Miracle-dz/UniFAR-FTUs huggingface dataset:
People making deontological judgments in the Trapdoor dilemma are perceived to be more prosocial in economic games than they actually are

Why do people make deontological decisions, although they often lead to overall unfavorable outcomes? One account is receiving considerable attention: deontological judgments may signal commitment to prosociality and thus may increase people’s chances of being selected as social partners–which carries obvious long-term benefits. Here we test this framework by experimentally exploring whether people making deontological judgments are expected to be more prosocial than those making consequentialist judgments and whether they are actually so. In line with previous studies, we identified deontological choices using the Trapdoor dilemma. Using economic games, we take two measures of general prosociality towards strangers: trustworthiness and altruism. Our results procure converging evidence for a perception gap according to which Trapdoor-deontologists are believed to be more trustworthy and more altruistic towards strangers than Trapdoor-consequentialists, but actually they are not so. These results show that deontological judgments are not universal, reliable signals of prosociality.
Depth-of-field effect in subjective and objective evaluation of image quality

Depth of field, as an important image feature, is always ignored when assessing the quality of photographs. The current study compared the subjective image quality evaluation with three NR image quality algorithms: BIQI, BRISQUE, and NIQE on the performance of scoring photographs with different levels of depth of field. The results showed that a large depth of field led to higher image quality in BRISQUE and depth of field did not influence the performance of the other two objective metrics and human perception. We also concluded that objective metrics such as BRISQUE, NIQE, BIQI underestimated the image quality of photographs compared with human perception.
Treatment of Coffee Husk with Ammonium-Based Ionic Liquids: Lignin Extraction, Degradation, and Characterization

Four ammonium-based ionic liquids were synthesized for the selective extraction and degradation of lignin from coffee husk. The extracted lignin samples were characterized by Fourier transform infrared, gel permeation chromatography, gas chromatography–mass spectrometry, UV–vis, 1H and 13C NMR, heteronuclear single-quantum coherence-NMR, thermogravimetric analysis, X-ray diffraction, and field emission scanning electron microscopy analyses. The analyzed results confirmed that these ionic liquids are able to effectively extract and decompose the lignin to smaller molecules from the biomass. Experimental results show that a significantly high yield, 71.2% of the original lignin, has been achieved. This processing method is an efficient, economical, and environmentally friendly green route for producing high-added-value lignin from wasted coffee husk.
Improving Tiny Vehicle Detection in Complex Scenes

Vehicle detection is still a challenge in complex traffic scenes, especially for vehicles of tiny scales. Though RCNN based two-stage detectors have demonstrated considerably good performance, less attention has been paid to the quality of the first stage, where, however, tiny vehicles are very likely to be missed. In this paper, we propose a deep network for accurate vehicle detection, with the main idea of using a relatively large feature map for proposal generation, and keeping ROI feature's spatial layout to represent and detect tiny vehicles. However, large feature maps in lower levels of a deep network generally contain limited discriminant information. To address this, we introduce a backward feature enhancement operation, which absorbs higher level information step by step to enhance the base feature map. By doing so, even with only 100 proposals, the resulting proposal network achieves an encouraging recall over 99%. Furthermore, unlike a common practice which flatten features after ROI pooling, we argue that for a better detection of tiny vehicles, the spatial layout of the ROI features should be preserved and fully integrated. Accordingly, we use a multi-path light-weight processing chain to effectively integrate ROI features, while preserving the spatial layouts. Experiments done on the challenging DETRAC vehicle detection benchmark show that the proposed method largely improves a competitive baseline (ResNet50 based Faster RCNN) by 16.5% mAP, and it outperforms all previously published and unpublished results.
Edge Guided Generation Network for Video Prediction

Video prediction is a challenging problem due to the highly complex variation of video appearance and motions. Traditional methods that directly predict pixel values often result in blurring and artifacts. Furthermore, cumulative errors can lead to a sharp drop of prediction quality in long-term prediction. To alleviate the above problems, we propose a novel edge guided video prediction network, which firstly models the dynamic of frame edges and predicts the future frame edges, then generates the future frames under the guidance of the obtained future frame edges. Specifically, our network consists of two modules that are ConvLSTM based edge prediction module and the edge guided frames generation module. The whole network is differentiable and can be trained end-to-end without any supervision effort. Extensive experiments on KTH human action dataset and challenging autonomous driving KITTI dataset demonstrate that our method achieves better results than state-of-the-art methods especially in long-term video predictions.
Sparse Learning in Gaussian Chain Graphs for State Space Models

The graphical lasso is a popular method for estimating the structure of undirected Gaussian graphical models from data by penalized maximum likelihood. This paper extends the idea of structure estimation of graphical models by penalized maximum likelihood to Gaussian chain graph models for state space models. First we show how the class of linear Gaussian state space models can be interpreted in the chain graph set-up under both the LWF and AMP Markov properties, and we demonstrate how sparsity of the chain graph structure relates to sparsity of the model parameters. Exploiting this relation we propose two different penalized maximum likelihood estimators for recovering the chain graph structure from data depending on the Markov interpretation at hand. We frame the penalized maximum likelihood problem in a missing data set-up and carry out estimation in each of the two cases using the EM algorithm. The common E-step is solved by smoothing, and we solve the two different M-steps by utilizing existing methods from high dimensional statistics and convex optimization.
Farnesoid X receptor‐α is a proviral host factor for hepatitis B virus that is inhibited by ligands in vitro and in vivo

Hepatitis B virus (HBV) infection and bile acid (BA) metabolism are interdependent: infection modifies the expression of the BA nuclear receptor farnesoid X receptor (FXR)‐α, and modulation of FXRα activity by ligands alters HBV replication. Mechanisms of HBV control by FXRα remain to be unveiled. FXRα silencing in HBV‐infected HepaRG cells decreased the viral covalently closed circular (ccc)DNA pool size and transcriptional activity. Treatment with the FXRα agonist GW4064 inhibited FXRα proviral effect on cccDNA similarly for wild‐type and hepatitis B viral X protein (HBx)–deficient virus, whereas agonist‐induced inhibition of pregenomic and precore RNA transcription and viral DNA secretion was HBx dependent. These data indicated that FXRα acts as a proviral factor by 2 different mechanisms, which are abolished by FXRα stimulation. Finally, infection of C3H/HeN mice by a recombinant adeno‐associated virus‐2/8‐HBV vector induced a sustained HBV replication in young mice in contrast with the transient decline in adult mice. Four‐week GW4064 treatment of infected C3H/HeN mice decreased secretion of HBV DNA and HB surface antigen in adult mice only. These results suggest that the physiologic balance of FXRα expression and activation by bile acid is a key host metabolic pathway in the regulation of HBV infection and that FXRα can be envisioned as a target for HBV treatment. —Mouzannar, K. , Fusil, F. , Lacombe, B. , Ollivier, A. , Ménard, C. , Lotteau, V. , Cosset, F. ‐L. , Ramière, C. , André, P. Farnesoid X receptor α is a proviral host factor for hepatitis B virus that is inhibited by ligands in vitro and in vivo. FASEB J. 33, 2472–2483 (2019). www.fasebj. org
Biomimetic adaptive impedance control in physical Human Robot Interaction

Human Robot Interaction has become a key point in the development of new robotic interfaces and controllers. In traditional control schemes for teleoperation, master devices are unaware of the user's arm dynamic characteristics, as well as of the complex motor control strategies adopted to perform the task. In this work, we propose a novel impedance controller to regulate the master device's dynamic properties based on the estimation of user's arm stiffness, with the aim of improving shared task performance. We developed a virtual planar reaching task, and we evaluated arm end-point stiffness's main axis changes in magnitude and direction using a non disruptive offline musculoskeletal model-based algorithm. Based on the stiffness modulation, the biomimetic variable impedance controller to adapt the master device's damping matrix. The direction of maximal damping was aligned with the estimated direction of maximal stiffness (Enhancing field), or to the perpendicular to the stiffness main axis (Isotropic field). The task performances under the biomimetic impedance controllers were tested and compared with the null damping condition. The results showed an increase in task performance, in terms of positional error and overshoots, with both biomimetic controllers. The analysis proved the potentiality of the biomimetic impedance modulation controller in terms of execution accuracy.
A Position Estimation Method for Single-Phase Electrical Machines Without Injecting Extra Test Pulses

Sensorless position estimation algorithms for electromagnetic actuators are becoming increasingly significant in the field of control and condition monitoring since they allow the estimation of the actuator position without any mechanical sensor. Such algorithms typically exploit the position dependency of the actuator inductance. This work presents a new technique capable of identifying the inductance of a single-phase electromagnetic actuator in operation without having to add test pulses, achieving high accuracy and with little signal processing effort. Using this technique, the inductance behavior of an industrial solenoid is characterized. In a further step, the obtained characteristic is modeled by means of different curve fitting approaches and inverted for position estimation. The resulting position estimation technique is implemented and validated experimentally on the Investigated solenoid.
“‘Academic’ is a dirty word”: Intended impact pathways of an emerging academic health centre in tropical regional Australia

Summary Background The Tropical Australian Academic Health Centre (TAAHC) is being established in northern Queensland across a vast rural geography. The study aim is to identify intended impact pathways and beneficiaries of TAAHC as well as experienced and anticipated challenges. Methodology The study is an empirical case study nested within a comparative multi‐case study on academic health centres (AHCs). Data were collected from documents, observation, and interviews with 24 health system and university stakeholders. Intended impact pathways were identified abductively from analysis of aspirations and challenges. Results Aspirations of TAAHC reflect an ultimate aim to improve the health of the northern Queensland population. Challenges were trust and communication, understanding value and return on investment, health system receptiveness to building a research culture, prioritising and influencing the research agenda, and structure of the health system. Discussion The study identifies three interdependent transitions that comprise the main intended impact pathway in TAAHC. Stakeholders expected TAAHC to effect health systems change and improvement rather than drive discovery‐oriented academic research associated with AHCs elsewhere. Conclusion The findings contribute to the empirical evidence base on the role of AHCs internationally and to ongoing initiatives to establish and resource AHCs in Australia.
Intriguing Behavioral Characteristics of Rare-Earth-Free Flux Switching Wind Generators at Small- and Large-Scale Power Levels

In this study, the design optimization of rare-earth-free flux switching machines (FSMs), viz., ferrite permanent magnets (PMs) and wound-fields (WFs), 12-stator slots/10-rotor poles (12/10) and 12/14, has been undertaken in finite element analyses for wind generator applications, in both small-scale (10 kW) and industrial-scale (3 MW) power levels. The focus is on the performance feasibility of these machines to replace rare-earth PMs, as well as on the suitability of the proposed machines for industrial-scale wind power generation. Hence, it is found that the high torque ripple effects typified by the flux focusing characteristics of FSMs are not enhanced by simply using rare-earth-free materials in place of rare-earth PMs, as is usually suggested. Among other listed findings, it is also found that at 10 kW power, the ferrite PM–FSM performs better in terms of lowest torque ripple and active mass, for both machine configurations. At 3 MW power, WF–FSMs have better torque densities, while ferrite PM–FSMs have better torque ripple values, which result in drastic reductions in the cost of the WF–FSMs at industrial-scale power levels compared to other sampled wind generator topologies. To this end, a 10 kW WF–FSM prototype of the considered variant was manufactured and tested for the first time, with some novel implementations. Based on the reported measured no-load to full-load tests, the study is proven beyond reasonable doubt.
Evaluating Socioeconomic Influences on Pinterest Consumer Behavior

Given the increasing popularity of social media channels for influential consumption mechanisms, this research aims to evaluate socioeconomic factors with Pinterest behaviors, underpinned by consumer behavior characteristics. Strategic recommendations are also proposed for marketing managers to optimize their usage of Pinterest. An online questionnaire was completed by a sample of 50 Pinterest users, while 4 face-to-face interviews were conducted with the aim of providing a framework for enhanced use of Pinterest. Findings indicated that virtual exploration is seen as a key Pinterest motivator, supported by the top pinboard rankings of Food, DIY, and Home. Secondly, occupation and family status were the two most significant socioeconomic factors that influences behavioral uses of Pinterest. A concentrated population between ages 25–34, representing higher income households and occupations consisting of Teachers and Business Professionals, exemplified the highest usage and self-efficacy of Pinterest. Low frequency of actual consumption through Pinterest, resulting in high visual consumption, curation of pins, and pinning behaviors were apparent throughout all socioeconomic factors, however the minimal actual consumption can be improved upon, as ease-of-use features are enhanced to embedded e-commerce and online blogs.
Adrenal incidentaloma: machine learning-based quantitative texture analysis of unenhanced CT can effectively differentiate sPHEO from lipid-poor adrenal adenoma

Objective: To evaluate the feasibility and accuracy of machine learning based texture analysis of unenhanced CT images in differentiating subclinical pheochromocytoma (sPHEO) from lipid-poor adenoma (LPA) in adrenal incidentaloma (AI). Methods: Seventy-nine patients with 80 LPA and 29 patients with 30 sPHEO were included in the study. Texture parameters were derived using imaging software (MaZda). Thirty texture features were selected and LPA was performed for the features selected. The number of positive features was used to predict results. Logistic multiple regression analysis was performed on the 30 texture features, and a predictive equation was created based on the coefficients obtained. Results: LPA yielded a misclassification rate of 19.39% in differentiating sPHEO from LPA. Our predictive model had an accuracy rate of 94.4% (102/108), with a sensitivity of 86.2% (25/29) and a specificity of 97.5% (77/79) for differentiation. When the number of positive features was greater than 8, the accuracy of prediction was 85.2% (92/108), with a sensitivity of 96.6% (28/29) and a specificity of 81% (64/79). Conclusions: Machine learning-based quantitative texture analysis of unenhanced CT may be a reliable quantitative method in differentiating sPHEO from LPA when AI is present.
Clinical effectiveness of the Manchester Glaucoma Enhanced Referral Scheme

Background Glaucoma referral filtering schemes have operated in the UK for many years. However, there is a paucity of data on the false-negative (FN) rate. This study evaluated the clinical effectiveness of the Manchester Glaucoma Enhanced Referral Scheme (GERS), estimating both the false-positive (FP) and FN rates. Method Outcome data were collected for patients newly referred through GERS and assessed in ‘usual-care’ clinics to determine the FP rate (referred patients subsequently discharged at their first visit). For the FN rate, glaucoma suspects deemed not requiring referral following GERS assessment were invited to attend for a ‘reference standard’ examination including all elements of assessment recommended by National Institute for Health and Care Excellence (NICE) by a glaucoma specialist optometrist. A separate 33 cases comprising randomly selected referred and non-referred cases were reviewed independently by two glaucoma specialist consultant ophthalmologists to validate the reference standard assessment. Results 1404 patients were evaluated in GERS during the study period; 651 (46.3%) were referred to the Hospital Eye Service (HES) and 753 (53.6%) were discharged. The FP rate in 307 assessable patients referred to the HES was 15.5%. This study reviewed 131 (17.4%) of those patients not referred to the HES through the GERS scheme; 117 (89.3%) were confirmed as not requiring hospital follow-up; 14 (10.7%) required follow-up, including 5 (3.8%) offered treatment. Only one patient (0.8%) in this sample met the GERS referral criteria and was not referred (true FN). There were no cases of missed glaucoma or non-glaucomatous pathology identified within our sample. Conclusion The Manchester GERS is an effective glaucoma filtering scheme with a low FP and FN rate.
A Miniature Endoscopic Optical Coherence Tomography Probe Based on C-Lens

We present a novel miniature endoscopic optical coherence tomography (OCT) probe based on an electrothermal microelectromechanical (MEMS) mirror and a C-lens. The MEMS mirror has a relatively large mirror plate of 0.5 mm × 0.5 mm on a small chip size of 1.5 mm × 1.3 mm, leading to the outer diameter of the endoscopic probe down to only 2.5 mm so that the probe is capable of being inserted through the biopsy channel of a conventional endoscope. A long focal length of 12 mm is achieved by properly designing the C-lens. Compared to commonly used GRIN lenses, C-lenses have advantages of much smaller sensitivities of the working distance and spot size to machining variations. The C-lens based probe can scan a large field of view (FOV) of 6 mm × 6 mm at only 5-V drive voltage. A swept source endoscopic OCT system is constructed using this miniature probe. Experiments show that the corresponding lateral and axial resolutions are about 50 and 14 μm, respectively. Various samples including human fingers, onions, and cancerous colon tissue are imaged and the result suggests this large-working-distance, large-FOV endoscopic probe is promising for applications in large tubular organs and large-area lesions.
Serum concentration of renin-angiotensin system components in association with ACE I/D polymorphism among hypertensive subjects in response to ACE inhibitor therapy

ABSTRACT Background: Renin-angiotensin system (RAS) is a complex network of enzymes and peptides with the essential role in blood pressure control. The relationships between RAS components, RAS-related genetic polymorphisms and therapy response in essential hypertension (EH) were widely explored but the results were inconclusive. Aim: The aim of this study was to explore the functional role of ACE insertion/deletion (I/D) polymorphism on the systemic quantity of angiotensin-converting enzyme (ACE), its homolog - ACE2, chymase and angiotensin II in EH patients with respect to achieved therapeutic blood pressure control. Results: Genotyping of ACE I/D polymorphism was performed among 140 patients with EH from Bulgaria. The serological analyses reveal the significant elevation of the serum quantity of all investigated enzymes in EH than normotensive controls. In addition, serum ACE2 (183.57 pg/ml; vs. 151.78 pg/ml; p = 0.02) and chymase (68.5 pg/ml; vs. 23.66 pg/ml; p = 0.034) were significantly higher in patients with uncontrolled EH than controlled EH in response to ACE-inhibitory therapy. Also, ACE I/D polymorphism showed a significant impact on the serum ACE and chymase levels. ACE quantity was the highest among carriers of DD-genotype, followed by ID and II-genotype. Contrary, chymase was in the highest quantity in II-genotype compared to ID-genotype (p = 0.025) and DD-genotype (p = 0.044). Conclusions: Our results suggest that insufficient blood pressure control by ACE-inhibitory therapy could be associated with elevation of serum ACE2 and chymase levels. Also, it appears that ACE I/D polymorphism may influence the circulating quantity of chymase in addition to ACE.
A longitudinal study of depression in old age II: depression and physical disability

Abstract Objectives: As part of an outcome study of depression in older people, the relationship between physical disability and depression was explored at baseline and longitudinally. The aims were to identify whether illness in specific body systems or physical disability was associated with a poorer outcome of depression. Method: Subjects over 65 with depression referred to an old age psychiatry service were recruited. Depression was diagnosed according to ICD-10 criteria. An in-depth initial assessment obtained data concerning depression severity and illness in specific body systems as well as disability levels. Objective and subjective ratings of health status were also made. Subjects were followed up at three, six, 12, 18, and 24 months. Ongoing assessments were made of depressive symptomatology and of physical status. Results: Subjects with higher disability levels had more severe depression at baseline. There was no relationship between illness in specific body systems and depression severity. At follow up assessments, those with higher disability scores had poorer outcomes as recorded by depression rating scales and by reviewing the longitudinal course of depression in terms of proportions remaining well, suffering relapses or remaining depressed. Conclusions: There is an ongoing relationship between depression and disability. Older people with greater physical disability have a poorer outcome of depression. Service providers should be aware of this relationship and respond rapidly and assertively to depression in older people with disability. There should be a lower threshold for initiating treatment in this population.