Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring Patient ’ s Perspectives and Experiences After Start with Inhalation Maintenance Therapy: A Qualitative Theory-Based Study

Background: Treatment of obstructive lung disease with inhalation therapy needs changes in patient behavior. Shortly after the start with inhaled corticosteroids (ICS) maintenance therapy, patients might be in need of additional pharmaceutical care, tailored to their individual needs. This study aimed to provide insight into patient behavior, goals and perceptions regarding their medical treatment at start with ICS therapy, by telephone interviews with ICS starters. Besides, this study investigated pharmacists ’ and patients ’ experiences with these interviews and opinions on the utility of this type of consultation for daily practice. Methods: Semi-structured telephone interviews were conducted by pharmacists with adult patients 2 – 3 weeks after starting ICS. The Theoretical Domain Framework (TDF) was used for data analysis and coding. Afterward, the patients and pharmacists were questioned about their experiences with the interview. Results: Five pharmacists conducted interviews with 23 ICS starters. Except the domains “ environmental context and resources ” , “ optimism ” , and “ reinforcement ” , the remaining 11 domains in the TDF were addressed in the interviews. The majority of patients de ﬁ ned personal goals, which mainly addressed disease or symptom control (clinical goals). Some patients showed a lack of knowledge regarding the clinical indication or therapy duration. Views on bene ﬁ cial medication effects differed between patients. Some patients speci ﬁ cally mentioned concerns or anxiety about side effects. The interviewees described different perceptions on the necessity of a personalized routine for regular medication use. Patients and pharmacists both felt positive about an added value of these interviews for daily practice. Conclusion: Patient interviews shortly after start with ICS therapy revealed various perceptions and beliefs that might in ﬂ uence medication use and achievement of individual treatment goals. The patients appreciated the opportunity to ask questions and share their perspectives and needs with their pharmacist, and the pharmacists experienced that the interviews had added value.
The Last Planner® System and Building Information Modeling in Construction Execution: From an Integrative Review to a Conceptual Model for Integration

Many researchers have stated that lean and building information modeling (BIM) have positive synergies. This integrative literature review aims at exploring this body of knowledge within the scope of combinations of BIM and the Last Planner® System, as an important Lean construction method, in the phase of construction execution. The research motivation is to find out whether a comprehensive understanding of how to take advantage of these synergies exists. Eventually, the question arises of how to condense this understanding—if existing—into a robust conceptual model for integration. As a theoretical backbone, we will make use of the original BIM-Lean interaction matrix. The hypothesis is that new BIM functionalities have been evolved since the first formulation of this interaction matrix almost 10 years ago. These new BIM functionalities cause new interactions with existing lean principles. We will focus on interactions that refer directly or indirectly to production planning and control and use them to find the most relevant literature for this review. Within the content analysis, as a part of this review, we focus on existing conceptual models and frameworks for integration of BIM and the Last Planner® System and reveal their shortcomings. Eventually, we will propose a new conceptual model.
Variation in Egg Size of Black-Tailed Godwits

As is the case for most avian species, there is considerable variation in the egg size of Continental Black-tailed Godwits Limosa l. limosa breeding in The Netherlands. It is interesting that egg size has costs and benefits yet varies considerably at the population level. To better understand this variation in egg size, we tested its relationship to a suite of individual and environmental factors. We found that egg size can decrease up to 2.8% throughout a breeding season and that egg size increases with clutch size by 1.4% with each additional egg in the clutch. Female body mass and body size explained 5% of the total variation in egg size observed across the population. Furthermore, females wintering south of the Sahara laid 3% smaller eggs than those wintering north of the Sahara. We also found that egg size increases with age, which may indicate age-related differences in the endogenous and/or exogenous conditions of females. The variation in egg size was, however, mostly the result of consistent differences among individuals across years (repeatability = 0.60). A comparison of daughters with mothers suggested that most of this individual repeatability reflects heritable variation (heritability = 0.64). The actual individual traits that underlie this heritable variation among individuals remain mostly undetermined. Smaller eggs did have a slightly lower chance of hatching, but we found no relationship between egg size and chick survival. Finally, nest and chick survival were strongly correlated with lay date. Thus, in Black-tailed Godwits, lay date may actually reflect a female's endogenous and/or exogenous condition at the moment of egg-laying. This finding may be general across birds, since food supplementation experiments usually result in advanced laying and larger clutch sizes rather than in larger eggs.
Regulatory Effect of Anwulignan on the Immune Function Through Its Antioxidation and Anti-Apoptosis in D-Galactose-Induced Aging Mice Clinical in Aging

Background: Aging is a spontaneous and inevitable phenomenon of biology, which can lead to the gradual deterioration of tissues and organs. One of the age-related deterioration processes is immunosenescence, which leads to changes in the function of immune systems, including immune cells and associated cytokines. A proper modulation of immune responses can improve the age-related immunosenescence process and then reach healthy aging. Schisandra sphenanthera , a traditional Chinese medicine, has been used as both a medicine and a nutritional supplement for thousands of years. Anwulignan, a monomer compound of Schisandra sphenanthera lignans, has been reported to possess an immunomodulatory effect. Therefore, this study was designed to further explore whether Anwulignan could also modulate the immune functions in aging model mice and the underlying mechanism. Methods: D-galactose (D-gal) is often used as an inducer of immunosenescence in animals. In this study, a mice model was created by subcutaneous D-gal (220 mg kg − 1 ) for successive 42 days. Then, the blood and spleen tissue samples were taken for the analysis and observation of cytokine levels, immunoglobulin levels, leukocyte numbers, and the phagocytic activity of macrophages, as well as the histological changes, the proliferation ability of lymphocytes, and the biochemical parameters in the spleen tissue. Results: Anwulignan signi ﬁ cantly increased the serum levels of IL-2, IL-4, IFN- γ , lgG, lgM, and lgA, decreased the content of TNF- α and IL-6 in the aging mice, and increased the blood leukocyte number, the phagocytic activity, the lymphocyte proliferation, and the spleen index in vitro. Anwulignan also signi ﬁ cantly increased the activities of SOD and GSH-Px, decreased the contents of MDA and 8-OHdG in the spleen tissue, up-regulated the expressions of Nrf2, HO-1, and Bcl2, down-regulated the expressions of Keap1, Caspase-3, and Bax in the spleen cells, and reduced the apoptosis of spleen lymphocytes. Conclusion: Anwulignan can restore the immune function that is declined in D-gal-induced aging mice partly related to its antioxidant capacity by activating the Nrf2/ARE pathway and downstream enzymes, as well as its anti-apoptotic effect by regulating Caspase-3 and the ratio of Bcl2 to Bax in the spleen. and explore the underlying mechanism. We hope this study will provide a basis for the development of anti-aging medicine or health care products.
Cu(ll) and Cd(ll) complexes containing 1, 10-Phenanthroline and Methylethylketone Thiosemicarbazone: synthesis, characterization and biological activity

Methylethylketone thiosemicarbazone (MEKT) L 1 with 1,10-phenanthroline (Phen) L 2 reacted with Cu(II) and Cd(II) metal salts to obtain mixed-ligand complexes. These complexes were characterized by elemental analysis, FT-IR and UV-Vis spectroscopies. Elemental analysis results of the compounds were in good agreement with the theoretical values. FT-IR spectral data implied the ligand as a tridentate bonding ion through thioketo sulphur, azomethine nitrogen and pyridine nitrogen. The results of the evaluation of antibacterial activity showed that both complexes exhibited considerable activity against gram-positive ( Staphylococcus aureus and Staphylococcus epidermides ) and gram-negative ( Escherichia coli and Pseudomonas aeruginosa ) pathogenic bacteria with both showing activity greater than that of the parent ligand MEKT. This implies that the ligand structural modifications accomplished enhanced the antibacterial activity of these compounds. Histopathological observation of the liver of wister rats treated with doses of 25 and 50 mg/kg body weight of MEKT and its Cu(II) and Cd(II) mixed-ligand complexes caused no observable variation when compared to the control group as cellular characteristics of lobular architecture were well preserved, normal hepatocytes, normal central vein and no indication of adhesion and no inflammatory cell infiltration an indication of little or no toxicity of the test drugs. Keywords : Methylethylketone thiosemicarbazone, 1,10-phenanthroline, antibacterial activity, Histopathology
Absence of Sac2/INPP5F enhances the phenotype of a Parkinson’s disease mutation of synaptojanin 1

Significance Extensive genetic studies have identified numerous genes whose mutations results on Parkinson’s disease (PD), including synaptojanin 1 (SJ1/Park20), a nerve terminal enriched protein that includes an inositol 4-phosphatase domain (Sac domain). In addition, many PD candidate genes have been identified by genome-wide association studies, but for most of these genes, the link to PD remains hypothetical. One such gene is Sac2/INPP5F, which, interestingly, also includes an inositol 4-phosphatase domain. While Sac2KO mice do not show obvious defects, we show a striking synthetic effect in mice of the KO of Sac2 and the Sac domain mutation of SJ1 found in PD patients. These findings support a synergistic role of SJ1 and Sac2 on a PI4P pool whose dysfunction results in PD. Numerous genes whose mutations cause, or increase the risk of, Parkinson’s disease (PD) have been identified. An inactivating mutation (R258Q) in the Sac inositol phosphatase domain of synaptojanin 1 (SJ1/PARK20), a phosphoinositide phosphatase implicated in synaptic vesicle recycling, results in PD. The gene encoding Sac2/INPP5F, another Sac domain-containing protein, is located within a PD risk locus identified by genome-wide association studies. Knock-In mice carrying the SJ1 patient mutation (SJ1RQKI) exhibit PD features, while Sac2 knockout mice (Sac2KO) do not have obvious neurologic defects. We report a “synthetic” effect of the SJ1 mutation and the KO of Sac2 in mice. Most mice with both mutations died perinatally. The occasional survivors had stunted growth, died within 3 wk, and showed abnormalities of striatal dopaminergic nerve terminals at an earlier stage than SJ1RQKI mice. The abnormal accumulation of endocytic factors observed at synapses of cultured SJ1RQKI neurons was more severe in double-mutant neurons. Our results suggest that SJ1 and Sac2 have partially overlapping functions and are consistent with a potential role of Sac2 as a PD risk gene.
Standard Patch Test Results in Patients with Contact Dermatitis

Background: A number of skin manifestations in patients with allergic contact dermatitis result from sensitization with specific allergens. The patch test is a primary diagnostic tool for identifying allergens causing allergic contact dermatitis. Objective: We identified the results of patch test with Korean standard series in patients with clinically diagnosed with contact dermatitis, and evaluated the specific relationship with each allergen. Methods: During a 5-year period, 743 patients were examined with patch test of standard Korean series. The results of patch test were then evaluated. Location of the skin lesion, age, sex, and occupation of the patients were completely reviewed. Results: Overall, 68.5% of patients had at least one positive reaction and 43.6% of patients had two or more positive reactions. Allergens most frequently causing positive reactions were nickel sulfate (27.1%), cobalt chloride (22.1%), potassium dichromate (17.9%), mercuric ammonium chloride (13.8%), and 4-phenyledediamine base (10.2%). Those patients in their 10s and 40s showed the highest rate of positive reaction. Metal allergens displayed higher positive rates than any other standard allergens. Of 201 patients who showed positive reaction to nickel, 37.8% and 27.3% of them also showed positive reaction to cobalt and chromium, respectively, representing concomitant reactions between metal-related antigens. In addition, polysensitization to cosmetics-related antigens including balsam peru and fragnance mix was evident. Conclusion: There was no significant difference in overall positive rate in patch test results compared with recent studies. However, we confirmed that metal-related allergens remain most common, and that multiple contact allergy were relatively common.
Effect of Mechanical Stimulation Applied to the Lower-Limb Musculature on Stability and Function of Stair Climbing

Mechanical muscle-tendon vibration affects musculature and the nervous system. As the vibrations used in previous studies were varied, consistently determining the effect of mechanical vibration was challenging. Additionally, only a few studies have applied vibrations to dynamic motion. This study investigated whether the vibration based on the sensorimotor response could affect the stability and function of stair climbing. Electroencephalogram (EEG) signals were recorded from the sensorimotor area, and mu rhythms, dependent on the vibration frequencies, were analyzed. Based on the analysis, the vibratory stimulus conditions were set and applied to the Achilles tendon of the lower limb during stair climbing. Simultaneously, electromyogram (EMG) signals from the gastrocnemius lateralis (GL), gastrocnemius medialis (GM), soleus (SOL), and tibialis anterior (TA) were recorded. Activations and co-activations of the shank muscles were analyzed according to the phases of stair climbing. When vibration was applied, the TA activation decreased in the pull-up (PU) phase, and calf muscle activations increased during the forward continuous (FCN) phase. These changes and their degrees differ significantly between stimulus conditions (p < 0.05). Co-activation changes, which differed significantly with conditions (p < 0.05), appeared mostly in the PU. These results imply that the vibration affects stability and function of stair climbing, suggesting that the vibration characteristics should be considered when they are applied to dynamic movement.
SPECIAL SECTION ON DATA MINING FOR INTERNET OF THINGS

With the rapid development of the mobile internet of things (IoTs) and mobile sensing devices, a large amount of mobile computing-oriented applications have attracted attention both from industry and academia. Deep learning based methods have achieved great success in artificial intelligence (AI) oriented applications. To advance the development of AI-based IoT systems, effective and efficient algorithms are in urgent need for IoT Edge Computing. Time-series data classification is an ongoing problem in applications for mobile devices (e.g. music genre classification on mobile phones). However, the traditional methods require field expertise to extract handcrafted features from the time-series data. Deep learning has been demonstrated to be effective and efficient in this kind of data. Nevertheless, the existing works neglect some of the sequential relationships found in the time-series data, which are significant for time-series data classification. Considering the aforementioned limitations, we propose a hybrid architecture, named the parallel recurrent convolutional neural network (PRCNN). The PRCNN is an end-to-end training network that combines feature extraction and time-series data classification in one stage. The parallel CNN and Bi-RNN blocks focus on extracting the spatial features and temporal frame orders, respectively, and the outputs of two blocks are fused into one powerful representation of the time-series data. Then, the syncretic vector is fed into the softmax function for classification. The parallel network structure guarantees that the extracted features are robust enough to represent the time-series data. Moreover, the experimental results demonstrate that our proposed architecture outperforms the previous approaches applied to the same datasets. We also take the music data as an example to conduct contrastive experiments to verify that our additional parallel Bi-RNN block can improve the performance of time-series classification compared with utilizing CNNs alone. INDEX TERMS Convolutional neural networks, parallel, time-series data classification.
Analysis of Road-User Interaction by Extraction of Driver Behavior Features Using Deep Learning

In this study, an improved deep learning model is proposed to explore the complex interactions between the road environment and driver’s behaviour throughout the generation of a graphical representation. The proposed model consists of an unsupervised Denoising Stacked Autoencoder (SDAE) able to provide output layers in RGB colors. The dataset comes from an experimental driving test where kinematic measures were tracked with an in-vehicle GPS device. The graphical outcomes reveal the method ability to efficiently detect patterns of simple driving behaviors, as well as the road environment complexity and some events encountered along the path.
The Effect that Auxiliary Taxonomized Auditory Distractions have on a P300 Speller while utilising Low Fidelity Equipment

In this paper, we ensue on the development of a taxonomy aimed at categorizing distractions in the P300b domain. Explicitly, we investigate the effect that auditory distractions, distinctively that of ambient noise (AN), passive talking (PT), and active listening (AL) have on the signal of a visual P300 Speller in terms of accuracy, amplitude, latency, user preference, signal morphology, and overall signal quality. This work is part of a larger EEG based project and is based on the P300 speller BCI (oddball) paradigm and the xDAWN algorithm, with eight healthy subjects; while using a non-invasive Brain-Computer Interface based on low fidelity electroencephalographic (EEG) equipment. Our results show that the accuracy was best for the Lab (LC) at 100%, followed by AN at 92.5%, PT at 90% and last AL at 87.5%, which results were in identical order to the subjects’ preferences. In addition, the amplitude and latency did not show any statistical significance in all settings. This paper provides additional results that impart insight into the practicability of the aforementioned P300 speller methodology and low-cost equipment to be used in real-world applications.
Gaussian Mixture Model Based Probabilistic Modeling of Images for Medical Image Segmentation

In this paper, we propose a novel image segmentation algorithm that is based on the probability distributions of the object and background. It uses the variational level sets formulation with a novel region based term in addition to the edge-based term giving a complementary functional, that can potentially result in a robust segmentation of the images. The main theme of the method is that in most of the medical imaging scenarios, the objects are characterized by some typical characteristics such a color, texture, etc. Consequently, an image can be modeled as a Gaussian mixture of distributions corresponding to the object and background. During the procedure of curve evolution, a novel term is incorporated in the segmentation framework which is based on the maximization of the distance between the GMM corresponding to the object and background. The maximization of this distance using differential calculus potentially leads to the desired segmentation results. The proposed method has been used for segmenting images from three distinct imaging modalities i.e. magnetic resonance imaging (MRI), dermoscopy and chromoendoscopy. Experiments show the effectiveness of the proposed method giving better qualitative and quantitative results when compared with the current state-of-the-art.
Accurate Determination of Interlayer Resistivity of 2-D Layered Systems: Graphene Case Study

In this article, we provide an accurate method to determine the interlayer resistivity of 2-D layered systems by directly measuring the resistance at a mono- to bi-layer step and feeding the measurement to a distributed resistance model. We take CVD-grown few-layer graphene (up to four layers) with different twist angles ranging from AB-stacked to totally decoupled graphene as an example. Our results show that the interlayer resistivity of AB-stacked CVD grown bilayer graphene (BLG) is in the range of 50–140 $\Omega $ . m, which is two to five orders of magnitude greater than the previously reported values for AB-stacked graphite. On the other hand, twisted BLG shows an interlayer resistivity as low as ${6}~\Omega $ . m and it decreases monotonically with increasing the twist angle, suggesting that interlayer conduction is not limited by phonon scattering, as previously reported. Furthermore, the total resistance of twisted BLG was found to be about one order of magnitude lower than its AB-stacked counterpart, which might lead to lower delay and energy-delay product in twisted graphene interconnects. In addition to that, the universality of our approach allows for accurate determination of interlayer resistivity of other 2-D layered systems such as metal dichalcogenides.
$CAG$ : Stylometric Authorship Attribution of Multi-Author Documents Using a Co-Authorship Graph

Stylometry has been successfully applied to perform authorship identification of single-author documents (AISD). The AISD task is concerned with identifying the original author of an anonymous document from a group of candidate authors. However, AISD techniques are not applicable to the authorship identification of multi-author documents (AIMD). Unlike AISD, where each document is written by one single author, AIMD focuses on handling multi-author documents. Due to the combinatoric nature of documents, AIMD lacks the ground truth information—that is, information on writing and non-writing authors in a multi-author document—which makes this problem more challenging to solve. Previous AIMD solutions have a number of limitations: (i) the best stylometry-based AIMD solution has a low accuracy, less than 30%; (ii) increasing the number of co-authors of papers adversely affects the performance of AIMD solutions; and (iii) AIMD solutions were not designed to handle the non-writing authors (NWAs). However, NWAs exist in real-world cases—that is, there are papers for which not every co-author listed has contributed as a writer. This paper proposes an AIMD framework called the Co-Authorship Graph that can be used to (i) capture the stylistic information of each author in a corpus of multi-author documents and (ii) make a multi-label prediction for a multi-author query document. We conducted extensive experimental studies on one synthetic and three real-world corpora. Experimental results show that our proposed framework (i) significantly outperformed competitive techniques; (ii) can effectively handle a larger number of co-authors in comparison with competitive techniques; and (iii) can effectively handle NWAs in multi-author documents.