Miracle-dz/UniFAR-FTUs huggingface dataset:
The effect of chronic pain on voluntary and involuntary capture of attention: An event-related potential study.

Although the interrupting effect of chronic pain on voluntary-directed attention is well-documented, research on the impact of chronic pain on involuntary-directed attention remains incomplete. This study aimed to investigate the influence of chronic pain on involuntary as well as voluntary allocation of attention as, respectively, indexed by the P3a and P3b components in the event-related potential derived from the electroencephalogram. Both involuntary and voluntary captures of attention were compared between 33 patients with chronic pain and 33 healthy controls using an auditory three-stimulus oddball task (with standard, target, and unexpected distractor tones). The results revealed a reduced P3a amplitude as well as a reduced P3b amplitude in patients with chronic pain compared to healthy controls, indicating a detrimental effect of chronic pain on involuntary and voluntary attention, respectively. This study extends the picture of the impairing effects of chronic pain on attentional allocation to a current task and attentional allocation to information outside the focus of attention. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
Evaluation of HAZUS-MH Flood Model with Local Data and Other Program

This paper presents an evaluation of the HAZUS-MH flood model conducted as part of the Harris County Risk Assessment Program completed in November, 2005. The county wide analysis proved the capability of the HAZUS-MH software for a large urban county application. For the pilot watershed study, the HAZUS-MH Level 1 analysis was quick and least costly. However, the loss estimates may be questionable. The Level 2 analysis produced much more reasonable loss estimates than the Level 1 analysis when compared with other detailed analyses. HAZUS-MH Level 2 estimated $179 million for 1% probability event and $286 million for 0.2% probability event building related economic loss for residential properties in White Oak Bayou watershed. This compares well with the results of the Section 211 Federal Flood Control Project: General Reevaluation Report study for the same area of $153 million for 1% and $292 million for 0.2% loss estimates. Both the building damage count and loss estimates from HAZUS-MH Level 2 showed a l.
Maximal summability operators on the dyadic hardy spaces

It is proved that the maximal operators of subsequences of N? rlund logarithmic means and Ces? ro means with varying parameters of Walsh-Fourier series is bounded from the dyadic Hardy spaces Hp to Lp. This implies an almost everywhere convergence for the subsequences of the summability means.
Over 20 Years of Machine Learning Applications on Dairy Farms: A Comprehensive Mapping Study

Machine learning applications are becoming more ubiquitous in dairy farming decision support applications in areas such as feeding, animal husbandry, healthcare, animal behavior, milking and resource management. Thus, the objective of this mapping study was to collate and assess studies published in journals and conference proceedings between 1999 and 2021, which applied machine learning algorithms to dairy farming-related problems to identify trends in the geographical origins of data, as well as the algorithms, features and evaluation metrics and methods used. This mapping study was carried out in line with PRISMA guidelines, with six pre-defined research questions (RQ) and a broad and unbiased search strategy that explored five databases. In total, 129 publications passed the pre-defined selection criteria, from which relevant data required to answer each RQ were extracted and analyzed. This study found that Europe (43% of studies) produced the largest number of publications (RQ1), while the largest number of articles were published in the Computers and Electronics in Agriculture journal (21%) (RQ2). The largest number of studies addressed problems related to the physiology and health of dairy cows (32%) (RQ3), while the most frequently employed feature data were derived from sensors (48%) (RQ4). The largest number of studies employed tree-based algorithms (54%) (RQ5), while RMSE (56%) (regression) and accuracy (77%) (classification) were the most frequently employed metrics used, and hold-out cross-validation (39%) was the most frequently employed evaluation method (RQ6). Since 2018, there has been more than a sevenfold increase in the number of studies that focused on the physiology and health of dairy cows, compared to almost a threefold increase in the overall number of publications, suggesting an increased focus on this subdomain. In addition, a fivefold increase in the number of publications that employed neural network algorithms was identified since 2018, in comparison to a threefold increase in the use of both tree-based algorithms and statistical regression algorithms, suggesting an increasing utilization of neural network-based algorithms.
Climate-Based Modeling and Prediction of Rice Gall Midge Populations Using Count Time Series and Machine Learning Approaches

The Asian rice gall midge (Orseolia oryzae (Wood-Mason)) is a major insect pest in rice cultivation. Therefore, development of a reliable system for the timely prediction of this insect would be a valuable tool in pest management. In this study, occurring between the period from 2013–2018: (i) gall midge populations were recorded using a light trap with an incandescent bulb, and (ii) climatological parameters (air temperature, air relative humidity, rainfall and insulations) were measured at four intensive rice cropping agroecosystems that are endemic for gall midge incidence in India. In addition, weekly cumulative trapped gall midge populations and weekly averages of climatological data were subjected to count time series (Integer-valued Generalized Autoregressive Conditional Heteroscedastic—INGARCH) and machine learning (Artificial Neural Network—ANN, and Support Vector Regression—SVR) models. The empirical results revealed that the ANN with exogenous variable (ANNX) model outperformed INGRACH with exogenous variable (INGRCHX) and SVR with exogenous variable (SVRX) models in the prediction of gall midge populations in both training and testing data sets. Moreover, the Diebold–Mariano (DM) test confirmed the significant superiority of the ANNX model over INGARCHX and SVRX models in modeling and predicting rice gall midge populations. Utilizing the presented efficient early warning system based on a robust statistical model to predict the build-up of gall midge population could greatly contribute to the design and implementation of both proactive and more sustainable site-specific pest management strategies to avoid significant rice yield losses.
Dermoscopy of Primary Cutaneous B-cell Lymphoma

© 2019 Indian Dermatology Online Journal | Published by Wolters Kluwer Medknow A 71‐year‐old Caucasian man presented with a 2‐year history of an asymptomatic, slowly growing lesion on the scalp. On physical examination, there was a well‐marginated, indurated, red, smooth plaque on the left frontal scalp [Figure 1]. Dermoscopy revealed branching vessels, white circles/ lines, scale with a perifollicular component, and circle hairs with a salmon‐colored background [Figure 2]. Histopathology showed a diffuse dermal B‐cell lymphocytic (Bcl) infiltrate confirmed by strong positivity for CD‐20 immunostain [Figure 3a and b]. Bcl‐2 and Bcl‐6 immunostains were also strongly positive. Evaluation for systemic involvement with positron emission tomography/computed tomography scan was negative, rendering a diagnosis of primary cutaneous B‐cell lymphoma (PCBCL), follicle cell type.
Risk assessment of people trapped in earthquake disasters based on a single building: a case study in Xichang city, Sichuan Province, China

Abstract Strengthening the study of trapped personnel distribution in an earthquake not only ensures the efficiency and orderliness of earthquake rescue but also maximizes the survival probability of trapped people and reduces casualties. Through distinguishing the use functions of buildings, this study constructed an assessment model of people trapped in a collapsed single building due to an earthquake and evaluated the risk of individuals trapped in Xichang area, China. The results showed that the risk level of people trapped in collapsed buildings in Xichang area is high. Under the influence of seismic intensity IХ, the proportion of people trapped in collapsed buildings has reached approximately 1–2% of the total regional population. The risk level of trapped people in the daytime and at nighttime caused by the same earthquake scenario is significantly different. The number of potentially trapped people at night is nearly two times greater than that during the day. The low seismic performance of buildings is the most important factor causing the high risk of people trapped. The use function of buildings also has an important effect on the risk assessment of the trapped population distribution. Some suggestions are provided for the local risk reduction of people trapped in earthquakes.
Accurate and Robust Object SLAM With 3D Quadric Landmark Reconstruction in Outdoors

Object-oriented SLAM is a popular technology in autonomous driving and robotics. In this letter, we propose a stereo visual SLAM with a robust quadric landmark representation method.The system consists of four components, including deep learning detection, quadric landmark initialization, object data association and object pose optimization. State-of-the-art quadric-based SLAM algorithms always face observation-related problems and are sensitive to observation noise, which limits their application in outdoor scenes. To solve this problem, we propose a quadric initialization method based on the separation of the quadric parameters method, which improves the robustness to observation noise. The sufficient object data association algorithm and object-oriented optimization with multiple cues enable a highly accurate object pose estimation that is robust to local observations. Experimental results show that the proposed system is more robust to observation noise and significantly outperforms current state-of-the-art methods in outdoor environments. In addition, the proposed system demonstrates real-time performance.
ART Registries–Characteristics and experiences: A comparative study

Background: The incident of infertility is continuously increasing. As a result, the demand for medical care such as assisted reproductive technology (ART) technology is equally increasing. In order to manage the growing data and information collected on ART, there is a need for a registry system can provide accurate statistics about activities and outcomes and ensure the quality control. Therefore, the aim of this study was to examine and compare In vitro fertilization (IVF) and ART registries. Methods: This is a descriptive-comparative study in which data from the national ART registries of 14 selected countries in 2018 were collected. In this study, databases such as PubMed, Web of Sciences, and Scopus, as well as Google Scholar websites were searched. Results: Important aspects of the registry were studied. One of the most important goals of these systems is to collect information about ART, as well as to monitor and report the results and implications, and also implement new care plans. Conclusion: A national registry helps to better understand the scope and the effect of assisted reproduction on the health of infertile couples. By this registry system, different countries can compare the data with other countries, allowing the improvement of techniques and the best possible care for patients.
Transcranial Photobiomodulation in Adults with High-Functioning Autism Spectrum Disorder: Positive Findings from a Proof-of-Concept Study.

Objective: To assess the efficacy and safety of transcranial photobiomodulation (tPBM) in adults with autism spectrum disorder (ASD). Methods: Adults with high-functioning-ASD, between 18 and 59 years of age, were enrolled to receive twice a week tPBM for 8 weeks in an open-label single group design. ASD symptom severity was assessed at baseline, midpoint, and end-point, by clinician-, self-, and informant-rated measures. Treatment response was defined as a ≥30% reduction in Social Responsiveness Scale-2nd Edition (SRS-2) total score and ASD Clinical Global Impression-Improvement score ≤2. Any possible adverse events were recorded at each visit. Paired-samples t-test analyses were performed. Results: Eleven participants were enrolled, and 10 participants (9 males; 30.0 ± 11.9 years) completed the study. One participant withdrew consent before baseline. All 10 completers were included in efficacy and safety analyses. Five participants (50%) met responder criteria at end-point. Overall, 8-week tPBM was associated with significant reduction in SRS-2 total scores at end-point (SRS-2: -30.6 ± 23, p < 0.001) particularly in Social Awareness (-3.0 ± 1.9, p < 0.001), Social Communication (-10.3 ± 6, p < 0.001), Social Motivation (-5.0 ± 2.4, p < 0.001), and Restricted/Repetitive Behaviors (-7.4 ± 4.1, p < 0.001). There were statistically significant improvements at end-point in Global Assessment of Functioning scores (+12.8 ± 4.2, p < 0.001) and Quality of Life Enjoyment and Satisfaction Questionnaire scores (+6.0 ± 7.9, p = 0.02). Three participants experienced transient, mild side effects (insomnia, headache, and warmth at treatment application site). No adverse events required changes in tPBM protocol. Adherence rate was 98%. Conclusions: tPBM is a safe and feasible treatment approach that has the potential to treat core features of ASD. Further research is necessary and warranted. ClinicalTrials.gov Identifier: NCT03724552.
Frequency-dependent closed-form expressions for inductance and resistance of a single interconnect on a silicon substrate

New closed-form expressions to calculate frequency-dependent distributed inductance and the associated distributed series resistance of a single interconnect on a lossy silicon substrate (CMOS technology) are presented. The proposed analytical model for series impedance is based on a self-consistent field method and the vector magnetic potential equation. It is shown that the calculated frequency-dependent distributed inductance and the associated resistances are in good agreement with the results obtained from rigorous full-wave solutions and CAD-oriented equivalent-circuit modelling approach.
Comparative Study on the Phenolic Fingerprint and Antioxidant Activity of Strawberry Tree (Arbutus unedo L.) Leaves and Fruits

The strawberry tree (Arbutus unedo L., Ericaceae family) is an evergreen Mediterranean shrub whose leaves and fruits are used in traditional medicine due to their antioxidant, antimicrobial, antidiabetic, diuretic, and antiproliferative properties. The health benefits are mainly attributed to the presence of phenolic compounds. The aim of this study was to compare the phenolic profiles, total phenolic content (TPC), and radical scavenging activity (RSA) of A. unedo leaves and fruits collected at two locations in Croatia. Phenolic profiles were identified using an ultra-high-performance liquid chromatograph (UHPLC) coupled with a hybrid mass spectrometer (LTQ Orbitrap MS). TPC was determined by Folin–Ciocalteu’s assay, while RSA was investigated using DPPH reagent. A total of 64 phenolics (60 and 42 compounds in leaves and fruits, respectively) were identified. Hyperoside and flavan-3-ols were predominant compounds in leaves, while gallocatechin and catechin were the major compounds found in fruits. To the authors’ knowledge, 16 and 5 phenolics in leaves and fruits, respectively, were reported for the first time. Principal component analysis (PCA) showed that UHPLC-LTQ Orbitrap MS could be used to identify which phenolics were able to discriminate samples regarding plant tissue and geographical origin. TPC in leaves and fruits were in the ranges of 67.07–104.74 and 16.78–25.86 mg gallic acid equivalents (GAE)/g dried weight (dw), respectively. RSA for leaves and fruits were in the ranges of 408.92–430.98 and 74.30–104.04 μmol Trolox equivalents (TE)/g dw, respectively. The number of identified phenolics was lower in fruits compared to leaves. Such a large number of bioactive phenolics identified and the strong antioxidant activity pointed to A. unedo as a promising health-promoting plant and natural food preservative.
A two-fluid blood stasis model for false lumen thrombosis after type B dissection repair

Abstract The formation of thrombosis is a major concern in the false lumen (FL) for post-TEVAR (thoracic endovascular aortic repair) patients. Blood stasis is one of the key factors which lead to the formation of thrombosis in the arterial systems. This study proposed a computational model for blood stasis, using a two-fluid principle to track the locations of blood residual over time. The current study applied this novel model to evaluate blood stasis and thrombosis potential in four patient-specific post-TEVAR FLs of type B aortic dissection, with their follow-up in-vivo observations two years after TEVAR. The locations and topologies of residual blood in the FL predicted by the model agreed well with the in-vivo observations of thrombus. In addition, the results corresponded better with clinical observations in terms of interpatient comparison of degree of thrombosis, compared with conventional hemodynamic parameters. The blood stasis model serves as a valuable addition to conventional metrics to better predict thrombosis potential. Collectively, these metrics can provide an efficient non-invasive method for evaluating blood stasis and thrombosis potential in arterial system, and useful guidance for clinicians’ operative planning and postoperative evaluation.
Study of Ferroelectric Phase Transition in Triglycine Selenate Crystal

Triglycine selenate (TGSe) is a Hydrogen bondend order disorder type ferroelectric, which go through a structural phase transition at Tc=295K. TGSe is very similar to the Triglycine Sulphate crystal, which is extensively used in infrared detection. In the present paper we are using double time thermal Green’s function method and modified pseudospin model to discuss ferroelectric behavior of TGSe crystal. Expressions for shift, width, soft mode frequency, dielectric constant, loss and transition temperature have been evaluated. By fitting model values of physical quantities in the theoretical expressions thermal dependence of soft mode frequency, dielectric constant and loss have been calculated in the vicinity of transition temperature. Theoretical results are in well agreement with experimental results of other researchers.
The checklist of Hungarian bryophytes – second update

According to the checklist presented here, the bryophyte flora of Hungary consists of 2 species in 2 genera and 2 families of hornworts, 146 species and 3 additional infraspecific taxa (1 subspecies and 2 varieties) in 60 genera and 34 families of liverworts, and 521 species and 17 additional infraspecific taxa (5 subspecies and 12 varieties) in 186 genera and 64 families of mosses, in total 669 species, 6 subspecies and 14 varieties or 689 taxa. During the last decade, 40 bryophyte taxa (6 liverworts and 34 mosses) were added to the Hungarian bryophyte flora (Appendix 1.1), and an additional 19 taxa (4 liverworts and 15 mosses) that were already part of the Hungarian flora but not recognised in the previous checklist, are now incorporated in the list (Appendix 1.2). On the other hand, 29 taxa (7 liverworts and 22 mosses) must be excluded according to our present state of knowledge (Appendix 2). Another 13 taxa (2 liverworts and 11 mosses) that are at present not considered members of the Hungarian bryoflora are annotated in Appendix 3. They were not recognised in the previous checklist (with one exception), but are reported from Hungary in some literature and with five exceptions are also recognised in the European checklist. In many cases we have insufficient information to definitely decide upon their status. Annotations to all taxa listed in the three appendices provide additional information. In Appendix 4 to all names of bryophyte taxa that appeared in the previous checklist (except excluded taxa) the presently accepted names are assigned.
Genital Chlamydia trachomatis Seroprevalence and Uterine Fibroid Development: Cohort Study of Young African-American Women

Few studies have investigated the 1930s hypothesis that reproductive tract infections are risk factors for fibroid development. In our 2017 cross-sectional analysis from the Study of Environment, Lifestyle, and Fibroids (2010–2018), a large Detroit community-based cohort of 23–35 year-old African-American women with ultrasound fibroid screening, we found an inverse association between seropositivity for genital Chlamydia trachomatis (gCT) infection and fibroids. With prospective data from the cohort (standardized ultrasounds every 20 months over 5 years), we examined gCT’s associations with fibroid incidence (among 1158 women fibroid-free at baseline) and growth. We computed adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs) for incidence by gCT serostatus using Cox proportional hazards models. GCT’s influence on growth was assessed by estimating the difference between fibroid size change for seropositive vs. seronegative between successive ultrasounds (1254 growth measures) using a linear mixed model. Growth was scaled to change over 18 months. GCT seropositivity was not associated with fibroid incidence (aHR, 1.0 95% CI: 0.79, 1.29) or growth (4.4%, 95% CI: −5.02, 14.64). The current evidence based on both biomarker gCT data, which can capture the common undiagnosed infections, and prospective ultrasound data for fibroids suggests that Chlamydia is unlikely to increase fibroid risk.
Subject-specific features of excitation/inhibition profiles in neurodegenerative diseases

Brain pathologies are based on microscopic changes in neurons and synapses that reverberate into large scale networks altering brain dynamics and functional states. An important yet unresolved issue concerns the impact of patients excitation/inhibition profiles on neurodegenerative diseases including Alzheimer’s disease, Frontotemporal Dementia and Amyotrophic Lateral Sclerosis. In this work we used a simulation platform, The Virtual Brain, to simulate brain dynamics in healthy controls and in Alzheimer’s disease, Frontotemporal Dementia and Amyotrophic Lateral Sclerosis patients. The brain connectome and functional connectivity were extracted from 3T-MRI scans and The Virtual Brain nodes were represented by a Wong-Wang neural mass model endowing an explicit representation of the excitatory/inhibitory balance. The integration of cerebro-cerebellar loops improved the correlation between experimental and simulated functional connectivity, and hence The Virtual Brain predictive power, in all pathological conditions. The Virtual Brain biophysical parameters differed between clinical phenotypes, predicting higher global coupling and inhibition in Alzheimer’s disease and stronger NMDA (N-methyl-D-aspartate) receptor-dependent excitation in Amyotrophic Lateral Sclerosis. These physio-pathological parameters allowed an advanced analysis of patients’ state. In backward regressions, The Virtual Brain parameters significantly contributed to explain the variation of neuropsychological scores and, in discriminant analysis, the combination of The Virtual Brain parameters and neuropsychological scores significantly improved discriminative power between clinical conditions. Eventually, cluster analysis provided a unique description of the excitatory/inhibitory balance in individual patients. In aggregate, The Virtual Brain simulations reveal differences in the excitatory/inhibitory balance of individual patients that, combined with cognitive assessment, can promote the personalized diagnosis and therapy of neurodegenerative diseases.