Miracle-dz/UniFAR-FTUs huggingface dataset:
The impact of the transition to Personal Independence Payment on claimants with mental health problems

Abstract This paper examines the impact of major social security reform on mental health claimants by analysing the transition to Personal Independence Payment in the UK. Personal Independence Payment was introduced in April 2013, replacing Disability Living Allowance as the main non-means tested disability benefit intended to assist with the additional costs associated with disability or long-term health conditions. It is important to gain a better understanding of how people with mental health problems have experienced this reform. Twelve service users were interviewed for this qualitative research. Analysis identified three main themes: problems with the Personal Independence Payment claims process; problems conveying mental health problems during the assessment process; and positive experiences associated with the transition to Personal Independence Payment. This research demonstrates that major changes in benefit policy are challenging for people with mental health problems, particularly when delivered in a climate of austerity. Points of Interest The UK Government has changed the main disability benefit for disabled adults. From April 2013, Disability Living Allowance (DLA) has been phased out and replaced by Personal Independence Payment (PIP). This research found that this significant change caused difficulties for people with mental health problems. Everyone who took part reported increased anxiety, problems with claiming PIP, communicating with benefit officials and the medical assessment. It is important to learn from these problems so that future benefit changes, both in the UK and in other countries, can be developed and rolled-out in ways which are more appropriate for people with mental health problems.
Vulnerabilizing invulnerable: pandemic and the consumption of affluent elderly

Abstract Consumer vulnerability is a condition that imbalances the consumer-market relationship, causing consumers to lose control of that relationship. The COVID-19 pandemic is an external event that has contributed to this imbalance. This article explains how consumers experience the vulnerability perceived during the pandemic and the role of consumption in dealing with the effects of such vulnerability. We study retired affluent consumers with health and cultural capital to carry out their plans. Interpretative research was conducted through in-depth interviews with 31 Brazilian affluent older people, and other sources were collected, such as memes, journalistic articles, and advertisements. We found that the external event made elderly vulnerable consumers only because of their age. These consumers did not perceive themselves as vulnerable before the pandemic. Also, consumption was revealed as part of the strategy to deal with the consequences of vulnerability, and the market response helped this population resume their feeling of invulnerability.
Noble-Metal-Free NixSy-C3N5 Hybrid Nanosheet with Highly Efficient Photocatalytic Performance

The construction of highly efficient, low-cost and noble-metal-free photocatalysts depends on photocatalytic technology. Recently, N-rich C3N5 has been explored as a novel carbon nitride material with a much narrower band gap (~2.2 eV) than that of traditional C3N4 (~2.7 eV). Planting noble-metal-free active sites on C3N5 to improve its photocatalytic activity is of great significance. Herein, 2D NixSy nanosheet is facially loaded on 2D C3N5 using a hydrothermal procedure under a low temperature. Due to the quick separation of photogenerated carries between C3N5 and NixSy, this inexpensive noble-metal-free NixSy-C3N5 hybrid nanosheet is highly efficient and stable as a multifunctional catalyst in various applications, including photocatalytic H2 production from water and NO removal. Impressively, the apparent quantum yield (AQY) value for H2 production reaches 37.0% (at 420 nm) on optimal NixSy-C3N5 hybrids, which is much higher than that of Pt-C3N5 material. This work opens an avenue to the fabrication of low-cost and noble-metal-free catalysts for multifunctional photocatalytic applications.
Antifungal Activity of ZnO and MgO Nanomaterials and Their Mixtures againstColletotrichum gloeosporioidesStrains from Tropical Fruit

Avocado (Persea americana) and papaya (Carica papaya) are tropical fruits with high international demand. However, these commercially important crops are affected by the fungusColletotrichum gloeosporioides, which causes anthracnose and results in significant economic losses. The antifungal activity of metal oxide nanomaterials (zinc oxide (ZnO), magnesium oxide (MgO), and ZnO:MgO and ZnO:Mg(OH)2composites) prepared under different conditions of synthesis was evaluated against strains ofC. gloeosporioidesobtained from papaya and avocado. All nanoparticles (NPs) at the tested concentrations significantly inhibited the germination of conidia and caused structural damage to the fungal cells. According to the radial growth test, the fungal strain obtained from avocado was more susceptible to the NPs than the strain obtained from papaya. The effect of the tested NPs on the fungal strains confirmed that these NPs could be used as strong antifungal agents againstC.gloeosporioidesto control anthracnose in tropical fruits.
The effects of fatigued working memory functions on hypothesis testing during acquisition of a motor skill.

Implicit motor learning paradigms aim to minimize verbal-analytical engagement in motor performance. Some paradigms do this by decreasing working memory activity during practice, which reduces explicit processes associated with the search for motor solutions (e.g., hypothesis testing). Here we designed a mentally demanding motor task to fatigue working memory prior to motor practice and then tested whether it reduced hypothesis testing. Fifty-nine participants were randomly assigned to complete the mentally demanding motor task (cognitive fatigue group) or to complete an undemanding motor task (nonfatigued control group). Feelings of fatigue, working memory functions, electroencephalography (EEG) Fz power, and vagal control were assessed pre- and posttask to quantify the effect of the mentally demanding motor task on cognitive fatigue. Thereafter, an adapted shuffleboard task was completed to determine the impact on hypothesis testing. Hypothesis testing was assessed by self-report, technique changes, and equipment-use solutions. Additionally, verbal-analytical engagement in motor performance was (indirectly) gauged with EEG T7-Fz connectivity and T7 power measures. Participants in the cognitive fatigue group reported more fatigue and displayed moderated working memory functions and Fz theta power. During practice of the shuffleboard task, participants also displayed more technique changes and higher verbal-analytical engagement in motor planning (EEG T7-Fz connectivity), compared with participants in the control group. The mentally demanding motor task suppressed working memory functions, but resulted in more, rather than less, hypothesis testing during shuffleboard practice. The implications are discussed in the context of implicit motor learning theory. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
Design and Modelling of 3D Bionic Cathode Flow Field for Proton Exchange Membrane Fuel Cell

Proton exchange membrane fuel cells (PEMFCs) have been utilized as a promising power source for new energy vehicles. Their performances are greatly affected by the structural design of the flow field in the bipolar plate. In this paper, we present a novel three-dimensional (3D) bionic cathode flow field, inspired by the small intestinal villi. The structural design and working principle of the 3D bionic flow field units are first described. A 3D numerical model is developed to study the mass transfer and distribution of the reactants and products, as well as the polarization performances of the PEMFC with the 3D bionic cathode flow field. The simulation results indicate that the proposed 3D bionic flow field can significantly improve the reaction gas supply from the flow field to porous electrodes, and thus would be beneficial for the removal of liquid water in the cathode. The mass transfer of gas in the PEMFC can be enhanced due to the increasing contact areas between the gas diffusion layer (GDL) and the cathode flow field, and the distribution of currents in the membrane would be more uniform. The obtained results demonstrated the feasibility of using the 3D bionic flow field for the development of highly efficient PEMFCs with high power density.
Real-time prediction of propulsion motor overheating using machine learning

ABSTRACT Thermal protection in marine electrical propulsion motors is commonly implemented by installing temperature sensors on the windings of the motor. An alarm is issued once the temperature reaches the alarm limit, while the motor shuts down once the trip limit is reached. Field experience shows that this protection scheme in some cases is insufficient, as the motor may already be damaged before reaching the trip limit. In this paper, we develop a machine learning algorithm to predict overheating, based on past data collected from a class of identical vessels. All methods were implemented to comply with real-time requirements of the on-board protective systems with minimal need for memory and computational power. Our two-stage overheating detection algorithm first predicts the temperature in a normal state using linear regression fitted to regular operation motor performance measurements, with exponentially smoothed predictors accounting for time dynamics. Then it identifies and monitors temperature deviations between the observed and predicted temperatures using an adaptive cumulative sum (CUSUM) procedure. Using data from a real fault case, the monitor alerts between 60 to 90 min before failure occurs, and it is able to detect the emerging fault at temperatures below the current alarm limits.
Characterization and in vitro Biocompatibility of Binary Mixtures of Chitosan and Polyurethanes Synthesized from Chemically Modified Castor Oil, as Materials for Medical Use

This study aimed to evaluate the effect of the incorporation of chitosan into polyurethane matrices synthesized from chemically modified castor (Ricinus communis) oil by transesterification with pentaerythritol. An additional aim of this study was to determine the degree of acceptance as a biomaterial (obtained from renewable sources), based on the analysis of its mechanical properties (stress/rupture strain), hydrophilic character (contact angle), morphology (SEM) and in vitro compatibility of polyurethanes when in contact with mouse fibroblast L929 cells. No significant changes in mechanical properties were observed with the addition of chitosan to polyurethanes synthesized from chemically modified castor oil. All polyurethane formulas showed morphological changes with increased chitosan concentration. As chitosan/polyurethane binary mixtures do not present a cytotoxicity risk for L929 mouse fibroblasts and possess similar mechanical properties to soft and cardiovascular tissues, their use as a biomedical material is suggested.
Learning to Assemble Noncylindrical Parts Using Trajectory Learning and Force Tracking

The purpose of this article is to teach a robot assembly skills from demonstrations, and we attempt to train both the trajectory and the insertion force simultaneously. We encode human demonstrations data via motion primitives and, then, generate a reference trajectory and a prescribed force profile for a new assembly task using the combination of the motion primitives. We then propose an adaptive impedance controller to track the prescribed force with unknown environment stiffness, where the impedance parameters are estimated by the optimal solution of an equivalent linearization model. Our approach combines adaptive impedance control techniques with learning from demonstration on the same that makes it tractable and applicable to a real robot. Experiments on several typical noncylindrical parts illustrate the efficiency of the proposed method.
Highly Ordered N-Heterocyclic Carbene Monolayers on Cu(111)

The benzannulated N-heterocyclic carbene, 1,3-dibenzylbenzimidazolylidene (NHCDBZ) forms large, highly ordered domains when adsorbed on Cu(111) under ultrahigh vacuum conditions. A combination of scanning tunnelling microscopy (STM), high-resolution electron energy loss spectroscopy (HREELS), and density functional theory (DFT) calculations reveals that the overlayer consists of vertical benzannulated NHC moieties coordinating to Cu adatoms. Long-range order results from the placement of the two benzyl substituents on opposite sides of the benzimidazole moiety, with their aromatic rings approximately parallel to the surface. The organization of three surface-bound benzyl substituents from three different NHCs into a triangular array controls the formation of a highly ordered Kagome-like surface lattice. By comparison with earlier studies of NHCs on Cu(111), we show that the binding geometry and self-assembly of NHCDBZ are influenced by intermolecular and adsorbate–substrate interactions and facilitated by the flexibility of the methylene linkage between the N-heterocycle and the aromatic wingtip substituents.
ER ligands ameliorate fatty liver through a non-classical ER / LXR pathway

Song-iee Han (shan@tara.tsukuba.ac.jp), Yoko Komatsu (s0310868_yoko@yahoo.co.jp), Akiko Murayama (akikomrym@agbi.tsukuba.ac.jp), Knut R. Steffensen (Knut.Steffensen@ki.se), Yoshimi Nakagawa (yosshy@md.tsukuba.ac.jp), Yuka Nakajima (nakajima@tara.tsukuba.ac.jp), Michiko Suzuki (s0910720@u.tsukuba.ac.jp), Shohei Oie (s_ooie@tara.tsukuba.ac.jp), Paolo Parini (Paolo.Parini@ki.se), Lise-Lotte Vedin (Lise-Lotte.Vedin@ki.se), Hiroyuki Kishimoto (h-kishimoto@tara.tsukuba.ac.jp), Hitoshi Shimano (hshimano@md.tsukuba.ac.jp), Jan-Åke Gustafsson (jgustafs@Central.UH.EDU), and Junn Yanagisawa (junny@agbi.tsukuba.ac.jp)
MBLT: Learning Motion and Background for Vehicle Tracking in Satellite Videos

Recently, satellite videos provide a new way to dynamically monitor the Earth's surface. The interpretation of satellite videos has attracted more and more attentions. In this article, we focus on the problem of the vehicle tracking in satellite videos. Satellite videos usually own a lower resolution, which leads to the following phenomena: 1) the size of a vehicle target usually includes a few pixels and 2) vehicles are usually with similar appearance which easily results in the wrong tracking within the observing region. General popular tracking methods usually focus on the representation of the target and recognize it from background which are limited in this problem. As a consequence, in this article, we propose to learn motion and background of the target in order to help the trackers recognize the target with higher accuracy. A prediction network is proposed to predict the location probability of the target in each pixel in next frame based on fully convolutional network (FCN) which is learned from previous results. In addition, a segmentation method is introduced to generate the feasible region for target in each frame and assign high probability for such a region. For quantitative comparison, we manually annotate 20 representative vehicle targets from nine satellite videos taken by JiLin-1. In addition, we also selected two public satellite video datasets for experiments. Numerous experimental results demonstrate the superior of the proposed method.
KINEMATICAL VARIABLES ANALYSIS OF DISCUS THROW ACTIVITY IN PARA-ATHLETICS (CLASS F57) AND THEIR RELATIONSHIPS WITH DIGITAL LEVEL ACHIEVEMENT. PART І.

The aim of this study is to analyze kinematical variables of discus throw activity in Para-Athletics F57 and to investigate their relationships with digital level achievement. International Para-athlete "Saifi Nassima" participated voluntarily in this study. The athlete throwed the discus with her right arm. Recordings were made by synching cameras (AEE MagicCam, 170° view, MOV Format Video, 720p Video Resolution, 120 ips NTFS, Screen Resolution 1280*720 16:9) for side and rear views by a LANC (CONTROL-L) device. The athlete wore reflective markers to track their motions on joints of the wrists, the elbows, the shoulders, the hip center, and down the neck with the least possible number of occlusions, to analyze the length and angle of movement by the x and y axis. The best six throws during the first and second phases (start and finish throwing) of the discus throw were included for analysis in two-dimensional by Dartfish.9 software. Means, standard deviations, minimum and maximum values were applied as descriptive statistics, and Pearson test for the correlations between all variables. As a result, there was a positive significant correlation of digital level with cubitus angle of the throwing hand (p< .001), trunk angle (p< .005) in the first phase, and with disk flight time (p< .005), throwing angle (p< .001) in the second phase. In conclusion, we confirm that the increase in the values of the variables of distance shot from the armrest, and the wrist angle of the shooting hand in the first phase of throwing, affects the digital level achievement. The decrease in the value of the throwing angle variable in the second phase of throwing affects the digital level achievement.
Remote Data Possession Checking Scheme with Supporting Efficient Group User Authority Management for Shared Cloud Data

Under the shared big data environment, most of the existing data auditing schemes rarely consider the authorization management of group users. Meanwhile, how to deal with the shared data integrity is a problem that needs to be pondered. Thus, in this paper, we propose a novel remote data checking possession scheme which achieves group authority management while completing the public auditing. To perform authority management work, we introduce a trusted entity – group manager. We formalize a new algebraic structure operator named authorization invisible authenticator (AIA). Meanwhile, we provide two versions of AIA scheme: basic AIA scheme and standard AIA scheme. The standard AIA scheme is constructed based on the basic AIA scheme and user information table (UIT), with advanced security and wider applicable scenarios. By virtue of standard AIA scheme, the group manager can perfectly and easily carry out authority management, including enrolling, revoking, updating. On the basis of the above, we further design a public auditing scheme for non-revoked users’ shared data. The scheme is based on identity-based encryption (IBE), which greatly reduce the necessary certificate management cost. Furthermore, the detailed security analysis and performance evaluation demonstrate that the scheme is safe and feasible.
Time-dependent reliability analysis for repairable consecutive-k-out-of-n:F system

In a repairable consecutive system, after the system operates for a certain time, some components may fail, some failed components may be repaired and the state of the system may change. The models developed in the existing literature usually assume that the state of the system varies over time depending on the values of n and k and the state of the system is known. Since the system reliability will vary over time, it is of great interest to analyse the time-dependent system reliability. In this paper, we develop a novel and simple method that utilizes the eigenvalues of the transition rate matrix of the system for the computation of time-dependent system reliability when the system state is known. In addition, the transition performance probabilities of the system from a known state to the possible states are also analysed. Computational results are presented to illustrate the applicability and accuracy of the proposed method.
Characterisation of temporal and regional differences in the elemental fractionation and mobility of urban particulate matter via online sequential extraction

ABSTRACT Numerous diffuse sources contribute in addition to industrial plants to atmospheric particulate matter (PM) concentrations causing concern regarding potential health effects and environmental impacts. Routine monitoring focuses on PM mass and determination of the total concentrations for selected elements. However, assessment of the (eco-)toxicological potential and the spatial distribution as well as the interaction in the environment requires suitable characterisation of the elemental speciation and mobility. Classical off-line sequential extraction techniques have been explored for this purpose but require high effort and were of limited suitability especially for low particle mass sampled on filters. A novel online sequential extraction (OSE) technique was recently developed using low amounts of model dust samples with transient elemental monitoring by inductively coupled plasma mass spectrometry (ICP-MS) to overcome the challenges. However, the application of this method to PM samples was not reported until now. In the current study, the OSE was adapted for application to punches of PM2.5 filter samples to achieve elemental fractionation with minimum manual input, low relative standard deviations and reduced risk of contamination or loss of residual sample material during solvent changes. Four samples from China and seven samples from Germany were exemplary investigated to identify regional and temporal changes in elemental fractionation and to highlight the potential of the OSE method for filter samples. Normalisation of the data as percentage of the aqua regia leachable fraction for each element demonstrated clear differences between the Chinese and the German samples. In particular, fireworks affected samples showed a unique characteristic mobility pattern. In addition, normalisation to the aqua regia leachable Mn content was performed to highlight the combination of the elemental fractionation pattern and the relative abundance between the various investigated samples. Thereby, a major improvement in the classification of the PM samples was achieved. Principal component analysis visualises the observed differences in 2-D plots with clusters of different regional and also partly different temporal samples. The obtained results indicate the potential of OSE for an improved understanding of chemical element patterns of PM samples in future studies.
Adoption of E-commerce in SMEs: the Colombian Case

The few studies in South American developing countries that refer to the adoption of e-commerce in SMEs require knowledge of how this context is presented. The objective of this study addresses this need and seeks to determine the variables that influence the adoption of e-commerce in SMEs in Colombia. The measurement tool (IMAES) was applied using a digital questionnaire; 263 surveys were collected in SMEs and the data were analysed using the partial least squares methodology, validating tool and model. The results found that Colombian SMEs adopt e-commerce because of pressure from senior management, performance expectations, the competitive advantage it offers, and pressure from their customers. This is one of the first studies in the region that empirically analyses the adoption of e-commerce, as well as describing the theoretical framework for this line of research.