Miracle-dz/UniFAR-FTUs huggingface dataset:
Relative importance of fuel management, ignition management and weather for area burned: evidence from five landscape–fire–succession models

The behaviour of five landscape fire models (CAFE, FIRESCAPE, LAMOS(HS), LANDSUM and SEM- LAND) was compared in a standardised modelling experiment. The importance of fuel management approach, fuel management effort, ignition management effort and weather in determining variation in area burned and number of edge pixels burned (a measure of potential impact on assets adjacent to fire-prone landscapes) was quantified for a standardised modelling landscape. Importance was measured as the proportion of variation in area or edge pixels burned explained by each factor and all interactions among them. Weather and ignition management were consistently more important for explaining variation in area burned than fuel management approach and effort, which were found to be statistically unimportant. For the number of edge pixels burned, weather and ignition management were generally more important than fuel management approach and effort. Increased ignition management effort resulted in decreased area burned in all models and decreased number of edge pixels burned in three models. The findings demonstrate that year-to-year variation in weather and the success of ignition management consistently prevail over the effects of fuel management on area burned in a range of modelled ecosystems.
Characterization and Modeling of the Ferromagnetic Shape Memory Alloy Ni-Mn-Ga for Sensing and Actuation

Ferromagnetic Shape Memory Alloys (FSMAs) in the Ni-Mn-Ga system are a recent class of active materials that can generate magnetic field induced strains of 10% by twin-variant rearrangement. This work details an extensive analytical and experimental investigation of commercial single-crystal Ni-Mn-Ga under quasi-static and dynamic conditions with a view to exploring the material’s sensing and actuation applications. The sensing effect of Ni-Mn-Ga is experimentally characterized by measuring the flux density and stress as a function of quasi-static strain loading at various fixed magnetic fields. A bias magnetic field of 368 kA/m is shown to mark the transition from irreversible to reversible (pseudoelastic) stress-strain behavior. At this bias field, a reversible flux-density change of 0.15 Tesla is observed over a range of 5.8% strain. A constitutive model based on continuum thermodynamics is developed to describe the coupled magnetomechanical behavior of Ni-Mn-Ga. Mechanical dissipation and the microstructure of Ni-Mn-Ga are incorporated through internal state variables. The constitutive response of the material is obtained by restricting the process through the second law of thermodynamics. The model is further modified to describe the actuation and blocked-force behavior under a unified framework. Blocked-force characterization shows that Ni-Mn-Ga exhibits a blocking stress of 1.47 MPa and work capacity of 72.4 kJ/m. The model requires only
Combining Deep and Handcrafted Image Features for Presentation Attack Detection in Face Recognition Systems Using Visible-Light Camera Sensors

Although face recognition systems have wide application, they are vulnerable to presentation attack samples (fake samples). Therefore, a presentation attack detection (PAD) method is required to enhance the security level of face recognition systems. Most of the previously proposed PAD methods for face recognition systems have focused on using handcrafted image features, which are designed by expert knowledge of designers, such as Gabor filter, local binary pattern (LBP), local ternary pattern (LTP), and histogram of oriented gradients (HOG). As a result, the extracted features reflect limited aspects of the problem, yielding a detection accuracy that is low and varies with the characteristics of presentation attack face images. The deep learning method has been developed in the computer vision research community, which is proven to be suitable for automatically training a feature extractor that can be used to enhance the ability of handcrafted features. To overcome the limitations of previously proposed PAD methods, we propose a new PAD method that uses a combination of deep and handcrafted features extracted from the images by visible-light camera sensor. Our proposed method uses the convolutional neural network (CNN) method to extract deep image features and the multi-level local binary pattern (MLBP) method to extract skin detail features from face images to discriminate the real and presentation attack face images. By combining the two types of image features, we form a new type of image features, called hybrid features, which has stronger discrimination ability than single image features. Finally, we use the support vector machine (SVM) method to classify the image features into real or presentation attack class. Our experimental results indicate that our proposed method outperforms previous PAD methods by yielding the smallest error rates on the same image databases.
Implications of prescribing a fixed-dose combination in clinical cardiology practice: a retrospective observational study using a single medical centre database in Korea

Objective Fixed-dose combination (FDC) prescribing enhances adherence to medication. However, there are limited data regarding the usefulness of FDC drugs across different risk groups. The aim of this study was to explore the relationship between FDC discontinuation and clinical outcomes. Methods From January 2008 to December 2014, patients with FDC prescriptions who visited a cardiology outpatient clinic at a tertiary university hospital in Daegu, Republic of Korea were retrospectively identified. The 10-year atherosclerotic cardiovascular disease (ASCVD) risk score and 20 conventional cardiovascular (CV) risk factors were assessed. Patients were classified according to FDC continuation, together with a tertile of 20 risks. CV events were defined as the composite of admission for worsening heart failure or diabetes, stroke, ischaemic heart disease, and CV death. Results 502 patients were prescribed with one of the following FDC products: calcium channel blocker (CCB) plus angiotensin receptor blockers (ARB), CCB plus statins, and ARB plus diuretics. During follow-up (mean 2.8±2.4 years), 203 discontinuations (40.4%) occurred. FDC-discontinued patients had lower ASCVD risk scores (24.8% vs. 28.8%, p<0.001), and patients with <6 risk factors discontinued FDC frequently. During follow-up, 57 events (11.4%) were reported: 30 (14.8%) in FDC-discontinued patients and 27 (9.1%) in FDC-continued patients (p=0.062). In multivariate models accounting for events, FDC discontinuation (p<0.001) and high ASCVD risk score (p=0.017) were associated with CV events. Conclusions FDC discontinuation was common among patients attending the cardiology outpatient clinic. Our analyses suggest that FDC discontinuation in patients at high ASCVD risk may have an impact on CV event rates.
Phenotypic and genotypic analyses of an attenuated porcine reproductive and respiratory syndrome virus strain after serial passages in cultured porcine alveolar macrophages

The porcine reproductive and respiratory syndrome virus (PRRSV) is a globally ubiquitous swine viral pathogen that causes major economic losses worldwide. We previously reported an over-attenuated phenotype of cell-adapted PRRSV strain CA-2-P100 in vivo. In the present study, CA-2-P100 was serially propagated in cultured porcine alveolar macrophage (PAM) cells for up to 20 passages to obtain the derivative strain CA-2-MP120. Animal inoculation studies revealed that both CA-2-P100 and CA-2-MP120 had decreased virulence, eliciting weight gains, body temperatures, and histopathologic lesions similar to those in the negative control group. However, compared to CA-2-P100 infection, CA-2-MP120 yielded consistently higher viremia kinetics and enhanced antibody responses in pigs. All pigs inoculated with CA-2-MP120 developed viremia and seroconverted to PRRSV. During 20 passages in PAM cells, CA-2-MP120 acquired 15 amino acid changes that were mostly distributed in nsp2 and minor structural protein-coding regions. Among these changes, 6 mutations represented reversions to the sequences of the reference CA-2 and parental CA-2-P20 strains. These genetic drifts may be hypothetical molecular markers associated with PRRSV macrophage tropism and virulence. Our results indicate that the PAM-passaged CA-2-MP120 strain is a potential candidate for developing a live, attenuated PRRSV vaccine.
Separate mesocortical and mesolimbic pathways encode effort and reward learning signals

Significance Learning about multiple features of a choice option is crucial for optimal decision making. How such multiattribute learning is realized remains unclear. Using functional MRI, we show that the brain exploits separate mesolimbic and mesocortical networks to simultaneously learn about reward and effort attributes. We show a double dissociation, evident in the expression of effort learning signals in dorsomedial prefrontal and reward learning in ventral striatal areas, with this dissociation being spatially mirrored in dopaminergic midbrain. At the time of choice, these segregated signals are integrated in ventral striatum. These findings highlight how the brain parses parallel learning demands. Optimal decision making mandates organisms learn the relevant features of choice options. Likewise, knowing how much effort we should expend can assume paramount importance. A mesolimbic network supports reward learning, but it is unclear whether other choice features, such as effort learning, rely on this same network. Using computational fMRI, we show parallel encoding of effort and reward prediction errors (PEs) within distinct brain regions, with effort PEs expressed in dorsomedial prefrontal cortex and reward PEs in ventral striatum. We show a common mesencephalic origin for these signals evident in overlapping, but spatially dissociable, dopaminergic midbrain regions expressing both types of PE. During action anticipation, reward and effort expectations were integrated in ventral striatum, consistent with a computation of an overall net benefit of a stimulus. Thus, we show that motivationally relevant stimulus features are learned in parallel dopaminergic pathways, with formation of an integrated utility signal at choice.
High fat diet‐induced oxidative stress blocks hepatocyte nuclear factor 4α and leads to hepatic steatosis in mice

Nonalcoholic fatty liver disease (NAFLD) is the most common form of chronic liver disease with manifestation of over‐accumulation of fat in liver. Increasing evidences indicate that NAFLD may be in part caused by malfunction of very low density lipoprotein (VLDL) secretion. Hepatocyte nuclear factor 4α (HNF4α), a nuclear receptor protein, plays an important role in sustain hepatic lipid homeostasis via transcriptional regulation of genes involved in secretion of VLDL, such as apolipoprotein B (ApoB). However, the exact functional change of HNF4α in NAFLD remains to be elucidated. In the present study, we found that high fat diet (HFD) induced cytoplasmic retention of HNF4α in hepatocytes, which led to down‐regulation of hepatic ApoB expression and its protein level in serum, as well as reduced secretion of VLDL. We further revealed that oxidative stress, elevated in fatty liver, was the key factor inducing the cytoplasmic retention of HNF4α in hepatocytes by activating protein kinase C (PKC)‐mediated phosphorylation in HNF4α. Thus, our findings reveal a novel mechanism underlying HFD‐induced fatty liver that oxidative stress impairs function of HNF4α on ApoB expression and VLDL secretion via PKC activation, eventually promoting fat accumulation in the liver. Therefore, oxidative stress/PKC/HNF4α pathway may be a novel target to treat diet‐induced fatty liver.
Regional Socioeconomic Inequalities in Physical Activity and Sedentary Behavior Among Brazilian Adolescents.

BACKGROUND This study aims to describe the regional prevalence and patterns of physical activity (PA) and sedentary behavior among Brazilian adolescents. METHODS Data from the Brazilian Scholar Health Survey, a nationally representative survey of ninth-grade adolescents [mean age: 14.29 y (14.27-14.29)] conducted in 2015 (n = 101,445), were used. Outcomes were television viewing, sitting time (ST), total PA, and active traveling collected via self-administered questionnaire. Information on frequency of physical education classes and type of school was collected from the school's director. Frequencies with 95% confidence intervals were used to determine the prevalence and patterns of outcomes. RESULTS Higher prevalence of PA (≥300 min/wk) and ST (>4 h/d) was found in Midwest (PA = 38.0%; ST = 44.5%), South (PA = 37.6%; ST = 50.1%), and Southeast (PA = 36.1%; ST = 49.3%) compared with Northeast (PA = 29.7%; ST = 36.9%) and North (PA = 34.4%; ST = 34.8%) regions of Brazil. ST was higher among adolescents from private schools (51.5%) than public schools (42.9%), whereas active traveling was greater among students of public schools than private schools (62.0% vs 34.4%). Most inequalities in outcomes between capital and interior cities were in the poorest regions. CONCLUSIONS The results indicate that national plans targeting regional inequalities are needed to improve PA and to reduce sedentary behavior among Brazilian adolescents.
Systematics of moduli stabilisation in Calabi-Yau flux compactifications

We study the large volume limit of the scalar potential in Calabi-Yau flux compactifications of type IIB string theory. Under general circumstances there exists a limit in which the potential approaches zero from below, with an associated non-supersymmetric AdS minimum at exponentially large volume. Both this and its de Sitter uplift are tachyon-free, thereby fixing all K? hler and complex structure moduli. Also, for the class of vacua described in this paper, the gravitino mass is independent of the flux discretuum, whereas the ratio of the string scale to the 4d Planck scale is hierarchically small but flux dependent. The inclusion of ? ' corrections plays a crucial role in the structure of the potential. We illustrate these ideas through explicit computations for a particular Calabi-Yau manifold.
Resilient Coordination of Networked Multiagent Systems Based on Distributed State Emulators

This note studies resilient coordination of networked multiagent systems in the presence of misbehaving agents, i.e., agents that are subject to adversaries modeled as exogenous disturbances. Apart from the existing relevant literature that make specific assumptions on the graph topology and/or the fraction of misbehaving agents, we present an adaptive control architecture based on distributed state emulators and show that the nominal networked multiagent system behavior can be retrieved even if all agents are misbehaving.
Arterial and Venous Pulmonary Vascular Morphology and Their Relationship to Findings in Cardiac Magnetic Resonance Imaging in Smokers

Objective Prior work has described the relationship between pulmonary vascular pruning on computed tomography (CT) scans and metrics of right-sided heart dysfunction in smokers. In this analysis, we sought to look at pruning on a lobar level, as well as examine the effect of the arterial and venous circulation on this association. Methods Automated vessel segmentation applied to noncontrast CT scans from the COPDGene Study in 24 subjects with cardiac magnetic resonance imaging scans was used to create a blood volume distribution profile. These vessels were then manually tracked to their origin and characterized as artery or vein. Results Assessment of pruning on a lobar level revealed associations between pruning and right ventricular function previously not observed on a global level. The right ventricular mass index, the right ventricular end-systolic volume index, and pulmonary arterial-to-aorta ratio were associated with both arterial and venous pruning, whereas right ventricular ejection fraction was associated with only arterial pruning. Conclusions Lobar assessment and segmentation of the parenchymal vasculature into arterial and venous components provide additional information about the relationship between loss of vasculature on CT scans and right ventricular dysfunction.
A Comparison of Near-Infrared Diffuse Optical Imaging and 18F-FDG PET/CT for the Early Prediction of Breast Cancer Response to Neoadjuvant Chemotherapy

In recent years, neoadjuvant chemotherapy (NAC) before surgery has become the standard of care for patients who present with advanced breast cancers or multiple lesions, in order to control distant metastases as well as reduce breast tumor size before surgery (1). The remaining medical oncology challenge is that most patients (.80%) have a positive response to NAC, yet many of these women (;40%–70%) fail to reach a complete pathologic response (pCR) and, therefore, do not realize the gains in diseasefree survival experienced by pCR (1). Thus, imaging breast cancers during the course of NAC offers scientific and clinical value in terms of understanding the biologic changes that occur in complete versus incomplete responses. It also affords the opportunity to develop image-based prognostic biomarkers that could lead to superior individualized treatment and patient care.
Pharmacokinetic and Bioequivalence Studies of Oral Cefuroxime Axetil250 mg Tablets in Healthy Human Subjects

The objective of this study was to determine the bioequivalence of two Cefuroxime oral 250 mg tablet formulation. One was the innovators brand (Zinnat®), was taken as reference brand (REF) and the other was a newly developed, optimized and cost effective formulation (TEST). A single dose, open, random sequence, cross over, two treatment study with a one week washout period in between was carried out in 12 healthy male Pakistani young volunteers. Reference and Test tablets were administered to these volunteers with 150 mL of water after an overnight fast. Blood samples were drawn 15 min prior to the administration of dose and at 0.5, 1, 1.5, 2, 3, 4, 5, 6, 7 and 8 hours post dose. The cefuroxime concentrations in the plasma were determined by a modified, simple HPLC method in which the mobile phase was 10 mM solution of ammonium acetate and acetonitrile, pH was adjusted to 5 ± 0.2 with glacial acetic acid. The wavelength of detection was 254 nm having a flow rate of 1ml/min and the retention time of 5.8 min. The method was validated as per the ICH requirements. Both compartmental and non-compartmental methods were used to determine the various PK parameters such as Cmax. Tmax, AUC0-t, AUC0-∞ , AUMC, MRT, t1/2, Kel, Vd and Cl using Kinetica® ver 4.4. 1 The bioequivalence between the REF and TEST cefuroxime axetil 250mg formulations was established as the Latin square design of ANOVA does not show any significant difference with a p≥0.05 for period and the 90% confidence interval lies within the acceptable range (80-125%) for the log transformed data of Cmax, Tmax, AUC0-t, AUC0-∞, t1/2, AUMC, MRT, Vd and Cl, showing a comparable plasma profiles generated by both the formulations. It is, thus concluded that both the formulations were bioequivalent.
Prevalence, toxin gene profile, antibiotic resistance, and molecular characterization of Clostridium perfringens from diarrheic and non-diarrheic dogs in Korea

Clostridium perfringens causes diarrhea and other diseases in animals and humans. We investigated the prevalence, toxin gene profiles, and antibiotic resistance of C. perfringens isolated from diarrheic dogs (DD) and non-diarrheic dogs (ND) in two animal hospitals in Seoul, Korea. Fecal samples were collected from clinically DD (n = 49) and ND (n = 34). C. perfringens was isolated from 31 of 49 DD (63.3%) and 21 of 34 ND dogs (61.8%). All C. perfringens strains were positive for the α toxin gene, but not for the β, ε, or ι toxin genes; therefore, all strains were identified as type A C. perfringens. All isolates were cpe-negative, whereas the β2 toxin gene was identified in 83.9% and 61.9% of isolates from DD and ND, respectively. Most isolates were susceptible to ampicillin (94%), chloramphenicol (92%), metronidazole (100%), moxifloxacin (96%), and imipenem (100%). However, 25.0% and 21.2% of isolates were resistant to tetracycline and clindamycin, respectively. Molecular subtyping of the isolated strains was performed by using pulsed-field gel electrophoresis. Fifty-two isolates were classified into 48 pulsotypes based on more than 90% similarity of banding patterns. No notable differences were observed among the isolates from DD and ND.
Multipass Target Search in Natural Environments

Consider a disaster scenario where search and rescue workers must search difficult to access buildings during an earthquake or flood. Often, finding survivors a few hours sooner results in a dramatic increase in saved lives, suggesting the use of drones for expedient rescue operations. Entropy can be used to quantify the generation and resolution of uncertainty. When searching for targets, maximizing mutual information of future sensor observations will minimize expected target location uncertainty by minimizing the entropy of the future estimate. Motion planning for multi-target autonomous search requires planning over an area with an imperfect sensor and may require multiple passes, which is hindered by the submodularity property of mutual information. Further, mission duration constraints must be handled accordingly, requiring consideration of the vehicle’s dynamics to generate feasible trajectories and must plan trajectories spanning the entire mission duration, something which most information gathering algorithms are incapable of doing. If unanticipated changes occur in an uncertain environment, new plans must be generated quickly. In addition, planning multipass trajectories requires evaluating path dependent rewards, requiring planning in the space of all previously selected actions, compounding the problem. We present an anytime algorithm for autonomous multipass target search in natural environments. The algorithm is capable of generating long duration dynamically feasible multipass coverage plans that maximize mutual information using a variety of techniques such as ϵ-admissible heuristics to speed up the search. To the authors’ knowledge this is the first attempt at efficiently solving multipass target search problems of such long duration. The proposed algorithm is based on best first branch and bound and is benchmarked against state of the art algorithms adapted to the problem in natural Simplex environments, gathering the most information in the given search time.