Miracle-dz/UniFAR-FTUs huggingface dataset:
Napping in College Students and Its Relationship With Nighttime Sleep

Abstract. Objective: To examine the habit of napping and its relationship with nighttime sleep in college students. Participants: Four hundred and forty undergraduate students who responded to an anonymous online survey in April 2010. Methods: Three questions were asked to determine the frequency, length, and timing of napping during the past month. Sleep quality was measured by the Pittsburgh Sleep Quality Index (PSQI). Results: The PSQI score significantly differed among self-reported nap-frequency (p = .047) and nap-length (p = .017) groups, with those who napped more than 3 times per week and those who napped more than 2 hours having the poorest sleep quality. Students who napped between 6 and 9 pm had shorter sleep on school nights compared with students in other nap-timing groups (p = .002). Conclusions: College students who are self-reported frequent, long, and late nappers may have a higher risk of poor nighttime sleep quality and more severe sleep deprivation.
NF-κB inhibits osteogenic differentiation of mesenchymal stem cells by promoting β-catenin degradation

Mesenchymal stem cell (MSC)-based transplantation is a promising therapeutic approach for bone regeneration and repair. In the realm of therapeutic bone regeneration, the defect or injured tissues are frequently inflamed with an abnormal expression of inflammatory mediators. Growing evidence suggests that proinflammatory cytokines inhibit osteogenic differentiation and bone formation. Thus, for successful MSC-mediated repair, it is important to overcome the inflammation-mediated inhibition of tissue regeneration. In this study, using genetic and chemical approaches, we found that proinflammatory cytokines TNF and IL-17 stimulated IκB kinase (IKK)–NF-κB and impaired osteogenic differentiation of MSCs. In contrast, the inhibition of IKK–NF-κB significantly enhanced MSC-mediated bone formation. Mechanistically, we found that IKK–NF-κB activation promoted β-catenin ubiquitination and degradation through induction of Smurf1 and Smurf2. To translate our basic findings to potential clinic applications, we showed that the IKK small molecule inhibitor, IKKVI, enhanced osteogenic differentiation of MSCs. More importantly, the delivery of IKKVI promoted MSC-mediated craniofacial bone regeneration and repair in vivo. Considering the well established role of NF-κB in inflammation and infection, our results suggest that targeting IKK–NF-κB may have dual benefits in enhancing bone regeneration and repair and inhibiting inflammation, and this concept may also have applicability in many other tissue regeneration situations.
Fuzzy Particle Filtering for Uncertain Systems

In this paper, we propose a novel fuzzy particle filtering method for online estimation of nonlinear dynamic systems with fuzzy uncertainties. This approach uses a sequential fuzzy simulation to approximate the possibilities of the state intervals in the state-space, and estimates the state by fuzzy expected value operator. To solve the degeneracy problem of the fuzzy particle filter, one corresponding resampling technique is introduced. In addition, we compare the fuzzy particle filter with ordinary particle filter in both aspects of the theoretical basis and algorithm design, and demonstrate that the proposed filter outperforms standard particle filters especially when the number of the particles is small. The numerical simulations of two continuous-state nonlinear systems and a jump Markov system are employed to show the effectiveness and robustness of the proposed fuzzy particle filter.
An Efficient Multicast Distribution Scheme Combining Erasure Codes and Direct Requests

For the efficient multicast distribution services on the Internet, suppressing the influence of packet loss is important issues. As a solution of this problem, Forward Error Correction (FEC) based on Reed-Solomon codes is usually used. However, in the case of content delivery services for a large amount of data, this approach is not suitable. In this paper, we focus on the erasure codes which are new approach of FEC and propose the efficient multicast video distribution method which combines the multicast distribution using erasure codes and direct request to the server. We implement proposal method and confirm its efficiency from the viewpoints of redundancy and processing time.
Long-Term Intrathecal Infusion of Outer Surface Protein C From Borrelia burgdorferi Causes Axonal Damage

Lyme neuroborreliosis (LNB) is the most frequent tick-borne infectious disease of the central nervous system. In acute LNB and the rare chronic state of infection, patients can experience cognitive deficits such as attention and memory disturbances. During LNB, single compounds of Borrelia burgdorferi sensu lato are released into the subarachnoid space. To investigate the pathogenesis of neurologic dysfunction in LNB, we determined that the outer surface protein C (OspC), a major virulence factor of B. burgdorferi, stimulated mouse microglial cells in a dose-dependent manner to release nitric oxide (EC50 = 0.24 mg/L) in vitro. To mimic pathophysiologic conditions of long-term release of this bacterial component in vivo, we treated C57BL/6 mice with recombinant OspC from Borrelia garinii or buffer by intraventricular infusion and tested them for behavioral deficits. After 4weeks, brains were examined by routine histology and immunohistochemistry. Assessment of spatial learning and memory of treated mice during OspC exposure did not reveal significant differences from controls. Continuous exposure to intrathecal B. burgdorferi OspC led to activation of microglia and axonal damage without demonstrable cognitive impairment in experimental mice. These results suggest that long-term intrathecal exposure to OspC resulted in axonal damage that may underlie the neurologic manifestations in chronic LNB.
Psychometric Properties of Spanish Version of the Three-Factor Eating Questionnaire-R18 (Tfeq-Sp) and Its Relationship with Some Eating- and Body Image-Related Variables

The aims of this study were to analyze the psychometric properties of the Spanish version of the Three-Factor Eating Questionnaire-R18 (TFEQ-SP), as well as determine its validity by evaluating the relationship of the TFEQ-SP with different parameters related to body mass index, weight perception, perception of physical fitness, self-esteem, and food intake, as well as with weight control-related variables. A total of 281 participants (aged 18.38 ± 6.31) were studied. The factor analysis yielded three factors: cognitive restraint (CR), uncontrolled eating (UE), and emotional eating (EE). The internal consistency of the TFEQ-SP was determined by means of Cronbach’s α coefficient, with values ranging between 0.75 and 0.87. Higher scores on CR were found in women (p < 0.5), overweight/obese participants (p < 0.001), participants with lower self-esteem (p < 0.05), participants who overestimated their weight (p < 0.001), participants who weighed themselves frequently (p < 0.001) and those who were about to go on a diet (p < 0.001). Higher EE scores were found in participants with lower self-esteem scores (p < 0.05), among participants with a poorer perception of their physical fitness (p < 0.01) and when participants were about to diet (p < 0.05). Higher scores on UE were observed in case of poorer perception of physical fitness (p < 0.05). The validation study of the TFEQ-SP meets the requirements for measuring the three different facets of eating behavior: CR, UE, and EE.
Comparing traditional and virtual group forms: identity, communication and trust in naturally occurring project teams

This study compares three types of project teams in a global high-tech organization: traditional (co-located), virtual (completely distributed), and ‘semi-virtual’ or hybrid (containing both local and remote members). We use in-group/out-group theories of subgroups to help explain the findings. Specifically, local members of semi-virtual teams report much more positive perceptions of their local than their remote members, while traditional and virtual team members appear similar. We conclude by drawing implications for practice, such as the avoidance of semi-virtual teams whenever possible and the development of strong team identities.
A new approach to defining disease status in ankylosing spondylitis: the Bath Ankylosing Spondylitis Disease Activity Index.

OBJECTIVE Disease status, in terms of disease activity, disease progression and prognosis is difficult to define in ankylosing spondylitis (AS). No gold standard exists. Therefore, the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), a self-administered instrument, has been developed as a new approach to defining disease activity in patients with AS. METHODS The index, designed by a multidisciplinary team with input from patients, consists of six 10 cm horizontal visual analog scales to measure severity of fatigue, spinal and peripheral joint pain, localized tenderness and morning stiffness (both qualitative and quantitative). The final BASDAI score has a range of 0 to 10. The index was distributed to a cross section of patients, including inpatients receiving 3 weeks of intensive physiotherapy treatment and hospital outpatients. BASDAI was completed by a total of 154 patients. Validation of the new instrument was achieved through analysis of user friendliness, reliability (consistency), score distribution and sensitivity to change. Comparisons were made with a previous Bath disease activity index (DAI) and the Newcastle Enthesis Index. RESULTS The BASDAI was found by patients to be quick and simple to complete (mean: 67 s). Test-retest reliability was good (r = 0.93; p < 0.001), as was the distribution of scores across the scale (score range: 0.5-10; mean: 4.31). BASDAI was sensitive to change, reflecting a 16% (mean) improvement in inpatient scores after 3 weeks of treatment. It is superior to the DAI in terms of construct and content validity and to the Enthesis Index in all aspects. CONCLUSION In summary, BASDAI is user friendly, reliability, sensitive to change and reflects the entire spectrum of disease. It is a comprehensive self-administered instrument for assessing disease activity in AS.
The relationship between dementia and direct involvement of the hippocampus and amygdala in Parkinson's disease

Severe dementia affects 10 to 20% of all patients with Parkinson's disease(PD) and is particularly common in those aged 65 years and over. In a clinicopathologic study, we correlated Mini-Mental State Examination scores and DSM-III dementia ratings with the density of Lewy bodies, Lewy neurites, neurofibrillary tangles, neuritic plaques, gliosis, and neurons in the hippocampus and amygdala of 27 PD patients without Alzheimer's disease changes. Cortical Lewy body densities were examined in the anterior cingulate gyrus. The degree of cognitive impairment was correlated with the density of Lewy neurites in the CA2 hippocampal field, raising the possibility that disruption of the connection between the dentate gyrus, entorhinal cortex, septal nuclei, and hypothalamus and the CA1 field contributes to dementia in PD.
RIPPNET: Efficient range indexing in peer-to-peer networks

Write-heavy applications present a challenge to peer-to-peer indexing methods which need to update the index for each write operation. The costs incurred when the distributed index is updated becomes a bottleneck. Current distributed indexing methods are designed for indexing and retrieving single tuples, giving a very high update cost. In this paper we present a new approach to efficient peer-to-peer range indexing that employs indexing of ranges to reduce average update costs as well as providing efficient data localization and decoupling from data placement policies. Based on results from experiments, we demonstrate the applicability and significantly reduced update cost of the new approach.
Holy Moses! Leveraging Existing Tools and Resources for Entity Translation

Recently, there has been an emphasis on creating shared resources for natural language processing applications. This has resulted in the development of high-quality tools and data, which can then be leveraged by the research community as components for novel systems. In this paper, we reuse an open source machine translation framework to create an Arabic-to-English entity translation system. The system first translates known entity mentions using a standard phrase-based statistical machine translation framework, which is then reused to perform name transliteration on unknown mentions. In order to transliterate names more accurately, we introduce an algorithm to augment a names database with name origin and frequency information from existing data resources. Origin information is used to learn name origin classifiers and origin-specific transliteration models, while frequency information is used to select amongst n-best transliteration candidates. This work demonstrates the feasibility and benefit of adapting such data resources and shows how off-the-shelf tools and data resources can be repurposed to rapidly create a system outside their original domain.
Optimum estimation via partition functions and information measures

In continuation to a recent work on the statistical-mechanical analysis of optimum estimation in Gaussian noise via its relation to the mutual information (I-MMSE relation), here we propose a more direct relation between optimum estimation and some information measures, which can be viewed as partition functions and hence are amenable to statistical-mechanical analysis. This approach has several advantages, most notably, its applicability to general sources/channels, as opposed to the I-MMSE relation and its variants which hold only for certain classes of channels. We also demonstrate the derivation of the optimum estimator and the MMSE in a few examples. One of them is generalizable to a fairly wide class of sources and channels. For this class, our approach yields an approximate conditional mean estimator and an MMSE formula that has the flavor of a single-letter expression.
Independent Component Analysis of Instantaneous Power-Based fMRI

In functional magnetic resonance imaging (fMRI) studies using spatial independent component analysis (sICA) method, a model of “latent variables” is often employed, which is based on the assumption that fMRI data are linear mixtures of statistically independent signals. However, actual fMRI signals are nonlinear and do not automatically meet with the requirement of sICA. To provide a better solution to this problem, we proposed a novel approach termed instantaneous power based fMRI (ip-fMRI) for regularization of fMRI data. Given that the instantaneous power of fMRI signals is a scalar value, it should be a linear mixture that naturally satisfies the “latent variables” model. Based on our simulated data, the curves of accuracy and resulting receiver-operating characteristic curves indicate that the proposed approach is superior to the traditional fMRI in terms of accuracy and specificity by using sICA. Experimental results from human subjects have shown that spatial components of a hand movement task-induced activation reveal a brain network more specific to motor function by ip-fMRI than that by the traditional fMRI. We conclude that ICA decomposition of ip-fMRI may be used to localize energy signal changes in the brain and may have a potential to be applied to detection of brain activity.
Parallel Rollout for Online Solution of Dec-POMDPs

A major research challenge is presented by scalability of algorithms for solving decentralized POMDPs because of their double exponential worst-case complexity for finite horizon problems. First algorithms have only been able to solve very small instances on very small horizons. One exception is the Memory-Bounded Dynamic Programming algorithm ‐ an approximation technique that has proved efficient in handling same sized problems but on large horizons. In this paper, we propose an online algorithm that also approximates larger instances of finite horizon DEC-POMDPs based on the Rollout algorithm. To evaluate the effectiveness of this approach, we compare the presented approach to a recently proposed algorithm called memory bounded dynamic programming. Experimental results show that despite the very high complexity of DEC-POMDPs, the combination of Rollout techniques and estimation techniques performs well and leads to a significant improvement of existing approximation techniques.
How ‘arm-twisting’ by the inducer triggers activation of the MalT transcription factor, a typical signal transduction ATPase with numerous domains (STAND)

Signal transduction ATPases with numerous domains (STAND) get activated through inducer-dependent assembly into multimeric platforms. This switch relies on the conversion of their nucleotide-binding oligomerization domain (NOD) from a closed, ADP-bound form to an open, ATP-bound form. The NOD closed form is stabilized by contacts with the arm, a domain that connects the NOD to the inducer-binding domain called the sensor. How the inducer triggers NOD opening remains unclear. Here, I pinpointed the NOD-arm interface of the MalT STAND transcription factor, and I generated a MalT variant in which this interface can be covalently locked on demand, thereby trapping the NOD in the closed state. By characterizing this locked variant, I found that the inducer is recognized in two steps: it first binds to the sole sensor with low affinity, which then triggers the recruitment of the arm to form a high-affinity arm-sensor inducer-binding site. Strikingly, this high-affinity binding step was incompatible with arm-NOD contacts maintaining the NOD closed. Through this toggling between two mutually exclusive states reminiscent of a single-pole double-throw switch, the arm couples inducer binding to NOD opening, shown here to precede nucleotide exchange. This scenario likely holds for other STANDs like mammalian NLR innate immunity receptors.
Failures of the One-Step Learning Algorithm

The Hinton network (Hinton, 2001, personal communication) is a deterministic mapping from an observable space x to an energy function E(x; w), parameterized by parameters w. The energy deflnes a probability P(xjw) = exp(iE(x; w))=Z(w). A maximum likelihood learning algorithm for this density model takes steps ¢w/ihgi 0 + hgi 1 where hgi 0 is the average of the gradient g = @E=@w evaluated at points x drawn from the data density, and hgi 1 is the average gradient for points x drawn from P(xjw). If T is a Markov chain in x-space that has P(xjw) as its unique invariant density then we can approximate hgi 1 by taking the data points x and hitting each of them I times with T, where I is a large integer. In the one-step learning algorithm of Hinton (2001), we set I to 1. In this paper I give examples of models E(x; w) and Markov chains T for which the true likelihood is unimodal in the parameters, but the one-step algorithm does not necessarily converge to the maximum likelihood parameters. It is hoped that these negative examples will help pin down the conditions for the one-step algorithm to be a correctly convergent algorithm. The Hinton network (Hinton, 2001, personal communication) is a deterministic mapping from anobservablespace xofdimension Dtoanenergyfunction E(x;w),parameterizedbyparameters w. The energy deflnesa probability
Do you want to take notes?: identifying research missions in Yahoo! search pad

Addressing user's information needs has been one of the main goals of Web search engines since their early days. In some cases, users cannot see their needs immediately answered by search results, simply because these needs are too complex and involve multiple aspects that are not covered by a single Web or search results page. This typically happens when users investigate a certain topic in domains such as education, travel or health, which often require collecting facts and information from many pages. We refer to this type of activities as "research missions". These research missions account for 10% of users' sessions and more than 25% of all query volume, as verified by a manual analysis that was conducted by Yahoo! editors. We demonstrate in this paper that such missions can be automatically identified on-the-fly, as the user interacts with the search engine, through careful runtime analysis of query flows and query sessions. The on-the-fly automatic identification of research missions has been implemented in Search Pad, a novel Yahoo! application that was launched in 2009, and that we present in this paper. Search Pad helps users keeping trace of results they have consulted. Its novelty however is that unlike previous notes taking products, it is automatically triggered only when the system decides, with a fair level of confidence, that the user is undertaking a research mission and thus is in the right context for gathering notes. Beyond the Search Pad specific application, we believe that changing the level of granularity of query modeling, from an isolated query to a list of queries pertaining to the same research missions, so as to better reflect a certain type of information needs, can be beneficial in a number of other Web search applications. Session-awareness is growing and it is likely to play, in the near future, a fundamental role in many on-line tasks: this paper presents a first step on this path.
Dynamic monitoring of circulating microRNAs as a predictive biomarker for the diagnosis and recurrence of papillary thyroid carcinoma

Circulating microRNAs (miRNAs/miRs) are considered to be potential biomarkers for numerous types of cancer. However, previous investigations into the expression of miRNAs in the serum of patients with papillary thyroid carcinoma (PTC) to predict diagnosis, prognosis and recurrence have reported conflicting results, and the role of miRNAs remains unclear. The present study dynamically assessed the circulating miRNA profile in patients with PTC and determined whether miRNAs in the serum could be used as biomarkers for the diagnosis, prognosis and recurrence of PTC. The expression levels of 3 reportedly upregulated miRNAs (miR-222, miR-221 and miR-146b) were analyzed using reverse transcription-quantitative polymerase chain reaction in 106 patients with PTC, 35 patients with benign thyroid nodules (BTN) and 40 paired controls. Patients with either newly diagnosed PTC or BTN who were undergoing thyroidectomies were recruited for a dynamic analysis of preoperative and postoperative serum miRNA levels. The results indicated that the expression levels of serum miR-222, miR-221 and miR-146b were significantly increased in patients with newly diagnosed PTC compared with controls and patients with BTN. Receiver operating characteristic curve analysis indicated that these miRNAs had a high diagnostic sensitivity and specificity for PTC prior to surgery. The expression of these three miRNAs in serum was significantly associated with poorer prognostic variables, including extrathyroidal invasion, metastatic lymph nodes and high-risk or advanced tumor node metastasis stage. More notably, the present study identified 2.36-, 2.69- and 5.39-fold reductions in the serum levels of miR-222, miR-221 and miR-146b, respectively, subsequent to patients undergoing a thyroidectomy. In addition, miR-222, miR-221 and miR-146b were overexpressed in the PTC with recurrence group compared with the PTC without recurrence group. Collectively, dynamic monitoring of circulating miRNAs may serve as a non-invasive biomarker for the diagnosis of PTC and the postoperative monitoring of its progression and recurrence.