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Dancing like Ancestors: An ethnographic investigation of trance practices and principles in contemporary UK psychedelic trance dance culture
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This research investigated the claim that contemporary UK psychedelic trance culture (psyculture) is re-enacting ancestral trance practices by investigating psyculture practices and principles through an ethnography of a living culture particularly at outside gatherings.
Background
Psychedelic trance music culture is a growing global culture that aligns itself with complex belief systems, customs, and practices that are associated with re-connecting with ancestral practices long forgotten but still believed in, the re-enactment of rituals and ceremonies that promote trance through dance, music, sound, and environment to initiate altered states of consciousness potentially leading to personal and group transformation and healing benefits. Psyculture demonstrates many small-scale societal principles and practices in terms of contribution, community and participation that brings benefits to members and the community as a whole.
Current research
Current research indicates that there are similarities between past and contemporary trance dance and psyculture dance practices and principles. The literature reviews psyculture practices in terms of trance, dance, participation, contribution, community, participation, connectivity, the environment and nature, material culture, and music. There are gaps in the study of contemporary trance cultures in the UK, particularly psyculture, with few local, country specific investigations. The aim was to provide deeper insight in the practices and principles of trance dance principles and practices in UK psyculture.
Methodology
The methodological approach taken was a relativist ontology with an emic, qualitative, interpretive epistemology because of a desire to gain an in-depth understanding of participant’s interpretations of psyculture. The methods were an online survey and interviews to ascertain the opinions of psyculture participants, and to find what ethnographic fieldwork reveals with use of data thematic analysis, ethnographic observation at specific gatherings, and an autoethnographic account.
Findings
Findings have shown potential similarities of practices and principles of trance dance in many societies centred around dance, sound, music, embodiment and sensory experiences, landscape and journeys, and the benefits of participation and contribution from a dancer’s perspective. In fact, community is the central cohering around which the desire to return to dance for long period in natural landscape pivots. The findings demonstrate the importance of belonging, community, contribution, and participation that are integrated outside in the liminal, temporary spaces.
Conclusion
In conclusion, dance, trance, beliefs, spiritualities, purposes, the centrality of sound and music, the importance of place, and the benefits of participation as key factors in participants’ involvement. What is revealing in terms of an original contribution is the dominance of dance and dancing for prolonged periods in groups preferably outside as the determining factors for participants to return to gatherings.
Contribution
The original contribution comes from an in-depth study of psyculture as a living co-presence sociality providing a comprehensive understanding of the established practices and principles which may help establish a framework for future studies in different EDM genre and cultures and their unique practices and principles. The unique findings show how psyculture survives in an often hostile environment as a small-scale EDM based community that shapes participants’ lives and identities as well as being the force that holds the culture together sustaining its survival with a rich depth in practices and principles beyond shallow hedonism. Foregrounded is the importance of returning to the gatherings to dance together with rich communality, contribution, and participation evident
Wealth Management and FinTech Innovation in UK & India
Get PDFThe wealth management sector has evolved significantly, driven by the rise of FinTech innovations that are reshaping traditional financial services. FinTech has introduced affordable, accessible solutions like robo-advisors, AI-powered analytics, and micro-investing platforms, enabling individuals with modest assets to participate. These technologies enhance personalization, efficiency, and financial inclusion by offering low-cost, scalable services. Additionally, WealthTech innovations such as blockchain, social trading platforms, and digital payment systems are broadening market access, empowering a new generation of investors.
The UK wealth management sector is experiencing rapid transformation, driven by technological innovation, shifting client demographics, and increased competition from FinTech firms. FinTech is reshaping the wealth management landscape, with robo-advisors, AI, and blockchain enhancing service efficiency and accessibility. The sector is also consolidating through mergers and acquisitions to scale operations and reduce costs. Despite economic uncertainties post-Brexit and inflation, the future of UK wealth management lies in continuous innovation and regulatory adaptation. The Indian wealth management sector is experiencing significant growth, driven by rising affluence and technological advancements. FinTech companies are playing a transformative role, democratizing access to wealth management through platforms. Key trends include the rise of WealthTech solutions like AI, robo-advisors, and automated services that make investment more accessible. FinTech has also spurred financial inclusion, expanding services to previously untapped rural, semi-urban areas.
The integration of FinTech in wealth management faces several challenges, despite its promising growth. Key issues include regulatory compliance, data privacy, cybersecurity threats, and diverse customer expectations. Wealth management firms must invest in robust cybersecurity to safeguard client data and maintain trust. Market competition intensifies as new FinTech entrants push traditional firms to innovate. However, barriers like low financial literacy and accessibility hinder the adoption of digital wealth management solutions
The Handbook of Antique Photographs: A Guide to Dating Nineteenth Century Portraits
Get PDFThe Handbook of Antique Photographs is a short publication created by UCLan Associate Lecturer Brandon Reece Taylorian as part of his Dating Antique Photographs Project funded by UCLan's Institute of Creativity, Communities and Culture. The Handbook begins with a brief history of the origins of portrait photography followed by Taylorian's introduction of a step-by-step method for deconstructing and dating antique photographs ('antique' is defined in the Handbook as referring to any photograph that is more than 100 hundred years old). The Handbook then goes on to provide details on each type of nineteenth-century photograph from the earliest type daguerreotypes to ambrotypes, tintypes, cartes de visite, cabinet cards and cartes postale with examples given for each. Each of the sections includes details on fashion and style of the period, the composition and settings for photographs and the items portrait subjects commonly held. The Handbook concludes by outlining the useful role that photographer logos and royal warrants can play in helping family historians to estimate when their nineteenth-century photographs were taken
OC51 Research priorities for patients and professionals in Chronic pain (CP) associated with Inflammatory bowel disease (IBD) – a mixed methods study
No full textIntroduction In adult IBD cohorts, CP prevalence is 48% in outpatients and 38% in hospital-based cohorts with significant impact on wellbeing, psychological health, social functioning, and higher health care utilisation and costs.1–3 Recent cochrane reviews identified limited evidence for specific treatments with a need for more studies. We set out to reach a patient and professional co-produced consensus on specific priorities, key outcomes and propose a model for understanding these findings.
Methods Initially an online delphi survey was sent out to patients and medical professionals invited from Crohn’s and Colitis UK who hold a large list of patients willing to perform research. Priorities for treatments, outcome measures and reasoning were the focus, with results collated and presented for further comment, as shown in table 1.
In the second phase, four online workshops were organised over a 6-week period by 2 facilitators, each lasting approximately 1 hour, to better understand the rationales for the research priorities chosen and triangulate the findings of phase one.
Results The survey was filled in by 128 participants (73 patients, 3 carers and 52 professionals). Diet was the top priority for both groups (although for patients equal numbers also ranked cannabis and acupuncture as their top choice). For both groups psychosocial therapies were the next priority.
Workshops were attended by 13 patients and 5 professionals. Transcripts were combined with the free text data from the delphi surveys and analysed through a three-phase qualitative technique. We identified 205 themes at the open phase, with 16 macro themes at the axial phase. These were synthetised into a novel model, displayed in figure 1, that highlights how patients and professionals made research prioritisation choices in this context.
Conclusion Low FODMAP diet was the highest rated research priority for both professionals and patients in our survey. For patients the same score was obtained for cannabidiol and acupuncture. This was followed by psychosocial therapies. We would recommend funding bodies and researchers to consider this, as well as the findings of our model, when making choices for future research
Risk rates and profiles at intake in child and adolescent mental health services: A cohort and latent class analyses of 21,688 young people in South London
Get PDFBackground: Children and young people (CYP) seen by child and adolescent mental health services (CAMHS) often experience safeguarding issues. Yet little is known about the volume and nature of these risks, including how different adversities or risks relate to one another. This exploratory study aims to bridge this gap, examining rates at entry to services and profiles of risk using a latent class analysis. Methods: Data were extracted for CYP who received at least one risk assessment at CAMHs in South London between January 2007 and December 2017. In total, there were 21,688 risk assessments. Latent class analysis was used to identify profiles of risk from the risk assessments. Results: Concerns about parent mental health (n = 5274; 24%), emotional abuse (n = 4487; 21%), violence towards others (n = 4210; 19%), destructive behaviour (n = 4005; 18%), and not attending school (n = 3762; 17%) were the most commonly identified risks. Six distinct profiles of risk were identified from the latent class analyses: (1) maltreatment and externalising behaviours, (2) maltreatment but low risk to self and others, (3) antisocial behaviour, (4) inadequate caregiver supervision and risk to self and others, (5) risk to self but not others, and (6) mental health needs but low risk. Conclusions: These findings provide fresh insights into adverse experiences and risks identified by CAMHS. For professionals, the profiles identified in this study might provide insights into profiles of identified risks, in contrast to traditional cumulative approaches to risk. For researchers, these profiles may be fertile ground for hypothesis‐driven work on the association between adversity and later outcomes
Introduction: Navigating Contemporary Sex Work; Navigating (In)Access to Justice and Rights
No full textIntelligent airborne monitoring of man-made marine objects using Machine Learning techniques - Part I
Get PDFThe objective of this study is to create a new platform for the automated detection of irregularly shaped man-made marine objects (ISMMMOs) in large datasets derived from marine aerial survey imagery. We present here the first part of the paper. The concluding part of the paper will be published in the next issue. The marine economy has historically been highly diversified and prolific due to the fact that the Earth's oceans comprise two-thirds of its total surface area. As technology advances, leading enterprises and ecological organisations are building and mobilising new devices supported by cutting-edge marine mechatronics solutions to explore and harness this challenging environment. Automated tracking of these types of industries and the marine life around them can help us figure out what's causing the current changes in species numbers, predict what could happen in the future, and create the right policies to help reduce the environmental impact and make the planet more sustainable. The objective of this study is to create a new platform for the automated detection of irregularly shaped man-made marine objects (ISMMMOs) in large datasets derived from marine aerial survey imagery. In this context, a novel nonparametric methodology, which harbours several hybrid statistical Machine Learning (ML) methods, was developed to automatically segment ISMMMOs on the sea surface in large surveys. This methodology was validated on a wide range of marine domains, providing robust empirical proof of concept. This approach enables the detection of ISMMMOs automatically, without any prior training, with accuracy (ACC), Matthews correlation coefficient (MCC), negative predictive value (NPV), positive predictive value (PPV), specificity (Sp) and sensitivity(Se) over 0.95. The outlined methodology can be utilised for a variety of purposes, but it's especially useful for researchers and policymakers who want to keep an eye on how the maritime industry is deploying and make sure the right policies are in place to meet regulatory and legal requirements to promote maritime tech innovation and shape what the future looks like for the marine ecosystem. For the first time in the literature, a method, the so-called ISMMMOD, has been developed to automate the detection of all types of ISMMMOs by statistical ML techniques that require no prior training, which will pioneer the monitoring of human footprint in the marine ecosystem
Financial Intelligence Forecasting Model on Regression Analysis and Support Vector Machine
No full textThe world today is gradually moving into the era of smart economy, and the application of artificial intelligence is bound to trigger huge changes in all walks of life. In the context of the current smart economy, how to use machine learning technology in artificial intelligence to improve the accuracy of enterprise financial analysis has become a hot direction for current research. To address the above issues, this paper proposes a financial intelligence forecasting model based on machine learning models. By establishing a mathematical model to analyse the annual financial statement data published by listed companies, and to determine whether there is fraud according to the model forecasting results. Firstly, from a large number of financial indicators, 60 financial indicators with high frequency of use were selected as variables of the model by using frequency statistics method. Secondly, as financial statement fraud is a typical classification problem, Twin Support Vector Machine (TSVM), a machine learning technique, was chosen and combined with K-Nearest Neighbor (KNN) in order to further improve the forecasting speed and accuracy. In addition, as the data samples for financial statement fraud forecasting are typically unbalanced data, the data are oversampled, undersampled and downsampled in this paper. Finally, for the judgement of model effectiveness, five indicators are selected for analysis in this paper. The experimental results show that compared with other single models, the KNN-TSVM model under the undersampling method has the highest Recall and can effectively identify the fraud samples
INVESTIGATING CUDC-101 EFFECT AND MECHANISM OF ACTION AGAINST GLIOBLASTOMA IN VITRO
No full textAIMS Glioblastoma (GB) has complex pathophysiology, difficult treatment and resultant poor prognosis. Its median survival rate is approximately 15 months. The aggressive nature of GB results in rapid disease progression in 60-70% patients often within 12 weeks. Limited treatment options include maximal safe surgical resection, followed by radiotherapy and temozolomide (TMZ). The blood brain barrier restricts chemotherapeutic entry and increases dosage leading to increased side effects and decreased treatment tolerance. Furthermore, significant disease heterogeneity means reoccurrence is expected in most cases, for which there are no standard treatment routes. This coupled with inefficient treatment with temozolomide (TMZ) due to the blood brain barrier, highlights the requirement for novel treatments. METHOD Histone deacetylases (HDAC) and endothelial growth factor receptor (EGFR) are mutated and upregulated in GB allowing tumour infiltration and proliferation. CUDC-101 is known to target both HDAC and EGFR in other cancers making it a promising therapeutic to trial in GB. Cell viability of U251, T98G and U87MG human cells was measured post-CUDC-101 administration at 24, 48 and 72hrs. SVGp19 embryonic non-cancerous human glial cells were used as a control to establish CUDC-101 preliminary specificity. Targeting another major hallmark of GB, wound healing assays were performed to assess CUDC-101 capacity to inhibit migration. In addition to this, long-term cellular resistance was investigated through clonogenic assays. Western blotting was then used to identify non-/treated expression levels of activated EGFR and acetylated histone H3. Expression levels in non/-treated cells were then visualised with fluorescent microscopy. In addition, flow cytometry was utilised to observe cell cycle changes. RESULTS Overall, results indicate CUDC-101 has a dose-dependent effect on cell viability (long-term and short-term) and migration. Additionally, fluorescent images show treatment does increase histone acetylation and decrease total EGFR. CONCLUSION Future work will solidify these datasets and show changes in activated EGFR and acetylated histone H3 using western blotting