Miracle-dz/UniFAR-FTUs huggingface dataset:
Isolation and characterization of phosphate solubilizing bacteria (Klebsiella oxytoca) with enhanced tolerant to environmental stress

The present investigation was aimed at the isolation and characterization of phosphate solubilizing bacteria with enhanced tolerant to environmental stress. The bacterial strain isolated from a metal-contaminated soil collected from abandoned mines was identified as Klebsiella oxytoca according to 16S rRNA analysis. The strain proved the ability to solubilize inorganic phosphate under a wide range of pH (4 to 10), temperature (20 to 40°C) and salt concentrations (0 to 7.5% NaCl). However, the maximum phosphate solubilization (615 µg ml-1) was recorded when the medium contained glucose (2%) and ammonium sulphate (0.1%), respectively as the source of carbon and nitrogen and NaCl (2.5%) with pH adjusted to 7 at 35°C. As revealed by the results of plant growth promoting assays on 1-aminocyclo-propane-1-carboxylic acid (ACC) deaminase activity and production of ammonia, hydrogen cyanide (HCN) and indole acitic acid (IAA), the strain was shown to be good plant growth promoter, which was further confirmed by the enhanced growth of mung bean seedlings inoculated with the strain (31.88 and 45.53% higher shoot and root length compared to un-inoculated control). Based on the results, the strain could be identified as an ideal candidate to be included in developing microbial inoculants suit for stress environments. Key words: Klebsiella oxytoca, phosphate solubilizing bacteria, stress environments, microbial inoculants.
A Proposed Artificial intelligence Model for Real-Time Human Action Localization and Tracking

In recent years, artificial intelligence (AI) based on deep learning (DL) has sparked tremendous global interest. DL is widely used today and has expanded into various interesting areas. It is becoming more popular in cross-subject research, such as studies of smart city systems, which combine computer science with engineering applications. Human action detection is one of these areas. Human action detection is an interesting challenge due to its stringent requirements in terms of computing speed and accuracy. High-accuracy real-time object tracking is also considered a significant challenge. This paper integrates the YOLO detection network, which is considered a state-of-the-art tool for real-time object detection, with motion vectors and the Coyote Optimization Algorithm (COA) to construct a real-time human action localization and tracking system. The proposed system starts with the extraction of motion information from a compressed video stream and the extraction of appearance information from RGB frames using an object detector. Then, a fusion step between the two streams is performed, and the results are fed into the proposed action tracking model. The COA is used in object tracking due to its accuracy and fast convergence. The basic foundation of the proposed model is the utilization of motion vectors, which already exist in a compressed video bit stream and provide sufficient information to improve the localization of the target action without requiring high consumption of computational resources compared with other popular methods of extracting motion information, such as optical flows. This advantage allows the proposed approach to be implemented in challenging environments where the computational resources are limited, such as Internet of Things (IoT) systems.
Tool Substitution with Shape and Material Reasoning Using Dual Neural Networks

This paper explores the problem of tool substitution, namely, identifying substitute tools for performing a task from a given set of candidate tools. We introduce a novel approach to tool substitution, that unlike prior work in the area, combines both shape and material reasoning to effectively identify substitute tools. Our approach combines the use of visual and spectral reasoning using dual neural networks. It takes as input, the desired action to be performed, and outputs a ranking of the available candidate tools based on their suitability for performing the action. Our results on a test set of 30 real-world objects show that our approach is able to effectively match shape and material similarities, with improved tool substitution performance when combining both.
Heterogeneity in Marginal Non-Monetary Returns to Higher Education

In this paper we estimate the effects of college education on cognitive abilities and health exploiting exogenous variation in college availability and student loan regulations. By means of semiparametric local instrumental variables techniques we estimate marginal treatment effects in an environment of essential heterogeneity. The results suggest heterogeneous but always positive effects on cognitive skills and homogeneously positive effects for all health outcomes but mental health, where the effects are around zero throughout. We find that likely mechanisms of positive physical health returns are effects of college education on physically demanding activities on the job and health behavior such as smoking and drinking while mentally more demanding jobs might explain the skill returns.
Table 1 CIWA for Alcohol NAUSEA AND VOMITING Ask ‘ ‘ Do you feel sick to your stomach ? Have you vomited ?

Background: Use of a symptom-triggered scale to measure the severity of alcohol withdrawal could reduce the rate of seizures and other complications. The current standard scale, the Clinical Institute of Withdrawal Assessment (CIWA), takes a mean (±SD) of 5 minutes to complete, requiring 30 minutes of nursing time per patient when multiple measures are required. Objectives: The objective was to assess the feasibility and reliability of a brief scale of alcohol withdrawal severity. Methods: The SHOT is a brief scale designed to assess alcohol withdrawal in the emergency department (ED). It includes four items: sweating, hallucinations, orientation, and tremor (SHOT). It was developed based on a literature review and a consensus process by emergency and addiction physicians. The SHOT was first piloted in one ED, and then a prospective observational study was conducted at a different ED to measure its feasibility and reliability. Subjects included patients who were in alcohol withdrawal. One nurse administered the SHOT and CIWA, and the physician repeated the SHOT independently. The SHOT was done only at baseline, before treatment was administered. Results: In the pilot study (12 patients), the SHOT took 1 minute to complete on average, and the CIWA took 5 minutes. Sixty-one patients participated in the prospective study. For the SHOT and the CIWA done by the same nurse, the kappa was 0.88 (95% confidence interval [CI] = 0.52 to 1.0; p < 0.0001), and the Pearson’s r was 0.71 (p < 0.001). The kappa for the nurse’s CIWA score and the physician’s SHOT score was 0.61 (95% CI = 0.25 to 0.97; p < 0.0006), and the Pearson’s r was 0.48 (p = 0.002). The SHOTs performed by the nurse and physician agreed on the need for benzodiazepine treatment in 30 of 37 cases (82% agreement, kappa = 0.35, 95% CI = 0.03 to 0.67; p < 0.02). The mean (±SD) time taken by nurses and physicians to complete the SHOT was 1 (± 0.52) minute (median = 0.6 minutes). Seventeen percent of patients scored positive on the SHOT for hallucinations or disorientation. Conclusions: The SHOT has potential as a feasible and acceptable tool for measuring pretreatment alcohol withdrawal severity in the ED. Further research is needed to validate the SHOT, to assess the utility of serial measurements of the SHOT, and to demonstrate that its use reduces length of stay and improves clinical outcomes. ACADEMIC EMERGENCY MEDICINE 2010; 17:1048–1054 a 2010 by the Society for Academic Emergency Medicine
Sensor fault-tolerant vector control of induction motors

The authors propose a multisensor switching strategy for fault-tolerant vector control of induction motors. The proposed strategy combines three current sensors and associated observers that estimate the rotor flux. The estimates provided by the observers are compared at each sampling time by a switching mechanism which selects the sensors-observer pair with the smallest error between the estimated flux magnitude and a desired flux reference. The estimates provided by the selected pair are used to implement a vector control law. The authors consider both field-oriented control and direct torque and flux control schemes. Pre-checkable conditions are derived that guarantee fault tolerance under an abrupt fault of a current sensor. These conditions are such that the observers that use measurements from the faulty sensor are automatically avoided by the switching mechanism, thus maintaining good performance levels even in the presence of a faulty sensor. Simulation results under realistic conditions illustrate the effectiveness of the scheme.
Primer and interviews: Advances in targeted gene modification

Gene targeting in mice, first reported 25 years ago, has led to monumental advances in the understanding of basic biology and human disease. The ability to employ a similarly straightforward method for gene manipulation in other experimental organisms would make their already significant contributions all the more powerful. Here, we briefly outline the strengths and weaknesses of reverse genetics techniques in non‐murine model organisms, ending with a more detailed description of two that promise to bring targeted gene modification to the masses: zinc finger nucleases (ZFNs) and transcription activator‐like effector nucleases (TALENs). Dana Caroll, a forefather of zinc finger technology, and Bo Zhang, among the first to introduce TALEN‐targeted mutagenesis to zebrafish, discuss their experience with these techniques, and speculate about the future of the field. Developmental Dynamics 240:2688–2696, 2011. © 2011 Wiley Periodicals, Inc.
Social capital and investment in R&D: new externalities

We introduce social capital in an endogenous growth model with physical capital, human capital, and research and development (R&D), and we compare the market with the efficient solutions. As social capital is not tradable in the market and since it favours research networks, it introduces new externalities in this framework. These externalities induce the market to invest less in social capital than would a social planner and decrease the tendency to underinvestment in R&D. We quantify the distortions in the model. In some conditions, the new distortions are strong enough to overcome the usual result of underinvestment in R&D.
Implantable Cardioverter-De fi brillator Use in Patients With Left Ventricular Assist Devices

RESULTS Six observational studies (n1⁄4 937) were included. Patients were 53 12 years of age, and 80% were male. Bridge-to-transplantation was the indication for LVAD use in 93% of the patients. A continuous-flow (CF) LVAD was present in 39% of patients. Mean left ventricular ejection fraction was 16 6%. An ICD was present in 355 patients (38%). During a mean follow-up of 7 months, 241 patients (26%) died (16% in the ICD group vs. 32% in the no-ICD group). Presence of an ICD was associated with a 39% relative risk reduction in all-cause mortality (RR: 0.61; 95% confidence interval [CI]: 0.46 to 0.82; p < 0.01). Among subgroup of patients with CF-LVAD (n 1⁄4 361), ICD use was associated with a statistically nonsignificant trend toward improved survival (RR: 0.76; 95% CI: 0.51 to 1.12; p 1⁄4 0.17).
Who are the poor? Measuring wealth inequality to aid understanding of socioeconomic contexts for conservation: a case-study from the Solomon Islands

SUMMARY Understanding the local socioeconomic context is important for the design of appropriate conservation initiatives and associated monitoring strategies, especially in areas with high degrees of inequality, to ensure conservation interventions do not inadvertently further disadvantage vulnerable people. Typical assessments of wealth inequality in remote rural areas are constrained by limited engagement with a cash economy, complex family and tribal ties, and an absence of basic infrastructure. This paper presents a simple participatory approach to measure wealth inequality that does not predefine indicators, such as income or assets, but allows the local people choose the most appropriate indicators. A case study from the Solomon Islands revealed poor households in Kahua were characterized by fewer members, fewer members of working age, and fewer male members than wealthier households. The poor also owned fewer of the locally defined indicators of wealth that were collectively correlated with limited land tenure, and, consequently, conservation or development initiatives that are tied to land in Kahua will be less likely to assist the poorest. Adopting this participatory approach could improve the effectiveness of community-based conservation, through facilitating opportunities to explore local poverty and routes for alleviation.
ic le Considerations for Assessing Model Averaging of Regression Coefficients Running Head : Assessing MA for regression coefficients

Model choice is usually an inevitable source of uncertainty in model-based statistical analyses. While the focus of model choice was traditionally on methods for choosing a single model, methods to formally account for multiple models within a single analysis are now accessible to many researchers. The specific technique of model averaging was developed to improve predictive ability by combining predictions from a set of models. However, it is now often used to average regression coefficients across multiple models with the ultimate goal of capturing a variable’s overall “effect. ” This use of model averaging implicitly assumes the same parameter exists across models so that averaging is sensible. While this assumption may initially seem tenable, regression coefficients associated with particular explanatory variables may not hold equivalent interpretations across all of the models in which they appear, making explanatory inference about covariates challenging. Accessibility to easily implementable software, concerns about being criticized for ignoring model uncertainty, and the chance to avoid having to justify choice of a final model have all ∗Montana State University, Department of Mathematical Sciences, Wilson Hall 2-214, P.O. Box 172400, Bozeman, MT 59717 †katharine.banner@montana.edu ‡Current: Neptune & Company, Inc., Bozeman, MT 59715 §mhiggs@neptuneinc.org This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as doi: 10.1002/eap.1419 This article is protected by copyright. All rights reserved. A cc ep te d A rt ic le led to the increasing popularity of model averaging in practice. We see a gap between the theoretical development of model averaging and its current use in practice, potentially leaving well-intentioned researchers with unclear inferences or difficulties justifying reasons for using (or not using) model averaging. We attempt to narrow this gap by revisiting some relevant foundations of regression modeling, suggesting more explicit notation and graphical tools, and discussing how individual model results are combined to obtain a model averaged result. Our goal is to help researchers make informed decisions about model averaging and to encourage question-focused modeling over method-focused modeling.
Evaluation of oxidative stress in rats (Rattus rattus) inhabiting Bathinda region of Punjab, India

Exposure to various toxic chemicals has become an increasingly recognized source of illness in human and animals, worldwide. The present study was designed to evaluate the oxidative stress in Rattus rattus inhabiting Bathinda region of Punjab. Punjab Agricultural University, Ludhiana campus rats served as control rats. Rattus rattus were brought to laboratory and separated according to sex. The animals were dissected, vital organ excised and weighed and blood and tissues were processed for histological and biochemical studies. Relative weights of liver, heart and kidney were observed to be higher in rats collected from Bathinda as compared to the control rats. Light microscopic observations of liver and kidney sections of Bathinda rats showed many histological changes. Levels of total proteins were found to be lower in blood, liver, kidney and brain of rats collected from Bathinda region. Activities of antioxidant enzymes namely catalase, glutathione peroxidase and glutathione transferase were reduced
Contributions of the driven process and the loading-unloading process during substorms: A study based on the IMAGE-SI12 imager

[1] Substorm energetics has been shown to have two components, the “loading-unloading” component releasing energy previously stored in the tail and the “directly driven” component dissipating simultaneously fed solar wind energy. Previous studies disagree about the relative importance of each process. The SI12 spectral imager onboard the IMAGE satellite provides images of the Doppler-shifted Lyman α auroral emission at 121.8 nm every 2 min. It has been used to determine the auroral intensity during substorms, which may be compared to the solar wind characteristics and interplanetary magnetic field components before and/or after substorm onsets. In this study, we analyze 256 substorms between June 2000 and December 2002, which satisfy criteria relative to the viewing conditions. We compare the mean nightside intensity during the expansion phase with the magnetic open flux, the epsilon parameter, and other coupling functions (used as proxies of transfer of solar wind energy to the magnetosphere) integrated over the growth phase or the expansion phase. The mean auroral intensity during the expansion phase correlates well with coupling functions integrated over the growth phase. We also find that the correlation between the auroral precipitation during the expansion phase and the coupling functions integrated over the expansion phase is lower but still significant. This implies that, even though both mechanisms contribute to the energy precipitated during substorms, the loading-unloading process is statistically dominant.
Dual inhibition of IGF 1 R and ER enhances response to trastuzumab in HER 2 positive breast cancer cells

Although HER2 targeted therapies have improved prognosis for HER2 positive breast cancer, HER2 positive cancers which co-express ER have poorer response rates to standard HER2 targeted therapies, combined with chemotherapy, than HER2 positive/ER negative breast cancer. Administration of hormone therapy concurrently with chemotherapy and HER2 targeted therapy is generally not recommended. Using publically available gene expression datasets we found that high expression of IGF1R is associated with shorter diseasefree survival in patients whose tumors are ER positive and HER2 positive. IGF1R is frequently expressed in HER2 positive breast cancer and there is significant evidence for crosstalk between IGF1R and both HER2 and ER. Therefore, we evaluated the therapeutic potential of targeting ER and IGF1R in cell line models of HER2/ER/IGF1R positive breast cancer, using tamoxifen and two IGF1R targeted tyrosine kinase inhibitors (NVP-AEW541 and BMS-536924). Dual inhibition of ER and IGF1R enhanced growth inhibition in the four HER2 positive cell lines tested and caused an increase in cell cycle arrest in G1 in BT474 cells. In addition, combined treatment with trastuzumab, tamoxifen and either of the IGF1R TKIs enhanced response compared to dual targeting strategies in three of the four HER2 positive breast cancer cell lines tested. Furthermore, in a cell line model of trastuzumab-resistant HER2 positive breast cancer (BT474/Tr), tamoxifen combined with an IGF1R TKI produced a similar enhanced response as observed in the parental BT474 cells suggesting that this combination may overcome acquired trastuzumab resistance in this model. Combining ER and IGF1R targeting with HER2 targeted therapies may be an alternative to HER2 targeted therapy and chemotherapy for patients with HER2/ER/IGF1R positive breast cancer.
Karyotype polymorphism correlates with intraspecific infertility in the homothallic ascomycete Sordaria macrospora

The homothallic fungus Sordaria macrospora produces perithecia with meiotically derived ascospores. In most cases, intraspecies crosses between strains from different culture collections generate fertile hybrid perithecia in the contact zone of two mycelia. However, in some of these crosses we observed a significant decrease in the fertility of the hybrid perithecia when strains of different origin were used for mating. Since we assumed that chromosome variability between the culture collection strains might contribute to this reduction in fertility, we performed pulsed‐field gel electrophoresis. In the course of our study, we were able to identify two major groups of electrophoretic karyotypes in S. macrospora culture collection strains. A quantitative analysis revealed that polymorphic karyotypes contribute to a reduction of fertility in forced crosses between strains carrying differently sized chromosomes. The observed intraspecific chromosome length polymorphism might have consequences on the speciation process of a homothallic fungus capable of sexual but not of asexual spore formation.
Stellar population properties for 2 million galaxies from SDSS DR14 and DEEP2 DR4 from full spectral fitting

We determine the stellar population properties - age, metallicity, dust reddening, stellar mass and the star formation history - for all spectra classified as galaxies that were published by the Sloan Digital Sky Survey (SDSS data release 14) and by the DEEP2 (data release 4) galaxy surveys. We perform full spectral fitting on individual spectra, making use of high spectral resolution stellar population models. Calculations are carried out for several choices of the model input, including three stellar initial mass functions and three input stellar libraries to the models. We study the accuracy of parameter derivation, in particular the stellar mass, as a function of the signal-to-noise of the galaxy spectra. We find that at low redshift, a signal to noise ratio per pixel around 20 (5) allows a statistical accuracy on $\log_{10}(M^{*}/M_{\odot})$ of 0.2 (0.4) dex, for the Chabrier IMF. For the first time, we study DEEP2 galaxies selected by their \OII luminosity in the redshift range $0.83<z<1.03$, finding that they are consistent with a flat number density in stellar mass in the range $10^9<M/M_{\odot}<10^{11.5}$. We find the resulting stellar mass function based on SDSS or eBOSS in agreement with previous studies (Maraston et al. 2013). We publish all catalogs of properties as well as model spectra of the continuum for these galaxies as a value added catalog of the fourteenth data release of the SDSS. This catalog is about twice as large as its predecessors (DR12) and will aid a variety of studies on galaxy evolution and cosmology.
Experimental Study of Helicopter Fuselage Drag

Experimental data are presented for the parasite drag of various helicopter fuselage components, such as skids, external fuel tanks, and tailplane. The experiments were conducted at the Kazan National Research Technical University (Kazan Aviation Institute) T-1K wind tunnel, investigating four versions of a fuselage similar to the Ansat helicopter. It was found that, for the range of pitch angles −10≤α≤10 deg, the skids added 80% to the drag of the bare fuselage, whereas the tailplane increased the drag by 20%. At the same conditions, external fuel tanks were found to add 48% to the clean fuselage drag. A simple rotor hub with a tail support added 74% to the bare fuselage in the range of pitch angles −8≤α≤6 deg. Streamlining the rear fuselage was found to reduce the drag by 16% over the range of pitch angles −10≤α≤10 deg. Apart from the parasite drag, ideas for drag reduction are also discussed.