Miracle-dz/UniFAR-FTUs huggingface dataset:
Prevalence and Associated Factors of Urinary Incontinence among Elderly in Pekanbaru, Indonesia

Background: The proportion of the elderly in Riau Province was 4.8% higher than that (4.2%) in 2011. Urinary incontinence (UI) is a common health problem among the elderly. This study aims to determine the prevalence and associated factors for UI among the elderly (≥60 years). Methods: This cross-sectional study was conducted in 20 public health centers in Pekanbaru City in 2018. A total of 351 elderly meeting the inclusion criteria were enrolled. Gender, age, education, occupation, marital status, obesity, depression, cognitive impairment, smoking status, history of chronic cough, and history of lower abdominal surgery served as the independent variables and UI as the dependent variable. Data were collected through interviews facilitated by staff trained by the research team. Data were analyzed using multiple logistic regression with a predictive factor model to assess the relationship between the independent and dependent variables. Results: The prevalence of UI was 6%, and the associated factors were chronic cough (prevalence odds ratio = 17.661; 95% CI: 6.380–48.884). Gender, age, education, and lower abdominal surgery were the confounding factors. Conclusions: Health workers at the public health center of Pekanbaru should educate the community and the elderly about the potential causes, prevention, and treatment of UI.
SEISMIC RISK COMPARISON BETWEEN 1- AND 2-STORY HOUSES FOR PERFORMANCE-BASED EARTHQUAKE ENGINEERING

In regional seismic risk assessments, the building stock is typically divided into a number of building categories, where, for each category, an index structure is used to represent the performance of the whole group. Thus, grouping buildings with significantly different seismic performances into a single class may result in important overor underestimations of the regional risk. Historically 1and 2-story single-family dwellings have been grouped into a single category for both insurance purposes, and regional risk assessments. This paper evaluates the relative seismic risk between 1and 2-story houses using simple models and first principles. For this purpose, simplified lumped-mass models are used to assess the influence of the fundamental period of vibration, lateral stiffness in each story, mass distribution, and nonlinear effects, on the seismic response of 1and 2-story houses. Results demonstrate that, in practically all cases, 2-story houses concentrate lateral deformation demands on their first stories, and that these demands are significantly larger than those in 1-story dwellings. Therefore, there are significantly higher probabilities of damage and expected losses in 2-story houses than in 1-story houses. This conclusion is perfectly consistent with the damage observed after different historical earthquakes, where 2-story houses have exhibited poorer performance than their 1-story counterparts. This work suggests that grouping 1and 2-story houses into a single class, as has been typically done for many years, is conceptually wrong. Consequently, future building classification systems for regional risk assessments should separate these types of structures.
Graph Convolutional Networks for Friend Recommendation

As more ethical concerns emerge about the use of user data by social networks, it is ever more important to respect user’s privacy. However, many recommendations algorithms for ads and friends often exploit user data. In this study, we were able to do link prediction on a social graph with only unsupervised features between nodes. We passed these features into a graph convolutional neural network to get node embeddings and inputted in pairs of node embeddings to a full connected network to receive link predictions. We were able to achieve a competitive mAP@10 of 67% without using any user data other than their current friends.
Monetary Policy Approach to Headline Inflation Control in Nigeria: Evidence from 1985-2018

Monetary policy remains one of the channels for controlling high inflation. Effective control of headline inflation using monetary policy measures depends on the degree of relationship that exists between the variables. In the light of this, the paper explores the relation between monetary policy and headline inflation with the aim of determining the effectiveness of monetary policy measures in curbing high headline inflation in Nigeria. The series employed are stationary at level and first difference respectively, after testing them for unit roots using Phillips-Perron and Zivot-Andrews structural break consistent unit root tests. The study adopts the Autoregressive distributed lag (ARDL) approach, Bound test, and Error Correction Model (ECM) for empirical analyses of the variables. The paper establishes the following: (a) exchange rate and headline inflation share strong negative relation both in the short-term and longterm; (b) Treasury bill rate exerts statistically significant positive influence on inflation in the long-run; and (c) strong interaction exists between deposit rate and headline inflation in the shortrun. We also find cointegrating relationships between monetary policy and headline inflation in Nigeria.
Inverting Facial Embeddings with GANs

Compression and regeneration of images is an extremely relevant task in the modern age. We seek to recreate images of people’s faces by only storing a vector (embedding) that captures their identity. We implement many methods to invert this embedding into the face in the original image. Using a Generative Adversarial Network (GAN) to generate faces, we propose a greedy search algorithm on the latent vector space of the GAN to ﬁnd a matching face. Our process yields latent vectors that generate images capable of fooling FaceNet [13], a state-of-the-art face recognition system.
Dimensional change of impression materials for dental prothesis using different measuring methods

The aim of this study was to verify the effectiveness of alternative techniques for measuring the linear dimensional change of molds obtained by different impression materials. A stainless-steel die containing three lines was used to get the impressions. The impression materials were handled according to the manufacturers' instructions. After gelation/polymerization time, the molds (n=12) were stored for 30 minutes and the lines were subsequently measured using: a microscope (Olympus Measuring Microscope STM; Olympus Optical Co) with a 30x magnification (MM, control group), a digital caliper (Mitutoyo Digimatic; Kawasaki) (DC) and digitization using a digital camera (Canon EOS Rebel 3Ti; Canon) (DI). For each mold, a mean of the length of the lines was obtained. For each impression material, the difference in the length between the metallic matrix and the mold was considered as linear dimensional change (%). The data were submitted to the non-parametric Kolmogorov-Smirnov test, followed by one-way Analysis of Variance (ANOVA) for each material, and the means were compared by the Tukey test (α=0.05). The DI group promoted values of dimensional accuracy without significant differences with the control group (MM), except for the putty-body condensation silicone. The DC group showed significant differences for MM and DI groups for all impression materials tested. The DI group showed to be a reliable methodology (Standard error of the mean <10%) to measure the linear dimensional change of all impression materials. The DI group presented molds with linear dimensional change values without significant differences with MM group, except for the putty-body addition silicone. The digitization is a reliable methodology to evaluate the linear dimensional changes of molds made with impression materials, except for the putty-body elastomeric impression materials. Key words: Dimensional Measurement Accuracy; Dental impression materials; Microscopy
IDENTIFICATION OF LIMIT STATES FOR DEVELOPING FRAGILITY CURVES OF CONCRETE BUILDINGS USING SHAKE TABLE TESTING

Shake table testing is conducted in this study to support the selection of performance criteria and to verify the inelastic modeling approach for the vulnerability assessment of RC buildings. A shear vulnerable RC specimen representing the framing system of a substandard building is subjected to a far-field earthquake record with four increasing intensity levels. The first indication of shear failure is detected in columns at eight times the design PGA, which is well predicted by the adopted shear strength approaches. The consistent results obtained from the shake table testing and dynamic response simulations verify the adopted inelastic modeling approach and provide insights into the suitable shear strength models for vulnerability assessment. A diverse range of multi-story buildings that represent pre-seismic code RC frame and shear wall structures is then assessed, considering the verified modeling approach using the shake table experiment and shear failure prediction models that account for the impacts of flexural ductility and shear-axial interaction on shear supply. Based on the dynamic response simulations of five reference buildings under the effect of far-field and near-source earthquake records, it is concluded that the influence of shear assessment on the performance limit states is observable, particularly for relatively medium-rise shear wall structures. The damage probabilities of pre-seismic code structures in the study region tend to increase with decreasing the building height. Therefore, earthquake scenario-structure-based performance criteria are selected and used to derive a wide range of analytically-derived experimentally-verified fragility relationships for the reference buildings under the effect of different earthquake scenarios.
Hidden Homelessness in Germany: Gathering Evidence on Couch Surfing in Telephone Surveys

\ Abstract_ The article provides survey evidence on hidden homelessness in Germany. I use an indirect approach to survey those who live with friends, family or other people as so-called sofa surfers or couch surfers. The data come from three multi-topic, randomly sampled telephone surveys, which were carried out in 2019 and early 2020. The survey respondents reported whether they had hosted homeless friends, family or other persons. The results show that within a period of 12 months, about 3 per cent accommodated a person for at least one night. The results are consistent over three independent samples and the socio-demographic profi le of the hidden homeless people fits well with results of previous research on other countries or using other approaches. I discuss potential caveats of telephone surveys with regard to potential bias in estimates of the prevalence of couch surfing and options how to assess and minimise bias. An alternative to telephone surveys would be to include questions on couch surfing and other forms of hidden homelessness in thematic modules on housing in recurrent household surveys. The present study shows the basic feasibility of collecting data on hidden homelessness from respondents in population surveys.
Social Distancing in the Context of COVID-19 Anxiety: A Social Cognitive Approach

As the impact of COVID-19 continues, engagement in social distancing is essential. Using Social Cognitive Theory, the current study examined the unique roles of COVID-19 anxiety and self-efficacy on the relationships between information-seeking and risk perception as predictors of social distancing intention. A convenience sample of 960 adults (M = 37.81 years, SD = 11.65) completed an author-designed online survey. Participants completed measures on behavioral intention, information-seeking, risk perception, COVID-19 anxiety, and self-efficacy. Moderated mediations examined the theoretically proposed relationships among the variables. COVID-19 anxiety moderated the relationship between risk perception and self-efficacy, but not the association between information-seeking and self-efficacy. Self-efficacy mediated the role of risk perception and information-seeking on behavioral intent. Self-efficacy was strongly associated with social distancing intention, consistent with previous research and underscoring the need to identify factors influencing self-efficacy in the context of a pandemic. Risk perception and information-seeking both directly and indirectly related to intention to social distance, with COVID-19 anxiety dampening the influence of perceived risk on self-efficacy. The roles of risk perception and information-seeking in relation to self-efficacy suggest the need to adequately describe risk, reduce pandemic-related anxiety, and provide accurate, transparent information.
Tumour immunity The lymphoid system and experimental neoplasias

In the last decade or so immunologists have left the test tubes in which their serological mysteries were enacted and turned to consider the cells which are involved in immune responses. The resultant cellular immunologists have made discoveries which ought to have lent precision to the quite old notion that the immune mechanism is part of the natural defence system which, in vertebrates, can operate against malignant cells. I intend first to summarize some of the salient findings of the cellular immunologists and secondly to consider a few examples of experimental interaction between the new-look lymphoid system and neoplastic cell populations.
Moodle and Problem-Based Learning: Pedagogical Designs and Contradictions in the Activity System

This paper presents an empirical study and related activity system analysis regarding the implementation and use of Moodle specifically, and learning management systems in general, in problem-based learning. The research involved an exploration of the characteristics that defined use of Moodle at a Danish university, the reasons why Moodle was or was not used in specific contexts and the way in which Moodle use was perceived by students. Some of the obstacles and challenges identified through this study highlighted the need for a deeper analysis of the elements that characterised the activity system(s) and their contradictions in this contextual setting, leading to a consideration of possible implications for change processes. The investigation consisted of a literature review, a survey of 345 students regarding their experiences with Moodle in conjunction with a nomination for the best Moodle course, an analysis of the 178 nominated courses and interviews with four university teachers about their use of Moodle. This examination revealed that many existing Moodle activities at Aalborg University focus more on sharing information and teaching materials and less on the students’ problem-based learning activities and projects. This finding is intriguing, as use of Moodle does not reflect that problem-based learning comprises the pedagogical foundation of Aalborg University’s academic programme. The investigation uncovered several reasons for the lack of focus on problem-based learning in Moodle structures and content and explored them through the contradictions identified within the activity systems and between the double contextual frame surrounding the interacting activity system.
Margins of postural stability in Parkinson’s disease: an application of control theory

Introduction: Postural instability is a restrictive feature in Parkinson’s disease (PD), usually assessed by clinical or laboratory tests. However, the exact quantification of postural stability, using stability theorems that take into account human dynamics, is still lacking. We investigated the feasibility of control theory and the Nyquist stability criterion—gain margin (GM) and phase margin (PM)—in discriminating postural instability in PD, as well as the effects of a balance-training program. Methods: Center-of-pressure (COP) data of 40 PD patients before and after a 4-week balance-training program, and 20 healthy control subjects (HCs) (Study1) as well as COP data of 20 other PD patients at four time points during a 6-week balance-training program (Study2), collected in two earlier studies, were used. COP was recorded in four tasks, two on a rigid surface and two on foam, both with eyes open and eyes closed. A postural control model (an inverted pendulum with a Proportional-integral-derivative (PID) controller and time delay) was fitted to the COP data to subject-specifically identify the model parameters thereby calculating |GM| and PM for each subject in each task. Results: PD patients had a smaller margin of stability (|GM| and PM) compared with HCs. Particularly, patients, unlike HCs, showed a drastic drop in PM on foam. Clinical outcomes and margins of stability improved in patients after balance training. |GM| improved early in week 4, followed by a plateau during the rest of the training. In contrast, PM improved late (week 6) in a relatively continuous-progression form. Conclusion: Using fundamental stability theorems is a promising technique for the standardized quantification of postural stability in various tasks.
Acute Oral and Contact Toxicity of Three Plant
Protection Products to Adult Solitary
Bees Osmia bicornis

Bee pollinators decline worldwide over the last decades mainly due to the widespread use of pesticides. However, the data on wild bee sensitivity to pesticides are scarce. As it may not be possible to stop using pesticides at the moment due to a growing food demand, we need to make every effort to ensure that they are used in a way that do not jeopardize pollinator populations. We tested the toxicity of three agrochemicals, namely Dursban 480 EC with chlorpyrifos as active ingredient (a.i.), Sherpa 100 EC (a.i. cypermethrin), and Mospilan 20 SP (a.i. acetamiprid), to female Osmia bicornis through oral and contact exposures. The estimated LC50s at infinite-time were lower than concentrations recommended for field application for Dursban in both exposure routes, whereas in case of Sherpa and Mospilan the values were lower for oral exposure only. Regardless of the exposure route, high mortality in less than 24 hours was observed in Dursban-treated bees at a fraction of concentration actually used by farmers in the field, indicating high toxicity of this product to O. bicornis. Therefore, some commonly used insecticides may cause unacceptable effects to pollinators even when applied in the field according to recommendations, indicating the urgent need for revising current pesticide usage regulations.
Deep Recurrent Semi-Supervised EEG Representation Learning for Emotion Recognition

EEG-based emotion recognition often requires sufficient labeled training samples to build an effective computational model. Labeling EEG data, on the other hand, is often expensive and time-consuming. To tackle this problem and reduce the need for output labels in the context of EEG-based emotion recognition, we propose a semi-supervised pipeline to jointly exploit both unlabeled and labeled data for learning EEG representations. Our semi-supervised framework consists of both unsupervised and supervised components. The unsupervised part maximizes the consistency between original and reconstructed input data using an autoencoder, while simultaneously the supervised part minimizes the cross-entropy between the input and output labels. We evaluate our framework using both a stacked autoencoder and an attention-based recurrent autoencoder. We test our framework on the large-scale SEED EEG dataset and compare our results with several other popular semi-supervised methods. Our semi-supervised framework with a deep attention-based recurrent autoencoder consistently outperforms the benchmark methods, even when small sub-sets (3%, 5% and 10%) of the output labels are available during training, achieving a new stateof-the-art semi-supervised performance.
The Poissonian Origin of Power Laws in Solar Flare Waiting Time Distributions

In this study we aim for a deeper understanding of the power-law slope, α, of waiting time distributions. Statistically independent events with linear behavior can be characterized by binomial, Gaussian, exponential, or Poissonian size distribution functions. In contrast, physical processes with nonlinear behavior exhibit spatiotemporal coherence (or memory) and “fat tails” in their size distributions that fit power-law-like functions, as a consequence of the time variability of the mean event rate, as demonstrated by means of Bayesian block decomposition in the work of Wheatland et al. In this study we conduct numerical simulations of waiting time distributions N(τ) in a large parameter space for various (polynomial, sinusoidal, Gaussian) event rate functions λ(t), parameterized with an exponent p that expresses the degree of the polynomial function λ(t) ∝ t p . We derive an analytical exact solution of the waiting time distribution function in terms of the incomplete gamma function, which is similar to a Pareto type II function and has a power-law slope of α = 2 + 1/p, in the asymptotic limit of large waiting times. Numerically simulated random distributions reproduce this theoretical prediction accurately. Numerical simulations in the nonlinear regime (p ≥ 2) predict power-law slopes in the range of 2.0 ≤ α ≤ 2.5. The self-organized criticality model yields a prediction of α = 2. Observations of solar flares and coronal mass ejections (over at least a half solar cycle) are found in the range of α obs ≈ 2.1–2.4. Deviations from strict power-law functions are expected due to the variability of the flare event rate λ(t), and deviations from theoretically predicted slope values α occur due to the Poissonian weighting bias of power-law fits.
Number of visits in arbitrary sets for $\phi$-mixing dynamics

It is well-known that, for sufficiently mixing dynamical systems, the number of visits to balls and cylinders of vanishing measure is approximately Poisson compound distributed in the Kac scaling. Here we extend this kind of results when the target set is an arbitrary set with vanishing measure in the case of φ-mixing systems. The error of approximation in total variation is derived using Stein-Chen method. An important part of the paper is dedicated to examples to illustrate the assumptions, as well as applications to temporal synchronisation of g-measures.
Dynamo instabilities in plasmas with inhomogeneous chiral chemical potential

We study the dynamics of magnetic fields in chiral magnetohydrodynamics, which takes into account the effects of an additional electric current related to the chiral magnetic effect in high energy plasmas. We perform direct numerical simulations, considering weak seed magnetic fields and inhomogeneities of the chiral chemical potential mu_5 with a zero mean. We demonstrate that a small-scale chiral dynamo can occur in such plasmas if fluctuations of mu_5 are correlated on length scales that are much larger than the scale on which the dynamo growth rate reaches its maximum. Magnetic fluctuations grow by many orders of magnitude due to the small-scale chiral dynamo instability. Once the nonlinear backreaction of the generated magnetic field on fluctuations of mu_5 sets in, the ratio of these scales decreases and the dynamo saturates. When magnetic fluctuations grow sufficiently to drive turbulence via the Lorentz force before reaching maximum field strength, an additional mean-field dynamo phase is identified. The mean magnetic field grows on a scale that is larger than the integral scale of turbulence after the amplification of the fluctuating component saturates. The growth rate of the mean magnetic field is caused by a magnetic alpha effect that is proportional to the current helicity. With the onset of turbulence, the power spectrum of mu_5 develops a universal k^(-1) scaling independently of its initial shape, while the magnetic energy spectrum approaches a k^(-3) scaling.