Miracle-dz/UniFAR-FTUs huggingface dataset:
Drought Tolerance Screening of Maize Inbred Lines at an Early Growth Stage

Drought is one of the major abiotic factors that have a serious effect on the production of cereals crops including maize, which is grown widely in the world. Screening based on drought facilitates selection of inbred lines and an understanding of droughttolerant traits. The effect of drought stress and rescue after stress on maize inbred lines was investigated in this study. Different plant growth attributes namely plant height, leaf area and weight, stem weight, root length, shoot and root fresh and dry weight, and total leaf chlorophyll content were measured. Six flint inbred lines (FLD 12, FLD 23, FLD 24, FLD 33, FLD 35, and FLD 37) were screened as drought-tolerant lines, whereas another six flint inbred lines (FLD 01, FLD 13, FLD 16, FLD 18, FLD 29, and FLD 31) were screened as drought susceptible lines. Growth attributes under different drought conditions were subjected to a correlation test and analysis of variance and showed highly significant relationships with each other. The drought effect differed with different inbred lines, indicating a wide variability of drought response at the early growth stage of maize plants. The results obtained from this study will be useful for selecting maize inbred lines in future breeding programs for enhancing drought tolerance.
The New Deal, the Deserving Poor, and the First Public Housing Residents in New York City

ABSTRACT Between 1934 and the time of the 1940 Census, the US government built and leased 30,151 units of public housing, but we know little about the residents who benefited from this housing. We use a unique methodology that compares addresses of five public housing developments to complete-count data from the 1940 Census to identify residents of public housing in New York City at the time of the census. We compare these residents to the larger pool of residents living in New York City in 1940 who were eligible to apply for the housing to assess how closely housing authorities adhered to the intent of the National Industrial Recovery Act (1933) and the Housing Act of 1937. This comparison produces a picture of whom public housing administrators considered deserving of this public benefit at the dawn of the public housing program in the United States. Results indicate a shift toward serving households with lower incomes over time. All the developments had a consistent preference for households with a “nuclear family” structure, but policies favoring racial segregation and other discretion on the part of housing authorities for tenant selection created distinct populations across housing developments. Households headed by a naturalized citizen were favored over households headed by a native-born citizen in nearly all the public housing projects. This finding suggests a more nuanced understanding of who public housing administrators considered deserving of the first public housing than archival research accounts had previously indicated.
VP136 The Impact Of Hospital Costing Methods On Economic Evaluations

INTRODUCTION: There are several methods to cost hospital contacts when estimating the cost effectiveness of a new intervention. In England, the National Insitute for Health and Care Excellence (NICE) recommends the use of diagnosis-related group (DRG)-based costs as a valuable way of costing hospital resource use. There are three main sources of unit costs of a DRG: (i) tariffs as used for reimbursement purposes, (ii) benchmarking finished consultant episode (FCE)-level reference costs and (iii) benchmarking spell-level reference costs. The purpose of this work is to compare the implications of choosing a particular source of DRG-based unit costs when conducting an economic evaluation. METHODS: As a case study, we used a cost-utility model developed to compare secondary fracture prevention models of care for hip fracture patients (1). A Markov model was derived from large primary and hospital care administrative datasets in England. Utilities were informed by a meta-regression of thirty-two studies. Hospital resource use (inpatient, outpatient, critical care and emergency care) was valued using the three different 2014–15 DRG-based unit costs and regression-based costing models were derived from 33,000 hip fracture patients to inform the health states of the model (2). For each source of DRG-based costs, we calculated mean life years, Quality-Adjusted Life Years (QALYs) and costs for a representative male and female associated with three models of care: (i) orthogeriatrician (OG)-led, (ii) nurse-led fracture liaison services and (iii) usual care. RESULTS: Using the benchmarking FCE-level DRG-based costs, the OG-led model was estimated to be the most effective model of care (1.77 QALYs, 95 percent Confidence Interval, CI 1.56-1.98) at a threshold of GBP30,000/QALY. However, it also resulted in the highest costs per patient. We will report the cost-effectiveness results using the two remaining DRG-based costs. CONCLUSIONS: Choosing a particular hospital costing method may have an impact on economic evaluations. We will reflect on the implications for the estimated hospital costs, decision uncertainty and adoption of models of care.
Evidence-Based Practice Change: Implementation of a Collaborative Practice Model for Diabetes

Background: The prevalence of type II diabetes mellitus (T2DM) in the United States is high, especially in underserved populations. Many patients with T2DM do not receive the optimal interprofessional collaborative care that has been shown to improve outcomes. A model of care that incorporates these evidence-based recommendations is integral to improving the quality of diabetes care. A growing body of literature identifies the use of a provider-clinical pharmacist collaborative practice (P-CPCP) model of care as an effective, innovative, and evidence-based practice that will improve patient outcomes. Purpose: In response to an identified need to improve T2DM patient care in an urban community health clinic (CHC), the purpose of this project was to implement a P-CPCP model of care. The expected outcomes included (a) increase the number of patients with T2DM that are referred to a clinical pharmacist; (b) improve provider satisfaction with the collaborative process; and (c) implement the P-CPCP model of care across all CHC agency clinics in the network to ensure the delivery of high-quality, evidence-based patient care. Design and Analysis: A quality improvement (QI) design was used and incorporated a rapid improvement cycle of plan-do-study-act (PDSA). After identification of a gap in care and analysis of the evidence, the QI project was created. A provider education module was presented and followed by a chart audit of electronic medical records (EMR) of patients with T2DM. These charts were examined to determine preand post-implementation usage of the model. Provider satisfaction and perceived effectiveness of the P-CPCP model was assessed using a brief electronic survey. Descriptive statistics and a cross tabulation analysis are presented to show the effectiveness of the model for increasing the number of referrals to the clinical pharmacist and EVIDENCE-BASED PRACTICE CHANGE 4 the number of patients seen by the clinical pharmacist in both pre and post groups, as well as to describe the most used pharmacist interventions and provider perceptions of the model. Results: The P-CPCP model increased utilization of the clinical pharmacist in diabetes care. Following implementation of the model referrals increased by 210%. The provider survey demonstrated an increase in provider satisfaction with collaboration, the usefulness of the model, and sustainability of the model. Of the pharmacist interventions, medication reconciliation education (MRE) was perceived as the most frequently used. Conclusions: This doctor of nursing practice (DNP) project reflects evidence-based practice methods on interprofessional collaboration and provides new insight into the implementation of a collaborative practice model and the role of the clinical pharmacist as a valued member of the collaborative team. Consistent use of the P-CPCP model of care improved provider satisfaction with the collaborative process, increased the number of patients referred to the clinical pharmacist, and led to the standardization of diabetes management at a CHC.
Do EU regions benefit from smart specialization

Smart specialization was conceived as a â€œbottom-upâ€ framework to identify new growth paths connected to the existing knowledge cores of regions. Operationalization of smart specialization has proven difficult, though a recent â€œmappingâ€ of technologies in terms of knowledge relatedness and complexity suggests a useful cost-benefit framework. We extend these ideas, locating EU cities in a smart specialization space and tracking their development of alternative technologies over the period 1981 to 2015. Panel models show employment growth and GDP growth are faster in cities that exhibit a logic of technological development consistent with the tenets of smart specialization.
Estimation of genetic diversity, structure and trait association of winged bean (Psophocarpus tetragonolobus (L.) DC.), genotypes through AFLP and ITS markers

The genetic diversity among ninety five accessions of winged bean (Psophocarpus tetragonolobus (L.) DC. ) belonging to six countries of African and Asiatic origin was detected by employing amplified fragment length polymorphism (AFLP) and internal transcribed spacer (ITS) of nuclear ribosomal DNA markers. A medium to low-level of genetic diversity exists among the accessions of P. tetragonolobus. Association between the AFLP markers and flower, pod and seed traits: days to 50% flowering (DFW), pod length (PDL), pod width (PDW), green pod length (GPL), number of pods per plant (PDSP), number of seeds per pod (SDPD), 100 seed weight (SWT) and seed-oil content (SOC) was carried out by employing the mixed linear model (MLM) based kinship matrix (K-model). Traits like SOC and PDW were found to be strongly associated with AFLP markers. Population structure analysis among the genotypes identified five discrete sub-populations among the studied African and Asiatic lines of P. tetragonolobus.
Mining Spatio-Temporal Reachable Regions With Multiple Sources over Massive Trajectory Data

Given a set of user-specified locations and a massive trajectory dataset, the task of mining spatio-temporal reachable regions aims at finding which road segments are reachable from these locations within a given temporal period based on the historical trajectories. Determining such spatio-temporal reachable regions with high accuracy is vital for many urban applications, such as location-based recommendations and advertising. Traditional approaches to answering such queries essentially perform a distance-based range query over the given road network, which does not consider dynamic travel time at different time of day. By contrast, we propose a data-driven approach to formulate the problem as mining actual reachable regions based on a real historical trajectory dataset. Efficient algorithms for the Single-location spatio-temporal reachability Query (S-Query) and the Union-of-multi-location spatio-temporal reachability Query (U-Query) were presented in our recent work. In this paper, we extend the previous ideas by introducing a new type of reachability query with multiple sources, namely, the Intersection-of-multi-location spatio-temporal reachability Query (I-Query). As we demonstrate, answering I-Queries efficiently is generally more computationally challenging than answering either S-Queries or U-Queries because I-Queries involve complicated intersect conditions. We propose two new algorithms called the Intersection-of-Multi-location Query Maximum Bounding region search (I-MQMB) algorithm and the I-Query Trace Back Search (I-TBS) algorithm to efficiently answer I-Queries, which utilize an indexing schema composed of a spatio-temporal index and a connection index. We evaluate our system extensively by using a large-scale real taxi trajectory dataset that records taxi rides in Shenzhen, China. Our results demonstrate that the proposed approach reduces the running time of I-Queries by 50 percent on average compared to the baseline method.
Social Innovation in Brazilian Social Entrepreneurships: A Proposed Scale for its Classification

Purpose – Social entrepreneurship and social innovation have attracted particular attention from policy makers, academics, and practitioners since the year 2000. As this area of knowledge is still incipient in the present literature, this study aims to develop and validate a scale to understand how social entrepreneurs identify social innovations generated by their entrepreneurships. Design/methodology/approach – In order to validate the scale , we applied it to 264 social enterprises in the 27 confederative units of Brazil. The statistical techniques used, besides the descriptive analysis of frequencies and central tendency and variability measures , were exploratory and confirmatory factor analysis. Findings – The results point to a validated scale consisting of 23 items that classify and identify social innovations of the product, organizational , and marketing types, and of incremental, disruptive , and institutional depths. Originality/value – The contribution to the understanding lies in the fact that the scale may stimulate social entrepreneurs or new entrants to better allocate their resources or their attention to certain types of social innovations in order to achieve better results for their entrepreneurships.
Additive negative effects of decadal warming and nitrogen addition on grassland community stability

Much recent research has explored how global warming and increased nitrogen (N) deposition, two important components of global environmental changes, influence the structure and functioning of natural ecosystems. However, how ecosystem dynamics respond to the combination of long‐term warming and N enrichment remains largely unexplored. We investigated the impact of warming and N addition on the temporal stability of plant communities in a decade‐long field experiment, conducted in a desert steppe in northern China, using a split‐plot design with warming as the main‐plot factor and N addition as the split‐plot factor. Long‐term warming and N addition had additive, negative effects on plant community stability. A warming‐induced decrease in species richness was not a significant driver of decreased community stability, which was instead driven by the decreased stability of dominant species under warming. On the other hand, a N‐induced decrease in community stability was ascribed to both decreased stability of dominant and common species and decreased asynchronous population dynamics under N addition. Synthesis. Our results suggest that ongoing anthropogenic environmental changes may have appreciable consequences for the stability of natural grassland functions and services while also highlighting the different mechanisms associated with the similar effects of climate warming and increased N deposition on grassland community stability.
Complete plastome sequence of Croton laevigatus Vahl (Euphorbiaceae): an endemic species in Hainan, China

Abstract Croton laevigatus grows as an evergreen tree or shrub with 15 meters height. It is distributed in the dense or open forests of Hainan province, China. Here, we report and characterize the complete plastome of C. laevigatus in an effort to provide genomic resources useful for promoting its systematics research. The plastome of C. laevigatus is found to possess a total length 162,515 bp with the typical quadripartite structure of angiosperms, contains two Inverted Repeats (IRs) of 26,866 bp, a Large Single-Copy (LSC) region of 90,234 bp and a Small Single-Copy (SSC) region of 18,549 bp. The plastome contains 113 genes, consisting of 79 unique protein-coding genes, 30 unique tRNA genes and four unique rRNA genes. The overall A/T content in the plastome of C. laevigatus is 64.10%. The phylogenetic analysis indicated that C. laevigatus is close to C. tiglium within Euphorbiaceae in this study. The complete plastome sequence of C. laevigatus will provide a useful resource for the conservation genetics of this species as well as for the phylogenetic studies of Euphorbiaceae.
The power of belief: religious freedom in Australian parliamentary debates on same-sex marriage

ABSTRACT More than merely a theme of the Australian parliamentary debates on the bill to legalise same-sex marriage, ‘religious freedom’ appeared in the bill’s very title. This paper explores why and how this happened using a corpus-assisted analysis of the 663 parliamentary speeches made during the marriage legislation debates from 2004 to 2017. The analysis demonstrates that by 2017, the idea that marriage equality was a profound threat to religious freedom was well entrenched in the parliamentary discourse. The study finds that the potential offence of religious sensibilities came to be regarded by politicians as more significant than ongoing discrimination, thereby granting tremendous social power to religious institutions to practise discrimination in the face of changing values in society.
The impact of minimum wage on unemployment, prices, and growth: A multivariate analysis for Turkey

The aim of this study is to research the impact of minimum wage on unemployment, prices, and growth for the Turkish economy. The data used is monthly and covers the period from January 2005 to March 2017. The producer price index represents prices and the industrial production index represents growth. The Autoregressive Distributed Lag (ARDL) model is used to see the effect of the minimum wage on these variables. An error-correction based Granger causality test is then conducted to see short-run and long-run causalities. The bounds test yields evidence of a long-run relationship between variables. The obtained ARDL results also show that while the minimum wage has a statistically significant effect on unemployment and prices, it does not have a statistically significant effect on production. While there is short-run causality from minimum wage to prices only, the obtained significant error correction terms indicate long-run causality for all of the variables. Consequently, the minimum wage plays a significant role in increasing prices and the number of unemployed people in Turkey.
Comparison of discrete, discrete-sectional, modal and moment models for aerosol dynamics simulations

Abstract An open source software (Aerosol and Air Quality Research Lab-Aerosol Dynamics Model, AAQRL-ADM) used for aerosol dynamics simulations is developed by including four models: discrete, discrete-sectional, method of moments, and modal. First, the mathematical description of these models as well as the effects of aerosol dynamics available in the software are reviewed, and a modal model is developed to use multiple modes to represent particle size spectrum. Second, the design of a working principle and user graphical interface (GUI) of AAQRL-ADM is described. Third, the models in AAQRL-ADM are validated by investigating the evolution of particle size distribution (PSD) in considering the effects of coagulation, condensation, and nucleation. Next, the trade-off between simulation accuracy and numerical efficiency is discussed for all of the four models, and a guide to choosing the appropriate aerosol dynamic model in practical simulation is presented. Finally, discrete-sectional, moment, and modal models are used to investigate the particle size distribution in a furnace aerosol reactor along a streamline, coupled with the velocity and temperature profiles. AAQRL-ADM is provided free of charge for the use of public researchers. Copyright © 2020 American Association for Aerosol Research
Facile synthesis of functionalized polyglycidyl methacrylate-magnetic nanocomposites for enhanced uranium sorption

Designing and fabricating nanocomposite magnetic sorbents (with more accessible active sites for achieving high sorption capacities, selectivity and rapid kinetics) has become an impending challenge in the removal of radionuclides. Two core–shell multifunctional magnetic-nanocomposites have been prepared suitably to be used as sorbents using facile two-step processes. In the first step, after synthesis of parent PGMA microparticles (by a dispersion polymerization method), the grafting of aminoalkylcarboxylate and aminoalkylphosphonic ligands (via an intermediary amination step of PGMA) allows increasing sorption capacities due to the specific reactivity of carboxylate and phosphonate groups, giving iminodiacetate (IDA-PGMA) and iminodiphosphonate (IDP-PGMA), respectively. In the second step, functionalized-PGMA was ball-milled with pre-formed magnetic nanoparticles using high-energy planetary milling, resulting in a magnetic nanocomposite structure (M-IDA-PGMA and M-IDP-PGMA). These sorbents were characterized by elemental analysis, FTIR, XRD, pHZPC, TEM, and VSM. The magnetic nanocomposite sizes were around 10.0 nm. The super paramagnetic properties of the hybrid materials make their solid/liquid separation quite easy using an external magnetic field. These materials were investigated for uranium sorption. Optimum pH was found to be close to 4.0; the maximum monolayer chemisorption capacities reach 122.9 and 147.0 mg g−1 for M-IDA- and M-IDP-PGMA, respectively. The adsorption activation energies were calculated from the Arrhenius equation. The sorption is spontaneous, endothermic and controlled by entropic change. Sorbents were tested for U(vi) removal from a real acidic leachate of ores collected in the El-Sella mining area. Finally, sodium bicarbonate revealed efficiency for uranium desorption and the re-use of sorbents was successfully tested for five cycles.
Autonomous Permission Recommendation

Modern smartphone operating systems (e.g., Android 6.0 and later versions) employ an ask-on-first-use policy to regulate app permissions. To assist users in policy decisions, relevant efforts have been focusing on leveraging contexts to capture users’ privacy preferences. However, these techniques have various limitations, such as heavily relying on users’ historical decisions on granting permissions, ignoring the fact that users are not experts on privacy protection, and hard to determine whether a permission shall be granted. To address this problem, we propose an autonomous permission recommendation system, AutoPer+, to automatically recommend users the permission decisions at runtime. The main insight of our proposed system is that the natural language description of an app reflects its functionality and its similarity to other apps, and thus can be used to analyze whether a permission is needed indeed by it, and the apps similar to it. First, we introduce a multi-topic model into app functionality mining, and design a topic-permission mapper for the proposed recommendation system. Then we propose a deep semi-supervised machine using Long Short-Term Memory (LSTM) neural networks to identify similar apps, by which we can explore privacy permission usage in a cluster of apps. Finally, we capture a trade-off between privacy and utility to present a systematic recommendation. In addition to the permission decision (“Allow” or “Deny”), the permission explanations are also provided for users to make decisions (called “Ask”). We evaluate the proposed system via extensive comparison experiments on 31,023 Android apps. The results show that our approach achieves an accuracy of 84.1%. Moreover, we conduct user studies via installing AutoPer+ in the participants’ own Android devices. We receive positive responses from the participants, which implies AutoPer+ is potentially for real-world deployment for enhancing current permission recommendation.