Miracle-dz/UniFAR-FTUs huggingface dataset:
Physical Activity Behavior Change Driven by Engagement With an Incentive-Based App: Evaluating the Impact of Sweatcoin

Background Physical inactivity, now the fourth leading cause of death, is a primary element of noncommunicable diseases. Despite a great number of attempts, there is still a lack of effective approaches that can motivate sedentary populations to increase their levels of physical activity over a sustained period. Incentives for exercise can provide an immediate reward for increasing activity levels, but because of limited funding to provide rewards, previous programs using this approach have only shown short-term changes in behavior. Sweatcoin (Sweatco Ltd, UK) is an app-based platform that converts physical movement into virtual currency. The currency can be exchanged for goods and services on their marketplace, providing a continuous incentive to be active. This study investigates the physical activity behavior change observed in Sweatcoin users over a 6-month period of app usage. Objective The aim of this study was to investigate the change in physical activity (measured using daily step count) of a sample of Sweatcoin users, the longevity of the change, and whether this change can be predicted by demographic and other lifestyle variables. Methods Activity data from a sample of 5892 Sweatcoin users were used to analyze daily step count. Activity change was measured in terms of the percentage change in average daily step count for each month after registration, relative to that in the 3 months before using the app. Users were grouped according to having no or negative, moderate, or high activity change. A subset of users completed a questionnaire that allowed differences between groups in terms of activity and demographic status to be investigated using regression analyses. Results Daily step count increased by 19% on average over the 6 months following registration (P<.001). Of the questionnaire respondents, 728 were valid responses. A multinomial logistic regression identified the key drivers of moderate and high activity behavior change relative to no or negative change based on the defined groupings. There was a clear impact of seasonality, with those registering for the app in winter (odds ratio [OR] 4.67; P=.001) and spring (OR 5.05; P=.001) being more likely to show high positive activity behavior change than those registering in summer. More striking were the results identifying those classified as overweight (measured through body mass index [BMI]; OR 1.83; P=.02) and less active (based on a self-reported scale of physical activity; OR 0.88; P=.048), being most likely to show high levels of physical activity change following registration with the app. Conclusions The results highlight that an incentives-based app can induce significant physical activity behavior change, sustained over a 6-month period. Importantly, the results suggest that those typically lacking motivation to exercise (sedentary and high BMI) are most likely to be incentivized to increase their activity levels.
Detection of minimal residual disease in unselected patients with acute myeloid leukemia using multiparameter flow cytometry for definition of leukemia-associated immunophenotypes and determination of their frequencies in normal bone marrow.

BACKGROUND AND OBJECTIVES Detection of minimal residual disease (MRD) by multiparameter flow cytometry is an emerging prognostic factor in patients with acute myeloid leukemia (AML). The present analysis aimed at improving the applicability of this approach to more patients with AML. DESIGN AND METHODS Bone marrow samples from unselected patients with AML at diagnosis and from healthy volunteers were immunophenotyped applying triple-stainings of 31 antigens. Leukemia-associated immunophenotypes were defined by gating on populations displaying an aberrant or infrequent immunophenotype and by applying Boolean algebra. The combination of gates obtained was applied to list mode data files containing measurements of normal bone marrow samples. Dilution experiments of AML samples in normal bone marrow were performed to test the linearity of measurements. RESULTS At least one aberrant/infrequent immunophenotype was identified (median, 2; range, 1-5) in all of 68 analyzed AML patients. The median frequencies of cells displaying an aberrant/infrequent immunophenotype within normal bone marrow ranged from 0.00% to 1.20% (median, 0.07%). Limiting this analysis to only the most sensitive aberrant/infrequent immunophenotype per patient resulted in frequencies of cells displaying an aberrant/infrequent immunophenotype within normal bone marrow ranging from 0.00% to 0.43% (median, 0.05%). Serial dilution experiments confirmed the linearity of measurements (R>0.90 in all cases analyzed). INTERPRETATION AND CONCLUSIONS The application of multiparameter flow cytometry to identify cells displaying an aberrant/infrequent immunophenotype and to quantify MRD is feasible in unselected patients with AML.
Subsidy Estimation: A Survey of Current Practice

This document is a technical manual addressed primarily to those individuals who are interested in preparing estimates of subsidies to particular products or sectors. It draws together the different valuation methods that are used and have been published, mainly by intergovernmental organizations and governments. While for most estimation methods the manual quotes multiple sources, often the approaches do not actually differ fundamentally, and users may simply want to refer to the one that makes most sense to them. In cases where they do differ markedly, users should choose whichever method best serves their purposes and can be implemented with the available data. The manual is also intended to kick-start a dialogue on reconciling differences between methods, providing guidance on when each should be used and establishing best-practice recommendations, with the ultimate goal that a set of international standards is agreed for estimating subsidy elements, and for preparing and using aggregates and derived indicators. For a user-friendly introduction to the manual, explaining which methods should be used to estimate which kinds of subsidies, please see our related policy brief, "A How-to Guide: Measuring subsidies to fossil-fuel producers. "
Stability of hysteretic controlled voltage source converters in a power system

This paper develops a tool for the stability analysis of hysteretic controlled voltage source converters that are connected to a power system. Each VSC is controlled by a state feedback control input to a hysteretic comparator. A suitable model of the converter is first developed by including the state feedback gains and hysteretic switching controller design. The model is then extended to incorporate parallel operation of two VSCs. To consider autonomous operation, droop controllers are incorporated in the model. A linearized model of the system is developed for eigen analysis. It has been shown that the system response predicted by the developed model matches PSCAD simulation results very closely. Since hysteretic control is widely used for commercial converters, the model developed can be used as an analytical tool.
Convergence to Equilibrium in Experimental Markets

The process by which market prices achieve equilibrium is an important topic, as the price formation process is fundamental to applied economic theory. Recently, economists have been applying complex mathematical functions to study the course of market prices convergence to equilibrium. Studies have made progress in modeling the price convergence process in at least one type of experimental market setting, the double auction. The double auction is of interest not only because of its prevalence in many types of real-world markets (e.g., the New York Stock Exchange), but also because of its extensive use in experimental economics. The double auction market is the quickest to reach equilibrium in experiments for virtually every type of supply and demand conditions, even in the presence of a variety of perturbations. Thus, it is a natural starting point for price formation modeling. This paper applies a chaos theory based model to a data set obtained from a series of double auction experiments. We find that the course of convergence to equilibrium is consistent with a deterministic chaotic model. Empirical tests examining a variety of experimental markets confirm similar fractal price patterns consistent with this model.
Arabidopsis amidase 1, a member of the amidase signature family

Amidase 1 (AMI1), a specific indole‐3‐acetamide amidohydrolase, is an Arabidopsis thaliana amidase signature enzyme that catalyzes the synthesis of indole‐3‐acetic acid from indole‐3‐acetamide. Amidase signature family members catalyze a diverse range of enzymatic reactions and are found widespread in nature, for instance in bacteria, mammals, and plants. At the protein level, the family members share a conserved stretch of ≈ 50–130 amino acids, the name‐giving amidase signature. Elucidation of the crystal structures of a mammalian fatty acid amide hydrolase and the bacterial malonamidase E2 revealed an unusual Ser‐cisSer‐Lys catalytic triad in proteins of this family. In addition, other members, such as the amidase from Rhodococcus rhodochrous strain J1 or Sulfolobus solfataricus, seem to use an accessory Cys‐cisSer‐Lys center. AMI1 possesses all conserved amino‐acid residues of the Ser‐cisSer‐Lys triad, but lacks the CX3C motif and therefore the Cys‐cisSer‐Lys catalytic site. Using a set of point‐mutated variants of AMI1 and chemical modifications, we analyzed the relative importance of single amino‐acid residues of AMI1 with respect to substrate conversion. These experiments revealed that a specific serine residue, Ser137, is essential for AMI1 enzymatic activity. We also report structural and functional differences of AMI1 from other amidase signature enzymes.
Estimated average annual rate of change of CD4+ T-cell counts in patients on combination antiretroviral therapy

Background Patients receiving combination antiretroviral therapy (cART) might continue treatment with a virologically failing regimen. We sought to identify annual change in CD4+ T-cell count according to levels of viraemia in patients on cART. Methods A total of 111,371 CD4+ T-cell counts and viral load measurements in 8,227 patients were analysed. Annual change in CD4+ T-cell numbers was estimated using mixed models. Results After adjustment, the estimated average annual change in CD4+ T-cell count significantly increased when viral load was <500 copies/ml (30.4 cells/mm3, 95% confidence interval [CI] 26.6–34.3), was stable when viral load was 500–9,999 copies/ml (3.1 cells/mm3, 95% CI -5.3–11.5) and decreased when viral load was ≥10,000 copies/ml (-14.8 cells/mm3, 95% CI -4.5– - 25.1). Patients taking a boosted protease inhibitor (PI) regimen had more positive annual CD4+ T-cell count changes than patients taking other regimens for any given viral load strata: 30.9 cells/mm3 (95% CI 27.7–34.1) when viral load was <500 copies/ml, 14.2 cells/mm3 (95% CI -2.1–30.4) when viral load was 500–9,999 copies/ml and -19.9 cells/mm3 (95% CI -36.6– -3.3) when viral load was ≥10,000 copies/ml. By contrast, among patients taking a non-nucleoside reverse transcriptase inhibitor (NNRTI)-based regimen, the CD4+ T-cell count significantly decreased when the viral load was 500–9,999 copies/ml (-18.6 cells/mm3, 95% CI -33.8– - 3.5) and decreased at a faster rate when the viral load was ≥10,000 copies/ml (-44.4 cells/mm3, 95% CI -62.0– -26.9; P=0.0012, test for interaction). Conclusions On average, CD4+ T-cell counts did not significantly decrease until the viral load exceeded 10,000 copies/ml in patients treated with a boosted PI-containing cART regimen, but decreased in patients taking an NNRTI-based cART regimen when viral load was 500–9,999 copies/ml.
Ionic currents in response to membrane depolarization in an Aplysia neurone.

1. Action potentials recorded in the soma of R15 neurones in the abdominal ganglia of Aplysia juliana were not suppressed by selective inhibition of either Na or Ca conductance alone. It was necessary to block both conductances to suppress action potentials. 2. Membrane currents generated by step depolarizations of the soma consisted of early transient and delayed steady‐state currents. The early transient current could have one or two components depending on the activating depolarization. 3. The early more rapid component had a reversal potential at +54 mV and the reversal potential changed with extracellular Na concentration in accord with the Nernst equation. It was blocked by substitution of impermeant cations for Na, by TTX and by internal injections of Zn. It was concluded that this component was normally a Na current. 4. The later slower component of the transient current had a reversal potential at about +65 mV and the reversal potential changed with extracellular Ca concentration is accord with the Nernst equation. It was blocked by substitution of Mg for Ca or addition of Mn, Co, Ni or verapamil to the extracellular solution. It was concluded that this component was normally a Ca current. 5. Na and Ca currents were generated at different threshold potentials, Na currents first appearing at about ‐20 mV and Ca currents at ‐5 to 0 mV. 6. The time‐to‐peak of both Na and Ca currents was affected by the holding potential, by the amplitude of the activating depolarization, by temperature and by divalent ion concentration. 7. The peak Na and Ca conductances both increased sigmoidally with increasing depolarization, the maximum Na conductance of 10‐‐15 microS being approximately twice the maximum Ca conductance. Peak conductances for Na and Ca reached half‐maximum at ‐8 and +3 mV, respectively. 8. The amplitude of the delayed steady‐state current could be varied by changing the extracellular K+ ion concentration or by adding tetraethylammonium to the extracellular solution. The reversal potential for 'tail currents' was ‐67 mV and shifted 18 mV when the extracellular K concentration was doubled. It was concluded that the delayed steady‐state current was K current. 9. With prolonged depolarizations, K current decayed with a time constant of the order of 1 sec. Peak K conductance increased with increasing depolarization with the half‐maximum occurring at a potential more positive than +20 mV. The maximum rate of fractional activation of K conductance was independent of the amplitude of the clamp step.
MicroRNA-27a-mediated repression of cysteine-rich secretory protein 2 translation in asthenoteratozoospermic patients

Cysteine-rich secretory protein 2 (CRISP2) is an important protein in spermatozoa that plays roles in modulating sperm flagellar motility, the acrosome reaction, and gamete fusion. Spermatozoa lacking CRISP2 exhibit low sperm motility and abnormal morphology. However, the molecular mechanisms underlying the reduction of CRISP2 in asthenoteratozoospermia (ATZ) remain unknown. In this study, low expression of CRISP2 protein rather than its mRNA was observed in the ejaculated spermatozoa from ATZ patients as compared with normozoospermic males. Subsequently, bioinformatic prediction, luciferase reporter assays, and microRNA-27a (miR-27a) transfection experiments revealed that miR-27a specifically targets CRISP2 by binding to its 3′ untranslated region (3′-UTR), suppressing CRISP2 expression posttranscriptionally. Further evidence was provided by the clinical observation of high miR-27a expression in ejaculated spermatozoa from ATZ patients and a negative correlation between miR-27a expression and CRISP2 protein expression. Finally, a retrospective follow-up study supported that both high miR-27a expression and low CRISP2 protein expression were associated with low progressive sperm motility, abnormal morphology, and infertility. This study demonstrates a novel mechanism responsible for reduced CRISP2 expression in ATZ, which may offer a potential therapeutic target for treating male infertility, or for male contraception.
Improving Pedestrian Recognition using Incremental Cross Modality Deep Learning

Late fusion schemes with deep learning classification patterns set up with multi-modality images have an essential role in pedestrian protection systems since they have achieved prominent results in the pedestrian recognition task. In this paper, the late fusion scheme merged with Convolutional Neural Networks (CNN) is investigated for pedestrian recognition based on the Daimler stereo vision data sets. An independent CNN-based classifier for each imaging modality (Intensity, Depth, and Optical Flow) is handled before the fusion of its probabilistic output scores with a Multi-Layer Perceptron which provides the recognition decision. In this paper, we set out to prove that the incremental cross-modality deep learning approach enhances pedestrian recognition performances. It also outperforms state-of-the-art pedestrian classifiers on the Daimler stereo-vision data sets.
Elimination kinetics of circulating antigens and immune complexes. III. Elimination of intravenously injected model antigens and soluble IgG immune complexes in mice.

The blood elimination kinetics of model antigens, i.e. dinitrophenyl-conjugated human serum albumin (DNP-HSA) preparations, and soluble immune complexes (IgG-anti-DNP + DNP-HSA) were analysed by the aid of a multicompartment model, allowing estimation of tissue uptake and degradation of the immune complexes (ICs). The haematocrit values remained stable after intravenous injection of the ICs in mice. Despite this fact, the blood clearance kinetics were excellently described by three exponential functions. This indicates that the rapid initial elimination of the ICs from the blood was not the result of IC-induced capillary leakage, but rather of rapid initial binding of the complexes to different tissue structures. We also present results indicating that the elimination of circulating complexes/protein aggregates is governed less by their size than by other physical/chemical properties.
CMedTEX: A Rule-based Temporal Expression Extraction and Normalization System for Chinese Clinical Notes

Time is an important aspect of information and is very useful for information utilization. The goal of this study was to analyze the challenges of temporal expression (TE) extraction and normalization in Chinese clinical notes by assessing the performance of a rule-based system developed by us on a manually annotated corpus (including 1,778 clinical notes of 281 hospitalized patients). In order to develop system conveniently, we divided TEs into three categories: direct, indirect and uncertain TEs, and designed different rules for each category of them. Evaluation on the independent test set shows that our system achieves an F-score of93.40% on TE extraction, and an accuracy of 92.58% on TE normalization under "exact-match" criterion. Compared with HeidelTime for Chinese newswire text, our system is much better, indicating that it is necessary to develop a specific TE extraction and normalization system for Chinese clinical notes because of domain difference.
A return to spatial proximity: combining global suppliers with local subcontractors

Over the last decades, the literature has extensively analysed the advantages of global supply networks, where spatial proximity becomes less important as a supplier selection criterion. However, in recent years a growing interest is rising on firms that are reshoring their operations, that is, moving their manufacturing back into their home countries. In this paper we aim to contribute to this field of research by analysing the partial reshoring of a firm that has recently modified the location of some of its suppliers to increase the spatial proximity with them. Our longitudinal case study suggests that the choice of increasing spatial proximity with some suppliers is the result of a process of strategic alignment of the portfolio of vertical relationships with a new business strategy that focuses on complex products characterised by a strong degree of customisation. The result of this process is a new global value chain, where global suppliers coexist with local suppliers and ICT are extensively used, deeply modifying the traditional value of spatial proximity and, thus, allowing the focal firm to act simultaneously at different spatial scales.
Predicting Online Islamophobic Behavior after #ParisAttack

The tragic Paris terrorist attacks of November 13, 2015 sparked a massive global discussion on Twitter and other social media, with millions of tweets in the ﬁrst few hours after the attacks. Most of these tweets were condemning the attacks and showing support for Parisians. One of the trending debates related to the attacks concerned possible association between Muslims and terrorism, which resulted in a world-wide debate between those attacking and those defending Islam. In this paper, we use this incident as a case study to examine using online social network interactions prior to an event to predict what attitudes will be expressed in response to the event. Speciﬁcally, we focus on how a person’s online content and network dynamics can be used to predict future attitudes and stance in the aftermath of a major event. In our study, we collected a set of 8.36 million tweets related to the Paris attacks within the 50 hours following the event, of which we identiﬁed over 900k tweets mentioning Islam and Muslims. We then quantitatively analyzed users’ network interactions and historical tweets to predict their attitudes towards Islam and Muslims. We provide a description of the quantitative results based on the tweet content (hashtags) and network interactions (retweets, replies, and mentions). We analyze two types of data: (1) we use post-event tweets to learn users’ stated stance towards Muslims based on sampling methods and crowd-sourced annotations; and (2) we employ pre-event interactions on Twitter to build a classi-ﬁer to predict post-event stance. We found that pre-event network interactions can predict attitudes towards Muslims
The Emotional Experience of Motherhood in Planned Lesbian Families in the South African Context: “… Look How Good a Job I’m Doing, Look How Amazing We Are”

ABSTRACT This article focuses on lesbian mothersʼ emotional experience of motherhood. It forms part of a larger qualitative and exploratory study with 10 lesbian couples in South Africa on their lived experience of planned motherhood. The study is located in a feminist phenomenological framework. Semi-structured interviews were conducted and interview transcripts were analyzed using thematic analysis. Participants described many different emotions associated with new motherhood: hope, joy, love, anxiety, helplessness, exhaustion, and feeling companionship and togetherness as well as feeling compromised and deprived. Mothers described these emotions but also focused on the development of a new identity, that of being a mother.
From Example Study to Problem Solving: Smooth Transitions Help Learning

Abstract Research has shown that it is effective to combine example study and problem solving in the initial acquisition of cognitive skills. Present methods for combining these learning modes are static, however, and do not support a transition from example study in early stages of skill acquisition to later problem solving. Against this background, the authors proposed a successive integration of problem-solving elements into example study until the learners solved problems on their own (i.e., complete example increasingly more incomplete examples problem to-be-solved). The authors tested the effectiveness of such a fading procedure against the traditional method of using example-problem pairs. In a field experiment and in 2 more controlled laboratory experiments, the authors found that (a) the fading procedure fosters learning, at least when near transfer performance is considered; (b) the number of problem-solving errors during learning plays a role in mediating this effect; and (c) it is more favorable to fade out worked-out solution steps in a backward manner (omitting the last solution steps first) as compared with a forward manner (omitting the first solution steps first).