Miracle-dz/UniFAR-FTUs huggingface dataset:
Synergistic Effect of Water-Soluble Hydroxylated Multi-Wall Carbon Nanotubes and Graphene Nanoribbons Coupled with Tetra Butyl Ammonium Bromide on Kinetics of Carbon Dioxide Hydrate Formation

In this work, the thermodynamics and kinetics of hydrate formation in 9.01 wt% tetra butyl ammonium bromide (TBAB) mixed with water-soluble hydroxylated multi-wall carbon nanotube (MWCNTol) systems were characterized by measuring hydrate formation conditions, induction time, and final gas consumption. The results showed that MWCNTols had little effect on the phase equilibrium of CO2 hydrate formation. Nanoparticles (graphene nanoribbons (GNs) and MWCNTols) could significantly shorten the induction time. When the concentration was ≤0.06 wt%, MWCNTols had a better effect on the induction time than the GN system, and the maximum reduction in induction time reached 44.22%. The large surface area of MWCNTols could provide sites for heterogeneous nucleation, thus shortening the induction time of hydrate formation. Furthermore, adding different concentrations of nanoparticles to the 9.01 wt% TBAB solution effectively increased the final gas consumption, and the maximum increase was 10.44% of the 9.01 wt% TBAB + 0.08 wt% GN system. Meanwhile, the suitable initial pressure and experimental temperature could also promote the hydrate formation and increase the motivation in hydrate formation. The 9.01 wt% TBAB + 0.02 wt% MWCNTol system had the best effect at 3.5 MPa and 277.15 K. The induction time was reduced by 66.67% and the final gas consumption was increased by 284.11% compared to those of the same system but at a different initial pressure and experimental temperature. This work helps to promote the industrial application of hydrate technology in CO2 capture and storage.
Detecting post- ﬁ re salvage logging from Landsat change maps and national ﬁ re survey data Remote Sensing of Environment

In Canadian boreal forests, wild ﬁ re is the predominant agent of natural disturbance often with millions of hectares burning annually. In addition to ﬁ re, nearly one quarter of Canada's boreal forest is also managed for industrial wood production. Post- ﬁ re logging (or salvage harvesting) is increasingly used to minimize economic losses from ﬁ re, notwithstanding that the ecological impacts of successive disturbance events remain poorly understood. Improved monitoring and management of post- ﬁ re environments will require new information regarding the location and timing of past operations. In this paper we present and evaluate a data integration approach for detecting spatial and temporal trends in post- ﬁ re logging. Here we utilize a series of maps relating timing and extent of burned area (from the Canadian Large Fire Database) and year of harvest (from Landsat change detection) to identify occurrences of post- ﬁ re logging between 1987 and 2008 for a portion of boreal forest located in central Saskatchewan, Canada. Using a design-based, strati ﬁ ed random sampling framework we found that 68% (95% con ﬁ dence interval (CI) [53 to 84%]) of the detected post- ﬁ re logging was correctly classi ﬁ ed, such that both ﬁ re and clearcutting disturbances were positively veri ﬁ ed by the reference data. The majority of map error resulted from spectral confusion between harvested areas and rock outcroppings exposed by ﬁ re and from mislabeling harvested unburned islands as post- ﬁ re logging. To add further con ﬁ dence to our classi ﬁ cation accuracy, we also found that mapped post- ﬁ re logging displayed similar temporal trends over a ten year period as salvage volume reported for a forest management area partially contained within the study area. Based upon the signi ﬁ cant relationship between these esti- mates (r=0.97, p b 0.001) and the good degree of observed map accuracy, we believe that the presented approach offers a viable and ﬂ exible option for characterizing the spatial and temporal dynamics of post- ﬁ re logging in boreal forests. Maps which reliably identify areas of post- ﬁ re logging stand to improve our capacity to manage and model the ecological impacts associated with multiple disturbance events. Published by Elsevier Inc.
Remote Sensing of Environment

Quantifying ecosystem carbon fluxes and stocks is essential for better understanding the global carbon cycle and improving projections of the carbon-climate feedbacks. Remote sensing has played a vital role in this endeavor during the last five decades by quantifying carbon fluxes and stocks. The availability of satellite observations of the land surface since the 1970s, particularly the early 1980s, has made it feasible to quantify ecosystem carbon fluxes and stocks at regional to global scales. Here we provide a review of the advances in remote sensing of the terrestrial carbon cycle from the early 1970s to present. First, we present an overview of the terrestrial carbon cycle and remote sensing of carbon fluxes and stocks. Remote sensing data acquired in a broad wavelength range (visible, infrared, and microwave) of the electromagnetic spectrum have been used to estimate carbon fluxes and/or stocks. Second, we provide a historical overview of the key milestones in remote sensing of the terrestrial carbon cycle. Third, we review the platforms/sensors, methods, findings, and challenges in remote sensing of carbon fluxes. The remote sensing data and techniques used to quantify carbon fluxes include vegetation indices, light use efficiency models, terrestrial biosphere models, data-driven (or machine learning) approaches, solarinduced chlorophyll fluorescence (SIF), land surface temperature, and atmospheric inversions. Fourth, we review the platforms/sensors, methods, findings, and challenges in passive optical, microwave, and lidar remote sensing of biomass carbon stocks as well as remote sensing of soil organic carbon. Fifth, we review the progresses in remote sensing of disturbance impacts on the carbon cycle. Sixth, we also discuss the uncertainty and validation of the resulting carbon flux and stock estimates. Finally, we offer a forward-looking perspective and insights for future research and directions in remote sensing of the terrestrial carbon cycle. Remote sensing is anticipated to play an increasingly important role in carbon cycling studies in the future. This comprehensive and insightful review on 50 years of remote sensing of the terrestrial carbon cycle is timely and valuable and can benefit scientists in various research communities (e.g., carbon cycle, remote sensing, climate change, ecology) and inform ecosystem and carbon management, carbon-climate projections, and climate policymaking. https://doi.org/10.1016/j.rse. 2019.111383 Received 9 January 2019; Received in revised form 10 August 2019; Accepted 20 August 2019 ⁎ Corresponding author. E-mail address: j.xiao@unh.edu (J. Xiao). Remote Sensing of Environment 233 (2019) 111383 0034-4257/ © 2019 Elsevier Inc. All rights reserved. T
Remote Sensing of Environment

We developed the Function of mask (Fmask) 4.0 algorithm for automated cloud and cloud shadow detection in Landsats 4–8 and Sentinel-2 images. Three major innovative improvements were made as follows: (1) integration of auxiliary data, where Global Surface Water Occurrence (GSWO) data was used to improve the separation of land and water, and a global Digital Elevation Model (DEM) was used to normalize thermal and cirrus bands; (2) development of new cloud probabilities, in which a Haze Optimized Transformation (HOT)-based cloud probability was designed to replace temperature probability for Sentinel-2 images, and cloud probabilities were combined and re-calibrated for different sensors against a global reference dataset; and (3) utilization of spectralcontextual features, where a Spectral-Contextual Snow Index (SCSI) was created for better distinguishing snow/ ice from clouds in polar regions, and a morphology-based approach was applied to reduce the commission error in bright land surfaces (e.g., urban/built-up and mountain snow/ice). The Fmask 4.0 algorithm showed higher overall accuracies for Landsats 4–8 imagery than the 3.3 version (Zhu et al., 2015) (92.40% versus 90.73% for Landsats 4–7 and 94.59% versus 93.30% for Landsat 8), and much higher overall accuracies for Sentinel-2 imagery than the 2.5. 5 version of the Sen2Cor algorithm (Müller-Wilm et al., 2018) (94.30% versus 87.10%).
Remote Sensing of Environment

Accurate delineation of global built-up area (BUA) is fundamental to a better understanding of human development and the impacts on global environmental change. Existing global datasets of human settlement were mostly generated at medium and coarse spatial resolutions, including BUA and other impervious surfaces. With multiple high-resolution satellite constellations now available (e.g., ZiYuan-3 (ZY3), SPOT-5/6/7, Cartosat-1/2, and WorldView-2/3), identifying the global BUA explicitly from the complex landscapes becomes possible. In this study, a novel method was proposed for automated extraction of BUA at the global scale, by fusing a series of building features. Specifically, two planar features, the Morphological Building Index (MBI) and Harris corner detector, were employed to characterize the structure and corner attributes of buildings. Moreover, two multiangular built-up indices (MABIs), i.e., Ratio Multi-angular Built-up Index (RMABI) and Normalized Difference Multi-angular Built-up Index (NDMABI), were proposed to represent the vertical properties of buildings based on multi-view images, which can further complement the planar features. 45 global cities were selected to validate the performance of the proposed method with images acquired by the ZY3 satellite constellation. The results show that the fusion of MBI and Harris corner can achieve satisfactory accuracy, i.e., 91.12%, 88.85%, 82.82% and 0.85, for the average overall accuracy (OA), user's accuracy (UA), producer's accuracy (PA), and F1-score, respectively, for all the test cities. After fusing the MABIs with the planar features, the average OA, UA, PA and F values of the final results were 92.00%, 86.20%, 89.14% and 0.87 for the RMABI, and 91.83%, 85.51%, 89.62% and 0.87 for the NDMABI, respectively. In particular, addition of the MABIs can further reduce the omission errors where medium/high rise buildings with low local contrast exist. We compared our results with two existing state-of-the-art global BUA products, Global Human Settlement Layer (GHSL) and Global Urban Footprint (GUF), which further corroborated the effectiveness of our method.
A neural model of information virality

Information sharing is an integral part of human interaction that serves to build social relationships and affects attitudes and behaviors in individuals and large groups. We present a unifying neurocognitive framework of mechanisms underlying information sharing at scale (virality). We argue that expectations regarding self-related and social consequences of sharing (e.g., in the form of potential for self-enhancement or social approval) are integrated into a domain-general value signal that encodes the value of sharing a piece of information. This value signal translates into population-level virality. In two studies ( n = 41 and 39 participants), we tested these hypotheses using functional neuroimaging. Neural activity in response to 80 New York Times articles was observed in theory-driven regions of interest associated with value, self, and social cognitions. This activity then was linked to objectively logged population-level data encompassing n = 117,611 internet shares of the articles. In both studies, activity in neural regions associated with self-related and social cognition was indirectly related to population-level sharing through increased neural activation in the brain ’ s value system. Neural activity further predicted population-level outcomes over and above the variance explained by article characteristics and commonly used self-report measures of sharing intentions. This parsimonious framework may help advance theory, improve predictive models, and inform new approaches to effective intervention. More broadly, these data shed light on the core functions of sharing — to express ourselves in positive ways and to strengthen our social bonds.
From Immigrants to Americans: The Rise and Fall of Fitting In

Chapter 1 Introduction Chapter 2 Chapter 1: An Immigrant's Decision Chapter 3 Chapter 2: A Historical View of Immigration to the United States Chapter 4 Chapter 3: Fitting in Economically Chapter 5 Chapter 4: Fitting in Linguistically Chapter 6 Chapter 5: Fitting in Officially Chapter 7 Chapter 6: Fitting into the Neighborhood Chapter 8 Chapter 7: Joining the Family
Psychological Experiences in Women with Polycystic Ovary Syndrome: A Qualitative Study

Background: Polycystic Ovary Syndrome (PCOS) is the most common endocrine disorder among women of reproductive years. In addition to multiple physical problems, this syndrome has many psychological complications. Thus, the present study attempted to explore the psychological experiences of women with PCOS in Iran's sociocultural context. Materials and Methods: The study was carried out in Isfahan, Iran, using a qualitative content analysis method. The participants were selected through purposive sampling from women with PCOS, their spouses, and healthcare providers in hospitals, clinics, workplaces, universities, and physicians' offices between September 2018 and November 2019. Data collection was performed through semi-structured interviews until data saturation. Data analysis was based on conventional content analysis. The interviews were transcribed and coded. Afterward, categories and concepts were extracted by grouping similar codes. Results: A total of 13 women with PCOS, four spouses, and 13 healthcare providers participated in this study. Data analysis yielded five main categories, including the patient's psychological reactions following infertility and its probability, psychological issues following menstrual disorders, patients' fear and concerns about the probability of developing chronic diseases, psychological problems following the disease, and psychological problems resulting from body appearance. Conclusions: The results of this study showed that women with PCOS were exposed to multiple psychological problems. Therefore, preventing and controlling the psychological consequences of PCOS and its complications requires healthcare providers' support and comprehensive and long-term planning to promote the mental health of these women.
Inverse Kinematics using Quaternions

In this project I describe the status of inverse kinematics research, with the focus ﬁrmly on the methods that solve the core problem. An overview of the diﬀerent methods are presented Three common methods used in inverse kinematics computation have been chosen as subject for closer inspection. The three methods are described in some detail. An analysis is performed where the three methods are compared, and benchmarked against each other. I conclude which of the methods are the most promising and what their respective forces, weaknesses and prospects are. All ﬁgures shown are made using the test suite, developed in this project and in [4]. Source code developed for this project includes the CCD method , improvements on the BFGS method and Jacobian inverse originally developed in [4]. 1
Evaluation of XPath queries against XML streams

XML is nowadays the de facto standard for electronic data interchange on the Web. Available XML data ranges from small Web pages to ever-growing repositories of, e.g., biological and astronomical data, and even to rapidly changing and possibly unbounded streams, as used in Web data integration and publish-subscribe systems. Animated by the ubiquity of XML data, the basic task of XML querying is becoming of great theoretical and practical importance. The last years witnessed efforts as well from practitioners, as also from theoreticians towards defining an appropriate XML query language. At the core of this common effort has been identified a navigational approach for information localization in XML data, comprised in a practical and simple query language called XPath. This work brings together the two aforementioned ``worlds'', i.e., the XPath query evaluation and the XML data streams, and shows as well theoretical as also practical relevance of this fusion. Its relevance can not be subsumed by traditional database management systems, because the latter are not designed for rapid and continuous loading of individual data items, and do not directly support the continuous queries that are typical for stream applications. The first central contribution of this work consists in the definition and the theoretical investigation of three term rewriting systems to rewrite queries with reverse predicates, like parent or ancestor, into equivalent forward queries, i.e., queries without reverse predicates. Our rewriting approach is vital to the evaluation of queries with reverse predicates against unbounded XML streams, because neither the storage of past fragments of the stream, nor several stream traversals, as required by the evaluation of reverse predicates, are affordable. Beyond their declared main purpose of providing equivalences between queries with reverse predicates and forward queries, the applications of our rewriting systems shed light on other query language properties, like the expressivity of some of its fragments, the query minimization, or even the complexity of query evaluation. For example, using these systems, one can rewrite any graph query into an equivalent forward forest query. The second main contribution consists in a streamed and progressive evaluation strategy of forward queries against XML streams. The evaluation is specified using compositions of so-called stream processing functions, and is implemented using networks of deterministic pushdown transducers. The complexity of this evaluation strategy is polynomial in both the query and the data sizes for forward forest queries and even for a large fragment of graph queries. The third central contribution consists in two real monitoring applications that use directly the results of this work: the monitoring of processes running on UNIX computers, and a system for providing graphically real-time traffic and travel information, as broadcasted within ubiquitous radio signals.
Perspective on the Role of Gut Microbiome in the Treatment of Hepatocellular Carcinoma with Immune Checkpoint Inhibitors

Background and Objectives: Hepatocellular carcinoma (HCC) is the leading cause of liver cancer worldwide and has a high mortality rate. Its incidence has increased due to metabolic-associated liver disease (MAFLD) epidemics. Liver transplantation and surgery remain the most resolute measures. Despite the optimistic use of multi-kinase inhibitors, namely sorafenib, the co-existence of chronic liver disease made the response rate low in these patients. Immune checkpoint inhibitors (ICIs) have become a promising hope for certain advanced solid tumors and, also, for advanced HCC. Unfortunately, a large cohort of patients with HCC fail to respond to immunotherapy. Materials and Methods: We conducted a narrative search on the main medical databases for original articles, reviews, meta-analyses, randomized clinical trials, and case series using the following keywords and acronyms and their associations: hepatocellular carcinoma, immunotherapy, checkpoint inhibitors, gut microbiota, and fecal microbiota transplantation. Results: ICIs are a promising and sufficiently safe treatment option for HCC. In detail, they have significantly improved survival and prognosis in these patients vs. sorafenib. Although there are several highlighted mechanisms of resistance, the gut microbiota signature can be used both as a response biomarker and as an effect enhancer. Practically, probiotic dose-finding and fecal microbiota transplantation are the weapons that can be used to increase ICI’s treatment-response-reducing resistance mechanisms. Conclusion: Immunotherapy has been a significant step-up in HCC treatment, and gut microbiota modulation is an effective liaison to increase its efficacy.
Innovative Approach and Model for Arabic Curriculum Development in The Society 5.0 Era

This study aims to describe approaches and models of Arabic curriculum development relevant to the era of Society 5.0. This research uses a qualitative-descriptive system with a literature study method. The results of this study found that the use of the STEAM approach and SAR (Systematic Action Research) development model are relevant to be used in developing the Arabic curriculum in the era of Society 5.0. Integrating an innovative Arabic curriculum through the STEAM approach and the SAR development model can actively motivate students, increase their interest in learning, and produce skills relevant to the demands of an increasingly technologically advanced society. These findings contribute to developing an Arabic curriculum that is more relevant to the needs of learners in the era of Society 5.0. This STEAM-based SAR model can guide educators in facing the challenges and opportunities that exist in developing Arabic learning that is adaptive and responsive to social and technological changes
Potential-field geophysical software for the PC, version 2.2

This report is preliminary and has not been reviewed for conformity with U.S. Geological Survey standards or stratigraphic nomenclature. Any use of trade names is for descriptive purposes only and does not imply endorsement by the U.S. Geological Survey. Although these programs and data have been used by the U.S. Geological Survey, no warranty, expressed or implied, is made by the USGS as to the accuracy and completeness of the data nor the accuracy and functioning of the programs and related program material, nor shall the fact of distribution constitute any such warranty, and no responsibility is assumed by the USGS in connection therewith.
Role of Hydrogen Sulfide in Inflammatory Bowel Disease

Hydrogen sulfide (H2S), originally known as toxic gas, has now attracted attention as one of the gasotransmitters involved in many reactions in the human body. H2S has been assumed to play a role in the pathogenesis of many chronic diseases, of which the exact pathogenesis remains unknown. One of them is inflammatory bowel disease (IBD), a chronic intestinal disease subclassified as Crohn’s disease (CD) and ulcerative colitis (UC). Any change in the amount of H2S seems to be linked to inflammation in this illness. These changes can be brought about by alterations in the microbiota, in the endogenous metabolism of H2S and in the diet. As both too little and too much H2S drive inflammation, a balanced level is needed for intestinal health. The aim of this review is to summarize the available literature published until June 2023 in order to provide an overview of the current knowledge of the connection between H2S and IBD.