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Unlocking the Potential of Herbal Therapies in the Management of Psoriasis: Prospects and Challenges
No full textSince the authors are not responding to the editor’s requests to fulfill the editorial requirement, therefore, the article has beenwithdrawn.Bentham Science apologizes to the readers of the journal for any inconvenience this may have caused.The Bentham Editorial Policy on Article Withdrawal can be found at https://benthamscience.com/editorial-policies-main.php.BENTHAM SCIENCE DISCLAIMER:It is a condition of publication that manuscripts submitted to this journal have not been published and will not be simultaneouslysubmitted or published elsewhere. Furthermore, any data, illustration, structure or table that has been published elsewheremust be reported, and copyright permission for reproduction must be obtained. Plagiarism is strictly forbidden, and by submittingthe article for publication the authors agree that the publishers have the legal right to take appropriate action against theauthors, if plagiarism or fabricated information is discovered. By submitting a manuscript the authors agree that the copyrightof their article is transferred to the publishers if and when the article is accepted for publication.</p
Advances in Iontophoresis-Based Drug Delivery
No full textThe localized dermal and transdermal delivery of therapeutics for managing diverse skin diseases (acne, psoriasis, skin cancer), ocular diseases, etc., is challenging. The anatomical features and presence of barriers are key hurdles in efficiently delivering drugs. Iontophoresis has emerged as a promising avenue for enhancing the permeability of drugs by overcoming the challenges mentioned above. It is an innovative drug delivery technique that utilizes low-level electrical currents to enhance the dermal or transdermal transport of charged therapeutic agents. The significant versatility in delivering drug doses in a controlled manner is the key benefit of the iontophoresis technique. This chapter covers recent advances in iontophoretic approaches used for drug delivery, focusing on iontophoresis transport mechanisms and routes of administration. Key factors influencing iontophoresis efficacy, such as current density, electrode design, etc., are discussed. Significant advancements in iontophoresis including the integration of iontophoresis with nanocarriers and microneedles, which improve drug permeation and provide targeted drug delivery, are also explained. In addition, the future perspectives section provides insight into further research required into combination therapies and real-time monitoring systems to enhance the clinical effectiveness of the iontophoretic drug delivery approach. Overall, iontophoresis represents a promising approach that could revolutionize noninvasive drug administration methods in modern drug delivery systems
Operating theatre nurses’ experiences in medical emergency response: An integrative literature review
Full text linkAims: This study aims to review the experiences of instrument and circulating nurses in responding to intra-operative medical emergencies.
Background: The operating theatre is a complex environment where surgical procedures are performed by surgical teams who are often required to adapt to rapidly changing circumstances. Although most surgeries are uneventful, medical emergencies can occur. Instrument and circulating nurses play pivotal roles in patient safety during the intra-operative phase. However, research into their experiences dealing with medical emergencies is limited, highlighting the need for a better understanding of their perspectives and identifying areas where additional training and support may be required.
Design: An integrative review.
Methods: We conducted an electronic literature search in Medline, CINAHL, Scopus, Science Direct and PubMed databases. Three reviewers independently screened, extracted data and assessed quality, using Joanna Briggs Institute software to facilitate the process. We followed the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines for reporting.
Results: Three studies were included, but they did not explicitly address instrument and circulating nurses’ experiences during intra-operative medical emergencies. Instead, they discussed these nurses’ involvement in such emergencies, emphasising their mental preparation and the importance of effective communication and coordination within the team. The overall team’s experience influenced how medical emergencies were managed.
Conclusions: The experiences of instrument and circulating nurses during intraoperative medical emergencies remain underexplored in the literature. While some research examines surgical adverse events, there is a gap in assessing these nurses’ confidence and competence in such events. Non-technical skills are crucial, but the interplay with technical skills remains unexplored.</jats:p
Impact of Visual Context on Noisy Multimodal NMT: An Empirical Study for English to Indian Languages
Full text linkNeural Machine Translation (NMT) has made remarkable progress using large-scale textual data, but the potential of incorporating multimodal inputs, especially visual information, remains underexplored in high-resource settings. While prior research has focused on using multimodal data in low-resource scenarios, this study examines how image features impact translation when added to a large-scale, pre-trained unimodal NMT system. Surprisingly, the study finds that images might be redundant in this context. Additionally, the research introduces synthetic noise to assess whether images help the model handle textual noise. Multimodal models slightly outperform text-only models in noisy settings, even when random images are used. The study’s experiments translate from English to Hindi, Bengali, and Malayalam, significantly outperforming state-of-the-art benchmarks. Interestingly, the effect of visual context varies with the level of source text noise: no visual context works best for non-noisy translations, cropped image features are optimal for low noise, and full image features perform better in high-noise scenarios. This sheds light on the role of visual context, especially in noisy settings, and opens up a new research direction for Noisy Neural Machine Translation in multimodal setups. The research emphasizes the importance of combining visual and textual information to improve translation across various environments. Our code is publicly available at https://github.com/babangain/indicMMT
Prevalence and risk factors of sexual harassment in the workplace by female readymade garment workers in Bangladesh.
Full text linkOBJECTIVES: Bangladeshi female readymade garment (RMG) workers' experience of sexual harassment in the workplace raises concerns about the overall working conditions of the garment sector. Female workers' feelings of being unsafe and threatened in the workplace have been considered an alarming issue for international buyers/brands who aim to ensure sexual harassment-free workplaces as a condition of sourcing clothing items. We hypothesise that the frequent experience of sexual harassment among Bangladeshi female RMG workers tends to be associated with (i) age, (ii) marital status, (iii) night shift (working during night time), (iv) non-existence of anti-sexual harassment cells (a formal body/committee works against sexual harassment incidence in the workplace), (v) trade union activity, and (vi) factory location and types. To our knowledge, there has been no previous research on the experience of sexual harassment by female garment workers and its connections to such a variety of occupational and geographical factors. By addressing this gap, the present study aimed to investigate the prevalence and risk factors associated with female garment workers' experience of sexual harassment. METHODS: Cross-sectional data were collected from 332 (mean age = 26.10 years; SD = 6.54 years) currently employed female garment workers in Bangladesh, between February and July 2018. Data were analysed using bivariate and multivariate logistic regression modelling. RESULTS: In the past 6 months, nearly one-quarter (22.0%) of workers reported experiencing frequent sexual harassment inside the factory, mainly by male co-workers (37.0%), supervisors (32.9%), security guards (27.4%), and factory owners (2.7%). Workers from the factories located in Chattogram (a peripheral region compared to Dhaka) reported a higher frequency of sexual harassment than those working in factories located in Dhaka (the capital city of Bangladesh). Overall, the percentages of unmarried and young female workers who experienced sexual harassment were almost double compared to married and aged female workers. Workers' frequent experience of sexual harassment at the workplace was associated with factory location (β 0.67, 95%CI 1.02, 3.76), night shift (β 2.58, 95%CI 6.92, 25.18), and non-existence of an anti-sexual harassment cell inside the factory (β 0.62, 95%CI 0.97, 3.55). CONCLUSION: Urgent improvements in overall workplace conditions and anti-sexual harassment programmes are needed to safeguard female workers in the Bangladeshi RMG sector
Pre/post-follow-up evaluation of person-centred care education in dementia care for direct care staff in the sub-acute aged rehabilitation setting.
No full textTo support the holistic needs of persons living with dementia undergoing rehabilitation, an education program informed by the Kitwood model of person-centred care (PCC) was provided to the direct care nursing, medical and allied health staff (n = 66) of one sub-acute aged rehabilitation hospital. A multi-methods pre/post/follow-up study design evaluated participant reactions, learning, behaviour and outcomes. Compared to pre-PCC education, at post- and at 6-months follow-up there were significant improvements in participant PCC confidence (p < 0.001, 95 % CI), knowledge and skills (p < 0.0001, 95 % CI), care quality (p = 0.000, phi = 0.37) and a 17.5 % improvement in service quality (p = 0.369, phi=0.08). PCC was maintained through policy, practice guidelines and communication aids instigated by PCC champions. PCC education is effective when it is accessible, streamlined and includes a range of learning options catering to direct care staff's preferred learning styles and according to learning needs
Advances in impact force identification: A comprehensive review of techniques and mathematical innovations
Full text linkThis review provides a comprehensive and critical synthesis of state-of-the-art methodologies for impact force identification, a pivotal inverse problem in aerospace, automotive, civil infrastructure, and robotics systems. A systematic taxonomy is established to evaluate impact force reconstruction techniques, including deconvolution, subspace state-space formulations, and data-driven models, as well as localization strategies, such as triangulation, similarity-based matching, and optimization-based algorithms. The comparative analysis underscores the trade-offs between model-based approaches, which offer high computational efficiency in linear regimes, and machine learning methods, which demonstrate robustness in capturing nonlinear and high-dimensional system behaviors. The paper delves into recent mathematical advancements aimed at mitigating the inherent ill-posedness of inverse problems, emphasizing the roles of advanced regularization schemes, compressed sensing, and sparsity-promoting techniques. Notable emerging directions include hybrid physics-informed machine learning frameworks, domain adaptation and transfer learning to alleviate data dependency, and incremental learning paradigms suited for real-time deployment. Unresolved challenges are also identified, particularly in scenarios involving multiple concurrent impacts, sparse sensor networks, and online operation under dynamic environmental conditions. The review concludes by outlining future research trajectories to advance the accuracy, generalizability, and real-time feasibility of impact force identification methods
Assessing the optimal drivers for flux data gap-filling using random forest networks
Full text linkThe Terrestrial Ecosystem Research Network (TERN) OzFlux group operates a network of eddy covariance stations that collect long-term atmospheric and soil measurements for monitoring and understanding changes in climate and the environment. Ideally, all data collected would be gap-free, however, all real data has gaps where instruments have not recorded measurements or data has been discarded due to low turbulence. To allow this data to be used as a continuous time-series in further analysis, the missing data is gap-filled using PyFluxPro. The standard community approach uses a predefined set of variables (drivers) for gap-filling, which are the same variables for all stations irrespective of location. However, the stations are located in a large range of climate zones, hence the standard gap-filling drivers might not be ideal for all sites. This is because the drivers were chosen for a small set of initial sites and might not be representative for a heating and drying climate.To identify which drivers were best suited for each station, we developed a random forest model to objectively assess the relative importance of input variables used to gap-fill ustar, carbon, and energy fluxes. We trained this model on the published TERN OzFlux data for all available Australian sites using a large range of input variables. This model then determined the relative importance of variables, mean absolute errors, and R2 for the accuracy of the model prediction for a target variable at each site. Next, we grouped the variables into atmospheric, energy, turbulence and soil categories of drivers, which highlighted a distinct variation in the contribution of each category of driver across sites. To assess the ecological significance of these trends, the model importances were sorted by the aridity index and grouped by the Köppen-Geiger classification of each site. There is a notable shift in the importance of energy, turbulence, and soil groups with decreasing aridity, and driver contributions were generally consistent within Köppen-Geiger classifications. Reprocessing the gap-filling of a representative subsample of sites demonstrated a marked improvement in predicting the gap-filled target variables, highlighting that this approach can inform driver selection at new and established sites and will improve the understanding of the ecological significance of different drivers in various climate regions
A rapid, efficient, and cost-effective method for titering third-generation lentiviral vectors
Full text linkLentiviral vectors are useful vectors for stable transduction and permanent expression in dividing and non-dividing cells. In particular, third-generation lentiviral vectors have been engineered to be significantly safer than their second-generation counterparts, incorporating several safety features not present in earlier versions. For example, the tat gene, which is essential for the replication of wild-type human immunodeficiency virus type 1, has been deleted, and vector packaging functions have been distributed across three separate plasmids, further enhancing safety. In both research and clinical settings, having a reliable and accurate method for titering lentiviral vectors is critical. We have developed a method using the Woodchuck Hepatitis Virus Post-transcriptional Regulatory Element as a template for a real-time quantitative polymerase chain reaction, coupled with TRIzol lysis buffer for ribonucleic acid isolation. This method yielded results comparable to those from a commonly used commercial kit, offering advantages of speed, cost-effectiveness, and accuracy. It presents a viable, economical alternative for both research and clinical laboratories
Recent Advances in Computational Methods, Predictions, and Applications to Critical Zones in Railways
No full textAccurate evaluation of the mechanical response of railway tracks subjected to train-induced repeated loading is a prerequisite for their proper design and maintenance planning. A multitude of approaches have been developed over the years to accurately predict some of the most crucial aspects of track behaviour. This theme paper presents the recent advances in computational methods that can be employed to predict the performance of railway tracks and demonstrates their capabilities. Firstly, the suitability of the finite element (FE) method in understanding the soil arching mechanism, which governs the behaviour of the pile-supported railway embankments, is demonstrated. The influence of pile spacing on the soil arching mechanism is illustrated. Subsequently, the utilisation of the FE method in evaluating the performance of the ballasted and slab tracks is explored. The vertical stress variation and the accumulation of settlement in both tracks are compared. In addition, a novel computational approach based on a geotechnical rheological track model is presented that can be employed to predict the long-term performance of a standard section of the railway track as well as the critical zones, such as bridge-embankment transitions. Finally, the practical applications of the computational techniques and their future scope are discussed
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