Miracle-dz/UniFAR-FTUs huggingface dataset:
Radiocarbon Dating and Wood Density Chronologies of Mangrove Trees in Arid Western Australia

Mangrove trees tend to be larger and mangrove communities more diverse in tropical latitudes, particularly where there is high rainfall. Variation in the structure, growth and productivity of mangrove forests over climatic gradients suggests they are sensitive to variations in climate, but evidence of changes in the structure and growth of mangrove trees in response to climatic variation is scarce. Bomb-pulse radiocarbon dating provides accurate dates of recent wood formation and tree age of tropical and subtropical tree species. Here, we used radiocarbon techniques combined with X-ray densitometry to develop a wood density chronology for the mangrove Avicennia marina in the Exmouth Gulf, Western Australia (WA). We tested whether wood density chronologies of A. marina were sensitive to variation in the Pacific Decadal Oscillation Index, which reflects temperature fluctuations in the Pacific Ocean and is linked to the instrumental rainfall record in north WA. We also determined growth rates in mangrove trees from the Exmouth Gulf, WA. We found that seaward fringing A. marina trees (∼10 cm diameter) were 48±1 to 89±23 years old (mean ± 1σ) and that their growth rates ranged from 4.08±2.36 to 5.30±3.33 mm/yr (mean ±1σ). The wood density of our studied mangrove trees decreased with increases in the Pacific Decadal Oscillation Index. Future predicted drying of the region will likely lead to further reductions in wood density and their associated growth rates in mangrove forests in the region.
Effect of acetazolamide and autoCPAP therapy on breathing disturbances among patients with obstructive sleep apnea syndrome who travel to altitude: a randomized controlled trial.

CONTEXT Many patients with obstructive sleep apnea syndrome (OSA) living near sea level travel to altitude, but this may expose them to hypoxemia and exacerbation of sleep apnea. The treatment in this setting is not established. OBJECTIVE To evaluate whether acetazolamide and autoadjusted continuous positive airway pressure (autoCPAP) control breathing disturbances in OSA patients at altitude. DESIGN, SETTING, AND PARTICIPANTS Randomized, placebo-controlled, double-blind, crossover trial involving 51 patients with OSA living below an altitude of 800 m and receiving CPAP therapy who underwent studies at a university hospital at 490 m and resorts in Swiss mountain villages at 1630 m and 2590 m in summer 2009. INTERVENTIONS Patients were studied during 2 sojourns of 3 days each in mountain villages, 2 days at 1630 m, 1 day at 2590 m, separated by a 2-week washout period at less than 800 m. At altitude, patients either took acetazolamide (750 mg/d) or placebo in addition to autoCPAP. MAIN OUTCOME MEASURES Primary outcomes were nocturnal oxygen saturation and the apnea/hypopnea index; secondary outcomes were sleep structure, vigilance, symptoms, adverse effects, and exercise performance. RESULTS Acetazolamide and autoCPAP treatment was associated with higher nocturnal oxygen saturation at 1630 m and 2590 m than placebo and autoCPAP: medians, 94% (interquartile range [IQR], 93%-95%) and 91% (IQR, 90%-92%) vs 93% (IQR, 92%-94%) and 89% (IQR, 87%-91%), respectively. Median increases were 1.0% (95% CI, 0.3%-1.0%) and 2.0% (95% CI, 2.0%-2.0). Median night-time spent with oxygen saturation less than 90% at 2590 m was 13% (IQR, 2%-38%) vs 57% (IQR, 28%-82%; P < .001). Acetazolamide and autoCPAP resulted in better control of sleep apnea at 1630 m and 2590 m than placebo and autoCPAP: median apnea/hypopnea index was 5.8 events per hour (5.8/h) (IQR, 3.0/h-10.1/h) and 6.8/h (IQR, 3.5/h-10.1/h) vs 10.7/h (IQR, 5.1/h-17.7/h) and 19.3/h (IQR, 9.3/h-29.0/h), respectively; median reduction was 3.2/h (95% CI, 1.3/h-7.5/h) and 9.2 (95% CI, 5.1/h-14.6/h). CONCLUSION Among patients with OSA spending 3 days at moderately elevated altitude, a combination of acetazolamide and autoCPAP therapy, compared with autoCPAP alone, resulted in improvement in nocturnal oxygen saturation and apnea/hypopnea index. TRIAL REGISTRATION clinicaltrials.gov Identifier: NCT00928655.
A Low-Complexity Full-Duplex Radio Implementation With a Single Antenna

This paper presents a novel low-complexity full-duplex radio design, which only uses a single patch antenna without any duplexer or circulator for passive suppression of self-interference, and a computationally efficient technique for linear digital cancellation. The proposed full-duplex design is tested for IEEE 802.11g Wireless Standard on the WARP (v3) software-defined radio implementation platform. It is shown that this design provides a total suppression of 88 dB, which is sufficient for low-power or short-range full-duplex communication. The dual polarized slot coupled patch antenna used in our design provides an interport isolation as high as 60 dB in 2.4 GHz band. Additionally, the digital domain cancellation utilizes a frequency domain-based estimation and reconstruction approach, which not only offers up to <inline-formula><tex-math notation="LaTeX">$61\%$</tex-math></inline-formula> reduction in the computational complexity but also provides a <inline-formula><tex-math notation="LaTeX">$5-7$ </tex-math></inline-formula> dB better digital cancellation performance in highly selective channel conditions, as compared to the time-domain-based techniques. The proposed full-duplex implementation can be easily applied in OFDM-based wireless systems, such as IEEE 802.11, which is the considered air interface in this paper.
Transmit Power Optimization for a Hybrid PLC/VLC/RF Communication System

The number of indoor smart devices is rapidly growing which requires ubiquitous wireless connectivity for data communications. The limited available radio frequency (RF) spectrum motivates finding alternate wireless solutions. Visible light communications (VLC) are a wireless technology which have shown a high potential to offer wireless data communications in both indoor and outdoor scenarios. Power-line communications (PLC) technology is employed in VLC networks for data transfer between VLC sources due to the ubiquity and the infrastructure availability of power-line networks. As a result, the hybrid wireline/wireless technology of PLC/VLC can be exploited in a complementary fashion to the existing indoor RF networks for improving wireless connectivity. In this paper, we investigate the power allocation problem of a hybrid system composed of a cascaded PLC/VLC link in parallel to an RF wireless link. We formulate and analyze the problem of minimizing the total transmission power consumption under a defined quality of service constraint. Our results show that the proposed hybrid system, under different realizations of PLC, VLC, and RF channel models, provides considerable performance improvement compared to conventional RF systems.
Canadian Chinese Adolescent Girls' Gender Roles and Identities

An autovideography approach was used to investigate the gender role and identity perceptions of ten adolescent Chinese girls in Vancouver. They were asked to take 20 photos in a week from the media that could illustrate ''what women should or should not be and what women should or should not do''. Individual face-to-face interviews were conducted discussing their choices. Six dominant themes emerged related to appearance, personality, work, family, interests and health. The results reveal that the interviewees aspired to be active in managing their body image, family and career. They valued financial independence and pursuing their dreams. They emphasized a woman's right to work and aspired to balance work and family. They showed little enthusiasm for the traditional Chinese female characteristics of gentleness and submissiveness.
Performance analysis of ambient RF energy harvesting: A stochastic geometry approach

Ambient RF (Radio Frequency) energy harvesting techniques have recently been proposed as a potential solution to provide proactive energy replenishment for wireless devices. This paper aims to analyze the performance of a battery-free wireless sensor powered by ambient RF energy harvesting using a stochastic-geometry approach. Specifically, we consider a random network model in which ambient RF sources are distributed as a Ginibre α-determinantal point process which recovers the Poisson point process when α approaches zero. We characterize the expected RF energy harvesting rate. We also perform a worst-case study which derives the upper bounds of both power outage and transmission outage probabilities. Numerical results show that our upper bounds are accurate and that better performance is achieved when the distribution of ambient sources exhibits stronger repulsion.
Escaping Saddles with Stochastic Gradients

We analyze the variance of stochastic gradients along negative curvature directions in certain non-convex machine learning models and show that stochastic gradients exhibit a strong component along these directions. Furthermore, we show that - contrary to the case of isotropic noise - this variance is proportional to the magnitude of the corresponding eigenvalues and not decreasing in the dimensionality. Based upon this observation we propose a new assumption under which we show that the injection of explicit, isotropic noise usually applied to make gradient descent escape saddle points can successfully be replaced by a simple SGD step. Additionally - and under the same condition - we derive the first convergence rate for plain SGD to a second-order stationary point in a number of iterations that is independent of the problem dimension.
Effects of age, education, and gender on verbal fluency in healthy adult Arabic-speakers in Egypt

ABSTRACT The objective of this study is to establish the effects of age, gender, and education and to provide preliminary normative data for letter and category fluency tasks in the Egyptian Arabic-speaking population. We evaluated 139 cognitively healthy volunteers aged 20–93 by adapting the letter and category verbal fluency tasks for the Egyptian population. On the letter fluency task, mean number of words generated in one-minute beginning with the Arabic letter “Sheen” (pronounced “sh”) was 8.14 words per minute (SD = 3.25). Letter fluency was significantly influenced by education. On category fluency tasks, mean number of animal names generated in one minute was 14.63 words (SD = 5.28). Category fluency was significantly influenced by age and education. We were able identify that age significantly affects category fluency while education significantly affected both letter and category fluency. We were also able to provide preliminary normative data for both tasks in the Egyptian population.
Beyond Frequencies: Graph Pattern Mining in Multi-weighted Graphs

Graph pattern mining aims at identifying structures that appear frequently in large graphs, under the assumption that frequency signifies importance. Several measures of frequency have been proposed that respect the apriori property, essential for an efficient search of the patterns. This property states that the number of appearances of a pattern in a graph cannot be larger than the frequency of any of its sub-patterns. In real life, there are many graphs with weights on nodes and/or edges. For these graphs, it is fair that the importance (score) of a pattern is determined not only by the number of its appearances, but also by the weights on the nodes/edges of those appearances. Scoring functions based on the weights do not generally satisfy the apriori property, thus forcing many approaches to employ other, less efficient, pruning strategies to speed up the computation. The problem becomes even more challenging in the case of multiple weighting functions that assign different weights to the same nodes/edges. In this work, we provide efficient and effective techniques for mining patterns in multi-weight graphs. We devise both an exact and an approximate solution. The first is characterized by intelligent storage and computation of the pattern scores, while the second is based on the aggregation of similar weighting functions to allow scalability and avoid redundant computations. Both meth-ods adopt a scoring function that respects the apriori property, and thus they can rely on effective pruning strategies. Extensive experiments under different parameter settings prove that the presence of edge weights and the choice of scoring function affect the patterns mined, and hence the quality of the results returned to the user. Finally, experiments on datasets of different sizes and increasing numbers of weighting functions show that, even when the performance of the exact algorithm degrades, the approximate algorithm
An Automated System for Internet Pharmacy Verification

In the past years, we have witnessed an explosion of web applications, and in particular of electronic commerce websites. This has led to unquestionable benefits for both producers and consumers of goods. On the other hand, however, untrusted companies have the opportunity to bypass checks and regulations imposed by relevant bodies. This problem is prevalent in the context of online commerce of pharmaceutical products, where it is essential that such products are safe, of good quality, and only used with a proper prescription. In this work, we study the problem of internet pharmacy verification. To this effect, we build a classifier, able to find patterns and predict the class of unseen data. Moreover, we devise algorithms that give a trust score to each pharmacy, in order to have a legitimacy indicator usable by human reviewers. We experimentally evaluate the proposed approach with real data coming from two different time periods. The results demonstrate the effectiveness of our approach, as well as the potential of using similar techniques for automatically checking regulation compliance in electronic commerce.
Lingering Effects: Stereotype Threat Hurts More than You Think

Starting with the first realization that negative stereotypes can cause people to underperform in the stereotyped domain, an impressive body of work has documented the robust and wide-ranging nature of stereotype and social identity threat. In this article, we look beyond the stereotyped ability domain and present evidence that coping with stereotypes and prejudice can linger, affecting a broad range of behaviors even in areas unrelated to the stigmatized ability. This stereotype threat spillover occurs because coping with negative stereotypes and prejudice leaves self-control resources depleted for challenges that arise later, even in unrelated situations. We suggest a number of different ways that individuals can empower and hopefully inoculate themselves against spillover including shifting appraisals and adopting positive coping strategies. We also discuss societal changes, encouraging governments and other organizations to enact policy that will reduce the prevalence of stereotyping and cultivate feelings of intrinsic motivation to reduce prejudice.
The Psychological Roots of Anti-Vaccination Attitudes: A 24-Nation Investigation

Objective: Strengthening of antivaccination movements in recent decades has coincided with unprecedented increases in the incidence of some communicable diseases. Many intervention programs work from a deficit model of science communication, presuming that vaccination skeptics lack the ability to access or understand evidence. However, interventions focusing on evidence and the debunking of vaccine-related myths have proven to be either nonproductive or counterproductive. Working from a motivated reasoning perspective, we examine the psychological factors that might motivate people to reject scientific consensus around vaccination. To assist with international generalizability, we examine this question in 24 countries. Methods: We sampled 5,323 participants in 24 countries, and measured their antivaccination attitudes. We also measured their belief in conspiracy theories, reactance (the tendency for people to have a low tolerance for impingements on their freedoms), disgust sensitivity toward blood and needles, and individualistic/hierarchical worldviews (i.e., people’s beliefs about how much control society should have over individuals, and whether hierarchies are desirable). Results: In order of magnitude, antivaccination attitudes were highest among those who (a) were high in conspiratorial thinking, (b) were high in reactance, (c) reported high levels of disgust toward blood and needles, and (d) had strong individualistic/hierarchical worldviews. In contrast, demographic variables (including education) accounted for nonsignificant or trivial levels of variance. Conclusions: These data help identify the “attitude roots” that may motivate and sustain vaccine skepticism. In so doing, they help shed light on why repetition of evidence can be nonproductive, and suggest communication solutions to that problem.
Betaine Supplementation Enhances Lipid Metabolism and Improves Insulin Resistance in Mice Fed a High-Fat Diet

Obesity is a major driver of metabolic diseases such as nonalcoholic fatty liver disease, certain cancers, and insulin resistance. However, there are no effective drugs to treat obesity. Betaine is a nontoxic, chemically stable and naturally occurring molecule. This study shows that dietary betaine supplementation significantly inhibits the white fat production in a high-fat diet (HFD)-induced obese mice. This might be due to betaine preventing the formation of new white fat (WAT), and guiding the original WAT to burn through stimulated mitochondrial biogenesis and promoting browning of WAT. Furthermore, dietary betaine supplementation decreases intramyocellular lipid accumulation in HFD-induced obese mice. Further analysis shows that betaine supplementation reduced intramyocellular lipid accumulation might be associated with increasing polyunsaturated fatty acids (PUFA), fatty acid oxidation, and the inhibition of fatty acid synthesis in muscle. Notably, by performing insulin-tolerance tests (ITTs) and glucose-tolerance tests (GTTs), dietary betaine supplementation could be observed for improvement of obesity and non-obesity induced insulin resistance. Together, these findings could suggest that inhibiting WAT production, intramyocellular lipid accumulation and inflammation, betaine supplementation limits HFD-induced obesity and improves insulin resistance.
Unlike adults, children and adolescents show predominantly increased neural activation to social exclusion by members of the opposite gender

ABSTRACT The effects of group membership on brain responses to social exclusion have been investigated in adults, revealing greater anterior cingulate responses to exclusion by members of one’s in-group (e.g., same-gender). However, social exclusion is a critical aspect of peer relations in youth and reaches heightened salience during adolescence, a time when social anxiety disorders are also emergent. While the behavioral and neural correlates of social exclusion in adolescence have been extensively explored, the effects of group membership on peer rejection are less clear. The current study used functional magnetic resonance imaging (fMRI) to investigate the differential neural correlates of being excluded by peers of one’s same- versus opposite-gender during an online ball-toss game. Participants were a group of typically developing children and adolescents (7–17 years). As predicted, anterior cingulate cortex showed a main effect of social exclusion versus fair play. However, unlike a previous adult study, this region did not show increased activation to same-gender exclusion. Instead, several regions differentiating same- versus opposite-gender exclusion were exclusively more sensitive to exclusion by one’s opposite gender. These results are discussed in the context of adolescent socio-emotional development.
Facial Landmarks Detection by Self-Iterative Regression based Landmarks-Attention Network

Cascaded Regression (CR) based methods have been proposed to solve facial landmarks detection problem, which learn a series of descent directions by multiple cascaded regressors separately trained in coarse and fine stages. They outperform the traditional gradient descent based methods in both accuracy and running speed. However, cascaded regression is not robust enough because each regressor's training data comes from the output of previous regressor. Moreover, training multiple regressors requires lots of computing resources, especially for deep learning based methods. In this paper, we develop a Self-Iterative Regression (SIR) framework to improve the model efficiency. Only one self-iterative regressor is trained to learn the descent directions for samples from coarse stages to fine stages, and parameters are iteratively updated by the same regressor. Specifically, we proposed Landmarks-Attention Network (LAN) as our regressor, which concurrently learns features around each landmark and obtains the holistic location increment. By doing so, not only the rest of regressors are removed to simplify the training process, but the number of model parameters is significantly decreased. The experiments demonstrate that with only 3.72M model parameters, our proposed method achieves the state-of-the-art performance.
Imagery Use and Self-Determined Motivations in a Community Sample of Exercisers and Non-Exercisers

This study examined the patterns of imagery use and motivational selfdetermination, and the relationships between them in regular exercisers (RE), nonexercisers who intend to exercise (NE-I), and non-exercisers who do not intend to exercise (NE-N). A survey was conducted through the random sampling of a large population. The NE-N group reported using the same amount of imagery as the other 2 groups. NE-N participants were the least and RE participants the most self-determined, with NE-I participants in between. The patterns of association among imagery and self-determination were different for the NE-N participants than the other 2 groups. It was concluded that imagery interventions that might be successful with RE and NE-I participants are unlikely to be effective with NE-N participants. jasp_566 135.152
THE ROLE OF BULGE FORMATION IN THE HOMOGENIZATION OF STELLAR POPULATIONS AT Z ∼ 2 AS REVEALED BY INTERNAL COLOR DISPERSION IN CANDELS

We use data from the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey to study how the spatial variation in the stellar populations of galaxies relates to the formation of galaxies at 1.5 < z < 3.5 ? > . We use the internal color dispersion (ICD), measured between the rest-frame UV and optical bands, which is sensitive to age (and dust attenuation) variations in stellar populations. The ICD shows a relation with the stellar masses and morphologies of the galaxies. Galaxies with the largest variation in their stellar populations as evidenced by high ICD have disk-dominated morphologies (with Sérsic indexes < 2 ? > ) and stellar masses between 10 < log ( M / M ⊙ ) < 11 ? > . There is a marked decrease in the ICD as the stellar mass and/or the Sérsic index increases. By studying the relations between the ICD and other galaxy properties including size, total color, star formation rate, and dust attenuation, we conclude that the largest variations in stellar populations occur in galaxies where the light from newly, high star-forming clumps contrasts older stellar disk populations. This phase reaches a peak for galaxies only with a specific stellar mass range, 10 < ? > log (M/ M ⊙ ? > ) < 11 ? > , and prior to the formation of a substantial bulge/spheroid. In contrast, galaxies at higher or lower stellar masses and/or higher Sérsic index ( n > 2 ? > ) show reduced ICD values, implying a greater homogeneity of their stellar populations. This indicates that if a galaxy is to have a quiescent bulge along with a star-forming disk, typical of Hubble sequence galaxies, this is most common for stellar masses 10 < ? > log (M/ M ⊙ ? > ) < 11 ? > and when the bulge component remains relatively small ( n < 2 ? > ).