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Abstract While majority of the current treatment approaches for cancer remain expensive and are associated with several side effects, development of new treatment modalities takes a significant period of research, time, and expenditure. An alternative novel approach is drug repurposing that focuses on finding new applications for the previously clinically approved drugs. The process of drug repurposing has also been facilitated by current advances in the field of proteomics, genomics, and information computational biology. This approach not only provides cheaper, effective, and potentially safer drugs with less side effects but also increases the processing pace of drug development. In this review, we wish to highlight some recent developments in the area of drug repurposing in cancer with a specific focus on the repurposing potential of anti-psychotic, anti-inflammatory and anti-viral drugs, anti-diabetic, antibacterial, and anti-fungal drugs.

Objective Methods Results Interpretation Patient‐reported outcome measures (PROMs), which capture patients' perspectives on the consequences of health and disease, are widely used in neurological care and research. However, it is unclear how PROMs relate to performance‐rated impairments. Sociodemographic factors are known to affect PROMs. Direct damage to brain regions critical for self‐awareness (i.e., parietal regions and the salience/ventral‐attention network) may also impair self‐report outcomes. This study examined the relationship between PROMs and performance‐based measures in stroke survivors with arm motor impairments. We hypothesized that PROMs would be distinct from performance‐based outcomes, influenced by sociodemographic factors, and linked to damage in brain circuits involved in self‐perception.We longitudinally assessed 54 stroke survivors using patient‐reported and performance‐rated measures at 4 timepoints. We used factor analysis to reveal the outcome battery's factorial structure. Linear regression examined the association between classes of measures and sociodemographics. Voxel‐lesion‐symptom‐mapping, region‐of‐interest‐based analysis, and voxel‐lesion‐network‐mapping investigated the relationship between classes of outcomes and stroke‐related injury.Performance‐based and patient‐reported measures formed distinct factors, consistent across recovery phases. Higher education (β1 = 0.36, p = 0.02) and income adequacy (β2 = 0.48, p = 0.05) were associated with patient‐reported, but not performance‐rated outcomes. Greater parietal lobe injury, irrespective of hemisphere, was associated with worse patient‐reported outcomes; greater corticospinal tract injury related to worse performance‐rated outcomes. Lesions with greater functional connectivity to the salience/ventral‐attention network were associated with worse patient‐reported outcomes (r = −0.35, p = 0.009).Our findings reveal important differences between performance‐rated and patient‐reported outcomes, each with specific associated factors and anatomy post‐stroke. Incorporating sociodemographic and neuroanatomic characteristics into neurorehabilitation strategies may inform and optimize patient outcomes. ANN NEUROL 2024 [ABSTRACT FROM AUTHOR]

The article from the Journal of Strategic Marketing explores the future of marketing and communications in the digital era, focusing on data analytics, digital narratives, and consumer engagement. It highlights the importance of personalized marketing, ethical considerations, and the role of narratives in engaging consumers. The research delves into influencer marketing, search engine marketing, customer journey analysis, B2B loyalty, and digital leadership, offering insights for marketers to navigate the complexities of the digital landscape effectively. The study emphasizes the need for agile, data-savvy, and narrative-focused strategies to succeed in the evolving digital marketing environment. [Extracted from the article]

Objective: The main objective of this study is to investigate the effectiveness of the stress management intervention package in improving stress-related burnout. Materials and Methods: An experimental study was done on 300 nurses selected by a nonprobability convenience sampling technique and a quasi-experimental one-group pre- and posttest research design was utilized. Modified expanded nurses stress scale and self-structured three-point Likert scale on the challenges that nurses may face following stressful life events utilized to collect information. The nurses signed up for six interactive sessions on various stress-coping methods by utilizing a variety of teaching strategies such as lecture cum discussion, video slides, group work, and direct interaction with the experts to explore stress-related issues. Results: Continuous stress affects both the body and the mind, causing psychosomatic symptoms. Data found that 2% to 10% of nurses frequently suffered with physical symptoms such as exhaustion, backache, acidity, headache, shoulder stiffness, and insomnia. Following the intervention, the number of nurses who had these symptoms frequently and sometimes decreased. Previously, 10% of nurses experienced emotional symptoms frequently; however, after intervention, this figure was reduced to < 2%. The greatest proportion of nurses (18%) reported frequently worrying, while 1.3% expressed frequent worrying after intervention. Maximum (5%) of nurses had a tendency to eat too little or too much; this has been reduced to 0.3% after the intervention. The intervention package on stress management significantly improved nurses' comprehensive well-being (P < 0.0001). Conclusion: An intervention package for stress management was helpful in lowering physical, emotional, psychological, and behavioral stress-related symptoms among nurses. [ABSTRACT FROM AUTHOR]

Abstract Quantitative susceptibility mapping (QSM), an imaging technique sensitive to brain iron, has been used to detect paramagnetic rims of iron-laden active microglia and macrophages in a subset of multiple sclerosis (MS) lesions, known as rim+ lesions, that are consistent with chronic active lesions. Because of the potential impact of rim+ lesions on disease progression and tissue damage, investigating their influence on disability and neurodegeneration is critical to establish the impact of these lesions on the disease course. This study aimed to explore the relationship between chronic active rim+ lesions, identified as having a hyperintense rim on QSM, and both clinical disability and imaging measures of neurodegeneration in patients with MS. The patient cohort was composed of 159 relapsing–remitting multiple sclerosis patients. The Expanded Disability Status Scale (EDSS) and Brief International Cognitive Assessment for Multiple Sclerosis, which includes both the Symbol Digit Modalities Test and California Verbal Learning Test-II, were used to assess clinical disability. Cortical thickness and thalamic volume were evaluated as imaging measures of neurodegeneration. A total of 4469 MS lesions were identified, of which 171 QSM rim+ (3.8%) lesions were identified among 57 patients (35.8%). In a multivariate regression model, as the overall total lesion burden increased, patients with at least one rim+ lesion on QSM performed worse on both physical disability and cognitive assessments, specifically the Symbol Digit Modalities Test (p = 0.010), California Verbal Learning Test-II (p = 0.030), and EDSS (p = 0.001). In a separate univariate regression model, controlling for age (p

Lignin, the most abundant biopolymer on earth, has been explored as an electroactive material in battery applications. One essential feature for such lignin‐based batteries to reach successful usage and implementation, e.g., large‐scale stationary grid applications, is to have slow self‐discharge characteristics on top of the essential safety and life‐cycle properties. Water‐in‐polymer salt electrolytes (WIPSEs) have been demonstrated as an attractive route to solve this issue; however, little has been done to understand the fundamentals of actual self‐discharge mechanisms. Herein, the impact of some critical chemical and physical parameters (pH, dissolved oxygen, viscosity, and cutoff potential) on self‐discharge of batteries based on WIPSE and lignin has been investigated. The pH range is crucial as there is an interplay between long‐term stability and high energy density. Indeed, lignin derivatives typically store relatively more charge in acidic media but later promote corrosion affecting device stability. A robust and high‐performing organic battery, incorporating potassium polyacrylate as WIPSE, is demonstrated, which expresses good self‐discharge behavior for a broad range of pH and with little impact on the atmosphere used for manufacturing. It is believed that the investigation will provide critical insights to the research community to promote the advancement of printed large‐scale energy storage devices.

The health and integrity of our water sources are vital for the existence of all forms of life. However, with the growth in population and anthropogenic activities, the quality of water is being impacted globally, particularly due to a widespread problem of nitrate contamination that poses numerous health risks. To address this issue, investigations into various detection methods for the development of in situ real-time monitoring devices have attracted the attention of many researchers. Among the most prominent detection methods are chromatography, colorimetry, electrochemistry, and spectroscopy. While all these methods have their pros and cons, electrochemical and optical methods have emerged as robust and efficient techniques that offer cost-effective, accurate, sensitive, and reliable measurements. This review provides an overview of techniques that are ideal for field-deployable nitrate sensing applications, with an emphasis on electrochemical and optical detection methods. It discusses the underlying principles, recent advances, and various measurement techniques. Additionally, the review explores the current developments in real-time nitrate sensors and discusses the challenges of real-time implementation.

Breakdowns and unplanned shutdowns in industrial processes and equipment can lead to significant loss of availability and revenue. It is imperative to perform optimal maintenance of such systems when signs of abnormal behavior are detected and before they propagate and lead to catastrophic failure. This is particularly challenging in systems with interconnected multiple components as it is difficult to isolate the effect of one component on the operation of other components in the system. In this work, an ensemble approach based on Cascaded Convolutional neural network and Long Short-term Memory (CC-LSTM) network models is proposed for detecting and predicting the time of onset of faults in interconnected multicomponent systems. The performance of the ensemble CC-LSTM model was demonstrated on an industrial 4-component system and was found to improve the accuracy of onset time predictions by ~15% compared to individual CC-LSTM models and ~25-40% compared to commonly used deep learning techniques such as dense neural networks, convolutional neural networks and LSTMs. The CC-LSTM and the ensemble models also had the lowest missed detection rates and zero false positive rates making them ideal for real-time monitoring and fault detection in multicomponent systems.

Particle packing technology is used to reduce the amount of cement in concrete by optimizing the concrete mix, resulting in more sustainable concrete. In this study, four different methods were used to determine the distribution of the mixture presented; packing density method, packing density method, IS code method, and packing density method. In the packing density method, the paste content that exceeds the voids will increase along with the increase in the quality of the concrete. In cases of packing density, the cement-water ratio decreases with the quality of the concrete. In the packing of too many trials, trials and tribulations should be carried out to achieve the ratio of water-cement and paste content for a certain grade of concrete. This correlation curve helps reduce the experiments involved in determining the ratio of semen and paste content for a given concrete quality. The water and cement contents for the packing density and the IS code method are almost the same for each particular concrete class. The workability of concrete achieved was more in the packing density method than the IS code method for the same concrete quality, because the water-cement ratio was slightly higher in the packing density method than the IS code method. The required fine aggregate particles are more in terms of packing density method compared to the IS code method. Therefore, more water and cement are required in terms of packing density. The correlation curve can be used to determine the ratio of water-cement and paste the content that exceeds the voids for a certain concrete quality

MXenes, with a particular emphasis on Ti3C2 (M3X2) have been extensively studied and established as the foundational material for 2D MXenes. However, the exploration of other transitional metals as 2D MXenes holds great promise, offering applications beyond the existing knowledge. Non‐Ti (M2X and M3X2) MXenes have garnered attention due to their distinctive properties. This review article focuses on explaining the potential and challenges of non‐Ti (M2X and M3X2) MXenes in energy storage and conversion systems, specifically in the domains of supercapacitors, batteries (Li‐ion and Li‐S), oxygen evolution reaction (OER), hydrogen evolution reaction (HER), and oxygen reduction reaction (ORR). By providing a comprehensive overview of the current progress and addressing the associated challenges, this review offers valuable insights into the future prospects of not only non‐Ti (M2X and M3X2) MXenes but also other MXenes for energy storage and conversion. The findings presented herein pave the way for further research and multifaceted applications of these MXenes across various fields. [ABSTRACT FROM AUTHOR]

MXenes, a two‐dimensional (2D) material, exhibit excellent optical, electrical, chemical, mechanical, and electrochemical properties. Titanium‐based MXene (Ti‐MXene) has been extensively studied and serves as the foundation for 2D MXenes. However, other transition metals possess the potential to offer excellent properties in various applications. This comprehensive review aims to provide an overview of the properties, challenges, key findings, and applications of less‐explored vanadium‐based MXenes (V‐MXenes) and their composites. The current trends in V‐MXene and their composites for energy storage and conversion applications have been thoroughly summarized. Overall, this review offers valuable insights, identifies potential opportunities, and provides key suggestions for future advancements in the MXenes and energy storage/conversion applications. [ABSTRACT FROM AUTHOR]

Heat transfer in flows created by buoyancy, or natural convection, is a widely studied topic across various disciplines spanning natural flows as well as those with engineering applications. The convective heat transfer rate on a surface is commonly represented by the Nusselt number (Nu), a ratio of convective to diffusive transport, expressed often as R a n P r m , where R a is the Rayleigh number, the buoyancy forcing parameter, and P r the Prandtl number. Motivated by the observation that n ∼ 1 / 3 for turbulent convection, which implies the heat flux is independent of the length scale (L , characteristic length related to the geometry), we propose an alternate and physically more meaningful non-dimensional heat transfer parameter, denoted by C q . C q is derived using only the near wall variables and does not contain L. For n = 1 / 3 , C q is constant. Even for laminar convection, where n ∼ 1 / 4 , C q ∼ R a − 1 / 12 , a weak function of R a. We show that for natural convection over several geometries and a wide range of Ra, the C q values within a narrow range while the corresponding Nu values span several orders of magnitude. We also show that C q is akin to the non-dimensional representation of wall shear stress, skin friction coefficient C f . We believe that just like C f , C q will be an equally useful non-dimensional measure of heat transfer in natural convection flows. [ABSTRACT FROM AUTHOR]

To understand the locomotory mechanisms of flying and swimming animals, it is often necessary to develop assays that enable us to measure their responses to external gust perturbations. Typically, such measurements have been carried out using a variety of gusts which are difficult to control or characterize owing to their inherently turbulent nature. Here, we present a method of generating discrete gusts under controlled laboratory conditions in the form of a vortex rings which are well-characterized and highly controllable. We also provide the theoretical guidelines underlying the design of gust generators for specific applications. As a case study, we tested the efficacy of this method to study the flight response of freely-flying soldier flies Hermetia illucens. The vortex ring based method can be used to generate controlled gusts to study diverse phenomena ranging from a natural flight in insects to the artificial flight of insect-sized drones and micro-aerial vehicles. [ABSTRACT FROM AUTHOR]