Miracle-dz/UniFAR-FTUs huggingface dataset:
Tracking Control for an Autonomous Airship based on Neural Dynamics model with the Basktepping technique and a Robust Sliding mode control

this paper presents a control approach hybrid for trajectory tracking of an autonomous airship. An integrated backstepping and sliding mode tracking control algorithm is developed for four dimensional tracking controls of an autonomous airship vehicles (AAV). First, a kinematic controller based on Neural Dynamics model with the Basktepping technique is integrated together with the dynamic controller uses a sliding mode control. In the traditional Backstepping method, speed jump occurs if the tracking error changes suddenly. The application of the biologically inspired model is designed to smooth the virtual velocity controller output, avoid speed jumps of autonomous airship vehicles in the large initial errors. Computer simulation results illustrate the effectiveness and efficiency of the control strategy proposed controller. Keywords— Autonomous airship vehicle, Biological inspired neurodynamics, Backstepping control, External disturbance, Sliding mode control, Trajectory control.
AMFORM , a new mass-based model for the calculation of the unit formula of amphiboles from 1 Electron MicroProbe analyses 2

11 In this work, we have studied the relationships between mass concentration and unit-formula of 12 amphibole using 114 carefully selected high-quality experimental data, obtained by EMP (Electron 13 Micro-Probe) + SREF (Single-crystal X-ray Structure REFinement) ± SIMS (Secondary-Ion Mass 14 Spectrometry) analyses, of natural and synthetic Li-free monoclinic species belonging to the Ca and 15 Na-Ca subgroups, and 75 Li-free and Mn-free C2/m end-members including oxo analogues of Ca 16 amphiboles. Theoretical considerations and crystal-chemical driven regression analysis allowed us to 17 obtain a number of equations which can be used to: (i) calculate from EMP analyses amphibole unit18 formulae consistent with SREF±SIMS data, (ii) discard unreliable EMP analyses and (iii) estimate 19 O and Fe contents in Li-free C2/m amphiboles with relatively low Cl contents (≤1 wt%). The 20 AMFORM approach mostly relies on the fact that while the cation mass in Cl-poor amphiboles 21
ESCOLA BRASILEIRA DE ADMINISTRAÇÃO PÚBLICA E DE EMPRESAS

This paper deals with the familiar enterprise succession leaving as a goal to identify, describe and analyze the factors which facilitate and make difficult the process of succession of the familiar enterprise. To this it contextualizes the familiar enterprise in the labor market through its contexts, process and characters. Afterward it treats of the familiar enterprise as an system in its complexity of this segment of the enterprise. It considered the need on studying its origin, evolution and characteristics. Also the ethics and familiar administration. It also, considered the cycle of life, the three-dimensional model of development having as a base the propriety, family and enterprise axes as well as the familiar profissionalization, the main focus reposes in the succession process having as a base its planning the field search reveals it self descriptive, that’s to say a case study through interview with the proprietors, successors, aggregates and succeeded ones. Finally the management indicators which aim, to contribute to the familiar succession.
An Internal Control for Evaluating Bisulfite Conversion in the Analysis of Short Stature Homeobox 2 Methylation in Lung Cancer

Objective: The methylation status is considered as powerful diagnostic, prognostic, and predictive biomarkers. However, the limited DNA amount and conversion efficiency after bisulfite treatment are considerable hindrances in quantitative methylation analysis. In this study, we designed an artificial internal control (IC) system that contained the cytosine-free fragment (CFF) following CpG sequences of the SHOX2 promoter whose methylation status has been described as a valuable biomarker of lung cancer. Its performance in quantifying DNA recovery and bisulfite conversion efficiency as well as in detecting false-positive SHOX2 methylation was determined on samples from lung cancer patients. Material and Methods: The IC system is composed of two pConIC and pUnIC plasmids that both contain a cytosine-free (CF) sequence derived from the CFF and the CpG containing SHOX2 sequences. They are identical in sequence, except that in the ConIC insert, all cytosines have been converted into thymines. Thus, the ConIC can be used as calibrator of 100% bisulfite conversion efficiency, while the UnIC is the indicator in order to evaluate the DNA recovery, bisulfite conversion efficiency of the SHOX2 promoter sequence by quantitative real time PCR. Results: The copy number of the target sequences impacted on both DNA recovery rates and bisulfite conversion efficiency. An amount of 0.005 ng pUnIC (106 copies) showed recovery rate of 18%, similar to that of pConIC, and a bisulfite conversion efficiency of the SHOX2 reaching 98.7%. On the contrary, higher copy number of pUnIC showed incomplete conversion (<85%) and over recovery (~42%). Using this calibrator/indicator couple, we were able to detect false-positive SHOX2 methylation (3.77% instead of 0.03%) due to incomplete bisulfite conversion. Conclusion: Our results proposed a customizable internal control using the ConIC/UnIC as calibrator/indicator to quantify simultaneously and accurately the DNA recovery and bisulfite conversion efficiencies of individual sequence as well as whole genome in methylation assays, thus promoting the validation of standardized clinical DNA methylation biomarker values to progress toward clinical applications.
HITS-SBD at the FinSBD Task: Machine Learning vs. Rule-based Sentence Boundary Detection

This paper presents two different approaches towards Sentence Boundary Detection (SBD) that were submitted to the FinSBD-2019 shared task. The ﬁrst is a supervised machine learning approach which tackled the SBD task as a combination of binary classiﬁcations based on TF-IDF representations of context windows. The second approach is unsupervised and rule-based and applies manually created heuristics to automatically annotated input. Since the latter approach yielded better results on the Dev set, we submitted it to evaluation for English and reached an F score of 0 . 80 and 0 . 86 for detecting begin of sentences and end of sentences, respectively.
Interest Rate Uncertainty as a Policy Tool

We study a novel policy tool—interest rate uncertainty—that can be used to discourage inefficient capital inflows and to adjust the composition of external account between shortterm securities and foreign direct investment (FDI). We identify the trade-offs faced in navigating between external balance and price stability. The interest rate uncertainty policy discourages short-term inflows mainly through portfolio risk and precautionary saving channels. A markup channel generates net FDI inflows under imperfect exchange rate passthrough. We further investigate new channels under different assumptions about the irreversibility of FDI, the currency of export invoicing, risk aversion of outside agents, and effective lower bound in the rest of the world. Under every scenario, uncertainty policy is inflationary.
Biosynthesis of cann fl avins A and B from Cannabis sativa L

In addition to the psychoactive constituents that are typically associated with Cannabis sativa L. , there exist numerous other specialized metabolites in this plant that are believed to contribute to its medicinal versatility. This study focused on two such compounds, known as cannflavin A and cannflavin B. These prenylated flavonoids specifically accumulate in C. sativa and are known to exhibit potent anti-inflammatory activity in various animal cell models. However, almost nothing is known about their biosynthesis. Using a combination of phylogenomic and biochemical approaches, an aromatic prenyltransferase from C. sativa (CsPT3) was identified that catalyzes the regiospecific addition of either geranyl diphosphate (GPP) or dimethylallyl diphosphate (DMAPP) to the methylated flavone, chrysoeriol, to produce cannflavins A and B, respectively. Further evidence is presented for an O-methyltransferase (CsOMT21) encoded within the C. sativa genome that specifically converts the widespread plant flavone known as luteolin to chrysoeriol, both of which accumulate in C. sativa. These results therefore imply the following reaction sequence for cannflavins A and B biosynthesis: luteolin ► chrysoeriol ► cannflavin A and cannflavin B. Taken together, the identification of these two unique enzymes represent a branch point from the general flavonoid pathway in C. sativa and offer a tractable route towards metabolic engineering strategies that are designed to produce these two medicinally relevant Cannabis compounds.
Explorer Data Quality : Theory and Practice

Real-life data are often dirty: inconsistent, inaccurate, incomplete, stale and duplicated. Dirty data have been a longstanding issue, and the prevalent use of Internet has been increasing the risks, in an unprecedented scale, of creating and propagating dirty data. Dirty data are reported to cost US industry billions of dollars each year. There is no reason to believe that the scale of the problem is any different in any other society that depends on information technology. With these comes the need for improving data quality, a topic as important as traditional data management tasks for coping with the quantity of the data. We aim to provide an overview of recent advances in the area of data quality, from theory to practical techniques. We promote a conditional dependency theory for capturing data inconsistencies, a new form of dynamic constraints for data deduplication, a theory of relative information completeness for characterizing incomplete data, and a data currency model for answering queries with current values from possibly stale data in the absence of reliable timestamps. We also discuss techniques for automatically discovering data quality rules, detecting errors in real-life data, and for correcting errors with performance guarantees. 1 Data Quality: An Overview Traditional database systems typically focus on the quantity of data, to support the creation, maintenance and use of large volumes of data. But such a database system may not find correct answers to our queries if the data in the database are “dirty”, i.e., when the data do not properly represent the real world entities to which they refer. To illustrate this, let us consider an employee relation residing in a database of a company, specified by the following schema: employee (FN, LN, CC, AC, phn, street, city, zip, salary, status) Here each tuple specifies an employee’s name (first name FN and last name LN), office phone (country code CC, area code AC, phone phn), office address (street, city, zip code), salary and marital status. An instance D0 of the employee schema is shown in Figure 1. Fan is supported in part by EPSRC EP/J015377/1, the RSE-NSFC Joint Project Scheme, the 973 Program 2012CB316200 and NSFC 61133002 of China.
Safe Generic Data Synchronizer

Reconciliating divergent data is an important issue in concurrent engineering, mobile computing and software configuration management. Actually, a lot of synchronizers or merge tools perform reconciliations, however, which strategy they apply ? is it correct ? In this paper, we propose to use a transformational approach to build a safe generic data synchronizer.
Communications in Mathematical Physics Graded Cluster Expansion for Lattice Systems

In this paper we develop a general theory which provides a unified treatment of two apparently different problems. The weak Gibbs property of measures arising from the application of Renormalization Group maps and the mixing properties of disordered lattice systems in the Griffiths’ phase. We suppose that the system satisfies a mixing condition in a subset of the lattice whose complement is sparse enough namely, large regions are widely separated. We then show how it is possible to construct a convergent multi-scale cluster expansion.
American Finance Association Contrarian Investment , Extrapolation , and Risk Author ( s ) :

For many years, scholars and investment professionals have argued that value strategies outperform the market. These value strategies call for buying stocks that have low prices relative to earnings, dividends, book assets, or other measures of fundamental value. While there is some agreement that value strategies produce higher returns, the interpretation of why they do so is more controversial. This article provides evidence that value strategies yield higher returns because these strategies exploit the suboptimal behavior of the typical investor and not because these strategies are fundamentally riskier. FOR MANY YEARS, SCHOLARS and investment professionals have argued that value strategies outperform the market (Graham and Dodd (1934) and Dreman (1977)). These value strategies call for buying stocks that have low prices relative to earnings, dividends, historical prices, book assets, or other measures of value. In recent years, value strategies have attracted academic attention as well. Basu (1977), Jaffe, Keim, and Westerfield (1989), Chan, Hamao, and Lakonishok (1991), and Fama and French (1992) show that stocks with high earnings/price ratios earn higher returns. De Bondt and Thaler (1985, 1987) argue that extreme losers outperform the market over the subsequent several years. Despite considerable criticism (Chan (1988) and Ball and Kothari (1989)), their analysis has generally stood up to the tests (Chopra, Lakonishok, and Ritter (1992)). Rosenberg, Reid, and Lanstein (1984) show that stocks with high book relative to market values of equity outperform the market. Further work (Chan, Hamao, and Lakonishok (1991) * Lakonishok is from the University of Illinois, Shleifer is from Harvard University, and Vishny is from the University of Chicago. We are indebted to Gil Beebower, Fischer Black, Stephen Brown, K. C. Chan, Louis Chan, Eugene Fama, Kenneth French, Bob Haugen, Jay Ritter, Ren6 Stulz, and two anonymous referees for helpful comments and to Han Qu for outstanding research assistance. This article has been presented at the Berkeley Program in Finance, University of California (Berkeley), the Center for Research in Securities Prices Conference, the University of Chicago, the University of Illinois, the Massachusetts Institute of Technology, the National Bureau of Economic Research (Asset Pricing and Behavioral Finance Groups), New York University, Pensions and Investments Conference, the Institute for Quantitative Research in Finance (United States and Europe), Society of Quantitative Analysts, Stanford University, the University of Toronto, and Tel Aviv University. The research was supported by the National Science Foundation, Bradley Foundation, Russell Sage Foundation, the National Bureau of Economic Research Asset Management Research Advisory Group, and the National Center for Supercomputing Applications, University of Illinois.
High dynamic range video

Some cameras and systems described herein, produces a still or video images of the dynamic range is improved. Furthermore, the image may have a control or reduce motion artifacts. Furthermore, the camera and the system in some cases, the dynamic range and / or motion artifacts to achieve the desired movie effect is adjusted. FIELD 3A
Contextually Defined Postural Markers Reveal Who ’ s in Charge : Evidence from Small Teams Collected with Wearable Sensors

Extant research shows that meaningful information about social interactions can be gained by studying ‘honest signals’. Honest signals represent aspects of communication not captured directly by content semantics, but rather by factors such as body language and proxemics. In this regard, research employing wearable technology such as the sociometric badge developed by the MIT Media Lab has proven to be particularly useful for analyzing the interactions of humans in work environments. Such research has tended to take a dyadic or network perspective. However, in this study, inspired by human activity recognition research, we investigate the possibility of identifying employees and differentiating their group-functions based on behavior, with particular emphasis on identifying those in positions of leadership. Working with a high-resolution dataset collected using sociometric badges deployed during small team meetings in a European financial services firm, and applying multi-class classification, we reveal that individual accelerometer-derived posture movement (left-right and frontback) and speaking volume (from a microphone located closest to a focal participant, thus also capturing information pertaining to posture) are particularly strong features for identification. Across all models, we achieve an average of 73% accuracy, with reasonably balanced precision and recall across individuals. Introduction Wearable technology (WT) encompasses worn devices that collect information about a user, and / or relay and display information to that user. WT research overlaps with Human Activity Recognition (HAR) research, employing individual-level analysis based on machine learning classification and signal processing for human activity pattern recognition [1,2,3,4,5], or group-level analysis based on methodologies such as social signal processing and network analysis [6,7,8,9,10,11]. The latter is particularly complimentary to the domain of workforce analytics and wearable-enabled organizational behavior research [12,13,14,15] and the study of social dynamics within organizations more broadly [16,17]. However, one notable opportunity at the intersection of these perspectives is to leverage what is known about approximation using data from wearable devices at an individual level, and to transfer this approach into workforce analytics as a basis for developing approaches to machine learning-based employee identification. One area of application for such an approach is in the identification of leaders, a fundamental scenario in
Effect of adding different additives on silage quality and milk production of lactating crossbred cows

The objective of this study was to determine the effect of urea-molasses and di-calcium phosphate additives on silage quality and milk yield of cows. Hence, three types of silages were prepared from Napier fodder namely-Napier silage, urea and molasses added Napier silage (UMN); and di-calcium phosphate added Napier (DCPN) silage. These types of silage fed to the selected nine lactating Holstein-Friesian crossbred cows and divided into three groups considering three of each. Along with 5 kg of respective silages, ad-libitum rice straw and 3 kg concentrate mixture supplied to each group of cows. Physical attributes of all prepared silages were possessing characteristics of good quality silage. Dry matter content in UMN and DCPN silages were 1.67 and 1.01% higher than Napier silage. UMN silage had 1.59 and 2.33% lower ADF from Napier and DCPN silage, respectively. Again, 1.29% higher NH3-N presents in UMN silage than Napier silage. From 1st to 4th fortnight milk yield data it was found that 23.70, 23.19 and 27.06% milk production increased those cows received Napier, UMN and DCPN silage, respectively. Considering above these, it might be concluded that addition of di-calcium phosphate as additive during silage making would be beneficial for the dairy farmers. Asian Australas. J. Biosci. Biotechnol. 2018, 3 (1), 40-44
Indoor Environmental Quality ( IEQ ) Title Comparison of mean radiant and air temperatures in mechanically-conditioned commercial buildings from over 200 , 000 field and laboratory measurements

We assessed the difference between mean radiant temperature (t? ̅? ) and air temperature (ta) in conditioned office buildings to provide guidance on whether practitioners should separately measure t? ̅? or operative temperature to control heating and cooling systems. We used measurements from 48 office buildings in the ASHRAE Global Thermal Comfort Database, five field studies in radiant and all-air buildings, and five test conditions from a laboratory experiment, including both radiant and all-air spaces. Considering only the ASHRAE Global Thermal Comfort Database because it is the largest and most representative dataset, under typical office conditions, the median absolute difference (e.g., disregarding direction of the difference) between t? ̅? and ta was 0.4 °C (with interquartile range = 0.4 °C), and more specifically, the median difference shows that t? ̅? was 0.4 °C (with interquartile range = 0.4 °C) warmer than ta. In the radiant cooled laboratory tests, t? ̅? was significantly (p<0.05) cooler than ta (average difference -0.1 °C) while in the all-air cooled laboratory tests t? ̅? was significantly (p<0.05) 20 warmer than ta (average difference +0.3 °C). While these observations are significant, the effect sizes are negligible to small based on Cohen’s d and Spearman’s rho. These observations indicate that t? ̅? and ta are typically closer in radiantly cooled spaces than in all-air cooled spaces. The results suggest that ta measurements are sufficient to estimate t? ̅? under typical office conditions, and that separately measuring t? ̅? or operative temperature is not likely necessary to improve thermal comfort, especially in buildings with radiant systems. Furthermore, spatial and temporal variations in ta can be greater than the difference between t? ̅? and ta at any one location in a thermal zone, thus we expect that such variations have a greater impact on occupant thermal comfort than the differences between t? ̅? and ta. Center for the Built Environment, UC Berkeley 2019 https://escholarship.org/uc/item/2sn4v9xr
Numerical thermo-elasto-plastic analysis of residual stresses on different scales during cooling of hot forming parts

In actual research, more and more attention is paid to the understanding of residual stress states as well as the application of targeted residual stresses to expand liftime or stiffness among other things. In course of that, the numerical simulation and analysis of the forming process of components, which goes along with the evolution of residual stresses, plays an important role. Temperature dependent forming processes, such as hot bulk forming, offer the opportunity to adjust material parameters, e.g. deformation state, temperature profile or cooling media, independently. Hence, the upsetting test of a cylinder with an eccentric hole at high temperatures on different scales is examined. In this contribution, we focus on the mircoscopic and mesoscopic level. This multiscale view enables a detailed description of phenoma on the microscale such as the lattice shearing from face-centered cubic austenite unit cells to body-centered tetragonal martensite cells and is directly related to the typical classification of residual stresses following [1]. A combination of a Multi-Phase-Field model, see [2], and a twoscale Finite Element method, see [3] is utilized for numerical analysis. A first microscopic simulation considers the lattice change, such that the results can be homogenized and applied on the mesoscale. Based on this result, a polycrystal consisting of a certain number of austenitic grains is built and the phase transformation from austenite to martensite is described with respect to the mesoscale. Afterwards, a twoscale Finite Element simulation is applied to introduce plastic effects and compute resulting residual stress states. In this contribution, the work flow will be explained and some first results will be discussed.