Miracle-dz/UniFAR-FTUs huggingface dataset:
Khuri-Treiman equations for 
3π
 decays of particles with spin

Khuri-Treiman equations have proven to be a useful theoretical tool in the analysis of 3-body decays, specially into the $3\pi$ final state. In this work we present in full detail the necessary generalization of the formalism to study the decays of particles with arbitrary spin, parity, and charge conjugation. To this extent, we find it most convenient to work with helicity amplitudes instead of the so-called invariant amplitudes, specially when dealing with the unitarity relations. The isobar expansions in the three possible ($s$-, $t$-, and $u$-) final channels are related with the appropriate crossing matrices. We pay special attention to the kinematical singularities and constraints of the helicity amplitudes, showing that these can be derived by means of the crossing matrix.
Optimization of Interval Type-2 Fuzzy Logic Controller for Uncertain Inverted Pendulum System

In this paper, an uncertain inverted pendulum system is controlled by an IT2 fuzzy logic controller (IT2 FLC) which was optimized by the particle swarm optimization (PSO) algorithm. The IT2 FLC, as an extension of the type-1 fuzzy logic controller (T1 FLC), has better control performance in dealing with uncertainties than T1 FLC. However, IT2 FLC has more complexity because the parameters of the IT2 FLC are more than the parameters of T1 FLC, so it is difficult to select appropriate parameters to get better performance. The PSO algorithm is used to optimize several parameters of IT2 FLC via two cost functions. According to simulations, the performance of the IT2 FLC is optimized by the PSO algorithm is better than the IT2 FLC without optimization, and the IT2 FLC has better performance in dealing with uncertainties than T1 FLC.
The massive cluster in front of the Orion nebula cluster

Aims. The aim of this work is to characterize the stellar population between Earth and the Orion A molecular cloud where the wellknown star formation benchmark Orion nebula cluster (ONC) is embedded. Methods. We used the denser regions the Orion A cloud to block optical background light, effectively isolating the stellar population in front of it. We then used a multi-wavelength observational approach to characterize the cloud’s foreground stellar population. Results. We find that there is a rich stellar population in front of the Orion A cloud, from B-stars to M-stars, with a distinct 1) spatial distribution; 2) luminosity function; and 3) velocity dispersion from the reddened population inside the Orion A cloud. The spatial distribution of this population peaks strongly around NGC 1980 (iota Ori) and is, in all likelihood, the extended stellar content of this poorly studied cluster. We infer an age of ∼4−5 Myr for NGC 1980 and estimate a cluster population of about 2000 stars, which makes it one of the most massive clusters in the entire Orion complex. This newly found population overlaps significantly with what is currently assumed to be the ONC and the L1641N populations, and can make up for more than 10−20% of the ONC population (30−60% if the Trapezium cluster is excluded from consideration). What is currently taken in the literature as the ONC is then a mix of several intrinsically different populations, namely 1) the youngest population, including the Trapezium cluster and ongoing star formation in the dense gas inside the nebula; 2) the foreground population, dominated by the NGC 1980 cluster; and 3) the poorly constrained population of foreground and background Galactic field stars. Conclusions. Our results support a scenario where the ONC and L1641N are not directly associated with NGC 1980, i.e., they are not the same population emerging from its parental cloud, but are instead distinct overlapping populations. The nearest massive star formation region and the template for massive starand cluster formation models is then substantially contaminated by the foreground stellar population of the massive NGC 1980 cluster, formed about 4–5 Myr ago in a different, but perhaps related, event in the larger Orion star formation complex. This result calls for a revision of most of the observables in the benchmark ONC region (e.g., ages, age spread, cluster size, mass function, disk frequency, etc.).
Multi‐layer power system tearing methodology for EMT‐TS hybrid parallel simulation

: Due to the fast development of UHVDC, the power transferring through HVDCs takes a great part of the power from West China to East China. The response for multiple-coupled HVDCs can only be simulated through EMT programmes. To increase the simulation accuracy, the EMT-TS Hybrid simulation has been used in studies of the power system operation. Currently, the EMT-TS hybrid simulation speed is too slow to be unaffordable. This paper presents a novel power system tearing technology to greatly improve the simulation speed in EMT-ST Hybrid Simulation. The TS network is teared according to obtain network islands as many as possible, while the EMT network is teared through the combined transmission line and electric nodes. An algorithm is supposed to form the EMT-ST sub-network groups, which has no coupling with each other. Then, a novel parallel programme structure is proposed to use this EMT-ST sub-network groups to realise the parallel simulation and speedup the simulation. The case studies of the grids with seven HVDCs and 3000 nodes show that the proposed method could greatly improve the simulation speed without lowering precision.
Online Surveys and Digital Demography in the Developing World: Facebook Users in Kenya

Digital platforms such as Facebook, Twitter, Wikipedia, and Amazon Mechanical Turk have transformed the study of human behavior and provided access to new subject pools for academic research. In our study, we leverage the Facebook Advertising Platform to conduct online surveys in the developing world. We assess the value of Facebook in Kenya, which has been chosen as a case study because it represents an average example of mobile and internet use on the African continent, and because we were able to synchronize our data collection with new rounds of the Afrobarometer survey and the 2019 national census. After a brief comparison of the 'audience estimates' produced by the Facebook Advertising Platform with population estimates from Kenya's 2009 census, we present the results of an online survey pilot run in July 2019. We compare the characteristics of the 957 online respondents to those surveyed by the 2016 Afrobarometer. We conclude with a discussion of next steps for the full scale study.
Real Exchange Rate Volatility , Trade and the Common Supplier Effect ∗

This paper examines the impact of the commonality of a country’s trade partners and bilateral trade on real exchange rate volatility. We construct new measures of trade commonality and bilateral trade and use a large panel of cross-country data over 1970–97 to test these channels. Results strongly support the hypothesis that countries with more common sets of suppliers of traded goods and larger bilateral trade experience smaller bilateral real exchange rate volatility. This result is robust across different sub-samples. These empirical findings are shown to be consistent with recent international trade models that highlight multi-country trade linkages.
Mean and variance causality between the Cyprus Stock Exchange and major equities markets by

This paper examines the issue of mean and variance causality across four equities markets using daily data for the period 1996-2002. We apply the testing procedure developed by Cheung and Ng (1996) in order to test for mean and variance spillovers. The main findings are: (i) In contrast to the findings of previous studies, EGARCH-M processes characterize each stock returns series in all markets; (ii) There is substantial evidence of causality in both mean and variance with the causality in mean largely being driven by the causality in variance; and (iii) The results indicate the stock markets of Athens, London and New York are the major exporters of causality and the stock market of Cyprus is an importer of causality.
Loop Quantum Gravity and the The Planck Regime of Cosmology

The very early universe provides the best arena we currently have to test quantum gravity theories. The success of the inflationary paradigm in accounting for the observed inhomogeneities in the cosmic microwave background already illustrates this point to a certain extent because the paradigm is based on quantum field theory on the curved cosmological space-times. However, this analysis excludes the Planck era because the background space-time satisfies Einstein’s equations all the way back to the big bang singularity. Using techniques from loop quantum gravity, the paradigm has now been extended to a self-consistent theory from the Planck regime to the onset of inflation, covering some 11 orders of magnitude in curvature. In addition, for a narrow window of initial conditions, there are departures from the standard paradigm, with novel effects, such as a modification of the consistency relation involving the scalar and tensor power spectra and a new source for nonGaussianities. Thus, the genesis of the large scale structure of the universe can be traced back to quantum gravity fluctuations in the Planck regime. This report provides a bird’s eye view of these developments for the general relativity community.
In fl uence of moderate electric fi elds on gelation of whey protein isolate

Proteins are one of the food constituents most affected by heating, and some of the changes involve their unfolding, denaturation and gelation. Ohmic heating has often been claimed to improve the quality of foodstuffs due to its uniform heating and (putative) presence of a moderate electric field (MEF). However, this is still subject to discussion, so it is important to determine the effect of ohmic heating and of its MEF upon food constituents. Hence, the aim of this work was to evaluate the effects of MEF on denaturation, aggregation and viscoelastic properties of whey protein isolate (WPI), and compare them with those obtained via conventional heating under identical treatment conditions (up to 30 min at 85 C). Results have shown that MEF interferes with whey protein unfolding and aggregation pathways at relatively high temperatures. MEF treatments have resulted in WPI solutions possessing more 8 and 10% of native b-Lactoglobulin and a-Lactalbumin, respectively, after 30 s of heating at 85 C, when compared with a conventional heating method. Protein aggregates fromMEF-treatedWPI solutions presented a maximum increase in size of 78 nm, whereas conventional heating produced an increase of 86 nm. Unlike in conventional heating, aggregation of whey proteins during MEF was not sufficiently strong to form a true elastic gel network, since decreases in both storage and loss modulus were observed following MEF treatment. Our results suggest that MEF may provide a novel method for production of a whey protein matrix with distinctive gel-forming properties. © 2014 Elsevier Ltd. All rights reserved.
Critical success factors for employee suggestion schemes : a literature

Employee suggestion schemes have existed for many years and numerous articles on this subject have been published over the last several decades. These schemes have been studied from many perspectives to illustrate their objectives, nature, content, processes, significance and benefits. Arguments have been made with respect to successes and failures of suggestion schemes. Although organizations widely use suggestion schemes to elicit the creative ideas of their employees, sustaining an effective suggestion scheme is still a challenge. The purpose of this paper is to extract critical success factors and critical success criteria to suggestion schemes and to discuss the importance of these factors on suggestion system sustainability. This is a literature review paper. It identifies 23 critical success factors and 9 critical success criteria for suggestion schemes. It also discusses the interconnection between critical success factors and critical success criteria. Further, the frequency of each of the factors is also presented. It recognizes the lack of work on assessment frameworks for suggestion scheme sustainability. This paper should be of value to practitioners of suggestion schemes and to academics who are interested in knowing how this program has evolved, where it is today and what future it holds. It offers practical help to an individual starting out on research on sustainability of suggestion schemes.
Dynamic compliance analysis of position-based impedance control for the LHDS of legged robot

Hydraulic drive mode enables legged robots to have excellent characteristics, such as greater power-to-weight ratios, higher load capacities, and faster response speeds than other robots. Nowadays, highly integrated valve-controlled cylinder, called hydraulic drive unit (HDU), is employed to drive the joints of these robots. However, various robot control issues exist. For example, during the walking process of legged robots, different obstacles are encountered, making it difficult to control such robots because the load characteristics of the ends of their feet change with the environment. Furthermore, although the adoption of HDUs has resulted in high-performance robot control, the hydraulic systems of these robots still have problems, such as strong nonlinearity, complex load characteristics and time-varying parameters. Consequently, robot control is very difficult and complex. In this paper, the leg hydraulic drive system(LHDS) of legged robots is studied. First, the mathematical model of HDU position control system is built. Then, combined with kinematics, statics and dynamics of the leg mechanical structure, the position-based impedance control method is applied to LHDS. Moreover, the serial-parallel composition of dynamic compliance of position-based impedance control is analyzed and three key factors influencing the impedance control accuracy are found, which is the main contribution of our paper. Finally, the key factors proposed in this paper are verified experimentally by using both LHDS and HDU performance test platform. The theories and experiments proposed in this paper provide theoretical foundation for the compensation of position-based impedance control. INDEX TERMS dynamic compliance, position-based impedance control, hydraulic drive unit (HDU), legg hydraulic drive system(LHDS)
Recent advances in energy efficient-QoS aware MAC protocols for wireless sensor network

Wireless sensor networks (WSNs) is a distribution of several tiny, low-cost sensor nodes, wirelessly connected altogether for the purpose of monitoring physical or environmental conditions. Due to the vast interest for WSN, a rapid technological breakthrough has been observed in sensor elements such as processor, operating system, radio, and battery. From the perspective of seven layer approach, the medium access control (MAC) protocols are identified as the most crucial element, being responsible for coordinating communication amongst the sensor nodes. In addition, the functionality of the WSN MAC protocol has a subtle influence on parameters such as battery consumption, packet collision, network lifetime and latency. In this paper, we survey some of the most recent WSN contention-based, scheduling-based, and hybrid MAC protocols by focusing on their underlying principle, various advantages and limitations and their applications. Treating energy saving as the benchmark, further examining the directed towards the treatment of quality of service (QoS) performance metrics within these particular protocols. The result shows that the majority of the protocols leaned towards energy conservation with other parameters are either supported partially or traded off. Latency, throughput, bandwidth utilization, channel utilization is not considered in the design of most of the protocols. Indeed, the energy domain has gotten a vital breakthrough with the advent of other modes of energy saving such as energy harvesting techniques. However, other parameters such as latency, throughput, packet loss, network and bandwidth availability that comes under QoS metrics also play a critical role in future development of MAC protocols for WSNs.
Mental Task Classification Using Electroencephalogram Signal

This paper studies the classification problem on electroencephalogram (EEG) data of mental tasks, using standard architecture of three-layer CNN, stacked LSTM, stacked GRU. We further propose a novel classifier - a mixed LSTM model with a CNN decoder. A hyperparameter optimization on CNN shows validation accuracy of 72% and testing accuracy of 62%. The stacked LSTM and GRU models with FFT preprocessing and downsampling on data achieve 55% and 51% testing accuracy respectively. As for the mixed LSTM model with CNN decoder, validation accuracy of 75% and testing accuracy of 70% are obtained. We believe the mixed model is more robust and accurate than both CNN and LSTM individually, by using the CNN layer as a decoder for following LSTM layers. The code is completed in the framework of Pytorch and Keras. Results and code can be found at this https URL.
Motivasi belajar meningkat sebesar 11,78% sedangkan Hasil belajar meningkat sebesar 17,89%. Motivasi belajar siswa meningkat dilihat dari aktifitas kelompok dalam berdiskusi, mengerjakan soal latihan, tanya jawab bersama tutor, serta turnamen antar kelompok sehingga dapat disimpulkan bahwa metode pe

Tujuan penelitian ini untuk meningkatkan motivasi dan hasil belajar menggunakan metode peer tutoriing dengan Kassitu. Pengumpulan data kuantitatif dengan soal pretest dan posttest sedangkan data kualitatif didapatkan melalui angket, dan lembar observasi. Data kuantitatif dianalisis dengan analisis deskriptif komparatif dengan melihat perbandingan nilai pre test dan pos test pra siklus, siklus 1 dan siklus 2. Data kualitatif dianalisis menggunakan analisis deskriptif kualitatif dengan mencari point penting dan informasi tambahan dari hasil observasi.
Effects of Foreign Direct Investment Inflows and Domestic Investment on Economic Growth : Evidence from Turkey Y ı

Foreign direct investment flows have increased worldwide over the past three decades in conjunction with financial globalization and thus many studies have been conducted to examine possible effects of foreign direct investment inflows on economic growth. This study investigates the relationship between economic growth and foreign direct investment inflows, domestic investment in Turkey during the period 1980–2012 by using co-integration test and vector error correction model based on autoregressive distributed lag bound test approach. We found that there was a long run relationship among the economic growth, foreign direct investment inflows and domestic investment. On the other hand our findings demonstrated that foreign direct investment inflows affected economic growth negatively in the short and long run, while gross domestic investments affected economic growth positively in the short and long run.
Mouse PGC allocation and differentiation 549 The allocation and differentiation of mouse primordial germ cells

Analysis of the lineage potency of epiblast cells of the early-streak stage mouse embryo reveals that the developmental fate of the cells is determined by their position in the germ layer. Epiblast cells that are fated to become neuroectoderm can give rise to primordial germ cells (PGCs) and other types of somatic cells when they were transplanted to the proximal region of the epiblast. On the contrary, proximal epiblast cells transplanted to the distal region of the embryo do not form PGCs. Therefore, the germ line in the mouse is unlikely to be derived from a predetermined progenitor population, but may be specified as a result of tissue interactions that take place in the proximal epiblast of the mouse gastrula. The initial phase of the establishment of the PGC population requires, in addition to BMP activity emanating from the extraembryonic ectoderm, normal Lim1 and Hnf3β activity in the germ layers. The entire PGC population is derived from a finite number of progenitor cells and there is no further cellular recruitment to the germ line after gastrulation. The XX PGCs undergo X-inactivation at the onset of migration from the gut endoderm and re-activate the silenced X-chromosome when they enter the urogenital ridge. Germ cells that are localised ectopically in extragonadal sites do not re-activate the X-chromosome, even when nearly all germ cells in the fetal ovary have restored full activity of both Xchromosomes. XXSxr germ cells can re-activate the X-chromosome in the sex-reversed testis, suggesting that the regulation of X-chromosome activity is independent of ovarian morphogenesis.
Spectrum aware clustering in cognitive radio ad hoc networks

Cognitive radio (CR) is an emerging technology developed for efficient utilization of the radio spectrum. CRN utilizes CR technology and enables the unlicensed users also referred as secondary users (SUs) to access free portions of the licensed spectrum in an opportunistic manner. To support scalability and stability in distributed CRNs also referred as cognitive radio ad hoc networks (CRAHNs), SUs are often organized into smaller groups known as clusters. Spectrum aware clustering is considered as the key technique to overcome numerous is-sues associated with the dynamic nature of CRAHNs. This article focuses on clustering in CRAHNs and presents a comprehensive review of various spectrum aware clustering algorithms presented in the literature. The article highlights notable clustering metrics and includes the description of cluster formation and maintenance process. The article also renders potential research gaps in existing research works and discusses open challenges and issues that need to be addressed for efficient clustering in CRAHNs.
IoT-Fog-Based Healthcare Framework to Identify and Control Hypertension Attack

Hypertension is a chronic disease causing risk of different types of disorders, such as hypertension attacks, cerebrovascular attacks, kidney failure, and cardiovascular diseases. To prevent such risks, statistics related to hypertension have to be monitored and analyzed in real-time. Internet of Things (IoT)-assisted fog health monitoring system can be used to monitor blood pressure (BP) and to diagnose the stage of hypertension in real-time. In this paper, IoT-fog-based healthcare system is proposed for continuous monitoring and analysis of BP statistics to predict hypertensive users. The proposed system initially identifies the stage of hypertension on the basis of user’s health parameters collected using IoT sensors at fog layer. After identifying the hypertensive stage, artificial neural network is used for predicting the risk level of hypertension attack in users at remote sites. The vital point of this paper is to continuously generate emergency alerts of BP fluctuation from fog system to hypertensive users on their mobile phones. Finally, analysis results and compiled medical information of each user are stored on cloud storage for sharing with domain experts, such as clinicians, doctors, and personal caregivers. The temporal information generated from fog layer can be utilized for providing precautionary measures and suggestions well on time for patients’ wellness. Experimental results reveal that proposed framework achieves low response time, high accuracy, and bandwidth efficiency.