Miracle-dz/UniFAR-FTUs huggingface dataset:
Transient Layers of Atmospheric Methane on Mars after Surface Release: a Model Study

Introduction: The presence of methane (CH4) on Mars has gained strong interest through repeated reports of its detection since 2003 [Formisano et al., 2004; Krasnopolsky et al., 2004; Mumma et al., 2009; Fonti and Marzo, 2010; Geminale et al., 2011; Krasnopolsky, 2012; Webster et al., 2015] and the possible implications for geophysical or biological activity on Mars. As methane is a reduced gas it is not stable in the highly oxidizing Martian atmosphere. Photochemical models have estimated that its lifetime is of the order of a few hundred years, assuming that the methane is destroyed only by the known photochemical processes [Summers et al., 2002]. As a result any presence of methane would point to more recent activity. One of the most likely sources for the atmospheric methane was that it was released from subsurface reservoirs by release through pores in the surface [Mumma et al., 2009]. The in-situ measurements by the Tunable Laser Spectrometer (TLS) of the Sample Analysis at Mars (SAM) on Curiosity represented a strong affirmation of the presence of methane on Mars in 2013-2014 [Webster et al., 2015], and showed a non-uniform trend of methane throughout the year, supporting the idea of intermittent methane release. Until present nothing is known about the vertical distribution of methane at the times of any of the positive detections. Moreover GCM studies of surface release of methane focused on its horizontal spreading [Lefèvre and Forget, 2009; Mischna et al., 2011; Holmes et al., 2015]. However the upcoming ESA/Roskosmos ExoMars Trace Gas Orbiter (TGO) mission carries two instruments that are designed to measure the first vertical profiles of methane. These are the Nadir and Occultation for Mars Discovery (NOMAD) spectrometer suite [Vandaele et al., 2015] and the Atmospheric Chemistry Suite (ACS) [Korablev et al., 2015]. In anticipation of their measurements it is important to better understand the behavior of methane also in the vertical after an emission from the surface. This is the purpose of the present work in which we present some simple methane release experiments in a GCM and analyze the resulting vertical distribution of methane [Viscardy et al., 2016].
Phase 2 Update for the Fallon FORGE Site , Nevada , USA

The Department of Energy (DOE) Frontier Observatory for Research in Geothermal Energy (FORGE) is to be a dedicated field laboratory where the scientific and engineering community can develop, test, and improve sub-surface technologies and techniques for the creation of cost-effective and sustainable enhanced geothermal systems (EGS) in a controlled environment. The establishment of FORGE will facilitate an understanding of the key mechanisms controlling a successful EGS. The Fallon FORGE site in Nevada is one of two sites that are still being evaluated as potential candidates for hosting the final FORGE laboratory. In Phase 1 of the FORGE initiative, the Fallon team reviewed extensive, pre-existing data including lithological, well log and flow test results from deep wells within the Fallon FORGE footprint that penetrate the target reservoir, as well as a suite of geophysical, geochemical, geological and hydrological data on and adjacent to the site. Such evaluation confirmed that the Fallon site is ideally positioned to host a sub-surface EGS laboratory, with low permeability, appropriate temperatures and depths (175-225°C, 1-4 km), no hydrothermal system, appropriate lithologies, and a favorable stress regime. In Phase 2, key activities included: o securing additional environmental permits and initiating an EA; o extensive outreach with key local, regional and state stakeholders; o preparing our induced seismicity mitigation plan (ISMP); o acquisition of seismic and geodetic baseline datasets (MEQ, GPS and InSAR); o reprocessing and reinterpretation of preexisting seismic reflection profiles; o acquisition of new, detailed gravity and magnetic data; o refining our detailed 3D model of the site (originally constructed in Phase 1) based on the new geophysical data and reinterpreted seismic reflection profiles; o geomechanical and reservoir modelling, and o siting and drilling a deep well to provide additional certainty that the target reservoir has low permeability. This paper provides an overview of these Phase 2 activities at the Fallon FORGE site, and how these activities have further improved our knowledge of site characteristics.
The Search for Shared Situational Awareness for Enhanced Collaboration in Airport Systems

Date: 24/06/2016 There is a demand for an enhancement in the collaborative decision making process at airports. To enable this increased collaboration, shared situational awareness is required. This enables adequate decision making in complex systems such as airports. To research this subject, the question “What are the specifics of developing shared situational awareness in airport systems? ” is asked. It is concluded that awareness is formed by sharing relevant information on a system wide scale. By identifying the most disruptive factors for airport operations and embedding these in an information system that provides timely and accurate information of each factors’ status, the shared information enables stakeholders to improve the performance of the airport system as a whole and to make more efficient use of available infrastructure and slots.
The Impact of Diglossia on Voweled and Unvoweled Word Reading in Arabic: A Developmental Study From Childhood to Adolescence

ABSTRACT All native speakers of Arabic read in a language variety that is remarkably distant from the one they use in everyday speech. The study tested the impact of this distance on reading accuracy and fluency by comparing reading of Standard Arabic (StA) words, used in StA only, versus Spoken Arabic (SpA) words, used in SpA too, among Arabic native speakers in Grades 2, 4, 6, 8, and 10 (N = 100). Pseudowords in SpA and StA were also compared. Analysis of variance results revealed significant differences in reading SpA versus StA words across all grades and in reading voweled and unvoweled words. The findings support the effect the linguistic distance between SpA and StA on word reading development.
Chapter 16 Agrobacterium-Mediated Genetic Transformation of PeanutAgrobacterium-Medi ted Genetic Transformation of Peanut

Legumes are important sources of dietary proteins and fats in developing countries of the semiarid tropics where peanut (Arachis hypogaea L.) is one of the important food legume crops. It is a rich source of protein (23 percent) and edible oil (43 percent; Norden, 1980) and is considered one of the principal economic crops of the world. The genus Arachis belongs to the subfamily Papilionaceae of the family Fabaceae. It is native to South America and comprises diploid (2n = 20), tetraploid (2n = 40) and octaploid (2n = 80) species. Peanut is a seed-propagating, self-pollinating crop originating from Brazil. The geographical classification of peanut is delineated into six regions: the Americas, Africa, Asia, Near East, Europe, and Oceania (Gregory et al., 1980). The total area under peanut cultivation is over 24.8 million hectares and the world’s production is over 32.8 million tons per year, with an average yield of 1.32 tons per hectare (Rao and Nigam, 2001). India is the major producer of peanut, with a total production of 8.9 million tons per year. Peanuts are utilized in several ways; the edible oil is important for human consumption and the meal is used for livestock feed. It is also used directly for food in industrial countries including the United States, Canada, and the European Union.
OTHER COMPREHENSIVE INCOME AND THE MARKET ’ S PROCESSING OF EARNINGS INFORMATION

This study examines whether OCI items impact the market’s ability to process earnings in the contexts of uncertainty/disagreement among market participants and value-relevance. We find that earnings and OCI gains and losses are individually associated with reduced market uncertainty/disagreement and are positively impounded into share prices by investors. However, we also find that both OCI gains and (especially) losses interact with earnings, weakening 1) the negative relation between earnings and market uncertainty/disagreement and 2) the valuerelevance of earnings. Further, we find that the apparent effects of OCI gains and losses on the market’s processing of earnings information are stronger in weak information environments, as measured by analyst following. Our findings suggest that OCI conveys information to the market that is useful but also noisy, thereby potentially hindering the market’s ability to interpret earnings, particularly in weaker information environments.
Self-Efficacy, Motivation, and Perceived Importance of English as an L2 Among Japanese University Students

The purpose of this study was to conduct action research examining the relationships between university students’ self-reported efficacy in the four skills, their perception of the importance of learning English, and their motivations for studying English as a second language (L2). Quantitative data was collected through a Likert scale questionnaire measuring these three constructs. The participants involved in the study were from intact classes at a university in Kansai. The data was analysed using SPSS (ver. 24). The results showed that although participants perceived English as being very important for their professional future, their motivation and self-perceived efficacy were low. This short study provides useful reflection for other educators at the tertiary level of education. 本論の目的は、大学生の自己評価による英語4技能の能力と、英語学習の重要性に対する認識と、英語学習に対する意欲の3つの関係性を探るため、アクションリサーチを行うことである。 これら三要素の関係性を明らかにするために、リッカート法によるアンケートを用いて定量的データ収集を行った。 本論は関西にある大学の学生の協力のもとに行われた。 データ分析にはSPSS (ver.24)を用いた。 その結果、学生は自分の将来のために英語を重要だと認識しているが、英語学習に対する意欲および自分の英語力に対する評価は低いことが分かった。 本論は、大学教員にとって 有益な情報を提供する。
Continental Fog Attenuation Empirical Relationship from Measured Visibility Data

Free Space Optics (FSO) has the great potential for future communication applications. However, weather influenced reduced availability had been the main cause for its restricted growth. Among different weather influences fog plays the major role. A new model generalized for all FSO wavelengths, has been proposed for the prediction of continental fog attenuation using visibility data. The performance of the proposed model has been compared with well known models for measured attenuation data of continental fog. The comparison has been performed in terms of Root Mean Square Error (RMSE).
IoT -Based Approach to Monitor Parking Space in Cities

Internet of Things is the next big thing, as almost everything developed now has an extensive use of data which is then used to get the daily statistics and usage of every individual. The work mainly consists of constructing a screen where the parking space will be shown, and a camera module will be set up, and PIR (Passive Infrared Sensor) will be at the entrance to detect the entrance of a car or any vehicle eligible to park at the lot. The vehicle will be scanned for its registration number in to provide a check whether the vehicle is registered to park or not. This also acts as the security of the parking lot. Moreover, a viable sensor will be placed at each parking slot through which the vacancy of each parking slot will be shown to determine the exact spot available to the user. In order to surpass the project completion, we will be using Raspberry Pi 3 with camera module mounted on it and by using Tensorflow, Node-Red we would be able to identify the car and the license number and also infrared sensor to detect the parking availability which would be displayed on the screen.
Chapter 8 Evaluation for smart air travel support system

Long haul air travel passengers will experience different level of physiological and psychological discomfort. It is because the long haul air travel is not a natural activity for human being. The literature review showed that seating comfort and discomfort is subjective and interchangeable. Comfort is an attribute that is highly demanded by most of the aircraft passengers. An aircraft passenger’s comfort depends on different features and the environment during air travel. Seat discomfort is a subjective issue because it is the customer who makes the adjustment based on their seating experience. The aircraft passenger seat has an important role to play in fulfilling the passenger comfort expectations. The seat is one of the important features of the aircraft where the aircraft passenger spends most of the time during air travel. A smart support system for long haul air travel has been developed at the Eindhoven University of Technology, the Netherlands. The purpose of the system is to reduce travel discomfort and improve the comfort experience during long haul air travel. In this chapter, four experiments were reported. The first study is to identify factors of seating comfort. Next, the survey of relationship between seat location and sitting posture is reported. It is followed by the validation of aircraft cabin simulator. Lastly, the validation experiment of Smart Neck Support System is described. The validation experiment is to validate the developed smart systems for neck support in a simulated ‘‘real life’’ setting. The aim of a developed smart system is to support the passenger’s head and reduce passenger neck muscle stress during air travel adaptively. An aircraft cabin simulator was utilized to conduct the validation experiment. The calibration experiment was conducted to gain information to be used for the validation experiment. The validation is an important process of Smart Neck Support System (SNes).
Off-Policy Deep Reinforcement Learning without Exploration : Supplementary Material

Theorem 1. Performing Q-learning by sampling from a batch B converges to the optimal value function under the MDP MB. Proof. Again, the MDP MB is defined by the same action and state space as M , with an additional terminal state sinit. MB has transition probabilities pB(s|s, a) = N(s,a,s ′) ∑ s̃N(s,a,s̃) , where N(s, a, s′) is the number of times the tuple (s, a, s′) is observed in B. If∑s̃N(s, a, s̃) = 0, then pB(sinit|s, a) = 1, where r(sinit, s, a) is to the initialized value of Q(s, a). For any given MDP Q-learning converges to the optimal value function given infinite state-action visitation and some standard assumptions (see Section A.2). Now note that sampling under a batch B with uniform probability satisfies the infinite state-action visitation assumptions of the MDP MB, where given (s, a), the probability of sampling (s, a, s′) corresponds to p(s′|s, a) = N(s,a,s ′) ∑ s̃N(s,a,s̃) in the limit. We remark that for (s, a) / ∈ B, Q(s, a) will never be updated, and will return the initialized value, which corresponds to the terminal transition sinit. It follows that sampling from B is equivalent to sampling from the MDP MB, and Q-learning converges to the optimal value function under MB.
A Global Optimal Path Planning Algorithm for Mobile Robot

For global optimal path planning of mobile robot,a linear operation based traversal algorithm is proposed firstly.This algorithm computes the step transform matrix(STM) by field scan at first,and then searches the shortest path in the STM with consideration of search direction coherence.Thus a global shortest path which avoids unnecessary turn is planned.Secondly,a new evaluation criterion is proposed to distinguish whether paths are excellent or not.Finally,path planning comparison experiments are conducted with round wave propagation algorithm by simulation.The results show that the algorithm can find better path than wave propagation algorithm under the proposed criterion.
ROLE OF IGF 1 IN MALE AND FEMALE REPRODUCTION IN BOVINES : A REVIEW

IGF 1 is an endocrine hormone which plays an important role in growth in calves and continues to have anabolic effects in adults. It plays a key role in reproduction because it has positive effect on cell proliferation, transformation and differentiation. IGF 1 supplementation to granulosa cell culture increased proliferation and functional activity of cells. Screening based on plasma IGF 1 level has been used as an indicator for improvement of breeding efficiency of either male or female bovines.
Śā kadravya ( Vegetables ) as Pathya in Metabolic Disorders — A Review from Classical Texts of Āyurveda with Current Evidences

Aim: To review the vegetables mentioned as pathya for metabolic diseases like prameha/madhumeha, hṛdroga, and sthaulya from 15 different classical texts and to analyze the available data critically with the help of reported research activities to establish their role in the prevention and management of metabolic disorders. Background: Metabolic syndrome is a multifactorial disorder, which can be prevented by changes in lifestyle and dietary habits. Among the preventive measures given for various disorders, the classical texts of Āyurveda describe all the vegetables along with their guṇa (properties), karma (action), and prayoga (indication) in different disease conditions under śākavarga. As diet is considered as the best preventive medicine, vegetables are indicated as pathya (wholesome diet) for metabolic diseases like prameha/madhumeha, hṛdroga, and sthoulya, and can be used in the prevention and management of metabolic disorders. Review results: It is observed that among 318 vegetables mentioned in compiled texts, 29 vegetables are indicated in prameha/madhumeha and 33 vegetables are indicated in hṛdroga. Majority of these vegetables are reported for their antidiabetic (18), anti-hyperlipidemia (14), cardio-protective (15), anti-hypertensive (7), and antiplatelet (5) activities. Conclusion: Vegetables mentioned under śākavarga in classical texts of Āyurveda can be effectively used as pathya in metabolic disorders. Clinical significance: On the basis of review results, further scientific studies can be planned clinically to evaluate the beneficial effects of these vegetables in clinical practice.
Grinding the Space: Learning to Classify Against Strategic Agents

We study the problem of online learning in strategic classification settings from the perspective of the learner, who is repeatedly facing myopically rational strategic agents. We model this interplay as a repeated Stackelberg game, where at each timestep the learner deploys a high-dimensional linear classifier first and an agent, after observing the classifier, along with his real feature vector, and according to his underlying utility function, best-responds with a (potentially altered) feature vector. We measure the performance of the learner in terms of Stackelberg regret for her 0-1 loss function. Surprisingly, we prove that in strategic settings like the one considered in this paper there exist worst-case scenarios, where any sequence of actions providing sublinear external regret might result in linear Stackelberg regret and vice versa. We then provide the Grinder Algorithm, an adaptive discretization algorithm, potentially of independent interest in the online learning community, and prove its data-dependent upper bound on the Stackelberg regret given oracle access, while being computationally efficient. We also provide a nearly matching lower bound for the problem of strategic classification. We complement our theoretical analysis with simulation results, which suggest that our algorithm outperforms the benchmarks, even given access to approximation oracles. Our results advance the known state-of-the-art results in the growing literature of online learning from revealed preferences, which has so far focused on smoother utility and loss functions from the perspective of the agents and the learner respectively.
Analyzing Activity of the Human Brain During Decision Making

The orbitofrontal cortex (OFC) is a region sitting at the front of the brain which function is not fully understood. However, it has been clearly implicated in decision making as shown by many neuroimaging studies over the last decades. Recent work by Saez et al. [1] has found evidence that OFC activity of high frequency (HFA) between 70-200 Hz is directly related to behavioral responses during decision making tasks. In particular, Saez et al. showed that some modulations of HFA correlated with the human choice and outcome in a simple betting game. Saez et al. conducted their analysis with univariate linear regression, predicting HFA values from one task-related parameter at a time to find electrodes which encode decision making information. This Thesis focused on extending these results and analyses of Saez et al. by applying multivariate methods to discover complex signals and important patterns in the neural data. For this, canonical correlation analysis and biclustering were used on 600 different datasets to find evidence of patterns in electrode responses and complicated combinations of behavioral responses encoded in the human brain signals. In addition, machine learning methods were used to analyze the patients’ behavioral tendencies towards risk-taking in a gambling task and to predict task-related events such as winning, losing and gambling from the neural data. Moderate to good performance was achieved with most methods, but in-depth analysis is still necessary to gain a full understanding of how activity in orbitofrontal cortex gives rise to human behavior in decision making tasks.
A Heuristic Approach for Switching Sequence Determination during Power System Restoration

An approach for switching operation during power system restoration is discussed in this paper. This approach is based on the heuristic search method, which determines the sequence of switching operation to load pick up. The shortest path that requires the minimum number of switching action, between supplying unit and load is selected to reduce duration of restoration. This method uses from priority list for loads based on defined criteria. The proposed scheme is tested on 39-bus New England test system, verify the effectiveness of the proposed method. Key-Words: Power system restoration, heuristic algorithm, switching strategy, loads priority.
Reflections on the 1951 Fitts list : Do humans believe now that machines surpass them ?

In 1951, Paul Fitts “surveyed the kinds of things men can do better than present-day machines, and vice versa” and introduced a list of statements, now commonly known as the Fitts list. A criticism sometimes raised with respect to the Fitts list is that it is outdated. Hence, it is important to address the issue of modernity, especially in light of the increasing rate of technological advance. A total of 249 engineering MSc students were asked to indicate whether humans surpass machines or whether machines surpass humans, for each of the 11 statements of the Fitts list, using an electronic voting system. 2,948 respondents from 103 countries did the same via a crowdsourcing facility. The results indicated that present-day machines are considered to surpass humans in respect to detection, perception, and long-term memory while Fitts argued that the opposite held true. However, a closer reading of the 1951 report reveals that some of the supposed disagreements were already anticipated at that time. © 2015 The Authors. Published by Elsevier B.V. Peer-review under responsibility of AHFE Conference.