Miracle-dz/UniFAR-FTUs huggingface dataset:
Issues and Perspectives from 10,000 Annotated Financial Social Media Data

In this paper, we investigate the annotation of financial social media data from several angles. We present Fin-SoMe, a dataset with 10,000 labeled financial tweets annotated by experts from both the front desk and the middle desk in a bank’s treasury. These annotated results reveal that (1) writer-labeled market sentiment may be a misleading label; (2) writer’s sentiment and market sentiment of an investor may be different; (3) most financial tweets provide unfounded analysis results; and (4) almost no investors write down the gain/loss results for their positions, which would otherwise greatly facilitate detailed evaluation of their performance. Based on these results, we address various open problems and suggest possible directions for future work on financial social media data. We also provide an experiment on the key snippet extraction task to compare the performance of using a general sentiment dictionary and using the domain-specific dictionary. The results echo our findings from the experts’ annotations.
Levels of reading comprehension questions in EFL classroom: higher order thinking skills (HOTS)

This paper presents the discussion on the teachers' reading comprehension questions in EFL classrooms of Senior High Schools in Padang. Higher-order thinking skill has become a significant theme in education. However, to what extent EFL teachers have applied it, does not clearly define yet. In the English language learning process, the students are encouraged to think critically. Therefore, teachers are required to provide the students with higher-order thinking skill, especially in reading comprehension. The higher level of reading comprehension questions can facilitate students' higher-order thinking skills. Many studies have revealed that the level of teacher questions determines the level of thinking of students. However, until now, most of the questions asked by teachers in the context of English as a foreign language (EFL) were low-level questions. Those questions were not as effective as high-level questions in helping students develop high-level thinking skills. Therefore, EFL teachers should ask different types of questions at each grade level.
Comparison of the Anti -Diabetic Effect of Aqueous Extract of Cinnamon (Cinnamomum Cassiae) With That of Glibenclamide on Streptozotocin Induced Diabetic Rats

Background: Diabetes mellitus is a metabolic disorder in which a person has high blood sugar either because the pancreas does not produce enough or because of relative insensitivity of insulin. Cinnamon extract decreases blood glucose level of some experimental animals by increasing glucose uptake in adiposities and by increasing sensitivity of insulin. Searching to evaluate the anti-diabetic effect of cinnamon (Cinnamomum cassiae) with glibenclamide in experimentally induced diabetic rats.Aim: To find out the anti diabetic effect of aqueous extract of cinnamon (Cinnamomum cassiae) and compare it with a stablished antidiabetic drug (Glibenclamide) in streptozotocin induced diabetic rats.Method: This was a experimental study conducted in the department of Pharmacology, Dhaka medical college & Hospital from July 2015 to June 2016. Sample size was 30.The study was desined as 2 parts: Experiment-1 & Experiment – 2. Result: Cinnamon produces no statistically significant effect on blood glucose level of non-diabetic rats ( Pvalue >0.10; which is not significant). ). Cinnamon significantly reduced blood glucose level of streptozotocin induced diabetic rats. There is no statistically significant difference between cinnamon and Glibenclamide on blood glucose lowering effect in streptozotocin induced diabetic rats( P – value >0.10; which is not significant). Conclusion: The study was conducted to find out anti diabetic effect of cinnamon on experimentally induced diabetic rats. The present study found that cinnamon (Cinnamomum cassaiae) significantly lowers blood glucose level in experimentally induced diabetic rats. So cinnamon can be used as alternative anti-diabetic medicine for its easy availability, cost effectiveness and as well as lack of significant side effects.
Timely: Pushing Data Movements And Interfaces In Pim Accelerators Towards Local And In Time Domain

Resistive-random-access-memory (ReRAM) based processing-in-memory $(\mathrm{R}^{2}\mathrm{P}\mathrm{I}\mathrm{M})$ accelerators show promise in bridging the gap between Internet of Thing devices’ constrained resources and Convolutional/Deep Neural Networks’ (CNNs/DNNs’) prohibitive energy cost. Specifically, $\mathrm{R}^{2}\mathrm{P}\mathrm{I}\mathrm{M}$ accelerators enhance energy efficiency by eliminating the cost of weight movements and improving the computational density through ReRAM’s high density. However, the energy efficiency is still limited by the dominant energy cost of input and partial sum (Psum) movements and the cost of digital-to-analog (D/A) and analog-to-digital (AD) interfaces. In this work, we identify three energy-saving opportunities in $\mathrm{R}^{2}\mathrm{P}\mathrm{I}\mathrm{M}$ accelerators: analog data locality, time-domain interfacing, and input access reduction, and propose an innovative $\mathrm{R}^{2}\mathrm{P}\mathrm{I}\mathrm{M}$ accelerator called TIMELY, with three key contributions: (1) TIMELY adopts analog local buffers (ALBs) within ReRAM crossbars to greatly enhance the data locality, minimizing the energy overheads of both input and Psum movements; (2) TIMELY largely reduces the energy of each single D/A (and AD) conversion and the total number of conversions by using time-domain interfaces (TDIs) and the employed ALBs, respectively; (3) we develop an only-once input read $(\mathrm{O}^{2}\mathrm{I}\mathrm{R})$ mapping method to further decrease the energy of input accesses and the number of D/A conversions. The evaluation with more than 10 CNN/DNN models and various chip configurations shows that, TIMELY outperforms the baseline $\mathrm{R}^{2}\mathrm{P}\mathrm{I}\mathrm{M}$ accelerator, PRIME, by one order of magnitude in energy efficiency while maintaining better computational density (up to $31.2\times$) and throughput (up to $736.6\times$). Furthermore, comprehensive studies are performed to evaluate the effectiveness of the proposed ALB, TDI, and $\mathrm{O}^{2}\mathrm{I}\mathrm{R}$ in terms of energy savings and area reduction.
ChildFreq: An Online Tool to Explore Word Frequencies in Child Language.

This technical report describes the implementation and use of ChildFreq, a tool for assessing lexical norms of children from one to seven years old. As the name implies, ChildFreq works by extracting word frequencies from a large corpus of child language. These can then be ordered by age or mean length of utterance, and it is also possible to split the data by the children’s gender. A query of words to count the frequency of produces both a line chart and a table with more detailed information. The child language data is taken from the English part of the CHILDES database 1 and comprises more than 5,000 transcriptions,a total of 3;500;000 word tokens. The children’s ages range from six months to seven years, with most children being three years old. ChildFreq is freely available online at http://childfreq.sumsar. net .
MANAGEMENT TRAINING AS A SOURCE OF COMPETITIVE ADVANTAGE: THE MONDRAGON COOPERATIVE GROUP CASE

Academic literature argues that managers, with their resources and capabilities, constitute a source of competitive advantage for companies, even though cooperatives generally have difficulties attracting and retaining competent managers. The present study examines the special efforts made in the creation and development of cooperative managers via corporate training centres in the Mondragon Cooperative Group. The fieldwork that supports this research is a qualitative study based on a series of in-depth interviews to 12 people in charge of Mondragon’s training structure. The empirical contrast carried out in this study confirms that Mondragon’s cooperatives overcome the difficulties in attracting and retaining valuable managers that are common to other cooperatives, additionally confirming that Mondragon’s management training policy, based on its corporate training centres, grants competitive advantages to the cooperatives in the attraction, development and retention of managers. 1 This is the first version of an article submitted to Economic and Industrial Democracy (i.e. the version before peer-review). The final version is available in Basterretxea, I. and Albizu, E. (2010) “Management training as a source of perceived competitive advantage: The Mondragon Cooperative Group case”, Economic and Industrial Democracy, Published online before print October 25, doi: 10.1177/0143831X10377809 http://eid.sagepub. com/content/early/2010/10/16/0143831X10377809. This first version was also presented in the 2nd International CIRIEC Research Conference on the Social Economy that took place in 2009, 1-2 October, in Östersund, Sweden. http://socek.se/ciriec_research_2009 2 Imanol Basterretxea (Corresponding author): Tel. :+ 34 946013868. E-mail address: imanol.basterretxea@ehu.es. Postal address: Universidad del País Vasco. Facultad de Ciencias Económicas y Empresariales. Avda. Lehendakari Aguirre, no 83. 48015 Bilbao (Spain). Eneka Albizu: Tel. : +34 946013119. E-mail address: eneka.albizu@ehu.es. Postal address: Universidad del País Vasco. EU Relaciones Laborales. Bo Sarriena s/n. 48940 Leioa (Spain).
M ONIQUA : M ODULO Q UANTIZED C OMMUNICATION IN D ECENTRALIZED SGD

Decentralized stochastic gradient descent (SGD), where parallel workers are connected to form a graph and communicate adjacently, has shown promising results both theoretically and empirically. In this paper we propose Moniqua, a technique that allows decentralized SGD to use quantized communication. We prove in theory that Moniqua communicates a provably bounded number of bits per iteration, while converging at the same asymptotic rate as the original algorithm does with full-precision communication. Moniqua improves upon prior works in that it (1) requires no additional memory, (2) applies to non-convex objectives, and (3) supports biased or linear quantizers. We demonstrate empirically that Moniqua converges faster with respect to wall clock time than other quantized decentralized algorithms. We also show that Moniqua is robust to very low bit-budgets, allowing less than 4-bits-per-parameter communication without affecting convergence when training VGG16 on CIFAR10.
How do economic variables affect the pricing of commodity derivatives and insurance?

This paper focuses on designing and pricing commodity derivatives and insurance within a novel financial engineering framework that is subsequently tested on commodity price data. These results contribute to a better understanding of the “financialization” of commodities. We quantify explicitly how futures and option prices, as well as insurance premiums, are affected by economic variables linked to commodity supply and demand (e.g., their price elasticity). Our approach is therefore structural instead of reduced-form. Our results generalize existing commodity derivative pricing models and further show under which conditions derivative instruments and insurance will not be offered.
Estimating and Testing Direct Effects in Directed Acyclic Graphs using Estimating Equations

In any association study, it is important to distinguish direct and indirect effects in order to build truly functional models. For this purpose, we consider a directed acyclic graph (DAG) setting with an exposure variable, primary and intermediate outcome variables, and confounding factors. In order to make valid statistical inference on the direct effect of the exposure on the primary outcome, it is necessary to consider all potential effects in the graph, and we propose to use the estimating equation method with robust Huber-White sandwich standard errors. Then, a large-sample Wald-type test statistic is computed for testing the absence of the direct effect. In this package, the proposed causal inference method based on estimating equations (CIEE) is implemented for both the analysis of continuous and time-to-event primary outcomes subject to censoring for the model in Figure 1. Additionally, standard multiple regression, regression of residuals, and the structural equation approach are implemented for fitting the same model.
Genome-wide characterization of Rice Black Streaked Dwarf Virus-responsive genes in rice

Background: Rice black streaked dwarf virus (RBSDV) is an important pathogen disease in rice and gramineous planting regions all over the world. The major phenotypes of RBSDV infected rice were dwarf with dark green leaves, which generally resulted in seriously loss of yield. The RBSDV known so far is preoperatively transmitted to rice in a persistent manner by small brown planthopper (SBPH), instead of transmitting to offspring through ovary. Results: To identify RBSDV responsive genes and to explore and clarify the molecular mechanisms involved in plantvirus interaction, digital gene expression profile (DGE) analysis was performed by high-throughput sequencing using wildtype (WT) and RBSDV infected rice leaves (IRL) as materials. A total of 165,975 and 165,940 unique tags were obtained in IRL and WT libraries, respectively. In comparison with the control, 896 differentially expressed genes (DEGs) were obtained, of which 500 DEGs were up regulated and 396 DEGs were down regulated. Functional analysis showed that DEGs mainly classified into10 groups, including metabolism, stress pathogen and defense, signal transduction, Transporter, transcription and post-transcription, cell structure and division etc. To further validate reliability and authenticity of the data, 10 DEGs were randomly picked and Real-time RT-PCR was carried out, and the expression trends of 7 genes were in line with the RNA-seq results. By searching the RBSDV related miRNA database of rice, 10 targeted genes of 6 significantly changed miRNAs were also identified in these DEGs. Conclusions: The data derived from RNA-seq were valid and credible. Through this research, a series of candidate RBSDV-responsive genes were obtained, and special signal transduction and metabolism pathways were built and pulled out in rice. This study provided further insight into the molecular mechanisms during compatible and incompatible interactions between viruses and their host plants. Copy rights: © This is an Open access article distributed under the terms of International License. Genome-wide characterization of Rice Black Streaked Dwarf Virus-responsive genes in rice Journal of Food Science & Technology (ISSN: 2472-6419) DOI: 10.25177/JFST.5. 2.RA. 615 Research
Effects of Data Preprocessing Methods on Addressing Location Uncertainty in Mobile Signaling Data

Recent years have witnessed an increasing use of big data in mobility research. Such efforts have led to many insights on the travel behavior and activity patterns of people. Despite these achievements, the data veracity issue and its impact on the processes of knowledge discovery have seldom been discussed. In this research, we investigate the veracity issue of mobile signaling data (MSD) when they are used to characterize human mobility patterns. We first discuss the location uncertainty issues in MSD that would hinder accurate estimations of human mobility patterns, followed by an examination of two existing methods for addressing these issues (clustering-based method and time window–based method). We then propose a new approach that can overcome some of the limitations of these two methods. By applying all three methods to a large-scale mobile signaling data set, we find that the choice of preprocessing methods could lead to changes in the data characteristics. Such changes, which are nontrivial, will further affect the characterization and interpretation of human mobility patterns. By computing four mobility indicators (number of origin–destination trips, number of activity locations, total stay time, and activity entropy) from the outputs of the three methods, we illustrate their varying impacts on individual mobility estimations relevant to location uncertainty issues. Our analysis results call for more attention to the veracity issue in data-driven mobility research and its implications for replicability and reproducibility of geospatial research.
Plant Biotechnology 24, 11–16 (2007)

Unique developmental aspects, divergent phenotypes and habitats of Solanaceae make the family an ideal model to investigate the basis of diversification and adaptation. In view of this uniqueness, a global tomato genome sequencing project designated “International Solanaceae Genome Project (SOL): Systems Approach to Diversity and Adaptation” has been launched. The goal of this initiative is to sequence the 220 Mb euchromatin that is expected to contain the majority of coding sequences, rather than 950 Mb full-length tomato genome. Given the high degree of similarity of tomato and pepper genomes, it will be particularly interesting to apply tomato genome information to pepper using a comparative genomics approach. In this review, we discuss the current progress in sequencing of tomato in Korea, genomics resources of pepper and beneficiary of the tomato sequence.
Exotic Dynamics of Inflation: Numerical Simulations

This paper develops a deterministic inflation model via a piecewise linear expectations-augmented Phillips curve. Simulations show that the areapreserving property of the model entails complex dynamics including nonattracting but observable periodic or chaotic behaviors. Such behaviors are relatively uncommon in the economic literature. JEL Classification Numbers: E31; E32
D1.3.6-Simulation and evaluation of the CARLINK-UMA multi-hop scenario by using VanetMobiSim/Ns-2

This deliverable describes the different simulations carried out to evaluate the performance of multi-hop Vehicular Ad-hoc NETworks (VANETs). The term multi-hop is used to express that the VANET is composed of more than two Mobile End Users (MEUs). We have simulated different scenarios using the VanetMobiSim/Ns-2 simulation tool where the MEUs use only ad-hoc operation mode of the IEEE 802.11b MAC Layer Standard to communicate each other; these features characterize the CARLINK-UMA scenario. The goal of this document is to present the obtained results to offer to the consortium different measures about transferring files in CARLINK-UMA scenario without deploying the VANET in real testbeds.
POPULATION GENETIC STRUCTURE IN THE EASTERN POPULATION OF GREATER SANDHILL CRANES (GRUS CANADENSIS TABIDA)

INTRODUCTION The Sandhill Crane (SACR; Grus canadensis) is the most populous of the 15 extant crane species. Their breeding range covers the majority of the continental U.S. and Canada and extends into Cuba and Eastern Siberia. Wintering areas are much more condensed and range typically from the southern and southeastern U.S. into Mexico (Meine and Archibald 1996). While not the most abundant population, the Eastern Population (EP) of greater SACRs (G. c. tabida) is likely the currently fastest growing (3.9% annual average growth rate; Amundsen and Johnson 2010). It is estimated to comprise approximately 60,000 birds (Kruse et al. 2012).
CYTOTOXIC EFFECT OF SNO2 NANOPARTICLES ON ALTERNATIVE CELLULAR MODEL: PARAMECIUM TETRAURELIA

The development of nanotechnologies and their uses, leads to an increase of nanoparticles concentrations in the air, water and soil. For better understanding the potential impacts of metal oxide nanoparticles in the ecosystem, the present study investigates the cytotoxic effect of SnO2 nanoparticles for different grain sizes on the alternative model of freshwater, water pollution bioindicator, Paramecium tetraurelia. The size of SnO2 nanometric powder (Sigma-Aldrich 99.99% pure) has been reduced using mechanical milling with different times. Obtained nanomaterials were then characterized by X-ray diffraction (XRD) and spectroscopy infrared Fourier transforms (FTIR). Moreover, the toxicity of SnO2 nanoparticles on paramecium was studied by following the evolution of the growth kinetics and percent response as a function of time; whereas the impact of SnO2 nanoparticles on paramecium was determined on two biomarkers of oxidative stress respectively, Catalase (CAT) and glutathione S-transferase (GST). The preliminary results show a non-negligible effect of SnO2 (NPs) via their grain sizes. Indeed, it was recorded an increase in the number of paramecium at low concentrations of SnO2 and its inhibition at high concentrations.
Development of a Communicative Knowledge Management Decision Support System for Rabbitry Farming

This study examined the current challenges being faced by rabbit breeders using the rabbitry section of Oyo State College of Agriculture and Technology and a Local Breeder as case studies. The necessity for the study was borne out of the current need for an electronic platform where experts and users can identify problems, solutions and recommendations. The instrument used for fact findings include observing day to day practice of the said section and an interview session with a staff in the section. These were needed in order to acquire information on the current challenges being experienced. A ‘D’ algorithm, which was later translated into model, was developed by the author to show the process of problem identification process, as well as the solution pathway for the system. The system was designed with tools such as HTML, JavaScript and MySQL Database. It was able to facilitate knowledge through communication between users and experts. The communication network adopted was client-server mode of communication. The result of the system developed showed that knowledge was shared, validated and stored for reusable purposes.
Pressure-Volume Controlled Mechanical Ventilator: Modeling and Simulation

In this publication, the pressure and volume controlled type ventilator, providing breathing artificially, has been modeled. Based on the types of ventilators used in clinical medicine, airflow (q) and volume (v) signals vary. This publication has produced the transfer function of the ventilator by taking the ratio of the Laplace transform of paw(t) and q(t) signals, creating [Q (s) / Paw (s)] as a result. Then having obtained the mathematical models of known and used airflow and volume signals in clinical medicine, LabVIEW and MATLAB / Simulink environment based simulations were carried out using the signals present. Pressure-controlled ventilator has been fully modeled with satisfactory simulations results obtained. Volume controlled ventilator has also been modeled, using approximate theoretical mathematical model, and the model has produced satisfactory results as well except a limited and acceptable approximations error. Then the two types of ventilators have been defined in the form of block diagrams using both Simulink and LabVIEW with all the parameters therein. In both simulations environments airway pressure is taken as input, and airflow as output. Volume signal had been obtained by integrating airflow signal properly. Literature surviliance and search have revealed that although input and output behavior of the system were present, transfer function of both types the ventilators has not been studied and simulated in different mediums, comparatively. This study differs from previous studies as it uses transfer functions representing both pressure and volume controlled types of ventilators. The simulations of the output signals, (q,v) signals, have also been done using the LabVIEW and Matlab / Simulink environment with the input signals as paw and system transfer function. Consequently, the modeling of the system generating signals used in clinical medicine and their verification and monitoring in simulation environments have been obtained.