Miracle-dz/UniFAR-FTUs huggingface dataset:
Perception of lung function, adherence to inhaled corticosteroids, and the role of peak expiratory flow feedback in paediatric asthma

The current BTS/SIGN asthma guideline emphasises that the diagnosis of asthma is a clinical one with no standardised definition of the type, severity or frequency of symptoms, nor of the findings on investigation that invariably leads to a diagnosis of asthma.1 However, central to all definitions of asthma is the presence of variable airflow obstruction. Documenting a history of changes in airflow obstruction either after bronchodilator treatment (reversibility) or spontaneously (variability) is an essential part of an asthma diagnosis, as well as contributing to assessment of asthma control. The variability of asthma in an individual has led to management strategies that educate and empower patients, or parents, to adjust their own therapy within a framework agreed with their clinician. This approach of ‘guided self- management’ has been shown to be effective in adults and children.2 ,3 Clark and Gong note that using a self-management approach acknowledges that clinicians cannot provide direction for every disease contingency. For effective disease control, patients need to exercise a high degree of independent decision making about adjusting their treatment. To do so, patients need to develop their own skills in self-management. Self-management is underpinned by the behavioural theory of self-regulation that has at its heart a cycle of ‘observation—judgment—reaction/s’. 4 It is by repeated iterations of this cycle that patients develop their personal repertoire of asthma management strategies. Two important questions necessarily arise. First, what observations best allow the patient/parent to monitor their asthma? Studies of self-management training programmes have commonly based asthma plans on assessment of symptoms and/or peak flow monitoring.2 ,3 ,5 ,6 Then, second, how best do clinicians ensure that patients are appropriately guided towards effective disease control? One problem is that, over time, a large number of patients fail to take prescribed medications in …
Updates on the Molecular Pathology of Selected Ocular and Ocular Adnexal Tumors: Potential Targets for Future Therapy

ABSTRACT Ophthalmic pathologic studies of retinoblastoma first definitively elucidated a genetic etiology for cancer three decades ago. Advances in DNA sequencing, protein expression profiling, and the exploration of epigenetics have since led to categorization of tumors and clinical prognostication based on genetic aberrancy. There are now many neoplasms that are defined by a characteristic genetic signature. In the past several years alone, much has been discovered in regard to the original tumor-suppressor gene initially defined in retinoblastoma as well as in other intraocular tumors such as medulloepithelioma. Our further understanding of ocular adnexal tumors that result in substantial morbidity and mortality, such as sebaceous carcinoma, has also benefited from a genetic approach. In this article, we review the clinicopathologic features of the foregoing three entities—retinoblastoma, medulloepithelioma, and sebaceous carcinoma—in order to highlight discoveries in their underlying abnormal molecular genetic functioning.
The Quantitative Characterization of Symbolic Series of a Boost Converter

In this letter, the authors put forward a symbolic approach to analyze the nonlinearities of switching power converters. This proposed method can be used to describe bifurcation and chaos behavior by means of coarse-grained symbols. First, the period-doubling structure of a symbolic series is studied in symbolic dynamics. Second, the block entropy, which is the related statistics of subsequences of a symbolic series, is introduced. Finally, two Boost converters are studied as examples to illustrate the applications of the proposed symbolic dynamics method. Via block entropy, both period-doubling and border collision bifurcations are identified and quantified, and initial value sensitivity is successfully used to distinguish chaos from periodic motions.
Design Analysis of Painted Pottery

Abstract This paper comprises a survey of selected publications describing various kinds of design analyses applied to pottery from two regions of the world that are relatively well known archaeologically: the U.S. Southwest and the Near East. My purpose is simply to demonstrate some progress, some problems, and some potentialities of this form of archaeological analysis as it has been used in these two geographic areas where painted pottery makes up a large and significant proportion of the prehistoric record.
Unsupervised, Knowledge-Free, and Interpretable Word Sense Disambiguation

Interpretability of a predictive model is a powerful feature that gains the trust of users in the correctness of the predictions. In word sense disambiguation (WSD), knowledge-based systems tend to be much more interpretable than knowledge-free counterparts as they rely on the wealth of manually-encoded elements representing word senses, such as hypernyms, usage examples, and images. We present a WSD system that bridges the gap between these two so far disconnected groups of methods. Namely, our system, providing access to several state-of-the-art WSD models, aims to be interpretable as a knowledge-based system while it remains completely unsupervised and knowledge-free. The presented tool features a Web interface for all-word disambiguation of texts that makes the sense predictions human readable by providing interpretable word sense inventories, sense representations, and disambiguation results. We provide a public API, enabling seamless integration.
Domain Adaptation from Synthesis to Reality in Single-model Detector for Video Smoke Detection

This paper proposes a method for video smoke detection using synthetic smoke samples. The virtual data can automatically offer precise and rich annotated samples. However, the learning of smoke representations will be hurt by the appearance gap between real and synthetic smoke samples. The existed researches mainly work on the adaptation to samples extracted from original annotated samples. These methods take the object detection and domain adaptation as two independent parts. To train a strong detector with rich synthetic samples, we construct the adaptation to the detection layer of state-of-the-art single-model detectors (SSD and MS-CNN). The training procedure is an end-to-end stage. The classification, location and adaptation are combined in the learning. The performance of the proposed model surpasses the original baseline in our experiments. Meanwhile, our results show that the detectors based on the adversarial adaptation are superior to the detectors based on the discrepancy adaptation. Code will be made publicly available on this http URL Moreover, the domain adaptation for two-stage detector is described in Appendix A.
Conservation of a dual-start motif in P22 lysis gene regulation

Gene 13 of bacteriophage P22 is functionally equivalent to lambda lysis gene S. Gene S codes for two products, the polypeptides S105 and S107, produced from translational initiation events at the third and first codon, respectively. We have shown that the two polypeptides have opposing functions in lysis: S105 is the lethal lysis effector, and S107 acts as an inhibitor of lysis (U. Bläsi, K. Nam, D. Hartz, L. Gold, and R. Young, EMBO J. 11:3501-3510, 1989). Gene 13 has a 108-codon reading frame and its product begins with a similar motif: Met-1-Lys-2-Lys-3-Met-4. Here, we present in vivo and in vitro evidence for the expression of a 13(108) and a 13(105) product and show that the lambda lysis control mechanisms is evolutionarily conserved in phage P22. In this case 13(108), like S107 in lambda, functions as the inhibitor of the lysis effector 13(105). Although the DNA sequences upstream of the S and 13 gene starts showed less homology, the same structural characteristics, i.e., stem-loop structures immediately upstream and about 10 codons downstream of the start region, were present in both reading frames. Using in vitro mutagenesis and toeprinting, we show that the upstream stem-loop structures of genes 13 and S, containing the Shine-Dalgarno sequence for initiations at Met-1, are interchangeable. Moreover, our data indicate that the stability of the secondary structures present in the translational initiation regions of genes S and 13 is set to create a particular ratio of initiation events at Met-1 and Met-3 or Met-4. The ratio of effector to inhibitor was much higher in P22 than in lambda. We propose that this reflects less transcriptional readthrough at the late terminator t(R) and suggests that the dual-start motif in genes 13 and S may be important for establishment of maintenance of the lysogenic state.
Inhibiting GPIb&agr; Shedding Preserves Post-Transfusion Recovery and Hemostatic Function of Platelets After Prolonged Storage

Objective—The platelet storage lesion accelerates platelet clearance after transfusion, but the underlying molecular mechanism remains elusive. Although inhibiting sheddase activity hampers clearance of platelets with storage lesion, the target platelet protein responsible for ectodomain shedding–induced clearance is not definitively identified. Monoclonal antibody 5G6 was developed recently to bind specifically human platelet receptor glycoprotein (GP)Ib&agr; and inhibit its shedding but not shedding of other receptors. Here, the role of GPIb&agr; shedding in platelet clearance after transfusion was addressed. Approach and Results—Both human leukoreduced apheresis-derived platelets and transgenic mouse platelets expressing human GPIb&agr; were stored at room temperature in the presence and absence of 5G6 Fab fragment. At various time points, aliquots of stored platelets were analyzed and compared. 5G6 Fab inhibited GPIb&agr; shedding in both platelets during storage and preserved higher level of GPIb&agr; on the platelet surface. Compared with age-matched control platelets, 5G6 Fab–stored platelets exhibited similar levels of platelet activation, degranulation, and agonist-induced aggregation. 5G6 Fab–stored human GPIb&agr; platelets exhibited significantly higher post-transfusion recovery and in vivo hemostatic function in recipient mice than control platelets. Consistently, 5G6 Fab–stored, 8-day-old human platelets produced similar improvement in post-transfusion recovery in immunodeficient mice and in ex vivo thrombus formation over collagen under shear flow. Conclusions—Specific inhibition of GPIb&agr; shedding in the stored platelets improves post-transfusion platelet recovery and hemostatic function, providing clear evidence for GPIb&agr; shedding as a cause of platelet clearance. These results suggest that specific inhibition of GPIb&agr; shedding may be used to optimize platelet storage conditions.
Foldamer hypothesis for the growth and sequence differentiation of prebiotic polymers

Significance Today’s lifeforms are based on informational polymers, namely proteins and nucleic acids. It is thought that simple chemical processes on the early earth could have polymerized monomer units into short random sequences. It is not clear, however, what physical process could have led to the next level—to longer chains having particular sequences that could increase their own concentrations. We study polymers of hydrophobic and polar monomers, such as today’s proteins. We find that even some random sequence short chains can collapse into compact structures in water, with hydrophobic surfaces that can act as primitive catalysts, and that these could elongate other chains. This mechanism explains how random chemical polymerizations could have given rise to longer sequence-dependent protein-like catalytic polymers. It is not known how life originated. It is thought that prebiotic processes were able to synthesize short random polymers. However, then, how do short-chain molecules spontaneously grow longer? Also, how would random chains grow more informational and become autocatalytic (i.e., increasing their own concentrations)? We study the folding and binding of random sequences of hydrophobic (H) and polar (P) monomers in a computational model. We find that even short hydrophobic polar (HP) chains can collapse into relatively compact structures, exposing hydrophobic surfaces. In this way, they act as primitive versions of today’s protein catalysts, elongating other such HP polymers as ribosomes would now do. Such foldamer catalysts are shown to form an autocatalytic set, through which short chains grow into longer chains that have particular sequences. An attractive feature of this model is that it does not overconverge to a single solution; it gives ensembles that could further evolve under selection. This mechanism describes how specific sequences and conformations could contribute to the chemistry-to-biology (CTB) transition.
Incidence and quantitative analysis of dissociated optic nerve fiber layer appearance: real loss of retinal nerve fiber layer?

Purpose: To assess the association between appearance of dissociated optic nerve fiber layer (DONFL) after internal limiting membrane (ILM) peeling and changes in the macular nerve fiber layer (NFL) area by spectral-domain optical coherence tomography (SD-OCT). Methods: This study included 132 consecutive patients who had successfully undergone vitrectomy with ILM peeling for idiopathic epiretinal membrane or macular holes and had been followed up for ≥6 months. Two examiners evaluated macular 5-line raster horizontal SD-OCT images and categorized the patients on the basis of presence (group I) or absence (group II) of DONFL. The average macular NFL areas in both groups were measured using ImageJ at baseline and 1, 3, and 6 months after surgery. Results: Among the 132 eyes of 132 patients, DONFL was noted in 42 (31.8%), 104 (78.8%), 106 (80.3%), and 106 (80.3%) eyes at 1, 3, and 6 months and at the last visit (12.8 ± 6.5 months) after surgery. These layers appeared most commonly between 1 and 3 months after ILM peeling. There was no significant difference in average macular NFL area between groups I and II (3453.4 ± 125.3 and 3513.0 ± 100.2 pixels, respectively) at 6 months after surgery (p = 0.56). Conclusions: Appearance of DONFL increased between postoperative months 1 and 3. Moreover, there was no significant difference in average NFL in terms of DONFL. Thus, appearance of DONFL might represent macular NFL rearrangement and reorganization rather than true mechanical damage to the NFL after ILM peeling.
Adaptive Recurrent Neural Network Based on Mixture Layer

Although Recurrent Neural Network (RNN) has been a powerful tool for modeling sequential data, its performance is inadequate when processing sequences with multiple patterns. In this paper, we address this challenge by introducing a novel mixture layer and constructing an adaptive RNN. The mixture layer augmented RNN (termed as M-RNN) partitions patterns in training sequences into several clusters and stores the principle patterns as prototype vectors of components in a mixture model. By leveraging the mixture layer, the proposed method can adaptively update states according to the similarities between encoded inputs and prototype vectors, leading to a stronger capacity in assimilating sequences with multiple patterns. Moreover, our approach can be further extended by taking advantage of prior knowledge about data. Experiments on both synthetic and real datasets demonstrate the effectiveness of the proposed method.
Enzymatically Modified Low-Density Lipoprotein Promotes Foam Cell Formation in Smooth Muscle Cells via Macropinocytosis and Enhances Receptor-Mediated Uptake of Oxidized Low-Density Lipoprotein

Objective— Enzyme-modified nonoxidized low-density lipoprotein (ELDL) is present in human atherosclerotic lesions. Our objective is to understand the mechanisms of ELDL uptake and its effects on vascular smooth muscle cells (SMC). Approach and Results— Transformation of murine aortic SMCs into foam cells in response to ELDL was analyzed. ELDL, but not acetylated or oxidized LDL, was potent in inducing SMC foam cell formation. Inhibitors of macropinocytosis (LY294002, wortmannin, amiloride) attenuated ELDL uptake. In contrast, inhibitors of receptor-mediated endocytosis (dynasore, sucrose) and inhibitor of caveolae-/lipid raft–mediated endocytosis (filipin) had no effect on ELDL uptake in SMC, suggesting that macropinocytosis is the main mechanism of ELDL uptake by SMC. Receptor for advanced glycation end products (RAGE) is not obligatory for ELDL-induced SMC foam cell formation, but primes SMC for the uptake of oxidized LDL in a RAGE-dependent manner. ELDL increased intracellular reactive oxygen species, cytosolic calcium, and expression of lectin-like oxidized LDL receptor-1 in wild-type SMC but not in RAGE−/− SMC. The macropinocytotic uptake of ELDL is regulated predominantly by intracellular calcium because ELDL uptake was completely inhibited by pretreatment with the calcium channel inhibitor lacidipine in wild-type and RAGE−/− SMC. This is in contrast to pretreatment with PI3 kinase inhibitors which completely prevented ELDL uptake in RAGE−/− SMC, but only partially in wild-type SMC. Conclusions— ELDL is highly potent in inducing foam cells in murine SMC. ELDL endocytosis is mediated by calcium-dependent macropinocytosis. Priming SMC with ELDL enhances the uptake of oxidized LDL.
The psychometric properties of the cervical nonorganic signs in patients with neck pain: an assessment of pain expression

Abstract Purpose: Neck pain is a common cause of disability. This study investigated the psychometric properties of the cervical nonorganic signs (CNOS), a tool for assessing abnormal illness behaviors in patients with neck pain. Methods: The CNOS was administered on patients with neck pain. Reliability and validity analyses were used to evaluate the psychometric properties. Exploratory factor analysis was used to investigate the dimensionality. Correlations with the Short Form-36 were used to investigate the convergent validity. Results: The results supported the reliability (inter-rater reliability intra-class correlation: 0.920), validity (correlated with body pain (|ρ|=0.31) and vitality (|ρ| =0.30), and two-factor dimensionality (χ2= 5.904, p= 0.66; χ2/df = 0.738; RMSEA< 0.001; CFI = 1.000; TLI = 1.024; SRMR = 0.047) of the scale. The two factors were pain (severe pain) and vitality (poor vitality) expressed by the patients. Conclusion: The CNOS is a reliable and valid instrument for assessing pain and vitality problems. It helps patients to express severe pain and lack of vitality. The rehabilitation discipline could use the scale to understand pain expression and to design proper rehabilitation programs. Implications for Rehabilitation The cervical nonorganic signs has two domains (pain and vitality). The scale is reliable and valid for patients with neck pain. Patients with high scores on the pain domain have severe body pain that may interfere with normal social activities. Clinicians should understand their suffering and try to help them to alleviate the pain.
The sequencing and interpretation of the genome obtained from a Serbian individual

Recent genetic studies and whole-genome sequencing projects have greatly improved our understanding of human variation and clinically actionable genetic information. Smaller ethnic populations, however, remain underrepresented in both individual and large-scale sequencing efforts and hence present an opportunity to discover new variants of biomedical and demographic significance. This report describes the sequencing and analysis of a genome obtained from an individual of Serbian origin, introducing tens of thousands of previously unknown variants to the currently available pool. Ancestry analysis places this individual in close proximity to Central and Eastern European populations; i.e., closest to Croatian, Bulgarian and Hungarian individuals and, in terms of other Europeans, furthest from Ashkenazi Jewish, Spanish, Sicilian and Baltic individuals. Our analysis confirmed gene flow between Neanderthal and ancestral pan-European populations, with similar contributions to the Serbian genome as those observed in other European groups. Finally, to assess the burden of potentially disease-causing/clinically relevant variation in the sequenced genome, we utilized manually curated genotype-phenotype association databases and variant-effect predictors. We identified several variants that have previously been associated with severe early-onset disease that is not evident in the proband, as well as putatively impactful variants that could yet prove to be clinically relevant to the proband over the next decades. The presence of numerous private and low-frequency variants, along with the observed and predicted disease-causing mutations in this genome, exemplify some of the global challenges of genome interpretation, especially in the context of under-studied ethnic groups.
Semi-Supervised Optimal Margin Distribution Machines

Semi-supervised support vector machines is an extension of standard support vector machines with unlabeled instances, and the goal is to find a label assignment of the unlabeled instances, so that the decision boundary has the maximal \textit{minimum margin} on both the original labeled instances and unlabeled instances. Recent studies, however, disclosed that maximizing the minimum margin does not necessarily lead to better performance, and instead, it is crucial to optimize the \textit{margin distribution}. In this paper, we propose a novel approach SODM (Semi-supervised Optimal margin Distribution Machine), which tries to assign the label to unlabeled instances and achieve optimal margin distribution simultaneously. Specifically, we characterize the margin distribution by the first- and second-order statistics, i.e., the margin mean and variance, and extend a stochastic mirror prox method to solve the resultant minimax problem. Extensive experiments on UCI data sets show that SODM is significantly better than compared methods, which verifies the superiority of optimal margin distribution learning.
Implementation of Chua's chaotic oscillator with an HP memristor

This paper proposes an innovative chaotic circuit based on Chua's oscillator. It combines traditional realization of a non-linear resistor in Chua's chaotic oscillator with a promising memristive circuitry. This mixed implementation connects old research works that were focused on diodes with relatively new research papers that are, now, concentrated on memristors. As a result, more reliable chaotic circuit with an HP memristor is obtained that could be used as a source of randomness. Dynamic behavior of the circuit is studied by obtaining fft analysis, different chaotic attractors and Lyapunov exponent spectrum. The results show that the addition of a memristor enhances chaotic behavior of the circuit while maintaining the same power dissipation.
Discover Multiple Novel Labels in Multi-Instance Multi-Label Learning

Multi-instance multi-label learning (MIML) is a learning paradigm where an object is represented by a bag of instances and each bag is associated with multiple labels. Ordinary MIML setting assumes a fixed target label set. In real applications, multiple novel labels may exist outside this set, but hidden in the training data and unknown to the MIML learner. Existing MIML approaches are unable to discover the hidden novel labels, let alone predicting these labels in the previously unseen test data. In this paper, we propose the first approach to discover multiple novel labels in MIML problem using an efficient augmented lagrangian optimization, which has a bag-dependent loss term and a bag-independent clustering regularization term, enabling the known labels and multiple novel labels to be modeled simultaneously. The effectiveness of the proposed approach is validated in experiments.