Area Of Interest Research Articles

Editorial

The aim of this issue is to ‘showcase’ the work of a number of writers who are engaged with research at post-graduate level, beyond any initial professional education. As will become evident some of this work is completed, or near to completion, whilst other work is at the start of the research process. All of the writers are experienced practitioners and/or academicswho have sought to expand their knowledge in an area of professional interest and to disseminate this to others. The research presented in this issue also represents different sectors within career education and guidance.

Bile Acid Nanoparticles - An Emerging Approach for Site Specific Drug Targeting

Abstract: Bile acids, a group of steroidal acids present in the bile act as biological surfactants and ligands for bile acid transporter proteins for signalling molecules to perform various paracrine and endocrine functions. The enterohepatic circulation of bile acids can be exploited to develop at-tractive drug delivery approaches with improved targetability of facial amphiphiles and enhanced drug bioavailability by improving absorption and metabolic stability. The effectiveness, safety and targetability of nanoparticles conjugated with bile acids and salts have been discussed in the present review. Various modifications of bile acids promoting absorption and oral bioavailability of drugs for treatment of various disease conditions such as cancer, diabetes and psychosis has al-so been discussed. Additionally, neuroprotective effect of bile acids and salts has demonstrated utility in various neurodegenerative disorders. Nanoparticles based on bile acids and salts repre-sent an area of emergent interest due to their unique and modifiable properties for improving ef-fectiveness of drugs.

Advanced Plant Phenotyping: Unmanned Aerial Vehicle Remote Sensing and CimageA Software Technology for Precision Crop Growth Monitoring

In production activities and breeding programs, large-scale investigations of crop high-throughput phenotype information are needed to help improve management and decision-making. The development of UAV (unmanned aerial vehicle) remote sensing technology provides a new means for the large-scale, efficient, and accurate acquisition of crop phenotypes, but its practical application and popularization are hindered due to the complicated data processing required. To date, there is no automated system that can utilize the canopy images acquired through UAV to conduct a phenotypic character analysis. To address this bottleneck, we developed a new scalable software called CimageA. CimageA uses crop canopy images obtained by UAV as materials. It can combine machine vision technology and machine learning technology to conduct the high-throughput processing and phenotyping of crop remote sensing data. First, zoning tools are applied to draw an area-of-interest (AOI). Then, CimageA can rapidly extract vital remote sensing information such as the color, texture, and spectrum of the crop canopy in the plots. In addition, we developed data analysis modules that estimate and quantify related phenotypes (such as leaf area index, canopy coverage, and plant height) by analyzing the association between measured crop phenotypes and CimageA-derived remote sensing eigenvalues. Through a series of experiments, we confirmed that CimageA performs well in extracting high-throughput remote sensing information regarding crops, and verified the reliability of retrieving LAI (R2 = 0.796) and estimating plant height (R2 = 0.989) and planting area using CimageA. In short, CimageA is an efficient and non-destructive tool for crop phenotype analysis, which is of great value for monitoring crop growth and guiding breeding decisions.

Cropland inundation mapping in a mountain dominated region based on multi-resolution remotely sensed imagery and active learning for semantic segmentation

Accurate and timely mapping of cropland inundated area is critical to loss assessment and recovery plan development. However, existing methods for cropland inundation mapping using Synthetic Aperture Radar (SAR) imagery are primarily designed for plain regions and may not be suitable for mountainous regions. The complex rugged terrain at large scale present challenges such as significant noise from radar shadows, smooth surfaces, floodplains, and permanent water bodies. To remove these noise for effectively mapping of cropland inundation, this study proposes a robust two-stage framework integrating the multi-resolution remotely sensed imageries and semantic segmentation method. First, active learning for cropland extraction is performed with Google Very-High-Resolution (VHR) imagery and Segformer model. Second, the cropland inundation area is obtained using marker-controlled watershed segmentation (MCW) on Sentinel-1 SAR imagery with area-of-interest (AOI) filtering. Results show that the extracted cropland mask are superior to six public cropland data products including ESA, ESRI, FCS30, FROM, GL30, and SLOPE. In addition, with AOI filtering, the F-score of the potential flood identification using MCW was increased from 0.685 to 0.828. At last, the monthly cropland inundation caused by intense rainfall varied approximately from 6.6 km2 to 436.1 km2 during monsoon season of 2017–2022 in Guangdong. Our approach offers a fast and feasible solution for mapping cropland inundation in large and complex mountainous regions, without requiring extensive parameter tuning or additional data.

Incorporating Season and Solar Specificity Into Renderings Made by a NeRF Architecture Using Satellite Images.

As a result of Shadow NeRF and Sat-NeRF, it is possible to take the solar angle into account in a NeRF-based framework for rendering a scene from a novel viewpoint using satellite images for training. Our work extends those contributions and shows how one can make the renderings season-specific. Our main challenge was creating a Neural Radiance Field (NeRF) that could render seasonal features independently of viewing angle and solar angle while still being able to render shadows. We teach our network to render seasonal features by introducing one more input variable - time of the year. However, the small training datasets typical of satellite imagery can introduce ambiguities in cases where shadows are present in the same location for every image of a particular season. We add additional terms to the loss function to discourage the network from using seasonal features for accounting for shadows. We show the performance of our network on eight Areas of Interest containing images captured by the Maxar WorldView-3 satellite. This evaluation includes tests measuring the ability of our framework to accurately render novel views, generate height maps, predict shadows, and specify seasonal features independently from shadows. Our ablation studies justify the choices made for network design parameters.

New Era in Cultural Heritage Preservation: Cooperative Aerial Autonomy for Fast Digitalization of Difficult-to-Access Interiors of Historical Monuments

Digital documentation of large interiors of historical buildings is an exhausting task since most of the areas of interest are beyond typical human reach. We advocate the use of autonomous teams of multi-rotor Unmanned Aerial Vehicles (UAVs) to speed up the documentation process by several orders of magnitude while allowing for a repeatable, accurate, and condition-independent solution capable of precise collision-free operation at great heights. The proposed multi-robot approach allows for performing tasks requiring dynamic scene illumination in large-scale real-world scenarios, a process previously applicable only in small-scale laboratory-like conditions. Extensive experimental analyses range from single-UAV imaging to specialized lighting techniques requiring accurate coordination of multiple UAVs. The system's robustness is demonstrated in more than two hundred autonomous flights in fifteen historical monuments requiring superior safety while lacking access to external localization. This unique experimental campaign, cooperated with restorers and conservators, brought numerous lessons transferable to other safety-critical robotic missions in documentation and inspection tasks.

Modern vocal pedagogy: Investigating a potential curricular framework for training popular music singing teachers

This study explores the content and pertinence of a curricular framework for training popular music (PM) singing teachers. The author conducted three extensive literature review studies over two years via an action research framework to investigate common areas of interest for potential pedagogical strategy. She developed a draft curricular topic framework, incorporating five PM-specific areas: vocal health and hygiene, PM stylistic advice, microphones/audio technology, resonance and breathing technique. Five international PM voice teaching representatives took part in the research as focus group participants and provided feedback on the curriculum content. Data from this feedback were analysed in an iterative cycle process and adjustments suggested. Findings from this study indicate that such a curriculum would be both necessary and timely. Suggestions were made to amend some elements and to place greater emphasis on aesthetic artistry, cultural context and emotional intent.

Spider Silk: Biosynthesis, Properties & Bioengineering

Abstract: Due to the remarkable and unique qualities of spider silk, it has much applicability in the coming days. The complicated diversity and structure of spider silk ensure its use in both nature and industry. Based on the uniqueness and distinctive qualities associated with spider silks, advancements in cloning and expression of these silks are a growing area of research and industrial use. The environmentally triggered spider silk assembly and further disassembly, the creation of fibers, films, and novel chimeric composite materials from genetically modified spider silks are interesting areas of research in nanotechnology. In this context, we have discussed the creation of hybrids made of spider silk that combine with organic nanoparticles, both naturally occurring and bioengineered spider silk proteins. The diversity of spider silk, its composition and architecture, the distinctions between spider silk and silkworm silk, and the biosynthesis of natural silk are also discussed. This article describes the current issues and expected outcomes using biochemical data and processes.

Publication patterns of posters and oral presentations at the Annual Meeting of the Joint AANS/CNS Cerebrovascular Section.

The American Association of Neurological Surgeons (AANS) and Congress of Neurological Surgeons (CNS) Joint Cerebrovascular (CV) Section serves as a centralized entity for the dissemination of information related to CV neurosurgery. The quality of scientific conferences, such as the CV Section's Society of NeuroInterventional Surgery Annual Meeting, can be gauged by the number of poster and oral presentations that are published in peer-reviewed journals. However, publication rates from the CV Section's meetings are unknown. The objective of this study was to assess the rate at which abstracts presented at the AANS/CNS CV Section Annual Meeting from 2014 to 2018 were subsequently published in peer-reviewed journals. The abstract titles for all accepted poster and oral podium presentation abstracts from the 2014-2018 Annual Joint AANS/CNS CV Section Meetings were searched using PubMed. A match was defined as sufficient similarity between the abstract and its corresponding journal publication with regard to title, authors, methods, and results. Five-year impact factors (IFs) from Journal Citation Reports (JCR), the country of the corresponding author, and the number of citations in the Scopus database were obtained using the articles' digital object identifier when available, or the exact article title, journal, and year of publication. Of the 607 total poster and oral presentations from the 2014-2018 Annual Meetings of the AANS/CNS Joint CV Section, 46.29% (n = 281) have been published. Published articles received 3233 total citations for an average number of citations per article (± SD) of 10.89 ± 16.37. The average 5-year JCR IF of published studies was 4.64 ± 3.13. Additionally, 98.22% of published abstracts were in publication within 4 years from the time the abstract was presented. The most common peer-reviewed neurosurgical journals featuring these publications were the Journal of Neurosurgery, World Neurosurgery, the Journal of NeuroInterventional Surgery, Neurosurgery, and the Journal of Clinical Neuroscience. Nearly half of all poster and oral presentations at the annual meetings of the AANS/CNS Joint CV Section from 2014 to 2018 have been published in PubMed-indexed, peer-reviewed journals. The average number of citations per publication (10.89 ± 16.37) reflects the high quality of abstracts accepted for presentation. It is important to continuously assess the quality of research presented at national conferences to ensure that standards are being maintained for the advancement of clinical practice in a given area of medicine. Conference abstract publication rates in peer-reviewed journals represent a way in which research quality can be gauged, and the authors encourage others to conduct similar investigations in their subspecialty area of interest and/or practice.

Spectral variations within solar flare ribbons

Context.Solar flare ribbons are intense brightenings of primarily chromospheric material that are responsible for a large fraction of the chromospheric emission in solar and stellar flares. We present an on-disc observation of flare ribbon substructures in an X9.3-class flare observed by the Swedish 1-m Solar Telescope.Aims.We aim to identify categories of ribbon substructures seen in the Ca II8542 Å, Hα, and Ca IIK lines, focusing on their spatial locations and their (spectro-)polarimetric properties.Methods.We used COlor COllapsed Plotting (COCOPLOT) software to assist in identifying areas of interest.Results.We present five categories of spectral profiles within the general body of the flare ribbon: (1) extremely broadened spectral line profiles, where the standard Fabry–Perot interferometer wavelength windows (≈70 km s−1) are not sufficiently wide to allow for a complete analysis of the dynamics and atmospheric conditions. The mechanisms causing this degree of this broadening are not yet clearly understood; (2) long-lived, dense kernels that manifest as more saturated chromospheric line profiles with lower signal in both Stokes parameters. They are interpreted as footpoints of bunched magnetic field loops, whose chromospheric lines form at greater heights than the nearby areas; (3) Doppler-shifted leading edges of the flare ribbon in regions that transiently display lower Stokes signals due to the emission dominating at greater heights in the atmosphere; (4) condensed coronal rain overlapping the flare ribbons in the line of sight, producing exceptionally high Doppler shifts near the footpoints; and (5) compact blueshifted areas close to areas with coronal rain down-flows, which are understood to be material that has been thrown up as a result of the down-flowing material impacting the chromosphere. Additionally, a ribbon formation height of about 700 km with respect to penumbral features is estimated using correlating structures on the ribbon and the underlying photosphere.Conclusions.When selecting areas of the flare ribbon for more general analysis (especially small regions consisting of a few pixels or low-resolution averages), it is important to be aware of the variety of substructures present within a flare ribbon and of the spatial context that can produce these differences. General behaviors across the ribbon should not be inferred from regions that show localized differences.

Computational Techniques in PET/CT Image Processing for Breast Cancer: A Systematic Mapping Review

The problem arises from the lack of sufficient and comprehensive information about the necessary computer techniques. These techniques are crucial for developing information systems that assist doctors in diagnosing breast cancer, especially those related to positron emission tomography and computed tomography (PET/CT). Despite global efforts in breast cancer prevention and control, the scarcity of literature poses an obstacle to a complete understanding in this area of interest. The methodologies studied were systematic mapping and systematic literature review. For each article, the journal, conference, year of publication, dataset, breast cancer characteristics, PET/CT processing techniques, metrics and diagnostic yield results were identified. Sixty-four articles were analyzed, 44 (68.75%) belong to journals and 20 (31.25%) belong to the conference category. A total of 102 techniques were identified, which were distributed in preprocessing with 7 (6.86%), segmentation with 15 (14.71%), feature extraction with 15 (14.71%), and classification with 65 (63.73%). The techniques with the highest incidence identified in each stage are: Gaussian Filter, SLIC, Local Binary Pattern, and Support Vector Machine with 4, 2, 7, and 35 occurrences, respectively. Support Vector Machine is the predominant technique in the classification stage, due to the fact that Artificial Intelligence is emerging in medical image processing and health care to make expert systems increasingly intelligent and obtain favorable results.

Multi-CNN based logical reasoning system for facial expression recognition on small-sample datasets

Facial expression recognition has long been an area of great interest across a wide range of fields. Deep learning is commonly employed in facial expression recognition and demonstrates excellent performance in large-sample classification tasks. However, deep learning models often encounter challenges when confronted with small-sample expression classification problems, as they struggle to extract sufficient relevant features from limited data, resulting in subpar performance. This paper presents a novel approach called the Multi-CNN Logical Reasoning System, which is based on local area recognition and logical reasoning. It initiates the process by partitioning facial expression images into two distinct components: eye action and mouth action. Subsequently, it utilizes logical reasoning based on the inherent relationship between local actions and global expressions to facilitate facial expression recognition. Throughout the reasoning process, it not only incorporates manually curated knowledge but also acquires hidden knowledge from the raw data. Experimental results conducted on two small-sample datasets derived from the KDEF and RaFD datasets demonstrate that the proposed approach exhibits faster convergence and higher prediction accuracy when compared to classical deep learning-based algorithms.

Towards Transformative Event Experiences: State of the Art and Future Research

This research note reviews and discusses the state-of-the-art research on event experiences. Through an in-depth literature review, the study bridges events research and experience design to zoom in on transformative event experiences as an emerging area of interest in events research and practice. A shift from managing events to designing events, as well as a change in events to human transformation is highlighted. Finally, an agenda for future research is presented that outlines five distinct avenues for deepening our understanding of the mechanisms of transformative event experiences. The article has important implications for research and practice for designing, facilitating, and guiding future event experiences, particularly those with a transformative potential.

Review on Pyrazole Hybrids as Anti-microbial Agents

Abstract: A five-membered heteroaromatic ring with two nitrogen atoms, pyrazole, is of immense significance. Pyrazole and its derivatives are well-known nitrogen-containing heterocyclic compounds that are significant in medicinal chemistry and have a variety of biological properties, according to a thorough analysis of this class of heterocyclic lead. This article summarises some biologically active, potent pyrazole hybrids and their structure-activity relationship for antimicrobial activity published by various researchers across the world. It is divided into two sections. The first part summarizes recent developments in pyrazole derivatives for various biological activities, such as anti-Alzheimer’s, antioxidant, anticancer, anti-inflammatory, and antiviral, while the second section focuses on a detailed substitution analysis of pyrazole with its hybrid, which is the structure-activity relationship needed for antimicrobial activity. The presence of pharmacological potential of pyrazole moiety has been demonstrated by the role of a nucleus in pharmacological agents from different therapeutic groups, such as the potent anti-inflammatory agent celecoxib, anti-obesity drug rimonabant, analgesic diphenamizole, H2-receptor agonist betazole, and antidepressant agent fezolamide. The design of new pyrazole derivatives has become an interesting research area due to their versatile nature and biological significance. Moreover, it has been observed that pyrazole in combination with another moiety has a strong potent antimicrobial effect.

Incorporating Mental Health Literacy Into the Sport Management Curriculum

Mental health is an emerging area of interest in sport, but there is a paucity of educational initiatives in sport management curricula to train the next generation of sport managers to address the mental health needs of athletes, a type of knowledge that the mental health literature operationalizes as mental health literacy. One goal of accrediting bodies such as the Commission on Sport Management Accreditation is for excellence in sport management education; thus, due to the changing landscape of sport, sport management curricula should incorporate mental health literacy competencies. This educational research review provides justification for the inclusion of mental health literacy competencies in sport management curricula and accreditation standards, as well as pedagogical strategies for implementation.

Energy-Efficient Device-to-Device Communications for Green Internet of Things Using Unmanned Aerial Vehicle-Mounted Intelligent Reflecting Surface

The Internet of Things (IoT) serves as a crucial element in interconnecting diverse devices within the realm of smart technology. However, the energy consumption of IoT technology has become a notable challenge and an area of interest for researchers. With the aim of achieving an IoT with low power consumption, green IoT has been introduced. The use of unmanned aerial vehicles (UAVs) represents a highly innovative approach for creating a sustainable green IoT network. UAVs offer advantages in terms of flexibility, mobility, and cost. Moreover, device-to-device (D2D) communication is essential in emergency communications, due to its ability to support direct communication between devices. The intelligent reflecting surface (IRS) is also a hopeful technology which reconstructs the radio propagation environment and provides a possible solution to reduce co-channel interference resulting from spectrum sharing for D2D communications. The investigation in this paper hence focuses on energy-efficient UAV-IRS-assisted D2D communications for green IoT. In particular, a problem of optimization aimed at maximizing the system’s average energy efficiency (EE) is formulated, firstly, by simultaneously optimizing the power coefficients of all D2D transmitters, the UAV’s trajectory, and the base station (BS)’s active beamforming, along with the IRS’s phase shifts. Second, to address the problem, we develop a multi-agent twin delayed deep deterministic policy gradient (MATD3)-based scheme to find a near-optimal solution, where D2D transmitters, the BS, and the UAV cooperatively learn to improve EE and suppress the interference. To conclude, numerical simulations are conducted to assess the availability of the proposed scheme, and the simulation results demonstrate that the proposed scheme surpasses the baseline approaches in both convergence speed and EE performance.

Tools to measure the burden on informal caregivers of cancer patients: A literature review.

(1) To describe existing tools to assess the burden of informal caregivers of people with cancer, (2) to describe how these tools have been validated and (3) to describe the areas of interest of existing assessment tool entries. The caregiver burden of informal caregivers of people with cancer greatly affects their lives. There is a wide variety of relevant assessment tools available, but there are no studies to help researchers to select tools. A search was conducted using the keywords 'cancer', 'caregiver', 'burden' and 'scale' in Medline (PubMed), CINAHL and EMBASE to include articles that developed or applied tools to assess the burden on informal caregivers of cancer patients. Once eligible tools were identified, we searched their 'primary reference' studies. If the original scale was assessed in a population other than informal caregivers of cancer patients, we again searched for psychometric measures in the population of caregivers of cancer patients. This study retrieved 938 articles on developing or applying the informal caregiver burden instrument for cancer patients, including 42 scales. Internal consistency of the original scales ranged from 0.53 to 0.96. Nineteen scales initially developed to assess caregiver burden for patients with dementia, stroke and other disorders were later used for caregivers of cancer patients, eight of which have not yet been validated. Reclassifying all scale domains of concern revealed that scale assessments focused more on caregivers' physical health, emotional state and caregiving tasks. This review identifies many scales for assessing informal caregiver burden in cancer patients and gives scales recommended. However, a portion still needs to be validated. The development of a new scale proposes to be based on a theoretical framework and to consider dimensions for assessing support resources. What problem did the study address?: This paper collates assessment tools on the burden of informal carers of people with cancer. It also provides information on the applicable population, reliability and validity. What were the main findings?: 41 scales could be considered for use, eight of which have not been validated. The scales focus more on assessing caregivers' physical health, emotional state and caregiving tasks, and less on the dimension of support resources. Where and on whom will the research have an impact?: There are implications for informal carers of cancer patients in hospitals or in the community, as well as for relevant researchers. Retrieved with reference to systematic evaluation. No patient or public contribution.

Lakeshore areas of conservation interest: Characteristics of nursery areas of the threatened lake‐dwelling grayling, Thymallus thymallus

AbstractResearch‐based knowledge is essential for effective conservation and restoration of threatened aquatic species and habitats. Here, our aim was to gather this knowledge on the lake‐dwelling grayling (Thymallus thymallus), typically a riverine fish. Such atypical populations are particularly vulnerable to anthropogenic impacts, including fishing pressure, climate change, eutrophication and waterway construction, some of which affect especially the early life stages. However, there is little information available to guide management and conservation of grayling in lakes. Accordingly, we assessed characteristics of the nursery areas in the threatened grayling population of Lake Puruvesi (eastern Finland). In particular, we used beach seines in two consecutive years to sample lakeshore sites (including islands) that were a priori presumed suitable for grayling. We assessed the occurrence of grayling fry (larvae and post‐larvae <40 mm in length) regarding depth, year, the site's exposure (fetch), bottom shear stress, substrate coarseness and shoreline's north–south orientation. Overall, we found grayling fry in low numbers at every fourth site, with the sites’ exposure and dominant substrate coarseness being most relevant variables. In particular, more exposed sites (i.e. with higher fetch values) and fine‐grained substrates dominated by sand or gravel had more grayling fry. Average depth, bottom shear stress or shoreline orientation along the north–south axis did not have a significant effect. Together, the results suggest that the most important nursery areas for lake‐dwelling grayling are lakeshore zones that are barren and exposed. Hence, the sites share characteristics with those used for reproduction by the more common riverine grayling. We hope that these findings will facilitate lake‐dwelling grayling's management and conservation efforts.

Unveiling the neuroprotective potential of chrysin on the pre-frontal cortex of adult male Wistar rats

Objectives Excessive free radicals in the human body predispose cells within the various systems to an imbalance and accumulation of oxygen-reactive species, known as oxidative stress. The central nervous system is not spared when it comes to these cell and tissue damages. Oxidative stress on the central nervous system may be responsible for anxiety, spatial memory impairment, neuronal cell depletion, and vacuole-tissue degeneration resulting from neurotoxicity. The use of chemotherapeutic agents such as doxorubicin has been implicated in the build-up of this imbalance between oxygen-reactive species and antioxidants. Therefore, it has become an area of research interest to seek antioxidant supplements that may offer neuroprotective effects. This study is aimed to evaluate the protective potential of chrysin on the pre-frontal cortex of male Wistar rats with doxorubicin-induced cognitive impairment. Material and Methods Thirty-five adult Wistar rats (180–200 g) were grouped into seven (1–7; n = 5). Group 1, the normal control, received normal saline treatment only throughout the study. Group 2 was administered with doxorubicin only for 21 days by intraperitoneal injection. Groups 3 and 4 were administered with chrysin in low and high doses for 21 days orally. Groups 5, 6 and 7 were exposed to doxorubicin and chrysin for 21 days intra-peritoneally and orally with low, medium and high doses, respectively. Results Anti-oxidative biomarkers analysed in Group 2 (doxorubicin-only) demonstrated a significant difference when compared to other groups. This corresponded to significant elevations in apoptotic indicators, inflammatory markers and histological lesions, which were indicative of cognitive impairment. 5, 7-dihydroxyflavone (chrysin) significantly mitigated and also reversed cognitive impairment caused by doxorubicin. Conclusion The data showed that chrysin protected against doxorubicin-induced cognitive impairment. This effect is probably made possible by suppressing oxidative stress, inflammation and apoptosis.

Insect immunity - adaptive mechanisms and survival strategies

Host-pathogen interactions play an important role in understanding the dynamics of the insect immune system. The analysis of environmental modulators, both biotic and abiotic, directs our attention to the impact of the surroundings on the effectiveness of immunological responses. This knowledge is essential for the comprehensive understanding of insect’s immune reaction after infection with a pathogen. This article discusses the role of the immune system in insect, with a special emphasis on greater wax moth Galleria mellonella and highlights its adaptive capabilities. The processes are not only extremely interesting area of scientific research but also indicate potential practical applications in the context of plan protection, pest population control and medicine.