Miracle-dz/UniFAR-FTUs huggingface dataset:
Spinal Cord Injury and Migraine Headache: A Population-Based Study

Migraine headaches are a common neurological condition, negatively impacting health and quality of life. Among potential risk factors for migraine headache, risk of migraine headaches was elevated in individuals with spinal cord injury (SCI). The association between migraines and SCI is intriguing to consider from the perspective that migraine headaches may be acquired in response to damage in the spinal cord. The primary objective of this study was to further examine the association between SCI and migraine headache, controlling for potential confounding variables. A secondary objective was to determine the impact of migraine headaches on self-perceived health. Data from a sample of 61,047 participants were obtained from the cross-sectional Canadian Community Health Survey. Multivariable logistic regression was used to explore the association between SCI and migraine headache using probability weights and adjusting for confounders. The multivariable age- and sex-adjusted model revealed a strong association between SCI and migraine headache, with an adjusted odds ratio for migraine of 4.82 (95% confidence interval [3.02, 7.67]) among those with SCI compared to those without SCI. Further, individuals who experienced both SCI and migraine tended to report poorer perceived general health compared with the other groups (i.e., SCI and no migraine). In conclusion, this study established a strong association between SCI and migraine headache. Further research is needed to explore the possible mechanisms underlying this relationship. Improvements in clinical practice to minimize this issue could result in significant improvements in quality of life.
The Keck+Magellan Survey for Lyman Limit Absorption. I. The Frequency Distribution of Super Lyman Limit Systems

We present the results of a survey for super Lyman limit systems (SLLSs; defined to be absorbers with 19.0 cm-2 ≤ log NH I ≤ 20.3 cm-2) from a large sample of high-resolution spectra acquired using the Keck and Magellan telescopes. Specifically, we present 47 new SLLSs from 113 QSO sight lines. We focus on the neutral hydrogen frequency distribution fH I(N, X) of the SLLS and its moments and compare these results with the Lyα forest and the damped Lyα systems (DLAs; absorbers with log NH I ≥ 20.3 cm-2). We find that the fH I(N, X) of the SLLSs can be reasonably described with a power law of index α = -1.43 or -1.19 depending on whether we set the lower NH I bound for the analysis at 1019.0 or 1019.3 cm-2, respectively. The results indicate a flattening in the slope of fH I(N, X) between the SLLSs and DLAs. We find little evidence for redshift evolution in the shape of fH I(N, X) for the SLLSs over the redshift range of the sample 1.68 < z < 4.47 and only tentative evidence for evolution in the zeroth moment of fH I(N, X), the line density ℓSLLS(X). We introduce the observable distribution function 𝒪(N, X) and its moment, which elucidates comparisons of H I absorbers from the Lyα forest through to the DLA. We find that a simple three-parameter function can fit 𝒪(N, X) over the range 17.0 cm-2 ≤ log NH I ≤ 22.0 cm-2. We use these results to predict that fH I(N, X) must show two additional inflections below the SLLS regime to match the observed fH I(N, X) distribution of the Lyα forest. Finally, we demonstrate that SLLSs contribute a minor fraction (≈15%) of the universe's hydrogen atoms and, therefore, an even smaller fraction of the mass in predominantly neutral gas.
Storm Studies in the Arctic (STAR)

The Storm Studies in the Arctic (STAR) network (2007–2010) conducted a major meteorological field project from 10 October–30 November 2007 and in February 2008, focused on southern Baffin Island, Nunavut, Canada—a region that experiences intense autumn and winter storms. The STAR research program is concerned with the documentation, better understanding, and improved prediction of meteorological and related hazards in the Arctic, including their modification by local topography and land–sea ice–ocean transitions, and their effect on local communities. To optimize the applicability of STAR network science, we are also communicating with the user community (northern communities and government sectors). STAR has obtained a variety of surface-based and unique research aircraft field measurements, high-resolution modeling products, and remote sensing measurements (including Cloudsat) as part of its science strategy and has the first arctic Cloudsat validation dataset. In total, 14 research flights were flown b.
Protective Effect of Aqueous Crude Extract of Neem (Azadirachta indica) Leaves on Plasmodium berghei-Induced Renal Damage in Mice

Malaria is a major public health problem in the world because it can cause of death in patients. Malaria-associated renal injury is associated with 45% of mortality in adult patients hospitalized with severe form of the disease. Therefore, new plant extracts to protect against renal injury induced by malaria infection are urgently needed. In this study, we investigated the protective effect of aqueous crude extract of Azadirachta indica (neem) leaves on renal injury induced by Plasmodium berghei ANKA infection in mice. ICR mice were injected intraperitoneally with 1 × 107 parasitized erythrocytes of PbANKA, and neem extracts (500, 1,000, and 2,000 mg/kg) were given orally for 4 consecutive days. Plasma blood urea nitrogen (BUN) and creatinine levels were subsequently measured. Malaria-induced renal injury was evidenced as marked increases of BUN and creatinine levels. However, the oral administration of neem leaf extract to PbANKA infected mice for 4 days brought back BUN and creatinine levels to near normalcy, and the highest activity was observed at doses of 1,000 and 2,000 mg/kg. Additionally, no toxic effects were found in normal mice treated with this extract. Hence, neem leaf extract can be considered a potential candidate for protection against renal injury induced by malaria.
Explicit modeling of organic chemistry and secondary organic aerosol partitioning for Mexico City and its outflow plume

Abstract. The evolution of organic aerosols (OA) in Mexico City and its outflow is investigated with the nearly explicit gas phase photochemistry model GECKO-A (Generator of Explicit Chemistry and Kinetics of Organics in the Atmosphere), wherein precursor hydrocarbons are oxidized to numerous intermediate species for which vapor pressures are computed and used to determine gas/particle partitioning in a chemical box model. Precursor emissions included observed C3-10 alkanes, alkenes, and light aromatics, as well as larger n-alkanes (up to C25) not directly observed but estimated by scaling to particulate emissions according to their volatility. Conditions were selected for comparison with observations made in March 2006 (MILAGRO). The model successfully reproduces the magnitude and diurnal shape for both primary (POA) and secondary (SOA) organic aerosols, with POA peaking in the early morning at 15–20 μg m−3, and SOA peaking at 10–15 μg m−3 during mid-day. The majority (≥75%) of the model SOA stems from reaction products of the large n-alkanes, used here as surrogates for all emitted hydrocarbons of similar volatility, with the remaining SOA originating mostly from the light aromatics. Simulated OA elemental composition reproduces observed H/C and O/C ratios reasonably well, although modeled ratios develop more slowly than observations suggest. SOA chemical composition is initially dominated by δ-hydroxy ketones and nitrates from the large alkanes, with contributions from peroxy acyl nitrates and, at later times when NOx is lower, organic hydroperoxides. The simulated plume-integrated OA mass continues to increase for several days downwind despite dilution-induced particle evaporation, since oxidation chemistry leading to SOA formation remains strong. In this model, the plume SOA burden several days downwind exceeds that leaving the city by a factor of >3. These results suggest significant regional radiative impacts of SOA.
Hyperbaric oxygen therapy in experimental and clinical stroke

Stroke, which is defined as a neurologic deficit caused by sudden impaired blood supply, has been considered as a common cause of death and disability for decades. The World Health Organization has declared that almost every 5 seconds a new stroke occurs, placing immense socioeconomic burdens. However, the effective and available treatment strategies are still limited. Additionally, the most effective therapy, such as thrombolysis and stenting for ischemic stroke, generally requires a narrow therapeutic time window after the event. A large majority of patients cannot be admitted to hospital and receive these effective treatments for reperfusion timely. Hyperbaric oxygen therapy (HBOT) has been frequently applied and investigated in stroke since 1960s. Numerous basic and clinical studies have shown the beneficial efficacy for neurological outcome after stroke, and meanwhile many underlying mechanisms associated with neuroprotection have been illustrated, such as cerebral oxygenation promotion and metabolic improvement, blood-brain barrier protection, anti-inflammation and cerebral edema, intracranial pressure modulation, decreased oxidative-stress and apoptosis, increased vascular and neural regeneration. However, HBOT in human stroke is still not sufficiently evidence-based, due to the insufficient randomized double-blind controlled clinical studies. To date, there are no uniform criteria for the dose and session duration of HBOT in different strokes. Furthermore, the additional effect of HBOT combined with drugs and other treatment strategies are being investigated recently. Therefore, more experimental and clinical research is imperative to identify the mechanisms more clearly and to explore the best protocol of HBOT in stroke treatment.
SLAW: A New Mobility Model for Human Walks

Simulating human mobility is important in mobile networks because many mobile devices are either attached to or controlled by humans and it is very hard to deploy real mobile networks whose size is controllably scalable for performance evaluation. Lately various measurement studies of human walk traces have discovered several significant statistical patterns of human mobility. Namely these include truncated power-law distributions of flights, pause-times and inter-contact times, fractal way-points, and heterogeneously defined areas of individual mobility. Unfortunately, none of existing mobility models effectively captures all of these features. This paper presents a new mobility model called SLAW (self-similar least action walk) that can produce synthetic walk traces containing all these features. This is by far the first such model. Our performance study using using SLAW generated traces indicates that SLAW is effective in representing social contexts present among people sharing common interests or those in a single community such as university campus, companies and theme parks. The social contexts are typically common gathering places where most people visit during their daily lives such as student unions, dormitory, street malls and restaurants. SLAW expresses the mobility patterns involving these contexts by fractal way points and heavy-tail flights on top of the way points. We verify through simulation that SLAW brings out the unique performance features of various mobile network routing protocols.
Action Recognition with Trajectory and Scene

Trajectory features have recently shown promising results to action recognition in video. Typically, they are extracted by tracking feature points with the KLT tracker or matching SIFT descriptors between frames. However, trajectory can be due to the action of interest, but also be caused by background or the camera motion. To overcome the problem, human detection is applied to roughly estimate of the location of the human in the video and segment video into Foreground/Background regions. In many cases, human actions can be identified not only by observing human body in motion, but also properties of the surrounding scene. In our work, we addresse the problem and propose an approach that integrates multiple features from scene and people. We evaluate our video description with a bag of-features model. We also present experimental results on two datasets with an increasing degree of difficulty and demonstrate significant improvements.
Rumination and Dissociation: The Mediating Role of Poor Sleep Quality and Presleep Cognitions

Rumination and dissociation are considered maladaptive cognitive-emotional responses to distress, which prevent its proper processing. The goal of the study was to explore the relationship between rumination and dissociation and possible mechanisms responsible for it. We hypothesized that rumination may exert influence on dissociation via four possible mediators: distress, perceived mental control, repetitive cognitive style, and poor sleep quality. Study 1 was conducted on a sample of 93 undergraduate students and pointed to a central role of sleep in this relationship. Study 2 included 218 undergraduate students and aimed to (a) replicate the results of Study 1 and (b) focus on the sleep factor and explore the role of bedtime strategies for dealing with negative thoughts. Both studies point to sleep quality as the central factor responsible for the positive link between rumination and dissociation. The repetitiveness and the negative valence of rumination predict poor sleep quality, which in turn predicts higher levels of dissociative experiences. We also found that ruminative individuals who cope with intrusive thoughts at bedtime using maladaptive and rigid strategies (aggressive suppression, behavior distraction and worry) slept poorly and reported more dissociative symptoms. We conclude that rumination and dissociation are linked through the disturbed cycle of wake and sleep states and impaired flexibility in transitioning between them. Implications for clinicians and researchers are discussed.
Feature selection with decision tree criterion

Classification techniques applicable to real life data are more and more often complex hybrid systems comprising feature selection. To augment their efficiency we propose two feature selection algorithms, which take advantage of a decision tree criterion. Large computational experiments have been done to test the possibilities of the two methods and to compare their results with other techniques of similar goal.
Modulation of the Kv1.3 Potassium Channel by Receptor Tyrosine Kinases

The voltage-dependent potassium channel, Kv1.3, is modulated by the epidermal growth factor receptor (EGFr) and the insulin receptor tyrosine kinases. When the EGFr and Kv1.3 are coexpressed in HEK 293 cells, acute treatment of the cells with EGF during a patch recording can suppress the Kv1.3 current within tens of minutes. This effect appears to be due to tyrosine phosphorylation of the channel, as it is blocked by treatment with the tyrosine kinase inhibitor erbstatin, or by mutation of the tyrosine at channel amino acid position 479 to phenylalanine. Previous work has shown that there is a large increase in the tyrosine phosphorylation of Kv1.3 when it is coexpressed with the EGFr. Pretreatment of EGFr and Kv1.3 cotransfected cells with EGF before patch recording also results in a decrease in peak Kv1.3 current. Furthermore, pretreatment of cotransfected cells with an antibody to the EGFr ligand binding domain (α-EGFr), which blocks receptor dimerization and tyrosine kinase activation, blocks the EGFr-mediated suppression of Kv1.3 current. Insulin treatment during patch recording also causes an inhibition of Kv1.3 current after tens of minutes, while pretreatment for 18 h produces almost total suppression of current. In addition to depressing peak Kv1.3 current, EGF treatment produces a speeding of C-type inactivation, while pretreatment with the α-EGFr slows C-type inactivation. In contrast, insulin does not influence C-type inactivation kinetics. Mutational analysis indicates that the EGF-induced modulation of the inactivation rate occurs by a mechanism different from that of the EGF-induced decrease in peak current. Thus, receptor tyrosine kinases differentially modulate the current magnitude and kinetics of a voltage-dependent potassium channel.
Generating Video Description using Sequence-to-sequence Model with Temporal Attention

Automatic video description generation has recently been getting attention after rapid advancement in image caption generation. Automatically generating description for a video is more challenging than for an image due to its temporal dynamics of frames. Most of the work relied on Recurrent Neural Network (RNN) and recently attentional mechanisms have also been applied to make the model learn to focus on some frames of the video while generating each word in a describing sentence. In this paper, we focus on a sequence-to-sequence approach with temporal attention mechanism. We analyze and compare the results from different attention model configuration. By applying the temporal attention mechanism to the system, we can achieve a METEOR score of 0.310 on Microsoft Video Description dataset, which outperformed the state-of-the-art system so far.
The Evolution of High Incomes in Northern America: Lessons from Canadian Evidence

This paper uses tax statistics to construct new series on Canadian top income shares from 1920 to 2000 and provides a systematic comparison with the U.S. experience. As in the United States, top income shares in Canada display a Ushaped pattern over the century, with a precipitous drop during World War II, followed by a slower decline until 1970. Since the late 1970s, top income shares have been increasing dramatically and the very top shares are now as high as in the pre-war era. As in the United States, the recent increase in top income shares is the consequence of a surge in top wages and salaries. The Canadian experience since the late 1970s does not appear to be well explained by tax changes, suggesting that the upward trend in Canada derives from the United States, perhaps because many high-income Canadians have an emigration option. This in turn suggests that the recent increase in U.S. personal income top shares is not merely a change in tax reporting behavior. The recent sharp increase in top income shares in Canada is of the same magnitude at the individual and family level and is not due to an increase in income mobility.
Collection Mode Effects in Free-list Elicitation : Comparing Oral , Written , and Web-based Data

The growth of the Internet opens new possibilities for web-based data collection in cognitive anthropology. This study examines whether free-list data collected online are comparable to those collected with face to face interviews or with self-administered paper questionnaires. We collected free lists for two cultural domains in the United States: one diffuse (things that mothers do) and one relatively well defined (racial and ethnic groups). We selected a purposive sample of 318 university students and randomly assigned participants to provide free lists for one of these domains using a web-based survey, a face to face interview, or a self-administered paper questionnaire. All three modes identified the same set of salient concepts in each domain. Median list length per respondent varied across modes in response to a standard free-list question and to supplementary probes. For the well-defined domain of ‘‘racial and ethnic groups,’’ supplementary probes widened differences among modes; for the more diffuse domain of ‘‘things that mothers do,’’ probes erased evidence of mode effects. Collecting free lists online is viable but may yield different results depending on the study population and attributes of the cultural domains.
From conversation to connection: a cross-case analysis of life-story work with five couples where one partner has semantic dementia

Abstract Semantic dementia causes progressive communication difficulties that significantly impact on the person and their family. There is a paucity of research examining conversation skills in this condition and associated interventions to support interaction, such as life-story work. This study used a multiple case study design to: (a) explore the everyday conversation experiences of five individuals with semantic dementia and their spouses; and (b) examine how intervention using interaction-focused life-story work could support communication needs. A total of 74 home visits were conducted over a longitudinal period. An innovative combination of conversation analysis of video and audio data alongside biographical interviewing was used. Information derived from these strands was utilised to design an individually tailored life-story intervention. Cross-case analysis examined the contribution of life-story work to interaction and other aspects of care. Results showed that a range of challenges and skills were present within conversation. Life-story work was delivered in all cases using a variety of formats and the work could be conceptualised under various points of connection: interactional, emotional, new, practical and future. Detailed assessment was important to define aims for intervention and appropriate format(s) for life-story work for the individual concerned. Outcomes for communication in this study were not solely about supporting the telling of facts about the person's life but represented a broader focus to facilitate embodied and emotional connections. This study demonstrates that creativity within life-story work is important to foster social interaction, beyond information exchange, using both verbal and non-verbal behaviours. In addition, video data show promise for exploring in-the-moment outcomes for research and practice, particularly to capture the non-verbal dimensions of this work.
A cross-situational learning algorithm for damping homonymy in the guessing game

There is a growing body of research on multi-agent systems bootstrapping a communication system. Most studies are based on simulation, but recently there has been an increased interest in the properties and formal analysis of these systems. Although very interesting and promising results have been obtained in these studies, they always rely on major simplifications. For example, although much larger populations are considered than was the case in most earlier work, previous work assumes the possibility of meaning transfer . With meaning transfer, two agents always exactly know what they are talking about. This is hardly ever the case in actual communication systems, as noise corrupts the agents’ perception and transfer of meaning. In this paper we first consider what happens when relaxing the meaning-transfer assumption, and propose a cross-situational learning scheme that allows a population of agents to still bootstrap a common lexicon under this condition. We empirically show the validity of the scheme and thereby improve on the results reported in (Smith, 2003) and (Vogt and Coumans, 2003) in which no satisfactory solution was found. It is not our aim to reduce the importance of previous work, instead we are excited by recent results and hope to stimulate further research by pointing towards some new challenges.
A surprising bubble catastrophe

Consider a tube with several orifices out of which fluid of a given volume protrudes. In gravity free conditions the equilibrium configuration will be one which minimizes total surface area subject to the volume constraint. The surface of each liquid drop will have the same constant mean curvature. Suppose that the orifices are cirlces with radii ri where each exposed drop is a spherical cap. We analyze this problem from the viewpoint of catastrophe theory. For a tube with two circular openings the interesting situation occurs when the configuration supports a double hemisphere (h, h) equilibrium. This gives a cusp catastrophe with the radii r1, r2 as universal unfolding parameters. For the case of three openings with a triple hemisphere equilibrium (h, h, h) we obtain an elliptic umbilic with the radii r1, r2, r3 as unfolding parameters. Further surprising phenomena occur along the cusp lines emanating from the elliptic umbilic.