Miracle-dz/UniFAR-FTUs huggingface dataset:
Mechanical Stimulation of Mesenchymal Stem Cell Proliferation and Differentiation Promotes Osteogenesis While Preventing Dietary‐Induced Obesity

Mesenchymal stem cells (MSCs) are defined by their ability to self‐renew and differentiate into the cells that form mesodermal tissues such as bone and fat. Low magnitude mechanical signals (LMMS) have been shown to be anabolic to bone and have been recently reported to suppress the development of fat in normal animals fed a regular diet. Using male C57BL/6J mice, the ability of LMMS (0.2g, 90‐Hz signal applied for 15 min/d, 5 d/wk) to simultaneously promote bone formation and prevent diet‐induced obesity was correlated to mechanical influences on the molecular environment of the bone marrow, as indicated by the population dynamics and lineage commitment of MSCs. Six weeks of LMMS increased the overall marrow‐based stem cell population by 37% and the number of MSCs by 46%. Concomitant with the increase in stem cell number, the differentiation potential of MSCs in the bone marrow was biased toward osteoblastic and against adipogenic differentiation, as reflected by upregulation of the transcription factor Runx2 by 72% and downregulation of PPARγ by 27%. The phenotypic impact of LMMS on MSC lineage determination was evident at 14 wk, where visceral adipose tissue formation was suppressed by 28%, whereas trabecular bone volume fraction in the tibia was increased by 11%. Translating this to the clinic, a 1‐yr trial in young women (15–20 yr; n = 48) with osteopenia showed that LMMS increased trabecular bone in the spine and kept visceral fat at baseline levels, whereas control subjects showed no change in BMD, yet an increase in visceral fat. Mechanical modulation of stem cell proliferation and differentiation indicates a unique therapeutic target to aid in tissue regeneration and repair and may represent the basis of a nonpharmacologic strategy to simultaneously prevent obesity and osteoporosis.
Prevalence and Impact of Cerebrovascular Lesions in Alzheimer and Lewy Body Diseases

Background: Data on the prevalence of cerebrovascular lesions (CVLs) and their impact on cognitive decline in Alzheimer disease (AD) and Lewy body disease are conflicting. Objective: Retrospective examination of the prevalence of CVL in a consecutive autopsy series. Material and Methods: 1,339 cases of autopsy-proven AD, Parkinson disease (PD), dementia with Lewy bodies (± AD), and 486 age-matched controls were examined according to standardized neuropathologic methods including immunohistochemistry. Diagnoses followed current consensus criteria, classification of CVLs and of cerebral amyloid angiopathy (CAA) in 5 grades [Acta Neurol Scand 2006;114:38–46; Acta Neuropathol 2005;110:345–359]. Results: Lewy body variant of AD and AD showed significantly more frequent CVLs (91.9 and 67.8%) than the other groups (29.4 to 45.7%), with the highest frequency of severe CVLs (old, recent infarcts and hemorrhages) in AD (23.6%), but 2.0–8.3% in the other groups. Severe CAA was most frequent in AD and the Lewy body variant of AD (97.9 and 85%), less in PD (36%) and controls (30%). CAA was more frequent/severe in demented than in nondemented cases. CVLs in cortico-subcortical and hippocampal areas were most frequent in AD; subcortical CVLs (lacunes) in both AD and PD were more frequent than in controls. The incidence and severity of CVLs significantly correlated with neuritic Braak stages. Cognitive impairment was largely independent of coexisting CVLs, but related to the severity/location of AD and/or Lewy pathology. Conclusions: The present data confirm the importance of CVLs in AD and in dementia with Lewy bodies with severe AD, and the little impact of CVLs alone, but show a close association of CAA with clinical dementia associated with AD pathology.
Novel Bayesian Inference Algorithms for Multiuser Detection in M2M Communications

The fifth generation and future wireless networks are expected to support massive machine-to-machine (M2M) communications. Due to the sporadic nature, massive M2M communications can be well supported by low-activity code division multiple access (LA-CDMA). In the literature, maximum a posteriori detector has been proposed to detect the active users in LA-CDMA when the user activity factor is known and small. However, such user activity factor is usually unknown and could be large in practice, which makes the multiuser detection for LA-CDMA a challenging task. In this paper, we first formulate the LA-CDMA uplink using single measurement vector (SMV) model and multiple measurement vector (MMV) model, then, propose novel Bayesian inference algorithms to recover the transmitted signals. For SMV model, we first introduce sparse Bayesian learning (SBL) that exploits the sparsity of the transmitted signals, then, add on the known finite-alphabet constraints and introduce Gaussian mixture model method to recover the transmitted signals. For MMV model, pattern coupled SBL (PCSBL) algorithm is introduced that takes into consideration the neighbor coherence of each device, then the block SBL is introduced through exploiting the row sparsity property and the column coherence of each device. The four Bayesian inference methods make use of various priors and hyperparameters, which can be autonomously learned through the training process via expectation maximization (EM) or variational EM iterative algorithms. Furthermore, the proposed Bayesian methods do not require the knowledge of user activity factor. Simulation results have shown that the proposed Bayesian inference methods outperform the classical algorithms.
Resolution of Disagreements between Romantic Partners, among Adolescents, and Young Adults: Qualitative Analysis of Interaction Discourses.

The study was designed to explore qualitatively developmental differences in disagreement negotiation and resolution skills between adolescent and young adult romantic partners. Twenty adolescent and 20 young adult couples participated in the study. The Knox inventory was used to measure the level of disagreement between partners on ten domains (e.g., friends or money). Partners were asked to discuss and resolve their greatest disagreement. Joint discussions were recorded and transcribed. A qualitative analysis of interactions revealed major differences between the two age groups, in discussion management and in strategies for resolution. Adolescents' interactions were concrete, concise, and brief. Their resolution of disagreements was based on superficial agreements or coercion of one partner. Young adults' interactions were more rich and developed, disagreements were understood as metaphors for the relationship, and resolution was accomplished by the two partners as a result of discussion. These differences are discussed in light of the theories on the development of romantic relationships.
Probability estimation and machine learning—Editorial

Most of this issue of the Biometrical Journal is dedicated to the special topic of probability estimation. The topic is introduced and detailed by the two comprehensive twin papers by Kruppa et al. (2014a, 2014b) on theory and applications compiled by a group of authors who had recently worked together, focusing in particular on machine learning methods. This work is then discussed in ﬁve accompanying commentaries (Binder, 2014; Boulesteix and Schmid, 2014; Shin and Wu, 2014; Simon, 2014; Steyerberg et al., 2014) which have been invited by the editors of the journal, and a reply is ﬁnally given by Andreas Ziegler (2014), the communicating author of the twin papers. Solicited by the editors, this Editorial would like to encourage the readers of the Biometrical Journal to look into probability estimation and machine learning in more detail. When going through the following papers, readers of the Biometrical Journal may get the impression that, ﬁnally, machine learning techniques have arrived in the journal. However, it is surely not the ﬁrst time that there were contributions concerning this topic; a simple search using the term “machine learning” identiﬁes over 50 contributions over the past ten years where this method played a role. What is new, however, is that the articles by Kruppa et al. (2014a, 2014b) give a comprehensive overview of theoretical as well as practical aspects of probability estimation using machine learning methods. In the spectrum of methods, they follow more or less what is considered valuable in recent textbooks, such as in the popular Hastie-Tibshirani-Friedman book on “Elements of Statistical Learning” (2009) and others (Berk, 2010; Malley et al., 2011). So, for example, nonparametric regression, random forests, k-nearest neighbors and support vector machines are covered. What makes the overview special is that it concentrates on probability estimation
A Study on the Use of Lexical Chunks by Chinese EFL Learners in Writing

Lexical Approach put forward by Michael Lewis (1993) is widely acknowledged in EFL teaching and lexical teaching is very important development in the evolution of language teaching (Lowe, 2003). For about thirty years of teaching English as a foreign language (EFL) in China, more and more teachers have realized the importance of teaching and encouraging learners to use ready-made lexical chunks. However, the present study focuses on the overuse of lexical chunks in learners’ writings in a high stake national test (College English Test Band 6 – CET6). The corpus-based data analysis will be done to find the most commonly used lexical chunks by Chinese EFL learners and demonstrate what is meant to be the overuse of lexical chunks. Furthermore, the reasons for misuse and overuse of lexical chunks will be discussed. The findings drawn from structural and functional analysis of lexical chunks also have some pedagogical implications.
Adaptive Fuzzy Approaches to Modelling Operator Functional States in a Human-Machine Process Control System

This paper assesses the operator functional state (OFS) of human operators based on a collection of psychophysiological and performance measures. Two types of adaptive fuzzy models, namely ANFIS (adaptive-network-based fuzzy inference system) and GA (genetic algorithm) based Mamdani fuzzy model, are employed to estimate the OFSs under a set of simulated process control tasks involved in an automation-enhanced cabin air management system (aCAMS). The adaptive fuzzy modelling procedures are described and then validated using real-life data measured from such a simulated human-machine process control system.
Physical Activity and Aging

Most human beings experience peak physical performance in their late teens and begin a slow decline in their early 20s, whose course is greatly affected by the activity levels undertaken by individuals in the years that follow. Many studies provide evidence that in developed nations such as the U.S., a sedentary lifestyle contributes significantly to development of the major risk factors for age‐related disease, prominent among them obesity, diabetes, and hypertension. Conversely, numerous studies document the benefits of physical activity, and in particular structured exercise programs, not only for reducing disease risk and improving physical performance, but also for enhancing substantially the quality of daily life. Aerobic and resistance training have complementary benefits, and can be undertaken at almost any age and physical condition, given appropriate medical clearance and supervision as warranted.
Staff Incentive Policies for Credit Officers : An analysis of their effects within heterogeneous firms and contexts and across multiple tasks

This paper explores how changes in monetary staff incentive contracts affect the productivity of credit officers within microfinance institutions. The study uses a unique data set from five microfinance institutions that includes productivity data at the credit officer level for several months before and after a change in the incentive schemes. In each of the institutions, the monetary incentives were increased from a relatively weak-powered scheme to a moderately strong-powered scheme. The effects were quite significant on various measures of productivity but were notably heterogeneous across tasks, individuals, branches, and institutions. The results are consistent with an expanded principal-agent framework that also accounts for noncontractible differences in local market conditions.
Factors Associated with Cell Phone Use in Adolescents in the Community of Madrid (Spain)

The purpose of this research is to measure cell phone use among high school adolescents and the factors associated with intensive cell phone use (depressive symptoms, social isolation, drug and alcohol use, school failure, and cell phone dependence). We conducted a cross-sectional survey study of 1,328 adolescents aged 13 to 20 years in nine secondary schools of the Community of Madrid between January to April 2007. The mean age of sample participants was 15.7 years. Almost all (96.5%) had their own cell phone (80.5% had one, and 15.9% had two or more). Some 54.8% take it to school and 46.1% keep it on during class; 41.7% use it intensively. The estimated prevalence of cell phone dependence was 20% (26.1% in females, 13% in males). Intensive cell phone use was associated with female sex, rural school location, good family economy, smoking tobacco, excessive alcohol consumption, depression, cell phone dependence, and school failure. More health education is needed to promote correct and effective cell phone use among adolescents. Factors associated with intensive use and dependence should be considered for possible intervention activities.
A Collaborative and Content Based Event Recommendation System Integrated with Data Collection Scrapers and Services at a Social Networking Site

There are many activities that people prefer/opt out attending and these events are announced for attracting people. An intelligent recommendation system can be used in a social networking site in order to recommend people according to content and collaboration assessment. This study is an effort to recommend events to users within a social networking site. It can be any networking environment. We have used social environment that has been designed as a facebook application. Our application has also been integrated with several web sites. System collects event data from several related web sites either by using web services or web scraping. It also permits users rating events they have attended or planned. Given the social network between people, system tries to recommend upcoming events to users. For this purpose a combination of content based and collaborative filtering has been used. We have also taken geographical location info and social concept of an event.
Hard Homogeneous Spaces

This note was written in 1997 after a talk I gave at the seminaire de complexite et cryptographie at the ´ Ecole Normale Superieure After it was rejected at crypto97 I forgot it until a few colleagues of mine informed me that it could be of some interest to some researchers in the field of algorithmic and cryptography. Although I am not quite happy with the redaction of this note, I believe it is more fair not to improve nor correct it yet. So I leave it in its original state, including misprints. I just added this introductory paragraph. If need be, I will publish an updated version later. We introduce the notion of hard homogeneous space (HHS) and briefly develop the corresponding theory. We show that cryptographic protocols based on the discrete logarithm problem have a counterpart for any hard homogeneous space. Indeed, the notion of hard homogeneous space is a more general and more natural context for these protocols. We exhibit conjectural hard homogeneous spaces independant from any discrete log- arithm problem. They are based on complex multiplication theory. This shows the existence of schemes for authentication and key exchange that do not rely on the difficulty of computing dicrete logarithm inany finite group nor factoring integers. We show that the concept of HHS fits with class field theory to provide a unified theory for the already used discrete logarithm problems (on multiplicative groups of finite fields or rational points on elliptic curves) and the HHS we present here. We discuss a few algorithmic questions related to hard homogeneous spaces. The paper is looking for a wider point of view on the discrete logarithm problem both mathematically and cryptographically.
Support for data parallelism in the CAL actor language

With the arrival of heterogeneous manycores comprising various features to support task, data and instruction-level parallelism, developing applications that take full advantage of the hardware parallel features has become a major challenge. In this paper, we present an extension to our CAL compilation framework (CAL2Many) that supports data parallelism in the CAL Actor Language. Our compilation framework makes it possible to program architectures with SIMD support using high-level language and provides efficient code generation. We support general SIMD instructions but the code generation backend is currently implemented for two custom architectures, namely ePUMA and EIT. Our experiments were carried out for two custom SIMD processor architectures using two applications. The experiment shows the possibility of achieving performance comparable to hand-written machine code with much less programming effort.
Conformational space annealing and an off-lattice frustrated model protein

A global optimization method, conformational space annealing (CSA), is applied to study a 46-residue protein with the sequence B9N3(LB)4N3B9N3(LB)5L, where B, L, and N designate hydrophobic, hydrophilic, and neutral residues, respectively. The 46-residue BLN protein is folded into the native state of a four-stranded β barrel. It has been a challenging problem to locate the global minimum of the 46-residue BLN protein since the system is highly frustrated and consequently its energy landscape is quite rugged. The CSA successfully located the global minimum of the 46-mer for all 100 independent runs. The CPU time for CSA is about seventy times less than that for simulated annealing (SA), and its success rate (100%) to find the global minimum is about eleven times higher. The amount of computational effort used for CSA is also about ten times less than that of the best global optimization method yet applied to the 46-residue BLN protein, the quantum thermal annealing with renormalization. The 100 separate CS.
Sampling Bias in Population Studies—How to Use the Lexis Diagram

Modified versions of the lifetime distribution are often used in survival analysis. The modifications depend on how we choose individuals for the study and on the assumptions on the behaviour of the population. A rigorous point process description of the Lexis diagram is used to make the sampling mechanisms and the preconditions transparent. The point process description gives a framework to handle all possible sampling patterns. The set‐up is generalized so it can handle more complicated life descriptions than just lifetimes, and the diability model is used as an example. Two set‐ups can be used. Conditional on the birthtimes, the lifetime distribution is left truncated and subject to either right censoring or right truncation. Assuming that the birthtimes can be described by a Poisson process the modifications are length bias and the recurrence time distribution known from renewal theory.
Verbal Learning Changes in Older Adults Across 18 Months

ABSTRACT The major aim of this study was to investigate individual changes in verbal learning across a period of 18 months. Individual differences in verbal learning have largely been neglected in the last years and, even more so, individual differences in change in verbal learning. The sample for this study comes from the Zurich Longitudinal Study on Cognitive Aging (ZULU; Zimprich et al., 2008a) and comprised 336 older adults in the age range of 65–80 years at first measurement occasion. In order to address change in verbal learning we used a latent change model of structured latent growth curves to account for the non-linearity of the verbal learning data. The individual learning trajectories were captured by a hyperbolic function which yielded three psychologically distinct parameters: initial performance, learning rate, and asymptotic performance. We found that average performance increased with respect to initial performance, but not in learning rate or in asymptotic performance. Further, variances and covariances remained stable across both measurement occasions, indicating that the amount of individual differences in the three parameters remained stable, as did the relationships among them. Moreover, older adults differed reliably in their amount of change in initial performance and asymptotic performance. Eventually, changes in asymptotic performance and learning rate were strongly negatively correlated. It thus appears as if change in verbal learning in old age is a constrained process: an increase in total learning capacity implies that it takes longer to learn. Together, these results point to the significance of individual differences in change of verbal learning in the elderly.
Parallelization of Real-time Control Algorithms on Multi-core Architectures using Ant Colony Optimization

The emerging digitalization of production is accelerating the transformation of Industrial Control Systems (ICSs) from simple logic controllers to sophisticated systems utilizing complex algorithms which are running under strict real-time conditions. The required performance has now reached the limitations of single-core processors, making a transition to multi-core systems necessary. The parallelization of the currently monolithic and sequentially designed control algorithms is a complex problem that is further complicated by inherent hardware dependencies and real-time requirements. A fine-grained distribution of the algorithms on multiple cores while maintaining deterministic behavior is required but cannot be achieved with state of the art parallelization and scheduling algorithms. This paper presents a new parallelization approach for mapping and scheduling of model-based designs of control algorithms onto ICSs. Since the mapping and scheduling problem is N P -complete, an ACO algorithm is utilized and the solution is validated by experimental results.
The Fitzpatrick skin type scale: a reliability and validity study in women undergoing radiation therapy for breast cancer.

OBJECTIVE This study aimed to evaluate the internal consistency reliability and construct validity of the Fitzpatrick Skin Type Scale during radiation therapy in a cohort of women receiving treatment for breast cancer. METHOD The assessment of the scale was performed as a nested study within a randomised controlled trial of two creams used for radiation therapy skin care for breast cancer patients. The sample consisted of 244 female patients undergoing radiation therapy for breast cancer. Participants completed a modified version of the Fitzpatrick Skin Type Scale. RESULTS Internal consistency as measured by Cronbach's alpha was 0.505, 0.829 and 0.339 for the Genetic Disposition, Sun Exposure and Tanning Habits subscales respectively. Only the Sun Exposure subscale surpassed the 0.70 cut-off, indicating good internal consistency. Maximum likelihood factor analysis with promax rotation method confirmed the a priori factor structure for the Sun Exposure subscale as well as providing evidence of construct validity for this subscale. Analysis for the other two subscales highlighted issues with internal reliability and construct validity suggesting that not all items on each subscale truly measure the intended trait. CONCLUSION The study findings support reliability and validity of the Sun Exposure subscale of the Fitzpatrick Skin Type Scale in a convenience sample of women receiving radiation therapy for cancer. Despite limitations with two of the three subscales, this tool continues to be used in clinical practice.