Miracle-dz/UniFAR-FTUs huggingface dataset:
Embracing the perspectives of older adults in organising and evaluating person‐centred and integrated care

Purpose s The aim of the present study was to develop a valid Geriatric ICF Core Set reflecting relevant health-related problems of community-living older adults without dementia. Methods s A Delphi study was performed in order to reach consensus (≥70% agreement) on second-level categories from the International Classification of Functioning, Disability and Health (ICF). The Delphi panel comprised 41 older adults, medical and non-medical experts. Content validity of the set was tested in a cross-sectional study including 267 older adults identified as frail or having complex care needs. Results s Consensus was reached for 30 ICF categories in the Delphi study (14 Body functions, 10 Activities and Participation, and 6 Environmental Factors categories). Content validity of the set was high: the prevalence of all problems was >10%, except for d530 Toileting . The most frequently reported problems were b710 Mobility of joint functions (70%), b152 Emotional functions (65%), and b455 Exercise tolerance functions (62%). No categories had missing values. Conclusion s The final Geriatric ICF Core Set is a comprehensive and valid set of 29 ICF categories, reflecting the most relevant health-related problems among community-living older adults without dementia. This Core Set may contribute to optimal care provision and support of the older population.
Motivational Objects in Natural Scenes (MONS): A Database of >800 Objects

In daily life, we are surrounded by objects with pre-existing motivational associations. However, these are rarely controlled for in experiments with natural stimuli. Research on natural stimuli would therefore benefit from stimuli with well-defined motivational properties; in turn, such stimuli also open new paths in research on motivation. Here we introduce a database of Motivational Objects in Natural Scenes (MONS). The database consists of 107 scenes. Each scene contains 2 to 7 objects placed at approximately equal distance from the scene center. Each scene was photographed creating 3 versions, with one object (“critical object”) being replaced to vary the overall motivational value of the scene (appetitive, aversive, and neutral), while maintaining high visual similarity between the three versions. Ratings on motivation, valence, arousal and recognizability were obtained using internet-based questionnaires. Since the main objective was to provide stimuli of well-defined motivational value, three motivation scales were used: (1) Desire to own the object; (2) Approach/Avoid; (3) Desire to interact with the object. Three sets of ratings were obtained in independent sets of observers: for all 805 objects presented on a neutral background, for 321 critical objects presented in their scene context, and for the entire scenes. On the basis of the motivational ratings, objects were subdivided into aversive, neutral, and appetitive categories. The MONS database will provide a standardized basis for future studies on motivational value under realistic conditions.
Illumination demultiplexing from a single image

A class of techniques in computer vision and graphics is based on capturing multiple images of a scene under different illumination conditions. These techniques explore variations in illumination from image to image to extract interesting information about the scene. However, their applicability to dynamic environments is limited due to the need for robust motion compensation algorithms. To overcome this issue, we propose a method to separate multiple illuminants from a single image. Given an image of a scene simultaneously illuminated by multiple light sources, our method generates individual images as if they had been illuminated by each of the light sources separately. To facilitate the illumination separation process, we encode each light source with a distinct sinusoidal pattern, strategically selected given the relative position of each light with respect to the camera, such that the observed sinusoids become independent of the scene geometry. The individual illuminants are then demultiplexed by analyzing local frequencies. We show applications of our approach in image-based relighting, photometric stereo, and multiflash imaging.
Wind/Wave Misalignment Effects on Mooring Line Tensions for a Spar Buoy Wind Turbine

The design methodology for mooring systems for a spar buoy wind turbine considers the influence of extreme events and wind/wave misalignments occurring in its lifetime. Therefore, the variety of wind and wave directions affects over the seakeeping and as a result the evaluation of the maxima loads acting on the spar-buoy wind turbine. In the present paper, the importance of wind/wave misalignments on the dynamic response of spar-type floating wind turbine [1] is investigated. Based on standards, International Electrotechnical Commission IEC and Det Norske Veritas DNV the design of position moorings should be carried out under extreme wind/wave loads, taking into account their misalignments with respect to the structure. In particular, DNV standard, in ‘Position mooring’ recommendations, specifies in the load cases definition, if site specific data is not available, to consider non-collinear environment to have wave towards the unit’s bow (0°) and wind 30° relative to the waves. In IEC standards, the misalignment of the wind and wave directions shall be considered to design offshore wind turbines and calculate the loads acting on the support structure. Ultimate Limit State (ULS) analyses of the OC3-Hywind spar buoy wind turbine are conducted through FAST code, a certified nonlinear aero-hydro-servo-elastic simulation tool by the National Renewable Energy Laboratory’s (NREL’s). This software was developed for use in the International Energy Agency (IEA) Offshore Code Comparison Collaborative (OC3) project, and supports NREL’s offshore 5-MW baseline turbine. In order to assess the effects of misaligned wind and wave, different wind directions are chosen, maintaining the wave loads perpendicular to the structure. Stochastic, full-fields, turbulence simulator Turbsim is used to simulate the 1-h turbulent wind field. The scope of the work is to investigate the effects of wind/wave misalignments on the station-keeping system of spar buoy wind turbine. Results are presented in terms of global maxima determined through mean up-crossing with moving average, which, then, are modelled by a Weibull distribution. Finally, extreme values are estimated depending on global maxima and fitted on Gumbel distribution. The Most Probable Maximum value of mooring line tensions is found to be influenced by the wind/wave misalignments. The present paper is organized as follows. Section ‘Introduction’, based on a literature study, gives useful information on the previous studies conducted on the wind/wave misalignments effects of floating offshore wind turbines. Section ‘Methodology’ describes the applied methodology and presents the spar buoy wind turbine, the used numerical model and the selected environmental conditions. Results and the corresponding discussion are given in Section ‘Results and discussion’ for each load case corresponding to the codirectional and misaligned wind and wave loads. Results are presented and discussed in time and frequency domains. Finally, in Section ‘Conclusion’ some conclusions are drawn.
SEMONTOQA: A Semantic Understanding-Based Ontological Framework for Factoid Question Answering

This paper presents an outline of an Ontological and Semantic understanding-based model (SEMONTOQA) for an open-domain factoid Question Answering (QA) system. The outlined model analyses unstructured English natural language texts to a vast extent and represents the inherent contents in an ontological manner. The model locates and extracts useful information from the text for various question types and builds a semantically rich knowledge-base that is capable of answering different categories of factoid questions. The system model converts the unstructured texts into a minimalistic, labelled, directed graph that we call a Syntactic Sentence Graph (SSG). An Automatic Text Interpreter using a set of pre-learnt Text Interpretation Subgraphs and patterns tries to understand the contents of the SSG in a semantic way. The system proposes a new feature and action based Cognitive Entity-Relationship Network designed to extend the text understanding process to an in-depth level. Application of supervised learning allows the system to gradually grow its capability to understand the text in a more fruitful manner. The system incorporates an effective Text Inference Engine which takes the responsibility of inferring the text contents and isolating entities, their features, actions, objects, associated contexts and other properties, required for answering questions. A similar understanding-based question processing module interprets the user's need in a semantic way. An Ontological Mapping Module, with the help of a set of pre-defined strategies designed for different classes of questions, is able to perform a mapping between a question's ontology with the set of ontologies stored in the background knowledge-base. Empirical verification is performed to show the usability of the proposed model. The results achieved show that, this model can be used effectively as a semantic understanding based alternative QA system.
A Theory of Statistical Inference for Matching Methods in Causal Research

Researchers who generate data often optimize efficiency and robustness by choosing stratified over simple random sampling designs. Yet, all theories of inference proposed to justify matching methods are based on simple random sampling. This is all the more troubling because, although these theories require exact matching, most matching applications resort to some form of ex post stratification (on a propensity score, distance metric, or the covariates) to find approximate matches, thus nullifying the statistical properties these theories are designed to ensure. Fortunately, the type of sampling used in a theory of inference is an axiom, rather than an assumption vulnerable to being proven wrong, and so we can replace simple with stratified sampling, so long as we can show, as we do here, that the implications of the theory are coherent and remain true. Properties of estimators based on this theory are much easier to understand and can be satisfied without the unattractive properties of existing theories, such as assumptions hidden in data analyses rather than stated up front, asymptotics, unfamiliar estimators, and complex variance calculations. Our theory of inference makes it possible for researchers to treat matching as a simple form of preprocessing to reduce model dependence, after which all the familiar inferential techniques and uncertainty calculations can be applied. This theory also allows binary, multicategory, and continuous treatment variables from the outset and straightforward extensions for imperfect treatment assignment and different versions of treatments.
Teaching Agile Model-Driven Engineering for Cyber-Physical Systems

Agile development methods, model-driven engineering, and cyber-physical systems are important topics in software engineering education. It is not obvious how to teach their combination while respecting individual challenges posed to students and educators. We have devised a software project class for teaching the agile MDE for CPS. The project class was held in three different semesters. In this paper, we report on the setup of our exploratory study and its goals for teaching. We base our evaluation and insights on interviews and questionnaires. Our results show the feasibility of combination of agile MDE for CPS but also the challenges this combination poses to students and educators.
Improving Scalability and Fault Tolerance in an Application Management Infrastructure

This paper explores the challenges associated with distributed application management in large-scale computing environments. In particular, we investigate several techniques for extending Plush, an existing distributed application management framework, to provide improved scalability and fault tolerance without sacrificing performance. One of the main limitations of Plush is the structure of the underlying communication fabric. We explain how we incorporated the use of an overlay tree provided by Mace, a toolkit that simplifies the implementation of overlay networks, in place of the existing communication subsystem in Plush to improve robustness and scalability.
Java Traits — Improving Opportunities for Reuse

One goal of Object-Oriented Programming is to enable programmers to craft elegant and reusable systems. In practice however, Java programmers have no choice but to copy and paste code that cannot be shared via inheritance. The resulting duplication makes systems difficult to understand and hard to maintain. Traits are a language feature, originally prototyped in Smalltalk, that directly address this barrier to reuse. Traits encapsulate collections of methods that can be reused anywhere in the inheritance hierarchy. We argue that Java would benefit from such a mechanism. To demonstrate, we present a case study of Java Swing, a large productionquality library, showing how we isolated pieces of duplicated code that could not be eliminated by conventional means and how traits could be used to eliminate them. In addition to a lack of multiple inheritance, our study revealed other barriers to reuse, including the use of private, final and synchronized qualifiers. Surprisingly, these are all easily overcome by a natural extension of traits.
Making asynchronous parallelism safe for the world

We need a programming model that combines the advantages of the synchronous and asynchronous parallel styles. Synchronous programs are determinate (thus easier to reason about) and avoid synchronization overheads. Asynchronous programs are more flexible and handle conditionals more efficiently. Here we propose a programming model with the benefits of both styles. We allow asynchronous threads of control but restrict shared-memory accesses and other side effects so as to prevent the behavior of the program from depending on any accidents of execution order that can arise from the indeterminacy of the asynchronous process model. These restrictions may be enforced either dynamically (at run time) or statically (at compile time). In this paper we concentrate on dynamic enforcement, and exhibit an implementation of a parallel dialect of Scheme based on these ideas. A single successful execution of a parallel program in this model constitutes a proof that the program is free of race conditions (for that particular set of input data). We also speculate on a design for a programming language using static enforcement. The notion of distinctness is important to proofs of noninterference. An appropriately designed programming language must support such concepts as “all the elements of this array are distinct,” perhaps through its type system. This parallel programming model does not support all styles of parallel programming, but we argue that it can support a large class of interesting algorithms with considerably greater efficiency (in some cases) than a strict SIMD approach and considerably greater safety (in all cases) than a full-blown MIMD approach.
Association between Sleep Habits and Metabolically Healthy Obesity in Adults: A Cross-Sectional Study

Higher body mass index (BMI) increases the risk of cardiometabolic diseases, but nearly a third of the people living with obesity (BMI: ≥30 kg/m2) are metabolically healthy (MHO). Extreme sleep durations and poor sleep quality are associated with higher bodyweight and cardiometabolic dysfunction, but the full extent to which sleep habits may help differentiate those with MHO versus metabolically abnormal obesity (MAO) is not yet known. Data from the U.S. National Health and Nutritional Examination Survey 2005–08 was used (BMI: ≥30 kg/m2; ≥20 y; N = 1,777). The absence of metabolic syndrome was used to define MHO. Those with MHO tended to be younger, female, Non-Hispanic Black, never smokers, more physically active, and with less physician diagnosed sleep disorders than MAO. Neither sleep duration nor overall sleep quality was related to MHO in crude or multivariable adjusted analyses; however, reporting “almost always” to having trouble falling asleep (OR (95% CI): 0.40 (0.20–0.78)), waking up during the night (0.38 (0.17–0.85)), feeling unrested during the day (0.35 (0.18–0.70)), and feeling overly sleepy during the day (0.35 (0.17–0.75)) was related to lower odds of MHO. Selected sleep quality factors, but not sleep quantity or overall sleep quality, are associated with the MHO phenotype.
Bacterial Community Diversity and their Composition in Different Soil Ecosystems Analyzed by PCR Coupled Culture Independent Methods

Exploration of bacterial community diversity linked with different forest and farm soil ecosystems is very essential to get information about their role in the maintenance of respective soil ecosystems. Different parameters associated with ecosystems have significant effect on inhabitance of diverse bacterial communities. Our study deals with, unraveling of bacterial community diversity and their composition in two different kinds of forest and farm soil ecosystems. This was accomplished by using molecular biology methods such as PCR-DGGE and sequencing of 16S rDNA clone library of metagenomes extracted from forest and farm soils. Study revealed that there was high level of similarity (about 77%) in bacterial community among two forest soil and more than 60% of similarity between forest and organic farm soil. However, less than 38% of similarity was seen between forest and degraded farm soil bacterial communities. Further 16S rDNA sequencing results were showed bacterial composition in each type of soil ecosystem. All soil types have shown presence of uncultured microbes with abundance of γγγγγ -proteobacterial communities. Apart from γγγγγ -proteobacteria, other bacterial communities such as Acidobacteria, Actinobacteria, γγγγγ -proteobacteria and Plactomycetes were found in organic farm soil whereas Firmicutes was present in degraded farm soil. The results of present study demonstrated that, the bacterial diversity observed in this experiment is very less irrespective of soil ecosystem. This reflects that, those may be intensively threatened by biotic/abiotic factors and human activities associated with it. Thus, these forest and farm soils are need to be protected for maintaining ecological balance.
Isolation and Characterization of Anti Pathogenic Plant Growth Promoting Bacteria from Cotton Rhizosphere

Sustainable farming systems strive to minimize the use of synthetic pesticides and to optimize the use of alternative management strategies to control soil borne pathogens. During the last decade numerous bio control experiments with bacteria have been reported. But when such bacterial formulation was tried on field, it was not able to give as nice response as its giving in lab. Therefore, it is necessary to develop efficient strains in field conditions. One possible approach is to explore soil microbial diversity for PGPR having combination of PGP activities and well adapted to particular soil environment. So keeping in view the above constrains, the present study was designed to screen certain rhizospheric bacterial isolates for their multiple plant growth promoting activities. In this research twelve bacterial isolates were successfully isolated from cotton rhizosphere which possess antagonistic activity against to main soil fungal pathogen of cotton as well as also shows plant growth promoting activities. All the potent isolates were characterized phenotypically and biochemically. One of them were also characterized molecularly by 16s r RNA sequencing and found to be novel. The selected isolates are antagonistic to Rhizoctonia solani and Fusarium oxysporum and could be developed into a valuable crop management tool to reduce the deleterious impact of plant pathogen .
Reducing Levels of Toxic Chemicals in Cigarette Smoke: A New Healthy People 2010 Objective

We developed and implemented a national surveillance system to monitor and reduce the levels of toxic chemicals in tobacco smoke. A developmental Healthy People 2010 (HP 2010) objective was revised to report on levels of three categories of chemicals—tobacco-specific nitrosamines, polyaromatic hydrocarbons, and volatile organic compounds—in the smoke of leading U.S. cigarette brands. Unit-based sales-weighted average levels were calculated for each chemical category. The target for the new HP 2010 objective is a 10% reduction in unit-based sales-weighted average levels of each chemical category. The Centers for Disease Control and Prevention provided the baseline, target data, and laboratory analyses. A national data source, national baseline data, and target were presented to the Healthy People Steering Committee during 2005 Midcourse Review. Approval of the revised objective initiated the surveillance of three major classes of toxic chemicals in cigarette smoke. The approved objective provides a feasible, innovative approach for monitoring and supporting measurable population-based reductions in levels of toxic and carcinogenic chemicals in tobacco smoke.
Diversification in the internet economy: the role of for-profit mediators

We investigate market forces that would lead to the emergence of new classes of players in the sponsored search advertising market. We report a multi-fold diversification triggered by an inherent feature of the sponsored search market, namely, capacity constraints, arising from the fact that there is a limit on the number of available advertisement slots, especially for the popular keywords. As a result, a significant pool of interested advertisers are left out. We present a comparative study of two scenarios motivated by capacity constraints - one where the additional capacity is provided by for-profit agents (or, mediators), who compete for slots in the original auction, draw traffic, and run their own sub-auctions, and the other, where the additional capacity is provided by the auctioneer herself, by essentially acting as a mediator and running a single combined auction. The quality of the additional capacity is measured by its fitness factor. We observe that the single combined-auction model seems inferior to the mediator-based model and market becomes more capacity efficient in the latter. For instance, the revenue of the auctioneer always increases when mediators are involved, unlike the auctioneer based scenario where often there is a tradeoff between the revenue and the capacity. Further, the social value (i.e. efficiency) always increases when mediators are involved. Thus, our analysis indicates that there are significant opportunities for diversification in the internet economy and we should expect it to continue to develop richer structure, with room for different types of market entities and mechanisms to coexist.
Phase Type

(cid:1) Moment distributions of phase-type and matrix-exponential distributions are shown to remain within their respective classes. We provide a probabilistic phase-type representation for the former case and an alternative representation, with an analytically appealing form, for the latter. First order moment distributions are of special interest in areas like demography and economics, and we calculate explicit formulas for the Lorenz curve and Gini index used in these disciplines.