Miracle-dz/UniFAR-FTUs huggingface dataset:
The impact of Inflammatory Bowel Disease related fatigue on Health-Related Quality of Life: a qualitative semi-structured interview study

Background Fatigue is a frequently reported symptom of Inflammatory Bowel Disease (IBD), having a negative impact on Health-Related Quality of Life (HRQoL). Patients’ experiences of this have not been researched in IBD. Methods Semi-structured interviews were conducted with adults with Crohn’s Disease from out-patient clinics in the United Kingdom. Interviews were audio-recorded and transcribed verbatim, then analysed using thematic analysis. Results Fourteen participant interviews were conducted. Three key themes were identified: 1) ‘The new normal’ established through adaptation and acceptance; 2) ‘Energy as a resource’ describing attempts to better manage fatigue through planning and prioritising tasks; 3) ‘Keeping healthy’ encompasses participants’ beliefs that ‘good health’ allows better management of fatigue. Conclusion Participants establish a ‘new’ normality, through maintaining the same or similar level of employment/education activities. However, this is often at the expense of social activities. Further research is required to explore patient led self-management interventions in IBD fatigue.
Estimation of Forest Fire Emissions in Southwest China from 2013 to 2017

Forest fire emissions have a great impact on local air quality and the global climate. However, the current and detailed regional forest fire emissions inventories remain poorly studied. Here we used Moderate Resolution Imaging Spectroradiometer (MODIS) data to estimate monthly emissions from forest fires at a spatial resolution of 500 m × 500 m in southwest China from 2013 to 2017. The spatial and seasonal variations of forest fire emissions were then analyzed at the provincial level. The results showed that the annual average emissions of CO2, CO, CH4, SO2, NH3, NOX, PM, black carbon, organic carbon, and non-methane volatile organic compounds from forest fires were 1423.19 × 103, 91.66 × 103, 4517.08, 881.07, 1545.04, 1268.28, 9838.91, 685.55, 7949.48, and 12,724.04 Mg, respectively. The forest fire emissions characteristics were consistent with the characteristics of forest fires, which show great spatial and temporal diversity. Higher pollutant emissions were concentrated in Yunnan and Tibet, with peak emissions occurring in spring and winter. Our work provides a better understanding of the spatiotemporal representation of regional forest fire emissions and basic data for forest fire management departments and related research on pollution and emissions controls. This method will also provide guidance for other areas to develop high-resolution regional forest fire emissions inventories.
The Impact of Health Reform on Underinsurance in Massachusetts: Do the Insured Have Adequate Protection?

Background When Massachusetts enacted its health care reform initiative in 2006, ensuring the affordability and adequacy of insurance coverage was a key goal. If residents were to be required to have health insurance, then the plans available to them must offer enough financial protection so that low-income residents who were formerly uninsured were now not simply underinsured. There was a concern among state leaders that the individual mandate might cause some people to choose plans that offer limited benefits and high cost-sharing in exchange for lower monthly premiums—the kind of coverage that could put them at risk of incurring high costs relative to income and skipping needed care to avoid the expense. As such, improving access to care while providing financial protection was central to the state’s discussions about benefit design. To help protect residents from becoming underinsured, the state established a standard for “minimum creditable coverage. ” Under this standard, all insurance plans must provide a broad scope of key benefits, including preventive and primary care, prescription drugs, and maximums for annual deductibles and out-of-pocket spending.
Functional MRI Investigation on Paradigmatic and Syntagmatic Lexical Semantic Processing

The word embeddings related to paradigmatic and syntagmatic axes are applied in an fMRI encoding experiment to explore human brain’s activity pattern during story listening. This study proposes the construction of paradigmatic and syntagmatic semantic embeddings respectively by transforming WordNet-alike knowledge bases and subtracting paradigmatic information from a statistical word embedding. It evaluates the semantic embeddings by leveraging word-pair proximity ranking tasks and contrasts voxel encoding models trained with the two types of semantic features to reveal the brain’s spatial pattern for semantic processing. Results indicate that in listening comprehension, paradigmatic and syntagmatic semantic operations both recruit inferior (ITG) and middle temporal gyri (MTG), angular gyrus, superior parietal lobule (SPL), inferior frontal gyrus. A non-continuous voxel line is found in MTG with a predominance of paradigmatic processing. The ITG, middle occipital gyrus and the surrounding primary and associative visual areas are more engaged by syntagmatic processing. The comparison of two semantic axes’ brain map does not suggest a neuroanatomical segregation for paradigmatic and syntagmatic processing. The complex yet regular contrast pattern starting from temporal pole, along MTG to SPL necessitates further investigation.
Intelligent insulin pens: A promising technology toward smart diabetic management systems

—Ever since their introduction, insulin pens have been playing a critical role within the Multiple Daily Injections. Insulin pens were originally a solution created to offer a couple of enhancements in injection. They were appreciated for their simplicity and accuracy. Recently, intelligent insulin pen technology has been introduced to offer a new direction toward enhancing the management of Multiple Daily Injections therapy. In general, technologies have always been playing a major role in the enhancement of insulin delivery; it has been more notable within the pumps therapy practices. For Multiple Daily Injections in particular, the use of technology was relatively limited, but with the introduction of intelligent insulin pens, there is an expectation that the Multiple Daily Injections therapy would elevate into a higher level of standards. Because the technology is still barely known among the groups of diabetic patients, the paper first presents a couple of assessment studies to evaluate the necessity of the intelligent insulin pen technology among diabetic patients. Based on the outcomes, patients and practitioners saw great potentials within this technology. Nevertheless, the study concluded that the intelligent insulin pens technology itself would be essential for certain groups among the diabetic patients, but for the general use, this technology could be a good alternative to the regular insulin pens. The intelligent insulin pens technology still needs to implement more functions that can serve the general diabetic patients. One feasible suggestion to achieve this goal is to extend this technology through the utilization of smart devices and ubiquitous technology. In the second stage, in order to examine the possibility of the previous point, a series of pilot studies was conducted to oversee their influence on the regular management. Based on the assessment study outcomes, a smart reminder system was proposed to test the influence on medication adherence and daily routines. The system utilizes the technology of smart devices and intelligent insulin pens. The final outcomes showed that the system could be a good support to the regular routines, and it had the potential to promote a better compliance toward the insulin medication.
Presence Detectors and Remote Heartbeat Sensing Using Radar Technology

Presence detectors based on different technologies have been around for many years now, with a constant expansion of situation implementations. In this thesis, an overview of the capabilities of different types of presence detectors has been done and the radar technology have been further investigated. A 60 GHz pulsed coherent radar has been used to measure the limits of the radar sensor’s distance and movement capabilities to extract motions originating from the heartbeat. With the radar set to a constant distance measurements of different aspects of the heart-beat characteristics as well as breathing pattern and its influence on the heart rate were performed.Measurements of the authors’ chest movement from breathing and heart beats have been performed to yield information about the morphology of the chest move-ment based on the characteristics of the heartbeats. A neural network was set upand trained by data sets from heartbeat movements while holding the breath to identify the small changes of heart beats from different persons and to classify and predict who the heartbeat belongs to. An average success rate of 90 % was achieved when predicting which person the heartbeat sequence belong to.The heart rate variability (HRV) has also been a subject to investigation where the breathing pattern is taken into account for changes in the heart rate through-out the breathing cycle. The results indicate a promising method of measuring breathing pattern, heart rate and corresponding heart rate variability needing no physical contact. (Less)
AERONAVE REMOTAMENTE PILOTADA DE BAIXO CUSTO NO ESTUDO DE PLANTAS INVASORAS EM ÁREAS DE CERRADO

The objective of this research is to analyze if the CHIS (Canopy Height Invasive Species) method represents an assertive classification routine in the identification of invasive species from RGB images in Cerrado area with evidence of disturbance. The methodology used was the production of the DSM (Digital Surface Model) and DTM (Digital Terrain Model) elevation models from the images collected in the drone field and later processed in the PhotoScan software. The production of the CHIS was based on the subtraction of the DSM and DTM models. To verify the accuracy of the CHIS model two conventional models were generated for comparison: unsupervised K-means classification and NGRDI (Normalized Red-Green Difference Index) vegetation index. The comparison between the models occurred in two sample areas chosen in a non-random manner. At the end, it was applied test of accuracy, correlation and Cohen's Kappa. The results demonstrate that the CHIS model obtained the best results in the identification of invasive species when compared with the K-means and NGRDI models. The accuracy tests for the CHIS model in sample area 1 and 2 were 0,973 and 0,9 respectively; K-means 0,209 and 0,6; NGRDI 0,795 and 0,518. The CHIS model has been shown to be promising in the identification of invasive species in disturbed areas when compared to conventionally used models.
The Development and Influence of Parasocial Relationships With Television Characters: A Longitudinal Experimental Test of Prejudice Reduction Through Parasocial Contact

The current study investigates parasocial relationships as the underlying mechanism explaining prejudice reduction following extended exposure to mediated outgroups. Heterosexual participants viewed a fictional television series for 10 weeks depicting outgroup (gay) characters in which the outgroup attribute (sexuality) was accentuated or sanitized. Parasocial relationships with outgroup characters grew significantly over the course of the study regardless of condition. White participants and participants who reported the strongest pretest prejudice experienced the most intense growth. Outgroup prejudice decreased significantly over time for participants in both experimental conditions. Parasocial relationships predicted both prejudice reduction over time and behavioral responses to the outgroup. Parasocial relationships with an ingroup character engaged in intergroup contact did not contribute to prejudice reduction beyond parasocial relationships with outgroup characters. This research suggests that audiences can develop socioemotional bonds with outgroup television characters that can influence attitudes and behaviors much the same as direct, interpersonal intergroup contact.
Designing an Accelerated Graduate Evaluation Course Using the First Principles of Instruction and Interactive Media

Evaluation skills are complex and require careful design to teach effectively. In our master’s program in Instructional Design and Performance Technology, students experienced unnecessary difficulty in our evaluation course. To facilitate students’ success, we redesigned the course using interactive media and the first principles of instruction, a comprehensive, research-based approach to creating quality teaching and learning. This article describes the obstacles identified in the initial evaluation course and how we worked to reduce their impact using interactive media and the first principles of instruction in the course redesign. We share course redesign results and make recommendations for designing evaluation courses.
Performance evaluation of K-means clustering on Hadoop infrastructure

Abstract Today we are living with the extensive volume of information which is developing at a very fast pace. Clustering is the process of group similar kinds of information. The serial k-means clustering method takes a large amount of computational time when it is applied to enormous data sets which are large in size of tera and petabyte. In this paper, we evaluated the performance of the K-means algorithm in different ways like K-mean simple (using java codes on MapReduce), K-means (using java codes on MapReduce) with IEC (Initial Equidistant Centres), K-mean on Mahout (using Machine learning library) and K-mean on Spark (Machine learning library) on static IP address data sets over the MapReduce framework. In addition to this we also compare the K-mean simple and K-mean (IEC) on different iteration level. Outcome shows on the better performance on the basis of time on different infrastructure and it also defines the behaviour of K-means algorithms on the basis of centroids and different iteration levels.
The Use of Socio-Cognitive Mindfulness in Mitigating Implicit Bias and Stereotype-Activated Behaviors

The following seven experiments were founded on the observation of a significant relationship between trait socio-cognitive mindfulness, as measured using the Langer Mindfulness Scale (LMS) and reduced implicit racial bias on the Black-White Implicit Attitudes Test (IAT), which suggested that more mindful individuals have a weaker implicit preference for white Americans over black Americans. This initial observation led to a subsequent interest in experimentally-introducing state socio-cognitive mindfulness as a prejudice reduction intervention, with implications for those contexts in which implicit bias has been found to predict social injustices and discrimination including health care, education, law enforcement, and the labor force. Five experiments in Chapter 3 evaluated the effectiveness of a state socio-cognitive mindfulness-based paradigm, rooted in novelty-production and engagement, in reducing implicit racial bias, in reducing implicit associations between race and criminality, in reducing implicit face-based bias related to facial maturity, and in increasing intergroup empathy. Across four experiments, having participants re-sort the same social stimuli (e.g., faces of people) according to novel, psychological categories was most effective at reorganizing their preconceptions and at reducing implicit social bias compared to re-sorting according to familiar, physical categories that likely activated stereotypes related to the respective social stimuli. A fifth, follow-up
Activity tracking and improved health outcomes

Activity tracking devices are a popular way for health-minded individuals to measure daily movement and estimate energy expenditure. Tracking, in its many forms, has been proven to improve health outcomes. From paper diaries to devices and smartphone applications, these data are becoming more important and have the potential to be used in the physician's office as part of a realistic physical activity plan for improved health outcomes. As a health-care professional, amid a rapidly expanding accelerometer market, it is important to know the application and practicality of these devices, as well as the evidence behind an individual's usage. What we choose to recommend, as health-care professionals, can influence the health and well-being of patients in the wellness arena. This chapter will look at research focused on activity tracking, including metrics such as sleep, nutrition, and physical activity, and health outcomes to further educate health-care professionals in an ever-evolving field.
High gain cylindrical dielectric resonator integrated with horn for multiband wireless applications

In this article, a multiband high gain cylindrical dielectric resonator (CDR) integrated with conical horn antenna is reported. This antenna has been designed for multiband wireless frequency applications. To enhance the gain, modified conical‐shaped horn is integrated to the CDR. The proposed antenna resonates at 2.3, 3.5, 3.9, 7.5, 9.2, and 9.95 GHz, respectively. Antenna attains measured 14.1 dBi peak gain at 10.7 GHz resonant frequency. In all the frequency bands, antenna offers more than 80% radiation efficiency. Simulated and experimental results show a commendable agreement. This antenna covers LTE services, Citizens Broadband Radio Service, WiMAX, vehicular communication, cellular communication, and radar applications.
Exoskeleton Online Learning and Estimation of Human Walking Intention Based on Dynamical Movement Primitives

Human walking intention estimation is a critical step for the active assistance control of lower limb exoskeleton, because the purpose of active assistance control is human motion assistance rather than human motion tracking. Complying with human walking intention is the basic requirement of human walking assistance. Hence, the human walking intention must be estimated first to ensure the exoskeleton will not impede human motion. Actually, estimating human walking intention is to estimate human joint torque during walking. In order to estimate a smooth personalized human joint torque profile, an online learning and prediction algorithm of human joint trajectory and joint torque is proposed in this article. The algorithm is based on the dynamical movement primitives model which is used for online learning and predicting human joint trajectory which is substituted into the human dynamics model to estimate the human joint torque. The results of human walking experiments demonstrate that the proposed algorithm can not only predict a smooth human joint trajectory and joint torque profile in real time but also compensate the phase delay caused by sensor signal filtering. Hence, the proposed algorithm is suitable for the active walking assistance control of exoskeleton.
The Value of Metacognitive Skills and Intrinsic Motivation for Current and Future Sport Performance Level in Talented Youth Athletes

Purpose: In order to spend training time efficiently, insight in factors that relate to the development of sport performance is highly relevant for competitive athletes and their trainers/coaches. Purpose is to unravel the value of metacognitive skills (MCS) and intrinsic motivation for current and future sport performance level. Methods: Talented youth athletes (n = 103) active in field hockey, basketball and soccer filled in questionnaires for IM and MCS. Level of sport performance was expressed by an adjusted version of the formula for Eliteness of Swann et al. (2015). Correlations between IM, MCS and current sport performance level were calculated and followed by structural equation modelling and regression analysis. For a subsample (n = 41), level of performance was also determined one year later (“future performance level”). Results: Results show that, in contrast to IM (r = -.10), MCS are positively related to current sport performance level (r = .33, p p p < .05) and 18% in future performance level can be explained by MCS. Conclusion: MCS are positively related to sport performance level in youth athletes, not only in the here and now, but even more over one year. With IM as underlying factor, using MCS and especially reflection, may help youth athletes to improve their sport performance.
Status from fighting? Reassessing the relationship between conflict involvement and diplomatic rank

ABSTRACT Recent research has provided evidence that conflict improves a belligerent’s status. I argue that this finding is based on a specification error. The relationship between the CINC index, which is used to control for material capabilities as a potential confounder, and change in diplomatic rank is not linear. Accounting for this non-linearity eliminates the apparent positive effect of MID initiation on change in diplomatic rank, and also reduces the effect of MID victory. The analysis has significant implications for foreign policy, for ongoing debates over the most useful way to model the link between status dissatisfaction and belligerence, and, more broadly, for analyses that use CINC to control for material capabilities.
Delineating the Seasonally Modulated Nonlinear Feedback Onto ENSO From Tropical Instability Waves

Tropical instability waves (TIWs), the dominant form of eddy variability in the tropics, have a peak period at about 5 weeks and are strongly modulated by both the seasonal cycle and El Niño–Southern Oscillation (ENSO). In this study, we first demonstrated that TIW‐induced nonlinear dynamical heating (NDH) is basically proportional to the TIW amplitude depicted by a complex index for TIW. We further delineated that this NDH, capturing the seasonally modulated nonlinear feedback of TIW activity onto ENSO, is well approximated by a theoretical formulation derived analytically from a simple linear stochastic model for the TIW index. The results of this study may be useful for the climate community to evaluate and understand the TIW‐ENSO multiscale interaction.
Stable artificial solid electrolyte interphase films for lithium metal anode via metal–organic frameworks cemented by polyvinyl alcohol

Lithium (Li) metal anodes have shown a huge potential for next-generation energy storage because of the high theoretical specific capacity and negative potential. Nevertheless, due to the change in the volume and the existence of Li dendrites, the application of the Li metal anode is significantly limited. For the purpose of developing a stable Li metal anode to avoid Li dendrite formation, we introduced a stable artificial solid electrolyte interphase (SEI) film, which was prepared by polyvinyl alcohol (PVA) cementing a metal organic framework (Zn-MOF). The environment-friendly and non-toxic PVA acted as a “glue” to cement the rigid Zn-MOF. The artificial SEI film had high Li ion conductivity and excellent flexibility, which is beneficial for uniform lithium flux, inhibiting dendrite growth and easing the volume change. Consequently, benefitting from the safeguard of the Zn-MOF/PVA artificial SEI film, the anode delivered high coulombic efficiency above 97.7% beyond 250 cycles at a current density of 3 mA cm−2.