Miracle-dz/UniFAR-FTUs huggingface dataset:
The Daily Movement Pattern and Fulfilment of Physical Activity Recommendations in Swedish Middle-Aged Adults: The SCAPIS Pilot Study

Different aspects of the daily movement pattern—sitting, light intensity physical activity, and moderate- and vigorous intensity physical activity—have each independently been associated with health and longevity. Previous knowledge of the amount and distribution of these aspects in the general Swedish population, as well as the fulfilment rate of physical activity recommendations, mainly relies on self-reported data. More detailed data assessed with objective methods is needed. The aim of the study was to present descriptive data on the daily movement pattern in a middle-aged Swedish population assessed by hip-worn accelerometers. The cohort consisted of 948 participants (51% women), aged 50 to 64 years, from the Swedish CArdioPulmonary bioImage pilot Study. In the total sample, 60.5% of accelerometer wear time was spent sitting, 35.2% in light physical activity and 3.9% in moderate- and vigorous physical activity. Men and participants with high educational level spent a larger proportion of time sitting, compared to women and participants with low educational level. Men and participants with a high educational level spent more time, and the oldest age-group spent less time, in moderate- and vigorous physical activity. Only 7.1% of the study population met the current national physical activity recommendations, with no gender, age or education level differences. Assessment of all three components of the daily movement pattern is of high clinical relevance and should be included in future research. As the fulfilment of national physical activity recommendations is very low and sitting time is very high in our middle-aged population, the great challenge remains to enhance the implementation of methods to increase the level of physical activity in this population.
A holistic snapshot of the impact of caring for a loved one who has Alzheimer’s disease: The collective reality from onset to end of life and beyond

Alzheimer’s is a ubiquitous disease. Referred to in terms of “a global epidemic”, the current estimate of people living with Alzheimer’s disease is 32.76 million. In Australia, alone, there is a current estimate of 289,177 care receivers and the co-related projection is that by 2025 there will be 255,800 informal caregivers caring for loved ones with the condition. This thesis focuses on investigating the question, What is the holistic and collective reality of caregivers’ c nceptions and understandings about the impact of caring for a loved one who has Alzheimer’s disease when the trajectory of caregiving spans from onset to end-of-life and beyond? Under the overarching umbrella of a qualitative paradigm, design, data collection, and analysis strategies were implemented within a framework of social constructivism. A hybrid methodology was believed to be the most effective tool to achieve the aim and to answer the research question. ; Submitted in the fulfilment of the requirements of the degree of Doctor of Philosophy, University of the Sunshine Coast, 2018.
Joint Optimization of Node Cooperation and Energy Saving in Wireless Sensor Networks with Multiple Access Channel Setting

Two critical issues in wireless sensor networks are cooperation of nodes and the limited availability of energy within network nodes. A widely employed energy-saving technique is to place nodes in sleep mode, corresponding to low-power consumption as well as to reduced operational capabilities. This causes a node may try to maximize the benefits it gets from the network without participating to its services (e.g. without forwarding packets of other nodes). To conquer with this problem, node cooperation schemes have been investigated in the literature. Therefore, it is crucial to find the optimal trade-off between the amount of cooperation and the amount of energy saving. In this work, we develop an analytical model of a sensor network which not only stimulates nodes to cooperation but also tries to satisfy energy consumption. In our scheme, nodes may enter a sleep mode while active nodes in a relay zone (Vakil and Liang, 2006) are allowed to cooperate with the source. We use this model to investigate the system performance in terms of node cooperation, energy consumption, and network capacity. Furthermore, the proposed model enables us to investigate the trade-off existing between these performance metrics. Numerical results show that the proposed scheme is successful in increasing node cooperation while energy consumption is satisfied.
Alimento Saudável para que/m?/Healthy food: for who/m?

O objetivo deste estudo conceitual é discutir as novas dimensões - culturais, sociais e ambientais - incorporadas ao conceito contemporâneo de alimentos saudáveis. O conceito de alimento saudável hoje deve atender à proposta desafiadora de ser saudável para todos (e tudo): para aqueles que o produzem, para aqueles que comem, para animais e plantas e para o planeta. Além disso, a experiência de comer com saúde e a liberdade de escolha promove diversas experiências sociais e sentimentos antagônicos como culpa, dúvidas, ansiedade e medo de comer. Diante da multiplicidade de propostas alimentares e de dietas e, consequentemente, da variedade de opções que tais ofertas representam para os consumidores, o padrão de consumo de alimentos que os indivíduos contemporâneos definem como saudável passa a simbolizar não apenas suas próprias identidades, mas também o desejo de ser discernido e realçado, assumindo formas cada vez mais peculiares de distinção social através da alimentação. AbstractThe aim of this conceptual study is to discuss the new dimensions - cultural, social and environmental - incorporated into the contemporary concept of healthy food. The question “what is a healthy food today” must meet the challenging proposal of being healthy for everyone (and everything): for those who produce it, for those who eat it, for animals and plants, and for the planet. Besides that, the experience of eating healthily today promotes diverse social experiences and antagonistic feelings as freedom of choice, guilt, doubts and fear to eat. Given the large supply of food and diet guidelines and, consequently, the variety of choices that this supply represents to consumers, the food consumption pattern that individuals define as healthy can be considered to symbolise not only their identities but also what they wish other individuals would think of them, taking on peculiar forms of social distinction via eating.Key words: healthy food; social distinction; food menu; contemporary consumer
Distributed coalition formation algorithms for cooperative broadcast networks with SWIPT

This paper addresses the application of coalitional game theory to cooperative broadcast networks with simultaneous wireless information and power transfer (SWIPT). To improve the reception reliability of destinations with poor channel conditions, we first divide destinations in the network into two types. The first type, Type I, refers to the destinations with the capability of successful decoding. They will help other users by first performing SWIPT and then relaying the source messages with the harvested energy. The second type of nodes, Type II, have poor connections to the source and hence compete to obtain help from Type I destinations. In order to maximize the data transmission rate of Type II destinations in a distributed manner, we model the cooperative scenario as a coalitional game and propose two coalition formation approaches with different payoff functions. One payoff function is based on how much help a destination can contribute or receive. The other payoff function considers the targeted data rate and ensures much better fairness among destinations. Finally, we propose a distributed coalition formation algorithm where destinations decide individually which coalition to join. Simulation results show that the proposed two cooperative schemes outperform the non-cooperative scheme, and the cooperative scheme II performs better than the cooperative scheme I as expected.
METHOD FOR EVALUATING OF DISCREPANCY BETWEEN REGULARITIES SYSTEMS IN DIFFERENT GROUPS

A new method of data analysis is discussed. Goal of represented techniques is complete and statistically valid comparing of regularities existing in two different groups of objects. It is supposed that regularities that tie levels of forecasted and explanatory variables are searched with the help of optimal partitioning technique. The developed technique was applied for analysis of genetic factors impact on severity of discirculatory encephalopathy (DEP). At the first stage computer method for evaluating of DEP severity was developed with the help of pattern recognition techniques. It was revealed that computer estimates of severity rather strongly correlate with DD variant of gene coding angiotensin-converting enzyme (ACE). Systems of regularities that ties various clinical or biochemical factors with computer estimates of severity were found with the help of optimal valid partitioning ( OVP) method in groups of patients with three different variants of gene coding ACE. Statistically significant discrepancies were found between revealed regularities systems with the help of developed methods of comparing.
Ghanaian immigrants’ differential trust in and obligation to obey the US police and Ghana police: findings from a qualitative study

Abstract Qualitative research enhances scholars’ and practitioners’ understanding of our social world. Most published studies on trust in the institution of policing and obligation to obey the police are undergirded by quantitative data; as a result, this research study enhances the literature on trust and obligation to obey by employing a qualitative approach. In this study, interviews obtained from two focus groups of Ghanaians in Alexandria, Virginia explored research participants’ understanding of trust in the institution of policing and obligation to obey the police in the United States and Ghana. The continued migration of sub-Saharan Africans to the United States means that the US police must begin to address this immigrant community’s policing needs. The results of this study show that although Ghanaian immigrants trust the US police more than the Ghana police, the respondents believe also that the US police are overbearing and abuse their authority. Additionally, the participants’ greater confidence in the US police is tempered by a lack of clarity as to whether the participants’ trust in the US police is due to their felt obligation to obey the police or due to a ‘dull compulsion. ’ The implications of the findings are discussed.
Towards automatically categorizing mathematical knowledge

Clearly, there is no definitive standard for categorizing information contained in mathematical papers. Even if AMS Mathematics Subject Classification was important for mathematicians for years, nowadays we can observe growing popularity of other schemes, e.g. arXiv categories. On the other hand, in the era of digital information storing one can expect from the process of classification to be more or less automatic. Furthermore, generic categorization can be done inside the search engine. At different level, the distinction between such classical tagging items as lemma, proposition, theorem etc. had the aim of showing importance of proven facts. Here the automatization is much harder, or, to be more precise, the results obtained can be far from the original tagging given by the author. In the paper we point out some problems and thoughts concerned with the categorization of mathematical knowledge, illustrating some of them by examples taken from the Mizar Mathematical Library, large machine-checked repository of mathematical facts.
Temporal Stability of Risk Preference Measures

We examine the temporal stability of risk preference measures obtained by different elicitation methods in a controlled laboratory experiment at two distinct times. Our results indicate remarkable temporal stability of risk measures at the aggregated level and temporal instability at the individual level. We control for the impact of, first, personality traits, and second, performance realized in a market game. When better market performers demonstrate more stable risk preferences, the impact of personality traits is marginal.
A novel model-based diagnosis engine: theory and applications

818-393-5342 Abstract- Over the past decade, the number of Earth orbiters and deep space probes has grown dramatically and is expected to continue in the future as miniaturization technologies drive spacecraft to become more numerous and more complex. This rate of growth has brought a new focus on autonomous and self-preserving systems that depend on fault diagnosis. Although diagnosis is needed for any autonomous system, current approaches are almost uniformly "ad-hoc," inefficient, and incomplete. Systematic methods of general diagnosis exist in literature, but they all suffer from two major drawbacks that severely limit their practical applications. First, they tend to be large and complex and hence difficult to apply. Second and more importantly, in order to find the minimal diagnosis set, i.e., the minimal set of faulty components, they rely on algorithms with exponential computational cost and hence are highly impractical for application to many systems of interest. Ib this paper, we propose a two-fold approach to overcome these two limitations. Then we report the details of a new and powerful tool, Diagnosis Engine version 1.0, we have developed based on these techniques. First, we propose a novel and compact reconstruction of General Diagnosis Engine (GDE), as one of the most fundamental approaches to model-based diagnosis. We then present a novel algorithmic approach for calculation of minimal diagnosis set. Using a powerful yet simple representation of the calculation of minimal diagnosis set, we map the problem onto two well-known problems, that is, the Boolean Satisfiability and 011 Integer Programming problems. The mapping onto Boolean Satisfiability enables the use of very efficient algorithms with a super-polynomial rather than an exponential complexity for the problem. The mapping onto 0/1 Integer Programming problem enables the use of a variety of algorithms that can efficiently solve the problem for up to several thousand components. These new algorithms significantly improve over the existing ones, enabling efficient diagnosis of large complex systems. In addition, the latter mapping allows, for the first time, determination of the bound on the solution, i.e., the minimum number of faulty components, before solving the problem. This is a powerful insight that can be exploited to develop yet more efficient algorithms for the problem. At the end, we report the results of validating and benchmarking of our engine based on this technology.
On shear-induced turbulence in rotating stars

We review various prescriptions which have been proposed for the turbulent transport of matter and angular mo- mentum in differentially rotating stellar radiation zones. A new prescription is presented for the horizontal transport associated with the anisotropic shear turbulence which is produced by the differential rotation in latitude; this "β-viscosity" is drawn from torque measurements in the classical Couette-Taylor experiment (Richard & Zahn 1999, A&A, 347, 734). Its implementation in a stellar evolution code leads to enhanced mixing, as illustrated by models of a rotating main-sequence star of 1.5 solar mass.
Physiological and self-report measures in emotion studies: Methodological considerations

Investigating human emotions empirically is still considered to be challenging, mostly due to the questionable validity of the results obtained when employing individual types of measures. Among the most frequently used methods to study emotional reactions are self-report, autonomic, neurophysiological, and behavioral measures. Importantly, previous studies on emotional responding have rarely triangulated the aforementioned research methods. In this paper we discuss main methodological considerations related to the use of physiological and self-report measures in emotion studies, based on our previous research on the processing of emotionally-laden narratives in the native and non-native language, where we employed the SUPIN S30 questionnaire as a self-report tool, and galvanic skin response (GSR) as a physiological measure (Jankowiak & Korpal, 2018). The findings revealed a more pronounced reaction to stimuli presented in the native relative to the non-native language, which was however reflected only in GSR patterns. The lack of correlation between GSR and SUPIN scores might have resulted from a number of methodological considerations, such as social desirability bias, sensitive questions, lack of emotional self-awareness, compromised ecological validity, and laboratory anxiety, all of which are thoroughly discussed in the article.
CLIP, a command line interpreter for a subset of C++

C++ is not the best choice for a first programming language, but if it is used, the learning circumstances need to be as easy as possible. We have developed a pedagogically designed interpreter for this purpose. Our hypothesis is that an interpreter is easier than a compiler for a novice programmer to use. We do not want students to use language properties they do not yet fully understand, so our approach is imperative-first. In addition, when using an interpreter, learning concepts such as libraries can be postponed until later in the course. C++ is a complex language and most of its language features are not needed by a novice programmer. Therefore we have simplified the language to a subset of C++ that we call C-. For instance, classes have been omitted. We have also put a lot of effort into producing clear, informative error messages, something that is made possible by of the simpler programming language. This article introduces some other C/C++ interpreters, their evaluation, and the description of our interpreter called CLIP. So far CLIP has not been used by students, so its evaluation is left as future work.
Performance of a linear robust control strategy on a nonlinear model of spatially developing flows

This paper investigates the control of self-excited oscillations in spatially developing flow systems such as jets and wakes using ${\mathcal H}_{\infty}$ control theory on a complex Ginzburg–Landau (CGL) model. The coefficients used in this one-dimensional equation, which serves as a simple model of the evolution of hydrodynamic instability waves, are those selected by Roussopoulos & Monkewitz (Physica D 1996, vol. 97, p. 264) to model the behaviour of the near-wake of a circular cylinder. Based on noisy measurements at a point sensor typically located inside the cylinder wake, the compensator uses a linear ${\mathcal H}_{\infty}$ filter based on the CGL model to construct a state estimate. This estimate is then used to compute linear ${\mathcal H}_{\infty}$ control feedback at a point actuator location, which is typically located upstream of the sensor. The goal of the control scheme is to stabilize the system by minimizing a weighted average of the ‘system response’ and the ‘control effort’ while rigorously bounding the response of the controlled linear system to external disturbances. The application of such modern control and estimation rules stabilizes the linear CGL system at Reynolds numbers far above the critical Reynolds number $Re_c \,{\approx}\, 47$ at which linear global instability appears in the uncontrolled system. In so doing, many unstable modes of the uncontrolled CGL system are linearly stabilized by the single actuator/sensor pair and the model-based feedback control strategy. Further, the linear performance of the closed-loop system, in terms of the relevant transfer function norms quantifying the linear response of the controlled system to external disturbances, is substantially improved beyond that possible with the simple proportional measurement feedback proposed in previous studies. Above $Re\,{\approx}\, 84$, the ${\mathcal H}_{\infty}$ control designs significantly outperform the corresponding ${\mathcal H}_2$ control designs in terms of their ability to stabilize the CGL system in the presence of worst-case disturbances. The extension of these control and estimation rules to the nonlinear CGL system on its attractor (a simple limit cycle) stabilizes the full nonlinear system back to the stationary state at Reynolds numbers up to $Re\,{\approx}\, 97$ using a single actuator/sensor pair, fixed-gain linear feedback and an extended Kalman filter incorporating the system nolinearity.
Fully secure constrained pseudorandom functions using random oracles

A constrained pseudorandom function (CPRF) PRF allows to derive constrained evaluation keys that only allow to evaluate PRF on a subset of inputs. CPRFs have only recently been introduced independently by three groups of researchers. However, somewhat curiously, all of them could only achieve a comparatively weak, selective-challenge form of security (except for small input spaces, very limited forms of constrained keys, or with superpolynomial security reductions). In this paper, we construct the first fully secure CPRF without any of the above restrictions. Concretely, we support “bit-fixing” constrained keys that hardwire an arbitrary subset of the input bits to fixed values, we support exponentially large input spaces, and our security reduction is polynomial. We require very heavyweight tools: we assume multilinear maps, indistinguishability obfuscation, and our proof is in the random oracle model. Still, our analysis is far from tautological, and even with these strong building blocks, we need to develop additional techniques and tools. As a simple application, we obtain the first adaptively secure non-interactive key exchange protocols for large user groups.
Assessing Benefits of a Buried Interconnect Layer in Digital Designs

In sub-15 nm technology nodes, local metal layers have witnessed extremely high congestion leading to pin-access-limited designs, and hence affecting the chip area and related performance. In this paper, we assess the benefits of adding a buried interconnect layer below the device layers for the purpose of reducing cell area, improving pin access, and reducing chip area. After adding the buried layer to a projected 7 nm standard cell library, results show <inline-formula> <tex-math notation="LaTeX">$\sim 9$ </tex-math></inline-formula>%–13% chip area reduction and 126% pin access improvement. This shows that buried interconnect, as an integration primitive, is very promising as an alternative method to density scaling.
Real-Time Sub-Time Early Warning of Airport Scheduled Flight Delay Based on Immune Algorithm

The paper combines the characteristics of airport flight operation and statistical data of flight delays and forms early warning grading standards of flight delays. It applies the negative selection algorithm to diagnose and forecast the state of the airport scheduled flight delay, uses the probability of flight delay in a certain period as divisory standards of mature detector and memory detector, presents the concept of the relative age in eliminating anile detectors in the process of training detectors. It uses corresponding flight data according to different time section of different date, increasing the week of flights weight coefficient on the basis of basic training flights data and improving the detecting and forecasting accuracy. The simulation experiment indicates, this method can veraciously forecast accumulative delay scheduled flight quantity in some time section, and carries on accurately early warning.