Miracle-dz/UniFAR-FTUs huggingface dataset:
OAEM_A_178544 147..159

*These authors contributed equally to this work Introduction: Stroke is one of the leading causes of morbidity, disability, and mortality in high-income countries. Early prehospital stroke recognition plays a fundamental role, because most clinical decisions should be made within the first hours after onset of symptoms. The Cincinnati Prehospital Stroke Scale (CPSS) is a validated screening tool whose utilization is suggested during triage. The aim of this study is to review the role of the CPSS by assessing its sensitivity and specificity in prehospital and hospital settings. Methods: A systematic review and a meta-analysis of the literature reporting the CPSS sensitivity and specificity among patients suspected of stroke were undertaken. Electronic databases were searched up to December 2018, and the quality assessment was carried out by using the Revised Quality Assessment of Diagnostic Accuracy Studies −2 (QUADAS-2). Results: Eleven studies were included in the meta-analysis. Results showed an overall sensitivity of 82.46% (95% confidence interval [CI] 74.83–88.09%) and specificity of 56.95% (95% CI 41.78–70.92). No significant differences were found in terms of sensitivity when CPSS was performed by physicians (80.11%, 95% CI 66.14–89.25%) or non-physicians (81.11%, 95% CI 69.78–88.87%). However, administration by physicians resulted in higher specificity (73.57%, 95% CI 65.78–80.12%) when compared to administration by non-physicians (50.07%, 95% CI 31.54–68.58%). Prospective studies showed higher specificity 71.61% (95% CI 61.12–80.18%) and sensitivity 86.82% (95% CI 74.72–93.63) when compared to retrospective studies which showed specificity of 33.37% (95% CI 22.79– 45.94%) and sensitivity of 78.52% (95% CI 75.08–81.60). Conclusions: The CPSS is a standardized and easy-to-use stroke screening tool whose implementation in emergency systems protocols, along with proper and consistent coordination with local, regional, and state agencies, medical authorities and local experts are suggested.
Two Stage Smooth Path Planning for Mobile Robot for Optimal Obstacle Avoidance Problem in Unknown Environment

One of the most fundamental tasks to be performed by a mobile robot is to find a collision-free and smooth path to follow satisfying certain optimization criteria. However, collision free path generated by existing techniques are very spiky which the robot would get it very hard to follow practically. These are known as the non-holonomic constraints in the robot. Smooth paths are important in robotics because smooth paths are more suitable for developing continuous control algorithms to follow the paths by such non-holonomic mobile robots. The main aim of this paper is to solve mobile robot path planning problem in unknown static environment by determining collision free path that satisfies the chosen criteria for shortest distance and path smoothness. The proposed path planning algorithm consist two stages. In the first stage, an optimized collision free path from starting to goal point is generated using a Genetic Algorithm (GA) added with a penalty function. In the second stage, the collision-free path obtained from first stage is interpolated using a Radial Basis Function Neural Network (RBFNN) to generate smoother paths providing to the non-holonomic constraints. The results of GA algorithm serve as a guide for RBFNN planner. The proposed algorithm is tested on various simple and complex environments. All the paths generated were optimal in terms of path length and path smoothness. The proposed algorithm also reduces the number of steps to be taken between the starting point and the target point. We also study the behavior of the best fitness value in all paths and configurations. Comparisons with previous examples in the literature are also included in the results. Detailed simulation results show the functionality and effectiveness of the proposed algorithm in different scenarios.
The role of domain in learning about referents

A number of natural language processing tasks such as knowledge representation, coreference resolution, or other information retrieval tasks depend on learning good representations of real-world entities. Here we demonstrate that the language associated with different entities is highly sensitive to the domain. By analyzing the entities associated with requests, reviews, and descriptions, we can learn entity representations that are stable across different textual domains, but that the entities that are relevant to a request are not necessarily easily translated into entities that are similar based on how they are described in reviews.
Automatic Identification in Document Indexing

Early information retrieval methods using exact keyword matching found unsatisfactory results. Some of the reasons related to this difficulty are obvious: natural language is fuzzy. In particular, one problem is synonymy; for example, when an article contains the word “automobile” and the query the word “car”, exact keyword matching fails to identify this article. Polysemy also adds complexity to the task of determining the true content of a document, because it is rarely the case that a word in any language is reserved for only one concept, and in many cases syntax and context determine semantics. Consider the following three examples which all contain the word "rose":
Learning-based risk assessment and motion estimation by vision for unmanned aerial vehicle landing in an unvisited area

Abstract. We proposed a vision-based methodology as an aid for an unmanned aerial vehicle (UAV) landing on a previously unsurveyed area. When the UAV was commanded to perform a landing mission in an unknown airfield, the learning procedure was activated to extract the surface features for learning the obstacle appearance. After the learning process, while hovering the UAV above the potential landing spot, the vision system would be able to predict the roughness value for confidence in a safe landing. Finally, using hybrid optical flow technology for motion estimation, we successfully carried out the UAV landing without a predefined target. Our work combines a well-equipped flight control system with the proposed vision system to yield more practical versatility for UAV applications.
Text to Speech Conversion with Emotion Detection

Emotion detection from text has been a great find in the field of information recognition since it could help in the better understanding of the data and could help with complex processing methods to provide accurate results. Plain text have been used in various fields such as text mining, but the introduction of the concept of emotion detection has provided a new dimension to the field of information processing making it more efficient and providing a better scope for further enhancements of the future generations. In this paper, various complex algorithms and techniques have been utilized to implement emotion detection from text and converting the text to emotional audio. This is done by recognizing patterns of emotion and retrieving the audio files from the multimedia database.
Stock prices and inflation: relationship revisited

This study examines the nature of relationship between inflation and stock price movement. The analytical literature mentions the possibility of a negative and a positive relationship both. Using the VAR framework based on monthly data for wholesale price index, index of industrial production, exchange rate, stock prices and foreign institutional investment we note that stock prices have an impact on inflation whereas the causality in the reverse direction is not prominent. The results from the impulse response function tend to suggest that the nature of relationship is rather negative. When stock prices are low the firms are reluctant to tap the capital market. Unless bank finance can substitute adequately for the capital market firm’s investment plans would be hit and production would decline. This may result in a price rise as the market demand may exceed the supply. An important policy implication is augmentation of production by encouraging investment through inexpensive bank finance. However in the very long run as we observe from the co-integrating equation, inflation influences stock prices and that too in a positive direction. Unexpected inflation raises the firm’s equity value if they are net debtor. Similarly tightening of monetary policy can reduce inflation and stock prices both as individuals will be left with less money to buy goods or buy stocks.
Should Consumer Subsidies Be More Flexible? A Structural Analysis and Case Study of the Food Stamps Program∗

In this paper, we study how consumers respond to subsidy designs with different spending restrictions, with implications to optimal design of consumer subsidies. In the context of SNAP (commonly known as the Food Stamps Program), we analyze the effect of food stamp benefits from the perspective of recipients (who care about overall consumer welfare) and the policymaker (who prefers that funds are used to buy food). Studying the effect of different subsidies in the context of SNAP is interesting since there are active proposals to change food stamp benefits in opposite ways: (i) to lift restrictions and provide cash with no strings attached, (ii) to add restrictions and exclude certain items (e.g., soda). To simulate consumer behavior under different subsidies, we develop a structural model of consumer demand which integrates consumer decisions for brands, categories, and stores. Our main finding is that expanding food stamp benefits to include household goods would be preferred by both benefit recipients and the policymaker. The mechanism driving this result is that flexible benefits give access to a wider selection of items which provides greater incentives to visit stores. In addition, we quantify trade-offs between different benefit designs and study the effect of banning benefit use on sweetened soda. Finally, our model of brand, category and store choice makes a technical contribution that could be interesting beyond the application considered in this paper. ∗The authors thank Greg Allenby, Carl F. Mela, Bryan Bollinger, Daniel Xu and seminar participants at the 40th ISMS Marketing Science Conference and Duke University IO Lunch Group for comments and suggestions. †Rudolf-Harri Oberg is a Ph.D. candidate in economics at Duke University (email: rudolf.harri.oberg@duke.edu). ‡Andres Musalem is an assistant professor at the Department of Industrial Engineering, University of Chile (email: amusalem@dii.uchile.cl). 1
Knockout of the MISO Gene in the Plasmodium Falciparum Vector Anopheles Gambiae Using the CRISPR-Cas9 System

In the course of this thesis I have sought to engineer a line of Anopheles gambiae mosquitoes, the primary vector of the African malaria parasite Plasmodium falciparum, with the Mating Induced Stimulator of Oogenesis (MISO) gene functionally knocked out of the genome. A MISO knockout line (misoKO) will enhance our ability to detect subtle phenotypes and improve the significance of earlier findings regarding MISO influence on egg production, egg development, and tolerance to Plasmodium falciparum infection. I have designed and implemented a piggyBac transgenic system to create a CRISPR/Cas9 mediated knockout of the reproductive gene MISO in Anopheles gambiae. I have isolated one mutant, misoA3DA76, which will likely be a hypomorphic allele of MISO. Mutant misoA3DA76 features a 290bp deletion of 49 amino acids constituting a removal of 25% of the amino acids in the total MISO sequence. MISO is a highly unstructured protein with no known domains besides an N-terminal secretion sequence. The misoA3DA76 mutant’s deletion removes 49 amino acids from the N-terminal unstructured region of the protein, including the putative secretion peptide sequence. The MISO knockout lines we are generating will revolutionize the ability of Professor Flaminia Catteruccia’s research group to interrogate the function of MISO protein activity.
Combining Interaction Techniques and Display Types for Virtual Reality

Full and partial immersion in virtual reality are fundamental different user experiences: partial immersion supports the feeling of “looking at” a virtual environment while full immersion supports the feeling of “being in” that environment. Working with a range of interactive virtual reality applications using different display systems we have found that the use of six-sided caves and panoramic displays results in different requirements to interaction techniques. These can be related to specific categories of interaction: orientating, moving and acting. In this paper I present a framework for the evaluation and design of interaction techniques for virtual reality focusing on the relations between interaction techniques and display types.
Geochemical Characteristics of Mineral Assemblages from the Yamansu Iron Deposit, NW China, and Their Metallogenic Implications

The Yamansu deposit, which is hosted in the volcanic-sedimentary sequence of the Carboniferous Yamansu Formation in Eastern Tianshan, NW China, contains many skarns, and the orebodies occur in the ore district in stratoidal, banded or lenticular forms. Four alteration stages, namely, albite–tourmaline–apatite–Grt1 (Stage I), K-feldspar–Grt2 (Stage II), magnetite–chlorite–epidote (Stage III), and quartz–calcite–axinite–Grt3 (Stage IV), are distinguished in the Yamansu deposit. The mineral geochemistry associated with each different stage is presented to provide a better understanding of the corresponding metallogenic processes. The ore-forming fluid in Stage I was derived from a magmatic–hydrothermal source and formed at high temperatures with many volatiles. This ore-forming fluid, which contained considerable metallogenic materials during the early stage, likely experienced diffusive metasomatism in a closed system with low water/rock (W/R) ratios. Mineral geochemical analyses show that the Fe content gradually increases from Stage I to Stage II, indicating that accumulated ore-forming materials were available during changes in the physicochemical conditions from a reducing environment with neutral pH to oxidizing conditions with mildly acidic pH. During the main metallogenic stage (Stage III), mineral assemblages reflect moderate- to high-temperature conditions, and the ore-forming fluid was created and destroyed periodically; the magnetite ores were deposited in a fluctuating fluid system. The multilayered orebodies, multigenerational garnets, and minerals with oscillatory zoning indicate that the ore-forming fluid may have developed periodic fluctuations, and this special multistage fluctuation of the hydrothermal fluid in the Yamansu deposit was the key factor controlling the multiple extraction, enrichment and precipitation of metallogenic materials.
How have the recent restructurings, consolidations, delisting and segmentation changes affected the cost of equity of companies listed on the Johannesburg Securities Exchange?

III TABLE OF FIGURES . V TABLE OF TABLES . V 1 INTRODUCTION . 1 2 LITERATURE REVIEW & PROBLEM STATEMENT. 3 2.1 The risk-free rate of return . 3 2.2 The Market Premium . 4 2.3 The coefficient of risk (Beta) . 5 3 RESEARCH METHODOLOGY . 7 3.1 Research Design . 7 3.1. 1 Overview of Research Method . 7 3.1. 2 Research Objectives . 8 3.1. 3 Research Hypothesis . 8 “Question 1: Is there a difference between the costs of equity using the ALSI and F&I data? ” (Correia & Uliana, 2004, p. 70) . 8 “Question 2: Do the different databases randomly result in different answers, and are the differences large? ” (Correia & Uliana, 2004, p. 70) . 9 “Question 3: Is there an association between the two sets of results? ” (Correia & Uliana, 2004, p. 70) . 9 Question 4: Is there a difference between the costs of equity as calculated in the original study and this study using a) ALSI and b) F&I data? 9 Question 5: Is there an association between the results of the two studies? 10 3.1. 4 What data is required? 10 3.1. 5 How was the data collected? 11
Trade and Catching Up to the Industrial Leader

We study the impact of trade on a country catching up to the industrial leader. We calibrate our dynamic, two-country model to Spain and UK from 1850 to 2000, accounting for the inter-war trade collapse (IWTC) and the subsequent catch up by Spain. In our model, the effects of trade disruptions are stronger with more distance to the leader and more openness. A collapse today (less distance, more openness) similar to the IWTC (more distance, less openness) decreases the capital stock thrice as much (12% instead of 4%). Importantly, traded varieties would fall today but increased during the IWTC.
Fabrication, Characterization and Application of Biomolecule Micropatterns on Cyclic Olefin Polymer (COP) Surfaces with Adjustable Contrast

Peptide and protein micropatterns are powerful tools for the investigation of various cellular processes, including protein–protein interactions (PPIs). Within recent years, various approaches for the production of functional surfaces have been developed. Most of these systems use glass as a substrate, which has several drawbacks, including high fragility and costs, especially if implemented for fluorescence microscopy. In addition, conventional fabrication technologies such as microcontact printing (µCP) are frequently used for the transfer of biomolecules to the glass surface. In this case, it is challenging to adjust the biomolecule density. Here, we show that cyclic olefin polymer (COP) foils, with their encouraging properties, including the ease of manufacturing, chemical resistance, biocompatibility, low water absorption, and optical clarity, are a promising alternative to glass substrates for the fabrication of micropatterns. Using a photolithography-based approach, we generated streptavidin/biotinylated antibody patterns on COPs with the possibility of adjusting the pattern contrast by varying plasma activation parameters. Our experimental setup was finally successfully implemented for the analysis of PPIs in the membranes of live cells via total internal reflection fluorescence (TIRF) microscopy.
Effects of the Entomopathogenic Fungus Metarhizium anisopliae on the Mortality and Immune Response of Locusta migratoria

Entomopathogenic fungi are the key regulators of insect populations and some of them are important biological agents used in integrated pest management strategies. Compared with their ability to become resistant to insecticides, insect pests do not easily become resistant to the infection by entomopathogenic fungi. In this study, we evaluated the mortality and immune response of the serious crop pest Locusta migratoria manilensis after exposure to a new entomopathogenic fungus strain, Metarhizium anisopliae CQMa421. M. anisopliae CQMa421 could effectively infect and kill the L. migratoria adults and nymphs. The locust LT50 under 1 × 108 conidia/mL concentration of M. anisopliae was much lower than that under conidial concentration 1 × 105 conidia/mL (i.e., 6.0 vs. 11.2 and 5.0 vs. 13.8 for adults and nymphs, respectively). The LC50 (log10) of M. anisopliae against locust adults and nymphs after 10 days was 5.2 and 5.6, respectively. Although the number of hemocytes in L. migratoria after exposure to M. anisopliae did not differ with that in the controls, the enzymatic activity of superoxide dismutase (SOD) and prophenoloxidase (ProPO) did differ between the two treatments. The activities of both SOD and ProPO under the M. anisopliae treatment were lower than that in the controls, except for the ProPO activity at 72 h and the SOD activity at 96 h. Further, the expression of the L. migratoria immune-related genes defensin, spaetzle, and attacin differed after exposure to M. anisopliae for 24 h to 96 h. Taken together, this study indicated that infection with M. anisopliae CQMa421 could cause the death of L. migratoria by interacting with the immune responses of the host, demonstrating that this fungal strain of M. anisopliae can be an efficient biocontrol agent against L. migratoria.
A tale of two liberalizations

In this paper I study how labor market institutions at the time of a trade reform determine the dynamic response of unemployment. I first document that for a large group of developing countries (1) unemployment increases on average following a trade reform, (2) there are significant cross-country differences in unemployment response, and (3) cross-country variation in the labor market institutions in place at the time of the reform can account for the observed unemployment changes. I interpret this evidence through the lens of a model of international trade, featuring heterogeneous firms, endogenous industry dynamics and search and matching frictions and a dual labor market. I estimate the model to match the pre-liberalization firm dynamics in Colombia and Mexico, two countries that differed by the labor regulations in place at the time of trade liberalization, and I characterize numerically the full transition path towards the new steady state. I show that the dynamic response of unemployment to a reduction in trade costs is non-linear across different combinations of labor market institutions in place at the time of the reform. Consistent with the cross-country evidence, the response is stronger and more persistent when the firing costs are lower and the statutory minimum wage and unemployment benefits are larger. These three institutions account for up to 46 percent of the average unemployment response in the case of Mexico, and up to 41 percent in the case of Colombia.
Model of real classification of meteorological parameters for regional prognosis

Offered model of short-term regional prognosis. The main idea of the method is to pick out air mass of area investigation, using common meteorological variable and synoptical parameters. Thus, initial point of offered method is the classification of air mass. Certain limits are put on meteorological variable quantity. Firstly, they are to be all to distinguish will air mass and, at the same time, they are to change a little within air mass itself. Secondly, they are to be regularly observed by variable quantities in the net of the stations.
Antioxidant and Antibacterial Peptides from Soybean Milk through Enzymatic- and Membrane-Based Technologies

Enzymatic hydrolysis of soybean milk proteins with cysteine protease papain was performed in an advanced bioreactor, operated with batch mode. In soybean milk protein hydrolysis reaction, enzyme and substrate ratio and reaction temperature were varied, ranging from 0.029:100–0.457:100 and 30–60 °C, respectively. The degree of hydrolysis of soybean milk proteins was increased with increase of enzyme and substrate (soybean milk protein) ratio. However, the degree of hydrolysis was increased due to change of reaction temperature from 30 °C to 60 °C with enzyme and substrate ratio 0.229:100 and was reduced when hydrolysis reaction was performed with enzyme and substrate ratio 0.11:100 at hydrolysis temperature 60 °C. Antioxidant capacity of enzyme-treated milk had a similar trend with degree of hydrolysis. In a later exercise, a membrane bioreactor was adopted for continuous production of antioxidant and antibacterial peptides from soybean milk. The membrane bioreactor was operated for 12 h with constant feeding. Ceramic-made tubular membrane with a pore size 20 nm was used. Application of static turbulence promoter in a membrane separation process was investigated and its positive effects, with respect to higher permeate flux and lower energy consumption in filtration process, were proven. Antioxidant capacity and antibacterial activity against Bacillus cereus of enzyme-hydrolyzed milk and permeate from membrane were confirmed.