Miracle-dz/UniFAR-FTUs huggingface dataset:
Feasibility of collecting and assessing patient-reported outcomes for emergency admissions: laparotomy for gastrointestinal conditions

Introduction Audit of emergency surgery is usually limited to immediate clinical outcomes relating to outcomes during the acute hospital episode with little attempt to capture patients’ views of their longer-term outcomes. Our aim was to determine the response rate to patient-reported outcome measures (PROMs) for patients who underwent an emergency laparotomy for gastrointestinal conditions, identify response bias and explore the feasibility of comparing outcomes with their prior health based on their recalled view collected during their admission. Methods Patients undergoing emergency laparotomy in 11 hospitals were recruited to complete a retrospective questionnaire containing the EQ-5D-3L and Gastrointestinal Quality of Life Index (GIQLI). Response rate for 3-month mailed follow-up questionnaire and potential response biases were assessed. Patients’ outcomes were compared with their baseline using χ2 and paired t-test to assess for differences. Results Of 255 patients contacted at 3 months, 190 (74.1%) responded. Responders were more likely to be older, female and more affluent. Patients’ health improved significantly as regards the GIQLI (93.3 vs 97.9; p=0.048) and the subscale on symptoms (51.9 vs 59.6; p<0.001). No significant change in subscales on emotion or physical aspects or for overall health status (EQ-5D: 0.58 vs 0.64; p=0.06). According to the social subscale, patients had deteriorated (11.0 vs 9.8; p<0.0006). Differences in change scores by patient characteristics were slight, suggesting minimal response bias. Conclusion This approach offers the opportunity for assessing the impact of treatment, from the patient’s perspective and the potential to evaluate emergency laparotomy care using PROMs.
Control Design for Soft Robots Based on Reduced-Order Model

Inspired by nature, soft robots promise disruptive advances in robotics. Soft robots are naturally compliant and exhibit nonlinear behavior, which makes their study challenging. No unified framework exists to control these robots, especially when considering their dynamics. This letter proposes a methodology to study this type of robots around a stable equilibrium point. It can make the robot converge faster and with reduced oscillations to a desired equilibrium state. Using computational mechanics, a large-scale dynamic model of the robot is obtained and model reduction algorithms enable the design of a low-order controller and observer. A real robot is used to demonstrate the interest of the results.
Improving Power Spectral Density Estimation of Unmanned Aerial Vehicle Rotor Noise by Learning from Non-Acoustic Information

A method to accurately estimate an unmanned aerial vehicle's (UAV) rotor noise power spectral density (PSD) is proposed, as part of the development of an effective UAV-mounted audio recording system that clearly captures the desired sound signals. Based on a previous study, the method seeks to improve rotor noise PSD estimation accuracy and robustness by utilising UAV rotor characteristics and microphone signals. Simulation results showed PSD estimation accuracy to within 1.3-3.3 dB log spectral distortion regardless of the presence of surrounding sound sources.
Neogenkwanine I from the flower buds of Daphne genkwa with its stereostructure confirmation using quantum calculation profiles and antitumor evaluation

Abstract Neogenkwanine I (1), a new daphnane-type diterpene with 4,7-ether group, along with four known ones (2–5), were isolated from Daphne genkwa. The structure including absolute configurations of 1 was established on the basis of NMR, 13C-NMR and ECD calculations and CD exciton chirality analysis. 13C-NMR and ECD calculations of daphnane-type diterpenes were reported here for the first time. All of the diterpenes were screened for their cytotoxic activities against MCF-7 and Hep3B cell lines. The cytotoxicity structure- activity relationship of compounds was illustrated with the absence of ortho-ester group of daphnane-type diterpenes. Graphical Abstract
A Fluidic Biosensor Based on a Phase-Sensitive Low-Coherence Spectral-Domain Interferometer

A phase-sensitive fluidic biosensor based on a spectral-domain low-coherence interferometer is presented in this paper. With a fiber optic probe employing the common-path interferometric configuration, subnanometric changes in thickness of the molecular layers can be detected through phase analysis of the acquired interference signal from the sensor surface. Advantages of this biosensor include its picometer-scale thickness sensitivity, 13.9-ms time response, and tolerance to the fluctuation in concentration of the target solution. The capabilities of this biosensor in monitoring specific molecular binding and recognizing specific molecular was successfully demonstrated by using the reactions between the molecules of protein A and IgG. The calculated minimum detectable concentration of IgG is 0.11 µg/mL.
Partners’ Depressive Symptoms Moderate the Effects of Expressive Suppression

Suppressing emotional expressions can hide one’s needs from relationship partners and thus prevent partners from providing support. Nevertheless, suppressing expressions may help people maintain more favorable evaluations of partners who are ultimately unsupportive because people may attribute a lack of support to partners being unaware of their needs. Thus, given that depressive symptoms reduce provisions of support, people with partners experiencing depressive symptoms may remain more satisfied to the extent that they previously suppressed emotional expressions. We tested these ideas in 1 experiment, 1 cross-sectional study, and 1 longitudinal study. In Study 1, participants imagined either expressing or suppressing their emotions, imagined their partner was either supportive or unsupportive to their needs, and reported their perceptions of their partner. In Studies 2 and 3, newlywed couples reported their depressive symptoms, their marital satisfaction, and the extent to which they suppressed their emotional expressions cross-sectionally (Study 2) or every year for 2 years (Study 3). Results revealed that people with unsupportive partners or partners high in depressive symptoms made more benevolent attributions for their partners’ unsupportive behavior and remained more satisfied with their partners to the extent that they suppressed their emotional expressions; however, people with supportive partners or partners low in depressive symptoms became more dissatisfied with their partners to the extent that they suppressed their emotional expressions. These results highlight the benefits of dyadic theoretical perspectives by revealing that qualities of the partner moderate the effects of expressive suppression.
Electronic Cigarettes and Smoking Cessation in the Perioperative Period of Cardiothoracic Surgery: Views of Australian Clinicians

For patients who smoke, electronic cigarettes may offer a pathway to achieve tobacco abstinence and reduce the risk of postoperative complications. Clinicians have a pivotal role in supporting smoking cessation by patients with lung cancer and coronary artery disease throughout the perioperative period of cardiothoracic surgery. However, the views of Australian cardiothoracic clinicians on electronic cigarettes and smoking cessation are unknown. Semi-structured interviews were conducted with 52 cardiothoracic surgeons, anaesthetists, nurses and physiotherapists in six hospitals in Sydney and thematically analysed. Clinicians’ knowledge about electronic cigarettes and the regulatory environment surrounding them was limited. Clinicians believed that: electronic cigarettes, though unlikely to be safe, were safer than tobacco cigarettes; electronic cigarettes may have a harm reduction role in public health; and electronic cigarettes were a potential smoking cessation tool for the extraordinary circumstances of surgery. The professional role of a clinician and their views about electronic cigarettes as a perioperative smoking cessation aid had an influence on future clinician-patient interactions. Electronic cigarette use is increasing in Australia and clinicians are likely to receive more frequent questions about electronic cigarettes as a cessation aid. Stronger guidance for clinicians is needed on the topic of electronic cigarettes and cardiothoracic surgery.
Frame-Online DNN-WPE Dereverberation

Signal dereverberation using the weighted prediction error (WPE) method has been proven to be an effective means to raise the accuracy of far-field speech recognition. But in its original formulation, WPE requires multiple iterations over a sufficiently long utterance, rendering it unsuitable for online low-latency applications. Recently, two methods have been proposed to overcome this limitation. One utilizes a neural network to estimate the power spectral density (PSD) of the target signal and works in a block-online fashion. The other method relies on a rather simple PSD estimation which smoothes the observed PSD and utilizes a recursive formulation which enables it to work on a frame-by-frame basis. In this paper, we integrate a deep neural network (DNN) based estimator into the recursive frame-online formulation. We evaluate the performance of the recursive system with different PSD estimators in comparison to the block-online and offline variant on two distinct corpora. The REVERB challenge data, where the signal is mainly deteriorated by reverberation, and a database which combines WSJ and VoiceHome to also consider (directed) noise sources. The results show that although smoothing works surprisingly well, the more sophisticated DNN based estimator shows promising improvements and shortens the performance gap between online and offline processing.
Nutritional status and related factors of schoolchildren in Çorum, Turkey

Abstract Objective We aimed to determine nutritional status and related factors among schoolchildren in Çorum, Central Anatolia, Turkey. Design Schoolchildren’s height and weight were measured to calculate BMI and BMI Z-scores. Height, weight and BMI Z-scores were analysed and nutritional status classified according to the WHO. Setting Central Anatolia, Turkey. Participants Schoolchildren aged 5–17 years (n 1684) participated in study. Results Of children, 4·2% were stunted, 6·9% thin, 13·8% overweight and 6·6% were obese. Proportions of stunting, thinness and overweight/obesity were significantly higher in children aged >10 years (78·6, 75·0 and 64·9%, respectively) than in those aged ≤10 years (21·4, 25·0 and 35·1%, respectively; all P <0·001). Median (range) birth weight and breast-feeding duration in children with stunting (2750 (1400–3600)g; 10 (0–36) months) were significantly lower and shorter, respectively, than those of normal height (3200 (750–5500)g; 15 (0–72) months) and tall children (3500 (2500–4900)g; 18 (0–36) months; P <0·001, <0·001, 0·011 and 0·016, respectively). The same relationship was observed in thin children (3000 (1000–4500)g; 12 (0–36) months) compared with normal-weight (3200 (750–5500)g; 15 (0–72) months) and overweight/obese children (3300 (1200–5500)g; 16 (0–48) months; P=0·026, <0·001, 0·045 and 0·011, respectively). Conclusions Overweight and obesity are health problems that must be addressed in schoolchildren. Adolescents also have a risk of double malnutrition. Promoting normal birth weight and encouraging long duration of breast-feeding are important to support normal growth in children.
Introducing Heuristic Information Into Ant Colony Optimization Algorithm for Identifying Epistasis

Epistasis learning, which is aimed at detecting associations between multiple Single Nucleotide Polymorphisms (SNPs) and complex diseases, has gained increasing attention in genome wide association studies. Although much work has been done on mapping the SNPs underlying complex diseases, there is still difficulty in detecting epistatic interactions due to the lack of heuristic information to expedite the search process. In this study, a method EACO is proposed to detect epistatic interactions based on the ant colony optimization (ACO) algorithm, the highlights of which are the introduced heuristic information, fitness function, and a candidate solutions filtration strategy. The heuristic information multi-SURF* is introduced into EACO for identifying epistasis, which is incorporated into ant-decision rules to guide the search with linear time. Two functionally complementary fitness functions, mutual information and the Gini index, are combined to effectively evaluate the associations between SNP combinations and the phenotype. Furthermore, a strategy for candidate solutions filtration is provided to adaptively retain all optimal solutions which yields a more accurate way for epistasis searching. Experiments of EACO, as well as three ACO based methods (AntEpiSeeker, MACOED, and epiACO) and four commonly used methods (BOOST, SNPRuler, TEAM, and epiMODE) are performed on both simulation data sets and a real data set of age-related macular degeneration. Results indicate that EACO is promising in identifying epistasis.
Non-Invasive Multi-Disease Classification via Facial Image Analysis Using a Convolutional Neural Network

Diabetes and lung disease are some of the most common medical conditions in the world. The economic costs and social burdens brought by these two diseases are considerable. Even though there are proven methodologies for diagnosing each disease individually in practice, there does not exist a single non-invasive methodology/procedure that can detect both diseases. With recent advancements made in machine learning and pattern recognition, the Convolutional Neural Network (CNN) has been widely used in many recognition applications due to its high efficiency and performance. Therefore, in this paper we propose an approach using CNN for non-invasive multi-disease classification called Multi-Disease CNN (MD-CNN). Facial images are first captured using our specially designed device. Next, four facial blocks are extracted located at specific regions on the face. Finally, the facial blocks are concatenated and used as input for our MD-CNN. Based on three datasets consisting of healthy control, diabetes and lung disease, the proposed method achieved an average accuracy of 73%. When compared to other classifiers not employing a deep learning architecture, MD-CNN produced the highest result. This show a potentially new way to perform multi-disease classification.
An Adaptive 3D Grid-Based Clustering Algorithm for Automotive High Resolution Radar Sensor

Novel automotive high resolution radar sensors can detect several thousands of reflection points from the surrounding environment, e.g., pedestrians, cyclists, vehicles and roadside infrastructure. For object classification and tracking, the detection points belonging to the same object shall be clustered into one group before further processing. This paper presents an adaptive clustering approach based on a range/angle/velocity-grid generated originally from the radar signal processing and angle estimation stage. In contrast to an x/y-approach, multiple reflection points will not be merged into one single grid cell at close ranges, but keep their individual information in different assigned grid cells. A time and storage efficient process with a clustering window according to grid indices is implemented to search for the points with similarity in all three dimensions. In order to eliminate the parameter dependency and the incorrect clustering due to uncertainties of real radar measurements, this approach is extended with a model-based clustering window depending on the tracked and estimated object contour. By validation with various measurement data, stable clustering results with almost perfect true positive rates are achieved independently of the prevailing parameters and object types.
Long Low-Loss-Litium Niobate on Insulator Waveguides with Sub-Nanometer Surface Roughness

In this paper, we develop a technique for realizing multi-centimeter-long lithium niobate on insulator (LNOI) waveguides with a propagation loss as low as 0.027 dB/cm. Our technique relies on patterning a chromium thin film coated on the top surface of LNOI into a hard mask with a femtosecond laser followed by chemo-mechanical polishing for structuring the LNOI into the waveguides. The surface roughness on the waveguides was determined with an atomic force microscope to be 0.452 nm. The approach is compatible with other surface patterning technologies, such as optical and electron beam lithographies or laser direct writing, enabling high-throughput manufacturing of large-scale LNOI-based photonic integrated circuits.
The Safety Concerns of Night Shift Schedule: Implications for Family, Homes and Human Health

Wealth does not correlate with health, neither does the ability to work longer hours and the night shift determine the level of one’s wealth. It is important to consider health and safety first when accepting new job schedules or offers. This study investigates how night shift schedules have contributed to workers’ poor well-being, quality of life and marriages. One-hundred ninety-one night shift workers voluntarily participated in the study. Respondents were grouped into three age categories: 18-34, 35-54, and 55-74. Responses were quantified and statistical analyses were run on the data. Results revealed that 24% of the respondents responded to be depressed and 57% indicated to have low energy after working a night shift schedule. The risk of divorce among the married respondents was found to be 1-person in every 5-workers. Poor appetite revealed 1 out of every 3-workers and 1 out of 2-workers have the risk of losing interest in their usual activities. Approximately seventeen percent reported having very bad quality of life, while 39% declared to have average quality of life. Thirty percent of the respondents revealed having concentration problems after working night shift. The paired t-test result revealed that a night shift schedule has a statistically significant effect on the workers’ well-being who work on night shift (t = 16.13, df = 190, p < 0.0001). The level of divorce, poor quality of life, less interest in usual activities and health issues as a result of workers’ schedule suggest the need for better work schedule structuring. The findings from this study highlight potential damages night shift schedule has done to human well-being and life style in general. Findings from this study could help families to better avert or handle health issues at home and with their spouses.
Analysis of Stock Price Flow Based on Social Media Sentiments

Prediction of mood uses the sentiment word lists obtained in various sources where general state of mood can be found using such word list or emotion tokens. With the number of messages posted on Stock Twits, it is believed that the general state of mood can be predicted with certain statistical significance. This paper explores the relationship between Stock Twits messages relationship with stock market movement, and how well, sentiment extracted from these feeds can be related to the shifts in stock prices. For this case we chose Apple Inc to perform the analysis, and estimate its accuracy.
Placenta Specific 8 Suppresses IL-18 Production through Regulation of Autophagy and Is Associated with Adult Still Disease

Adult Still disease (ASD) is a systemic disorder of unknown etiology characterized by high spiking fever, rash, and arthritis. The purpose of this study was to identify genes specifically associated with the active phase of the disease. In this study, we have reported that placenta specific 8 (PLAC8) was a newly specific gene involved in ASD. DNA microarray and validation analysis using human monocytes revealed that the expression of PLAC8 was significantly higher in active-ASD patients than in inactive-ASD patients and healthy controls. In ASD, PLAC8 expression level correlated with serum levels of CRP, ferritin, IL-1β, and IL-18. Stimulation of monocytes with LPS results in PLAC8 upregulation. LPS or nigericin stimulation of PLAC8-overexpressing human monocytic cell line (THP-1), but not mock THP-1 cells, was associated with a significant decrease in IL-1β and IL-18 production. PLAC8 overexpression in THP-1 cells was associated with enhanced autophagy and suppression of IL-1β and IL-18 production. Therefore, we found that PLAC8 was upregulated in activated monocytes, as was IL-1β and IL-18. The upregulated PLAC8 acts on the synthesis of inactive precursors of IL-1β and IL-18 and seemed to suppress the production of IL-1β and IL-18 by negative feedback through enhanced autophagy, resulting in the suppression of ASD. The results highlight the role of PLAC8 in the pathogenesis of ASD and suggest its potential suitability as an activity marker and therapeutic target in ASD.
Increased Optical Absorption and Light–Matter Interaction in Silicon Thin-Film Solar Cell Nanostructure Using Graphene and 2-D Au/Ag Nanograting

Silicon solar cells with graphene have commonly some drawbacks in assuming Schottky junction configurations, small active areas, carrier’s recombination at interface of graphene/silicon junction, high cost, and complex manufacture processes. We report a new silicon thin-film solar cell structure with graphene, gold (Au) nanograting, and back silver (Ag) contact, which has advantages of simple fabrication method, no graphene/silicon Schottky junction complexity, high absorption, and high short circuit current density. We simulate the proposed specific graphene–silicon solar cell layer assembly by using the 2-D FEM under the standard global <italic>AM1.5</italic> spectrum conditions. The generation of strong magnetic resonance field arises due to graphene sheet covered on top of gold nanograting and specific dielectric spacer thickness and slit period and leads to increase absorption and transport of charge carriers in p-i-n silicon layer sandwiched between dielectric spacer and back contact. We report that absorption improvement can be simply tuned by adjusting few geometric parameters of proposed device and maximum absorption is achieved up to 80% in near-infrared wavelength ranges. As an outcome, maximum short circuit current density (<inline-formula> <tex-math notation="LaTeX">$J_{\mathrm {sc}}$ </tex-math></inline-formula>) of 32 mA/cm<sup>2</sup>, open-circuit voltage (<inline-formula> <tex-math notation="LaTeX">$V_{\mathrm {oc}}$ </tex-math></inline-formula>) of 0.45 V, and calculated power conversion efficiency of 10.5% are achieved without chemical doping of graphene. The proposed simple structure configuration of silicon thin-film solar cell with graphene on top offers flexible tuneability, high short circuit current values, and increased optical absorption that are beneficial for practical fabrication and industrial applications.
Motion Planning With Flexible Trajectory Chains

This paper presents a novel methodology for motion planning. The basic idea is to model vehicle trajectories as chains with adjustable joints and links. The characteristic parameters of these chains are chosen in accordance with the limitations due to driving dynamics. A key feature of the approach is that trajectories can be modified in a fast and intuitive manner, e.g., in order to avoid suddenly emerging obstacles. It is possible to simultaneously generate trajectories of multiple dynamic objects, taking into account interactions and dependencies between the objects. The trajectory chain model is extended by continuous collision detection, which allows collisions along a chain link to be covered with a single collision query. The simple structure of the chain model and the ability to react to dynamic objects offers advantages in applications in which a multitude of trajectories have to be calculated in a dynamic environment. The method was successfully implemented and validated by simulations. Its functionality is shown in collision avoidance scenarios.