Miracle-dz/UniFAR-FTUs huggingface dataset:
Long‐Term Exercise and Bone Mineral Density Changes in Postmenopausal Women—Are There Periods of Reduced Effectiveness?

There is increasing evidence that physical exercise can prevent fractures in postmenopausal women. However, even with careful adaptation of the exercise program to subjects' changing bone, health, and fitness status, effectivity may still decrease over the time. This could be specifically the case where the limitations of higher age collide with the specification of the exercise program. Thus, the aim of this study was to monitor bone mineral density (BMD) changes over a 16‐year period of supervised exercise. Our hypothesis was that BMD differences at lumbar spine (LS) and femoral neck (FN) between exercisers (EG) and nontraining controls (CG) increased throughout the intervention with significant differences for each of the four 4‐year observation periods. Sixty‐seven (EG, n = 39 versus CG, n = 28) initially early‐postmenopausal osteopenic women of the Erlangen Fitness and Osteoporosis Prevention Study (EFOPS) with complete BMD data sets for baseline (1998) and 4‐, 8‐, 12‐, and 16‐year follow‐up were included in the analysis. The exercise protocol initially focused on a high‐intensity strategy that addressed bone but increasingly shifted to a more comprehensive intervention. LS‐BMD differences between the EG and CG continuously increased (year 4: 2.4% (95%‐ Confidence Interval 1.0% to 3.8%), year 8: 3.1% (1.6% to 4.7%), year 12: 3.9% (1.9% to 5.8), year 16: 4.5% (2.5% to 6.6%). Correspondingly, rising differences for FN‐BMD (0.9% (–0.2% to 2.1%) versus 1.9% (0.4% to 3.3%) versus 2.0% (0.5% to 3.8%) versus 3.0% (1.0% to 5.0%)) were observed. However, in contrast to our hypothesis, group differences within the four 4‐year periods were not consistently significant (LS, p = 0.001 to 0.097; FN, p = 0.026 to 0.673); further, BMD kinetics among the groups varied between LS and FN. Of particular importance, significant differences (p ≤ 0.030) for both regions were still found in the final period. We conclude that exercise—even when adapted for subjects' decreasing bone, health, and fitness status—is consistently effective in favorably affecting BMD in (initially) early‐postmenopausal osteopenic women without any leveling‐off effect after 16 years of exercise. © 2015 American Society for Bone and Mineral Research.
Reconstruction Privacy: Enabling Statistical Learning

Non-independent reasoning (NIR) allows the information about one record in the data to be learnt from the information of other records in the data. Most posterior/prior based privacy criteria consider NIR as a privacy violation and require to smooth the distribution of published data to avoid sensitive NIR. The drawback of this approach is that it limits the utility of learning statistical relationships. The differential privacy criterion considers NIR as a non-privacy violation, therefore, enables learning statistical relationships, but at the cost of potential disclosures through NIR. A question is whether it is possible to (1) allow learning statistical relationships, yet (2) prevent sensitive NIR about an individual. We present a data perturbation and sampling method to achieve both (1) and (2). The enabling mechanism is a new privacy criterion that distinguishes the two types of NIR in (1) and (2) with the help of the law of large numbers. In particular, the record sampling effectively prevents the sensitive disclosure in (2) while having less effect on the statistical learning in (1).
Microbial Growth and Quorum Sensing Antagonist Activities of Herbal Plants Extracts

Antimicrobial and antiquorum sensing (AQS) activities of fourteen ethanolic extracts of different parts of eight plants were screened against four Gram-positive, five Gram-negative bacteria and four fungi. Depending on the plant part extract used and the test microorganism, variable activities were recorded at 3 mg per disc. Among the Gram-positive bacteria tested, for example, activities of Laurus nobilis bark extract ranged between a 9.5 mm inhibition zone against Bacillus subtilis up to a 25 mm one against methicillin resistant Staphylococcus aureus. Staphylococcus aureus and Aspergillus fumigatus were the most susceptible among bacteria and fungi tested towards other plant parts. Of interest is the tangible antifungal activity of a Tecoma capensis flower extract, which is reported for the first time. However, minimum inhibitory concentrations (MIC's) for both bacteria and fungi were relatively high (0.5-3.0 mg). As for antiquorum sensing activity against Chromobacterium violaceum, superior activity (>17 mm QS inhibition) was associated with Sonchus oleraceus and Laurus nobilis extracts and weak to good activity (8-17 mm) was recorded for other plants. In conclusion, results indicate the potential of these plant extracts in treating microbial infections through cell growth inhibition or quorum sensing antagonism, which is reported for the first time, thus validating their medicinal use.
Nonlinear Model Predictive Control using sampling and goal-directed optimization

In this paper a novel method called Sampling-Based Model Predictive Control (SBMPC) is proposed as an efficient MPC algorithm to generate control inputs and system trajectories. The algorithm combines the benefits of sampling-based motion planning with MPC while avoiding some of the major pitfalls facing both traditional sampling-based planning algorithms and traditional MPC. The method is based on sampling (i.e., discretizing) the input space at each sample period and implementing a goal-directed optimization method (e.g., A*) in place of standard numerical optimization. This formulation of MPC readily applies to systems with nonlinear dynamics and avoids the local minima which can limit the performance of MPC algorithms implemented using traditional, derivative-based, nonlinear programming. The SBMPC algorithm is compared with a more standard online MPC algorithm using cluttered environment navigation for an Ackerman steered vehicle and a set point problem for a nonlinear, continuous stirred-tank reactor (CSTR).
Faster GPS via the sparse fourier transform

GPS is one of the most widely used wireless systems. A GPS receiver has to lock on the satellite signals to calculate its position. The process of locking on the satellites is quite costly and requires hundreds of millions of hardware multiplications, leading to high power consumption. The fastest known algorithm for this problem is based on the Fourier transform and has a complexity of O(n log n), where n is the number of signal samples. This paper presents the fastest GPS locking algorithm to date. The algorithm reduces the locking complexity to O(n√(log n)). Further, if the SNR is above a threshold, the algorithm becomes linear, i.e., O(n). Our algorithm builds on recent developments in the growing area of sparse recovery. It exploits the sparse nature of the synchronization problem, where only the correct alignment between the received GPS signal and the satellite code causes their cross-correlation to spike. We further show that the theoretical gain translates into empirical gains for GPS receivers. Specifically, we built a prototype of the design using software radios and tested it on two GPS data sets collected in the US and Europe. The results show that the new algorithm reduces the median number of multiplications by 2.2x in comparison to the state of the art design, for real GPS signals.
A scalable protocol for content-based routing in overlay networks

In content networks, messages are routed on the basis of their content and the interests (subscriptions) of the message consumers. This form of routing offers an interesting alternative to unicast or multicast communication in loosely-coupled distributed systems with large number of consumers, with diverse interests, wide geographical dispersion, and heterogeneous resources (e.g., CPU, bandwidth). In this paper, we propose a novel protocol for content-based routing in overlay networks. This protocol guarantees perfect routing (i.e., a message is received by all, and only those, consumers that have registered a matching subscription) and optimizes the usage of the network bandwidth. Furthermore, our protocol takes advantage of subscription aggregation to dramatically reduce the size of the routing tables, and it fully supports dynamic subscription registrations and cancellations without impacting the routing accuracy. We have implemented this protocol in the application-level routers of an overlay network to build a scalable XML-based data dissemination system. Experimental evaluation shows that the size of the routing tables remains small, even with very large populations of consumers.
Subject Preference and Choice in Co-Educational and Single-Sex Secondary Schools.

Summary. The subject preferences and subject choices of 1,204 pupils in 19 secondary schools were investigated. Sex-linked polarisation of subject preferences were more marked in co-educational than in single-sex schools. An investigation of the effect of attitudes towards teachers showed a relationship between liking for teacher and subject preference, but not subject choice. The results are discussed in relation to the current reorganisation of secondary schools along co-educational, as well as comprehensive, lines.
Comparative proteome analysis of tracheal tissues in response to infectious bronchitis coronavirus, Newcastle disease virus, and avian influenza virus H9 subtype virus infection

Infectious bronchitis coronavirus (IBV), Newcastle disease virus (NDV), and avian influenza virus (AIV) H9 subtype are major pathogens of chickens causing serious respiratory tract disease and heavy economic losses. To better understand the replication features of these viruses in their target organs and molecular pathogenesis of these different viruses, comparative proteomic analysis was performed to investigate the proteome changes of primary target organ during IBV, NDV, and AIV H9 infections, using 2D‐DIGE followed MALDI‐TOF/TOF‐MS. In total, 44, 39, 41, 48, and 38 proteins were identified in the tracheal tissues of the chickens inoculated with IBV (ck/CH/LDL/97I, H120), NDV (La Sota), and AIV H9, and between ck/CH/LDL/97I and H120, respectively. Bioinformatics analysis showed that IBV, NDV, and AIV H9 induced similar core host responses involved in biosynthetic, catabolic, metabolic, signal transduction, transport, cytoskeleton organization, macromolecular complex assembly, cell death, response to stress, and immune system process. Comparative analysis of host response induced by different viruses indicated differences in protein expression changes induced by IBV, NDV, and AIV H9 may be responsible for the specific pathogenesis of these different viruses. Our result reveals specific host response to IBV, NDV, and AIVH9 infections and provides insights into the distinct pathogenic mechanisms of these avian respiratory viruses.
Meaning in Life: A Spiritual Matter—Projected Changes Post-Retirement for Baby Boomers

This article presents an understanding of the principal aspects of life that provide meaning in life for six baby boomers and how they might foresee that meaning change as they age. The qualitative aspect of the research undertaken is addressed. This article presents the rationale, aims, and importance of the study. The relationship between spirituality and meaning in life is explored and meaning in life from the baby boomers' perspective as revealed in literature is considered. Semi-structured interviews were used to collect the data. The study revealed that experiencing age-related negative changes could affect the meaning placed in life and therefore had the potential to affect overall well-being into later life.
Frequency Domain Passive Broadband Speaker Localization using a Permutation-Free Blind Source Separation Algorithm

Traditional passive broadband source localization techniques like maximum likelihood estimation and MUSIC have shown difficulties in situations where multiple correlating source signals are interfering with each other. Blind source separation (BSS) algorithms on the other hand have demonstrated good performance in separating correlated mixture signals into independent sources. In this paper it will be shown that the performance of traditional source localization algorithms can be improved by using a permutation-free frequency domain BSS algorithm as a front end. In addition a source localization method based solely on information gained from the separated BSS solution and sensor array architecture is presented. The methodologies are illustrated in an undercomplete acoustic scenario involving 3 speech sources and a 6 element microphone array.
Does training on self-regulated learning facilitate students' learning with hypermedia?

The authors examined the effectiveness of self-regulated learning (SRL) training in facilitating college students' learning with hypermedia. Undergraduate students (N = 131) were randomly assigned to either a training condition or a control condition and used a hypermedia environment to learn about the circulatory system. Students in the SRL group were given a 30-min training session on the use of specific, empirically based SRL variables designed to foster their conceptual understanding; control students received no training. Pretest, posttest, and verbal protocol data were collected from both groups. The SRL condition facilitated the shift in learners' mental models significantly more than did the control condition; verbal protocol data indicated that this was associated with the use of the SRL variables taught during training.
Designing a Role-Play Game for Learning Taiwan History and Geography

In recent years, digital games have been widely used in all fields for learning. Learners are immersed in the context and content, and have increased willingness to participate learning activities which implies the enhancement of learning motivations. The game built in this research was done with Oblivion game engine. First, we design a role-play game script according to the anti-Japanese war history and geography of Southern Taiwan. And then we import interactive map, roles, and contexts to construct the complete scene. We expect that learner can enhance the learning effectiveness to learning Taiwanese history and geography, as well as their learning motivation. The entertaining, challenging, rules, and interactive feedbacks of digital games can be transformed into learning motivations.
Shunt Active Power Filter with Selective Harmonics Compensation for LV distribution grid

A Shunt Active Power Filter (SAPF) employable in a Low Voltage distribution grid four-wires model is presented. The use of this device helps to improve Power Quality compensating harmonic currents, reactive power and current unbalances of a disturbing loads. Each compensating function can be activated or disabled according to the specific requirements of the application. A selective harmonic compensation is also possible, in order to avoid possible resonances at specific frequencies. A current hysteresis modulation with predictive calculation of threshold bands achieving fixed switching frequency is adopted for a fast dynamic response. The compensation performance of the proposed active power filter and the associate control scheme under steady state and transient conditions is demonstrated through digital simulations.
Is a lack of self‐confidence hindering women entrepreneurs?

Purpose – Studies have concluded that men tend to have higher self‐confidence than women and that this affects their entrepreneurial intentions. However, little is known about how self‐confidence affects entrepreneurs in their start‐up decision, and even less is understood about how it affects entrepreneurs' decisions and actions in their ongoing business. The purpose of this paper is to meet these two objectives by using a gender comparative approach.Design/methodology/approach – A total of 50 entrepreneurs (25 women and 25 men) in New Zealand were interviewed in a semi‐structured format.Findings – Women exhibit a lack of self‐confidence in their own abilities as entrepreneurs compared to men. This finding parallels results of prior research. Once in an established business, women relate to entrepreneurship less than men and do not feel comfortable calling themselves entrepreneurs. For some women, entrepreneurial self‐confidence grew over their time in business. For other women, it appears to continue to.
Valkyrie: Behavioral malware detection using global kernel-level telemetry data

The growth in malware remains a major challenge to Internet security. In this paper, we present Valkyrie, a classification system that is able to identify malicious binaries purely based on behavioral traits gathered from large-scale telemetry submitted by endhosts using a lightweight sensor component. Valkyrie utilizes the Apache Spark data processing framework and is therefore able to process a large volume of real-world data in a short amount of time. In addition, since Valkyrie conducts all its heavy computation in the cloud, it therefore imposes minimal load on endpoints. Valkyrie achieves high confidence predictions at a very low false positive rate, making it a suitable solution for use with production systems.
Anytime search-based footstep planning with suboptimality bounds

Efficient footstep planning for humanoid navigation through cluttered environments is still a challenging problem. Many obstacles create local minima in the search space, forcing heuristic planners such as A* to expand large areas. The goal of this work is to efficiently compute long, feasible footstep paths. For navigation, finding the optimal path initially is often not needed as it can be improved while walking. Thus, we propose anytime search-based planning using the anytime repairing A* (ARA*) and randomized A* (R*) planners. This allows to obtain efficient paths with provable suboptimality within short planning times. Opposed to completely randomized methods such as rapidly-exploring random trees (RRTs), these planners create paths that are goal-directed and guaranteed to be no more than a certain factor longer than the optimal solution. We thoroughly evaluated the planners in various scenarios using different heuristics. ARA* with the 2D Dijkstra heuristic yields fast and efficient solutions but its potential inadmissibility results in non-optimal paths for some scenarios. R*, on the other hand borrows ideas from RRTs, yields fast solutions, and is less dependent on a well-designed heuristic function. This allows it to avoid local minima and reduces the number of expanded states.
A Visual Landmark Recognition System for Autonomous Robot Navigation

This paper presents a vision system for autonomously guiding a robot along a known route using a single CCD camera. The prominent feature of the system is the real-time recognition of shape-based visual landmarks in cluttered backgrounds, using a memory feedback modulation (MFM) mechanism, which provides a means for the knowledge from the memory to interact and enhance the earlier stages in the system. Its feasibility in autonomous robot navigation is demonstrated in both indoor and outdoor experiments using a vision-based navigating vehicle.
Exploring the role of Ba in family business context

Purpose – The purpose of this paper is to analyze the family business succession process using Nonaka's theory of knowledge creation and conceptualisation of a knowledge‐creating place, Ba to enhance one's understanding of critical managerial challenges in family business succession.Design/methodology/approach – Based on literature review, Nonaka's theory of knowledge creation and knowledge‐creating space is applied to the family business succession process.Findings – Through literature review and synthesis thereof the paper concludes that Nonaka's theory of knowledge creation is a highly valid framework for analyzing and supporting the family business succession process. The paper proposes that Ba is a perception of a place – the family firm – and a shared purpose among family members in that firm. It is posited that the absence of Ba can be a significant barrier to a family firm adopting a successful succession process. Creating a Ba is essential for family firms to survive.Research limitations/implicat.
Sequence similarity between multidrug resistance efflux pumps of the ABC and RND superfamilies.

Recently, Venter et al. (2003) used molecular genetic techniques to cleave the ATP-hydrolysing domain from the integral membrane transporter domain of LmrA and demonstrated that the latter could catalyse drug transport driven by the transmembrane proton electrochemical gradient. Substrate : proton symport or antiport is a general characteristic of simple carriers also called secondary active transporters. Their observations suggested that the primary active transporter, LmrA, was derived from a secondary carrier by superimposition of the ATP-hydrolysing subunit onto the carrier during evolution as suggested previously (Saier, 2000a).
Human milk glycobiome and its impact on the infant gastrointestinal microbiota

Human milk contains an unexpected abundance and diversity of complex oligosaccharides apparently indigestible by the developing infant and instead targeted to its cognate gastrointestinal microbiota. Recent advances in mass spectrometry-based tools have provided a view of the oligosaccharide structures produced in milk across stages of lactation and among human mothers. One postulated function for these oligosaccharides is to enrich a specific “healthy” microbiota containing bifidobacteria, a genus commonly observed in the feces of breast-fed infants. Isolated culture studies indeed show selective growth of infant-borne bifidobacteria on milk oligosaccharides or core components therein. Parallel glycoprofiling documented that numerous Bifidobacterium longum subsp. infantis strains preferentially consume small mass oligosaccharides that are abundant early in the lactation cycle. Genome sequencing of numerous B. longum subsp. infantis strains shows a bias toward genes required to use mammalian-derived carbohydrates by comparison with adult-borne bifidobacteria. This intriguing strategy of mammalian lactation to selectively nourish genetically compatible bacteria in infants with a complex array of free oligosaccharides serves as a model of how to influence the human supraorganismal system, which includes the gastrointestinal microbiota.
Privacy-preserving inference in crowdsourcing systems

Machine learning has widely been used in crowdsourcing systems to analyze the behavior of their mobile users. However, it naturally raises privacy concerns, as personal data needs to be collected and analyzed in the cloud, and results need to be sent back to the users to improve their local estimates. In this paper, we focus on the use of a specific type of learning algorithms, called maximum a posteriori (MAP) inference, in crowdsourcing systems, and use a crowdsourced localization system as an example. With MAP inference, the accuracy of each estimate of the user state may be improved by analyzing other users' estimates. Naturally, the privacy of the user state needs to be protected. Within the general framework of differential privacy, we show how private user states can be perturbed while preserving statistically accurate results. For the crowdsourcing system, we design a non-interactive mechanism for a group of users to perform inference without revealing their true states to any other party. The mechanism is implemented and verified in an indoor localization system. By comparing with the state-of-the-art, we have shown that our proposed privacy-preserving mechanism produces highly accurate results efficiently.