Miracle-dz/UniFAR-FTUs huggingface dataset:
Vertical Sleeve Gastrectomy Is Effective in Two Genetic Mouse Models of Glucagon-Like Peptide 1 Receptor Deficiency

Glucagon-like peptide 1 (GLP-1) is a peptide hormone that is released from the gut in response to nutrient ingestion and that has a range of metabolic effects, including enhancing insulin secretion and decreasing food intake. Postprandial GLP-1 secretion is greatly enhanced in rats and humans after some bariatric procedures, including vertical sleeve gastrectomy (VSG), and has been widely hypothesized to contribute to reduced intake, weight loss, and the improvements in glucose homeostasis after VSG. We tested this hypothesis using two separate models of GLP-1 receptor deficiency. We found that VSG-operated GLP-1 receptor–deficient mice responded similarly to wild-type controls in terms of body weight and body fat loss, improved glucose tolerance, food intake reduction, and altered food selection. These data demonstrate that GLP-1 receptor activity is not necessary for the metabolic improvements induced by VSG surgery.
Characterization of apolipoprotein E-containing lipoproteins in cerebrospinal fluid: effect of phenotype on the distribution of apolipoprotein E.

BACKGROUND Apolipoprotein (apo) E, one of the main apolipoproteins in the central nervous system, may play an important role in lipid metabolism; however, the details of its function are poorly understood. In this study, we characterized apoE-containing lipoproteins in cerebrospinal fluid (CSF) and examined the effect of apoE phenotype on the distribution of apoE among the lipoprotein fractions. METHODS CSF lipoproteins were fractionated by gel filtration and ultracentrifugation, and then characterized by electrophoresis, immunoblot, electron microscopy, and analysis of apoE, total cholesterol, and phospholipid concentrations. RESULTS The ratio of sialylated to nonsialylated apoE was higher in CSF than in serum. However, the fundamental forms containing apoE homodimers or heterodimers [such as apo(E-AII) and apo(AII-E2-AII) complexes] were similar in CSF and serum. apoE-containing lipoproteins were fractionated at densities of <1.006, 1.063-1.125, and 1.125-1.21 kg/L. Neither apoE nor apoAI was detected in the fraction with a density range of 1.006-1.063 kg/L. The diameters of the lipoprotein particles with densities of <1.006, 1.063-1.125, and 1.125-1.21 kg/L were 16.7 +/- 3.1, 14.0 +/- 3.2, and 11.6 +/- 2.8 nm (mean +/- SD, n = 200), respectively. All of these lipoproteins exhibited a spherical structure. The distribution profile of apoE-containing lipoproteins was affected by the apoE phenotype. A relatively large amount of apoE-containing lipoproteins was isolated from the fraction with a density >1.125 kg/L obtained from CSF associated with apoE2 or apoE3. This tendency was more obvious in CSF associated with apoE2 than in CSF without apoE2. apoE-containing lipoproteins were predominantly observed in the fraction with a density of <1.006 kg/L obtained from CSF associated with apoE4. CONCLUSIONS The lipoproteins in CSF have a unique composition that is different from that of the lipoproteins in plasma. However, the differences in diameter between the CSF fractions were not as large as for the serum fractions. Our data suggest that the apoE phenotype may affect the distribution profile of apoE-containing lipoproteins in the CSF. This would mean that the metabolism of apoE-containing lipoproteins depends on the apoE isoform present.
Tutoring Answer Explanation Fosters Learning with Understanding

In a previous formative evaluation of the PACT Geometry tutor, we found significant learning gains, but also some evidence of shallow learning. We hypothesized that a cognitive tutor may be even more effective if it requires students to provide explanations for their solution steps. We hypothesized that this would help students to learn with deeper understanding, as reflected by an ability to explain answers, transfer to related but different test items, and an ability to deal with unfamiliar questions. We conducted two empirical experiments to test the effectiveness of learning at the explanation level. In each experiment, we compared two versions of the PACT Geometry Tutor. In the “answeronly” version of the tutor, students were required only to calculate unknown quantities in each geometry problem. In the “reason” version, students also needed to provide correct explanations for their solution steps, by citing geometry theorems and definitions. They did so by selecting from the tutor’s Glossary of geometry knowledge, presented on the screen. The results provide evidence that explaining answers leads to greater understanding. Students who explained their solution steps had better post-test scores and were better at providing reasons for their answers. They also did better at a type of transfer problem in which they were asked to judge if there was sufficient information to find unknown quantities. Also, students who explained solution steps were significantly better at steps where quantities sought were difficult to guess (in other words, require deeper knowledge) while answer-only students did better on easy-to-guess items indicating superficial understanding. Finally, students who explained answers did fewer problems during training, which suggests that the training on reason-giving transfers to answer-giving.
Blind, Greedy, and Random: Ordinal Approximation Algorithms for Graph Problems

We study Matching, Clustering, and related problems in a partial information setting, where the agents' true utilities are hidden, and the algorithm only has access to ordinal preference information. Our model is motivated by the fact that in many settings, agents cannot express the numerical values of their utility for different outcomes, but are still able to rank the outcomes in their order of preference. Specifically, we study problems where the ground truth exists in the form of a weighted graph of agent utilities, but the algorithm receives as input only a preference ordering for each agent induced by the underlying weights. Against this backdrop, we design algorithms to approximate the true optimum solution with respect to the hidden weights. Perhaps surprisingly, such algorithms are possible for many important problems, as we show using our framework based on greedy and random techniques. Our framework yields a 1.6-approximation algorithm for the maximum weighted matching problem, a 2-approximation for the problem of clustering agents into equal sized partitions, a 4-approximation algorithm for Densest $k$-subgraph, and a 1.88-approximation algorithm for Max TSP as long as the hidden weights constitute a metric. Our results are the first non-trivial ordinal approximation algorithms for such problems, and indicate that in many situations, we can design robust algorithms even when we are agnostic to the precise agent utilities.
Atomic Force Microscopy of Cell Growth and Division in Staphylococcus aureus

ABSTRACT The growth and division of Staphylococcus aureus was monitored by atomic force microscopy (AFM) and thin-section transmission electron microscopy (TEM). A good correlation of the structural events of division was found using the two microscopies, and AFM was able to provide new additional information. AFM was performed under water, ensuring that all structures were in the hydrated condition. Sequential images on the same structure revealed progressive changes to surfaces, suggesting the cells were growing while images were being taken. Using AFM small depressions were seen around the septal annulus at the onset of division that could be attributed to so-called murosomes (Giesbrecht et al., Arch. Microbiol. 141:315-324, 1985). The new cell wall formed from the cross wall (i.e., completed septum) after cell separation and possessed concentric surface rings and a central depression; these structures could be correlated to a midline of reactive material in the developing septum that was seen by TEM. The older wall, that which was not derived from a newly formed cross wall, was partitioned into two different surface zones, smooth and gel-like zones, with different adhesive properties that could be attributed to cell wall turnover. The new and old wall topographies are equated to possible peptidoglycan arrangements, but no conclusion can be made regarding the planar or scaffolding models.
Long-term training affects cerebellar processing in skilled keyboard players

We studied cerebellar hemodynamic responses in highly skilled keyboard players and control subjects during complex tasks requiring unimanual and bimanual finger movements. Both groups showed strong hemodynamic responses in the cerebellum during the task conditions. However, non-musicians showed generally stronger hemodynamic responses in the cerebellum than keyboard players. We conclude that, due to long-term motor practice a different cortical activation pattern can be visualized in keyboard players. For the same movements fewer neurons need to be recruited. The different volume of the activated cortical areas might therefore reflect the different effort necessary for motor performance in both groups.
An Efficient Water-Filling Solution for Linear Coherent Joint Estimation

We consider a sensor network with distributed sensors observing multiple sources and transmitting local observations over a Gaussian multiple access channel to a fusion center where the signals are coherently combined. We develop a joint estimation method based on the linear analog forwarding scheme at each local node, which can be cast as a nonlinear optimization problem. By minimizing the gap to the performance benchmark, we obtain a closed-form solution that follows the water-filling strategy. Numerical results are given to demonstrate the average estimation performance in a fading communication environment.
CC Chemokine Receptor 2 Deficiency Aggravates Cognitive Impairments and Amyloid Pathology in a Transgenic Mouse Model of Alzheimer's Disease

Circulating monocytoid cells have the ability to infiltrate nervous tissue, differentiate into microglia, and clear amyloid-β (Aβ) from the brain of mouse models of Alzheimer's disease. Interaction between the chemokine CCL2 and its CC chemokine receptor 2 (CCR2) plays a critical role in the recruitment of inflammatory monocytes into the injured/diseased brain. Here, we show that CCR2 deficiency aggravates mnesic deficits and amyloid pathology in transgenic mice expressing the chimeric mouse/human β-amyloid precursor protein and presenilin 1 (APPSwe/PS1). Indeed, memory impairment was accelerated and enhanced in APPSwe/PS1/CCR2−/− mice. Apparition of cognitive decline occurred earlier (i.e., at 3 months of age before plaque formation) and correlated with intracellular accumulation of soluble oligomeric forms of Aβ. Memory deficits worsened with age and were aggravated in APPSwe/PS1/CCR2−/− mice compared with their respective control groups. Soluble Aβ assemblies increased significantly in APPSwe/PS1 mice in a context of CCR2 deficiency, whereas the plaque load remained relatively similar in the brain of aging APPSwe/PS1 and APPSwe/PS1/CCR2−/− mice. However, CCR2 deficiency stimulated the expression of TGF-β1, TGF-β receptors, and CX3CR1 transcripts in plaque-associated microglia, a pattern that is characteristic of an antiinflammatory subset of myeloid cells. A decreased expression of CCR2 could play a potential role in the etiology of Alzheimer's disease, a neurodegenerative pathology that could be treated by a genetic upregulation of the transgene in monocytoid cells.
Distributed Scheduling of Tasks with Deadlines and Resource Requirements

A set of four heuristic algorithms is presented to schedule tasks that have headlines and resource requirements in a distributed system. When a task arrives at a node, the local scheduler at that node attempts to guarantee that the task will complete execution on that node before its deadline. If the attempt fails, the scheduling components on individual nodes cooperate to determine which other node in the system has sufficient resource surplus to guarantee the task. Simulation studies are performed to compare the performance of these algorithms with respect to each other as well to two baselines. The first baseline is the noncooperative algorithm where a task that cannot be guaranteed locally is not sent to any other node. The second is an (ideal) algorithm that behaves exactly like the bidding algorithm but incurs no communication overheads. The simulation studies examine how communication delay, task laxity, load differences on the nodes, and task computation times affect the performance of the algorithms. The results show that distributed scheduling is effective even in a hard real-time environment and that the relative performance of these algorithms is a function of the system state. >
Optimal Annuity Risk Management

This paper studies the life-cycle consumption and portfolio choice problem taking account of annuity risk at retirement. The study allows for government-provided annuity income. Optimally, households allocate retirement wealth to nominal, inflation-linked and variable annuities, and condition this choice on the state of the economy. The case in which there are limitations in the types of annuities that are available is also considered and the costs of annuity market incompleteness are quantified. Subsequently, the paper determines how investors optimally anticipate annuitization before retirement. The conclusion is that ignoring annuity risk before and at retirement can be economically costly. Copyright 2011, Oxford University Press.
Dramatic shifts in Hawaiian monk seal distribution predicted from divergent regional trends

Total estimated abundance of Hawaiian monk seals was just 1,161 individuals in 2008 and this number is decreasing. Most monk seals reside in the remote Northwestern Hawaiian Islands (NWHI) where the decline is approximately 4%/yr, whereas relatively fewer seals currently occupy the main Hawaiian Islands (MHI). It is widely accepted that the MHI population is increasing, although there are no formal estimates of total abundance, population growth rate or vital rates. This lack of information has hampered efforts to anticipate future scenarios and plan conservation measures. We present the first estimates of MHI monk seal survival and age-specific reproductive rates. Using these rates, a conservative estimate of current MHI abundance and a previously published stochastic simulation model, we estimate the MHI population growth rate and projected abundance trend. Analogous estimates for the NWHI are derived from a much richer data set. Estimated survival from weaning to age 1 yr is 77% in the MHI, much higher than recent NWHI estimates ranging from 42% to 57%. Moreover, MHI females begin reproducing at a younger age and attain higher birth rates than observed in the NWHI. The estimated MHI intrinsic rate of population growth is 1.07 compared to a 0.89-0.96 range in the NWHI. Assuming an initial abundance of 152 animals in the MHI, projections indicate that if current demographic trends continue, abundance in the NWHI and MHI will equalize in approximately 15 yr. These results underscore the imperative to mitigate the NWHI decline while devoting conservation efforts to foster population growth in the MHI, where documented threats including fishery interactions, direct killing, and disease could rapidly undo the current fragile positive trend.
A novel model for synthesizing parallel I/O workloads in scientific applications

One of the challenging issues in performance evaluation of parallel storage systems through synthetic-trace-driven simulation is to accurately characterize the I/O demands of data-intensive scientific applications. This paper analyzes several I/O traces collected from different distributed systems and concludes that correlations in parallel I/O inter-arrival times are inconsistent, either with little correlation or with evident and abundant correlations. Thus conventional Poisson or Markov arrival processes are inappropriate to model I/O arrivals in some applications. Instead, a new and generic model based on the alpha-stable process is proposed and validated in this paper to accurately model parallel I/O burstiness in both workloads with little and strong correlations. This model can be used to generate reliable synthetic I/O sequences in simulation studies. Experimental results presented in this paper show that this model can capture the complex I/O behaviors of real storage systems more accurately and faithfully than conventional models, particularly for the burstiness characteristics in the parallel I/O workloads.
An integrated friction model structure with improved presliding behavior for accurate friction compensation

Presents a dynamical friction model structure which allows accurate modeling both in the sliding and the presliding regimes. Transition between these two regimes is accomplished without a switching function. The model incorporates a hysteresis function with nonlocal memory and arbitrary transition curves. These last aspects prove essential for modeling presliding friction that is encountered in real physical situations. The model as a whole can also handle the Stribeck effect and stick-slip behavior as has been demonstrated by validation on a KUKA IR 361 robot. In this sense, this model can be considered as more complete in comparison with others found in the literature. The general friction model allows modeling of individual friction systems through the identification of a set of parameters that determine the complete behavior of the system. In this way, the model structure has been used to identify the friction behavior of a linear slide as well as that of the above mentioned KUKA robot. The results of the latter identification have been consequently used for feedforward friction compensation to obtain the most accurate tracking.
Regional Gray Matter Volume Is Associated with Restrained Eating in Healthy Chinese Young Adults: Evidence from Voxel-Based Morphometry

Highlight Participants were non-clinical young adults with different restrained eating levels. We assessed relations of restrained eating (RE) with regional gray matter volume (rGMV). High RE scores were related to larger GMV in specific areas related to reward. High RE scores were also linked to less GMV in regions related to response inhibition. Objective: Dieting is a popular method of weight control. However, few dieters are able to maintain initial weight losses over an extended period of time. Why do most restrained dieters fail to lose weight? Alterations in brain structures associated with restrained eating (RE) represent one potentially important mechanism that contributes to difficulties in maintaining weight loss within this group. To evaluate this contention, we investigated associations between intentional, sustained restriction of food intake to lose or maintain body weight, and regional gray matter volume (rGMV) within a large non-clinical young adult, sample. Methods: Participants (150 women, 108 men) completed measures of RE and demographics prior to undergoing an MRI scan. Voxel-based morphometry (VBM) evaluated strengths of association between RE scores and rGMV. Results: Higher RE levels corresponded to more rGMV in regions linked to risk of overeating and binge-eating including the left insula and orbitofrontal cortex (OFC). Conversely, RE had significant negative correlations with rGMV in the left and right posterior cingulum gyrus, regions linked to inhibitory control and potential risk for future weight gain. Conclusions: Together, findings suggested individual differences in RE among young adults correspond to GMV variability in regions linked to overweight and obesity risk.
Number of measurements in sparse signal recovery

We analyze the asymptotic performance of sparse signal recovery from noisy measurements. In particular, we generalize some of the existing results for the Gaussian case to subgaussian and other ensembles. An achievable result is presented for the linear sparsity regime. A converse on the number of required measurements in the sub-linear regime is also presented, which cover many of the widely used measurement ensembles. Our converse idea makes use of a correspondence between compressed sensing ideas and compound channels in information theory.
Coupling geothermal energy capture with carbon dioxide sequestration in naturally permeable, porous geologic formations: A comparison with enhanced geothermal systems

Geothermal energy offers clean, consistent, reliable electric power with no need for grid-scale energy storage, unlike wind and solar renewable power alternatives. However, geothermal energy is often underrepresented in renewable energy discussions and has considerable room for growth. New technology and methods will be critical for future investment, and rapid implementation of new techniques will be critical in ensuring geothermal energy plays a significant role in the future energy landscape worldwide. Here, we discuss a novel approach with the potential to permit expansion of geothermal energy utilization while supporting rapid implementation through the use of existing technologies: geothermal heat use in naturally porous, permeable geologic formations with carbon dioxide as the working heat exchange fluid.
Generative vs Discriminative Approaches to Entity Recognition from Label-Deficient Data

Annotating biomedical text for Named Entity Recognition (NER) is usually a tedious and expensive process, while unannotated data is freely available in large quantities. It therefore seems relevant to address biomedical NER using Machine Learning techniques that learn from a combination of labelled and unlabelled data. We consider two approaches: one is discriminative, using Support Vector Machines, the other generative, using mixture models. We compare the two on a biomedical NER task with various levels of annotation, and dieren t similarity measures. We also investigate the use of Fisher kernels as a way to leverage the strength of both approaches. Overall the discriminative approach using standard similarity measures seems to out-perform both the generative approach and the Fisher kernels. R esum e L’annotation de textes m edicaux pour la reconnaissance d’entit es nomm ees est un travail p enible et couteux, alors que, au contraire, de larges quantit es de donn ees non annot ees sont disponibles gratuitement sur le Web, par exemple sur MedLine/PubMed. Il est donc particuli erement pertinent de s’attaquer au probl eme de la reconnaissance d’entit es biom edicales a l’aide de techniques d’apprentissage automatique qui apprennent a partir de m elanges de donn ees annot ees et non annot ees. Nous consid erons deux approches: l’une est discriminative, elle repose sur l’utilisation de mod eles a point support ou SVM ; l’autre est g en erative et utilise des mod eles de m elange. Nous comparons les deux approches sur une tache de reconnaissance d’entit es biom edicales avec divers niveaux d’annotation, et en utilisant di erentes mesures de similarit e. Nous etudions aussi l’utilisation des noyaux de Fisher an de tenter de combiner les atouts de chacune des deux approches. Dans l’ensemble, l’approche discriminative utilisant des mesures de similarit e standard semble plus performante que l’approche g enerative, ainsi que l’utilisation des noyaux de Fisher.
Bosonic string with antisymmetric fields and a non-local Casimir effect

The coupling, in a non-standard way, of a bosonic string theory with a dilaton and antisymmetric fields is investigated. By integrating over the antisymmetric fields, a Coulomb-like interaction term is generated. The static potential of a theory of this kind is obtained from the corresponding non-local zeta function, in some approximation. An interpretation of the static potential as a type of non-local Casimir effect is given.