Miracle-dz/UniFAR-FTUs huggingface dataset:
Low-Dose Nonlinear Effects of Smoking on Coronary Heart Disease Risk

Some recent discussions of adverse human health effects of active and passive smoking have suggested that low levels of exposure are disproportionately dangerous, so that “The effects of even brief (minutes to hours) passive smoking are often nearly as large (averaging 80% to 90%) as chronic active smoking” (Barnoya and Glantz, 2005). Recent epidemiological evidence (Teo et al., 2006) suggests a more linear relation. This paper reexamines the empirical relation between self-reported low levels of active smoking and risk of coronary heart disease (CHD) in public-domain data from the National Health and Nutrition Examination Survey (NHANES). Consistent with biological evidence on J-shaped and U-shaped relations between smoking-associated risk factors and CHD risks, we find that low levels of active smoking do not appear to be associated with increased CHD risk. Several methodological challenges in epidemiology may explain how model-derived estimates can predict low-dose linear or concave dose-response estimates, even if the empirical (i.e., data-based) relation does not show a clear increased risk at the lowest doses.
Passive Surveillance for I. scapularis Ticks: Enhanced Analysis for Early Detection of Emerging Lyme Disease Risk

ABSTRACT Lyme disease (LD) is emerging in Canada because of the northward expansion of the geographic range of the tick vector Ixodes scapularis (Say). Early detection of emerging areas of LD risk is critical to public health responses, but the methods to do so on a local scale are lacking. Passive tick surveillance has operated in Canada since 1990 but this method lacks specificity for identifying areas where tick populations are established because of dispersion of ticks from established LD risk areas by migratory birds. Using data from 70 field sites in Quebec visited previously, we developed a logistic regression model for estimating the risk of I. scapularis population establishment based on the number of ticks submitted in passive surveillance and a model-derived environmental suitability index. Sensitivity-specificity plots were used to select an optimal threshold value of the linear predictor from the model as the signal for tick population establishment. This value was used to produce an “Alert Map” identifying areas where the passive surveillance data suggested ticks were establishing in Quebec. Alert Map predictions were validated by field surveillance at 76 sites: the prevalence of established I. scapularis populations was significantly greater in areas predicted as high-risk by the Alert map (29 out of 48) than in areas predicted as moderate-risk (4 out of 30) (P < 0.001). This study suggests that Alert Maps created using this approach can provide a usefully rapid and accurate tool for early identification of emerging areas of LD risk at a geographic scale appropriate for local disease control and prevention activities.
A cooperative demand response program for smart grids

Demand response as a demand side management program, can be a solution for providing the electrical power at peak times. In this paper an effective demand response program is proposed that not only reduces the consumer bill costs and demand peak, but also increases the utility benefit. According to use different method of demand response use, different results are obtained that can be either useful for cost saving or peak reduction. Produced structures by proposed demand response method are optimized by differential evolution algorithm. Simulation results for proposed structures are presented and an executive comparison for these results is done.
An Empirical Study on Business/ICT Alignment in European Organisations

The information and communication technology (ICT) literature has demonstrated that alignment between business and ICT has a positive effect on business performance and effectiveness. This study builds on these results, complemented with some theoretical foundations of the firm, to argue that Business/ICT alignment can be the basis of a sustainable competitive advantage for organisations. To do so, we first evaluate how well-aligned European organisation really are. We report on the results of a survey1 carried out in Belgium, France, Germany, United Kingdom, The Netherlands, Italy and Spain. More than 640 valid responses were analysed. The goal of the study is twofold: to analyse context dependency of business/ICT alignment and to deduce some practical guidelines for managers in the field. Two important results are discussed: First, we demonstrate the influence of different ICT strategies on alignment performance. Next, we describe how organisations which establish specific ICT management routines obtain, on average, better alignment performance scores.
The Development of Character Judgments From Faces

First impressions play a central role in human social interaction. In particular, the face is a rich source of information that perceivers use in making both initial and lasting character judgments. Despite the large and growing body of work demonstrating that these judgments affect outcomes in domains as crucial as elections and criminal sentencing, little remains known about the ontogenetic origins of this consequential aspect of human social cognition. The purpose of this dissertation is to provide a set of early investigations into the development of face-to-trait inferences. Paper 1 demonstrates that, like adults, even children as young as 3-4 years of age provide consistent trait judgments when asked to judge two-dimensional computer-generated face images, suggesting that this general ability is so fundamental as to emerge strongly at the earliest ages tested. Paper 2 shows that this propensity is so deeply ingrained at an early age that similar consensus across the lifespan emerges in response to static faces belonging to adults, children, and even rhesus macaques. Paper 3 investigates the potential consequences of these judgments, showing that face-based character assessments influence attributions of trait-relevant behaviors and even cause children to modulate their own behaviors towards others. The findings of this dissertation clearly illustrate that face-to-trait inference emerges early in development, and is therefore a fundamental element of human social cognition with important consequences throughout the lifespan.
Origins of Efficient Perovskite Solar Cells with Low-Temperature Processed SnO2 Electron Transport Layer

Recently, SnO2 has been noticed as a promising material for electron-transport layer of planar perovskite solar cells. SnO2 layer presents advantages of low-temperature processability and high power-conversion efficiency, and understanding the correlations between the SnO2 properties and device performance will provide a key to realize more efficient perovskite solar cells. Herein, uniform electron-transport layer using SnO2 nanoparticles is fabricated, and the effect of annealing on the solar-cell performance is discussed. Solar cells with low-temperature processed SnO2-nanoparticle layer (below 120 °C or even at room temperature) exhibit desirable short-circuit current, open-circuit voltage, and fill factor with the highest efficiency of 19.0%. Using atomic force microscopy and ultraviolet photoelectron spectroscopy, both great surface uniformity and favorable band alignment of low-temperature processed SnO2 layer have been observed, which are responsible for the device performance. Furthermore, deep el.
A new benzopyran derivative from Pseuduvaria indochinensis Merr.

From the twigs and leaves of Pseuduvaria indochinensis Merr. , a new benzopyran derivative, pseudindochin (1), was isolated together with three known compounds, oligandrol (2), (6E,10E)-isopolycerasoidol (3) and polycerasoidol (4). The structure of compound 1 was elucidated on the basis of extensive spectroscopic data interpretation, including 1D, 2D NMR, HR-ESI-MS, UV and IR. Moreover, compounds 1–4 were evaluated in vitro for their cytotoxic activities against HL-60 and SMMC-7721 cell lines, but these compounds were essentially non-cytotoxic (IC50>30 μg/mL).
Changes in the Vision-related Resting-state Network in Pituitary Adenoma Patients After Vision Improvement

Background: The aim of this research was to investigate the changes in the vision-related resting-state network (V-RSN) in pituitary adenoma (PA) patients after vision improvement, which was induced by operative treatment. Methods: Ten PA patients with an improved visual acuity or/and visual field after transsphenoidal pituitary tumor resection were recruited and underwent a complete neuro-ophthalmologic evaluation, as well as an magnetic resonance imaging (MRI) protocol, including structural and resting-state functional MRI sequences before and after the operation. The regional homogeneity (ReHo) of the V-RSN was evaluated. Two sample t-test was performed to identify the significant differences in the V-RSN in the PA patients before and after transsphenoidal pituitary tumor resection. Results: Compared with the preoperation counterparts, the PA patients with improved vision after the operation exhibited reduced ReHo in the bilateral thalamus, globus pallidus, caudate nucleus, putamen nucleus, supplementary motor area, and left hippocampal formation, and increased ReHo in the bilateral cuneus gyrus, calcarine gyrus, right lingual gyrus, and fusiform gyrus. Conclusions: PA patients with improved vision exhibit increased neural activity within the visual cortex, but decreased neural activity in subareas of the multisensory and multimodal systems beyond the vision cortex.
Technological Innovations in Data Collection: Acceptance, Data Quality and Costs

Whether computer assisted data collection methods should be used for survey data collection is no longer an issue. Most professional research organizations, commercial, government and academic, are adopting these new methods with enthusiasm. Computer assisted telephone interviewing (CATI) is most prevalent, and computer assisted personal interviewing (CAPI) is rapidly gaining in popularity. Also, new forms of electronic reporting of data using computers, telephones and voice recognition technology are emerging. This paper begins with a taxonomy of current computer assisted data collection methods. It then reviews conceptual and theoretical arguments and empirical evidence on such topics as: (1) respondents and interviewer acceptance of new techniques, (2) effect of computer assisted interviewing on data quality, (3) consequences for survey costs and (4) centralized vs. decentralized deployment of CATI.
New Energy Analytical Results for the Regulation of Underactuated Overhead Cranes: An End-Effector Motion-Based Approach

In this paper, we present a novel end-effector (payload) motion-based control development approach for the regulation of underactuated overhead cranes, which is efficient even in the presence of external disturbance and system parameter variations/uncertainties. The control system is elegantly constructed so that the problem of simultaneously regulating the trolley motion and suppressing the payload swing is successfully addressed by stabilizing a newly defined payload motion signal. Specifically, we first couple the actuated trolley motion and the unactuated payload swing via the defined payload motion signal, based on which a new energy storage function is established. Consequently, a payload motion-based control law is constructed straightforwardly, and the equilibrium point of the resulting closed-loop system is proven to be asymptotically stable by Lyapunov techniques and LaSalle's invariance theorem. Unlike traditional energy-based controllers, the proposed control law takes a much simpler structure independent of the system parameters. Both simulation and experimental results are included to demonstrate the superior performance of the proposed control method over some traditional controllers and its robustness against parameter variations, which illuminates the promising practical application potentiality of the designed crane control system.
Discriminative Maximum Margin Image Object Categorization with Exact Inference

Categorizing multiple objects in images is essentially a structured prediction problem: the label of an object is in general dependent on the labels of other objects in the image. We explicitly model object dependencies in a sparse graphical topology induced by the adjacency of objects in the image, which benefits inference, and then use maximum margin principle to learn the model discriminatively. Moreover, we propose a novel exact inference method, which is used in training to find the most violated constraint required by cutting plane method. A slightly modified inference method is used in testing when the target labels are unseen. Experiment results on both synthetic and real datasets demonstrate the improvement of the proposed approach over the state-of-the-art methods.
Blood conservation strategies reduce the need for transfusions in ascending and aortic arch surgery

Introduction: Ascending and aortic arch surgery is associated with higher levels of blood loss and subsequent need for allogeneic blood transfusions. We hypothesized that aggressive, comprehensive blood conservation strategies may limit the need for transfusions and, subsequently, improve postoperative outcomes. Methods: Over a five-year period, 189 patients underwent proximal aortic surgery at our institution. Fifty-one patients underwent surgery using a comprehensive blood conservation strategy (BCS), including preoperative hemoglobin optimization, antifibrinolytic therapy, intraoperative acute normovolemic hemodilution, cell salvage and meticulous surgical technique. The remaining 138 patients underwent surgery using conventional techniques (CONV). Results: Patients in the BCS group required fewer transfusions during their hospital stay compared to the conventional group (56.9% vs. 72.5%, p=0.041). When examining elective cases, this trend widens, with 40.0% of BCS patients requiring any transfusions compared to 72.9% patients in the conventional group (p=0.001). Red cell (47.1% vs. 62.3%, p=0.06), plasma (43.1% vs. 61.6%, p=0.02) and platelets (27.5% vs. 47.8%, p=0.01) were also less frequently required in the BCS group than the conventional group, respectively. When a transfusion was required, patients in the BCS group received significantly fewer units of red blood cells (2.8 ± 7.0 units) than the conventional group (5.81 ± 9.5 units; p=0.039). Mortality was similar in both groups (BCS 7.8%, conventional 10.9%, p=0.54); however, there was significantly less morbidity in the BCS group, using a composite of any of 10 major postoperative complications (23.5% vs. 39.1%; p=0.046). Median intensive care unit (ICU) and hospital lengths of stay were 2 and 7 days in the BCS group and 2 and 8 days in the CONV group (p=0.15), respectively. Conclusions: The aggressive use of a comprehensive blood conservation strategy in ascending and aortic arch surgery can significantly reduce the need for blood transfusions and is associated with less postoperative morbidity. Further evaluation with a randomized, controlled trial is warranted.
Distributed fixed-structure control of spatially interconnected systems

Novel stability and quadratic performance conditions in LMI form are presented that allow the design of fixed-structure controllers for linear time-space-invariant spatially interconnected systems in input-output form. By using an implicit distributed input-output representation, Finsler's Lemma can be applied, while avoiding issues resulting from non-causality of spatially interconnected systems. An illustrative example is used to compare distributed fixed-structure and full-order designs to control spatially interconnected systems.
Managing Mutual Information & Transfer Entropy In Synthetic Ecologies

In this paper, we consider transfer entropy and mutual information in terms of their application in the emerging highly interconnected and dynamic synthetic ecologies underpinned by the Cyber. We consider existing models relating to the management of learning and change within organizations and as they may relate to mutual information (MI) and transfer entropy (TE) within socio and info/techno settings, based upon a Mech-Organic perspective. A premise of this paper is that change is costly and that it needs to be seen through a social as well as an info/techno lens. We identify potential improvements to existing models (i.e. for managing change, over time) and applications applied to the management of change by considering alternative models such as transferring knowledge between handovers and how MI and TE may be applied collaboratively within a learning organization.
Detection and Interpretation of Opinion Expressions in Spoken Surveys

This paper describes a system for automatic opinion analysis from spoken messages collected in the context of a user satisfaction survey. Opinion analysis is performed from the perspective of opinion monitoring. A process is outlined for detecting segments expressing opinions in a speech signal. Methods are proposed for accepting or rejecting segments from messages that are not reliably analyzed due to the limitations of automatic speech recognition processes, for assigning opinion hypotheses to segments and for evaluating hypothesis opinion proportions. Specific language models are introduced for representing opinion concepts. These models are used for hypothesizing opinion carrying segments in a spoken message. Each segment is interpreted by a classifier based on the Adaboost algorithm which associates a pair of topic and polarity labels to each segment. The different processes are trained and evaluated on a telephone corpus collected in a deployed customer care service. The use of conditional random fields (CRFs) is also considered for detecting segments and results are compared for different types of data and approaches. By optimizing the choice of the strategy parameters, it is possible to estimate user opinion proportions with a Kullback-Leibler divergence of 0.047 bits with respect to the true proportions obtained with a manual annotation of the spoken messages. The proportions estimated with such a low divergence are accurate enough for monitoring user satisfaction over time.
A 1 SPM 0 Core 0 A 1 SPM 3 Core 3 Page SPM 2 Core 2 Page App SPM 1 Core 1

Distributed scratchpad memories (SPM) in embedded many-core systems require careful selection of data placement such that good performance can be achieved. In this paper, we propose SPMPool to share the available on-chip scratchpads on many-cores among executing applications in order to reduce the overall memory access latency. By pooling SPM resources, we can assign underutilized memory resources, due to idle cores or low memory-usage, to applications based on their needs. As the first workload-aware SPM mapping solution for many-cores, SPMPool dynamically allocates data at runtime in order to address the unpredictable set of applications concurrently executing (workload); this is accomplished without prior knowledge of the workload. The data mapping can be adaptively re-allocated at runtime based on temporal variance of the workload and the proximity of SPM resources. Our simulations for many-core systems with a range of configurations from 16 to 1024 cores show that significant improvements can be achieved: for many complex application scenarios, SPMPool can decrease the total memory access latency by up to 55% compared to limiting executing cores to use their local SPM.
Clinical characteristics of ADHD in Thai children.

OBJECTIVE To study the clinical characteristics of children who were diagnosed as ADHD. MATERIAL AND METHOD A retrospective chart review was conducted on 202 children who came to a child mental health clinic and were diagnosed as ADHD. RESULTS Most cases were in the 6-12 years age group and came from small families with 1-2 children. Males outnumbered females (M:F = 3.4:1). One-fifth of the sample received previous psychiatric evaluation from other health professionals but parents needed 'second opinion'. The most frequent chief complaints were academic/learning problems. Almost one-fourth of the samples came for problems not directly related to ADHD. In this group the most frequent complaints were aggressive and oppositional behavior Comorbidity was found in 53.5%. More than half of the cases who took intelligence tests had an IQ below 90. Behavioral management was the only treatment modality in 38% of the sample. In 62% stimulants were instituted either at the beginning of treatment or as an "add-on" after behavioral management proved to be insufficient. Among cases that received stimulants, 28% needed the combination of other psychotropic medications, mostly antidepressant and anxiolytic drugs. CONCLUSION A study of the clinical characteristics of ADHD in Thai children revealed male preponderance and high rates of non-ADHD presentations and comorbid conditions. Awareness of varied presentations of ADHD and proper treatment of comorbid conditions is imperative in the comprehensive care of ADHD children.
Direct and Indirect Influence of Non-Native Neighbours on Pollination and Fruit Production of a Native Plant

Background Entomophilous non-native plants can directly affect the pollination and reproductive success of native plant species and also indirectly, by altering the composition and abundance of floral resources in the invaded community. Separating direct from indirect effects is critical for understanding the mechanisms underlying the impacts of non-native species on recipient communities. Objectives Our aims are: (a) to explore both the direct effect of the non-native Hedysarum coronarium and its indirect effect, mediated by the alteration of floral diversity, on the pollinator visitation rate and fructification of the native Leopoldia comosa and (b) to distinguish whether the effects of the non-native species were due to its floral display or to its vegetative interactions. Methods We conducted field observations within a flower removal experimental setup (i.e. non-native species present, absent and with its inflorescences removed) at the neighbourhood scale. Results Our study illustrates the complexity of mechanisms involved in the impacts of non-native species on native species. Overall, Hedysarum increased pollinator visitation rates to Leopoldia target plants as a result of direct and indirect effects acting in the same direction. Due to its floral display, Hedysarum exerted a direct magnet effect attracting visits to native target plants, especially those made by the honeybee. Indirectly, Hedysarum also increased the visitation rate of native target plants. Due to the competition for resources mediated by its vegetative parts, it decreased floral diversity in the neighbourhoods, which was negatively related to the visitation rate to native target plants. Hedysarum overall also increased the fructification of Leopoldia target plants, even though such an increase was the result of other indirect effects compensating for the observed negative indirect effect mediated by the decrease of floral diversity.
A hybrid mode matching/FEM technique with edge elements for solving waveguides discontinuity problems

A hybrid mode matching/finite element method (FEM) for the analysis of waveguide discontinuities is presented. The method combines the computational efficiency of the modal analysis with the versatility and flexibility of the FEM, and enables us to accurately model geometries where a modal expansion is not available. Moreover, the use of Whitney's edge element within the FEM region allows us to overcome the problem of the spurious solutions arising in nodal FEM. Numerical results that illustrate the accuracy of the method are presented.