questionnaire investigating childhood asthma knowledge, attitude, and practice was administered during child welfare clinic visits to 118 caregivers. To gain insights into caregivers’ beliefs about asthma management practice behavior, focus group discussions were conducted among two groups of 10 caregivers. Data were analyzed using the IBM SPSS Version 25.0. Statistical significance was set at p < 0.05 and 95% CI. Result: More than 70% of caregivers knew that asthma is associated with airway inflammation and about 90% knew that Flu infections triggered asthma attacks in their children. Overall, 70% of caregivers from the focus group discussions found preventive measures including avoidance of common triggers like dust and smoke, wearing warm clothes in cold weather, environmental sanitation, regular visits to the clinic, and medication adherence helpful. Similarly, caregivers reported the use of quick-to-relieve OTC drugs rather than seeking medical attention. Caregivers with higher income (OR = 3.0; 95% CI = 1.558-5.778; P = 0.001) were 3.0 times more likely to practice proper asthma behavior than those with a lesser income. Conclusion: Despite having moderate knowledge of asthma, caregivers of asthmatic children had wrong perceptions and inadequate knowledge about preventive and treatment options. An optimal public health approach is needed to identify and target underserved communities that suffer poorer asthma outcomes and improve caregivers’ knowledge and skills in asthma management practices. The need to pay more attention to the proper management of childhood asthma among caregivers in underserved populations cannot be overemphasized.

The present study investigates the decision-making process of investors on the Pakistan Stock Exchange with regard to portfolio construction, explicitly focusing on the incorporation of ESG concerns. The present study employed SmartPLS and structural equation modeling (SEM) to quantitatively assess data received from a sample of 393 out of 400 respondents. Based on the available data, investors participating in the Pakistan Stock Exchange are notably impacted by ESG aspects. The findings of this study hold significance for emerging economy firms, regulators, and investors, both in terms of theoretical and practical ramifications. The study's findings demonstrate a clear indication of investors' significant emphasis on ESG matters. Furthermore, it provides valuable insights for stakeholders who are involved in the ever-evolving realm of sustainable finance within developing countries

Widespread poverty is the most serious threat and social problem that Bangladesh faces. Regional vulnerability to climate change threatens to escalate the magnitude of this poverty. It is essential that projections of poverty be made while bearing in mind the effects of climate change. The main purpose of this paper is to investigate the agrarian sub-national regional analysis of climate change vulnerability in Bangladesh under various climate change scenarios and its potential impact on poverty. This study is relevant to socio-economic research on climate change vulnerability and agriculture risk management and has the potential to contribute new insights to the complex interactions in household income and climate change risks to agricultural communities in Bangladesh and South Asia. The current study uses analysis of variance, cluster analysis, decomposition of variance and log-normal distribution to estimate the parameters of income variability that ascertain vulnerability levels and help us to understand the poverty levels that climate change could potentially incur. It is found that the income share in income sources revealed that income category shares across the various regions of Bangladesh are far from uniform. The variance decomposition of income showed that agricultural income in Mymensingh and Rangpur is the main cause of income difference. Moreover, large variance of agricultural income in the regions is induced by gross income from rice production. Additionally, constant reduction of rice yield due to climate change in Bangladesh is not such a severe problem for farmers, however, the extreme events like flood, flash flood, drought, sea level rise, and greenhouse gas emission based on RCPs could increase the poverty rates in Mymensingh, Rajshahi, Barisal, and Khulna regions that would be highly affected by unexpected yield loss due to extreme climatic events. Therefore, research and development of adaptation measures to climate change for regions where farmers are largely dependent on agricultural income is important.

BackgroundHeart failure is a life-threatening disease affecting millions worldwide. Tolvaptan is the first FDA-approved orally active nonpeptide vasopressin 2 receptor antagonist to be used in hypervolemic hyponatremia, heart failure, cirrhosis, etc. In clinical trials, tolvaptan impacts short-term in increasing water excretion, and restoring Na+ and dyspnoea. Aims & ObjectivesThe objective is to analyze the outcomes of tolvaptan in existing cases of heart failure. MethodologyWe conducted a database search of the MEDLINE, Embase, and Cochrane Central Register of Controlled Trials and RCTs till 1st September 2019 were included following PRISMA guidelines after being matched with inclusion and exclusion criteria. 21 RCTs were included with 7,357 patients receiving tolvaptan and 7,273 patients being the control group. We used the MESH strings such as 'tolvaptan', 'vasopressin V2 receptor blocker', 'acute heart failure', and 'acute decompensated heart failure'. ResultsMeta-analysis showed that Tolvaptan was associated with a significant reduction in edema (RR = 1.05, 95% CI = 1.019-1.081, p=0.001) and significant body weight reduction (Control-SMD = -0.489, 95% CI =-0.637 to -0.342, p<0.001)&(Placebo-SMD = -0.425, 95% CI = -0.425 to -0.382, p<0.001) It shows significant decrease in serum sodium levels (SMD = 0.678, 95% CI = 0.609 to 0.748, p<0.001). There was no significant decrease in all-cause mortality (Control-RR = 0.855, 95% CI 0.470 to 1.555, p=0.607)(Placebo-RR= 0.972, 95% CI = 0.879-1.074, p=0.575). Results for Worsening renal function in heart failure (Placebo-RR = 0.798 95% CI 0.619 to 1.028, p=0.081)(Control-RR = 1.349, 95% CI=0.927-1.964, p=0.118). ConclusionAlthough tolvaptan may significantly reduce edema, congestive symptoms and decreased body weight, it has no impact on all-cause mortality and worsening renal function in heart failure.

Rhombencephalosynapsis (RES) is a rare, congenital developmental disorder of the central nervous system. Even after many years of its identification, the etiology and pathogenesis of RES remain unclear. It occurs in combination with many syndromes and thus has overlapping symptoms. The clinical presentation of this disorder varies depending on the severity of the maldevelopment of vermis. Here, we present a case of a 60-year-old Indian female diagnosed with Rhombencephalosynapsis. Clinical and MRI characteristics of RES along with treatment options have been discussed.

Presenting a case report about a 14-year-old female patient presenting with a history of weakness in all four limbs since the age of 5. The patient has a history of difficulty in walking, wearing footwear, climbing stairs, and performing fine motor tasks. During the neurological examination showed mild spasticity, muscle weakness, areflexia, ill-sustained clonus, and sensory deficits. Radiological examination, including a contrast-enhanced MRI of the brain was done which showed findings that are consistent with Megalencephalic leukoencephalopathy with subcortical cysts, also known as Van der Knaap disease.

CLIPPERS which stand for Chronic lymphocytic inflammation with pontine perivascular enhancement responsive to steroids, is a chronic inflammatory disorder of the central nervous system. The aetiology of CLIPPERS remains unclear, although its pathogenesis shows immune-mediated processes. The diagnosis of CLIPPERS is challenging without a specific biomarker hence, it is important to consider if both the clinical and radiological features are consistent with the diagnosis, or rather any other disease that mimics CLIPPERS. The Authors present a case of a 40-year-old Female patient diagnosed with CLIPPERS syndrome in India. Differential diagnosis, clinical and MRI characteristics of CLIPPERS syndrome, and treatment approaches are discussed.

Presenting a case report about an occurrence of duodeno-duodenal intussusception in a 17-year-old female patient. Intussusception is typically observed in children. The patient has a history of recurrent pain and vomiting for four days. During the examination tenderness in the epigastric area worsened when the legs were elevated. An initial X-ray of the abdomen was done and the findings were normal. Subsequent ultrasound and abdominal CECT scans of the abdomen revealed intussusception involving the 2^nd, 3^rd, and 4^th part of the duodenum ampulla of Vater and pancreas without any identifiable cause for this condition. There was no abnormal thickening of the wall. This case shows how using radiological imaging and surgical management helps to prevent severe complications in cases like duodeno-duodenal intussusception in adults.

Traditional marketing tactics have been significantly challenged by marketers, especially in the food sector. Companies have been engaging in covert and overt advertisements as an emerging marketing communication strategy to circumvent customer skepticism, build a good image, and create value for the brand. But there is a lack of literature regarding integrating traditional and new marketing tactics in building intention and ecologically conscious consumer behavior. Therefore, the purpose of the present study is to provide empirical evidence concerning the integration of different marketing tactics, i.e., Green Product Features, Green Pricing, Covert Advertisement, Overt Advertisement and Guerrilla Marketing, and their effects on Purchase Intention and Ecologically Conscious Consumer Behavior. The study also employs moderation of Brand Evangelism, Environmental Knowledge and Habitat Attitude between intention and behavior building. A visual appraisal technique was used by showing a video or picture as a sample of covert or overt marketing tactics before filling out a close-ended questionnaire to get accurate responses. The data from 568 customers of the frozen food industry were analyzed using the co-variance-based structure equation modeling technique with the help of AMOS. The findings of the study elaborate that parallel to the significant impact of conventional marketing mix tactics, covert, overt and guerrilla marketing are strong antecedents for intention building, which eventually develops Ecologically Conscious Consumer Behavior (ECCB). The results also affirm that intention can lead to ECCB significantly through brand evangelism and environmental knowledge. These findings reflect the importance of shifting marketers from conventional marketing tactics to novel hidden marketing techniques.

Bone fractures are very common in the geriatric population and poses a great economic burden worldwide. While traditional methods for repairing bone defects have primarily been autografts, there are several drawbacks limiting its use. Bone graft substitutes have been used as alternative strategies to improve bone healing. However, there remains several impediments to achieving the desired healing outcomes. Injectable hydrogels have become attractive scaffold materials for bone regeneration given their high performance in filling irregularly sized bone defects, ability to encapsulate cells and bioactive molecules, and mimic the native ECM of bone. We investigated the use of an injectable chitosan-based hydrogel scaffold to promote differentiation of preosteoblasts in vitro. The hydrogels were characterized by evaluating cell homogeneity, cell viability, rheological and mechanical properties, and differentiation ability of preosteoblasts in hydrogel scaffolds. Cell-laden hydrogel scaffolds exhibited shear thinning behavior and the ability to maintain shape fidelity after injection. The CNC-CS hydrogels exhibited higher mechanical strength and significantly upregulated the osteogenic activity and differentiation of preosteoblasts as shown by ALP activity assays and histological analysis of hydrogel scaffolds. These results suggest that this injectable hydrogel is suitable for cell survival, can promote osteogenic differentiation of preosteoblasts, and structurally support new bone growth.

Introduction Menstrual hygiene is a critical issue encountered by women and girls of the reproductive age, which negatively affects their health and empowerment. It is still deemed a taboo in several parts of the world and girls hesitate to discuss menstruation with their family members, friends, or schoolteachers, which creates hurdles when they attain their menarche. Girls residing in rural areas encounter more problems, since they lack proper resources, and knowledge to manage their menstruation in school as well as at home. Methods The descriptive cross-sectional design was used to assess the study questions. The consecutive sampling techniques was applied to recruit 300 female participants from remote area of Gilgit, Pakistan, who were 13- to 22-year-old. A pre-tested questionnaire was utilized to collect the data, and to analyze the data the SPSS version 21.0 was used. Results The study found that more than half of the participants had poor level of knowledge, practices, and negative attitude towards menstrual hygiene. This could be because of many cultural and social taboos attached to menstrual hygiene. Conclusions The study concluded that the study participants were not knowledgeable about menstrual hygiene. They had poor practices and attitude regarding menstrual hygiene. Hence, it is recommended that frequent sessions should be conducted by health care workers to enhance the knowledge of parents, teachers, and young girls, to increase the positive attitude and practices regarding menstrual hygiene. Keywords menstruation, knowledge, attitude, practices, Adolescents

We studied the influence of lava meal, zeolite and top layer of sandy soil as bedding additives on gaseous C and N losses from a sloping-floor barn of naturally ventilated animal housing. We selected four barn units where eight young bulls’ group was reared in each barn. Chopped straw of wheat and barley applied daily at the rate of 5 kg per livestock unit (LU) in bedding areas where one LU consisted of 500 kg body mass of live bulls. Zeolite, lava meal and sandy soil (18% clay + silt) applied in barn at the rate of 10, 20 and 30% of straw dose, respectively. Static flux chamber was used to measure gases emissions from the barn unit and mass balance calculation was used to calculate straw manure total N (TN) losses during housing phase. On an average, all bedding additives decreased 85% of the NH₃ emission compared to control; however, they did not influence CH₄ emission. Zeolite decreased CO₂ (35%) and N₂O (37%) emission rates. Subsequently, lava meal, sandy soil and zeolite decreased 23, 37, and 50% of TN losses from barn manure, respectively. Overall, measured N emissions through NH₃-N and N₂O-N from the barns was 11% of calculated TN losses while remainder 89% was most probably attributed to di-nitrogen (N₂), a harmless gas. Hence, in straw-based cattle housings, zeolite could be a promising additive for reduction of CO₂, N₂O and NH₃ emissions and sandy soil can be considered as cheap and readily available resource for reducing NH₃ emission.

Use of rhizosphere microorganisms provides an alternative or supplement to conventional plant breeding to improve water deficit tolerance of tomato plants. Experiment was carried out to explore the effect of two microbial species, AMF (Rhizophagus irregularis) and Bacillus subtilis, in single and co-application, on growth, colonization, and molecular aspects of tomato plants under drought stress. Co-inoculated plants showed less reduction in growth traits, photosynthetic pigments, colonization rate, and increased compatible solutes like proline which help in sustaining relative water content than non-inoculated plants. Inoculation considerably enhanced proline dehydrogenase activity, and significantly reduced both Δ1-pyrroline-5-carboxylate reductase Δ1-pyrroline-5-carboxylate synthetase activity causing lower proline accumulation in inoculated plants under drought stress. Co-inoculated plants showed obvious upregulation of antioxidant system, thus facilitating amelioration of oxidative stress through exclusion of reactive oxygen species. No inoculation under drought stress upregulated abscisic acid related genes expression but have no effect in plants inoculated either sole or mixed inoculation. Expression of aquaporin genes was upregulated in plants co-inoculated and with AMF alone under normal condition. However the expression of aquaporin genes were decreased or unaffected in plants inoculated with Bacillus subtilis but increased in non-inoculated plants. Co-applied AMF and bacillus subtilis substantially increase drought tolerance by upregulating proline metabolism, antioxidant enzymes and aquaporin genes. Therefore our results suggest that co-inoculation mediated drought tolerance is linked with increased proline accumulation, enhanced antioxidant enzyme activities and differential regulation of ABA biosynthetic and aquaporin genes, which is vital for osmotic adjustment of host plant.

Pyrocumulonimbus (pyroCb) thunderclouds, produced from extreme bushfires, can initiate frequent cloud-to-ground (CG) lightning strikes containing extended continuing currents. This, in turn, can ignite new spotfires and inflict massive harm on the environment and infrastructures. This study presents a 3D numerical thundercloud model for estimating the lightning of different types and its striking zone for the conceptual tripole thundercloud structure which is theorized to elucidate the lightning phenomenon in pyroCb storms. More emphasis is given to the lower positive charge structure thundercloud to thoroughly examine various electrical parameters including the longitudinal electric field, electric potential, and surface charge density. The simulation outcomes on pyroCb thunderclouds with a tripole structure confirm the presence of negative longitudinal electric field initiation at the cloud’s lower region. This initiation is accompanied by enhancing the lower positive charge region, resulting in an overall positive electric potential increase. Consequently, negative surface charge density appears underneath the pyroCb thundercloud which has the potential to induce positive cloud-to-ground (+CG) lightning flashes. The suggested model would establish the basis for identifying the potential area impacted by lightning and could also be expanded to analyze the dangerous conditions that may arise in wind energy farms or power substations in times of severe pyroCb events.

This paper reports modelling outcomes for improvements to building energy performance in Indonesia. Long-term climate effects due to building energy demands including carbon emissions are also considered. The global change assessment model (GCAM) was used to generate the related end-user building energy data, including socioeconomics for urban areas of Indonesia. As a comprehensive study, the total life cycle of carbon in the building sector and the concept of zero-carbon buildings, including energy efficiency, zero-emissions electricity and fuel switching options were considered. Building shell conductance (u-value) of building envelope, floor area ratio (FAR), air conditioner (AC) efficiency, electrical appliances (APLs) efficiency, rooftop photovoltaic (PV) performance and ground source heat pump (GSHP) systems were considered as parameters to mitigate carbon emissions under the operational energy category in GCAM. Carbon mitigation associated with the cement production process was considered in the raw material category. Urban population and labour productivity in Indonesia were used as base inputs with projected growth rates to 2050 determined from available literature. Low growth rate ‘LowRate’ and high growth rate ‘HighRate’ were considered as variable inputs for u-value, FAR, AC efficiency, APLs efficiency, and PV capacity factor to model emissions mitigation. The energy consumption of the GSHP was compared to the conventional reverse cycle ACs to identify the potential of the GSHP as a fuel-switching option. Only base input data were used for cement production process parameters without applying any variable inputs. GCAM base scenarios based on input data only (without modifying variable data) for the residential building sector in Indonesia were considered the benchmark for this study. Total potential carbon emissions mitigation was found to be 432 Mt CO2-e for the residential building sector in Indonesia over 2020-2050. It was found that an average of 24% carbon emissions mitigation could be achieved by 2020-30 and 76% in 2031-2050.

Hyper spectral imaging (HSI) is a technique that is used to obtain the spectrum for each pixel in the image. It helps in finding objects and identifying materials etc. Such an identification is very difficult using other imaging techniques. It allows the researchers to investigate the documents without any physical contact. Nowadays detection of unequal Ink mismatch based on HSI has shown vast improvement in distinguishing the inks. Detection of unequal Ink mismatch is an unbalanced clustering problem. This paper used K-means Clustering for ink mismatch detection. K-means Clustering find same subgroups in the data based on Euclidean distance. This paper demonstrates performance in unequal Ink mismatch based on HSI.

Abiotic stresses greatly influenced wheat productivity executed by environmental factors such as drought, salt, water submergence, and heavy metals. The effective management at molecular level is mandatory for thorough understanding of plant response to abiotic stress. The molecular mechanism of stress tolerance is complex and requires information at the omic level to understand it effectively. In this regard, enormous progress has been made in the omics field in the areas of genomics, transcriptomics, and proteomics. The emerging field of ionomics is also being employed for investigating abiotic stress tolerance in wheat. Omic approaches generate a huge amount of data, and adequate advancements in computational tools have been achieved for effective analysis. However, the integration of omic-scale information to address complex genetics and physiological questions is still a challenge. In this review, we have described advances in omic tools in the view of conventional and modern approaches being used to dissect abiotic stress tolerance in wheat. Emphasis was given to approaches such as quantitative trait loci (QTL) mapping, genome-wide association studies (GWAS), and genomic selection (GS). Comparative genomics and candidate gene approaches are also discussed considering identification of potential genomic loci, genes, and biochemical pathways involved in stress tolerance mechanism in wheat. This review also provides a comprehensive catalog of available online omic resources for wheat and its effective utilization. We have also addressed the significance of phenomics in the integrated approaches and recognized high-throughput multi-dimensional phenotyping as a major limiting factor for the improvement of abiotic stress tolerance in wheat.

This study assesses the pursued impacts of Tulsi value chain development intervention on the livelihoods of rural poor in Uttarakhand state of India. Tulsi as an alternative livelihood, particularly for the rural poor, is less explored. With increased crop depredation of major cereal crops grown in the district by wild animals and pests, and decreasing availability of water agriculture, attempts were made to improve earnings from Tulsi as an alternative livelihood. Findings suggest that the average households’ gross profit from Tulsi farming increases by more than double within a span of two years. Total crop income of beneficiary farmers’ increases by 0.8 percent for every 1 percent increase in Tulsi income. Intervention helped enhance productivity of Tulsi, thereby enhancing earnings from Tulsi farming. Most importantly, intervention has shown a tremendous adoption rate. Towards the end of the intervention, the value chain work was out-scaled to another 19 villages in Chamoli district, thereby reaching out to more than 400 households.