Miracle-dz/UniFAR-FTUs huggingface dataset:
Pain in German physiotherapists: an analysis of pain prevalence and analgesics intake

Abstract Background Healthcare professionals of different occupations report pain, in particular back pain. It is known that the handling of patients and standing for long periods of time – like physiotherapists do, as well as working in bent posture – are causes of back pain. A high prevalence of low back pain (LBP) in German physiotherapists is to be expected. Objective To determine pain point prevalence, severity of pain, type of pain (acute, chronic, recurrent), most affected body locations and extent of analgesics intake in German physiotherapists. Method This was a nationwide online survey with German physiotherapists. Univariable and multivariable methods were applied to identify associations between sociodemographic variables and pain, type of pain and pain location as well as analgesic intake by type of pain. In addition, severity of pain by type was examined using the Kruska-Wallis Test. Results A total of 550 physiotherapists were included in the analysis. Prevalence of pain was 63.09 % (acute: 4.18 %, chronic: 15.27 %, recurrent: 43.64 %). Most frequently mentioned pain locations were lumbar spine (49.27 %), cervical spine (48.39 %) and head (40.47 %). Participants with chronic pain reported a higher pain severity than physiotherapists with recurrent pain. Analgesics were used by 35.29 % of study participants with pain. Participants with chronic pain indicated a significantly higher probability of using analgesics compared to physiotherapists with recurrent pain. Conclusion This study indicates a high prevalence of pain and analgesics intake in participating physiotherapists. Therefore, measures are needed to reduce pain in German physiotherapists.
Implementing Privacy-Preserving Genotype Analysis with Consideration for Population Stratification

In bioinformatics, genome-wide association studies (GWAS) are used to detect associations between single-nucleotide polymorphisms (SNPs) and phenotypic traits such as diseases. Significant differences in SNP counts between case and control groups can signal association between variants and phenotypic traits. Most traits are affected by multiple genetic locations. To detect these subtle associations, bioinformaticians need access to more heterogeneous data. Regulatory restrictions in cross-border health data exchange have created a surge in research on privacy-preserving solutions, including secure computing techniques. However, in studies of such scale, one must account for population stratification, as under- and over-representation of sub-populations can lead to spurious associations. We improve on the state of the art of privacy-preserving GWAS methods by showing how to adapt principal component analysis (PCA) with stratification control (EIGENSTRAT), FastPCA, EMMAX and the genomic control algorithm for secure computing. We implement these methods using secure computing techniques—secure multi-party computation (MPC) and trusted execution environments (TEE). Our algorithms are the most complex ones at this scale implemented with MPC. We present performance benchmarks and a security and feasibility trade-off discussion for both techniques.
Elliptic Array Luminescent Solar Concentrators for Combined Power Generation and Microalgae Growth

The full utilization of broadband solar irradiance is becoming increasingly useful for applications such as long-term space missions, wherein power generation from external sources and regenerative life support systems are essential. Luminescent solar concentrators (LSCs) can be designed to separate sunlight into photosynthetically active radiation (PAR) and non-PAR to simultaneously provide for algae cultivation and electric power generation. However, the efficiency of LSCs suffers from high emission losses. In this work, we show that by shaping the LSC in the form of an elliptic array, rather than the conventional planar configuration, emission losses can be drastically reduced to the point that they are almost eliminated. Numerical results, considering the combined effects of emission, transmission and surface scattering losses show the optical efficiency of the elliptic array LSC is 63%, whereas, in comparison, the optical efficiency for conventional planar LSCs is 47.2%. Further, results from numerical simulations show that elliptic array luminescent solar concentrators can convert non-PAR and green-PAR to electric power with a conversion efficiency of ~17% for AM1.5 and 17.6% for AM0, while transmitting PAR to an underlying photobioreactor to support algae cultivation.
Towards practice research in ethnomusicology

ABSTRACT This paper argues for ethnomusicologists to begin using performance not just as a tool to understand the social and cultural field, but to use music and dance as methods in ‘translational’ ethnomusicology that focuses upon the translation and communication of artistic performance aesthetics and to theorise a space for research outcomes that are sited in original performative knowledge, explored, produced and delivered through performance itself. The paper briefly surveys some of the key historical discussions of musical performance in/as research and the epistemological challenges that surround a methodologically defined field such as ethnomusicology where there is no central musical canon. The paper introduces the concept of ‘emic resistance’ where the researcher–performer resists translating their non-verbal, somatic aesthetic musical knowledge into text. The paper concludes by drawing on some of the most recent developments in both ethnomusicological and closely related performance-analytical scholarship to propose a translational model for practice research in ethnomusicology.
Improving Wheelset Stability of Railway Vehicles by Using an H∞/LPV Active Wheelset System

The complexity of railway vehicle structures has been part of an evolutionary process for almost two hundred years. Challenges such as increased weight, increased maintenance, higher costs and energy consumption have become common. The vision for future railway vehicles is to reduce complexity, hence enable simpler structures and reduce maintenance and cost, and of course various research challenges arise from this. In fact, a number of papers in the railway engineering literature have presented practical ways to control steering of railway vehicles to improve performance. The model of the railway wheelset is highly nonlinear, mainly due to the nature of the wheelset structure and the related wheel-rail contact forces involved during operation. In this paper, the simplest design in terms of retrofitting, the actuated solid-axle wheelset is considered, we investigate actively controlled wheelsets from a Linear Parameter Varying (LPV) control aspect. We use the grid-based LPV approach to synthesize the H∞ / LPV controller, which is self-scheduled by the forward velocity, as well as the longitudinal and lateral creep coefficients. The aim of the controller is to reduce the lateral displacement and yaw angle of the wheelset. Simulation results show that the proposed controller ensures the achievement of the above targets in the considered frequency domain up to 100 rad/s.
Brazilian Portuguese

The aim of this article is twofold. In the first place, we present evidence that the syntactic change towards overt pronominal subjects observed in Brazilian Portuguese is not a stable phenomenon; rather, our empirical results allow to follow the parametric change in course and to identify the progressive loss of crucial properties related to ‘consistent’ null subject languages. The contrastive analysis with European Portuguese shows the stronger and the weaker structural contexts in this continuous battle towards the implementation of overt pronouns. Personal sentences (with definite and ‘indefinite’ – arbitrary and generic – subjects, usually referred as “impersonal”) are analyzed in more detail than those we consider impersonal sentences, which include a variety of structures, with climate, existential and unaccusative verbs, . They are, however, shown to have been deeply affected by the re-setting of the value of the Null Subject Parameter. Then, we will briefly compare Brazilian Portuguese with Finnish null subjects to conclude that Brazilian Portuguese does not seem to fit the group of the so called ‘partial’ null subject languages, which seem to exhibit null subjects in very restricted contexts, have a lexical expletive in apparent variation with null and generic subjects as well as in impersonal sentences, when it seems to be merged to avoid a verb-initial sentence.
The role of spatial distribution for growth and survival of juvenile cod Gadus morhua in the Barents Sea

While the importance of early life survival and growth variations for population dynamics is well documented, there is still a relatively limited understanding of how survival and growth is affected by the species’ spatial distribution. Using Barents Sea spatial bottom survey data (1994–2018), we study the spatiotemporal variability of the juvenile Atlantic cod (Gadus morhua) growth and survival. We used indices of the spatial distribution of juvenile cod at age-1 to study the role of distribution for the change in abundance and mean body size through their second winter of life (from age-1 to age-2). Over the 24 years analysed, we found that the location where the age-1 cod are in the Barents Sea matters for their growth and survival. We found that year-classes growing up in the western Barents Sea have higher mortality but faster growth than year-classes distributed farther east. Our results indicate that the biotic and abiotic conditions encountered at the settlement location may influence the spatial survival and growth of age-1 cod and subsequently the population dynamics. Our results underscore the importance of distribution for survival and growth early in life and by providing this essential information has implications for stock assessment and spatial fisheries management.
Optimal Location and Sizing of DGs in DC Networks Using a Hybrid Methodology Based on the PPBIL Algorithm and the VSA

In this paper, we propose a master–slave methodology to address the problem of optimal integration (location and sizing) of Distributed Generators (DGs) in Direct Current (DC) networks. This proposed methodology employs a parallel version of the Population-Based Incremental Learning (PPBIL) optimization method in the master stage to solve the location problem and the Vortex Search Algorithm (VSA) in the slave stage to solve the sizing problem. In addition, it uses the reduction of power losses as the objective function, considering all the constraints associated with the technical conditions specific to DGs and DC networks. To validate its effectiveness and robustness, we use as comparison methods, different solution methodologies that have been reported in the specialized literature, as well as two test systems (the 21 and 69-bus test systems). All simulations were performed in MATLAB. According to the results, the proposed hybrid (PPBIL–VSA) methodology provides the best trade-off between quality of the solution and processing times and exhibits an adequate repeatability every time it is executed.
Approximate Hardware Architecture for the Interpolation Filters of Versatile Video Coding

— The new Versatile Video Coding (VVC) standard was recently developed to improve compression efﬁciency of previous video coding standards and to support new applications. The compression efﬁciency gain was achieved in the standardization process at the cost of an increase in the computational complexity of the encoder algorithms, which leads to the need to develop hardware accelerators and to apply approximate computing techniques to reach the performance and power dissipation required for systems that encode video. This work proposes the implementation of an approximate hardware architecture for interpolation ﬁlters deﬁned in the VVC standard targeting fractional motion estimation requirements of real-time processing of high resolution videos scenario. The architecture includes four ﬁlter cores in parallel, each one generating 15 fractional per clock cycle, so it calculates 60 fractional pixels in parallel. Each ﬁlter core is based on approximating the original 8-tap and 7-tap interpolation ﬁlters deﬁned in the VVC standard to 6-tap interpolation ﬁlters, and by applying Multiple Constant Multiplication (MCM) algorithm to optimize ﬁlter datapaths. The architecture is able to process up to 2560 × 1600 pixels videos at 30 fps with power dissipation of 23.9 mW when operating at a frequency of 522 MHz, with an average compression efﬁciency degradation of only 0.41% compared to default VVC video encoder software conﬁgura-tion
Who and Why? Understanding Rural Out-Migration in Uganda

Rural–urban migration in developing countries is considered to be a key process for sustainable development in the coming decades. On the one hand, rural–urban migration can contribute to the socioeconomic development of a country. On the other hand, it also leads to labor transfer, brain-drain in rural areas, and overcrowded cities where planning is lagging behind. In order to get a better insight into the mechanisms of rural–urban migration in developing countries, this paper analyzes motivations for rural–urban migration from the perspective of rural households in Uganda. A total of 1015 rural households located in southwestern Uganda were surveyed in 2019. A total of 48 percent of these households reported having at least one out-migrant. By means of logistic regression modeling, the likelihood for rural out-migration was assessed using household- and community-level socioeconomic characteristics as predictors. The results show that most out-migrants are from relatively wealthy households with a higher-than-average education level. Typically, these households are located in villages that are well connected with urban centers. Poor households in remote locations send significantly fewer migrants because of their limited access to migration information and poor transport networks. From these findings, the following policy recommendations are made: Firstly, efforts should be made to extend basic social services, including quality education, towards rural areas. Secondly, in order to reduce socially disruptive long-distance migration and the eventual overcrowding and sprawls of major cities, government investments should be oriented towards the upgrading of secondary towns, which can offer rural out-migrants rewarding employment and business opportunities.
Model-based event-triggered adaptive formation control for underactuated surface vehicles via the minimal learning parameter technique

This article presents an adaptive neural formation control algorithm for underactuated surface vehicles by the model-based event-triggered method. In the algorithm, the leader–follower structure is employed to construct the formation model. Meanwhile, two new coordinate variables are introduced to avoid the possible singularity problem that exists in the polar coordinate system. Furthermore, the event-triggered mechanism is developed by constructing the adaptive model in a concise form. Related state variables and control parameters are required to be updated only at the event-triggered instants. Thus, the communication load between the controller and the actuator could be effectively reduced. Besides, for merits of the radial basis function neural network and the minimal learning parameter techniques, only two adaptive parameters are employed to compensate for the effects of the model uncertainties and the external disturbances. With the Lyapunov theory, all signals in the closed-loop system are proved to be semi-global uniformly ultimately bounded. Finally, numerical simulations are conducted to illustrate the effectiveness and feasibility of the proposed algorithm.
An Experimental Study of the Possibility of In Situ Hydrogen Generation within Gas Reservoirs

Hydrogen can be generated in situ within reservoirs containing hydrocarbons through chemical reactions. This technology could be a possible solution for low-emission hydrogen production due to of simultaneous CO2 storage. In gas fields, it is possible to carry out the catalytic methane conversion (CMC) if sufficient amounts of steam, catalyst, and heat are ensured in the reservoir. There is no confirmation of the CMC’s feasibility at relatively low temperatures in the presence of core (reservoir rock) material. This study introduces the experimental results of the first part of the research on in situ hydrogen generation in the Promyslovskoye gas field. A set of static experiments in the autoclave reactor were performed to study the possibility of hydrogen generation under reservoir conditions. It was shown that CMC can be realized in the presence of core and ex situ prepared Ni-based catalyst, under high pressure up to 207 atm, but at temperatures not lower than 450 °C. It can be concluded that the crushed core model improves the catalytic effect but releases carbon dioxide and light hydrocarbons, which interfere with the hydrogen generation. The maximum methane conversion rate to hydrogen achieved at 450 °C is 5.8%.
An equivalent electrical circuit for the Hindmarsh‐Rose model

Hardware realizations of neural networks can pave the way towards a new generation of processors due to the biological role model being superior in terms of speed and energy‐efficiency compared to today's processors. This can be achieved by deriving novel design principles for circuits being obtainable when replicating and investigating real biological neural networks in depth. This has, for example, been done by utilizing the Hindmarsh‐Rose model, offering a rich repertoire of neuronal firing patterns. Our aim is to synthesize a theoretical, equivalent electrical circuit of the Hindmarsh‐Rose model being well interpretable in terms of biology, since this supports the derivation of design principles from biology and can serve as a basis for a systematic circuit simplification. We do this by starting from a linearized model because this allows for a systematic approach and then first derive a linear and afterwards a nonlinear equivalent electrical circuit. The resulting circuit has a structure similar to conductance‐based models, where a deployed negative impedance converter can be seen as a deeper modeling of ion pump activity. Simulation results of the proposed circuits show the functionality of the equivalent circuits.
Importance of the forest state in estimating biomass losses from tropical forests: combining dynamic forest models and remote sensing

Abstract. Disturbances, such as extreme weather events, fires, floods, and biotic agents, can have strong impacts on the dynamics and structures of tropical forests. In the future, the intensity of disturbances will likely further increase, which may have more serious consequences for tropical forests than those we have already observed. Thus, quantifying aboveground biomass loss of forest stands due to tree mortality (hereafter biomass loss) is important for the estimation of the role of tropical forests in the global carbon cycle. So far, the long-term impacts of altered tree mortality on rates of biomass loss have been described little. This study aims to analyse the consequences of long-term elevated tree mortality rates on forest dynamics and biomass loss. We applied an individual-based forest model and investigated the impacts of permanently increased tree mortality rates on the growth dynamics of humid, terra firme forests in French Guiana. Here, we focused on biomass, leaf area index (LAI), forest height, productivity, forest age, quadratic mean stem diameter, and biomass loss. Based on the simulations, we developed a multiple linear regression model to estimate biomass losses of forests in different successional states from the various forest attributes. The findings of our simulation study indicated that increased tree mortality altered the succession patterns of forests in favour of fast-growing species, which changed the forests’ gross primary production, though net primary production remained stable. Tree mortality intensity had a strong influence on the functional species composition and tree size distribution, which led to lower values in LAI, biomass, and forest height at the ecosystem level. We observed a strong influence of a change in tree mortality on biomass loss. Assuming a doubling of tree mortality, biomass loss increased (from 3.2 % y−1 to 4.5 % y−1). We also obtained a multidimensional relationship that allowed for the estimation of biomass loss from forest height and LAI. Via an example, we applied this relationship to remote sensing data of LAI and forest height and mapped biomass loss for French Guiana. We estimated a mean biomass loss rate of 3.2 % per year. The approach described here provides a novel methodology for quantifying biomass loss, taking the successional state of tropical forests into account. Quantifying biomass loss rates may help to reduce uncertainties in the analysis of the global carbon cycle.
Disentangling Associations Between Frequency of Specific Social Networking Site Platform Use, Normative Discrepancies, and Alcohol Use Among Adolescents and Underage Young Adults

Although there is a robust literature examining normative discrepancies for drinking, less is known related to normative discrepancies related to alcohol-posting behavior on social networking sites (SNS). Given that SNS are posited to be an important risk factor for adolescent and young adult alcohol use, the aims of the present study were to: (1) document descriptive and injunctive normative discrepancies for number of alcohol-related posts on SNS, (2) examine associations between frequency of using SNS platforms (Facebook, Instagram, Snapchat) and descriptive and injunctive normative discrepancies, and (3) to examine whether descriptive and injunctive normative discrepancies are associated with willingness to use alcohol and drinking among adolescents and young adults. Data were drawn from the baseline assessment of a larger longitudinal experimental study (N= 306, age 15-20). Overall, participants perceived that their peers are more approving of and post about alcohol use more often than they do themselves, thus indicating significant descriptive and injunctive normative discrepancies. More frequent use of Facebook was associated with having greater descriptive normative discrepancies, whereas frequency of both Facebook and Instagram use were associated with greater injunctive normative discrepancies. Results further indicated that controlling for frequency of SNS use, descriptive normative discrepancies, but not injunctive, were associated with greater willingness to drink and drinks per week. Results provide evidence that in particular, descriptive normative discrepancies for SNS use may be important to target when planning intervention programs to reduce the impact of SNS use on adolescent and young adult alcohol use.
Partisan Enclaves and Information Bazaars: Mapping Selective Exposure to Online News

Many now believe a segregated online news market has led to increased polarization in the United States. Indeed, experimental studies in political science and psychology show that partisans are more interested in reading attitude-reinforcing information. Yet, observational studies of web browsing behavior have thus far found limited differences between Democratic and Republican online news consumption. We present two new pieces of evidence showing how partisans selectively approach congenial news online. First, using a data set of web-browsing histories from the 2016 US general election (August–November 2016), we show that Democrats (Republicans) split their news consumption between left-leaning (right-leaning) sources and moderate/mainstream sources. Most partisan convergence occurs at portal sites—such as Yahoo and MSN—that specialize in nonnews and nonpolitical content. Second, using high-profile scandals from the 2016 election (Access Hollywood and the Comey letter), we show that partisans consume more news when an event benefits their preferred candidate.