Miracle-dz/UniFAR-FTUs huggingface dataset:
A Multivariate Meta-Analysis of Motivational Interviewing Process and Outcome

Motivational interviewing (MI) theory proposes a process whereby a set of therapist behaviors has direct effects on client outcomes and indirect effects through in-session processes (e.g., client change talk). Despite clear empirical support for the efficacy of MI across settings, the results of studies evaluating proposed links between MI process and outcome have been less clear. In the present study, we used a series of multivariate meta-analyses to test whether there are differential relationships between specific MI-consistent and MI-inconsistent therapist behaviors, MI therapist global ratings, client change language, and clinical outcomes. Based on 19 primary studies (N = 2,614), we found a significant relationship between MI-consistent therapist behaviors and greater client change talk, as well as greater client sustain talk. Higher therapist global ratings (empathy and MI spirit) were significantly related to increased MI-consistent behaviors, decreased MI-inconsistent behaviors, increased client change talk, yet also increased client sustain talk. Therapist global ratings were not significantly related to clinical outcomes. Client sustain talk was a significant predictor of worse clinical outcomes, while client change talk was unrelated to outcome. Variability within the correlations indicated that MI-consistent and MI-inconsistent therapist behaviors were differentially related to therapist global ratings of empathy and MI spirit. Similar to past research, present findings provide equivocal support for hypothesized MI process outcome relationships. Clinical implications and future areas of MI mechanism research are discussed.
An Investigation of Signal Characteristics and T1 Relaxation Time in Brain MR Images of Young versus Old Healthy Adults

During healthy aging, the brain undergoes several structural changes such as atrophy and volumetric changes. Although less evident, changes in tissue concentration also occur. Such differences in brain tissues introduce prominent low contrast effects to the MRI images of the aging population, causing segmentation problems in the data processing pipeline. Measures of tissue characteristics such as T1 provide unique and complementary information to widely used measures of brain signal characteristics. In this study, multiple Fast Low Angle Shot (FLASH) images are collected for T1 mapping of whole brains from young and old adults. Tissue signal characteristics are evaluated on predefined regions and compared across Magnetization Prepared Rapid Gradient Echo (MPRAGE) and T1 maps. Additionally, segmentation performance is analyzed. As a result, we found that T1 maps are superior to MPRAGE protocol in terms of contrast, especially within sub-cortical areas. Furthermore, degradation of grey-white-ratio (GWR) due to aging processes is observed to be less pronounced in T1 estimated whole brain images. Moreover, sensitivity of T1 maps (54.6%) are higher than MPRAGE images (34.4%) in detection of sub-cortical gray matter. In sum we concur that T1 maps provide better avenues to investigate age related morphological changes in the brain.
Exploring the Impact of and Perceptions about Interactive, Self-Explaining Environments in Molecular- Level Animations

This mixed-method study investigates the effects of interactivity in animationsof a molecular-level process and explores perceptions aboutthe animated learning tool used. Treatments were based on principlesof cognitive psychology designed to study the main effects of treatmentand spatial ability and their interaction. Results with students (n=189)showed that science majors scored higher than non-science majors inretention measures (i.e., structure and function) but not in transfer.Significant main effects were found for treatment in function questions and spatial ability in structure questions. There was a significant interaction between treatment and spatial ability in structure questions. Additionally, in this study participants believed the key and the motion of ions and molecules were the most helpful parts of the animation. This study shows that students perceive the animations as being supportive of their learning, suggesting that animations do have a role in science classrooms.
Research on Volatile Organic Compounds From Bacillus subtilis CF-3: Biocontrol Effects on Fruit Fungal Pathogens and Dynamic Changes During Fermentation

The dynamic changes of the levels of volatile organic compounds (VOCs) produced by Bacillus subtilis CF-3 and their biocontrol effects on common fungal pathogens were researched in this study. The results showed that the VOCs in 24-h fermentation liquid (24hFL) of B. subtilis CF-3 inhibited mycelial growth of Botrytis cinerea, Colletotrichum gloeosporioides, Penicillium expansum, Monilinia fructicola, and Alternaria alternata, with a mean inhibition rate of 59.97%. The inhibitory effect on M. fructicola and C. gloeosporioides was the highest; they were therefore selected as target fungal pathogens for further experiments. Based on headspace solid-phase microextraction combined with gas chromatography-mass spectrometry (HS-SPME-GC-MS), 74 potential VOCs were identified during the fermentation: 15 alcohols, 18 ketones, 4 pyrazines, 4 esters, 10 acids, 5 phenols, 3 hydrocarbons, 3 amines, 2 aldehydes, 5 ethers, and 5 other components. At different fermentation times, the type and content of VOCs were different. Most of the potential VOCs (62 VOCs) were identified in the 48hFL. The inhibition rates of all VOCs reached their peaks (73.46% on M. fructicola and 63.63% on C. gloeosporioides) in the 24hFL. Among the identified VOCs, 2,4-di-tert-butylphenol, 1-octanol, and benzothiazole showed significant positive correlations with the rates of M. fructicola and C. gloeosporioides inhibition. Benzoic acid and benzaldehyde showed a significant positive correlation with the rates of M. fructicola inhibition, and anisole and 3-methylbutanal showed a significant positive correlation with the rates of C. gloeosporioides inhibition. In vitro, 2,4-di-tert-butylphenol showed a strong inhibitory effect on both M. fructicola and C. gloeosporioides. In vivo, benzothiazole showed the strongest inhibitory effect on the mycelial extensions of both M. fructicola and C. gloeosporioides, which also led to an increased rate of healthy fruit. The results of the present study clarified that 2,4-di-tert-butylthiophenol and benzothiazole are key inhibitory VOCs produced by B. subtilis CF-3.
Combining NSAM and CPC concentrations to determine airborne nanoparticle count median diameter: Application to various laboratory and workplace aerosols

ABSTRACT Because nanomaterials have been increasingly developed and used in many technology and industry sectors over the last 20 years, an increasing number of workers is likely to be exposed to airborne nanoparticles. In addition, the question of the nanomaterial characteristics that should be assessed in epidemiological studies remains open. Thus, assessing occupational exposure to airborne nanoparticles will not only rely on mass concentration and chemical composition. Rather, key parameters, such as particle size, have to be included in measurement strategies. We previously proposed a methodology to estimate the Count Median Diameter (CMD) of an aerosol based on the simultaneous size-integrated measurement of two particle concentrations, lung-deposited surface area, and number, thanks to field-portable, commercially available aerosol instruments (Nanoparticle Surface Area Monitor/Condensation Particle Counter combination). In addition to previous work, this study investigates the case of various polydisperse metal oxides, organic oil, and salt particles with CMDs ranging from 16–410 nm. Once corrected, the CMDs derived from the NSAM/CPC agree within ±20% with regard to the reference electrical mobility equivalent diameter, regardless of aerosol composition, morphology, or geometric standard deviation (GSD). Furthermore, the field-applicability of the method was tested through 6 sets of experimental data stemming from workplace measurement campaigns where different materials were produced and handled (TiO2, SiO2, Ag, Multi-Walled Carbon Nanotubes—MWCNT), covering a range of CMDs between 40 and 190 nm. All situations considered, the approach based on the combination of a NSAM and a CPC leads to a satisfying estimation of particle CMD, within ±20% compared to reference CMD.
Olympic Committee consensus statement on prevention , diagnosis and management of paediatric anterior cruciate ligament ( ACL ) injuries

In October 2017, the International Olympic Committee hosted an international expert group of physiotherapists and orthopaedic surgeons who specialise in treating and researching paediatric anterior cruciate ligament (ACL) injuries. Representatives from the American Orthopaedic Society for Sports Medicine, European Paediatric Orthopaedic Society, European Society for Sports Traumatology, Knee Surgery and Arthroscopy, International Society of Arthroscopy Knee Surgery and Orthopaedic Sports Medicine, Pediatric Orthopaedic Society of North America, and Sociedad Latinoamericana de Artroscopia, Rodilla y Deporte attended. Physiotherapists and orthopaedic surgeons with clinical and research experience in the field, and an ethics expert with substantial experience in the area of sports injuries also participated. Injury management is challenging in the current landscape of clinical uncertainty and limited scientific knowledge. Injury management decisions also occur against the backdrop of the complexity of shared decision-making with children and the potential long-term ramifications of the injury. This consensus statement addresses six fundamental clinical questions regarding the prevention, diagnosis, and management of paediatric ACL injuries. The aim of this consensus statement is to provide a comprehensive, evidence-informed summary to support the clinician, and help children with ACL injury and their parents/guardians make the best possible decisions.
Germination and early plant development of ten plant species exposed to titanium dioxide and cerium oxide nanoparticles

Ten agronomic plant species were exposed to different concentrations of nano–titanium dioxide (nTiO2) or nano–cerium oxide (nCeO2) (0 μg/mL, 250 μg/mL, 500 μg/mL, and 1000 μg/mL) to examine potential effects on germination and early seedling development. The authors modified a standard test protocol developed for soluble chemicals (OPPTS 850.4200) to determine if such an approach might be useful for screening engineered nanomaterials (ENMs) and whether there were differences in response across a range of commercially important plant species to 2 common metal oxide ENMs. Eight of 10 species responded to nTiO2, and 5 species responded to nCeO2. Overall, it appeared that early root growth may be a more sensitive indicator of potential effects from ENM exposure than germination. The observed effects did not always relate to the exposure concentration, indicating that mass‐based concentration may not fully explain the developmental effects of these 2 ENMs. The results suggest that nTiO2 and nCeO2 have different effects on early plant growth of agronomic species, with unknown effects at later stages of the life cycle. In addition, standard germination tests, which are commonly used for toxicity screening of new materials, may not detect the subtle but potentially more important changes associated with early growth and development in terrestrial plants. Environ Toxicol Chem 2016;35:2223–2229. Published 2016 Wiley Periodicals Inc. on behalf of SETAC. This article is a US Government work and, as such, is in the public domain in the United States of America.
Benthic Algal Community Structures and Their Response to Geographic Distance and Environmental Variables in the Qinghai-Tibetan Lakes With Different Salinity

Uncovering the limiting factors for benthic algal distributions in lakes is of great importance to understanding of their role in global carbon cycling. However, limited is known about the benthic algal community distribution and how they are influenced by geographic distance and environmental variables in alpine lakes. Here, we investigated the benthic algal community compositions in the surface sediments of six lakes on the Qinghai-Tibetan Plateau (QTP), China (salinity ranging from 0.8 to 365.6 g/L; pairwise geographic distance among the studied lakes ranging 8–514 km) employing an integrated approach including Illumina-Miseq sequencing and environmental geochemistry. The results showed that the algal communities of the studied samples were mainly composed of orders of Bacillariales, Ceramiales, Naviculales, Oscillatoriales, Spirulinales, Synechococcales, and Vaucheriales. The benthic algal community compositions in these QTP lakes were significantly (p < 0.05) correlated with many environmental (e.g., dissolved inorganic and organic carbon, illumination intensity, total nitrogen and phosphorus, turbidity and water temperature) and spatial factors, and salinity did not show significant influence on the benthic algal community structures in the studied lakes. Furthermore, geographic distance showed strong, significant correlation (r = 0.578, p < 0.001) with the benthic algal community compositions among the studied lakes, suggesting that spatial factors may play important roles in influencing the benthic algal distribution. These results expand our current knowledge on the influencing factors for the distributions of benthic alga in alpine lakes.
Hierarchical QoE model for wireless video streaming with fountain codes

The rapid growth of video in wireless networks is a crucial issue to be addressed by content providers. Nowadays, an emerging and promising trend is the development of solutions aimed at maximizing the quality of experience (QoE) of end users. However, the prediction of the QoE perceived by users in different conditions remains a major challenge. In this paper, we propose a two-layer hierarchical QoE model for wireless video streaming systems that employ fountain codes in forward error correction (FEC). The first layer decomposes the impact of fountain codes on the user QoE into three factors, namely the initial playback delay, the rebuffering frequency and the rebuffering time. The second layer of the QoE model relates the user QoE in terms of the mean opinion score (MOS) to the aforementioned three factors using a quadratic function. An exemplary application of the developed QoE model in the admission control of a bandwidth-limited video on demand (VoD) system is given with the goal toward guaranteeing the QoE quality of all users. Simulation results confirms the effectiveness of the developed admission control technique.
Cardiovascular disease detection using a new ensemble classifier

One of the biggest problems in mechanical life is the lack of mobility that can cause thousands of problems in human health. In the last decade, along with the life of a machine, many diseases, including cancer and cardiovascular disease, have been common in many societies that kill many people every year. Data mining is based on collected data and existing history to create a model that can be effective in predicting new cases of a disease, whether they are risky or not. The higher the accuracy of the prediction or recognition of a given pattern or model means the higher efficiency of the algorithm. In this study, data on cardiovascular patients collected from the UCI Laboratory is utilized for applying discovery pattern algorithms including Decision tree, Neural Networks, Rough Set, SVM, Naive Bayes, and compare their accuracy and prediction. Finally, we propose a hybrid algorithm to increase the accuracy of these algorithms. Based on the results, the proposed hybrid method achieved an F-measure of 86.8% which outperforms other competing methods.
Actin-binding proteins differentially regulate endothelial cell stiffness, ICAM-1 function and neutrophil transmigration

ABSTRACT Chronic vascular inflammation is driven by interactions between activated leukocytes and the endothelium. Leukocyte &bgr;2-integrins bind to endothelial intercellular adhesion molecule 1 (ICAM-1), which allows leukocyte spreading, crawling and transendothelial migration. Leukocytes scan the vascular endothelium for permissive sites to transmigrate, which suggests that there is apical membrane heterogeneity within the endothelium. However, the molecular basis for this heterogeneity is unknown. Leukocyte adhesion induces ICAM-1 clustering, which promotes its association to the actin-binding proteins filamin B, &agr;-actinin-4 and cortactin. We show that these endothelial proteins differentially control adhesion, spreading and transmigration of neutrophils. Loss of filamin B, &agr;-actinin-4 and cortactin revealed adaptor-specific effects on a nuclear-to-peripheral gradient of endothelial cell stiffness. By contrast, increasing endothelial cell stiffness stimulates ICAM-1 function. We identify endothelial &agr;-actinin-4 as a key regulator of endothelial cell stiffness and of ICAM-1-mediated neutrophil transmigration. Finally, we found that the endothelial lining of human and murine atherosclerotic plaques shows elevated levels of &agr;-actinin-4. These results identify endothelial cell stiffness as an important regulator of endothelial surface heterogeneity and of ICAM-1 function, which in turn controls the adhesion and transmigration of neutrophils.
Olive Polyphenols and the Metabolic Syndrome

Here, the effects of consuming polyphenol-rich olive products, including olive leaves, their crude extract, and extra virgin olive oil, on aspects of the metabolic syndrome are reviewed. We have sought to summarize the available scientific evidence from dietary intervention trials demonstrating a role for these phytochemicals in ameliorating aberrant glucose metabolism, high blood pressure and elevated blood lipids, and we discuss the potential mechanisms underpinning these observations. Searches for relevant literature published in English were conducted via PubMed and Science Direct. Based on published dietary intervention studies, there is convincing evidence to show that olive polyphenols, independently of olive lipids, reduce risk factors for metabolic syndrome, in particular by improving blood sugar and blood pressure control, and in reducing low density lipoprotein oxidation. There is more limited evidence to suggest that the consumption of olive polyphenols or related products can reduce body weight and visceral fat or impede weight gain, and similarly there are some limited data suggesting improved lipid profiles. There is some mechanistic data to support observations made in human volunteers, but further work is needed in this area. The consumption of olive polyphenols within the context of a healthy pattern of food intake may, in part, explain the reduced risk of metabolic disease associated with adherence to the Mediterranean diet.
An End‐to‐End Steel Strip Surface Defects Recognition System Based on Convolutional Neural Networks

Steel strip surface defects recognition is very important to steel strip production and quality control, which needs further improvement. In this paper, an end‐to‐end surface defects recognition system is proposed for steel strip surface inspection. This system is based on the symmetric surround saliency map for surface defects detection and deep convolutional neural networks (CNNs) which directly use the defect image as input and defect category as output for seven classes of steel strip defects classification. The CNNs are trained purely on raw defect images and learned defect features from the training of network, which avoiding the separation between feature extraction and image classification, so that forms an end‐to‐end defects recognition pipeline. To further illustrate the superiority of the defect recognition methods with CNNs, an authoritative and standard steel strip surface defect dataset − NEU is also used to evaluate the defect recognition effect using CNNs. Experimental results demonstrate that the proposed methods perform well in steel strip surface defect detection of different types and achieve a high recognition rate for defect images. In addition, a series of data augmentation methods are discussed to analyze its effect on avoiding over‐fitting for defects recognition.
Prevalence and co-prevalence of comorbidities among patients with type 2 diabetes mellitus

Abstract Objective: Patients with type 2 diabetes (T2DM) often have multiple comorbidities which may impact the selection of antihyperglycemic therapies. The purpose of this study was to quantify the prevalence and co-prevalence of common comorbidities. Research design and methods: A retrospective study was conducted using the Quintiles Electronic Medical Record database. Adult patients with T2DM who had ≥1 encounter from July 2014 to June 2015 (index period) with ≥1 year medical history available were included. The index date was defined as the most recent encounter date during the 1 year index period. Main outcome measures: Comorbid conditions were assessed using all data available prior to and including the index date. Patient characteristics, laboratory measures, and comorbidities were summarized via descriptive analyses, overall and by subgroups of age (<65, 65–74, 75+ years) and gender. Results: Of the 1,389,016 eligible patients, 53% were female and the median age was 65 years. 97.5% of patients had at least one comorbid condition in addition to T2DM and 88.5% had at least two. The comorbidity burden tended to increase in older age groups and was higher in men than women. The most common conditions in patients with T2DM included hypertension (HTN) in 82.1%; overweight/obesity in 78.2%; hyperlipidemia in 77.2%; chronic kidney disease (CKD) in 24.1%; and cardiovascular disease (CVD) in 21.6%. The highest co-prevalence was demonstrated for the combination of HTN and hyperlipidemia (67.5%), followed by overweight/obesity and HTN (66.0%), overweight/obesity and hyperlipidemia (62.5%), HTN and CKD (22.4%), hyperlipidemia and CKD (21.1%), HTN and CVD (20.2%), hyperlipidemia and CVD (20.1%), overweight/obesity and CKD (19.1%) and overweight/obesity and CVD (17.0%). Limitations: Limitations include the potential for misclassification/underreporting due to the use of diagnostic codes, drug codes, or laboratory measures for identification of medical conditions. Conclusions: The vast majority of patients with T2DM have multiple comorbidities. To ensure a comprehensive approach to patient management, the presence of multimorbidity should be considered in the context of clinical decision making.
Enhancing Correlation Filter based Trackers with Size Adaptivity and Drift Prevention

To enhance correlation filter (CF) based trackers with size adaptivity and more robustness; we propose a new strategy which integrates an external segmentation methodology with CF based trackers in a closed feedback loop. Employing this strategy both enables object size disclosure during tracking; and automatic alteration of track models and parameters online in non-disturbing manner, yielding better target localization. Obviously, consolidation of CF based trackers with these properties introduces much more robustness against track center drifts and relaxes widespread perfectly centralized track initialization assumption. In other words, even if track window center is given with certain offset to center of target object at track initialization; proposed methodology achieves target centralization by aligning tracker template center with target center smoothly in time. Experimental results indicates that proposed algorithm increases performance of CF trackers in terms of accuracy and robustness without disrupting their real-time processing capabilities.