Miracle-dz/UniFAR-FTUs huggingface dataset:
Simulated Phase Behavior of Model Surfactant Solutions

We performed molecular dynamics simulations in an attempt to model the phase behavior of a nonionic surfactant. We employed a coarse-grained model, parametrized to yield the phase behavior of the corresponding physical system, instead of using a realistic model with its severe spatial and temporal limitations. Within that model our surfactants are composed of chains of Lennard−Jones sites connected by harmonic springs, and the solvent is modeled as a Lennard−Jones fluid. The simulated systems comprise up to 100 000 sites with a maximum of 12 sites per surfactant molecule. We examine the effect of different conditions (temperature and concentration) and different model parameters (head/tail size and ratio, strength of interaction between the different sites). Our simulations show that some of the real system's characteristics can be mirrored by the coarse-grained model, whereas some aspects cannot.
A Comprehensive Study of Renewable Energy Management for 5G Green Communications: Energy Saving Techniques and Its Optimization

: Wireless communication has reached new heights with the increasing subscriber demands thus leading to emerging of environmental problems. Green communication is capable to offer an effective solution for addressing these issues. It’s mitigation to the problem of CO 2 emission and better performance has drawn researcher’s attention in past few years. It is also being thought as an energy efficient communication. The upcoming 5G networks are undergoing standardization and need to have least power consumption. To meet the demands of an increased capacity, an improved data rate, and a better quality of the service of the next-generation networks, there is a need to adopt energy-efficient architectures. The 5G networks exhibit relevant services for critical and timely applications for greater aspects in the smart cities and grid. In the present day electricity markets, 5G provides new business models to the energy providers and improves the way the utility communicates with the communication systems. Hence, a green communication is an urgent need. In this paper we discussed about the study renewable energy and various techniques for the power optimization of the upcoming 5G networks.
Multiple Levels of Meaning-Making The First Principles of Changing Meanings in Development and Therapy

We see meaning about one’s self in relation to the world of people and things, and in relation to one’s own self, as a core organizing concept in approaches as varied and contentious as Body Psychotherapies, psychoanalysis, psychodynamics, Cognitive Behavioral Therapy, dialectical cognitive therapies, dyadic therapies, attachment therapies, relational therapies, and others (Tronick, 2007; Harrison, 2003; Ogden, 1997; Modell, 1993). Meanings about one’s self are made continuously and simultaneously, in real time, at multiple levels, and by multiple body and brain systems. Loss of any of these meanings— the meaning about one’s self to one’s self, or one’s self to the world— leads to serious psychopathology. Indeed, a failure to “make meaning” is a psychic catastrophe: a trauma (Modell, 1993). More common than failures are the meanings made about more mundane events that distort one’s sense of the world and one’s self. Such meanings often generate further distortions and increasingly insidious debilitations. Critical to our view is the idea that these endogenous meaningmaking processes demand realtime seeking of information through active engagement by the individual with the world of people, things, and the individual’s own self in order to apprehend, in both body and mind, the information that is integrated with past meaning into the meaning of the relation of the self to the world. Moreover, and often underappreciated, meaningmaking is a psychobiological process that involves not only the brain, but other somatic systems that generate implicit meanings and memories that shape our ways of being in the world. Thus, the process of making sense of the world inherently involves the whole individual in an endless and continuous process.
Phenological, Physiological and yield markers as efficient tools to identify 1 drought tolerant rice genotypes in Eastern India 2 3

36 Rice production is severely threatened by drought stress in Eastern India. To develop drought tolerant 37 varieties, selection of donors for breeding programme is crucial. Twenty one selected rice genotypes including 38 both tolerant and sensitive to drought were grown under well-watered and drought stress conditions in dry 39 seasons of two successive years of 2017 and 2018. Leaf water potential, relative water content displayed 40 significant difference among the genotypes during vegetative screening. At reproductive stage drought 41 screening, days to 50% flowering was delayed in all genotypes except N22 and Anjali (showed early flowering) 42 however grain yield and other yield related traits decreased significantly compared to well-watered condition. 43 Correlation analysis of phenological and yield related traits with grain yield revealed that tiller numbers and 44 panicle numbers are highly correlated with grain yield both under well-watered and water stress conditions and 45 contributes maximum towards grain yield. The dendrogram grouped Mahamaya, Sahabhagidhan, Poornima, 46 IBD 1, Hazaridhan, Samleshwari and Danteshwari into one cluster which performed better under water stress 47 conditions and had grain yield more than 1.69 tha -1 . Sahabhagidhan, Poornima, Vandana, and N22 displayed 48 tolerance to drought both under vegetative and reproductive conditions which could be a good selection for the 49 breeders to develop drought tolerant rice cultivars for eastern region of India.
Restructuring the West European Party Space in the Great Recession: continuity and change

The paper focuses on the impact of the Great Recession and the Euro crisis on the structuration of party competition in Western Europe. Has it served as a catalyst of long-term trends by boosting conflicts over new cultural issues and reinforcing tri-polar party configurations? Alternatively, does it invert the trends by reinvigorating economic conflicts and reconfiguring party systems in a classic bipolar left-right opposition? Theoretically, the paper combines structural and strategic approaches to party competition. Empirically, it examines six countries (Austria, Britain, France, Germany, the Netherlands, and Switzerland) from the 1970s to 2015 based on an original content analysis of mass media. Overall, the crisis has not fundamentally modified the long-term trends. Party competition continues to be structured by two dimensions, and the configurations are tri-polar at least. In addition to mainstream left and right, the populist radical right constitutes a third pole in all six countries by now.
Kernelized Similarity Learning and Embedding for Dynamic Texture Synthesis

Dynamic texture (DT) exhibits statistical stationarity in the spatial domain and stochastic repetitiveness in the temporal dimension, indicating that different frames of DT possess a high similarity correlation that is critical prior knowledge. However, existing methods cannot effectively learn a synthesis model for high-dimensional DT from a small number of training samples. In this article, we propose a novel DT synthesis method, which makes full use of similarity as prior knowledge to address this issue. Our method is based on the proposed kernel similarity embedding, which can not only mitigate the high dimensionality and small sample issues, but also has the advantage of modeling nonlinear feature relationships. Specifically, we first put forward two hypotheses that are essential for the DT model to generate new frames using similarity correlations. Then, we integrate kernel learning and the extreme learning machine into a unified synthesis model to learn kernel similarity embeddings for representing DTs. Extensive experiments on DT videos collected from the Internet and two benchmark datasets, i.e., Gatech Graphcut Textures and Dyntex, demonstrate that the learned kernel similarity embeddings can provide discriminative representations for DTs. Further, our method can preserve the long-term temporal continuity of the synthesized DT sequences with excellent sustainability and generalization. Meanwhile, it effectively generates realistic DT videos with higher speed and lower computation than the current state-of-the-art methods. The code and more synthesis videos are available at our project page https://shiming-chen.github. io/Similarity-page/Similarit.html.
Average size and size distribution of large droplets produced in a free-jet expansion of a liquid

The experimental parameters and fluid properties affecting the average size N and the size distribution P(N) of droplets formed by fragmentation of a liquid after expansion into a vacuum are investigated. The mean droplet size is found to be a function of the surface tension of the liquid, the nozzle diameter, and a characteristic flow speed. The size distribution is found to be a linear exponential distribution; measurements deviate from this distribution at small sizes if a factor which is a function of the cluster size is included in the measuring process. Good agreement with measured distributions of both positive and negative droplet ions formed from neutral 4He droplets by electron impact is found. The strong dependence of mean droplet size on source–orifice diameter found in the present analysis indicates that earlier correlations of droplet size with specific entropy in the source were useful at best only for a fixed nozzle size.
The Internet of Things: Architecture, Security Threats, and Risk Mitigation Techniques

Devices in the consumer, commercial, healthcare and industrial sectors are becoming increasingly more connected to the Internet. These interconnected devices range from smart devices in the home and wearable health monitoring devices to sensors and actuators within critical infrastructure environments. The framework of connected devices that share data is referred as the Internet of Things (IoT). There is an increasing security concern regarding this framework and devices that are considered part of IoT. As the number of devices that are able to send sensitive information over networks increases, so does the threat of this data being compromised. To mitigate and minimize this threat, research has been performed to develop a number of potential approaches to increase security levels for these IoT devices. This paper will present a few of those security risks and mitigations, as well as best practices to implement by administrators of IoT networks.
Independent Control Of Active And Reactive Powers From DFIG By Logic Fuzzy

This paper presents the study and use by simulating the fuzzy logic control of asynchronous generator dual fuel in the production of electrical energy that the . for I prepared a study of the wind system and a model of the wind turbine was established by following the study and modeling of doubly fed asynchronous. Two types of vector control have been the subject of study in this work for independent control of active and reactive power: the direct and indirect control . la fuzzy PI control is introduced to increase the robustness of markers vis-à-screw parametric variation of the machine in the simulation results obtained were compared to the validated work articles cited in the bibliography.
Mechanism of collisional spin relaxation in molecules.

We measure and theoretically determine the effect of molecular rotational splitting on Zeeman relaxation rates in collisions of cold 3 (cid:1) molecules with helium atoms in a magnetic ﬁeld. All four stable isotopomers of the imidogen (NH) molecule are magnetically trapped and studied in collisions with 3 He and 4 He . The 4 He data support the predicted 1 =B 2 e dependence of the collision-induced Zeeman relaxation rate coefﬁcient on the molecular rotational constant B e . The measured 3 He rate coefﬁcients are much larger than the 4 He coefﬁcients, depend less strongly on B e , and theoretical analysis indicates they are strongly affected by a shape resonance. The results demonstrate the inﬂuence of molecular structure on collisional energy transfer at low temperatures.
Crystallization mechanism of regioregular poly(3‐alkyl thiophene)s

The crystallization properties of three regioregular poly(3-alkyl thiophene)s (P3ATs) are studied: poly(3-hexyl thiophene) (P3HT), poly(3-octyl thiophene) (P3OT), and poly(3-dodecyl thiophene) (P3DDT). The morphology of the isothermally crystallized samples is a whisker type. The values of the enthalpy of fusion of ideal crystals (ΔH), determined from the melting point depression in the polymer–diluent system, are 99, 73.6, and 52 J/g for P3HT, P3OT, and P3DDT, respectively. The values of the equilibrium melting point (T), determined from the Hoffman–Weeks extrapolation procedure, are 300, 230, and 180 °C for P3HT, P3OT, and P3DDT, respectively. From the linear extrapolation of the P3AT data, the T and ΔH values of unsubstituted polythiophene are predicted to be 400 °C and 139 J/g, respectively. The crystallization kinetics of these polymers are studied with differential scanning calorimetry, and the Avrami exponents vary between 0.6 and 1.4, indicating one-dimensional heterogeneous nucleation with linear growth. As the P3AT whiskers are produced from the chain-folding process, the Lauritzen–Hoffman growth rate theory is applied to analyze the temperature coefficient of the crystallization rate data. Graphical plots indicate a transition from regime I to regime II during isothermal crystallization for all the P3ATs studied. The fold surface energy and the work of chain folding calculated from the slopes of the graphical plots decrease with an increase in the number of carbon atoms of the side chain. The primary crystallization process of the side-chain crystallization is very fast and is attributed to the zipping effect of the main-chain crystals. © 2002 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys 40: 2073–2085, 2002
FORMAL VERIFICATION OF LOCAL AND DISTRIBUTED PYTHON SOFTWARE TRANSACTIONAL MEMORIES

Both local and distributed Python STMs are targeting a wide range of application domains, including critical infrastructures, such as cyber-physical systems, internet of things, etc., and formal verification of such software components is considered mandatory. Recently, the push/pull semantic model of transactions has appeared as a solution that unifies a wide range of transactional memory algorithms. In this paper, we formally prove that both local and distributed Python STM implementations are serializable by constructing their push/pull model and by showing that the push/pull model satisfies the correctness criteria for the relevant push/pull semantic rules. The main contributions of the paper are the following: (i) the PSTM and DPSTM push/pull semantic model, (ii) the proofs of the relevant push/pull semantic rules, and (iii) the way how the model and the proofs have been constructed.
Going Beyond Gold: Can Equities be Safe- Haven?

Popular investment choice like fixed income, gold, and real estate has generated low returns over long horizons. Equity seems to have performed much better despite its‟ inherent risk. Although, investors prefer safe-haven assets, they are increasingly moving to equities in search for better returns. We consider whether equity could be a safe-haven investment if chosen from quality stocks‟ basket. We examine the safe-haven and hedging properties of the Nifty-50 constituent stocks over the period 2008–2020. To address this, we employ copula-based framework to model the dependence structure between stocks and five indices. We distinguish between safe-haven attributes and hedging features of the individual stocks. We show that the safe-haven properties of the Nifty-50 listed stocks are not as concentrated as gold but they show much low co-movement with the market. We call them pseudo–safe-haven as they are the safe-bets for investors seeking relatively safe-haven assets with impressive returns.
Particle Swarm Optimization-based Dark Channel

Underwater images are confronted with blurriness and poor color consistency due to the haze produced by the absorption and scattering effects of the turbid water. Dark Channel Prior (DCP) is the state-of-the-art and the algorithmic basis to solve underwater image restoration. However, the default parameters of DCP may not be applicable to underwater images with different levels of degradation. The selection of the appropriate DCP parameters for each underwater image is considered as an optimization problem and can be solved using Particle Swarm Optimization (PSO). The proposed PSO-based selection algorithm is defined by its operators: objective function, swarm size, inertial weights and acceleration coefficients. Obtaining appropriate combination of these operators are elaborated. The qualitative and quantitative evaluations observed acceptable visual improvements and measurements to underwater images applied with DCP at optimally selected parameters, in comparison to underwater images applied with DCP at default parameters. Hence, the proposed algorithm provides good adaptability and effectivity to the exhaustive search of appropriate DCP parameters.
Hierarchical ConvNets for Traffic Sign Detection and Recognition

Traffic sign detection and recognition play important role in the advances of self-driving cars and building more informative maps. In this thesis, we focus on solving the problem of traffic sign localisation, detection and recognition using deep learning methods. Despite recent literature showed that the problem is solved by applying state-of-the-art machine learning approaches and achieving superhuman classification rates 99.4%, we argue that the problem is far from being solved. We mention the limitation of the current approaches and conclude the challenges. Then, we propose methods to overcome these challenges and push forward the current limitations. Then, we present a critical analysis for the performance of the proposed method. Finally. we compare the performance of the proposed methods against the state-of-the art methods. We then mention the work that was not realised during the project, so it can be carried out in the future.
The Impact Generated by the Key Audit Matters on the Application of Audit Procedures

The international standards related to the structure of the audit report over the years have undergone significant structural changes, especially with ISA 701 (in Brazil NBC TA 701), where the audit report started to document a discretionary section called Key Audit Matters (KAM), whose objective is to disclose issues or critical points identified by the auditors, who admittedly considered important for a better understanding of the financial statements by external users, in addition to understanding the procedures performed by the auditors themselves. Through documentary analysis of 16 audit reports related to 8 financial statements without KAM (2015) and 8 financial statements with KAM (2016), as well as the respective working papers, letters of external circulation and workbooks prepared by the audit teams, obtained together with a certain relevant external audit company in the Brazilian domestic market, information was tabulated regarding the audit procedures applied, where the objective was to verify whether the need to disclose the paragraph of KAM made the auditors more skeptical in performing the audit work. By the comparative method, as well as by the application of the t-Test: two samples in pair for averages was identified strong and positive correlation between the variables tested. Thus, the results obtained suggest that the disclosure of the KAM paragraph caused an increase in the procedures performed when comparing the reports between 2015 and 2016.
Removal of Singularities for Stein Manifolds

We adapt the technique of removal of singularities to the holomorphic setting and prove a general flexibility result for holomorphic vector bundles over Stein manifolds. If D : V →W is an elliptic differential operator between holomorphic vector bundles over a Stein Manifold, then a q-tuple (θ1, . . . , θq) of holomorphic sections generating W may be deformed to an exact holomorphic q-tuple (Dφ1, . . . , Dφq) generating W . We also prove a parametric version of this theorem with holomorphic dependence on a Stein parameter X and obtain a 1-parametric h-principle. The parametric hprinciple works relative to closed complex analytic subsets A of X. As corollaries we will obtain h-principles for holomorphic immersions and free maps of Stein Manifolds.
Math Journaling in Inductive Thinking Learning Models to Enhance Students Self-Regulated Learning

The quality of educational outcomes in Indonesia so far has not shown satisfactory results. Besides, the government's very low graduation standard does not require students to work hard and does not foster students to have self-regulation in learning. This article aims to explain math journaling as an inductive thinking learning model to improve the skills of self-regulated learning (SRL). This article followed the systematic literature review (SLR) method. The researcher collected the data from books and scientific articles that discuss math journaling, inductive thinking learning models, and self-regulated learning. The collected data is then analyzed qualitatively. The analysis results indicate that math journaling is under the concept of inductive thinking learning models and a good model to improve students' self-regulated learning abilities. Based on these findings, the use of math journaling as an inductive thinking learning model is suggested as an alternative learning model to improve students' SRL abilities so that students become independent learners.
Smile, its anatomy, types, components and cosmetics in orthodontics: A review

An attractive smile is the centre of attraction of the face. The smile is the most dominant, bright, moving part of the face and hence noticed first. Currently there has been a shift from traditional treatment goals, such as ideal occlusion and cephalometric standards, to include goals embodying principles of micro esthetics and soft tissue harmony. Orthodontists have an important role to play in smile designing which involves the correction or modification of all the parts that comes in the smile frame, including the upper and lower lips, gingival exposure during smile, the size, color and shape of the teeth and the negative spaces between the tooth and the cheeks. Best esthetics in smile can only be designed by proper understanding of the structures contributing to smile and establishing a good harmony and balance between those structures.