Miracle-dz/UniFAR-FTUs huggingface dataset:
Molecular Composition of the Endocannabinoid System at Glutamatergic Synapses

Endocannabinoids play central roles in retrograde signaling at a wide variety of synapses throughout the CNS. Although several molecular components of the endocannabinoid system have been identified recently, their precise location and contribution to retrograde synaptic signaling is essentially unknown. Here we show, by using two independent riboprobes, that principal cell populations of the hippocampus express high levels of diacylglycerol lipase α (DGL-α), the enzyme involved in generation of the endocannabinoid 2-arachidonoyl-glycerol (2-AG). Immunostaining with two independent antibodies against DGL-α revealed that this lipase was concentrated in heads of dendritic spines throughout the hippocampal formation. Furthermore, quantification of high-resolution immunoelectron microscopic data showed that this enzyme was highly compartmentalized into a wide perisynaptic annulus around the postsynaptic density of axospinous contacts but did not occur intrasynaptically. On the opposite side of the synapse, the axon terminals forming these excitatory contacts were found to be equipped with presynaptic CB1 cannabinoid receptors. This precise anatomical positioning suggests that 2-AG produced by DGL-α on spine heads may be involved in retrograde synaptic signaling at glutamatergic synapses, whereas CB1 receptors located on the afferent terminals are in an ideal position to bind 2-AG and thereby adjust presynaptic glutamate release as a function of postsynaptic activity. We propose that this molecular composition of the endocannabinoid system may be a general feature of most glutamatergic synapses throughout the brain and may contribute to homosynaptic plasticity of excitatory synapses and to heterosynaptic plasticity between excitatory and inhibitory contacts.
The Role of Probation and Parole Officers in the Collaborative Response to Sex Offenders

IN JUNE 2007, the American Probation and Parole Association was awarded a cooperative agreement from the National Institute of Corrections to develop a curriculum for training community corrections professionals on how to deal with low-level/low-risk sex offenders from a collaborative framework. The training module included two components: 1) a module focusing on how to define, identify, and supervise low-level sex offenders, and 2) a module focusing on strategies to promote collaboration in working with these sex offenders. In this article, the authors introduce the collaborative response to sex offenders, with a specific focus on the role of probation and parole officials in this collaborative response system.
Using Technology to Support an Embodied Approach to Learning Concepts in Mathematics

In this paper I will explain what I mean by an ‘embodied approach’ to mathematics. I shall contrast and compare it with two other modes: the ‘proceptual’ (manipulating symbols as process and concept) and the ‘axiomatic’ based on formal definitions and formal proof. Each of these has its own standard of ‘truth’. I argue that the embodied mode, though it lacks mathematical proof when used alone, can provide a fundamental human basis for meaning in mathematics. I shall give examples of an embodied approach in mathematics, particularly in the calculus, using technology that makes explicit use of a visual and enactive interface.
Telomere Length and Physical Performance at Older Ages: An Individual Participant Meta-Analysis

Background Telomeres are involved in cellular ageing and shorten with increasing age. If telomere length is a valuable biomarker of ageing, then telomere shortening should be associated with worse physical performance, an ageing trait, but evidence for such an association is lacking. The purpose of this study was to examine whether change in telomere length is associated with physical performance. Methods Using data from four UK adult cohorts (ages 53–80 years at baseline), we undertook cross-sectional and longitudinal analyses. We analysed each study separately and then used meta-analytic methods to pool the results. Physical performance was measured using walking and chair rise speed, standing balance time and grip strength. Telomere length was measured by quantitative real-time polymerase chain reaction (PCR) in whole blood at baseline and follow-up (time 1, time 2). Results Total sample sizes in meta-analyses ranged from 1,217 to 3,707. There was little evidence that telomere length was associated with walking speed, balance or grip strength, though weak associations were seen with chair rise speed and grip strength at baseline (p = 0.02 and 0.01 respectively). Faster chair rise speed at follow-up, was associated with a smaller decline in telomere length between time 1 and time 2 (standardised coefficient per SD increase 0.061, 95% CI 0.006, 0.115, p = 0.03) but this was consistent with chance (p = 0.08) after further adjustment. Conclusions Whereas shortening of leukocyte telomeres might be an important measure of cellular ageing, there is little evidence that it is a strong biomarker for physical performance.
Research in Social Computing : Approaches and New Directions

People have begun to accept technology as a matter of course in the day-to-day areas of their lives. As a result, the development and proliferation of social software has enjoyed exponential growth in the past several years. In this paper we argue that as researchers and practitioners who create social technologies, we must take a “social engineering” approach, actively designing social applications to help users achieve their social goals. We then review current trends in innovation in social technologies, and discuss some of the hard problems that need to be addressed by the field in the next several years. We expect that as social technologies continue to innovate in areas such as social networks, social navigation, lightweight authoring, and mobile and ubiquitous computing, we must increasingly envision an integrated social computing experience: that is, a social computing platform.
Multi-Objective Economic Emission Dispatch using Backtracking Search Optimization Algorithm

To provide reliable and uninterrupted electrical su pply to consumers, electrical utilities face many econom ic and technical problems in operation, planning and control of power systems. Most of the power system optimization probl ems like economic load dispatch include complex and non-linear characteristics with heavy equality and inequality c onstraints. Cost minimization of power generation is one of the m ost important power system problems. In this project, an attempt is made to minimize the cost for generation in a power system. The aim of this project is to find the optimum set of p ower to be generated for a given loading conditions. Equality c onstraint which is the relation between power generated, losses and power demand is taken into account. In this thesis, trans mission losses have not been taken. Inequality constraints such as the maximum and minimum generation values for each of the generators are also considered along with valve point loading. This paper introduces backtracking search optimization algorithm (BSA), a new evolutionary algorithm (EA) for solving real-valued numerical optimization problems . EA's are popular stochastic search algorithms that are widely used to solve non- linear, non-differentiable and complex numerical optimization problems. Unlike many search algorithms, BSA has a single control parameter. BSA has a simple structure that is effecti ve, fast and capable of solving multi modal problems and that enables it to easily adapt to different numerical optimization pr oblems. BSA's strategy for generating a trail population includes two new crossover and mutation operators.BSA strategies for g enerating trail populations and controlling the amplitude of the search-direction matrix and search space boundaries give it very powerful exploration and exploitation capabilities. In particular BSA possesses a memory in which it stores a population from a randomly chosen previous generation for use in generating the search-direction matrix. Thus BSA's memory allows it to take advantage of experiences gained from previous generations when it generates a trail preparation. The proposed algo rithm is applied to EED problem. The purpose of EED is to obtain the optimal amount of generated power for the generating unit in the system by simultaneously minimizing the fuel and emission costs. To demonstrate the effectiveness of this method BSA have been performed on 6-unit system with valve point loading effect to obtain lesser fuel and emission costs
Divergent regulation of Akt1 and Akt2 isoforms in insulin target tissues of obese Zucker rats.

To determine whether impaired Akt (protein kinase B or rac) activation contributes to insulin resistance in vivo, we examined the expression, phosphorylation, and kinase activities of Akt1 and Akt2 isoforms in insulin target tissues of insulin-resistant obese Zucker rats. In lean rats, insulin (10 U/kg i.v. x 2.5 min) stimulated Akt1 activity 6.2-, 8.8-, and 4.4-fold and Akt2 activity 5.4-, 9.3-, and 1.8-fold in muscle, liver, and adipose tissue, respectively. In obese rats, insulin-stimulated Akt1 activity decreased 30% in muscle and 21% in adipose tissue but increased 37% in liver compared with lean littermates. Insulin-stimulated Akt2 activity decreased 29% in muscle and 37% in liver but increased 24% in adipose tissue. Akt2 protein levels were reduced 56% in muscle and 35% in liver of obese rats, but Akt1 expression was unaltered. Phosphoinositide 3-kinase (PI3K) activity associated with insulin receptor substrate (IRS)-1 or phosphotyrosine was reduced 67-86% in tissues of obese rats because of lower IRS-1 protein levels and reduced insulin receptor and IRS-1 phosphorylation. In adipose tissue of obese rats, in spite of an 86% reduction in insulin-stimulated PI3K activity, activation of Akt2 was increased. Maximal insulin-stimulated (100 nmol/l) glucose transport was reduced 70% in isolated adipocytes, with a rightward shift in the insulin dose response for transport and for Akt1 stimulation but normal sensitivity for Akt2. These findings suggest that PI3K-dependent effects on glucose transport in adipocytes are not mediated primarily by Akt2. Akt1 and Akt2 activations by insulin have a similar time course and are maximal by 2.5 min in adipocytes of both lean and obese rats. We conclude that 1) activation of Akt1 and Akt2 in vivo is much less impaired than activation of PI3K in this insulin-resistant state, and 2) the mechanisms for divergent alterations in insulin action on Akt1 and Akt2 activities in tissues of insulin-resistant obese rats involve tissue- and isoform-specific changes in both expression and activation.
Detailed Spectroscopic and Photometric Analysis of DQ White Dwarfs

We present an analysis of spectroscopic and photometric observations of cool DQ white dwarfs based on improved model atmosphere calculations. In particular, we revise the atmospheric parameters of the trigonometric parallax sample of Bergeron, Leggett, & Ruiz and discuss the astrophysical implications on the temperature scale and mean mass, as well as the chemical evolution of these stars. We also analyze 40 new DQ stars discovered in the First Data Release of the Sloan Digital Sky Survey (SDSS). Our analysis confirms that effective temperatures (Teff) derived from model atmospheres including carbon are significantly lower than the temperatures obtained from pure helium models. Similarly, the mean mass of the trigonometric parallax sample, ⟨M⟩ = 0.62 M☉, is significantly lower than that obtained from pure helium models, ⟨M⟩ = 0.73 M☉, and more consistent with the spectroscopic mean mass of DB stars, ⟨M⟩ = 0.59 M☉, the most likely progenitors of DQ white dwarfs. We find that DQ stars form a remarkably well-defined sequence in a carbon abundance versus effective temperature diagram; below Teff ~ 10,000 K, carbon pollution decreases monotonically with decreasing effective temperature. Improved evolutionary models including diffusion and connecting to the PG 1159 phase are used to infer a typical value for the thickness of the helium layer MHe/M⋆ between 10-3 and 10-2, compatible with the predictions of post-AGB models. Several DQ stars in our sample, however, show larger than average carbon abundances. We argue that these DQ stars are all massive white dwarfs and could represent the high-mass tail of the white dwarf mass distribution, with their hotter counterparts corresponding to the hot DQ stars reported recently by Liebert et al. The number distribution of DQ white dwarfs as a function of effective temperature clearly shows a sudden drop at about Teff ~ 7000 K and an abrupt cutoff at Teff ~ 6000 K. The existence of this cutoff is now statistically more significant with the addition of the SDSS stars. The physical mechanism responsible for this cutoff is still unknown, even though it is believed to be somehow related to the existence of the so-called C2H stars at lower temperatures.
RUSTY OLD STARS: A SOURCE OF THE MISSING INTERSTELLAR IRON?

Iron, the universe's most abundant refractory element, is highly depleted in both circumstellar and interstellar environments, meaning it exists in solid form. The nature of this solid is unknown. In this Letter, we provide evidence that metallic iron grains are present around oxygen-rich asymptotic giant branch stars, where it is observationally manifest as a featureless mid-infrared excess. This identification is made using Spitzer Space Telescope observations of evolved globular cluster stars, where iron dust production appears ubiquitous and in some cases can be modeled as the only observed dust product. In this context, FeO is examined as the likely carrier for the 20 μm feature observed in some of these stars. Metallic iron appears to be an important part of the dust condensation sequence at low metallicity, and subsequently plays an influential role in the interstellar medium. We explore the stellar metallicities and luminosities at which iron formation is observed, and how the presence of iron affects the outflow and its chemistry. The conditions under which iron can provide sufficient opacity to drive a wind remain unclear.
Association Between Hypermethylated Tumor and Paired Surgical Margins in Head and Neck Squamous Cell Carcinomas

Purpose: Surgical margin status is reported to be a relevant prognostic factor in head and neck squamous cell carcinoma (HNSCC), associated with a high risk of local recurrence. This study examines whether gene-promoter hypermethylation could be detected in HNSCC surgical margins with no histologic evidence of malignancy, and if so, whether it reflects epigenetic events of primary tumors. Experimental Design: Promoter methylation status of MGMT, p16, and DAP-K genes was evaluated by methylation-specific PCR in 20 primary HNSCC tumors. Histopathologically negative surgical margins of hypermethylated tumors were collected, and their methylation status compared with the primary tumor status. Results: Promoter hypermethylation in at least one of the three tested genes was detected in 65% (13 of 20) of tumors. MGMT was hypermethylated in 50% (10 of 20), DAP-K in 45% (9 of 20), and p16 in 20% (4 of 20) of tumors. Methylation status was analyzed in 35 margins from 11 of 13 patients showing promoter hypermethylation in the tumor tissue. Identical methylation events were seen for at least one gene in primary tumor and surgical margins in 9 of 11 cases (82%). Association was found for gene-specific hypermethylation status in tumors and paired surgical margins, and gene-specific concordance was 63% for MGMT (κ = 0.24), 90% for DAP-K (κ = 0.74), and 90% for p16 (κ = 0.79). Conclusions: Our results support the hypothesis that detection of gene promoter hypermethylation in HNSCC tumor cells–free surgical margins may be a helpful biomarker to identify molecularly altered fields in areas adjacent to the tumor.
Promoting positive outcomes through strengths interventions: A literature review

Abstract This paper reviews studies of strengths interventions published between 2011 and 2016. Strengths interventions aim to promote well-being or other positive outcomes by facilitating strengths identification, and sometimes also strengths use and/or development. The present review provides an overview of the different strengths interventions that are investigated, their effectiveness, and moderating and mediating factors. Results of the 18 (quasi-)experimental studies that were identified through a systematic literature search showed that all types of strengths interventions had positive outcomes in terms of well-being, job outcomes (e.g. work engagement), personal growth initiative, and group or team outcomes (e.g. class cohesion). Hope, positive affect, authentic self-expression, perceptions of the employment relationship, and feelings of social worth were identified as mediators, whereas extraversion and having specific strengths (e.g. persistence) were identified as moderators. Based on these findings, we discuss implications for future research and practice.
Recommending Information Sources to Information Seekers in Twitter

Finding high-quality sources in the expanding micro-blogging community using Twitter becomes essential for information seekers in order to cope with information overload. In this paper, we present a recommendation algorithm aiming to identify potentially interesting users to follow in the Twitter network. This algorithm first explores the graph of connections starting at the target user (the user to whom we wish to recommend previously unknown followees) in order to select a set of candidate users to recommend, according to an heuristic procedure. The set of candidate users is then ranked according to the similarity between the content of tweets that they publish and the target user interests. Experimental evaluation was conducted to determine the impact of different profiling strategies.
Stability of Processor Sharing Networks with Simultaneous Resource Requirements

We study the phenomenon of entrainment in processor sharing networks, whereby, while individual network resources have sufficient capacity to meet demand, the requirement for simultaneous availability of resources means that a network may nevertheless be unstable. We show that instability occurs through poor control, and that, for a variety of network topologies, only small modifications to controls are required in order to ensure stability. For controls which possess a natural monotonicity property, we give some new results for the classification of the corresponding Markov processes, which lead to conditions both for stability and for instability.
Erratum to “How many zeros of a random polynomial are real?”

In Section 4.3 of the article “How many zeros of a random polynomial are real? ” by Alan Edelman and Eric Kostlan (Bull. Amer. Math. Soc. (N.S.) 32 (1) (1995), 1–37), we meant to say that the eigenvector matrix, not the incidence matrix, is the tensor (or Kronecker) product of ( 1 1 1 −1 ) n times. This tensor product is the simplest Hadamard matrix. The eigenvalues of the incidence matrix may then be seen to be 2k − n for k = 0, . , n. We regret the statement in Section 2.5 that the constant C1 in the asymptotic expansion of the Kac formula was unknown to previous researchers. Indeed the constant C1 and further asymptotic terms were known to Wilkins [1], who also reports on previous work deriving C1 by Jamrom and Wang going back to 1971 and 1983 respectively. We do believe, however, that our derivation is new.
Distinguishing mangrove species with laboratory measurements of hyperspectral leaf reflectance

As a first step in developing classification procedures for remotely acquired hyperspectral mapping of mangrove canopies, we conducted a laboratory study of mangrove leaf spectral reflectance at a study site on the Caribbean coast of Panama, where the mangrove forest canopy is dominated by Avicennia germinans, Laguncularia racemosa, and Rhizophora mangle. Using a high‐resolution spectrometer, we measured the reflectance of leaves collected from replicate trees of three mangrove species growing in productive and physiologically stressful habitats. The reflectance data were analysed in the following ways. First, a one‐way ANOVA was performed to identify bands that exhibited significant differences (P value<0.01) in the mean reflectance across tree species. The selected bands then formed the basis for a linear discriminant analysis (LDA) that classified the three types of mangrove leaves. The contribution of each narrow band to the classification was assessed by the absolute value of standardised coefficients associated with each discriminant function. Finally, to investigate the capability of hyperspectral data to diagnose the stress condition across the three mangrove species, four narrow band ratios (R 695/R 420, R 605/R 760, R 695/R 760, and R 710/R 760 where R 695 represents reflectance at wavelength of 695nm, and so on) were calculated and compared between stressed and non‐stressed tree leaves using ANOVA. Results indicate a good discrimination was achieved with an average kappa value of 0.9. Wavebands at 780, 790, 800, 1480, 1530, and 1550 nm were identified as the most useful bands for mangrove species classification. At least one of the four reflectance ratio indices proved useful in detecting stress associated with any of the three mangrove species. Overall, hyperspectral data appear to have great potential for discriminating mangrove canopies of differing species composition and for detecting stress in mangrove vegetation.
Investigating recognition accuracy improvement by adding user's acceleration data to location and power consumption-based in-home activity recognition system

Recently, there are many studies on automatic recognition of activities of daily living (ADL) to provide various services such as elderly monitoring, intelligent concierge, and health support. In particular, real-time ADL recognition is essential to realize an intelligent concierge service since the service needs to know user's current or next activity for supporting it. We have been studying real-time ADL recognition using only user's position data and appliances' power consumption data which are considered to include less privacy information than audio and visual data. In the study, we found that some activities such as reading and operating smartphone that happen in similar conditions cannot be classified with only position and power data. In this paper, we propose a new method that adds the acceleration data from wearable devices for classifying activities happening in similar conditions with higher accuracy. In the proposed method, we use the acceleration data from a smart watch and a smartphone worn by user's arm and waist, respectively, in addition to user's position data and appliances' power consumption data, and construct a machine learning model for recognizing 15 types of target activities. We evaluated the recognition accuracy of 3 methods: our previous method (using only position data and power consumption data); the proposed method using the mean value and the standard deviation of the acceleration norm; and the proposed method using the ratio of the activity topics. We collected the sensor data in our smart home facility for 12 days, and applied the proposed method to these sensor data. As a result, the proposed method could recognize the activities with 57% which is 12 % improvement from our previous method without acceleration data.