Miracle-dz/UniFAR-FTUs huggingface dataset:
Polite speech emerges from competing social goals – Supplementary Materials

2 Language is a remarkably efficient tool for transmitting information. Yet human speakers 3 make statements that are inefficient, imprecise, or even contrary to their own beliefs, all in 4 the service of being polite. What rational machinery underlies polite language use? Here, we 5 show that polite speech emerges from the competition of three communicative goals: to 6 convey information, to be kind, and to present oneself in a good light. We formalize this goal 7 tradeoff using a probabilistic model of utterance production, which predicts human utterance 8 choices in socially-sensitive situations with high quantitative accuracy, and we show that our 9 full model is superior to its variants with subsets of the three goals. This utility-theoretic 10 approach to speech acts takes a step towards explaining the richness and subtlety of social 11 language use. 12
THE INFLUENCE OF SALTS ON PYRUVATE KINASE FROAM

The enzyme pyruvate kinase which catalyzes the reversible transfer of phosphate from phosphoenolpvruvate (PEPA) to adenosine diphosphate (ADP) yielding pyruvate and adenosine triphosphate (ATP) is widely distributed in living organisms (2, 3, 4, 8, 9, 11, 15). Lohmann and AMeverhof (11) in 1934 demonstrated that the activity of pyrtuvate kinase from rat muscle was dependent on the presence of Mg++ in the assay medium. Utter and Werkman (22) reported that extracts from Escherichia coli contained pyruvate kinase and that it was activated by Mg++ or \In++. In their experiments Ni++, Na+ and K+ were either without effect or were inhibitory. The K+ activation of pyruvate kinase from rat muscle was shown initially by Boyer, Lardy and Phillips (3, 4) and late; by Lardy and Ziegler (9). The complete dependence of the activity of the enzyme on univalent cations was demonstrated first bv the work of Kachmar and Boyer (8). This requirement was in addition to that for divalent cations. K+, NH4' or Rb+ satisfied the univalent cation requirement but Na+, Li' or Ca++ counteracted the activation. In the absence of K+, Na+ additions resulted in a small btit significant stimulation. Boyer (2) reported that extracts from eleven different vertebrate and invertebrate organisms contained pyruvate kinase and that the enzyme from all sources was strongly activated by K+. The optimum concentrations of univalent cations in molarity were 0.15, 0.01 and 0.05 for activity of the enzyme from muscles of rabbit, Anodonta and Limulus, respectively. Introductory studies (14) on the fermentation of phosphoglyceric acid by dialyzed yeast extracts showed no univalent cation activation. Later, Seitz (18) reported that yeast extracts that had been thoroughly dialyzed failed to ferment phosphoglyceric acid unless K+ or NH4+ was supplied. In the absence of univalent cations the phosphoglyceric acid fermentation stopped at the phosphoenolv-pyruvate stage. With this system NH4+ was more effective than K+ as an activator which is in contrast to observations with the enzyme from other sources. Stumpf (20) and Tewfik and Stumpf (21) have provided indirect evidence for the presence of pyruvate kinase in higher plants. Extracts of an acetone powder of pea seed or leaves contained enzymes that catalyzed the conversion of phosphoglyceric acid to p)yruvate. When dialyzed extracts were used, the ad-
Analysis of the Microscopic Flow Structure of a CFB Downer Reactor Using Solids Concentration Signals

The microflow structure in a downer reactor was studied by measuring the solids concentration fluctuations at various elevations and radial positions, using an optical fiber probe, at a sampling rate of 970 Hz. The downer reactor (0.1 m i.d. and 10 m high) was operated at gas velocities ranging from 3.5 to 10.0 m/s and solids flux from 50 to 200 kg/m2s, with spent FCC catalyst of Sauter mean diameter of 67 mm and density of 1500 kg/m3. The analysis of solids concentration time series was performed using statistical, spectral and chaos techniques. Results from these analyses were compared and related to the operating conditions (gas velocity and solids circulation rate) as well as to the spatial locations (radial and axial positions) in the downer reactor. Different techniques of time series analysis gave similar results but with different sensitivity to changes in the dynamics. A combination of the three signal analysis techniques proved to be more useful in providing more insight understanding of the microflow structure.
The Correlation Between Quality of Life, Depression, Anxiety, Stress, and Spiritual Well-Being in Patients with Heart Failure and Family Caregivers

Objective: This study aimed to examine the correlation between quality of life, depression, anxiety, stress, and spiritual well-being in patients with heart failure and their family caregivers. Methods: This descriptive, correlational study was carried out in a coronary outpatient clinic, located in Ankara between March-October 2018. Sixty patients with heart failure, and 60 family caregivers who providing care for these individuals, a total of 120 participants were included in the study. The Kansas City Cardiomyopathy Questionnaire, the Depression Anxiety Stress Scale, the World Health Organization Quality of Life Short Form, and the Functional Assessment of Chronic Illness Therapy-Spiritual Well-Being Scale were utilized for data collection. The data were analyzed using descriptive and correlational statistics. The Pearson correlation test was used to determine the association between the Kansas City Cardiomyopathy Questionnaire, the Depression Anxiety Stress Scale, the World Health Organization Quality of Life Short Form, and the Functional Assessment of Chronic Illness Therapy-Spiritual Well-Being Scale scores. Results: As quality of life scores increased in patients with heart failure, depression, anxiety, stress scores increased (p<0.05). On the other hand, as quality of life scores increased in patients with heart failure, spiritual well-being scores increased (p<0.05). With regard to family caregivers, as quality of life scores decreased, depression, anxiety, stress scores increased, and spiritual well-being scores decreased (p<0.05). Moreover, as quality of life and spiritual well-being scores of patients with heart failure decreased, depression, anxiety, stress scores of family caregivers increased (p<0.05). Conclusion: This study revealed that as quality of life and spiritual well-being scores decreased, depression, anxiety, stress scores of both patients with heart failure and family caregivers increased. Further education and counseling programs targeting patients with heart failure and their family caregivers are recommended to assess both patients' and family caregivers' psychological health and spiritual well-being.
Research review on AI and Machine learning related works

Research Abstract AI farming concepts have made significant contributions to increase food production and sustainability in the 21st century. These systems combine software and hardware that allows farmers to measure, monitor and control certain agronomic parameters. Smart farming technologies are becoming more prominent with technological advances in farming in fields of automation, ICT (information and communication technology), and robotics. Several applications of artificial intelligence (AI) are already developed for use in agriculture and farming purposes and it is anticipated that use of “AI farming” will assist the agriculture sector in the future to drive more efficient production. To understand how to leverage the advantages of AI farming system in developing innovative farming applications, the following questions need to be answered: (1) What kinds of sensors should be used and data collected considering the cost and efficiency? (2) How do we seamlessly transfer new AI technologies from other industries to agricultural problems which have different requirements in terms of accuracy, scalability, operation, environment, etc. (3) What customized and innovative method should be developed dedicated to agriculture on the top of current general
Microsoft Word-99999528-file00.docx

In contrast to other terrestrial arthropods where gaseous O2 that fuels aerobic metabolism diffuses to the tissues in tracheal tubes, and most other metazoans where O2 is transported to tissues by circulating respiratory proteins, the myriapods (millipedes and centipedes) strikingly have tracheal systems as well as circulating hemocyanin (Hc). In order to elucidate the evolutionary origin and biological significance of millipede Hc we report the molecular structure (subunit composition and amino acid sequence) of multimeric (36-mer) Hc from the forest-floor dwelling giant African millipede Archispirostreptus gigas and its allosteric oxygen binding properties under various physico-chemical conditions. A. gigas Hc consists of only a single subunit type with differential glycosylation. Phylogenic analysis reveals that millipede Hc is a sister group to centipede HcA, which supports an early divergence of distinct Hc subunits in myriapods and an ancient origin of multimeric Hcs. A. gigas Hc binds O2 with a high affinity and shows a strong normal Bohr effect. O2 binding is moreover modulated by Ca 2+ ions, which increase the O2 affinity of the Hc in the T (tense; deoxygenated) as well as the R (relaxed; oxygenated) states, and by (L)-lactate, which modulates Hc-O2 affinity by changing the allosteric equilibrium constant, L. Cooperativity in O2-binding at half O2-saturation (n50) is pH-dependent and maximal at pH ~7.4 and the number of interacting O2 binding sites (q) is markedly increased by binding Ca. The data is discussed in the light of role of mutually supplementary roles of Hc and the tracheal system for tissue O2 supply.
Predicting Price of Cryptocurrency - A Deep Learning Approach

—Bitcoin, a type of cryptocurrency is currently a thriving open-source community and payment network, which is currently used by millions of people. As the value of Bitcoin varies everyday, it would be very interesting for investors to forecast the Bitcoin value but at the same time making it difficult to predict. Bitcoin is a cryptocurrency technology that has attracted investors because of its big price increases. This has led to researchers applying various methods to predict Bitcoin prices such as Support Vector Machines, Multilayer Perceptron, RNN etc. To obtain accuracy and efficiency as compared to these algorithms this research paper tends to exhibit the use of RNN using LSTM model to predict the price of cryptocurrency. The results were computed by extrapolating graphs along with the Root Mean Square Error of the model which was found to be 3.38.
"Ignorance and Prejudice" in Software Fairness

Machine learning software can be unfair when making human-related decisions, having prejudices over certain groups of people. Existing work primarily focuses on proposing fairness metrics and presenting fairness improvement approaches. It remains unclear how key aspect of any machine learning system, such as feature set and training data, affect fairness. This paper presents results from a comprehensive study that addresses this problem. We find that enlarging the feature set plays a significant role in fairness (with an average effect rate of 38%). Importantly, and contrary to widely-held beliefs that greater fairness often corresponds to lower accuracy, our findings reveal that an enlarged feature set has both higher accuracy and fairness. Perhaps also surprisingly, we find that a larger training data does not help to improve fairness. Our results suggest a larger training data set has more unfairness than a smaller one when feature sets are insufficient; an important cautionary finding for practising software engineers.
Gender-related differences in psychometric properties of World Health Organization Disability

To investigate the gender-related DIF in 12-item World Health Organization Disability Assessment Schedule 2.0 (WHODAS) amongst patients with chronic musculoskeletal pain . Cross-sectional survey study with 1988 consecutive chronic musculoskeletal pain patients at university’s Physical and Rehabilitation Medicine outpatient clinic. To assess a DIF, WHODAS 2.0 items were dichotomized as ‘none’ rated by respondents as ‘0’ versus ‘any limitation’ rated as ‘1,2,3 or 4’. The item response theory analysis (IRT) was used to define discrimination and difficulty parameters of a questionnaire. The probit logistic regression was used to test uniformity of DIF between gender groups. The results of DIF analysis were presented and evaluated graphically as item characteristic curves based on 2-parameter IRT analysis of dichotomized responses. High to perfect discrimination ability was observed for all the items except one. Difficulty levels of eight items were shifted towards the elevated disability level, four items demonstrated a perfect difficulty property. Significant DIF between genders was observed in seven out of 12 items. All the detected DIFs were uniform. For item ‘household’, ‘emotional affection’ and ‘work’, men had to experience slightly worse disability than women to achieve the same score. A reverse effect was observed for items ‘concentration’, ‘washing’, ‘dressing’ and dealing with strangers. In this study, significant DIF between genders was found in seven of twelve items of 12-item WHODAS 2.0. amongst 1988 patients with chronic musculoskeletal pain. All the detected DIFs were uniform. Even if this study showed gender-related DIF in seven out of 12 items, we recommend using and studying 12-item WHODAS 2.0 in different populations.
Toward Exploratory Understanding of Software using Test Suites

Changing software without correctly understanding it often leads to confusion, as developers do not understand how the change corresponds to the new observed behaviour of the system. Today, many software systems are equipped with a test suite. Test suites document code and give feedback on changed program behaviour. We explored ways to use test suites for software comprehension and implemented a tool that provides additional visualisation and gives immediate feedback on software changes. Information about changes in the software and their implications to the test suite are collected using mutation testing. The tool uses this information to present relevant test cases for developers, and additionally prioritise test executions for immediate feedback. Our research indicates that entropy metrics can find test cases that are relevant for a specific context in the source code. Additionally, simple test case prioritisation strategies can already lead to a significant decrease in feedback time. Based on our case study we argue that test suites are not only useful for regression testing but can be used to generate meaningful information for software comprehension activities.
HEALTH RISK ANALYSIS IN EPIDEMIOLOGY

V.A. Mishchenko1,2, O.V. Ladygin1, I.P. Bykov1, J.A. Zakharova1, A.G. Sergeev1,3, I.A. Kshnyasev2 Rospotrebnadzor's Yekaterinburg Research Institute of Viral Infections, 23 Letnyaya Str. , Yekaterinburg, 620030, Russian Federation Institute of Plant and Animal Ecology of the Urals Department of Russian Academy of Science, 202 8 Marta Str. , URAN, Yekaterinburg, 620144, Russian Federation Ural State Medical University of the RF Public healthcare Ministry, 3 Repina Str. , 630028, Yekaterinburg, Russian Federation
Oversampling Tabular Data with Deep Generative Models: Is it worth the effort?

In practice, machine learning experts are often confronted with imbalanced data. Without accounting for the imbalance, common classiﬁers perform poorly, and standard evaluation metrics mislead the practitioners on the model’s performance. A standard method to treat imbalanced datasets is under-and oversampling. In this process, samples are removed from the majority class, or synthetic samples are added to the minority class. In this paper, we follow up on recent developments in deep learning. We take proposals of deep generative models and study these approaches’ ability to provide realistic samples that improve performance on imbalanced classiﬁcation tasks via oversampling. Across 160K+ experiments, we show that the improvements in terms of performance metric, while shown to be signiﬁcant when ranking the methods like in the literature, often are minor in absolute terms, especially compared to the required effort. Furthermore, we notice that a large part of the improvement is due to undersampling, not oversampling.
ENERGY GAIN FROM ERROR-CORRECTING CODING IN CHANNELS WITH GROUPING ERRORS

Abstract. This article explores the a mathematical model of the a data transmission channel with errors grouping. We propose an estimating method for energy gain from coding and energy efficiency of binary codes in channels with grouped errors. The proposed method uses a simplified Bennet and Froelich’s model and allows leading the research of the energy gain from coding for a wide class of data channels without restricting the way of the length distributing the error bursts. The reliability of the obtained results is confirmed by the information of the known results in the theory of error-correcting coding in the simplified variant.
Measurement and Correlation of Phase Diagram Data for Several Hydrophilic Alcohol + Citrate Aqueous Two-Phase Systems at 298.15 K

Binodal data for the ethanol + (NH4)3C6H5O7 + water system and the 2-propanol + (NH4)3C6H5O7/Na3C6H5O7/K3C6H5O7 + water systems were experimentally determined at 298.15 K. Three empirical equations were used to correlate binodal data. On the basis of the equation with the highest accuracy and lever rule, the liquid−liquid equilibrium data were calculated by MATLAB. The reliability of the calculation method and the corresponding tie-line data was proved by the Othmer−Tobias equation and Bancroft equation. The determined binodal data were also correlated by two theoretical equations on the basis of excluded volume theory. The calculated effective excluded volume (EEV) of salt and the binodal curves plotted in molality both indicate that the salting-out abilities of the investigated salts are in the order Na3C6H5O7 ≈ K3C6H5O7 > (NH4)3C6H5O7, and the phase-separation abilities of the investigated alcohols are in the order 2-propanol > ethanol.
On-Line mass spectrometer analysis of gasification gas

The mass spectrometer is capable of making rapid, repetitive multicomponent analyses with measurement times as short as a second or less. Mass spectrometers used to be too expensive to be used for process analyses, but simpler and cheaper versions have been developed during the last decade. Mass spectrometers are commonly used within the petrochemical industry, but their use for fuel gas streams is not so widespread. This paper describes tests on a quadrupole mass spectrometer in three different gasification projects. Calibration methods and analysis accuracies obtained are accounted for. On the basis of the tests, it can be concluded that the quadrupole mass spectrometer is very suitable for continuous analysis of complex process streams. An important result is that the separation of CO and N-2, an analysis problem that is traditionally regarded as difficult, worked very well. The analysis frequency was approximately once per minute, which should be enough for most control loops. (Less)
Supporting Information Life-Cycle Analysis of Microwave Assisted Pectin Extraction at Pilot-scale

The first Life-Cycle Assessment (LCA) of an acid-free, microwave-assisted process for pectin production at pilot-scale is reported. The properties of the resulting pectin were measured and compared against the criteria for commercial pectin, whilst the energy consumption of the microwave process was measured to compare its life cycle impacts with that of the current commercial process. Overall, the pectin met all the criteria for food-grade commercial pectin. The microwave unit was estimated to have <25% of the environmental impact of traditional acid-assisted thermal process
Extending the three-tier constructivist learning model for alternative delivery: ahead the COVID-19 pandemic in Nigeria

Constructivist theory defines a learning process whereby a learner denotes meaning for him/herself as he/she learns Its challenges inform us that focus and intervention needs to be given to our curricular and instructional material, so that we may have something to offer students in the next century in terms of scientific development, drawing us into technological isolation Study seeks to ascertain readability of some textbooks used in the teaching of science, technology, engineering and mathematics in tertiary institutions in Delta State We chose 72 institutions using quota sampling To uphold the virtues of internationalization, results show we must devise strategies against de-territorializing of knowledge And thus, redefine educational goals to meet globalization as a means of network and unification Thus, constructivism yields and apt description of both individual, group and organizational adoption patterns of technology for teaching and learning across disciplines at the various schools and educational levels It images exemplary practices for teaching, learning and research, highlighting evidences that links technology integration, readability and quality students learning © 2021 Institute of Advanced Engineering and Science All rights reserved
Your Photo is so Funny that I don’t Mind Violating Your Privacy by Sharing it: Individual Humor Styles and Photo-sharing Behaviors

Sharing photos of strangers, sometimes with additional alterations (e.g., overlaying text captions to create memes), has become commonplace online. Such photos often go ‘viral’ because of their humorous aspects and reach a large audience. Such widespread attention, however, can pose significant risks to the privacy of the people appearing in them. Interventions such as encouraging photo-sharers to consider the consequences of their sharing may be a viable approach to restrict the circulation of such photos, but requires understanding how individual differences affect photo-sharing behaviors. In this study, we investigated how the humor style of a person dictates their photo-sharing behaviors. Our results suggest that humor style is a significant predictor of the likelihood to share memes. In particular, our finding suggest that people with a more aggressive and self-deprecating style of humor are most likely to violate the privacy of others when sharing photos online. Our findings have implications for the design of effective strategies based on personal characteristics to discourage the sharing of photos that can violate others’ privacy.