Miracle-dz/UniFAR-FTUs huggingface dataset:
Individually Tailored Internet-Based Treatment for Young Adults and Adults With Panic Attacks: Randomized Controlled Trial

Background Previous studies on Internet-based treatment with minimal therapist guidance have shown promising results for several specific diagnoses. Objective To (1) investigate the effects of a tailored, therapist-guided, Internet-based treatment for individuals with reoccurring panic attacks, and (2) to examine whether people in different age groups (18–30 years and 31–45 years) would respond differently to the treatment. Methods We recruited 149 participants from an online list of individuals having expressed an interest in Internet treatment. Screening consisted of online questionnaires followed by a telephone interview. A total of 57 participants were included after a semistructured diagnostic interview, and they were randomly assigned to an 8-week treatment program (n = 29) or to a control condition (n = 28). Treatment consisted of individually prescribed cognitive behavior therapy text modules in conjunction with online therapist guidance. The control group consisted of people on a waitlist who later received treatment. Results All dependent measures improved significantly immediately following treatment and at the 12-month follow-up. The between-group effect size on the primary outcome measure, the Panic Disorder Severity Scale, was d = 1.41 (95% confidence interval 0.81–1.95) at posttreatment. The within-group effect size from pretreatment to 12-month follow-up was d = 1.66 (95% confidence interval 1.14–2.35). Age group had no effect, suggesting that age did not influence the outcome. Conclusions Tailoring an Internet-based treatment can be a feasible approach in the treatment of panic symptoms and comorbid anxiety and depressive symptoms. Younger adults benefit as much as adults over 30 years and up to 45 years of age. Trial Registration Clinicaltrials.gov NCT01296321; http://www.clinicaltrials. gov/ct2/show/NCT01296321 (Archived by WebCite at http://www.webcitation.org/65wddsqlL)
Timed discrete-event system supervisory control for under-load tap-changing transformers

Timed discrete-event systems (TDES) have so far not been used for modelling and control of electrical power system. Since these systems have both logical and temporal behavior, we propose to use TDES to address their control problems. Under-load tap-changing transformers (ULTC) which obviously have discrete-event behavior are widely used in transmission systems to take care of instantaneous variations in the load conditions in substations. ULTC may be controlled either automatically or manually. This paper discusses the modelling and synthesis of a timed discrete-event system supervisory controller for ULTC. Different modes of operation are considered and it is shown that the specifications are controllable and the closed loop control system is non-blocking. Protective system designers in electrical power systems can use the proposed approach to verify their required temporal and logical behavior.
Growth and mortality of coccolithophores during spring in a temperate Shelf Sea (Celtic Sea, April 2015)

Coccolithophores are key components of phytoplankton communities, exerting a critical impact on the global carbon cycle and the Earth’s climate through the production of coccoliths made of calcium carbonate (calcite) and bioactive gases. Microzooplankton grazing is an important mortality factor in coccolithophore blooms, however little is currently known regarding the mortality (or growth) rates within non-bloom populations. Measurements of coccolithophore calcite production (CP) and dilution experiments to determine microzooplankton (≤63 μm) grazing rates were made during a spring cruise (April 2015) at the Central Celtic Sea (CCS), shelf edge (CS2), and within an adjacent April bloom of the coccolithophore Emiliania huxleyi at station J2. CP at CCS ranged from 10.4 to 40.4 μmol C m−3 d−1 and peaked at the height of the spring phytoplankton bloom (peak chlorophyll-a concentrations ∼6mgm). Cell normalised calcification rates declined from ∼1.7 to ∼0.2 pmol C cell−1 d−1, accompanied by a shift from a mixed coccolithophore species community to one dominated by the more lightly calcified species E. huxleyi and Calciopappus caudatus. At the CCS, coccolithophore abundance increased from 6 to 94 cells mL−1, with net growth rates ranging from 0.06 to 0.21 d−1 from the 4th to the 28th April. Estimates of intrinsic growth and grazing rates from dilution experiments, at the CCS ranged from 0.01 to 0.86 d−1 and from 0.01 to 1.32 d−1, respectively, which resulted in variable net growth rates during April. Microzooplankton grazers consumed 59 to >100% of daily calcite production at the CCS. Within the E. huxleyi bloom a maximum density of 1986 cells mL was recorded, along with CP rates of 6000 μmol C m−3 d−1 and an intrinsic growth rate of 0.29 d−1, with ∼80% of daily calcite production being consumed. Our results show that microzooplankton can exert strong top-down control on both bloom and non-bloom coccolithophore populations, grazing over 60% of daily growth (and calcite production). The fate of consumed calcite is unclear, but may be lost either through dissolution in acidic food vacuoles, and subsequent release as CO2, or export to the seabed after incorporation into small faecal pellets. With such high microzooplanktonmediated mortality losses, the fate of grazed calcite is clearly a high priority research direction.
Dietary beetroot juice – effects on physical performance in COPD patients: a randomized controlled crossover trial

Background and objective Dietary beetroot juice (BR) supplementation has been shown to reduce the oxygen (O2) consumption of standardized exercise and reduce resting blood pressure (BP) in healthy individuals. However, the physiological response of BR in chronic obstructive pulmonary disease (COPD) remains controversial. The objective was to test exercise performance in COPD, supplementing with higher doses of BR for a longer duration compared to previous trials in this patient group. Methods Fifteen COPD patients consumed concentrated BR (2×70 mL twice daily, each containing 300 mg nitrate) or placebo (PL) (2×70 mL twice daily, nitrate-negligible) in a randomized order for 6 consecutive days. On day 7, participants consumed either BR or PL 150 min before testing. BP was measured before completing 6-minute walk test (6MWT) and two trials of submaximal cycling. The protocol was repeated after a minimum washout of 7 days. Results Plasma nitrite concentration was higher in the BR condition compared to PL (P<0.01). There was no difference between the BR and PL conditions regarding the covered distance during the 6MWT (mean ± standard error of the mean: 515±35 m (BR) vs 520±38 m (PL), P=0.46), O2 consumption of submaximal exercise (trial 1 P=0.31 vs trial 2 P=0.20), physical activity level (P>0.05), or systolic BP (P=0.80). However, diastolic BP (DBP) was reduced after BR ingestion compared to baseline (mean difference: 4.6, 95% CI: 0.1–9.1, P<0.05). Conclusion Seven days of BR ingestion increased plasma nitrite concentrations and lowered DBP in COPD patients. However, BR did not increase functional walking capacity, O2 consumption during submaximal cycling, or physical activity level during the intervention period.
Evidence for Shared Genetic Dominance Between the General Factor of Personality, Mental and Physical Health, and Life History Traits

Abstract We reanalyze previously published data on 309 MZ and 333 DZ twin pairs aged 25 to 74 years from the MIDUS survey, a nationally representative archived sample, to examine how much of the genetic covariance between a general factor of personality (GFP), a lower-order life history factor, and a general physical and mental health factor, is of the nonadditive variety. We found nonadditive genetic effects (D) could not be ruled out as a contributor to the shared variance of these three latent factors to a Super-K Life History factor. We suggest these genetic correlations support the view that a slow (K-selected) life history strategy, good health, and the GFP coevolved and are mutually coadapted through directional selection.
Blood pressure estimation using oscillometric pulse morphology

A novel pulse morphology-based approach for estimation of blood pressure from non-invasive oscillometric blood pressure measurement is presented. Quantitative measures that describe the pulse morphology are utilized to obtain the estimates of mean arterial, systolic, and diastolic pressures. Preliminary results obtained from a small set of measurements are used to demonstrate the feasibility of the proposed approach. The estimates obtained through pulse morphology-based approach is compared with those obtained from a commercial blood pressure device.
Potassium Fertilization on Fruits Orchards: A Study Case from Brazil

What captures attention of those who are familiar with the production of fruits in Brazil is the diversity of species the country offers its people and foreign markets. From the temper‐ ate regions to the tropics and the equator line, only few varieties do not find their ideal cli‐ mate and soil conditions across the country. It is common knowledge that brazilian people are privileged when it comes to the question of supply. Domestic consumers have year round acess to the types of fruit they prefer and, more recently, have even had the chance to select their product according to the different production systems. The planted area in 2010, it was 2.240 million hectares. The activity involves up wards of 5 million people throughout the country. In general, fruit growing is carried out on holdings of up to 10 hectares and provide enough income for the families to live life of quality.
Systematic corrections to the Thomas–Fermi approximation without a gradient expansion

We improve on the Thomas–Fermi approximation for the single-particle density of fermions by introducing inhomogeneity corrections. Rather than invoking a gradient expansion, we relate the density to the unitary evolution operator for the given effective potential energy and approximate this operator by a Suzuki–Trotter factorization. This yields a hierarchy of approximations, one for each approximate factorization. For the purpose of a first benchmarking, we examine the approximate densities for a few cases with known exact densities and observe a very satisfactory, and encouraging, performance. As a bonus, we also obtain a simple fourth-order leapfrog algorithm for the symplectic integration of classical equations of motion.
Adaptive Sensitive Reweighting to Mitigate Bias in Fairness-aware Classification

Machine learning bias and fairness have recently emerged as key issues due to the pervasive deployment of data-driven decision making in a variety of sectors and services. It has often been argued that unfair classifications can be attributed to bias in training data, but previous attempts to 'repair' training data have led to limited success. To circumvent shortcomings prevalent in data repairing approaches, such as those that weight training samples of the sensitive group (e.g. gender, race, financial status) based on their misclassification error, we present a process that iteratively adapts training sample weights with a theoretically grounded model. This model addresses different kinds of bias to better achieve fairness objectives, such as trade-offs between accuracy and disparate impact elimination or disparate mistreatment elimination. We show that, compared to previous fairness-aware approaches, our methodology achieves better or similar trades-offs between accuracy and unfairness mitigation on real-world and synthetic datasets.
Internet Use Frequency and Patient-Centered Care: Measuring Patient Preferences for Participation Using the Health Information Wants Questionnaire

Background The Internet is bringing fundamental changes to medical practice through improved access to health information and participation in decision making. However, patient preferences for participation in health care vary greatly. Promoting patient-centered health care requires an understanding of the relationship between Internet use and a broader range of preferences for participation than previously measured. Objective To explore (1) whether there is a significant relationship between Internet use frequency and patients’ overall preferences for obtaining health information and decision-making autonomy, and (2) whether the relationships between Internet use frequency and information and decision-making preferences differ with respect to different aspects of health conditions. Methods The Health Information Wants Questionnaire (HIWQ) was administered to gather data about patients’ preferences for the (1) amount of information desired about different aspects of a health condition, and (2) level of decision-making autonomy desired across those same aspects. Results The study sample included 438 individuals: 226 undergraduates (mean age 20; SD 2.15) and 212 community-dwelling older adults (mean age 72; SD 9.00). A significant difference was found between the younger and older age groups’ Internet use frequencies, with the younger age group having significantly more frequent Internet use than the older age group (younger age group mean 5.98, SD 0.33; older age group mean 3.50, SD 2.00; t 436=17.42, P<.01). Internet use frequency was positively related to the overall preference rating (γ=.15, P<.05), suggesting that frequent Internet users preferred significantly more information and decision making than infrequent Internet users. The relationships between Internet use frequency and different types of preferences varied: compared with infrequent Internet users, frequent Internet users preferred more information but less decision making for diagnosis (γ=.57, P<.01); more information and more decision-making autonomy for laboratory test (γ=.15, P<.05), complementary and alternative medicine (γ=.32, P<.01), and self-care (γ=.15, P<.05); and less information but more decision-making autonomy for the psychosocial (γ=-.51, P<.01) and health care provider (γ=-.27, P<.05) aspects. No significant difference was found between frequent and infrequent Internet users in their preferences for treatment information and decision making. Conclusions Internet use frequency has a positive relationship with the overall preferences for obtaining health information and decision-making autonomy, but its relationship with different types of preferences varies. These findings have important implications for medical practice.
Some specific heuristics for situation clustering problems

The present work is a continuation of several preceding author's works dedicated to a specific multiheuristic approach to discrete optimization problems. This paper considers those issues of this multiheuristic approach which relate to the problems of clustering situations. In particular it considers the issues of the author’s approach to the problems and the description of specific heuristics for the problems. We give the description of a particular example from the group of “Hierarchical Clustering Algorithms”, which we use for clustering situations. We also give descriptions of some common methods and algorithms related to such clustering. There are two examples of metrics on situations sets for two different problems; one of the problems is a classical discrete optimization problem and the other one is a game-playing programming
A machine learning approach for biomechanics-based tracking of lung tumor during external beam radiation therapy

Lung cancer radiotherapy is prone to errors due to uncertainties caused by the respiratory motion. If not accounted for, these errors may lead to poor radiation dose distribution, including insufficient does to the tumor volume and excessive dose to the healthy lung parenchyma. One effective method to account for respiratory motion is motion modeling. In this paper, we present a hybrid motion model which consists of two parts: 1) a computational biomechanical model of the lung for real-time tumor location/deformation estimation and 2) a Neural Network (NN) for real-time estimation of loading and boundary conditions of the lung biomechanical model. The second part uses the chest and abdomen surface motion as surrogate for the loading and boundary conditions, and is the main driver of the lung’s biomechanical model of the lung. In practice, the tumor location/deformation data estimated using the proposed motion model can be fed to actuators that guide a radiation therapy LINAC for continuous lung tumor targeting. The focus of this paper is two-fold: 1) developing two NNs for predicting the lung BC’s, including the diaphragm motion and transpulmonary pressure and 2) incorporating the NNs into a previously developed lung FE model to determine tumor location/deformation. Results of these two steps show highly favorable accuracy of the NNs in estimating the lung BC’s and highly favorable accuracy of the proposed motion model in predicting the lung tumor motion. As such, the proposed tracking approach can be potentially used for managing lung respiratory motion/deformation necessary for effective EBRT.
A Serious Game for Anesthesia-Based Crisis Resource Management Training

Simulation-based training has been widely adopted in medical education as a tool in the practice and development of skills within a safe, controlled, and monitored environment. However, significant cost and logistical challenges exist within traditional simulation practices. The rising popularity of gaming has seen the wide application of serious games to medical education and training. Serious gaming (and virtual simulation in general) offers a viable alternative to traditional training practices, offering students/trainees the opportunity to train until they reach a specific competency level in a safe, interactive, engaging, and cost-effective manner for effective skills transfer to the real world. Here we present a serious game for anesthesia-based crisis resource management (ACRM) training. The ACRM serious game provides trainees the opportunity to react to a simulated medical emergency within a virtual operating room while providing an interactive, and engaging training experience. Results of an experiment that was conducted to examine the usability (the ease of use of the serious game and its interface) of the serious game, and its ability to engage trainees, indicate that although improvements to the user interface can be made, it shows promise as an immersive and engaging complementary training tool.
Low tumor necrosis factor‐α levels predict symptom reduction during electroconvulsive therapy in major depressive disorder

Changes in the tumor necrosis factor‐α (TNFα) have been associated with major depressive disorder (MDD). Findings concerning the effects of electroconvulsive therapy (ECT) on the TNFα level have been contradictory. The aim was to examine the immediate and long‐term changes in the TNFα level and their associations with symptom reduction in patients with MDD during ECT.
Particle-based Pedestrian Path Prediction using LSTM-MDL Models

Recurrent neural networks are able to learn complex long-term relationships from sequential data and output a probability density function over the state space. Therefore, recurrent models are a natural choice to address path prediction tasks, where a trained model is used to generate future expectations from past observations. When applied to security applications, like predicting pedestrian paths for risk assessment, a point-wise greedy evaluation of the output pdf is not feasible, since the environment often allows multiple choices. Therefore, a robust risk assessment has to take all options into account, even if they are overall not very likely. Towards this end, a combination of particle filtering strategies and a LSTM-MDL model is proposed to address a multimodal path prediction task. The capabilities and viability of the proposed approach are evaluated on several synthetic test conditions, yielding the counter-intuitive result that the simplest approach performs best. Further, the feasibility of the proposed approach is illustrated on several real world scenes.
whole slide imaging in pathology: advantages, limitations, and emerging perspectives

Significant technologic gains have led to the adoption of innovative digital imaging solutions in pathology. Whole slide imaging (WSI), which refers to scanning of conventional glass slides in order to produce digital slides, is the most recent imaging modality being employed by pathology departments worldwide. WSI continues to gain traction among pathologists for diagnostic, educational, and research purposes. This article provides a technologic review of WSI platforms and covers clinical and nonclinical pathology applications of these imaging systems. Barriers to adoption of WSI include limiting technology, image quality, problems with scanning all materials (eg, cytology slides), cost, digital slide storage, inability to handle high-throughput routine work, regulatory barriers, ergonomics, and pathologists' reluctance. Emerging issues related to clinical validation, standardization, and forthcoming advances in the field are also addressed.
Beyond black-boxes in Bayesian inverse problems and model validation: applications in solid mechanics of elastography

The present paper is motivated by one of the most fundamental challenges in inverse problems, that of quantifying model discrepancies and errors. While significant strides have been made in calibrating model parameters, the overwhelming majority of pertinent methods is based on the assumption of a perfect model. Motivated by problems in solid mechanics which, as all problems in continuum thermodynamics, are described by conservation laws and phenomenological constitutive closures, we argue that in order to quantify model uncertainty in a physically meaningful manner, one should break open the black-box forward model. In particular we propose formulating an undirected probabilistic model that explicitly accounts for the governing equations and their validity. This recasts the solution of both forward and inverse problems as probabilistic inference tasks where the problem's state variables should not only be compatible with the data but also with the governing equations as well. Even though the probability densities involved do not contain any black-box terms, they live in much higher-dimensional spaces. In combination with the intractability of the normalization constant of the undirected model employed, this poses significant challenges which we propose to address with a linearly-scaling, double-layer of Stochastic Variational Inference. We demonstrate the capabilities and efficacy of the proposed model in synthetic forward and inverse problems (with and without model error) in elastography.