Miracle-dz/UniFAR-FTUs huggingface dataset:
6B.6 NEXRAD DIFFERENTIAL REFLECTIVITY CALIBRATION

NCAR (National Center for Atmospheric Research) has been tasked by the Office and Science and Technology (OS&T) of NWS (National Weather Service) to determine the uncertainty of various methods for the calibration of Zdr using S-Pol, NCAR’s S-band polarimetric radar. Three techniques are investigated 1) the vertical pointing (VP) technique, 2) the engineering calibration (EC) technique and 3) the crosspolar power (CP) technique (Hubbert et al. 2003). Uncertainty of measurements is a way to quantify the probability that a measurement (in the present case a calculated calibration factor) lies within some error bounds. Thus, the goal of this this project is to quantify the uncertainty of the estimated Zdr calibration factors determined by each method. Dual polarized radars promise to increase the accuracy of radar rainfall measurements. The copolar differential power measurement, Zdr, as well as the specific differential phase, φdp, contain additional information about the scattering medium that can be used to increase the accuracy of precipitation measurements that are based solely on radar reflectivity. However, to realize this benefit, Zdr should be calibrated to about one tenth of a dB. One widely accepted way to calibrate Zdr is to point the radar dish vertically in light rain and measure Zdr while turning the dish 360 degrees. Since raindrops have no preferred orientation (i.e., distributed uniform randomly in the plane of polarization) 360-degreeintegrated, intrinsic Zdr is zero dB. Thus, any measured non-zero dB Zdr yields the radar system Zdr offset. A second way to calibrate Zdr is with an EC approach based on engineering measurements (Zrnić et al. 2006). The radar transmit and receive paths are divided into “active” and “passive” parts. The gains and losses of the “passive” or “static” parts, i.e. the waveguides and antenna, are measured by using test signals and radiation from the sun. The gain of the active signal path (i.e., receiver chain) is monitored via test signal injection on a continuous basis. Transmit powers are also monitored. By combining the passive and active calibration measurements, the Zdr bias can be estimated. In this paper estimated uncertainty of the three Zdr calibration techniques are given. Issues affecting the
Exploring the Distributional Properties of the Non-Gaussian Random Field Models.

In the environmental modeling field, the exploratory analysis of responses often exhibits spatial correlation as well as some non-Gaussian attributes such as skewness and/or heavy-tailedness. Consequently, we propose a general spatial model based on scale-shape mixtures of the multivariate skew-normal distribution. Intuitively, it incorporates distinct random effects to account for the spatial dependencies not explained by a simple Gaussian random field model. Importantly, the proposed model is capable of generating a wide range of skewness and kurtosis levels. Meanwhile, we demonstrate that the skewness mixing can induce asymmetric tail dependence at sub-asymptotic and/or asymptotic levels.
Changes in Poverty and Inequality in Latin America during the Great Recession 1 1

Poverty is perhaps the most important indicator of social welfare. The World Development Reports of 2000 and 2010 highlighted the prominence of poverty reduction as the main objective of developing economies. The Millenium Development Goals set by the United Nations made of poverty reduction a specific global target to achieve within a precise time frame. Setting goals and targets has induced a global agenda of poverty reduction and important advances have been achieved in the area of poverty reduction. However, economic crises, even though usually shortlived, may derail these objectives. It is been documented that these crises may delay the achievement of poverty reduction targets and may also have ripple effects on other areas of welfare beyond monetary poverty.
Histomorphological Study of Upper GI Endoscopic Biopsies.

Background: Upper Gastrointestinal tract disorders are of the most frequently encountered cases in clinical practices. Endoscopic biopsy is common procedure to establish the diagnosis of different benign and malignant lesion. The biopsy specimen is used for histopathological study to confirm the endoscopic diagnosis in suspected malignancy and to rule out the benign appearing lesions for malignancy. The endoscopic biopsies are also used in monitoring the disease course, recurrence and response to therapy. Objectives: 1. To study the overall frequency, age and sex distribution of various lesion. 2. To study varied spectrum of histopathological lesion both non-neoplastic and neoplastic in patients undergoing upper gastrointestinal biopsy. Materials and Methods: The present study included endoscopic biopsies those were taken from patients, who were clinically diagnosed to have an upper gastrointestinal tract lesion needing biopsy, at the department of gastroenterology; Hi-Tech medical college. The selection of study material was prospective study (September 2012August 2014). Results: Out of the 72 upper GI endoscopic biopsy samples that were studied during the period of two years, 12 (16.66%) were from the oesophagus, 57 (79.17%) from stomach and 3 (4.17%) from duodenum. The highest incidence of upper GI endoscopic lesions was seen between 51-60 years of age. The male to female ratio in the present study was 2.6:1 which indicates male predominance. Conclusion: There is predominance of malignancy compared to non neoplastic lesions in the present study. In patients below 50 years of age the most common lesion was gastritis and in patients more than 50 years of age the most common lesion was gastric malignancies. Endoscopic and histopathologic correlation was achieved in 84.72% of the cases. There is concordance of endoscopic biopsy findings with post biopsy resected specimens.
Reverting ontogeny: rapid phenotypic plasticity of colour vision in cichlid fish

Phenotypic plasticity, particularly during development, allows organisms to rapidly adjust to different environmental conditions. Yet, it is often unclear whether the extent and direction of plastic changes are restricted by an individual's ontogeny. Many species of cichlid fishes go through ontogenetic changes in visual sensitivity, from short to long wavelengths, by switching expression of cone opsin genes crucial for colour vision. During this progression, individuals often exhibit phenotypic plasticity to the ambient light conditions. However, it is commonly assumed that once an adult visual phenotype is reached, reverting to an earlier ontogenetic state with higher sensitivity at shorter wavelengths is not common. In this study, we experimentally demonstrate that four-month-old Midas cichlid fish (Amphilophus astorquii) show plasticity in single cone opsin expression after experiencing drastic changes in light conditions. Resulting shifts of visual sensitivity occurred presumably in an adaptive direction—towards shorter or longer wavelengths when exposed to short- or long-wavelength light, respectively. Single cone opsin expression changed within only a few days and went through a transitional phase of co-expression. When the environment was experimentally enriched in long-wavelength light, the corresponding change occurred gradually along a dorsoventral gradient within the retina. This plasticity allowed individuals to revert earlier ontogenetic changes and return to a more juvenile visual phenotype demonstrating previously unrecognized insights into temporal and spatial dynamics of phenotypic plasticity of the visual system in response to ambient light.
Early animal evolution: a morphologist's view

Two hypotheses for the early radiation of the metazoans are vividly discussed in recent phylogenomic studies, the ‘Porifera-first’ hypothesis, which places the poriferans as the sister group of all other metazoans, and the ‘Ctenophora-first’ hypothesis, which places the ctenophores as the sister group to all other metazoans. It has been suggested that an analysis of morphological characters (including specific molecules) could throw additional light on the controversy, and this is the aim of this paper. Both hypotheses imply independent evolution of nervous systems in Planulozoa and Ctenophora. The Porifera-first hypothesis implies no homoplasies or losses of major characters. The Ctenophora-first hypothesis shows no important synapomorphies of Porifera, Planulozoa and Placozoa. It implies either independent evolution, in Planulozoa and Ctenophora, of a new digestive system with a gut with extracellular digestion, which enables feeding on larger organisms, or the subsequent loss of this new gut in the Poriferans (and the re-evolution of the collar complex). The major losses implied in the Ctenophora-first theory show absolutely no adaptational advantages. Thus, morphology gives very strong support for the Porifera-first hypothesis.
Can a Robot Catch You Lying? A Machine Learning System to Detect Lies During Interactions

Deception is a complex social skill present in human interactions. Many social professions such as teachers, therapists and law enforcement officers leverage on deception detection techniques to support their work activities. Robots with the ability to autonomously detect deception could provide an important aid to human-human and human-robot interactions. The objective of this work is to demonstrate the possibility to develop a lie detection system that could be implemented on robots. To this goal, we focus on human and human robot interaction to understand if there is a difference in the behavior of the participants when lying to a robot or to a human. Participants were shown short movies of robberies and then interrogated by a human and by a humanoid robot “detectives. ” According to the instructions, subjects provided veridical responses to half of the question and false replies to the other half. Behavioral variables such as eye movements, time to respond and eloquence were measured during the task, while personality traits were assessed before experiment initiation. Participant's behavior showed strong similarities during the interaction with the human and the humanoid. Moreover, the behavioral features were used to train and test a lie detection algorithm. The results show that the selected behavioral variables are valid markers of deception both in human-human and in human-robot interactions and could be exploited to effectively enable robots to detect lies.
Mesenchymal Stromal Cell Therapeutic Delivery: Translational Challenges to Clinical Application

For several decades, multipotent mesenchymal stromal cells (MSCs) have been extensively studied for their therapeutic potential across a wide range of diseases. In the preclinical setting, MSCs demonstrate consistent ability to promote tissue healing, down-regulate excessive inflammation and improve outcomes in animal models. Several proposed mechanisms of action have been posited and demonstrated across an array of in vitro models. However, translation into clinical practice has proven considerably more difficult. A number of prominent well-funded late-phase clinical trials have failed, thus calling out for new efforts to optimize product delivery in the clinical setting. In this review, we discuss novel topics critical to the successful translation of MSCs from pre-clinical to clinical applications. In particular, we focus on the major routes of cell delivery, aspects related to hemocompatibility, and potential safety concerns associated with MSC therapy in the different settings.
Biomarkers for Predicting Efficacies of Anti-PD1 Antibodies

Therapeutic options for treating advanced melanoma are progressing rapidly. Although anti-programmed cell death 1 (PD1) antibodies (e.g., nivolumab, pembrolizumab) have been approved as first-line and anchor drugs, respectively, for treating advanced melanoma, the efficacy appears limited as we expected, especially in Asian populations. Biomarkers to predict or evaluate the efficacy of anti-PD1 antibodies are needed to avoid subjecting patients to potentially severe adverse events associated with switching to other anti-melanoma drugs. This review focuses on the recent development of biomarkers for assessing the efficacy of anti-PD1 antibodies using routine blood tests such as the neutrophil-to-lymphocyte ratio, eosinophil ratio, serum markers such as lactate dehydrogenase, programmed cell death ligand 1 (PD-L1) expression on melanoma cells, microsatellite instability and mismatch repair deficiency assays, as well as soluble CD163, and tumor-associated macrophage-related chemokines (e.g., CXCL5, CXCL10).
Layer-Wise Relevance Propagation for Explaining Deep Neural Network Decisions in MRI-Based Alzheimer's Disease Classification

Deep neural networks have led to state-of-the-art results in many medical imaging tasks including Alzheimer's disease (AD) detection based on structural magnetic resonance imaging (MRI) data. However, the network decisions are often perceived as being highly non-transparent, making it difficult to apply these algorithms in clinical routine. In this study, we propose using layer-wise relevance propagation (LRP) to visualize convolutional neural network decisions for AD based on MRI data. Similarly to other visualization methods, LRP produces a heatmap in the input space indicating the importance/relevance of each voxel contributing to the final classification outcome. In contrast to susceptibility maps produced by guided backpropagation (“Which change in voxels would change the outcome most? ”), the LRP method is able to directly highlight positive contributions to the network classification in the input space. In particular, we show that (1) the LRP method is very specific for individuals (“Why does this person have AD? ”) with high inter-patient variability, (2) there is very little relevance for AD in healthy controls and (3) areas that exhibit a lot of relevance correlate well with what is known from literature. To quantify the latter, we compute size-corrected metrics of the summed relevance per brain area, e.g., relevance density or relevance gain. Although these metrics produce very individual “fingerprints” of relevance patterns for AD patients, a lot of importance is put on areas in the temporal lobe including the hippocampus. After discussing several limitations such as sensitivity toward the underlying model and computation parameters, we conclude that LRP might have a high potential to assist clinicians in explaining neural network decisions for diagnosing AD (and potentially other diseases) based on structural MRI data.
Isoproterenol-Induced Cardiac Diastolic Dysfunction in Mice: A Systems Genetics Analysis

We examined an isoproterenol heart failure model across a panel of diverse inbred strains of mice, the Hybrid Mouse Diversity Panel (HMDP), using left atrial (LA) and lung weights as well as echocardiogram parameters as surrogates for cardiac diastolic function. We identified gene transcripts that significantly correlated with diastolic function. In addition, we mapped echocardiographic parameters associated with diastolic function. We identified a locus near Tns3-Hus1 to be associated with baseline E/A ratio in mice (p = 1.65E-06), the syntenic region of which was recently associated with E/A ratio in a genome-wide association study (GWAS) meta-analysis of the EchoGen consortium in humans. We also identified a locus near Cdkn2a-Cdkn2b, which is a region syntenic to the human 9p21 locus, to be associated with week 3 A/E ratio (p = 2.15E-06). Our study is the first study to map diastolic dysfunction in mice, in which a locus was found to be shared with a recent human GWAS on diastolic function. Moreover, our cardiac transcriptome correlation and eQTL analysis generated hypotheses for future basic investigations. These results showed that, although technical and physiological challenges limit diastolic function assessment in mice and humans, future investigations examining the genetic architecture of diastolic function among a diverse mouse population, such as the HMDP, in controlled experimental settings, offer distinct advantages in understanding the genetic determinants of diastolic function.
Art of Learning – An Art-Based Intervention Aimed at Improving Children’s Executive Functions

Executive functions (EFs) can be conceptualized as a mean of behavioral self-regulation, and difficulties with EFs may adversely affect school success, social function, and cognitive and psychological development. Research about EFs and how they are affected by various educational and psychosocial factors is sparse. EFs are of great importance to understand how children can handle the challenges that they meet at various stages of development. There has been an increased focus on programs aimed at improving EFs, either as a primary outcome, or as a supplemental result of a specific activity. In this randomized controlled study, 66 children (31 girls, mean age 7:1 years) were given an arts and culture rich intervention (Art of Learning) aimed at improving EFs. EFs were assessed with the Behavior Rating Inventory of Executive Functioning-teacher version (BRIEF-teacher form) before, immediately after, and 6 months after intervention. Outcome in the intervention group was compared to children from two schools serving as controls (n = 37, 18 girls, mean age 7:3 years). In addition, teachers from intervention schools were also interviewed both individually and in focus groups. The results reveal that both groups improved their EFs, as measured with BRIEF, over time on the global executive composite (GEC) score, the metacognition index, and on behavioral regulation index (BRI). However, the intervention group displayed a significantly greater improvement than the control group on GEC and BRI. The teacher interviews reveal positive effects for the children when it comes to several aspects: collaboration, conflict management, inclusion, vocabulary, and confidence. These factors are regarded as important for EFs development and academic outcome. The results support the notion of best training transfer effects for tasks addressing global executive functioning and specifically behavioral regulation skills (BRI).
Infralimbic Estradiol Enhances Neuronal Excitability and Facilitates Extinction of Cocaine Seeking in Female Rats via a BDNF/TrkB Mechanism

Women are more susceptible to developing cocaine dependence than men, but paradoxically, are more responsive to treatment. The potent estrogen, 17β-estradiol (E2), mediates these effects by augmenting cocaine seeking but also promoting extinction of cocaine seeking through E2’s memory-enhancing functions. Although we have previously shown that E2 facilitates extinction, the neuroanatomical locus of action and underlying mechanisms are unknown. Here we demonstrate that E2 infused directly into the infralimbic-medial prefrontal cortex (IL-mPFC), a region critical for extinction consolidation, enhances extinction of cocaine seeking in ovariectomized (OVX) female rats. Using patch-clamp electrophysiology, we show that E2 may facilitate extinction by potentiating intrinsic excitability of IL-mPFC neurons. Because the mnemonic effects of E2 are known to be regulated by brain-derived neurotrophic factor (BDNF) and its receptor, tropomyosin-related kinase B (TrkB), we examined whether BDNF/TrkB signaling was necessary for E2-induced enhancement of excitability and extinction. We found that E2-mediated increases in excitability of IL-mPFC neurons were abolished by Trk receptor blockade. Moreover, blockade of TrkB signaling impaired E2-facilitated extinction of cocaine seeking in OVX female rats. Thus, E2 enhances IL-mPFC neuronal excitability in a TrkB-dependent manner to support extinction of cocaine seeking. Our findings suggest that pharmacological enhancement of E2 or BDNF/TrkB signaling during extinction-based therapies would improve therapeutic outcome in cocaine-addicted women.
Using Genetically Encoded Voltage Indicators (GEVIs) to Study the Input-Output Transformation of the Mammalian Olfactory Bulb

Genetically encoded voltage indicators (GEVIs) are fluorescent protein reporters of membrane potential. These tools can, in principle, be used to monitor the neural activity of genetically distinct cell types in the brain. Although introduced in 1997, they have been a challenge to use to study intact neural circuits due to a combination of small signal-to-noise ratio, slow kinetics, and poor membrane expression. New strategies have yielded novel GEVIs such as ArcLight, which have improved properties. Here, we compare the in vivo properties of ArcLight with Genetically Encoded Calcium Indicators (GECIs) in the mouse olfactory bulb. We show how voltage imaging can be combined with organic calcium sensitive dyes to measure the input-output transformation of the olfactory bulb. Finally, we demonstrate that ArcLight can be targeted to olfactory bulb interneurons. The olfactory bulb contributes substantially to the perception of the concentration invariance of odor recognition.
Recharge and dynamics of a karst groundwater system in Kakheti (Eastern Georgia)

Abstract Monitoring temporal variations of 18O and 2H isotopes in precipitation, groundwater and surface water was performed in the region of Kakheti (East Georgia). Data were collected from three meteorological stations at altitudes between 400 - 1,100 m a.s. l. , from two shallow and one deep hydrogeological boreholes, and from two surface water monitoring stations (Alazani River and Patmasuri karstic stream). 18O values in precipitation show an annual variation between -22 ‰ and +1 ‰ and a distinct altitude effect. A clear correlation exists between the seasonal isotope composition of precipitation, shallow groundwater and surface water. A five-fold amplitude dampening and a delay of 10-15 days was observed. The data show that precipitation in the Caucasus Mountains to the North infiltrates into the Upper Jurassic - Lower Cretaceous karstic aquifer and travels to the Alazani valley towards south-east. The isotopic signature of winter precipitation is reflected in stream water as well as in shallow groundwater isotope data of groundwater in a 2,000-m-deep hydrogeological borehole at Heretiskari show a distinctly different character with δ18O ranging between -2.8 ‰ to -2.2 ‰ and a deuterium excess of -25 ‰.
Analysis of the Criteria Adopted in Industry to Extract Microservices

A microservice architecture is expected to provide a better modularization and management of small and autonomous services. Other expected benefits include increased availability and time to market. There is a growing interest of both industry and academia on streamlining the migration of existing systems to a microservice architecture. However, the success of this migration is largely dependent on the use of appropriate criteria for extracting microservices from a code base. Recent studies indicate the selection and decomposition of microservices represent the main challenge along the migration. Academic techniques tend to support the extraction of microservices with either one or two conventional criteria, namely coupling and cohesion. There is limited knowledge on the criteria actually considered as useful by practitioners. Thus, we have performed an exploratory online survey with 15 specialists experienced on migrating systems to a microservices architecture. In particular, we question the relative usefulness of seven possible criteria for supporting decision-making along microservice extraction. The participants were also questioned about tools they have used, their limitations, and whether the decisions on extracted microservices were considered unsuccessful. Overall, the survey results suggest academic techniques do not totally satisfy the needs of practitioners. Practitioners often need to consider simultaneously at least four dominant criteria as well as their trade-offs to support their decisions. Most practitioners consider existing tooling support insufficient or even irrelevant to support their microservice extraction decisions.