Miracle-dz/UniFAR-FTUs huggingface dataset:
High-resolution mapping of nitrogen oxide emissions in large US cities from TROPOMI retrievals of tropospheric nitrogen dioxide columns

Abstract. Satellite-derived spatiotemporal patterns of nitrogen oxide (NOx) emissions can improve accuracy of emission inventories to better support air quality and climate research and policy studies. In this study, we develop a new method by coupling the chemical transport Model-Independent SATellite-derived Emission estimation Algorithm for Mixed-sources (MISATEAM) with a divergence method to map high-resolution NOx emissions across US cities using TROPOspheric Monitoring Instrument (TROPOMI) tropospheric nitrogen dioxide (NO2) retrievals. The accuracy of the coupled method is validated through application to synthetic NO2 observations from the NASA-Unified Weather Research and Forecasting (NU-WRF) model, with a horizontal spatial resolution of 4 km × 4 km for 33 large and mid-size US cities. Validation reveals excellent agreement between inferred and NU-WRF-provided emission magnitudes (R= 0.99, normalized mean bias, NMB = −0.01) and a consistent spatial pattern when comparing emissions for individual grid cells (R=0.88±0.06). We then develop a TROPOMI-based database reporting annual emissions for 39 US cities at a horizontal spatial resolution of 0.05° × 0.05° from 2018 to 2021. This database demonstrates a strong correlation (R= 0.90) with the National Emission Inventory (NEI) but reveals some bias (NMB = −0.24). There are noticeable differences in the spatial patterns of emissions in some cities. Our analysis suggests that uncertainties in TROPOMI-based emissions and potential misallocation of emissions and/or missing sources in bottom-up emission inventories both contribute to these differences.
male Zaspilothynnus trilobatus Turner wasps

28 The effective use of prescribed fire in biodiversity conservation is currently inhibited by a 29 limited understanding of fire effects on ecosystem processes such as pollination. Orchids 30 inhabiting fire-prone landscapes are likely to be particularly sensitive because they often 31 exhibit highly specialised pollination systems and provide no reward to pollinators, making 32 them dependent on co-flowering heterospecifics to attract and support pollinators. We 33 investigated the hypothesis that fire-driven changes in the local abundance of rewarding 34 heterospecific flowers influence pollination in two rewardless Australian orchid species, 35 Diuris maculata sensu lato and Caladenia tentaculata . Diuris maculata s.l. is thought to 36 achieve pollination by mimicking papilionoid Fabaceae flowers. Caladenia tentaculata 37 attracts male thynnine wasps through sexual deceit, and these wasps forage on the open-38 access flowers of other taxa. We used a space-for-time substitution design with sites in 39 different stages of post-fire succession where we recorded capsule set in Diuris maculata s.l. , 40 pollinator visitation to Caladenia tentaculata , the floral abundance of rewarding 41 heterospecifics, and abiotic conditions. Many rewarding taxa responded to fire age, but there 42 was only weak evidence that capsule set in D. maculata s.l. was positively related to the local 43 floral abundance of rewarding species. There was evidence of an overriding effect of rainfall 44 on capsule set that may have obscured effects of the floral community. Visitation to C. 45 tentaculata was not positively associated with any rewarding heterospecifics, and was 46 negatively associated with rewarding Burchardia umbellata . Our preliminary findings 47 highlight the need to account for multiple factors when trying to detect fire effects on 48 pollination. 49
Predicting grounding state for adaptive explanation generation in analogical problem-solving

This paper’s main contribution is a Bayesian hierarchical grounding state prediction model implemented in an adaptive explainer agent assisting users with analogical problem-solving. This model lets the agent adapt dialogue moves regarding previously unmentioned domain entities that are similar to the ones already explained when they are instances of the same generalised schema in different domains. Learning such schemata facilitates knowledge transfer between domains and plays an important role in analogical reasoning. An ex-plainer agent should be able to predict to what extent the explainee has learned to induce a schema in order to build up on this in the explanation process and make it more cooperative. This paper describes the approach of hierarchical grounding state prediction, introduces the analogy-based explanation generation process and the agent architecture implemented for this approach, as well as provides some example interactions as the first developers’ evaluation of the system in preparation for upcoming empirical studies.
Using Markov Chain Monte Carlo Inversion to Characterize the Rheology of the Early Hadean Upper Mantle

The early Hadean upper mantle was likely orthopyroxene-dominated, and investigating the rheological properties of this mineral is significant for an understanding of the dynamics of the early mantle. In this work, we apply the Markov chain Monte Carlo (MCMC) inversion method of Mullet et al. (2015) to published laboratory data on the deformation of orthoenstatite aggregates from Bystricky et al. (2016) with the aim of establishing experimental bounds on early Hadean upper mantle rheology. We focus on the two creep tests conducted in the orthoensatite stability field, first performing reanalyses of individual and combined data sets with stresses above 200 MPa for dry dislocation creep deformation mechanisms. We then perform simultaneous inversions for the flow-law parameters of orthoensatite in both dry diffusion creep and dry dislocation creep regimes, showing that composite rheology inversion provides a better fit to the data. Composite inversion yields a median activation energy for dislocation creep of Q 1 = 637 kJ/mol, a median activation energy for diffusion creep of Q 2 = 352 kJ/mol, and a median stress exponent of n = 2.61 in the dislocation creep regime. Our flow-law parameters demonstrate a higher activation energy and a smaller stress exponent for orthoenstatite when compared to the parameters reported by Bystricky et al. (2016). We illustrate the importance of considering both dislocation and diffusion deformation mechanisms when constraining flow-law parameters and emphasize the need for more experimental effort in understanding rheological properties of the Hadean upper mantle, particularly for lower-stress conditions and wet deformation mechanisms.
Landscape of tumor-infiltrating immune cells in human immunogenic cancers:B cells are inversely associated with CD8T cells, but positively correlated with Treg cells

The composition of tumor-infiltrating immune cells may be a strong predictor of cancer treatment responses and survival outcomes. While B cells have been suggested to suppress T cell cytotoxicity in preclinical studies, it has been less understood whether B cells will exert immune-regulatory roles in human cancers. We explored immune cell landscapes in six human immunogenic cancers, including bladder cancer, head and neck cancer, lung adenocarcinoma, lung squamous cell carcinoma, melanoma, and renal cell carcinoma by calculating gene expression patterns of immune cell-specific metagenes in a total of 2951 cancers. We demonstrated that tumor-infiltrating activated B cells was correlated with regulatory T cell (Treg) infiltration, but had an inverse association with activated CD8 T cell infiltration consistently across all six human cancers. Tumors infiltrated by activated B cells (ActB+ tumors) demonstrated an elevated expression of regulatory cytokines and immune checkpoints, compared to tumors without infiltration by activated B cells (ActB-tumors). Activated B infiltration was not significantly associated with survival outcomes. Précis This human cancer tissue analysis showed that tumor infiltration by activated B cells correlates with decreased infiltration by activated CD8 T cells in immunogenic solid tumors, implicating B cell inhibition may enhance T cell-mediated cytotoxicity.
A REVIEW ON COMPLETE NUTRIENT PROFILE OF BANANA FLOWER (MUSA)

Banana blossom or banana male bud are other names for banana flower. It is a substantial dark maroon blossom that grows from the end of a bunch of bananas. Since the flower is a rich source of a class of bioactive compounds, including alkaloids, flavanoids, tannins, vitamins, minerals and phenolic compounds. These pretty flower can be eaten incorporate of different type of food products like –chocolate, cookies, because this type food products shelf life long lasting. In this study, the antioxidant and anti-huperglycemic properties of banana flower from six different Malaysian cultivars –namely, pisang Abu (Musa balbisiana cv p. Abu), pisang Berangan (Musa acuminata cv p. Berangan), pisang Nipah (Musa balbisiana cv p. Nipah), pisang susu (Musa acuminata cv p. Mas). The flower‟s functional characteristics, such as bulk density, oil and water holding capacity, swelling power, and solubility, were also examined. The flower‟s low bulk density revealed that banana flower power could be added to a variety of foods to boost their antioxidant and fibre content. Banana flower many or health benefits prevent diabetes, lower menstrual bleeding, increase the milk production for lactating women, good for gastrointestinal health, helpful in weight loss, prevent ulcer, constipation.
Reducing variance in importance-weighted cross-validation under covariate shift

Covariate shift classification problems can in principle be tackled by importance-weighting of training samples. However, the sampling variance of the risk estimator is often scaled up dramatically by employing such weighting. One of the consequences of this is that during cross-validation -- when the importance-weighted risk is repeatedly estimated -- suboptimal hyperparameter estimates are produced. We study the sampling variance of the importance-weighted risk estimator as a function of the width of the source distribution. We show that introducing a control variate can reduce its sampling variance, which leads to improved regularization parameter estimates when the training data is smaller in scale than the test data.
Challenges of neural interfaces for stroke motor rehabilitation

More than 85% of stroke survivors suffer from different degrees of disability for the rest of their lives. They will require support that can vary from occasional to full time assistance. These conditions are also associated to an enormous economic impact for their families and health care systems. Current rehabilitation treatments have limited efficacy and their long-term effect is controversial. Here we review different challenges related to the design and development of neural interfaces for rehabilitative purposes. We analyze current bibliographic evidence of the effect of neuro-feedback in functional motor rehabilitation of stroke patients. We highlight the potential of these systems to reconnect brain and muscles. We also describe all aspects that should be taken into account to restore motor control. Our aim with this work is to help researchers designing interfaces that demonstrate and validate neuromodulation strategies to enforce a contingent and functional neural linkage between the central and the peripheral nervous system. We thus give clues to design systems that can improve or/and re-activate neuroplastic mechanisms and open a new recovery window for stroke patients.
Spatio-Temporal modelling of Dengue Fever in Zulia state, Venezuela

Over half of the world's population are at risk of infection from dengue fever (Guha-Sapir2005). This viral disease is transmitted by the female Aedes aegypti mosquito and is the major source of human death in the world when compared with any other vector borne disease (Gubler1998a). The first important epidemic of dengue haemorrhagic fever (DHF) in America was reported in Cuba in 1981 and subsequently in Venezuela during 1989 and 1990 (Oletta2006, Brightmer1998). There has been a trend of increased incidence in many Central and South American countries since 1990 - Brazil, Venezuela, Honduras and Mexico (SanMartin2010) with Venezuela having the highest number of cases of DHF. The urgent need for more effective public health measures to combat this disease in Venezuela drove the decision to undertake the work described in this dissertation. Spatio-Temporal modelling has been developed for the prediction of the occurrence of dengue fever in Zulia state, Venezuela. A systematic approach has been adopted to validate this tool. At the first stage of the analysis an exploratory study was performed to underline the most significant features of the dynamics of incidence rates of dengue fever from 2002 to 2008. In the second stage a Generalized Linear Model (GLM) approach was used in the form of Negative Binomial Generalized Linear Mixed model (GLMM) to compare Relative Risk (RR) across exposure groups by age and sex, using an epidemiological dataset covering the whole of Zulia State, Venezuela. This approach used both a frequentist and a Bayesian perspective for comparative purposes of both outcomes and methodologies. Finally a Spatio-Temporal model was constructed based on Generalized Additive Mixed model (GAMM) framework because the earlier analysis identified a complex association between covariates and response variables. This GAMM structure was further developed so that it could be used to help predict future outbreaks of the disease in Zulia state with a good degree of accuracy.
Advances in Mobile Mapping Technology

Foreword: Advances in mobile mapping technology C.V. Tao and J. Li Part 1 Terrestrial and airborne mobile mapping systems Digital mobile mapping systems-state of the art and future trends K.P. Schwarz and N. El-Sheimy GEOVAN: The mobile mapping system from the Cartographic Institute of Catalonia J. Talaya, E. Bosch, R. Alamus, A. Serra and A. Baron ORTHOROAD: A low cost mobile mapping system for road mapping G. Artese A mobile mapping system for road data capture via a single camera H. Gontran, J. Skaloud and P.-Y. Gillieron Airborne remote sensing supporting traffic flow estimation D.A. Grejner-Brzezinska, C.K. Toth and E. Paska Part 2 Multi-sensor integration Performance analysis of integrated IMU/DGPS systems for mobile mapping systems A.W. L. Ip, N. El-Sheimy and M.M. R. Mostafa Appearance based positioning in urban environments using Kalman filtering L. Paletta, R. Wack, G. Paar, G. Ogris and C. Le Gal Multi-sensor systems for pedestrian navigation and guidance services G. Retscher Integrated technologies for augmented reality applications A. Kealy and S. Scott-Young Part 3 Image processing and object extraction Constrained bundle adjustment of panoramic stereo images for Mars landing site mapping K. Di, F. Xu and R. Li Vehicle classification from LiDAR data to support traffic flow estimates C.K. Toth and D.A. Grejner-Brzezinska Extraction of streets in dense urban areas from segmented LiDAR data X. Hu, C.V. Tao and Y. Hu Semi-automated extraction of urban highway intersections from IKONOS imagery H. Dong, J. Li and M.A. Chapman Part 4 Mobile GIS and distributed GIS Mobile GIS-based navigation guide B. Huang, C. Xie and S.Y. Loh Framework for multi-risk emergency response S. Zlatanova, D. Holweg and M. Stratakis
Epidemiology of Maternal Nutritional Status and Risk of Adverse Birth Outcomes in Undernourished Mothers with Sickle Cell Disease: A Systematic Review and Meta-Analysis Protocol

In pregnancies complicated by sickle cell disease (SCD), the maternal-fetal dyad is at high risk for mortality and morbidity. In healthy pregnancies, maternal nutritional status is a critical factor for the healthy growth and development of the fetus. However, there are no reviews of the current research on the nutritional status of pregnant women with SCD and pregnancy outcomes. First, we aim to assess the burden of malnutrition in pregnant women with SCD. Next, we aim to systematically evaluate if pregnant women with SCD who have poor nutritional status are at increased risk for adverse birth outcomes compared to pregnant women with sickle cell disease and normal nutritional status. We will systematically search multiple electronic databases. Our exposure is pregnant women with SCD and poor nutritional status. The primary outcomes of interest include low birth weight (categorical) and birth weight z-scores (continuous). We will also evaluate maternal and perinatal outcomes as secondary outcomes. We will evaluate the risk of bias and overall certainty of evidence with Risk of Bias in Non-randomized Studies—of Interventions (ROBINS-I), and the overall evidence will be assessed using Grading of Recommendation Assessment, Development, and Evaluation (GRADE) criteria. We will pool findings with a meta-analysis if sufficient homogeneity exists among studies. Findings will be published in a peer-reviewed journal and disseminated to SCD advocacy groups. PROSPERO registration number: 429412.
Implementation of MEC-Assisted Collective Perception in an Integrated Artery/Simu5G Simulation Framework

Advanced vehicle-to-everything (V2X) safety applications must operate with ultra-low latency and be highly reliable. Therefore, they require sophisticated supporting technologies. This is especially true for cooperative applications, such as Collective Perception (CP), where a large amount of data constantly flows among vehicles and between vehicles and a network intelligence server. Both low and high-level support is needed for such an operation, meaning that various access technologies and other architectural elements also need to incorporate features enabling the effective use of V2X applications with strict requirements. The new 5G core architecture promises even more supporting technologies, like Multi-access Edge Computing (MEC). To test the performance of these technologies, an integrated framework for V2X simulations with 5G network elements is proposed in the form of combining Simu5G, a standalone 5G implementation, with the go-to V2X-simulator, Artery. As a first step toward a fully functional MEC-assisted CP Service, an extension to Simu5G’s edge implementation is introduced. The edge application is responsible for dispatching the Collective Perception Messages generated by the vehicles via the 5G connectivity so that a MEC server provided by the network can process incoming data. Simulation results prove the operability of the proposed integrated system and edge computing’s potential in assisting V2X scenarios.
Impact of acidic beverages on esthetic restorations concerning microhardness and color stability: a comparative assessment

Recently, the focus has been placed on esthetic restorations by both clinicians and subjects. With the intake of acidic beverages popular these days, erosive wear of the esthetic restoration results in discoloration, raising a concern and affecting the cost. The objective of the current research was to assess how acidic drinks affected the microhardness and color stability of several esthetic restorative materials. 120 samples were split into three groups of 40 individuals. Each Group I had organically modified ceramics (ORMOCER), Group II had nanoceramics, and Group III had microhybrid composite restorations. The samples were made from the aluminum cylindrical mold of 5mm depth and 10mm diameter, followed by immersion in 25ml acidic beverages (Pepsi) for 10 minutes for 20 days. Microhardness was then assessed using a Vickers diamond intender for each sample on the 10th and 20th day. At baseline, mean hardness was 58.12±1.74, 60.06±0.36, and 63.22±0.44, respectively, for ormocer, nanoceramics, and microhybrid composite. It was seen that the microhardness was higher for the microhybrid composite. However, the difference was statistically non-significant between the three groups with p=0.864. Microhardness on the 10th day was highest for the microhybrid composite, followed by nanoceramics and ormocer (p= 0.001). However, on the 20th day, the difference was statistically non-significant between the three groups. The study, considering its limitations, concludes that the finest behavior and microhardness are associated with organically modified ceramics after immersion in acidic beverages. Nanoceramics showed the second-best behavior, and microhybrid composite resins were the least among the three.
Comparison of the respiratory effects of commonly utilized general anaesthesia regimes in male Sprague-Dawley rats

Background: Respiratory parameters in experimental animals are often characterised under general anaesthesia. However, anaesthesia regimes may alter the functional and mechanical properties of the respiratory system. While most anaesthesia regimes have been shown to affect the respiratory system, the effects of general anaesthesia protocols commonly used in animal models on lung function have not been systematically compared. Methods: The present study comprised 40 male Sprague-Dawley rats divided into five groups (N = 8 in each) according to anaesthesia regime applied: intravenous (iv) Na-pentobarbital, intraperitoneal (ip) ketamine-xylazine, iv propofol-fentanyl, inhaled sevoflurane, and ip urethane. All drugs were administered at commonly used doses. End-expiratory lung volume (EELV), airway resistance (Raw) and tissue mechanics were measured in addition to arterial blood gas parameters during mechanical ventilation while maintaining positive end-expiratory pressure (PEEP) values of 0, 3, and 6 cm H2O. Respiratory mechanics were also measured during iv methacholine (MCh) challenges to assess bronchial responsiveness. Results: While PEEP influenced baseline respiratory mechanics, EELV and blood gas parameters (p < 0.001), no between-group differences were observed (p > 0.10). Conversely, significantly lower doses of MCh were required to achieve the same elevation in Raw under ketamine-xylazine anaesthesia compared to the other groups. Conclusion: In the most frequent rodent model of respiratory disorders, no differences in baseline respiratory mechanics or function were observed between commonly used anaesthesia regimes. Bronchial hyperresponsiveness in response to ketamine-xylazine anaesthesia should be considered when designing experiments using this regime. The findings of the present study indicate commonly used anaesthetic regimes allow fair comparison of respiratory mechanics in experimental animals undergoing any of the examined anaesthesia protocols.
First serological and molecular investigation of hepatitis E virus infection in dromedary camels in Algeria

Hepatitis E is an acute self-limited or fulminant infection in humans, caused by the hepatitis E virus (HEV). This member of the Hepeviridae family has been identified in a wide range of domestic and wild animals all over the world, with a possible transmission to humans through fecal oral route, direct contact and ingestion of contaminated meat products, making it one of the global zoonotic and public health major concerns. Since there is no monitoring program and a lack of data on HEV in animals in Algeria, the current preliminary survey has been undertaken to elucidate the exposure to the virus in camels at abattoirs of six southern provinces of Algeria. Two-hundred and eight sera/plasma were collected and analyzed (by double antigen sandwich ELISA) for the presence of total anti-HEV antibodies, among which 35.1% were positive, but no HEV RNA could be isolated from them (by two pan-HEV nested RT-PCR and broad range real-time reverse transcription RT-PCR). The univariate analysis showed significant associations (p < 0.05) between HEV seroprevalence and province of origin, age, and sex of camels, whereas the multivariable logistic regression analysis revealed a negative impact of camels’ age on it. The obtained results confirm that HEV infection is widespread established in the camelid population of Algeria.