Area Of Research Research Articles

SPECTRUM AND TIME-FREQUENCY ANALYSIS TO CHARACTERIZE MICROTREMOR DATA IN SEPAKU SUB-DISTRICT, EAST KALIMANTAN

Microtremor analysis has been done in the Sepaku Sub-District as a part of the New Capital City of Indonesia. This study aims to determine the characteristics of microtremors in the Sepaku Sub-District using Spectrum Analysis and Time-Frequency Analysis (TFA). Data in this study were taken using a seismometer on the 18 measurement points. The data were processed using default analysis from Geopsy software. Spectrum analysis and TFA used Fourier Transform to change time domain data into the frequency domain. Both analysis ways result in the characteristic microtremor data in the research area. The spectrum analysis data obtained shows two frequency ranges with maximum peaks: middle-frequency (5-8.8 Hz) and high-frequency (11.5-17.6 Hz). Afterward, the TFA shows similar results, where the characteristics of microtremor data are divided into two zones. The maximum peak occurs at the middle-frequency range of 5-10 Hz, and the high frequency ranges above 10 Hz

Hydrocarbon Extraction with Ionic Liquids.

Separation and reaction processes are key components employed in the modern chemical industry, and the former accounts for the majority of the energy consumption therein. In particular, hydrocarbon separation and purification processes, such as aromatics extraction, desulfurization, and denitrification, are challenging in petroleum refinement, an industrial cornerstone that provides raw materials for products used in human activities. The major technical shortcomings in solvent extraction are volatile solvent loss, product entrainment leading to secondary pollution, low separation efficiency, and high regeneration energy consumption due to the use of traditional organic solvents with high boiling points as extraction agents. Ionic liquids (ILs), a class of designable functional solvents or materials, have been widely used in chemical separation processes to replace conventional organic solvents after nearly 30 years of rapid development. Herein, we provide a systematic and comprehensive review of the state-of-the-art progress in ILs in the field of extractive hydrocarbon separation (i.e., aromatics extraction, desulfurization, and denitrification) including (i) molecular thermodynamic models of IL systems that enable rapid large-scale screening of IL candidates and phase equilibrium prediction of extraction processes; (ii) structure-property relationships between anionic and cationic structures of ILs and their separation performance (i.e., selectivity and distribution coefficients); (iii) IL-related extractive separation mechanisms (e.g., the magnitude, strength, and sites of intermolecular interactions depending on the separation system and IL structure); and (iv) process simulation and design of IL-related extraction at the industrial scale based on validated thermodynamic models. In short, this Review provides an easy-to-read exhaustive reference on IL-related extractive separation of hydrocarbon mixtures from the multiscale perspective of molecules, thermodynamics, and processes. It also extends to progress in IL analogs, deep eutectic solvents (DESs) in this research area, and discusses the current challenges faced by ILs in related separation fields as well as future directions and opportunities.

Reservoir Quality, Lithotype Assessment, and Geochemical Source Rock Analysis: Insights from Well Logs and Pyrolysis Data, Karama Field, North-Western Desert, Egypt

Reservoir characteristics and source rock geochemistry are essential for petroleum system investigation as they reveal reservoir quality and hydrocarbon generation capability, respectively. The primary Karama oil field reservoir of Abu El Gharadig Basin is the limestone-sand-shale Abu Roash G (AR/G) Member. This study examines AR/G, analyzes source rocks for maturity and organic elements, and defines the main reservoir lithotypes and evaluates reservoir properties. Five well log datasets and an AR/F pyrolysis analysis on another well were used in this study to characterize the AR/G’s 168-foot effective thickness and assess the AR/F source-rock maturation. The effective porosity is up to 30%. The highest shale concentration was 24% in central and western parts of the field. Therefore, drilling development wells in this area, especially east and north, demands caution. The composition and vertical and lateral lithofacies variations of the defined reservoir in the Karama field region are a significant control of its petrophysical properties. The pyrolysis of AR/F revealed 1.32–5.84% content of organic matter. That content qualifies AR/F as a hydrocarbon source if thermal maturity is reached. Type I and type II kerogen in the Abu Roash F Member suggests oil production. The Abu Roash G Member and Upper Bahariya (UB) formation produce oil and gas due to their own type II and III kerogen. GC biomarker data suggests that the research area is predominantly maritime, with most samples showing environmental degradation. The area under consideration has one reservoir, AR/G, and three members of source rocks in AR/F&G and UB. AR/G electrofacies revealed various lithotypes and flow units.

BitTrace

Bitcoin is a digital currency system built on the foundation of fairness. However, some malicious miners, driven by their own interests, employ unfair tactics such as selfish mining to compete, which disregard the legitimate miners' investments in computational power and energy consumption. In order to assess the efficiency of the Bitcoin system in real-time and promptly detect malicious miners in the network, this paper proposes a data collection framework called BitTrace, which addresses the issues of low efficiency, lack of timeliness, and data loss in traditional data collection frameworks. BitTrace enables real-time collection and analysis of the blockchain formation process, storing it as structured data. Furthermore, the paper discusses factors that influence the efficiency of data collection and proposes a topological control scheme based on the DPC algorithm to enhance the integrity and efficiency of data collection. Researchers can explore various research areas and applications, such as selfish mining detection and legitimate mining strategy research.

Computational investigation of high Curie temperature in a new N‐type ferromagnetic diluted magnetic semiconductors, especially iron‐doped on GaSb

AbstractDiluted magnetic semiconductors have become a research area in the past few years due to the importance of new technology, spintronics devices, and green technology to withstand rising global temperatures. Both n‐type and p‐type diluted magnetic semiconductors are used in pairs for perfect performance, especially for p‐n junction diodes, the p‐d Zener model, GMR, and TMR spintronics devices. The main challenge for some researchers is to find a ferromagnetic diluted magnetic semiconductor with a Curie temperature greater than room temperature for both n‐type and p‐type ferromagnetic diluted semiconductors, but this study has solved this problem. In the present study, the ferromagnetic properties of an n‐type gallium iron antimonide diluted semiconductor have been studied using the Hamiltonian model without applying an external magnetic field, electric field, or chemical potential. We have formulated a Hamiltonian model in the system, considering the application of the green formalism function and the transformation of Holstein–Primakaff. The Curie temperature, dispersion, number of magnons, reduced magnetization, and specific heat capacity of ferromagnetic magnons of the n‐type (Ga, Fe)Sb formula are formulated. The Curie temperature versus concentration graph is plotted, and the specific heat capacity and magnetization versus temperature graphs are plotted. In this study, a surprising situation is that the Curie temperature of n‐type diluted magnetic semiconductor is investigated above room temperature, which is 330.4 K. The ferromagnetic properties of appear up to 330.4 K, which is able to play a major role in spintronic and next‐generation green nanotechnology devices.

Educational Opportunities in the Maritime Sector and the Development of the Bangladeshi Economy

The concept of a blue economy recognizes the seas and oceans as main drivers for economic development with great potential for innovation and growth. Bangladesh is blessed with an approximately 700 km long coast with nearly 1,18,813 sq. km. of maritime area. Hence it is likely to emerge as an important maritime State. The maritime sector in this country has a huge potential to boost national economic growth and thereby harness the blue economy. To tap the benefits from this sector, among others, there is a need to develop maritime human resources. Competent maritime human resources are considered the backbone of the blue economy and hence the national economic growth. As such Bangladesh needs to emphasize more on developing human resources in this sector through proper maritime education. Collaboration at the national and international level in the area of maritime research and education may be given priority to mitigate the challenges militating against the national economic growth. Bangabandhu Sheikh Mujibur Rahman Maritime University, Bangladesh may play a key role in unlocking the potential of Maritime Education for enhanced national economic growth.

Alternative Forms of Currency: An Exploratory Theoretical Analysis of Bitcoin

Objective: The study aims to critically analyse the role of digital currencies in the context of the monetary system and the challenges and implications for monetary liberalism. Method: Critical review based on an analysis of financial doctrine. A descriptive approach was applied to identify the relevant theories, followed by a critical analysis of the perspectives adopted by the authors. The main theoretical arguments are identified and debated. The methodology enables a critical study to be carried out through comparisons. Results and conclusions: The results highlight the clarity of the arguments, the logical solidity, and the relevance of the evidence presented by the authors. The comparative analysis reveals points of convergence and divergence in the arguments. Inclusive interpretation and reflection allowed the implications of the theoretical approaches for the field of study to be analysed. The conclusions reveal the evidence obtained. Implications if the research: They include an in-depth understanding of the financial theories examined at the level of Bitcoin, highlighting contributions and limitations. Promotes the advancement of knowledge in the theoretical field, identifies possible gaps in the literature, and suggests areas for future research. Provides relevant insights for academia, society, and policymakers. Originality/value: It resides in the application of a critical and analytical approach to financial theories, offering a detailed and contextualised review of the literature. The value comes from providing enlightened insights into the theoretical foundations and possible applications, contributing to the advancement of the academic and social fields.

APPLICATION OF THE NEXT GENERATION SEQUENCING IN BIOLOGY AND MEDICINE

Next-Generation Sequencing (NGS), also known as high-throughput sequencing, refers to a set of modern DNA sequencing technologies that have revolutionized the field of genomics. Advantages of NGS techniques involving high speed (parallel sequencing is faster than traditional methods, allowing researchers to obtain results more quickly), cost-effectiveness (ability to sequence multiple fragments simultaneously reduces the cost per base compared to traditional sequencing), and scalability (platforms can be scaled to accommodate varying levels of throughput depending on experimental needs). NGS has significantly accelerated genomics research, enabling breakthroughs in fields such as personalized medicine, cancer genomics, and evolutionary biology. However, challenges such as data analysis complexity, error rates, and cost still exist and are areas of ongoing research and improvement within the field of sequencing technologies. Paper contains the brief explanation of the current NGS platforms and their features. NGS biomedical application is described with the main advantages and abilities of the analysed tools.

Technology, relationships, and well-being: An overview of critical research issues and an introduction to the special issue

Technology, relationships, and well-being represent three influential parts of our daily lives. They also represent a common area of research for scholars in a variety of disciplines. Here, we offer guidance for researchers interested in studying the connections among these issues and introduce the special issue in the Journal of Social and Personal Relationships focused on the confluence of these topics. We take each issue in turn, along with their interconnections, and describe some common pitfalls along with ideas to advance research in these areas. After analyzing the body of research on technology, relationships, and well-being, we present the special issue. We explain how our analysis of this body of research along with obstacles we encountered conducting research in this area shaped our approach to the issue. For the edification of future editors, we briefly reflect on the strengths and weaknesses of our atypical editorial process before presenting the articles that compose this issue.

The relationship between blast-related mild traumatic brain injury and executive function is moderated by white matter integrity.

Blast-related mild traumatic brain injury (BR mTBI) is a critical research area in recent combat veterans due to increased prevalence of survived blasts. Post-BR mTBI outcomes are highly heterogeneous and defining neurological differences may help in discrimination and prediction of cognitive outcomes. This study investigates whether white matter integrity, measured with diffusion tensor imaging (DTI), could influence how remote BR mTBI history is associated with executive control. The sample included 151 Veterans from the Minneapolis Veterans Affairs Medical Center who were administered a clinical/TBI assessment, neuropsychological battery, and DTI scan as part of a larger battery. From previous research, six white matter tracts were identified as having a putative relationship with blast severity: the cingulum, hippocampal cingulum, corticospinal tract, inferior fronto-occipital fasciculus, superior longitudinal fasciculus and uncinate. Fractional anisotropy (FA) of the a priori selected white matter tracts and report of BR mTBI were used as predictors of Trail-Making Test B (TMT-B) performance in a multiple linear regression model. Statistical analysis revealed that FA of the hippocampal cingulum moderated the association between report of at least one BR mTBI and poorer TMT-B performance (p < 0.008), such that lower FA value was associated with worse TMT-B outcomes in individuals with BR mTBI. No significant moderation existed for other selected tracts, and the effect was not observed with predictors aside from history of BR mTBI. Investigation at the individual-tract level may lead to a deeper understanding of neurological differences between blast-related and non-blast related injuries.

MMKG-PAR: Multi-Modal Knowledge Graphs-Based Personalized Attraction Recommendation

As the tourism industry rapidly develops, providing personalized attraction recommendations has become a hot research area. Knowledge graphs, with their rich semantic information and entity relationships, not only enhance the accuracy and personalization of recommendation systems but also energize the sustainable development of the tourism industry. Current research mainly focuses on single-modal knowledge modeling, limiting the in-depth understanding of complex entity characteristics and relationships. To address this challenge, this paper proposes a multi-modal knowledge graphs-based personalized attraction recommendation (MMKG-PAR) model. We utilized data from the “Travel Yunnan” app, along with users’ historical interaction data, to construct a collaborative multi-modal knowledge graph for Yunnan tourist attractions, which includes various forms such as images and text. Then, we employed advanced feature extraction methods to extract useful features from multi-modal data (images and text), and these were used as entity attributes to enhance the representation of entity nodes. To more effectively process graph-structured data and capture the complex relationships between nodes, our model incorporated graph neural networks and introduced an attention mechanism for mining and inferring higher-order information about entities. Additionally, MMKG-PAR introduced a dynamic time-weighted strategy for representing users, effectively capturing and precisely describing the dynamics of user behavior. Experimental results demonstrate that MMKG-PAR surpasses existing methods in personalized recommendations, providing significant support for the continuous development and innovation in the tourism industry.

Temporal and Spatial Evolution of Meteorological Drought in Inner Mongolia Inland River Basin and Its Driving Factors

In order to analyze the temporal and spatial evolution of meteorological drought and explore its driving factors, the inland river basin of Inner Mongolia (IMIRB) was taken as a typical research area, the Standardized Precipitation Evapotranspiration Index (SPEI) of various scales was calculated, and the spatio-temporal trend change characteristics of meteorological drought were analyzed combined with the modified Mann–Kendall trend test (MMK). The typical meteorological drought events were analyzed by using the three-dimensional identification method, and the spatio-temporal evolution characteristics and dynamic evolution law of meteorological drought were analyzed comprehensively and accurately. The driving effects of Pacific Decadal Oscillation (PDO), North Atlantic Multidecadal Oscillation (AMO), Arctic Oscillation (AO), El Niño-Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), and sunspot on meteorological drought were investigated by using the cross wavelet method. The results are as follows: (1) with the increase of SPEI time scale, the frequency of meteorological drought decreased, but the duration and intensity of drought increased; (2) the trend was greatest in spring, with the largest number of areas showing a significant downward trend in SPEI, the strongest persistence in intensity, and significant aridification characteristics; (3) summer meteorological droughts had the largest area of high intensity drought but the smallest area of high frequency areas, and winter droughts had the smallest area of high intensity drought but the largest percentage of high frequency areas; (4) the meteorological drought event that occurred from April 2017 to December 2017 was the most serious, and reached its maximum value in June 2017, which mainly experienced five processes: occurrence—intensification—attenuation—re-intensification—extinction; (5) atmospheric circulation factor, sunspot, and meteorological drought of IMIRB were correlated, and ENSO had the greatest effect on drought. This study provides effective theoretical support for IMIRB drought prevention and disaster reduction.

Enhancing Human-in-the-Loop Ontology Curation Results through Task Design

The success of artificial intelligence (AI) applications is heavily dependent on the quality of data they rely on. Thus, data curation, dealing with cleaning, organising, and managing data, has become a significant research area to be addressed. Increasingly, semantic data structures such as ontologies and knowledge graphs empower the new generation of AI systems. In this article, we focus on ontologies as a special type of data. Ontologies are conceptual data structures representing a domain of interest and are often used as a backbone to knowledge-based intelligent systems or as an additional input for machine learning algorithms. Low-quality ontologies, containing incorrectly represented information or controversial concepts modelled from a single viewpoint, can lead to invalid application outputs and biased systems. Thus, we focus on the curation of ontologies as a crucial factor for ensuring trust in the enabled AI systems. While some ontology quality aspects can be automatically evaluated, others require a human-in-the-loop evaluation. Yet, despite the importance of the field, several ontology quality aspects have not yet been addressed and there is a lack of guidelines for optimal design of human computation tasks to perform such evaluations. In this article, we advance the state-of-the-art by making two novel contributions. First, we propose a human computation (HC)–based approach for the verification of ontology restrictions —an ontology evaluation aspect that has not yet been addressed with HC techniques. Second, by performing two controlled experiments with a junior expert crowd, we empirically derive task design guidelines for achieving high-quality evaluation results related to (i) the formalism for representing ontology axioms and (ii) crowd qualification testing . We find that the representation format of the ontology does not significantly influence the campaign results. Nevertheless, contributors expressed a preference in working with a graphical ontology representation. Additionally, we show that an objective qualification test is better fitted at assessing contributors’ prior knowledge rather than a subjective self-assessment and that prior modelling knowledge of the contributors had a positive effect on their judgements. We make all artefacts designed and used in the experimental campaign publicly available.

Psychiatrists’ Engagement in Research as a Pathway towards the Expansion of Distributed Medical Education (DME): A Regional Analysis across Two Provinces in Atlantic Canada

In the context of Canadian medical education, Distributed Medical Education (DME) plays a crucial role in addressing healthcare disparities, particularly in rural areas. This study focuses on the Department of Psychiatry at Dalhousie University, analyzing psychiatrists’ engagement and willingness to participate in research at DME sites in Nova Scotia (NS) and New Brunswick (NB). The cross-sectional study, encompassing data from an environmental scan, surveyed 60 psychiatrists involved in medical education across seven health zones. Results revealed significant associations between gender, type of graduates, and specialist training. A majority of psychiatrists (68.3%) do not currently engage in mental health or translational research, citing barriers such as a lack of protected time and financial incentives. Notably, participants expressed interest in future research areas, including health services/quality improvement and addiction research. Geriatric psychiatry, predominantly female-dominated, lacked current research activities. The study emphasizes the need to address barriers and promote motivators, both intrinsic and extrinsic, to enhance psychiatrists’ research engagement. This strategic approach is essential for fostering active participation in research, thereby contributing to the expansion of DME sites in Atlantic Canada and beyond.

Recent Trends and Applications of Nanostructure-based Drug Delivery in Alleviating Chronic Obstructive Pulmonary Disease (COPD).

Chronic Obstructive Pulmonary Disease (COPD), a chronic lung disease that causes breathing difficulties and obstructs airflow from the lungs, has a significant global health burden and affects millions of people worldwide. The use of pharmaceuticals in COPD treatment is aimed to alleviate symptoms, improve lung function, prevent exacerbations, and enhance the overall quality of life for patients. Nanotechnology holds great promise to alleviate the burden of COPD. The main goal of this review is to present the full spectrum of therapeutics based on nanostructures for the treatment and management of COPD, including nanoparticles, polymeric nanoparticles, polymeric micelles, solid-lipid nanoparticles, liposomes, exosomes, nanoemulsions, nanosuspensions, and niosomes. Nanotechnology is just one of the many areas of research that may contribute to the development of more effective and personalized treatment modalities for COPD patients in the future. Future studies may be focused on enhancing the therapeutic effectiveness of nanocarriers by conducting extensive mechanistic investigations to translate current scientific knowledge for the effective management of COPD with little or no adverse effects.

Water quality and geochemical facie of high-altitude lakes in Tawang, Eastern Himalaya, India.

High-altitude lakes (HALs) can be used as a supplement or alternative source of water in areas where there is a water shortage. When these lakes are efficiently managed, they can supply more water resources to fulfil the increasing demand. Water quality assessment aids in the identification of adequate and safe drinking water sources. It minimizes threats to the public's health by making sure that lake water extraction fulfills safety and health regulations. Water quality and hydrogeochemical study was conducted on six HALs of the Tawang district of Arunachal Pradesh during the year 2022. The water quality index (WQI) values varied from excellent to poor (33.87 to 101.95). Lake 6 stands out with its exceptional water quality as it had the minimum average WQI value of 52.98. In contrast, Lake 5 had the lowest water quality among the studied lakes with the maximum average WQI value of 95.31. However, the water might not be safe to drink due to the elevated levels of fluoride in these lakes. It is crucial to address and minimize the high fluoride levels to ensure the safety and acceptability of the water for consumption. The Piper diagram showed that Ca2+ > Mg2+ > Na+ > K+ and HCO3- > Cl- > SO42-, respectively, were the primary cations and anions present in these lakes. The Gibbs diagram also demonstrated the effect of rock weathering and precipitation dominance on the water chemistry in the research area. These results provide insightful information about the water quality of HALs, which is essential information for concerned government departments and agencies to manage water issues more efficiently. Based on current research, the HALs in this region have a lot of potential to meet the growing demand for drinking water.

Trends in Anisakis simplex Global Research: A Bibliometric Analysis Study.

Anisakis simplex is a fish-borne zoonotic parasite. Although this parasite has been known since the 19th century, publications on anisakiasis have increased in recent years. Despite this, this subject has yet to be well studied by bibliometric analysis. This study was conducted to show the research points and trends of A. simplex. The Web of Science Core Collection (WoSCC) was mined for articles on A. simplex. The VOSviewer software visually evaluated countries, institutions, authors, references, and keywords in this field. A total of 1362 publications were included in this bibliometric analysis. The included publications were published between 1970 and 2022 from 79 countries, mainly from Spain (n=456, 33.48%). The most prolific year was 2020 (n=74). The research area that attracted the most publications was parasitology (n=452), while the most productive author in this area was Cuellar C (n=53). "Anisakis simplex", "Anisakis" and "anisakiasis" were the most used three keywords. The number of publications on anisakiasis has been increasing over time, suggesting that A. simplex is becoming an increasingly important disease worldwide. Research cooperation should be established between researchers from developed and developing countries to determine effective control strategies for anisakiasis.

Autoimmune diseases and adverse pregnancy outcomes: an umbrella review

BackgroundThere is a high prevalence of autoimmune conditions in women specially in the reproductive years; thus, the association with adverse pregnancy outcomes has been widely studied. However, few autoimmune conditions/adverse outcomes have been studied more than others, and this umbrella review aims to consolidate existing knowledge in this area with the aim to provide new knowledge and also identify gaps in this research area.MethodsMedline, Embase, and Cochrane databases were searched from inception to December 2023. Screening, data extraction, and quality appraisal (AMSTAR 2) were done by two independent reviewers. Data were synthesised narratively and quantitatively. Relative risks (RR)/odds ratio (OR) with 95% confidence intervals were reported.ResultsThirty-two reviews were included consisting of 709 primary studies. The review reported the association between 12 autoimmune conditions and 16 adverse pregnancy outcomes. Higher risk of miscarriage is reported in women with Sjögren’s syndrome RR 8.85 (95% CI 3.10–25.26) and systemic lupus erythematosus (SLE) OR 4.90 (3.10–7.69). Pre-eclampsia was reported higher in women with type 1 diabetes mellitus (T1DM) OR 4.19 (3.08–5.71) and SLE OR 3.20 (2.54–4.20). Women reported higher risk of diabetes during pregnancy with inflammatory bowel disease (IBD) OR 2.96 (1.47–5.98). There was an increased risk of intrauterine growth restriction in women with systemic sclerosis OR 3.20 (2.21–4.53) and coeliac disease OR 1.71 (1.36–2.14). Preterm birth was associated with T1DM OR 4.36 (3.72–5.12) and SLE OR 2.79 (2.07–3.77). Low birth weight babies were reported in women with women with SLE or systemic sclerosis OR 5.95 (4.54–7.80) and OR 3.80 (2.16–6.56), respectively. There was a higher risk of stillbirth in women with T1DM OR 3.97 (3.44–4.58), IBD OR 1.57 (1.03–2.38), and coeliac disease OR 1.57 (1.17–2.10). T1DM in women was associated with 32% lower odds of small for gestational age baby OR 0.68 (0.56–0.83).ConclusionsPregnant women with autoimmune conditions are at a greater risk of developing adverse pregnancy outcomes. Further research is required to develop better preconception to postnatal care for women with autoimmune conditions.

The Musculoskeletal Tumor Society Clinical Practice Guideline on the Management of Metastatic Humeral Disease.

Management of Metastatic Humeral Disease is based on a systematic review of published studies surrounding the management of metastatic disease, multiple myeloma, and lymphoma limited to the humerus. This guideline contains seven action statements to assist orthopaedic surgeons, orthopaedic oncologists, physicians, and any other qualified healthcare professionals involved in the surgical management of metastatic disease of the humerus. It is also intended to serve as an information resource for decision makers, researchers, and developers of clinical practice guidelines. In addition to providing pragmatic practice recommendations, this guideline also highlights gaps in the literature and informs areas for future research and quality measure development. This guideline has been endorsed by the American Academy of Orthopaedic Surgeons.

Facioscapulohumeral Muscular Dystrophy European Patient Survey: Assessing Patient Reported Disease Burden and Preferences in Clinical Trial Participation.

Facioscapulohumeral muscular dystrophy (FSHD) is a genetic disorder characterized by progressive muscle weakness leading to permanent disability. There are no curative treatments, however, there are several upcoming clinical trials testing new therapies in FSHD. This study aimed to explore the disease burden and patient preferences of people with FSHD to ensure that clinical trials can be designed to include outcome measures that are relevant and important to patients. A survey was developed with a steering committee clinicians and physiotherapists with relevant experience in the disease, patient representatives, a registry expert and industry consultants. Themes of the survey included; participant demographics, disease progression and impact on function, factors encouraging or discouraging clinical trial participation, and positive outcomes of a clinical trial. 1147 participants responded to the online survey, representing 26 countries across Europe and a range of disease severities. The study highlighted the key symptoms causing concern for FSHD patients - muscle weakness and mobility issues - reflecting what participants want targeted for future therapies. The need for clear information and communication throughout clinical trials was emphasised. Factors most encouraging trial participation included access to new investigational therapies, access to trial results and benefits for the FSHD community. Factors most discouraging trial participation included travel related issues and fear of side effects. The results from this study identify the patient reported burden of FSHD and should provide researchers and industry with areas of therapeutic research that would be meaningful to patients, as well as supporting the development of patient centric outcome measures in clinical trials.