Miracle-dz/UniFAR-FTUs huggingface dataset:
COVID-19 Data Utilization in North Carolina: Qualitative Analysis of Stakeholder Experiences

Background As the world faced the pandemic caused by the novel coronavirus disease 2019 (COVID-19), medical professionals, technologists, community leaders, and policy makers sought to understand how best to leverage data for public health surveillance and community education. With this complex public health problem, North Carolinians relied on data from state, federal, and global health organizations to increase their understanding of the pandemic and guide decision-making. Objective We aimed to describe the role that stakeholders involved in COVID-19–related data played in managing the pandemic in North Carolina. The study investigated the processes used by organizations throughout the state in using, collecting, and reporting COVID-19 data. Methods We used an exploratory qualitative study design to investigate North Carolina’s COVID-19 data collection efforts. To better understand these processes, key informant interviews were conducted with employees from organizations that collected COVID-19 data across the state. We developed an interview guide, and open-ended semistructured interviews were conducted during the period from June through November 2020. Interviews lasted between 30 and 45 minutes and were conducted by data scientists by videoconference. Data were subsequently analyzed using qualitative data analysis software. Results Results indicated that electronic health records were primary sources of COVID-19 data. Often, data were also used to create dashboards to inform the public or other health professionals, to aid in decision-making, or for reporting purposes. Cross-sector collaboration was cited as a major success. Consistency among metrics and data definitions, data collection processes, and contact tracing were cited as challenges. Conclusions Findings suggest that, during future outbreaks, organizations across regions could benefit from data centralization and data governance. Data should be publicly accessible and in a user-friendly format. Additionally, established cross-sector collaboration networks are demonstrably beneficial for public health professionals across the state as these established relationships facilitate a rapid response to evolving public health challenges.
Effects of Exercise Training on Cardiopulmonary Function and Quality of Life in Elderly Patients with Pulmonary Fibrosis: A Meta-Analysis

(1) Objective: Our objective was to conduct a meta-analysis of randomized controlled trials that have evaluated the benefits of exercise training for elderly pulmonary fibrosis (PF) patients. (2) Methods: Studies in either English or Chinese were retrieved from the China National Knowledge Infrastructure (CNKI) and the Wanfang, PubMed, Web of Science and SPORTDiscus databases from inception until the first week of April 2021. Age, body mass index (BMI), and exercise frequency, intensity, type, and duration were considered for each participant. The specific data recorded were the six-minute walk distance (6MWD), maximal rate of oxygen consumption (peak VO2), predicted forced vital capacity (FVC% pred), predicted diffusing capacity of the lung for carbon monoxide (DLCO% pred), predicted total lung capacity (TLC% pred), St. George’s respiratory questionnaire (SGRQ) total score and a modified medical research council score (mMRC). (3) Results: Thirteen studies comprised this meta-analysis (eleven randomized controlled trials and two prospective studies design), wherein 335 patients were exercised and 334 were controls. The results showed that exercise training increased the 6MWD (Cohen’s d = 0.77, MD = 34.04 (95% CI, 26.50–41.58), p < 0.01), peak VO2 (Cohen’s d = 0.45, MD = 1.13 (95% CI, 0.45–1.82), p = 0.0001) and FVC% pred (Cohen’s d = 0.42, MD = 3.94 (95% CI, 0.91–6.96), p = 0.01). However, exercise training reduced scores for the SGRQ (Cohen’s d = 0.89, MD = −8.79 (95% CI, −10.37 to −7.21), p < 0.01) and the mMRC (Cohen’s d = 0.64, MD = −0.58 (95% CI, −0.79 to −0.36), p < 0.01). In contrast, exercise training could not increase DLCO% pred (Cohen’s d = 0.16, MD = 1.86 (95% CI, −0.37–4.09), p = 0.10) and TLC% pred (Cohen’s d = 0.02, MD = 0.07 (95% CI, −6.53–6.67), p = 0.98). Subgroup analysis showed significant differences in frequency, intensity, type, and age in the 6MWD results (p < 0.05), which were higher with low frequency, moderate intensity, aerobic–resistance–flexibility–breathing exercises and age ≤ 70. Meanwhile, the subgroup analysis showed significant differences in exercise intensity and types in the mMRC results (p < 0.05), which were lower with moderate intensity and aerobic–resistance exercises. (4) Conclusions: Exercise training during pulmonary rehabilitation can improved cardiopulmonary endurance and quality of life in elderly patients with PF. The 6MWDs were more noticeable with moderate exercise intensity, combined aerobic–resistance–flexibility–breathing exercises and in younger patients, which all were not affected by BMI levels or exercise durations. As to pulmonary function, exercise training can improve FVC% pred, but has no effect on DLCO% pred and TLC% pred.
Women Leaders Improve Environmental Outcomes: Evidence from Crop Fires in India

This paper provides causal evidence that women leaders improve environmental outcomes. Using a close-election regression discontinuity design, we find that the election of a female politician over a male politician decreases crop fire incidence and biomass-related particulate emissions in India. These effects are concentrated during the harvest and post-harvest months in districts that follow fire-suited cropping patterns. To understand mechanisms, we survey 424 male and female village council leaders between December 22-March 23 in Punjab, the Indian state with the highest per capita incidence of crop fires. We find women leaders are more likely to consider crop fires a serious issue, weigh their impacts on child health, support regulation to decrease crop fire incidence, and implement specific crop residue management policies like private residue collection or encouraging crop residue use as fodder.
Human-guided Collaborative Problem Solving: A Natural Language based Framework

We consider the problem of human-machine collaborative problem solving as a planning task coupled with natural language communication. Our framework consists of three components -- a natural language engine that parses the language utterances to a formal representation and vice-versa, a concept learner that induces generalized concepts for plans based on limited interactions with the user, and an HTN planner that solves the task based on human interaction. We illustrate the ability of this framework to address the key challenges of collaborative problem solving by demonstrating it on a collaborative building task in a Minecraft-based blocksworld domain. The accompanied demo video is available at https://youtu.be/q1pWe4aahF0.
Multispecies coalescent and its applications to infer species phylogenies and cross-species gene flow

Abstract Multispecies coalescent (MSC) is the extension of the single-population coalescent model to multiple species. It integrates the phylogenetic process of species divergences and the population genetic process of coalescent, and provides a powerful framework for a number of inference problems using genomic sequence data from multiple species, including estimation of species divergence times and population sizes, estimation of species trees accommodating discordant gene trees, inference of cross-species gene flow and species delimitation. In this review, we introduce the major features of the MSC model, discuss full-likelihood and heuristic methods of species tree estimation and summarize recent methodological advances in inference of cross-species gene flow. We discuss the statistical and computational challenges in the field and research directions where breakthroughs may be likely in the next few years.
Barriers, enablers, and motivations for staff adoption of learning analytics: Insights for professional learning opportunities from an Australian university

Understanding the capabilities and motivations of academics towards adopting and using Learning Analytics (LA) to support their development of technology-enhanced learning is an important first step in designing an effective and flexible adoption plan. Situated in a regional university, this paper reports on the initial data-gathering stage of an on-going study aimed at designing and trialing an adoption plan to support individual staff to engage deeply with LA to inform and enhance their teaching practice and their students’ experiences. This paper analyses a staff survey (N=74) and transcripts from 28 semi-structured interviews conducted over 22 months with eight academics. Survey respondents reported low levels of knowledge about, and use of, LA, as well as a lack of confidence in accessing, interpreting, and acting on, data. Inductive and deductive thematic analyses of interview transcripts support these findings. Analysis further identified three main themes of indicators of successful LA adoption: effective learning design and enhanced teaching practice; improved student experience; and academic recognition. Based on these results, this paper proposes elements that can be included in a suite of professional learning opportunities that will enable academic developers and institutions to support individual staff to successfully adopt of LA.
Variability in the mechanical properties of commercially available thermally modified hardwood lumber

Research indicates that users of thermally modified wood lack information regarding the improved performance and any variations that may exist for the “same” product when manufactured by different companies. The goal of this study was to evaluate the variability in mechanical properties of three thermally modified hardwoods and determine the variability between three different manufacturers. To determine the hardness, bending (modulus of elasticity and module of rupture) and shrinkage values, testing was conducted following ASTM standard D143. The samples were conditioned at 20 °C and a relative humidity of 65% until they reached an equilibrium moisture content before testing. Analysis of variance was used to determine the variability within and between the different processes used by each company. Seven out of 18 (39%) tests indicated that there were statistical differences regarding the mechanical performances of the wood samples. Yellow poplar had the least variation between companies (only difference in equilibrium moisture content, EMC) and red maple had the most (hardness, tangential shrinkage, and EMC). While the means for these properties were statistically different, the differences in application for hardness and EMC are slight. For example, the largest difference between processes in hardness was 83.6 kg, for tangential shrinkage, 0.45% and 1.37% for EMC. These differences are suggested to be inconsequential when compared to the values that exist between different species of untreated wood.
Spatial Aliasing and Loudspeaker Directivity in Unified Wave Field Synthesis Theory

Sound Field Synthesis aims at the physical reproduction of arbitrary target sound fields over an extended listening area by employing a dense ensemble of loudspeakers, termed the secondary source distribution (SSD). The loudspeakers are fed with properly chosen driving functions, so that the resultant field of the individual SSD elements ideally coincides with the target sound field in the intended receiving area [1, 2]. Wave Field Synthesis (WFS) is one of the prominent SFS methods, extracting the required driving functions from a suitable boundary integral representation of the target sound field [3, 4]. In a recent contribution by the present authors a unified WFS formulation was given, allowing the reproduction of arbitrary virtual sound fields, by using a smooth, convex distribution of secondary sources and optimizing the synthesis on an arbitrary reference curve [5]. Besides WFS-like implicit approaches explicit solutions are known for the SFS problem in special SSD geometries. For a linear loudspeaker array the explicit solution is referred to as the Spectral Division Method (SDM), obtaining driving functions in the wavenumber domain [6]. Recently it was proven by the present authors that under high frequency conditions a wavefront matching, spatial approximation can be given for the general explicit solution, shown to be equivalent to the unified WFS driving functions [7]. Basic WFS and SDM theories assume the continuous distribution of 3D point sources as the secondary source distribution. In practice these assumptions are obviously violated, when an ensemble of directive sources located at discrete positions is applied. Both the artifacts and possibilities for their avoidance have been studied extensively in the related literature [8, 9, 10]. Discretization results in clearly audible artifacts in the synthesized sound field: amplitude errors and coloration of the synthesized field, as well as echoes following the intended synthesized wavefront due to spatial aliasing. The present contribution revisits the topic of source directivity and spatial aliasing within the context of unified WFS theory.
Defeating the Fakes: Vocal Fake Detection using Discrete Fourier Transform in Neural Networks

—We examine two methods to distinguish real voices from deepfake voices. One method uses Fourier transform arrays in a fully connected neural network to classify the voices. The second method uses spectrogram images in a convolutional neural network. We compare the two models in terms of accuracy and computational performance. Moreover, two different datasets are used to evaluate performance on unseen data. Results show that discrete Fourier transforms can be used to successfully detect deepfake voices, reaching an accuracy of 99.9% when using spectrogram images. Though using discrete Fourier transform arrays as input reaches a lower accuracy of 88.6%, training this model is at least 20 times faster.
Biodiesel production from a free fatty acid containing Karanja oil by a single-step heterogeneously catalyzed process

ABSTRACT Karanja oil, containing 6.2% free fatty acids (FFAs), was considered for biodiesel production using a single-step solid-phase acid catalyzed process. Different types of zeolites and Amberlyst15 catalysts were tested and biodiesel was produced. Under similar conditions, the highest biodiesel yield was achieved using an Amberlyst15 catalyst, which contained 3–5% of moisture. The effects of operating parameters of the reaction such as reaction temperature, catalyst amount, and methanol-to-oil ratio were studied. An increase of methanol:oil ratio revealed a non-monotonic increase in biodiesel yields. Similar non-monotonic behavior was observed when Jatropha oil was used. Leaching and catalyst reusability were also considered. No significant effects of leaching were observed and catalyst reusability appeared to be affected by methanol interactions. The presence of a co-solvent, Tetrahydrofuran (THF), increased the biodiesel yield. Furthermore, an optimum amount of THF (THF:methanol volume ratio of 1:2) gave rise to the highest biodiesel yield. A biodiesel yield of 93% was achieved at 120 °C using a single-step process with Amberlyst15 as a catalyst, THF as a co-solvent, and a methanol:oil ratio of 30:1.
Changes in the physico-chemical and biochemical compositions of custard apple (Annona squamosa L.) fruits during growth, development and ripening

SummaryFruits of annona (Annona squamosa L.) cvs. Barbadose Seedling and Washington-97 were analyzed at 15 d intervals after flowering to harvest maturity and at ripe stage. Fruits took 120 ± 5 d to reach harvest maturity and then another of 2–5 d to the ripe stage. Fruits exhibited a double sigmoid growth curve and a climacteric respiration. Physical characters recorded were fruit weight, size, density, T.S. S. , percentage of edible pulp, peel, seed and central stalk and biochemical constituents like dry matter, alcohol, insoluble solids, total and individual sugars, total acids, citric acid, total soluble amino acids, total tannins, vitamins A and C, chlorophylls and minerals (P, K, Fe, Na, Ca, Mg). Sugar/acid ratio and the appearance of a yellow colour in the edible pulp may be considered as acceptable harvest criteria.
Immersive Analytics of Heterogeneous Biological Data Informed through Need-ﬁnding Interviews

The goal of this work is to improve existing biological analysis processes by means of immersive analytics. In a ﬁrst step, we conducted need-ﬁnding interviews with 12 expert biologists to understand the limits of current practices and identify the requirements for an enhanced immersive analysis. Based on the gained insights, a novel immersive analytics solution is being developed that enables biologists to explore highly interrelated biological data, including genomes, transcriptomes, and phe-nomes. We use an abstract tabular representation of heterogeneous data projected onto a curved virtual wall. Several visual and interactive mechanisms are offered to allow biologists to get an overview of large data, to access details and additional information on the ﬂy, to compare selected parts of the data, and to navigate up to about 5 million data values in real-time. Although a formal user evaluation is still pending, initial feedback indicates that our solution can be useful to expert biologists.
Quantitative Research on China's Business Environment Policy Text from the Perspective of Policy Tools

Under the background that the importance of business environment is increasing day by day, and the innovation of government policies on business environment plays an increasingly important role in optimizing our country's business environment, how to innovate business environment policies is even more important. Using content analysis method, 33 business environment policies promulgated by the central government from 2015 to 2019 will be coded and counted, and will be studied in combination with the business environment report issued by the World Bank. The research shows that China has comprehensively used three different business environment policy tools, and environmental policy tools are the main means to optimize and innovate the business environment. It is suggested that the government should pay more attention to supply-side innovation, pay more attention to taxation and talents, and enhance the implementation of policies and government credit to improve the level of business environment in China.
You May Also Like... Privacy: Recommendation Systems Meet PIR

Abstract We describe the design, analysis, implementation, and evaluation of Pirsona, a digital content delivery system that realizes collaborative-filtering recommendations atop private information retrieval (PIR). This combination of seemingly antithetical primitives makes possible—for the first time—the construction of practically efficient e-commerce and digital media delivery systems that can provide personalized content recommendations based on their users’ historical consumption patterns while simultaneously keeping said consumption patterns private. In designing Pirsona, we have opted for the most performant primitives available (at the expense of rather strong non-collusion assumptions); namely, we use the recent computationally 1-private PIR protocol of Hafiz and Henry (PETS 2019.4) together with a carefully optimized 4PC Boolean matrix factorization.
Why we volunteer

Second, we believe that our field can do better. We have learned much over the last 20 years, and yet there is so much that we still don’t know. We need to continue to advance the state of the art, both in research and in practice. We also need to re-invent both the HCI research agenda and the practice of user experience design as new technologies come into play – as we have seen with GUIs, with the Web, and with mobile devices. As technology changes, so must we change. As volunteers, we provide the leadership and the momentum that drives our field forward.
Microwave-induced H2SO4 activation of activated carbon derived from rice agricultural wastes for sorption of methylene blue from aqueous solution

AbstractActivated carbon derived from the rice straw was used for the rapid removal and fast adsorption of methylene blue (MB) from the solvent phase of the aqueous solution. The developed adsorbent was characterized using various analytical techniques such as scanning electron microscopy and FTIR. The effect of various influential parameters including solution pH, adsorbent dosage, contact time, initial adsorbate concentration, stirring speed, and temperature on MB removal were well investigated and optimized. The experimental optimized data showed that a maximum amount of MB ions can be removed at contact time 25 min, dye ion concentration 40 mg/L, and pH of 7. The obtained results of the isotherm study revealed that adsorption data was in good agreement with Langmuir isotherm model (with R2 value of 0.988 and maximum adsorption capacity of 62.5 mg/g at initial pH of 7 and temperature of 298 K). The negative values of ΔG° and the positive values of ΔH° (22.73 kJ/mol) and ΔS° (104 J/mol K) showed that th.
Land surface modeling over the Dry Chaco: the impact of model structures, and soil, vegetation and land cover parameters

Abstract. In this study, we tested the impact of a revised set of soil, vegetation and land cover parameters on the performance of three different state-of-the-art land surface models (LSMs) within the NASA Land Information System (LIS). The impact of this revision was tested over the South American Dry Chaco, an ecoregion characterized by deforestation and forest degradation since the 1980s. Most large-scale LSMs may lack the ability to correctly represent the ongoing deforestation processes in this region, because most LSMs use climatological vegetation indices and static land cover information. The default LIS parameters were revised with (i) improved soil parameters, (ii) satellite-based interannually varying vegetation indices (leaf area index and green vegetation fraction) instead of climatological vegetation indices, and (iii) yearly land cover information instead of static land cover. A relative comparison in terms of water budget components and “efficiency space” for various baseline and revised experiments showed that large regional and long-term differences in the simulated water budget partitioning relate to different LSM structures, whereas smaller local differences resulted from updated soil, vegetation and land cover parameters. Furthermore, the different LSM structures redistributed water differently in response to these parameter updates. A time-series comparison of the simulations to independent satellite-based estimates of evapotranspiration and brightness temperature (Tb) showed that no LSM setup significantly outperformed another for the entire region and that not all LSM simulations improved with updated parameter values. However, the revised soil parameters generally reduced the bias between simulated surface soil moisture and pixel-scale in situ observations and the bias between simulated Tb and regional Soil Moisture Ocean Salinity (SMOS) observations. Our results suggest that the different hydrological responses of various LSMs to vegetation changes may need further attention to gain benefits from vegetation data assimilation.