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Experimental characterisation of small-diameter ropes for representing synthetic moorings in tank testing
Get PDFOffshore renewable energy (ORE) developers are increasingly choosing synthetic ropes in their mooring designs. In hydrodynamic tank testing, the scaled elasticity of these ropes is typically represented by springs, which are attractive for their simplicity but fail to imitate the non-linear, viscoelasticity of synthetic ropes. Employing small-diameter ropes may offer a more accurate portrayal of mooring dynamics for advanced design stages; however, these ropes are rarely produced for engineering purposes and their properties are poorly documented. Consequently, this study characterises a range of small-diameter ropes via tension testing and compares their properties with those of commercial mooring ropes at scales relevant to ORE tank testing (1:25, 1:50 and 1:100). Small-diameter rope candidates were found for commercial polyester ropes used in large (10–15 MW) floating wind moorings at both 1:25 and 1:50 scale, and for nylon ropes at 1:25 scale only. No suitable candidates were found at 1:100 scale or for the smaller commercial ropes used in wave energy. Notably, simply scaling the diameter of a rope of the same material does not reliably reproduce the scaled stiffness. This work offers a means to advance tank-scale mooring designs, thereby increasing the accuracy of experimental hydrodynamic data used for numerical model validation.Graphical abstrac
Art opening minds:An experimental study on the effects of temporal and perspectival complexity in film on open-mindedness
Get PDFAesthetic Cognitivism posits that artworks have the potential to enhance open-mindedness. However, this claim has not yet been explored empirically. Here, we present two experiments that investigate the extent to which two formal features of film – temporal and perspectival complexity - can ‘open our minds’. In Experiment 1, we manipulated the temporal complexity of film. Participants (Ntotal=100) watched a film (Memento) either in its original non-chronological order or the same film in a chronological order. In Experiment 2, we manipulated perspectival complexity in film. Participants (Ntotal=100) watched an excerpt from a film (Jackie Brown) that either included the perspectives of multiple characters on an event or a single character’s perspective on the same event. Film conditions in both experiments were further compared with a control condition in which participants did not watch a film (N=50). Participants’ open-mindedness was assessed in both experiments through four empirical indicators (creativity, imaginability, cognitive flexibility, openness to new evidence), and in Experiment 2 participants’ eye movements, heart rate and electrodermal activity were measured while watching the film. Results showed that watching films, regardless of their temporal or perspectival complexity, modulated only one facet of open-mindedness —cognitive flexibility— when compared to the no-film control condition, providing only limited support for the aesthetic cognitivist claim that artistic films can ‘open our minds’. Real-time measures in Experiment 2 revealed that pupil size and number of fixations were modulated by perspectival complexity: both were smaller when watching a film from multiple perspectives compared to a single perspective. Possible explanations for this difference are examined in relation to the viewers' cognitive processes involved in understanding and interpreting film content
Exploring the Limitations of Detecting Machine-Generated Text
Get PDFRecent improvements in the quality of the generations by large language models have spurred research into identifying machine-generated text. Such work often presents high-performing detectors. However, humans and machines can produce text in different styles and domains, yet the the performance impact of such on machine generated text detection systems remains unclear. In this paper, we audit the classification performance for detecting machine-generated text by evaluating on texts with varying writing styles. We find that classifiers are highly sensitive to stylistic changes and differences in text complexity, and in some cases degrade entirely to random classifiers. We further find that detection systems are particularly susceptible to misclassify easy-to-read texts while they have high performance for complex texts, leading to concerns about the reliability of detection systems. We recommend that future work attends to stylistic factors and reading difficulty levels of human-written and machine-generated text.</p
Calving from horizontal forces in a revised crevasse-depth framework
Get PDFCalving is a key process for the future of our ice sheets and oceans, but representing it in models remains challenging. Among numerous possible calving parameterisations, the crevasse-depth law remains attractive for its clear physical interpretation and its performance in models. In its classic form, however, it requires ad-hoc and arguably unphysical modifications to produce crevasses that are deep enough to result in calving. Here, we adopt a recent analytical approach accounting for the feedback between crevassing and the stress field and varying the density of water in basal crevasses, and show that it removes the need for such ad-hoc modifications. After accounting for ice tensile strength and basal friction, we show that the revised formulation predicts that full-thickness calving should occur at flotation when the calving front ice thickness is greater than around 400 m. It also predicts no calving for ice thinner than around 400 m, suggesting that calving at such glacier fronts is not driven purely by horizontal forces. We find good observational support for this analysis. We advance the revised crevasse-depth formulation as a step towards understanding differing calving styles and a better representation of calving in numerical models
Rational causal induction from events in time
Get PDFA longstanding focus in the causal learning literature has been on inferring causal relations from contingencies, where these abstract away from time by collating independent instances or by aggregating over regularly demarcated trials. In contrast, individual causal learners encounter events in their daily lives that occur in a continuous temporal flow with no such demarcation. Consequently, the process of learning causal relationships in naturalistic environments is comparatively less understood. In this paper, we lay out a rational framework that foregrounds the role of time in causal learning. We work within the Bayesian rational analysis tradition, starting by considering how causal relations induce dependence between events in continuous time and how this can be modeled by stochastic processes from the Poisson--Gamma distribution family. We derive the qualitative signatures of causal influence, and the general computations needed to infer structure from temporal patterns. We show that this rational account can parsimoniously explain the human preference for causal models that invoke shorter, more reliable and more predictable causal influences. Furthermore, we show this provides a unifying explanation for human judgments across a wide variety of tasks in reanalysis of seven experimental datasets. We anticipate the framework will help researchers better understand the many manifestations of continuous-time causal learning across human cognition and the tasks that probe it, from explicit causal structure induction settings to implicit associative or reinforcement learning settings
The reliability of replications:A study in computational reproductions
Get PDFThis study investigates researcher variability in computational reproduction, an activity for which it is least expected. Eighty-five independent teams attempted numerical replication of results from an original study of policy preferences and immigration. Reproduction teams were randomly grouped into a 'transparent group' receiving original study and code or 'opaque group' receiving only a method and results description and no code. The transparent group mostly verified original results (95.7% same sign and p-value cutoff), while the opaque group had less success (89.3%). Second-decimal place exact numerical reproductions were less common (76.9 and 48.1%). Qualitative investigation of the workflows revealed many causes of error, including mistakes and procedural variations. When curating mistakes, we still find that only the transparent group was reliably successful. Our findings imply a need for transparency, but also more. Institutional checks and less subjective difficulty for researchers 'doing reproduction' would help, implying a need for better training. We also urge increased awareness of complexity in the research process and in 'push button' replications.</p
Blood pressure variability:a review
Get PDFBlood pressure variability (BPV) predicts cardiovascular events independent of mean blood pressure. BPV is defined as short-term (24-h), medium or long- term (weeks, months or years). Standard deviation, coefficient of variation and variation independent of the mean have been used to quantify BPV. High BPV is associated with increasing age, diabetes, smoking and vascular disease and is a consequence of premature ageing of the vasculature. Long-term BPV has been incorporated into cardiovascular risk models (QRISK) and elevated BPV confers an increased risk of cardiovascular outcomes even in subjects with controlled blood pressure. Long-acting dihydropyridine calcium channel blockers and thiazide diuretics are the only drugs that reduce BPV and for the former explains their beneficial effects on cardiovascular outcomes. We believe that BPV should be incorporated into blood pressure management guidelines and based on current evidence, long-acting dihydropyridines should be preferred drugs in subjects with elevated BPV.</p
Sociodemographic, clinical, and genetic factors associated with self-reported antidepressant response outcomes in the UK Biobank
Get PDFBACKGROUND: In major depressive disorder (MDD), only ~35% achieve remission after first-line antidepressant therapy. Using UK Biobank data, we identify sociodemographic, clinical, and genetic predictors of antidepressant response through self-reported outcomes, aiming to inform personalized treatment strategies.METHODS: In UK Biobank Mental Health Questionnaire 2, participants with MDD reported whether specific antidepressants helped them. We tested whether retrospective lifetime response to four selective serotonin reuptake inhibitors (SSRIs) ( N = 19,516) - citalopram ( N = 8335), fluoxetine ( N = 8476), paroxetine ( N = 2297) and sertraline ( N = 5883) - was associated with sociodemographic (e.g. age, gender) and clinical factors (e.g. episode duration). Genetic analyses evaluated the association between CYP2C19 variation and self-reported response, while polygenic score (PGS) analysis assessed whether genetic predisposition to psychiatric disorders and antidepressant response predicted self-reported SSRI outcomes. RESULTS: 71%-77% of participants reported positive responses to SSRIs. Non-response was significantly associated with alcohol and illicit drug use (OR = 1.59, p = 2.23 × 10 -20), male gender (OR = 1.25, p = 8.29 × 10 -08), and lower-income (OR = 1.35, p = 4.22 × 10 -07). The worst episode lasting over 2 years (OR = 1.93, p = 3.87 × 10 -16) and no mood improvement from positive events (OR = 1.35, p = 2.37 × 10 -07) were also associated with non-response. CYP2C19 poor metabolizers had nominally higher non-response rates (OR = 1.31, p = 1.77 × 10 -02). Higher PGS for depression (OR = 1.08, p = 3.37 × 10 -05) predicted negative SSRI outcomes after multiple testing corrections. CONCLUSIONS: Self-reported antidepressant response in the UK Biobank is influenced by sociodemographic, clinical, and genetic factors, mirroring clinical response measures. While positive outcomes are more frequent than remission reported in clinical trials, these self-reports replicate known treatment associations, suggesting they capture meaningful aspects of antidepressant effectiveness from the patient's perspective.</p
Endometriosis: A Review
Get PDFImportance: Endometriosis is a chronic, estrogen-dependent, inflammatory disease defined by endometrial-like tissue (lesions) outside the uterine lining. It affects up to 10% of women worldwide, and 9 million women in the US, during reproductive years. Observations: Endometriosis has varying clinical presentations; however, 90% of people with endometriosis report pelvic pain, including dysmenorrhea, nonmenstrual pelvic pain, and dyspareunia, and 26% report infertility. Risk factors for endometriosis include younger age at menarche, shorter menstrual cycle length, lower body mass index, nulliparity, and congenital obstructive müllerian anomalies such as obstructed hemivagina. Although definitive diagnosis requires surgical visualization of lesions, a suspected clinical diagnosis can be made based on symptoms, supported by physical examination findings and imaging with transvaginal ultrasound and/or pelvic magnetic resonance imaging; normal physical examination and imaging do not exclude the diagnosis. The diagnosis is often delayed, averaging 5 to 12 years after onset of symptoms, with most women consulting 3 or more clinicians prior to diagnosis. Hormonal medications, such as combined oral contraceptives and progestin-only options, are first-line treatment and should be offered to symptomatic premenopausal women who do not currently desire pregnancy. In a network meta-analysis (n = 1680, 15 clinical trials), hormonal treatments including combined oral contraceptives, progestins, and gonadotropin-releasing hormone (GnRH) agonists led to clinically significant pain reduction compared with placebo, with mean differences ranging between 13.15 and 17.6 points (0-100 visual analog scale) with little difference in effectiveness among options. However, 11% to 19% of individuals with endometriosis have no pain reduction with hormonal medications and 25% to 34% experience recurrent pelvic pain within 12 months of discontinuing hormonal treatment. Surgical removal of lesions, usually with laparoscopy, should be considered if first-line hormonal therapies are ineffective or contraindicated. Second-line hormone therapies include GnRH agonists and antagonists, and third-line treatments include aromatase inhibitors. Hysterectomy with surgical removal of lesions may be considered when initial treatments are ineffective. However, approximately 25% of patients who undergo hysterectomy for endometriosis experience recurrent pelvic pain and 10% undergo additional surgery, such as lysis of adhesions, to treat pain. Conclusions and Relevance: Endometriosis is a common cause of pelvic pain affecting approximately 10% of reproductive-age women. Hormonal suppression with combined estrogen-progestin contraceptives or progestins is first-line treatment for women who are not seeking immediate pregnancy. Surgical removal of endometriosis lesions may be performed if hormonal therapies are ineffective or contraindicated, and hysterectomy may be considered if medical treatments and surgical removal of lesions do not relieve symptoms.</p
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