Miracle-dz/UniFAR-FTUs huggingface dataset:
Mechanisms and Structural Determinants of HIV-1 Coat Protein, gp41-Induced Neurotoxicity

Of the individuals with human immunodeficiency virus type 1 (HIV-1) infection, 20–30% will develop the neurological complication of HIV-associated dementia (HAD). The mechanisms underlying HAD are unknown; however, indirect immunologically mediated mechanisms are theorized to play a role. Recently, the HIV-1 coat protein gp41 has been implicated as a major mediator of HAD through induction of neurocytokines and subsequent neuronal cell death. Using primary mixed cortical cultures from neuronal nitric oxide synthase (NOS) null (nNOS−/−) mice and immunological NOS null (iNOS−/−) mice, we establish iNOS-derived NO as a major mediator of gp41 neurotoxicity. Neurotoxicity elicited by gp41 is markedly attenuated in iNOS−/− cultures compared with wild-type and nNOS−/− cultures. The NOS inhibitor l-nitroarginine methyl ester is neuroprotective in wild-type and nNOS−/− cultures, confirming the role of iNOS-derived NO in gp41 neurotoxicity. Confirming that iNOS−/− cultures lack iNOS, gp41 did not induce iNOS in iNOS−/− cultures, but it markedly induced iNOS in wild-type and nNOS−/− cultures. We elucidate the region of gp41 that is critical for iNOS induction and neuronal cell death by monitoring iNOS induction with overlapping peptides spanning gp41. We show that the N-terminal region of gp41, which we designate as the neurotoxic domain, induces iNOS protein activity and iNOS-dependent neurotoxicity at picomolar concentrations in a manner similar to recombinant gp41 protein. Our experiments suggest that gp41 is eliciting the induction of iNOS through potential cell surface receptors or binding sites because the induction of iNOS is dose dependent and saturable and occurs at physiologically relevant concentrations. These data confirm that the induction of iNOS by gp41 and the production of NO are primary mediators of neuronal damage and identify a neurotoxic domain of gp41 that may play an important role in HAD.
A virtual-reality based integrated driving-traffic simulation system to study the impacts of intelligent transportation system (ITS)

Travel behaviour under information is a complex process which includes traveller interaction with the environment and consequent information. This process were not fully explored in the past studies because the difficulties in collecting the data. In this paper, a VR based integrated driving-traffic simulation system is presented to collect data needed to address the travellers behaviour under information. The major advantage is that this system has sophisticated control on generated traffic condition and consequent information, which are crucial for the studies on information impacts on travel behaviour. The conceptual design of integrated system is discussed in this paper. In addition, results from a pilot study are also discussed. The results of the pilot study provide some information on future experiment designs with developed system.
Impacts of Human Body Shadowing in Wireless Body-Centric Communications

In wireless body-centric communications, either the transmitter or the receiver, or both are located in close proximity to the human body. Thus, the Line-of-Sight (LOS) components of the radio signal are particularly susceptible to shadowing caused by human body. In earlier, the effect of human body shadowing was studied using κ-μ fading channel, where the resultant dominant signal components due to body shadowing effect was characterized by log-normal distribution and Nakagami-m distribution in different experiments. In this context, this article provides a comprehensive comparison of two aforementioned methods of human body shadowing effects in wireless body-centric communications. Here, the dominant component characterized by log-normal distribution is mentioned as shadowed log-normal model, whereas the Nakagami-m distribution dominant component model is mentioned as shadowed Nakagami-m model. Different wireless body-centric communications scenarios, namely on-body, off-body, and body-tobody, are tested separately with these two distribution methods. MATLAB based simulations indicate that the shadowed Nakagami-m distribution provides better fit to the empirical results in comparison of shadowed log-normal distribution. Moreover, the probability density function of shadowed Nakagami-m model provides numerical advantages over shadowed log-normal model.
Approaching Parents to Take Part in a Cleft Gene Bank: A Qualitative Pilot Study

Objective A gene bank, comprising genetic material and environmental and family history data, is being established in the United Kingdom to improve the understanding of the etiology of orofacial clefting (OFC). This study aimed to identify factors that might contribute to participation in a cleft gene bank and what issues need to be considered in approaching parents to be included. Design A qualitative approach was adopted, using focus groups and interviews. Transcripts of audio recordings were analyzed using inductive thematic analysis. Participants A UK cleft center invited 100 families of children born with OFC to participate. Inclusion criteria included any parent of a child aged between 6 months and 16 years willing to take part. Sixteen parents participated. Results Participants were generally motivated to take part in a cleft gene bank because they value the discovery of new knowledge of the etiology of OFC. They wanted reassurance about the purpose and integrity of the project. Many conveyed shock at the diagnosis of cleft and offered mixed accounts of experiences with health care professionals. They suggested an individualized approach from a trustworthy and sensitive professional when being invited to join the gene bank, avoiding difficult times associated with new-baby challenges and issues related to the cleft. Conclusions This pilot study indicates that parents of children born with OFC would be supportive of developing a cleft gene bank, but sensitive issues need to be considered.
Platelet mechanosensing of substrate stiffness during clot formation mediates adhesion, spreading, and activation

Significance Platelets are cell fragments in the blood that initiate clot formation at the site of bleeding. Although the biological aspects of this process have been well characterized, whether platelets can detect and physiologically respond to the mechanical aspects of its local environment is unclear. Here, we show that platelets sense the stiffness of the underlying clot substrate, and increasing substrate stiffness increases platelet adhesion and spreading. Importantly, adhesion on stiffer substrates leads to higher levels of platelet activation. Mechanistically, we determined that Rac1, actin, and myosin activity mediate this process. This newfound capability of how platelets adjust their degree of activation based on the mechanical properties of their environment provides new insight into how clots are formed. As platelets aggregate and activate at the site of vascular injury to stem bleeding, they are subjected to a myriad of biochemical and biophysical signals and cues. As clot formation ensues, platelets interact with polymerizing fibrin scaffolds, exposing platelets to a large range of mechanical microenvironments. Here, we show for the first time (to our knowledge) that platelets, which are anucleate cellular fragments, sense microenvironmental mechanical properties, such as substrate stiffness, and transduce those cues into differential biological signals. Specifically, as platelets mechanosense the stiffness of the underlying fibrin/fibrinogen substrate, increasing substrate stiffness leads to increased platelet adhesion and spreading. Importantly, adhesion on stiffer substrates also leads to higher levels of platelet activation, as measured by integrin αIIbβ3 activation, α-granule secretion, and procoagulant activity. Mechanistically, we determined that Rac1 and actomyosin activity mediate substrate stiffness-dependent platelet adhesion, spreading, and activation to different degrees. This capability of platelets to mechanosense microenvironmental cues in a growing thrombus or hemostatic plug and then mechanotransduce those cues into differential levels of platelet adhesion, spreading, and activation provides biophysical insight into the underlying mechanisms of platelet aggregation and platelet activation heterogeneity during thrombus formation.
Socially aware path planning for mobile robots

SUMMARY Human–robot interaction is an emerging area of research where a robot may need to be working in human-populated environments. Human trajectories are generally not random and can belong to gross patterns. Knowledge about these patterns can be learned through observation. In this paper, we address the problem of a robot's social awareness by learning human motion patterns and integrating them in path planning. The gross motion patterns are learned using a novel Sampled Hidden Markov Model, which allows the integration of partial observations in dynamic model building. This model is used in the modified A* path planning algorithm to achieve socially aware trajectories. Novelty of the proposed method is that it can be used on a mobile robot for simultaneous online learning and path planning. The experiments carried out in an office environment show that the paths can be planned seamlessly, avoiding personal spaces of occupants.
On the temporal equivalence of sequential circuits

The authors extend the abstract notion of temporal behavior to compare arbitrary circuits with arbitrary multiphase clocking schemes. They consider the input-output behavior of circuits with respect to time. Properties are discussed that remain invariant under certain transformations. Constraints are derived that permit a legal retiming in the case of multiphase sequential circuits with edge triggered and/or transparent latches. For a particular design style an efficient procedure is described to check for temporal equivalence of sequential circuits. A model and a formal definition for the temporal behavior of an arbitrary multiphase circuits and an algorithm for formal verification of the temporal behavior of circuits are outlined. <<ETX>>
An Intelligent Particle Swarm Optimization for Short-Term Traffic Flow Forecasting Using on-Road Sensor Systems

On-road sensor systems installed on freeways are used to capture traffic flow data for short-term traffic flow predictors for traffic management, to reduce traffic congestion and improve vehicular mobility. This paper intends to tackle the impractical time-invariant assumptions which underlie the methods currently used to develop short-term traffic flow predictors: 1) the characteristics of current data captured by on-road sensors are assumed to be time invariant with respect to those of the historical data, which is used to developed short-term traffic flow predictors; and 2) the configuration of the on-road sensor systems is assumed to be time-invariant. In fact, both assumptions are impractical in the real world, as the current traffic flow characteristics can be very different from the historical ones, and also the on-road sensor systems are time varying in nature due to damaged sensors or component wear. Therefore, misleading forecasting results are likely to be produced when short-term traffic flow predictors are designed using these two time-invariant assumptions. To tackle these time-invariant assumptions, an intelligent particle swarm optimization (IPSO) algorithm is proposed to develop short-term traffic flow predictors by integrating the mechanisms of PSO, neural network and fuzzy inference system, to adapt to the time-varying traffic flow characteristics and the time-varying configurations of the on-road sensor systems. The proposed IPSO was applied to forecast traffic flow conditions on a section of freeway in Western Australia, whose traffic flow information can be captured on-line by the on-road sensor system. These results clearly demonstrate the effectiveness of using the proposed IPSO for real-time traffic flow forecasting based on traffic flow data captured by on-road sensor systems.
Softspec: Software-based Speculative Parallelism

We present Softspec, a technique for parallelizing sequential applications using only simple software mechanisms, requiring no complex program analysis or hardware support. Softspec parallelizes loops whose memory references are stride-predictable. By detecting and speculatively executing potential parallelism at runtime Softspec succeeds in parallelizing loops whose memory access patterns are statically indeterminable. For example, Softspec can parallelize while loops with un-analyzable exit conditions, linked list traversals, and sparse matrix applications with predictable memory patterns. We show performance results using our prototype implementation.
Mining for Topics to Suggest Knowledge Model Extensions

Electronic concept maps, interlinked with other concept maps and multimedia resources, can provide rich knowledge models to capture and share human knowledge. This article presents and evaluates methods to support experts as they extend existing knowledge models, by suggesting new context-relevant topics mined from Web search engines. The task of generating topics to support knowledge model extension raises two research questions: first, how to extract topic descriptors and discriminators from concept maps; and second, how to use these topic descriptors and discriminators to identify candidate topics on the Web with the right balance of novelty and relevance. To address these questions, this article first develops the theoretical framework required for a “topic suggester” to aid information search in the context of a knowledge model under construction. It then presents and evaluates algorithms based on this framework and applied in Extender, an implemented tool for topic suggestion. Extender has been developed and tested within CmapTools, a widely used system for supporting knowledge modeling using concept maps. However, the generality of the algorithms makes them applicable to a broad class of knowledge modeling systems, and to Web search in general.
Visual contrast sensitivity

To the Editor: Schroth et all correctly remind us that in herpes simplex encephalitis (HSE) antiviral therapy must be initiated early if we hope to prevent devastating neurologic damage. They reported superiority of MRI over CT in making early diagnosis, but made no comment about the utility of EEG, and no mention of EEG findings was made in their three case reporta. Whitley et a12 reported that EEG is the most useful neurodiagnostic aid in 113 patients with biopsy-proven H S E EEG localization for brain biopsy was found in 81% of cases versus 50% of cases with a localized lesion found on isotope scan and 59% of focal lesions found by CT. Whitley et al concluded, “our dependence on CT scans will delay diagnosis and subsequent institution of treatment. ”* A comparison of early EEG abnormality and MRI needs to be studied.
Acute Effects of a Respiratory Sprint-Interval Session on Muscle Contractility.

INTRODUCTION Respiratory muscle training has been shown to improve physical performance in healthy individuals and patients. One training modality for both inspiratory and expiratory muscles is respiratory muscle endurance training (RMET), which consists of normocapnic hyperpnea at constant ventilation for 30 min. Here, a new training regimen, respiratory muscle sprint-interval training (RMSIT), is introduced and tested for its potential to fatigue respiratory muscles. In addition, effects of both modalities on airway properties are investigated. METHODS In 12 healthy subjects (six men and six women; 24 ± 3 yr; forced expiratory volume in 1 s, 115% ± 10%), changes in inspiratory transdiaphragmatic twitch pressure (Pdi,tw) and expiratory gastric twitch pressure (Pga,tw) were assessed during cervical magnetic stimulation or thoracic magnetic stimulation before and after a single bout of RMET and RMSIT. At similar time points, mechanical airway properties were assessed by impulse oscillometry. RMET was performed for 30 min at 60% of maximal voluntary ventilation, with constant tidal volume and breathing frequency. RMSIT consisted of six 30-s respiratory sprints (with 2-min breaks in between) at constant tidal volume, with the greatest possible breathing frequency and added resistance. RESULTS Pdi,tw and Pga,tw decreased significantly after RMET (-17.7% ± 9.0% and -22.4% ± 18.5%; P < 0.01) and RMSIT (-18.1% ± 12.8% and -21.2% ± 13.1%; P < 0.01), and changes did not differ between training modalities (P = 0.50 and P = 0.12), suggesting similar levels of fatigue. Work of breathing per minute was 2.4 ± 0.8-fold greater in RMSIT than in RMET, whereas total work of breathing was substantially smaller in RMSIT (3.4 ± 0.8 kJ) than in RMET (15.0 ± 0.42 kJ). No subject showed clinically relevant changes in mechanical airway properties. CONCLUSIONS Despite different work history, RMSIT appears to place a metabolic load on respiratory muscles similarly to RMET and could therefore be considered a time-saving and safe training alternative.
Influence of attitudes towards change and self-directness on dropout in eating disorders: a 2-year follow-up study.

OBJECTIVE This study examined dropout-related factors at the Outpatient Eating Disorders Treatment Programme. METHOD One hundred ninety-six eating disorders patients following DSM-IV diagnostic criteria that consecutively commenced treatment were recruited and followed up for a 2-year period. A total of 151 patients completed the whole assessment with a set of questionnaires evaluating eating and general psychopathology. The Attitudes towards Change in Eating Disorders questionnaire was used, and personality was evaluated using the Temperament and Character Inventory. During the follow-up period, patients were re-assessed. Two years later, 102 patients continued on treatment. RESULTS Scores on Precontemplation at the beginning were predictors for dropout at 2-year follow-up. Character variables, as Responsibility, Integrity and Self-acceptance were protective factors to be at Precontemplation stage. DISCUSSION The clinician's challenge is to help eating disorders patients to develop an unyielding sense of responsibility and self-acceptance, aimed to integrate the therapeutic choice into their own intrapersonal frame of goals.
Epidemiological and clinical characteristics of psoriatic arthritis in northern Norway

Background: To determine the characteristics of psoriatic arthritis (PsA) in northern Norway, where the human leucocyte antigen HLA‐B27 is prevalent. Methods: An observational study of patients with ICD‐9 CR codes for psoriatic arthropathy (696.0 and 713.3) and spondylarthritis (720) seen during a 19‐year period at a single regional rheumatology department. In patients with confirmed PsA demographics, date of onset of arthritis and psoriasis, clinical presentation and subsequent disease course (including therapeutic measures) were recorded during a mean follow‐up of 11.1 years. Results: Arthritis was documented in 329/657 (50%) of patients with a diagnostic code for PsA. The mean annual incidence rate for PsA was 6.9/100 000 and the point prevalence was 130/100 000 (0.13%) adults. The male to female ratio was 1.4 and the mean age at onset of psoriasis was 27.8 years (SD 14.1), and 35 years (SD 11.8) at onset of arthritis. Arthritis preceded psoriasis in 13.8% of cases. Oligoarthritis was the most frequent subtype (48%), followed by polyarthritis (32%), spondylitis (9%), monoarthritis (7%), and classic distal interphalangeal (DIP) arthritis (2%). Erosive disease (56% of cases) occurred mainly with polyarthritis; arthritis mutilans occurred in six patients (2%). Surgical interventions were performed in 22% of patients. Disease activity fluctuated considerably over time. Mortality (4.3%) was increased in PsA patients with polyarthritis and secondary amyloidosis (n = 5). Conclusion: The prevalence of PsA and related spondylitis is not increased in northern Norway. PsA does, however, lead to a considerable burden of disease due to erosive disease development and surgical intervention.
Lead-Induced Impairments in the Neural Processes Related to Working Memory Function

Background It is well known that lead exposure induces neurotoxic effects, which can result in a variety of neurocognitive dysfunction. Especially, occupational lead exposures in adults are associated with decreases in cognitive performance including working memory. Despite recent advances in human neuroimaging techniques, the neural correlates of lead-exposed cognitive impairment remain unclear. Therefore, this study was aimed to compare the neural activations in relation to working memory function between the lead-exposed subjects and healthy controls. Methodology/Principal Findings Thirty-one lead-exposed subjects and 34 healthy subjects performed an n-back memory task during MRI scan. We performed fMRI using the 1-back and 2-back memory tasks differing in cognitive demand. Functional MRI data were analyzed using within- and between-group analysis. We found that the lead-exposed subjects showed poorer working memory performance during high memory loading task than the healthy subjects. In addition, between-group analyses revealed that the lead-exposed subjects showed reduced activation in the dorsolateral prefrontal cortex, ventrolateral prefrontal cortex, pre supplementary motor areas, and inferior parietal cortex. Conclusions/Significance Our findings suggest that functional abnormalities in the frontoparietal working memory network might contribute to impairments in maintenance and manipulation of working memory in the lead-exposed subjects.
Mapping the Political Twitterverse: Candidates and Their Followers in the Midterms

Twitter provides a new and important tool for political actors. In the 2010 midterm elections, the vast majority of candidates for the U.S. House of Representatives and virtually all candidates for U.S. Senate and governorships used Twitter to reach out to potential supporters, direct them to particular pieces of information, request campaign contributions from them, and mobilize their political action. Despite the level of activity, we have little understanding of what the political Twitterverse looks like in terms of communication and discourse. This project seeks to remedy that lack of understanding by mapping candidates and their followers according to their use of hashtags (keywords) and user mentions (direct mentioning of other Twitter users). We have a unique data set constructed from tweets of most of the candidates running for the U.S. House of Representatives in 2010, all the candidates for the Senate and governorships, and a random sample of their followers. From this we utilize multidimensional scaling to construct a visual map based on hashtag and user mention usage. We find that our data have both local and global interpretations that reflect both political leaning and strategies of communication. This study provides insight into innovation in new media usage in political behavior in particular and a bounded topic space in general.