Miracle-dz/UniFAR-FTUs huggingface dataset:
Prolonged hypoxia augments L-citrulline transport by system A in the newborn piglet pulmonary circulation.

AIMS Pulmonary arterial endothelial cells (PAECs) express the enzymes needed for generation of l-arginine from intracellular l-citrulline but do not express the enzymes needed for de novo l-citrulline synthesis. Hence, l-citrulline levels in PAECs are dependent on l-citrulline transport. Once generated, l-arginine can be converted to l-citrulline and nitric oxide (NO) by the enzyme NO synthase. We sought to determine whether hypoxia, a condition aetiologically linked to pulmonary hypertension, alters the transport of l-citrulline and the expression of the sodium-coupled neutral amino acid transporters (SNATs) in PAECs from newborn piglets. METHODS AND RESULTS PAECs isolated from newborn piglets were cultured under normoxic and hypoxic conditions and used to measure SNAT1, 2, 3, and 5 protein expression and (14)C-l-citrulline uptake. SNAT1 protein expression was increased, while SNAT2, SNAT3, and SNAT5 expression was unaltered in hypoxic PAECs. (14)C-l-citrulline uptake was increased in hypoxic PAECs. Studies with inhibitors of System A (SNAT1/2) and System N (SNAT3/5) revealed that the increased (14)C-l-citrulline uptake was largely due to System A-mediated transport. Additional studies were performed to evaluate SNAT protein expression and l-citrulline levels in lungs of piglets with chronic hypoxia-induced pulmonary hypertension and comparable age controls. Lungs from piglets raised in chronic hypoxia exhibited greater SNAT1 expression and higher l-citrulline levels than lungs from controls. CONCLUSION Increased SNAT1 expression and the concomitant enhanced ability to transport l-citrulline in PAECs could represent an important regulatory mechanism to counteract NO signalling impairments known to occur during the development of chronic hypoxia-induced pulmonary hypertension in newborns.
The Nonparametric Kernel Bayes Smoother

Recently, significant progress has been made developing kernel mean expressions for Bayesian inference. An important success in this domain is the nonparametric kernel Bayes’ filter (nKB-filter), which can be used for sequential inference in state space models. We expand upon this work by introducing a smoothing algorithm, the nonparametric kernel Bayes’ smoother (nKB-smoother) which relies on kernel Bayesian inference through the kernel sum rule and kernel Bayes’ rule. We derive the smoothing equations, analyze the computational cost, and show smoothing consistency. We summarize the algorithm, which is simple to implement, requiring only matrix multiplications and the output of the nKB-filter. Finally, we report experimental results that compare the nKB-smoother to previous parametric and nonparametric approaches to Bayesian filtering and smoothing. In the supplementary materials, we show that the combination of the nKB-filter and the nKB-smoother allows marginal kernel mean computation, which gives an alternative to kernel belief propagation.
Interleukin17A Promotes Postoperative Cognitive Dysfunction by Triggering β-Amyloid Accumulation via the Transforming Growth Factor-β (TGFβ)/Smad Signaling Pathway

Although postoperative cognitive dysfunction (POCD) is relatively common in elderly patients who have undergone major surgery, the mechanisms underlying this postoperative complication are unclear. Previously, we have investigated the role of cytokine-mediated hippocampal inflammation in the development of POCD in a rat model. Here, we sought to determine in mice the role of cytokine interleukin17A (IL17A) in POCD and to characterize the associated signaling pathways. Old mice underwent hepatectomy surgery in the presence or absence of IL17A monoclonal antibody, and cognitive function, hippocampal neuroinflammation, and pathologic markers of Alzheimer’s disease (AD) were assessed. We found that the level of IL17A in the hippocampus was increased in hepatectomy mice and that cognitive impairment after surgery was associated with the appearance of certain pathological hallmarks of AD: activation of astrocytes, β-amyloid1-42 (Aβ1–42) production, upregulation of transforming growth factor-β (TGFβ), and increased phosphorylation of signaling mother against decapentaplegic peptide 3 (Smad3) protein in the hippocampus. Surgery-induced changes in cognitive dysfunction and changes in Aβ1–42 and TGFβ/Smad signaling were prevented by the administration of IL17A monoclonal antibody. In addition, IL17A-stimulated TGFβ/Smad activation and Aβ1–42 expression were reversed by IL17A receptor small interfering RNA and a TGFβ receptor inhibitor in cultured astrocytes. Our findings suggest that surgery can provoke IL17A-related hippocampal damage, as characterized by activation of astrocytes and TGFβ/Smad pathway dependent Aβ1–42 accumulation in old subjects. These changes likely contribute to the cognitive decline seen in POCD.
Reducing Noises for Recall-Oriented Patent Retrieval

Patents have been considered as key enablers for many knowledge- and information-centric companies as well as institutes. The higher the required patent capability, the more important is the need for an effective and efficient patent search system. Many conventional patent search systems produce unsatisfactory results for patent queries because the inherent search systems come from traditional keyword-based models, which inevitably lead to too many unrelated items in the search results. Consequently, these systems cost the patent experts lots of time to iteratively refine search results manually. In this paper, we propose a specialized patent-searching method, in which relationships between the keywords within each document and their implication for each patent document are investigated. With this elaborated ranking capability, keywords for valid patents are placed in higher ranks and those for noise patents are placed in sub-ranked data positions. As a benefit, our method significantly eliminates noisy data from the search results. Hence, our method is very useful for recall-oriented search for patents. Experimental results with real-life datasets show that our method outperformed many conventional patent search systems with respect to time and cost.
Deciphering the Cross-Talk Between Sphingolipid Mechanism and Signaling Pathways in Baker's Yeast

As most of the known diseases exhibit dysfunctional aspects in the signal transduction networks, there has been a great deal of enthusiasm to identify novel drug targets based on the knowledge of key signal transduction components and their links to diseases. In the present study, a computational framework was recruited for the reconstruction of protein-protein interaction networks of specific signaling mechanisms in Baker’s yeast. The objective was to analyze the interconnection between these signaling networks in order to identify the possible crosstalks between sphingolipid signaling and other signaling mechanisms. These networks are composed of the candidate proteins belonging to sphingolipid signaling, target of rapamycin (TOR) signaling, high osmolarity glycerol (HOG) signaling, pheromone response and calcium (Ca) mediated signaling in Saccharomyces cerevisiae. A detailed map including physical and functional connections that link the relevant signal transduction components to each other and to adjacent networks is developed. The proposed framework can effectively be used as a tool to give insight into the important and complicated network of signaling in higher eukaryotes.
Displacement, deprivation and hard work among Syrian refugee children in Lebanon

Background The protracted Syrian war resulted in the largest refugee crisis of our time. The most vulnerable are children who face separation from parents, interruption of schooling and child labour. This study explores the living and working conditions of Syrian children in Lebanon. Methods In this cross-sectional study, we randomly selected 153 informal tented settlements and conducted interviewer-administered surveys among Syrian refugee working children in the Bekaa Valley in Lebanon. Those aged 8–18 completed a questionnaire on sociodemographic and occupational characteristics; those aged 4–8 years were surveyed through a household questionnaire. Results We surveyed 1902 households, including 12 708 individuals and 4377 working children. Female-headed households were poorer and more food-insecure than male-headed households. Among working children (4–18 years), the average age of starting work was 10.9 years and 74.8% worked in agriculture. Compared with boys, girls earned less and were less likely to be enrolled in school. For 96.3% of working children aged 8–18 years, forced exodus to Lebanon was associated with a first child labour experience. Working conditions were harsh and worse for girls who compared to boys were less likely to receive their salary on time and take time off work. Girls worked longer in the sun and cold and were more likely to report having a health symptom at work, working under pressure and using sharp or heavy objects at work. Seventy-nine children reported knowing another child who died following a work accident. Conclusion Children, as young as 4, are forced to work, and many are compelled to forgo educational opportunities in favour of harsh and harmful labour due to difficult economic conditions. State policies facilitating access to work for adult refugees will help families meet basic needs and decrease their dependence on child labour as a coping strategy.
Automatic classification of pinnipeds based on their vocalizations and fusion of cepstral features

Acoustic vocalizations are common in marine mammals which can be used for classification purposes. Pinnipeds are a group of carnivore mammals composed by seals, sea lions, and walruses. But although, there is a great interest in research literature about acoustic monitoring of marine mammals, the identification of pinnipeds trough experts systems has been poorly studied. This paper brings a novel method for the automatic taxonomic classification of pinnipeds using a fusion of Mel and Linear Frequency Cepstral Coefficients (MFCCs and LFCCs), representing the acoustic signal in both low and high frequencies. In our experiment, we have used kNN for classification, achieving an average identification of 96.48% ± 9.17 over 18 pinniped species.
Considering Global Variance of the Log Power Spectrum Derived from Mel-Cepstrum in HMM-based Parametric Speech Synthesis

This paper utilizes global variance (GV) of the log power spectrum (LPS) derived from mel-cepstrum to improve hidden Markov model (HMM) based parametric speech synthesis. In order to alleviate over-smoothing of the generated spectral structures, an LPS-GV modeling method using line spectral pairs (LSPs) has been proposed in our previous work, where the estimated distribution of LPS-GV was combined with the trained acoustic model to determine the optimal spectral features at synthesis time. In this paper, we extend this method to the condition where mel-cepstral coefficients are used as spectral features. Further, a method of integrating LPS-GV distortions into the criterion of minimum generation error (MGE) model training is proposed in order to avoid high computational complexity of the parameter generation algorithm with GV model. Experimental results show that the parameter generation algorithm using LPS-GV model produces more natural acoustic features than the conventional GV modeling method when mel-cepstrum features are adopted. Besides, integrating LPS-GV distortions into model training criterion achieves similar performance as applying LPS-GV model at synthesis time.
Improving Twister Messaging System Using Apache Avro

Twister [1] , an iterative MapReduce framework developed by SALSA group in Pervasive Technology Institute of Indiana University takes MapReduce [2] paradigm a level further by catering applications that are iterative in nature. Twister uses publish/subscribe messaging system by using NaradaBrokering [3] . The problem triggered by this is the messaging experience delays when exchanging relatively large data messages in contrast to smaller control messages. This inspires us to implement another approach, the Remote Procedure Calls (RPC), for messaging to increase performance. We chose Apache Avro [4] as our RPC framework.
Reactive Key Management Scheme for Access Control in Group Communications

To control various access privileges in group-oriented applications having multiple data streams, we present a novel reactive key management scheme where each member can obtain the key of a data stream from public parameters only when necessary. Compared with the previous schemes, this scheme significantly reduces the amount of rekey messages for dynamic membership change due to its reactive nature.
Additive Effect of Diesel Exhaust Particulates and Ozone on Airway Hyperresponsiveness and Inflammation in a Mouse Model of Asthma

Allergic airway diseases are related to exposure to atmospheric pollutants, which have been suggested to be one factor in the increasing prevalence of asthma. Little is known about the effect of ozone and diesel exhaust particulates (DEP) on the development or aggravation of asthma. We have used a mouse asthma model to determine the effect of ozone and DEP on airway hyperresponsiveness and inflammation. Methacholine enhanced pause (Penh) was measured. Levels of IL-4 and IFN-γ were quantified in bronchoalveolar lavage fluids by enzyme immunoassays. The OVA-sensitized-challenged and ozone and DEP exposure group had higher Penh than the OVA-sensitized-challenged group and the OVA-sensitized-challenged and DEP exposure group, and the OVA-sensitized-challenged and ozone exposure group. Levels of IFN-γ were decreased in the OVA-sensitized-challenged and DEP exposure group and the OVA-sensitized-challenged and ozone and DEP exposure group compared to the OVA-sensitized-challenged and ozone exposure group. Levels of IL-4 were increased in the OVA-sensitized-challenged and ozone exposure group and the OVA-sensitized-challenged and DEP exposure group, and the OVA-sensitized-challenged and ozone and DEP exposure group compared to OVA-sensitized-challenged group. Co-exposure of ozone and DEP has additive effect on airway hyperresponsiveness by modulation of IL-4 and IFN-γ suggesting that DEP amplify Th2 immune response.
Real-time vehicle counting method based on image sequences with laser line

Being robust to changeable illumination and shadow are essential requirements of a practical vehicle counting system. In this paper, we come up with a method that detects vehicle by analyzing the state of laser line projected on lane. In addition, we use the entropy of histogram of oriented gradients (HOG) descriptor extracted from the region of interest (ROI) to quantify area percent of vehicle in a ROI. Normalized HOG descriptor is with better invariance to illumination and shadow, which makes a great contribution to the robustness of our method. Once the laser line disappears or appears in an image, we use entropy of HOG to judge that whether a vehicle is driving into or driving out of the ROI. We tested this method under different conditions, experimental results also prove that our method is robust to the change of illumination, and shadow of vehicles has no impact on accuracy and recall rate of detection result.
Referential and Visual Cues to Structural Choice in Visually Situated Sentence Production

We investigated how conceptually informative (referent preview) and conceptually uninformative (pointer to referent’s location) visual cues affect structural choice during production of English transitive sentences. Cueing the Agent or the Patient prior to presenting the target-event reliably predicted the likelihood of selecting this referent as the sentential Subject, triggering, correspondingly, the choice between active and passive voice. Importantly, there was no difference in the magnitude of the general Cueing effect between the informative and uninformative cueing conditions, suggesting that attentionally driven structural selection relies on a direct automatic mapping mechanism from attentional focus to the Subject’s position in a sentence. This mechanism is, therefore, independent of accessing conceptual, and possibly lexical, information about the cued referent provided by referent preview.
Minimum Truth Serums with Optional Predictions

In this paper, I introduce a class of mechanisms for eliciting private correlated signals from a group of expected score maximizers without external verification or knowledge about the agents’ belief structure. Built on proper scoring rules, these minimum truth serums ask agents to report a signal and a prediction of the signals of others. If two agents with the same signal have the same expectations about the signals of others, the Bayesian incentive compatibility of these mechanisms follows with no further assumptions on the agents’ belief structure. With a slight modification, the mechanism is still feasible and incentive compatible when the prediction portion of the report is optional.
A BRIEF-Gist based efficient place recognition for indoor home service robots

Visual place recognition has been vastly researched in the last decade. Most of the previous works have concentrated on improvement of performance when the environment changes due to illumination, weather or season at outdoor with abundant features and textures for place recognition. On the other hand, when a robot moves in a home environment, input images sometimes contain less features or textures for place recognition, which in turn degrades the precision and recall performance. This paper presents an efficient place recognition method based on a binary robust independent elementary features gist (BRIEF-Gist) descriptor for indoor home service robot. The proposed method simply extracts multiple BRIEF-Gist descriptors from an input image, which results in a higher performance. A simple data structure for fast comparison between images is also presented. In home environment experiments, the original BRIEF-Gist and the proposed method shows the maximum recall rate of 1.6% and 9.7%, respectively, both with a precision of 100%. On the other hand, local feature based DLoopDetector method shows below 5% of both recall and precision performance. For comparison, computation times, which are the average execution times for processing place recognition algorithms of one image with 2058 places in a map, are measured; the proposed method without the proposed data structure takes 31.4 ms, and the proposed method with the proposed data structure takes 10.5 ms.
Measuring the Flexibility of Information Technology Infrastructure: Exploratory Analysis of a Construct

Researchers and practitioners alike have taken note of the potential value of an organization's IT infrastructure. IT infrastructure expenditures account for over 58 percent of an organization's IT budget and the percentage is growing at 11 percent a year. Some even have called IT infrastructure the new competitive weapon and see it as being crucial in developing a sustained competitive advantage. Unique characteristics of an IT infrastructure determine the value of that infrastructure to an organization. One characteristic, IT infrastructure flexibility, has captured the attention of researchers and practitioners. In fact, in most recent surveys featuring issues of most importance to IT executives, the development of a flexible and responsive IT infrastructure and related topics are always at or near the top of the responses. Although the importance of IT infrastructure flexibility has been established, the development of a valid, reliable instrument to measure this construct has not been reported in the literature. The purpose of this paper is to better define the IT infrastructure flexibility construct and to develop a valid, reliable measurement instrument for this construct. In addition to the definition and operationalization of the IT infrastructure flexibility construct, this study explores the instrument's predictive validity with possible antecedent and consequent variables.
Secure Resource Allocation and Scheduling for OFDMA Decode-and-Forward Relay Networks

In this paper, we formulate an optimization problem for secure resource allocation and scheduling in orthogonal frequency division multiple access (OFDMA) half-duplex decode-and-forward (DF) relay assisted networks. Our problem formulation takes into account artificial noise generation to combat a passive multiple antenna eavesdropper and the effects of imperfect channel state information at the transmitter (CSIT) in slow fading. The optimization problem is solved by dual decomposition which results in a highly scalable distributed iterative resource allocation algorithm. The packet data rate, secrecy data rate, power, and subcarrier allocation policies are optimized to maximize the average secrecy outage capacity (bit/s/Hz securely and successfully delivered to the users via relays). Simulation results illustrate that our proposed distributed iterative algorithm converges to the optimal solution in a small number of iterations and guarantees a non-zero secrecy data rate for given target secrecy outage and channel outage probability requirements.
Mortality Modelling and Forecasting: a Review of Methods

ABSTRACT Continuing increases in life expectancy beyond previously-held limits have brought to the fore the critical importance of mortality forecasting. Significant developments in mortality forecasting since 1980 are reviewed under three broad approaches: expectation, extrapolation and explanation. Expectation is not generally a good basis for mortality forecasting, as it is subjective; expert expectations are invariably conservative. Explanation is restricted to certain causes of death with known determinants. Decomposition by cause of death poses problems associated with the lack of independence among causes and data difficulties. Most developments have been in extrapolative forecasting, and make use of statistical methods rather than models developed primarily for age-specific graduation. Methods using two-factor models (age-period or age-cohort) have been most successful. The two-factor Lee–Carter method, and, in particular, its variants, have been successful in terms of accuracy, while recent advances have improved the estimation of forecast uncertainty. Regression-based (GLM) methods have been less successful, due to nonlinearities in time. Three-factor methods are more recent; the Lee–Carter age-period-cohort model appears promising. Specialised software has been developed and made available. Research needs include further comparative evaluations of methods in terms of the accuracy of the point forecast and its uncertainty, encompassing a wide range of mortality situations.
Differences Among Self-Esteem in a Nationally Representative Sample of 15-17-Year-Old Omani Adolescents

 This study aimed to understand the association between self-esteem (SE) and gender, age, body mass index (BMI) and rural-urban dichotomy among Omani teenagers. Multivariable regression analyses were conducted using generalized linear models to study the impact of gender, age, BMI, and place of residence on the SE score after adjusting for other variables. Of the 4,432 teenagers studied, 47.4% were boys and 52.6% girls. The majority (64.4%) were from rural areas and 35.6% from urban areas of Oman. About 23% were physically underweight, while 51% were normal and 26.2% were overweight or obese. The results of this study revealed that Omani girls have higher SE than boys. It also showed that no relationship between SE and BMI. Finally, the results showed that children residing in rural areas had higher SE than those in city dweller.