Miracle-dz/UniFAR-FTUs huggingface dataset:
American Journal of Epidemiology Original Contribution Simply Ask Them about Their Balance—future Fracture Risk in a Nationwide Cohort Study of Twins

The principal causal components of an osteoporotic fracture are a fall and weakened bone strength. While bone quality measures have been frequently studied, the ability of simple measures of impaired balance to predict fracture risk has received less attention. Computer-assisted telephone interviews were conducted between 1998 and 2000 among 24,598 Swedish twins aged 55 years or older. Impaired balance at the time of interview was reported by 2,890 (12%) of the twins. Twin pairs who were discordant with regard to impaired balance were selected for analysis and followed for fractures through 2005. In a pairwise analysis, the odds ratio for hip fracture was 3.13 (95% confidence interval (CI): 1.62, 6.05) among twins with impaired balance as compared with their co-twins with normal balance. When previously recognized clinical risk factors for osteoporotic fracture were considered in the model, the odds ratio for hip fracture with impaired balance was 3.88 (95% CI: 1.40, 10.72). Approximately 40% of all hip fractures were attributable to impaired balance. The odds ratios for any fracture and any osteoporotic fracture for twins with impaired balance were 2. These results imply that self-reported impaired balance is a novel and readily assessed risk factor for future fractures in the elderly. The principal component causes of an osteoporotic fracture are a fall and a fragile skeleton. Most research on primary prevention of these fractures has focused on bone-related risk factors (1–3). However, the vast majority of all fractures in elderly persons occur after a fall. Therefore , the risk of a future fall, not only bone quality, should be integrated into an individual risk profile for osteoporotic fracture (4). Attempts to examine the value of variables related to balance and fall risk in assessing the risk of osteoporotic fracture have been few. A measured impaired balance is associated with increased risk of falls (5, 6). However, even if direct measurement of balance performance might be preferable, it is not easily accomplished or reproduced. Thus, self-reports could be used as a good and simple alternative. Self-reported impaired balance is strongly associated with performance-based inferior postural stability (7–12). Measured impaired balance is an independent risk factor for osteoporotic fractures in some (13) but not all (14–16) prospective studies. Self-reported falls have also been reported as a risk factor (15, 16) but not an independent predictor of fracture risk (14). There is a need for a simple tool with which to identify subjects …
Trilateration Localization for Multi-robot Teams

The ability of robots to quickly and accurately localize their neighbors is extremely important for robotic teams. Prior approaches typically rely either on global information provided by GPS, beacons and landmarks, or on complex local information provided by vision systems. In this paper we describe our trilateration approach to multi-robot localization, which is fully distributed, inexpensive, and scalable [15]. Our prior research [14] focused on maintaining multi-robot formations indoors using trilateration. This paper pushes the limits of our trilateration technology by testing formations of robots in an outdoor setting at larger inter-robot distances and higher speeds.
The influence of wing–wake interactions on the production of aerodynamic forces in flapping flight

SUMMARY We used two-dimensional digital particle image velocimetry (DPIV) to visualize flow patterns around the flapping wing of a dynamically scaled robot for a series of reciprocating strokes starting from rest. The base of the wing was equipped with strain gauges so that the pattern of fluid motion could be directly compared with the time history of force production. The results show that the development and shedding of vortices throughout each stroke are highly stereotyped and influence force generation in subsequent strokes. When a wing starts from rest, it generates a transient force as the leading edge vortex (LEV) grows. This early peak, previously attributed to added-mass acceleration, is not amenable to quasi-steady models but corresponds well to calculations based on the time derivative of the first moment of vorticity within a sectional slice of fluid. Forces decay to a stable level as the LEV reaches a constant size and remains attached throughout most of the stroke. The LEV grows as the wing supinates prior to stroke reversal, accompanied by an increase in total force. At stroke reversal, both the LEV and a rotational starting vortex (RSV) are shed into the wake, forming a counter-rotating pair that directs a jet of fluid towards the underside of the wing at the start of the next stroke. We isolated the aerodynamic influence of the wake by subtracting forces and flow fields generated in the first stroke, when the wake is just developing, from those produced during the fourth stroke, when the pattern of both the forces and wake dynamics has reached a limit cycle. This technique identified two effects of the wake on force production by the wing: an early augmentation followed by a small attenuation. The later decrease in force is consistent with the influence of a decreased aerodynamic angle of attack on translational forces caused by downwash within the wake and is well explained by a quasi-steady model. The early effect of the wake is not well approximated by a quasi-steady model, even when the magnitude and orientation of the instantaneous velocity field are taken into account. Thus, the wake capture force represents a truly unsteady phenomenon dependent on temporal changes in the distribution and magnitude of vorticity during stroke reversal.
Review of a Coding Scheme for Additive White Noise Channels with Feedback

We review the capacity-achieving coding scheme for the power-constrained wide-band Additive White Gaussian Noise (AWGN) channel (with noiseless feedback) that was proposed in [1]. The performance of this scheme for the cases of (i) non-Gaussian additive white noise on the forward path, and (ii) AWGN on both forward and feedback paths, is also discussed.
Teaching for critical thinking: preparing hospitality and tourism students for careers in the twenty-first century

ABSTRACT Twenty-first century tourism educators and career-seeking graduates are faced with a host of novel challenges. Given the dynamic, complex nature of the contemporary tourism industry, students must be equipped with relevant twenty-first century skills. To address this need, critical thinking is currently being promoted, via university initiatives, as an employable skill. This study assesses the extent to which critical thinking is being transmitted to tourism students at a large southeastern university in the United States. Precourse and postcourse data were collected from students (n = 85) who participated in a tourism management class, that emphasized case study learning, during the fall 2014, spring 2015, and spring 2016 semesters. Uncorrected results indicate significant positive increases in overall critical thinking and two of five sub-domains – inference and deduction; however, in the conservative, corrected results there are no significant effects. Recommendations for improving critical thinking and three sub-domains – analysis, evaluation, and induction – are discussed.
Corruption in an Unstable Environment

In this paper we study the influence of economic stability on the level of corruption in a country, where high stability is defined as a low level of variance in economic output growth. We present a political competition model with exogenous shocks to economic output where politicians can decide about the level of corruption and an election is held within the framework of a Bayesian game. Corruption is assumed to be harmful to the economy and politicians try to maximize income from corrupt activities as well as the probability of getting reelected. We show that independent of the absolute size of economic output growth a low degree of economic stability yields a high level of corruption and vice versa. Thus we conclude that not only does corruption influence economic activity, but also the opposite effect might exist, namely that exogenously caused fluctuations of output influence the readiness of politicians to behave in a corrupt manner. To support our theoretical findings we additionally carry out a cross-country empirical analysis of GDP growth variance and corruption and come to results confirming our thesis.
Semantic degrees for Industrie 4.0 engineering: deciding on the degree of semantic formalization to select appropriate technologies

Under the context of Industrie 4.0 (I4.0), future production systems provide balanced operations between manufacturing flexibility and efficiency, realized in an autonomous, horizontal, and decentralized item-level production control framework. Structured interoperability via precise formulations on an appropriate degree is crucial to achieve software engineering efficiency in the system life cycle. However, selecting the degree of formalization can be challenging, as it crucially depends on the desired common understanding (semantic degree) between multiple parties. In this paper, we categorize different semantic degrees and map a set of technologies in industrial automation to their associated degrees. Furthermore, we created guidelines to assist engineers selecting appropriate semantic degrees in their design. We applied these guidelines on publicly available scenarios to examine the validity of the approach, and identified semantic elements over internally developed use cases concerning plug-and-produce.
Hcp-4, a Cenp-C–Like Protein inCaenorhabditis elegans, Is Required for Resolution of Sister Centromeres

The centromere plays a critical role in the segregation of chromosomes during mitosis. In mammals, sister centromeres are resolved from one another in the G2 phase of the cell cycle. During prophase, chromosomes condense with sister centromeres oriented in a back to back configuration enabling only one chromatid to be captured by each half spindle. To study this process, we identified a centromere protein (CENP)-C–like protein, holocentric protein (HCP)-4, in Caenorhabditis elegans based on sequence identity, loss of function phenotype, and centromeric localization. HCP-4 is found in the cytoplasm during interphase, but is nuclear localized in mitosis, where it localizes specifically to the centromere. The localization of HCP-4 to the centromere is dependent on the centromeric histone HCP-3; in addition, HCP-3 and HCP-4 are both required for localization of a CENP-F–like protein, HCP-1, indicating an ordered assembly pathway. Loss of HCP-4 expression by RNA-mediated interference resulted in a failure to generate resolution of sister centromeres on chromosomes, suggesting that HCP-4 is required for sister centromere resolution. These chromosomes also failed to form a functional kinetochore. Thus, the CENP-C–like protein HCP-4 is essential for both resolution sister centromeres and attachment to the mitotic spindle.
Determining the Orientation and Localization of Membrane-Bound Peptides

Many naturally occurring bioactive peptides bind to biological membranes. Studying and elucidating the mode of interaction is often an essential step to understand their molecular and biological functions. To obtain the complete orientation and immersion depth of such compounds in the membrane or a membrane-mimetic system, a number of methods are available, which are separated in this review into four main classes: solution NMR, solid-state NMR, EPR and other methods. Solution NMR methods include the Nuclear Overhauser Effect (NOE) between peptide and membrane signals, residual dipolar couplings and the use of paramagnetic probes, either within the membrane-mimetic or in the solvent. The vast array of solid state NMR methods to study membrane-bound peptide orientation and localization includes the anisotropic chemical shift, PISA wheels, dipolar waves, the GALA, MAOS and REDOR methods and again the use of paramagnetic additives on relaxation rates. Paramagnetic additives, with their effect on spectral linewidths, have also been used in EPR spectroscopy. Additionally, the orientation of a peptide within a membrane can be obtained by the anisotropic hyperfine tensor of a rigidly attached nitroxide label. Besides these magnetic resonance techniques a series of other methods to probe the orientation of peptides in membranes has been developed, consisting of fluorescence-, infrared- and oriented circular dichroism spectroscopy, colorimetry, interface-sensitive X-ray and neutron scattering and Quartz crystal microbalance.
Effects of Timing Regularity and Metrical Expectancy on Spoken-Word Perception

Abstract Certain types of speech, e.g. lists of words or numbers, are usually spoken withhighly regular inter-stress timing. The main hypothesis of this study (derived fromthe Dynamic Attending Theory) is that listeners attend in particular to speech eventsat these regular time points. Better timing regularity should improve spoken-wordperception. Previous studies have suggested only a weak effect of speech rhythm onspoken-word perception, but the timing of inter-stress intervals was not controlledin these studies. A phoneme monitoring experiment is reported, in which listenersheard lists of disyllabic words in which the timing of the stressed vowels was eitherregular (with equidistant inter-stress intervals) or irregular. In addition, metricalexpectancy was controlled by varying the stress pattern of the target word, as eitherthe same or the opposite of the stress pattern in its preceding words. Resulting reac-tiontimes show a main effect of timing regularity, but not of metrical expectancy.These results suggest that listeners employ attentional rhythms in spoken-word per-ception,and that regular speech timing improves speech communication.
A Time/Frequency-Domain Unified Delayless Partitioned Block Frequency-Domain Adaptive Filter

In this letter, a delayless counterpart of the partitioned frequency-domain adaptive filter algorithm is straightforwardly derived from the block least-mean-square (BLMS) algorithm. To improve its tracking capability, a time/frequency-domain unified (TFU) adaptation scheme is proposed. It is further shown that other delayless realizations can be seen as simplified implementations of the TFU technique. Simulations are presented to support the analyses and demonstrate the good convergence and tracking performance of the proposed algorithm.
Understanding the participatory library through a grounded theory study

Lankes and Silverstein (2006) introduced the “participatory library” and suggested that the nature and form of the library should be explored. In the last several years, some attempts have been made in order to develop contemporary library models that are often known as Library 2.0. However, little research has been based on empirical data and such models have had a strong focus on technical aspects but less focus on participation. The research presented in this paper fills this gap. A grounded theory approach was adopted for this study. Six librarians were involved in in-depth individual interviews. As a preliminary result, five main factors of the participatory library emerged including technological, human, educational, social-economic, and environmental. Five factors influencing the participation in libraries were also identified: finance, technology, education, awareness, and policy. The study’s findings provide a fresh perspective on contemporary library and create a basis for further studies on this area.
Randomization inference and principal stratification in HIV prevention studies

TRACY L. NOLEN, MSTAT: RANDOMIZATION INFERENCE AND PRINCIPAL STRATIFICATION IN HIV PREVENTION STUDIES (Under the direction of Michael G. Hudgens, Ph.D.) Infectious disease prevention studies often aim to test or estimate the “causal effect” of a preventive measure on outcomes by comparing the potential outcomes individuals would have under treatment versus control. Examples of outcomes of interest include infection incidence or post-infection outcomes (e.g., disease severity, death). Two analytical challenges of interest exist for these studies. First, analyses on post-infection outcomes are subject to selection bias as only a subset of the randomized population become infected (i.e., infection status is a post-randomization measure on which analyses are often conditioned). Treatment comparisons conditional on post-randomization measures using standard analytic methods do not have a causal interpretation in that the estimates obtained are not unbiased estimates of the contrast between potential outcomes. The principal stratification framework provides estimates of treatment causal effect in the presence of potential selection bias due to post-randomization measures; however, existing methods comprise only Bayesian or large-sample frequentist approaches. To date a general approach to randomization inference within principal strata has not been developed. Furthermore, while principal stratification approaches are abundant in statistical literature, their presence as an applied analytic approach within infectious disease journals is limited. The second challenge of prevention studies involves the analysis of repeated low-dose mucosal challenge preclinical studies of potential vaccines which are becoming more prevalent in an attempt to conduct studies that better mirror ‘real life’ human transmission. Current statistical literature exploring the analysis of
An Instantiation of the Multiple-Transfer Framework to Reduce Efforts in Context Model Learning for New Users in Smart Homes

Since a real-life environment may encounter various uncertainties due to its dynamic nature, a smart-home system needs to improve its adaptability in response to the inevitable uncertainties. In this regard, a multi-transfer framework was proposed to keep context models adaptable in order to reduce the efforts in retraining context models in the event of an uncertainty. The framework is used to transfer knowledge from a source domain to a target one by reusing as much information from the source domain. This way, the efforts of training activity models for new users in the target domain can be effectively reduced. This paper presents one instantiation of the framework and its implementation details. The preliminary results show that the effort of training activity models for a new user can be effectively reduced meanwhile maintaining satisfactory performance.
Enhancing Alkane Production in Cyanobacterial Lipid Droplets: A ModeFl Platform for Industrially Relevant Compound Production

Cyanobacterial lipid droplets (LDs) are packed with hydrophobic energy-dense compounds and have great potential for biotechnological expression and the compartmentalization of high value compounds. Nostoc punctiforme normally accumulates LDs containing neutral lipids, and small amounts of heptadecane, during the stationary phase of growth. In this study, we further enhanced heptadecane production in N. punctiforme by introducing extrachromosomal copies of aar/adc genes, and report the discovery of a putative novel lipase encoded by Npun_F5141, which further enhanced alkane production. Extra copies of all three genes in high light conditions resulted in a 16-fold higher accumulation of heptadecane compared to the wild type strain in the exponential phase. LD accumulation during exponential phase also increased massively to accommodate the heptadecane production. A large number of small, less fluorescent LDs were observed at the cell periphery in exponential growth phase, whereas fewer number of highly fluorescent, much larger LDs were localized towards the center of the cell in the stationary phase. These advances demonstrate that cyanobacterial LDs are an ideal model platform to make industrially relevant compounds, such as alkanes, during exponential growth, and provide insight into LD formation in cyanobacteria.
A Practical Management and Engineering Approach to Offshore Collaboration

Firms developing or maintaining software products can't ignore global software development's impact. Managing multiple simultaneous projects and production support with a global staff over the last several years has also made us aware of traps to avoid. The global software development model provides a tactical approach for companies pursuing or planning to expand into offshore development. We present a practitioner's view of our model for offshore development and insights into our management and engineering techniques, which can be replicated in other environments. This article adds to the existing literature by providing a structural framework and the guidelines necessary to maintain the quality of offshore engagements
Underwater augmented reality game using the DOLPHYN

The introduction of virtual and mixed realities in aquatic leisure activities constitutes a technological rupture when compared with the status of related technologies. With the extension of Internet to underwater applications, the innovative character of the project becomes evident, and the impact of this development in the littoral and beach tourism may be considerable. In fact, there are recent developments to extend the use of computers and computer components, such as the mouse, to underwater uses. The Dolphyn is an underwater-computerized display system with various sensors and devices conceived for existing swimming pools and for beach shores, associating computer functions, video gaming and multisensory simulations.
Parameter Analysis of DDE-Based PID Controller Tuning Method

The PID controller tuning method based on desired dynamic equation is analyzed on its close-loop control performance and stability. The stable region calculation method for DDE-based PID controller is proposed based on Nyquist stability criterion and open-loop frequency response. Then the influence of tunable parameter k on set point tracking error is analyzed when the order of controller does not consist with the relative degree of process. Simulation indicates that for the linear system with relative degree unknown or higher than two, the tracking error decreases with the growth of parameter k initially and increases afterwards, so an optimal parameter k exists, but the scaling factor l could expand the feasible scope of k largely.
Support Vector Machine Used for Analysis Texture of Cirrhosis Liver

Diagnostic ultrasound is a useful and noninvasive method in clinical medicine. Although due to its qualitative, subjective and experience-based nature, ultrasound image interpretation can be influenced by image conditions such as scanning frequency and machine settings. In this paper, a method is proposed to extract the cirrhosis and normal liver features using the entropy of texture edge co-occurrence matrix based on ultrasound images, which is not sensitive to changes in emission frequency and gain. Then, support vector machine are employed to test a group of 30 in-vivo liver cirrhosis images from 18 patients, as well as other 30 liver images from 18 normal human volunteers. The results showed that the support vector machine was 94.4% in sensitivity for Liver Cirrhosis (LC) while neural network provided 92.31 % in LC [23], and the system was considered to be helpful for clinical and educational use.