Miracle-dz/UniFAR-FTUs huggingface dataset:
Using the AR-V7 biomarker to determine treatment in metastatic castrate resistant prostate cancer, a feasibility randomised control trial, conclusions from the VARIANT trial

Background Prostate cancer is the most commonly diagnosed malignancy in the UK. Castrate resistant prostate cancer (CRPC) can be difficult to manage with response to next generation hormonal treatment variable. AR-V7 is a protein biomarker that can be used to predict response to treatment and potentially better inform management in these patients. Our aim was to establish the feasibility of conducting a definitive randomised controlled trial comparing the clinical utility of AR-V7 biomarker assay in personalising treatments for patients with metastatic CRPC within the United Kingdom (UK) National Health Service (NHS). Due to a number of issues the trial was not completed successfully, we aim to discuss and share lessons learned herein. Methods We conducted a randomised, open, feasibility trial, which aimed to recruit 70 adult men with metastatic CRPC within three secondary care NHS trusts in the UK to be run over an 18-month period. Participants were randomised to personalised treatment based on AR-V7 status (intervention) or standard care (control). The primary outcome was feasibility, which included: recruitment rate, retention and compliance. Additionally, a baseline prevalence of AR-V7 expression was to be estimated. Results Fourteen participants were screened and 12 randomised with six into each arm over a nine-month period. Reliability issues with the AR-V7 assay meant prevalence was not estimated. Due to limited recruitment the study did not complete to target. Conclusions Whilst the trial did not complete to target, we have ascertained that men with advanced cancer are willing to take part in trials utilising biomarker guided treatment. A number of issues were identified that serve as important learning points in future clinical trials.
Non-conservation of Carter in black hole spacetimes

Freely falling point particles in the vicinity of Kerr black holes are subject to a conservation law, that of their Carter constant. We consider the conjecture that this conservation law is a special case of a more general conservation law, valid for arbitrary processes obeying local energy momentum conservation. Under some fairly general assumptions we prove that the conjecture is false: there is no conservation law for conserved stress–energy tensors on the Kerr background that reduces to conservation of Carter for a single point particle.
A Deep Learning Approach to Online Social Network Account Compromisation

The major threat to online social network (OSN) users is account compromisation. Spammers now spread malicious messages by exploiting the trust relationship established between account owners and their friends. The challenge in detecting a compromised account by service providers is validating the trusted relationship established between the account owners, their friends, and the spammers. Another challenge is the increase in required human interaction with feature selection. Research available on supervised learning has limitations with feature selection and accounts that cannot be profiled, like application programming interface (API). Therefore, this article discusses the various behaviors of OSN users and the current approaches in detecting a compromised OSN account, emphasizing its limitations and challenges. We propose a deep learning approach that addresses and resolve the constraints faced by previous schemes. We detailed our proposed optimized nonsymmetric deep autoencoder (OPT_NSDAE) for unsupervised feature learning, which reduces the required human interaction levels in the selection and extraction of features. We evaluated our proposed classifier using three different social network datasets, Facebook, Google+, and Twitter, in addition to the NSL-KDD and KDDCUP’99 datasets, in a graphical-user-interface-enabled Weka application. The experimental results show that our proposed approach outperformed most of the traditional schemes in OSN compromised account detection.
Establishment and Extension of a Fast Descriptor for Point Cloud Registration

Point cloud registration (PCR) is a vital problem in remote sensing and computer vision, which has various important applications, such as 3D reconstruction, object recognition, and simultaneous localization and mapping (SLAM). Although scholars have investigated a variety of methods for PCR, the applications have been limited by low accuracy, high memory footprint, and slow speed, especially for dealing with a large number of point cloud data. To solve these problems, a novel local descriptor is proposed for efficient PCR. We formed a comprehensive description of local geometries with their statistical properties on a normal angle, dot product of query point normal and vector from the point to its neighborhood point, the distance between the query point and its neighborhood point, and curvature variation. Sub-features in descriptors were low-dimensional and computationally efficient. Moreover, we applied the optimized sample consensus (OSAC) algorithm to iteratively estimate the optimum transformation from point correspondences. OSAC is robust and practical for matching highly self-similar features. Experiments and comparisons with the commonly used descriptor were conducted on several synthetic datasets and our real scanned bridge data. The result of the simulation experiments showed that the rotation angle error was below 0.025° and the translation error was below 0.0035 m. The real dataset was terrestrial laser scanning (TLS) data of Sujiaba Bridge in Chongqing, China. The results showed the proposed descriptor successfully registered the practical TLS data with the smallest errors. The experiments demonstrate that the proposed method is fast with high alignment accuracy and achieves a better performance than previous commonly used methods.
Residential Area Socioeconomic Deprivation is Associated with Physical Dependency and Polypharmacy in Community-Dwelling Older Adults: An Analysis of Health Administrative Data in Ireland

Introduction Socioeconomic disadvantage is associated with multiple adverse health outcomes in ageing. Whether this negative impact persists in populations of more advanced age and dependency is less clear. We aimed to determine the association between residential area deprivation and pre-specified health characteristics among community-dwelling dependent older adults. Methods We conducted a cross-sectional analysis of data from 1591 community-dwelling adults aged 65 years and older of mean age 83.9 ± 7.1 years and in receipt of state home support in Ireland. The HP Pobal Deprivation Index was used to categorize residential areas by socioeconomic deprivation. Health variables analysed included physical dependency (Barthel Index), polypharmacy (≥5 medications), previous acute hospital admission, cognitive impairment, and mental health diagnoses. Associations between residential area deprivation and prespecified health outcomes were explored in multivariable logistic regression analysis. Results In socioeconomically disadvantaged areas, high physical dependency was twice that observed in affluent areas (16.2% vs 6.9%, p = 0.009). Similarly, acute hospitalization, as the trigger for increased dependency, was more common in deprived settings (41.6% v 29.1%, p < 0.001). Polypharmacy was common in this population (67.6%), but significantly higher in deprived vs affluent settings (74.7% v 64.5%, p = 0.030). The findings persisted in multivariable analyses when adjusted for age and gender. While all participants were accessing home support, those in deprived areas were on average 6.5 years younger than in affluent areas. Associations between residential deprivation and mental health conditions or cognitive impairment, however, were not observed in this study. Conclusion Community-dwelling older adults living in socioeconomically disadvantaged areas experienced greater polypharmacy, high physical dependency, hospitalization-associated dependency, and a 6.5-year earlier need for state home support than in affluent settings. The findings suggest that health inequality persists in populations of more advanced age and dependency and highlight a need for further research as well as community-based health and social care initiatives.
Dynamic Models of Learning and Education Measurement

Pre-post testing is a commonly used method in physics education community for evaluating students' achievement and or the effectiveness of teaching through a specific period of instruction. A popular method to analyze pre-post testing results is the normalized gain first brought to the physics education community in wide use by R.R. Hake. This paper presents a measurement based probabilistic model of the dynamic process of learning that explains the experimentally observed features of the normalized gain. In Hake's study with thousands of students' pre-post testing results, he observed that on average 48 courses employing "interactive engagement" types of instruction achieved average normalized gains about two standard deviations greater than did 14 courses subjected to traditional instruction. For all courses the average normalized gains had a very low correlation +0.02 with average pretest scores. This feature of the normalized gain has allowed researchers to investigate the effectiveness of instruction using data collected from classes with widely different average pretest scores. However, the question of why the average normalized gain has this feature and to what extent this feature is generally present is not well understood. In addition, there have been debates as to what the normalized gain actually measures, and concerns that it lacks a probability framework that undergirds psychometric methods such as Item Response Theory (IRT). The present model leads to an explanation of the observed features of the normalized gain, connects to other models such as IRT, and shows that the normalized gain does have a probability framework but one different from that emphasized by IRT.
Electric Propulsion for Low Earth Orbit Communication Satellites

Electric propulsion was evaluated for orbit insertion, satellite positioning and de-orbit applications on big (hundreds of kilograms) and little (tens of kilograms) low earth orbit communication satellite constellations. A simple, constant circumferential thrusting method was used. This technique eliminates the complex guidance and control required when shading of the solar arrays must be considered. Power for propulsion was assumed to come from the existing payload power. Since the low masses of these satellites enable multiple spacecraft per launch, the ability to add spacecraft to a given launch was used as a figure of merit. When compared to chemical propulsion ammonia resistojets, ion, Hall, and pulsed plasma thrusters allowed an additional spacecraft per launch Typical orbit insertion and de-orbit times were found to range from a few days to a few months.
A Novel C@Fe@Cu Nanocomposite Loaded with Doxorubicin Tailored for the Treatment of Hepatocellular Carcinoma

High mortality and morbidity rates are related to hepatocellular carcinoma (HCC), which is the most prevalent type of liver cancer. A new vision for cancer treatment and cancer cell targeting has emerged with the application of nanotechnology, which reduces the systemic toxicity and adverse effects of chemotherapy medications while increasing their effectiveness. It was the goal of the proposed work to create and investigate an anticancer C@Fe@Cu nanocomposite (NC) loaded with Doxorubicin (DOX) for the treatment of HCC. Scanning and transmission electron microscopes (SEM and TEM) were used to examine the morphology of the produced NC. The formulation variables (DOX content, C@Fe@Cu NC weight, and stirring speed) were analyzed and optimized using Box-Behnken Design (BBD) and Response Surface Methodology (RSM). Additionally, X-ray diffraction patterns (XRD) and Fourier Transform Infrared (FTIR) were investigated. Doxorubicin and DOX- loaded C@Fe@Cu NC (DOX-C@Fe@Cu NC) were also assessed against HEPG2 cells for anticancer efficacy (Hepatic cancer cell line). The results revealed the formation of C@Fe@Cu NC with a mean size of 7.8 nm. A D-R model with a mean size of 24.1 nm best fits the adsorption behavior of DOX onto the C@Fe@Cu NC surface. DOX-C@Fe@Cu NC has also been demonstrated to have a considerably lower IC50 and higher cytotoxicity than DOX alone in an in vitro investigation. Therefore, DOX-C@Fe@Cu NC is a promising DOX delivery vehicle for the full recovery of HCC.
The automatic control of numerical integration

This paper reviews the recent advances in developing automatic control algorithms for the numerical integration of ordinary di(cid:11)erential equations (ODEs) and di(cid:11)erential-algebraic equations (DAEs). By varying the stepsize, the error committed in a single step of the discretization method can be a(cid:11)ected. Modern time-stepping methods provide an estimate of this error, and by comparing the estimate to a speci(cid:12)ed accuracy requirement a control algorithm selects the next stepsize. To construct e(cid:14)cient controllers it is necessary to analyze the dynamic behaviour of the discretization method together with the controller. Based on feedback control theory, this systematic approach has replaced earlier heuristics and resulted in a more consistent and robust performance. Other quantities affected by the stepsize are convergence rates of (cid:12)xed-point and Newton iterations, and we therefore also review new techniques for the coordination of nonlinear equation solvers with the primary stepsize controller. Taken together, the recent development provides principles and guidelines for constructing ODE/DAE software where heuristics and tuning parameters have largely been eliminated.
Spot activity on HD 89546 (FG UMa) from long‐term photometry

We present the analysis of 20 years of time-series BV photometry of the SB1 RS CVn binary HD 89546. The system's yearly mean V brightness, the B – V color index, the photometric period, and the light curve amplitude all show clear cyclic variability with an ≈9-year time scale. We also find some evidence for brightness variability on a time scale longer than the 20-year time span of our observations, perhaps indicating a longer cycle analogous to the solar Gleissberg cycle. We estimate the unspotted V magnitude of HD 89546 to be 7.m154, which is ≈0.m2 brighter than the observed maximum brightness. Spot modelling of the system shows that spot temperature variations affect the observed B – V color as well as the V brightness. Two active longitudes are observed, centered around 180° and 360° longitude on the G9 III primary, each covering a longitude range of 120°. Furthermore, two inactive longitude zones are seen spanning only 60° between the two active longitudes. The longitudinal distribution of the spots exhibits no strong cyclic variability but does show rapid jumps of 120° that look like the flip-flop phenomenon. We estimate the differential rotation coefficient of the star as k = 0.086 by considering the range of observed photometric period variations and assumed latitudinal spot variations over 45° (© 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)
Physico-chemical Characterization and Estimation of Antimicrobial Activity of Modified Aspirin in the form of Nano-organometallic Compounds

Aspirin is one of the most commonly used drugs. It is necessary to find and develop analgesic anti- inflammatory drugs that are safe against their adverse effects. From this standpoint, new nano- organometallic Cu(II), Mn(II), Ni(II), Cd(II) and Zn(II) compounds of modified aspirin were prepared and characterized using elemental and spectroscopic techniques such as infrared and ultraviolet, proton nuclear magnetic resonance, mass spectroscopy, electron spin resonance and electron microscope, as well as magnetism, conductivity and thermal analysis. Thermal and spectral results showed the octahedral geometry and stability of these compounds up to 45oC. The data indicated that, using low concentration against microbes, aspirin and ligand no effect was observed, however, the complexes showed moderate to high effect, The order for Gram positive is Cd(II) complex (10)> Cd(II) complex (11)> ampicillin> Zn(II) complex (8)> Cu(II) complex (4)> Cu(II) complex (6)= Ni(II) complex (12)> Cu(II) complex (2) = Cu(II) complex (3)> ligand (1)> aspirin> Mn(II)complex(14) and for Gram negative is ampicillin> Cd(II) complex (10)> Cd(II) complex (11)> Cu(II) complex (2) > Cu(II) complex (6)> Cu(II) complex (3)> Cu(II) complex (4) > Zn(II) complex (8)> aspirin> Ni(II) complex (12) > ligand (1)> Mn(II) complex (14) and for Aspergillus flavus is Cd(II) complex (10)>amphotericin B> Cd(II) complex (11)> ligand (1)= aspirin= Cu(II) complex (2)= Cu(II) complex (3)= Cu(II) complex (4)= Cu(II) complex (6) = Zn(II) complex (8)= Ni(II) complex (12)= Mn(II) complex (14) and for Candida albicans is Cd(II) complex (10)> Cd(II) complex (11)> amphotericin B > Ni(II) complex (12)> Cu(II) complex (3)= Cu(II) complex (6)> Cu(II) complex (2)= Cu(II) complex (4)> ligand(1) = aspirin= Zn(II) complex (8)= Mn(II) complex (14). The order of the catalytic effect of the tested complexes on decomposition of H2O2 was Mn(II) complex (14)> Ni(II) complex (12) > Cu(II) complex (4) > Cu(II) complex (6)> Cu(II) complex (2) respectively.
Occluded Pedestrian-Attribute Recognition for Video Sensors Using Group Sparsity

Pedestrians are often obstructed by other objects or people in real-world vision sensors. These obstacles make pedestrian-attribute recognition (PAR) difficult; hence, occlusion processing for visual sensing is a key issue in PAR. To address this problem, we first formulate the identification of non-occluded frames as temporal attention based on the sparsity of a crowded video. In other words, a model for PAR is guided to prevent paying attention to the occluded frame. However, we deduced that this approach cannot include a correlation between attributes when occlusion occurs. For example, “boots” and “shoe color” cannot be recognized simultaneously when the foot is invisible. To address the uncorrelated attention issue, we propose a novel temporal-attention module based on group sparsity. Group sparsity is applied across attention weights in correlated attributes. Accordingly, physically-adjacent pedestrian attributes are grouped, and the attention weights of a group are forced to focus on the same frames. Experimental results indicate that the proposed method achieved 1.18% and 6.21% higher F1-scores than the advanced baseline method on the occlusion samples in DukeMTMC-VideoReID and MARS video-based PAR datasets, respectively.
Active versus passive: evaluating the effectiveness of inoculation techniques in relation to misinformation about climate change

ABSTRACT Objective The current study evaluated whether an active inoculation (interactive skill development) or a passive inoculation message (provision of information) were effective tools for conferring resistance to misinformation about climate science in the context of extreme weather events. Method Participants were randomly assigned to one of the three conditions: a control condition (no training); a passive inoculation condition; or an active inoculation condition. Participants completed demographic questions followed by training or no training and then evaluated a misinformation and factual article for reliability and persuasiveness. Results Participants in the active inoculation condition rated the reliability and persuasiveness of the misinformation article and the reliability of the factual article lower than participants in the control condition. Participants in the passive inoculation training did not rate the reliability and persuasiveness of a misinformation and factual article significantly differently to those in the control condition. When factors such as ideological worldview and climate change beliefs were controlled for however, the inoculation interventions had no significant effect on ratings of reliability and persuasiveness for a misinformation or factual article. Conclusion Inoculation seems to be a promising method of preventing the acceptance of misinformation on climate science. However, this analysis highlights that more investigation is required in order to determine the most effective inoculation training design. KEY POINTS What is already known about this topic: (1) Misinformation about the occurrence of anthropogenic climate change has led to a lack of support for policies which address climate change. (2) Inoculation theory and its application have been extensively studied and are considered an effective method for conferring resistance to persuasion. (3) There is some conflict within the literature as to whether an active or passive inoculation is the most effective method for conferring resistance. What this topic adds: (1) Further evidence for the effectiveness of inoculation interventions in the recent application to climate science misinformation. (2) Active inoculation was more effective than passive inoculation. (3) Need for further evaluation into the mechanisms which facilitate resistance to persuasion and therefore evoke attitude/behaviour change.
A comprehensive insight on the main physiological biochemical and related genes expression changes during the development of superficial scald in “Yali” pear

Superficial scald is a serious physiological disorder in “Yali” pear (Pyrus bretschneideri Rehd. cv. Yali) after long-term cold storage. Changes in superficial scald, ethylene production, α-farnesene and phenylpropane metabolism with associated gene expression in “Yali” pear treated with and without (control) 1-methylcyclopropene (1-MCP) were investigated. Compared with the control group (without 1-MCP), 1-MCP (1.0 μl L–1) significantly lowered the superficial scald index after 180 days of cold storage. During cold storage and shelf life, the contents of α-farnesene, conjugated trienols, chlorogenic acid, and epicatechin in the peel were reduced, while quercetin was enhanced in 1-MCP-treated fruit, and the expression of genes associated with ethylene synthesis (ACS1, ACO1), receptors (ETR2, ERS1) and signal transduction (ERF1), α-farnesene metabolism (AFS1, HMGR2, GST7), phenolic biosynthesis (PAL1, C4H1, C4H2, HCT3, 4CL2, C3H), and oxidases (PPO1, PPO5, and LAC7) were significantly downregulated by 1-MCP. These results suggested that the onset and development of superficial scald was closely related to the ethylene receptor, conjugated trienols, chlorogenic acid and epicatechin and related genes expression in “Yali” pear.