Miracle-dz/UniFAR-FTUs huggingface dataset:
Role of LAB in silage fermentation: Effect on nutritional quality and organic acid production—An overview

Lactic acid bacteria (LAB) inocula play a key role in the preservation and fermentation of forage crops within inoculated silages. LAB is a significant group of the bacterial community as they successfully reduce pH, inhibit the survival of undesirable microorganisms and control nutrient loss in fermented silage. Ensiled plants and metabolites such as simple plant carbohydrates have been utilized by LAB (homo-fermentative and hetero-fermentative LAB) to initiate the production of organic acids including lactic and acetic acids. LAB as a biological silage additive provides stable feed value and secondary metabolic products during rapid anaerobic primary silage fermentation. They are able to ferment a large number of forage crops and also to reduce pH levels in fermented forages, which helps to suppress the growth of spoilage microorganisms. Furthermore, silage inoculants can enhance silage quality, nutritional recovery and shelf life of the inoculated product. When ingested silage, Lactobacilli in the rumen may degrade secondary plant metabolites as part of the rumen microbiota, along with endogenous enzymes. Also, the forages harvesting time are key factors in the development of essential metabolites particularly carbohydrates and proteins which is essential nutrition for LAB survival and production of organic acids. The higher population of LAB could reduce the pH faster and control of deleterious microbial growth in silage. This review presents LAB function in silage production and the potential impacts of its fermentative activity. In addition, the advantage of LAB additives in silage production is discussed, with a focus on recent literature.
Experimental confirmation of efficient island divertor operation and successful neoclassical transport optimization in Wendelstein 7-X

We present recent highlights from the most recent operation phases of Wendelstein 7-X, the most advanced stellarator in the world. Stable detachment with good particle exhaust, low impurity content, and energy confinement times exceeding 100 ms, have been maintained for tens of seconds. Pellet fueling allows for plasma phases with reduced ion-temperature-gradient turbulence, and during such phases, the overall confinement is so good (energy confinement times often exceeding 200 ms) that the attained density and temperature profiles would not have been possible in less optimized devices, since they would have had neoclassical transport losses exceeding the heating applied in W7-X. This provides proof that the reduction of neoclassical transport through magnetic field optimization is successful. W7-X plasmas generally show good impurity screening and high plasma purity, but there is evidence of longer impurity confinement times during turbulence-suppressed phases.
Instagram Influencer Selection Analysis on the SME’s Brand Campaign in Indonesia using Correlation Analysis (Case Study: IAM.ID)

The number of Small Medium Enterprises (SMEs) in Indonesia reached 64,194,057 units in 2018 and made a good impact on Indonesia’s economy. However, it turns out that SMEs face various problems, such as business strategy, marketing, and branding. Only 12% of SMEs currently use digital as one of their platforms and most of these businesses are still in stagnant condition. Currently, SMEs are starting to use influencers as their marketing strategy on Instagram. However, it is difficult to find a suitable influencer for their product or service due to so many influencers with various categories. The market potential in this field is quite high considering that Indonesia has the largest number of social media users in the world, especially Facebook and Instagram. Globally 5-10 billion USD marketing is done through influencer marketing in 2020, 65% of companies plan to use more influencer marketing and 92% of customers trust personal recommendations more than conventional advertising. An analysis was conducted of the selection of Instagram influencers on the brand campaign in Indonesia through a case study from IAM.ID. This company provides solutions in the fields of influencer marketing and technology with influencers data analytics. IAM.ID services include content creations, endorsement, store visits, and influencer’s community. In this research, the hypothesis is based on the level of engagement and influencer category. Influencers are considered more effective if they match the advertised brand. Influencer data analytics are obtained from engagement rate (ER) influencers, the number of followers, influencer categories, and content analysis. Brand analysis is obtained from brand preferences obtained through questionnaires. Then a correlation analysis was carried out on the ER campaign and the result was that both the number of followers and ER influencers had a strong relationship to the ER campaign. Besides, the suitability of the influencer category can also be checked using content analysis.
Warm-up spectroscopy of quadrupole-split nuclear spins in 
n
-GaAs epitaxial layers

The e ﬃ ciency of the adiabatic demagnetization of nuclear spin system (NSS) of a solid is limited, if quadrupole e ﬀ ects are present. Nevertheless, despite a considerable quadrupole interaction, recent experiments validated the thermodynamic description of the NSS in GaAs. This suggests that nuclear spin temperature can be used as a probe of nuclear magnetic resonances. We implement this idea by analyzing the modiﬁcation of the NSS temperature in response to an oscillating magnetic ﬁeld at various frequencies, an approach termed as the warm-up spectroscopy. It is tested in a n -GaAs sample where both mechanical strain and built-in electric ﬁeld may contribute to the quadrupole splitting, yielding the parameters of electric ﬁeld gradient tensors for 75 As and both Ga isotopes, 69 Ga and 71 Ga.
Synergy Emergence in Deep Reinforcement Learning for Full-Dimensional Arm Manipulation

Full-dimensional natural arm manipulation is a challenging task in the field of model-based control due to its high degree of freedom and unknown dynamics of the given system. Deep reinforcement learning (DRL) offers a promising model-free approach for handling high-dimensional robotics problems. Although impressive results for the arm manipulation task have been reported, it still remains an open problem on how we can create human-like synergetic reaching motion using learning algorithms. In this study, we apply DRL for managing full-dimensional arm manipulation in a simulation study, and verify the relations among motion error, energy, and synergy emergence, to reveal the mechanism of employing motor synergy. Although synergy information has never been encoded into the reward function, the synergy naturally emerges along with feedforward control, leading to a similar situation as human motion learning. To the best of our knowledge, this is a pioneer study demonstrating the error and energy optimization issue exists behind the motor synergy employment in DRL for reaching tasks. In addition, our proposed feedback-augmented DRL controller shows better capability over DRL in terms of synergy development and the coupled criteria of error-energy index. This implies that feedback control can support the learning process under redundancy by voiding unnecessary random exploration.
Optimal observing strategies for velocity-suppressed dark matter annihilation

Numerous particle models for the cosmological dark matter feature a pair-annihilation rate that scales with powers of the relative velocity between the annihilating particles. As a result, the annihilation rate in the central regions of a dark matter halo can be significantly lower than at the halo’s periphery for particular ambient gravitational potentials. While this might be offset by an increasing dark matter pair number density in the inner halo, it raises the question: what angular region for dark matter models with velocity-suppressed annihilation rates optimizes signalto-noise? Here, we consider simplified background models for galactic and extragalactic targets and demonstrate that the optimal observing strategy varies greatly case-by-case. Generally, a bright central source warrants an annular region of interest, while a flatter background warrants as large as possible an angular region, possibly including the central regions.
Crystal structure of poly[diaqua-µ2-(E)-5-oxo-4-((5-oxo-1,5-dihydro-4H- 1,2,4-triazol-4-yl)diazenyl)-4,5-dihydro-1,2,4-triazol-1-ide-κ3O:O:N) sodium], C4H7N8NaO4

Abstract C4H7N8NaO4, monoclinic, C2/c (no. 15), a = 19.42(2) Å, b = 6.514(5) Å, c = 15.38(1) Å, β = 93.23(2)°, V = 1942.9 Å3, Z = 8, Rgt(F) = 0.0631, wRref(F2) = 0.1660, T = 293 K.
A 75–305-GHz Power Amplifier MMIC With 10–14.9-dBm Pout in a 35-nm InGaAs mHEMT Technology

The demonstration of a 75–305-GHz power amplifier (PA) monolithic microwave integrated circuit (MMIC) is presented in this letter. The PA is based on an eight-cell traveling-wave unit amplifier (UA). Each cell contains an RF cascode with two two-finger transistors with a gate width of 20 $\mu \text{m}$ each. In the output stage, a balanced configuration combines two UAs with Lange couplers. In front, a third UA is used as a driver amplifier. The PA MMIC is fabricated in a 35-nm gate-length metamorphic high-electron-mobility transistor technology. From 75 to 305 GHz, the PA yields a minimum output power of 10 dBm with an average value of 12.8 dBm. At 200 GHz, a peak output power and PAE of 14.9 dBm and 6.6% is achieved, respectively. To the best of the authors’ knowledge, this is the first PA MMIC with an octave-bandwidth that provides an output power of 10 dBm at 300 GHz.
Estudo comparativo de métricas de ranqueamento em redes complexas utilizando coeficientes de correlação

Resumo—A classificação e o ranqueamento de vértices é um tema muito estudado em redes complexas. Existem na literatura diversas métricas utilizadas na classificação de vértices em uma rede. Este trabalho visa comparar as diferentes métricas calculando o coeficiente de correlação entre elas. Resultados demonstram que as métricas Grau e Hub apresentam a maior correlação, ranqueando os vértices de maneira mais similar, enquanto as métricas Hub e PageRank obtiveram o menor coeficiente de correlação.
Dynamic modelling of covid-19 and the use of “Merah Putih” vaccination and herbal medicine treatment as optimal control strategies in Semarang city Indonesia

The Corona virus is a disease that threatens human population on earth in early 2020, the first infection began in China, is thought to be a virus that host in mammals and then able transmits into human body, this present paper will describe dynamic system of Covid-19, analyzing direction of the equilibrium, Disease Free Equilibrium (DFE) and Endemic Equilibrium (EE), which can be done by determining dimensionless number of Basic Reproduction Number (R 0). And then we put vaccine and treatment as control variables to reduce the infected population, we use the vaccinations and treatments recommended by the Indonesian government. Furthermore, we use Pontryagin Minimum Principle to find optimal solution of the control. Optimal control method in this paper is fixed time and fixed end point, means that we are determined the duration of the control and set goal for reaching the final state point. This optimal control will aim to minimize the number of infected population and values (cost) of control measures. Numerical calculations also performed to illustrate the graph.
Model for Predicting Customer Desertion of Telephony Service using Machine Learning

In the present study, it is observed that many people are affected by the services provided by telephony, who leave the service for different reasons, for which the use of a model based on decision trees is proposed, which allows predicting potential dropouts from Customers of a telecommunications company for telephone service. To verify the results, several algorithms were used such as neural networks, support vector machine and decision trees, for the design of the predictive models the KNIME software was used, and the quality was evaluated as the percentage of correct answers in the predicted variable. The results of the model will allow acting proactively in the retention of clients and improves the services provided. A data set with 21 predictor variables that influence customer churn was used. A dependent variable (churn) was used, which is an identifier that determines if the customer left = 1, did not leave = 0 the company's service. The results with a test data set reach a precision of 91.7%, which indicates that decision trees turn out to be an attractive alternative to develop prediction models of customer attrition in this type of data, due to the simplicity of interpretation of the results.
Exploring Exciton and Polaron Dominated Photophysical Phenomena in Ruddlesden-Popper Phases of Ban+1ZrnS3n+1 (n = 1-3) from Many Body Perturbation Theory.

Ruddlesden-Popper (RP) phases of Ban+1ZrnS3n+1 are an evolving class of chalcogenide perovskites in the field of optoelectronics, especially in solar cells. However, detailed studies regarding its optical, excitonic, polaronic, and transport properties are hitherto unknown. Here, we have explored the excitonic and polaronic effect using several first-principles based methodologies under the framework of Many Body Perturbation Theory. Unlike its bulk counterpart, the optical and excitonic anisotropy are observed in Ban+1ZrnS3n+1 (n = 1-3) RP phases. As per the Wannier-Mott approach, the ionic contribution to the dielectric constant is important, but it gets decreased on increasing n in Ban+1ZrnS3n+1. The exciton binding energy is found to be dependent on the presence of large electron-phonon coupling. We further observed maximum charge carrier mobility in the Ba2ZrS4 phase. As per our analysis, the optical phonon modes are observed to dominate the acoustic phonon modes, leading to a decrease in polaron mobility on increasing n in Ban+1ZrnS3n+1 (n = 1-3).
NMPC trajectory planner for urban autonomous driving

This paper presents a trajectory planner for autonomous driving based on a Nonlinear Model Predictive Control (NMPC) algorithm that accounts for Pacejka's nonlinear lateral tyre dynamics as well as for zero speed conditions through a novel slip angle calculation. In the NMPC framework, road boundaries and obstacles (both static and moving) are taken into account with soft and hard constraints implementation. The numerical solution of the NMPC problem is carried out using ACADO toolkit coupled with the quadratic programming solver qpOASES. The effectiveness of the proposed NMPC trajectory planner has been tested using CarMaker multibody models. The formulation of vehicle, road and obstacles' models has been specifically tailored to obtain a continuous and differentiable optimisation problem. This allows to achieve a computationally efficient implementation by exploiting automatic differentiation. Moreover, robustness is improved by means of a parallelised implementation of multiple instances of the planning algorithm with different spatial horizon lengths. Time analysis and performance results obtained in closed-loop simulations show that the proposed algorithm can be implemented within a real-time control framework of an autonomous vehicle.
Preparation of Three-Dimensional Co3O4/graphene Composite for High-Performance Supercapacitors

Here, we developed a simple and efficient route for the preparation of three-dimensional (3D) Co3O4-anchored graphene composites using the sacrificial template-assisted method and the subsequent deposition process of Co3O4 nanoparticles. As structural guiding materials, polystyrene (PS) spheres provide 3D porous architectures with a high surface area. 3D porous graphene materials serve as conductive supporters for the deposition of Co3O4 nanoparticles through precipitation growth. The 3D porous composite structures of Co3O4/graphene composites were intensively investigated using scanning electron microscope, transmission electron microscope, and X-ray diffraction. The 3D Co3O4/graphene composites show a high specific capacitance of 328 F g−1 with efficient and fast charge–discharge process in aqueous 6 M KOH electrolyte. In addition, the composites provide a good cycle lifetime, which retained 98% capacitance retention over 2000 cycles.
RCIVMM: A Route Choice-Based Interactive Voting Map Matching Approach for Complex Urban Road Networks

With the enhancement of location-acquisition technologies, GPS trajectories play an essential role in data-driven intelligent transportation applications, which requires an accurate approach to match raw GPS trajectories to road segments on a digital map. However, for complex urban roads containing elevated roads and surface roads, map matching for low-frequency GPS data is still challenging. This article aims to address the biases and instability problem in existing approaches. To this end, we combine the spatial-temporal characteristics of GPS data in complex roads with driving behaviours and present a novel global map matching method including truncated density clustering algorithm, statistic features based spatial-temporal analysis, and driving-behaviour-based track modification. Additionally, a weighted-matrix based interactive voting algorithm is proposed to select the best results from a global perspective. The experiments are conducted with two real GPS trajectory datasets under three road conditions. The result shows that our approach outperforms state-of-art approaches for urban complex road networks in both accuracy and efficiency.
AWCD: An Efficient Point Cloud Processing Approach via Wasserstein Curvature

In this paper, we introduce the adaptive Wasserstein curvature denoising (AWCD), an original processing approach for point cloud data. By collecting curvatures information from Wasserstein distance, AWCD consider more precise structures of data and preserves stability and effectiveness even for data with noise in high density. This paper contains some theoretical analysis about the Wasserstein curvature and the complete algorithm of AWCD. In addition, we design digital experiments to show the denoising effect of AWCD. According to comparison results, we present the advantages of AWCD against traditional algorithms.
Growth performance, well-being, and gut microbial population of broilers raised in cages and floor pens under the hot and humid tropical climate

Abstract The study was carried out to compare the growth performance, gut microbiota, incidence of footpad dermatitis (FPD), leg weakness, physiological, and immunological responses in broilers kept in cage (CS) and floor pen (FS) rearing systems under a tropical environment. One-day-old male Cobb 500 chicks were allocated to either three-tiered wire-floored battery cages or floor pens with wood shavings. The body weight on day 42 and feed intake from days 1 to 42 of caged chickens were lower than those of chickens reared in floor pens. However, the caged chickens had significantly better overall (days 1–42) feed conversion ratios than those on floor pens. The FS system was detrimental to the incidence of FPD. The FS birds showed higher and lower caecal counts of Escherichia coli and Salmonellae, respectively than the CS birds. The FS birds had longer durations of latency-to-lie than their caged counterparts, which suggested that the former had a lower incidence of leg weakness. Higher serum basal concentrations of corticosterone, ovotransferrin and ceruloplasmin were noted in the FS chickens compared to the CS group. Antibody titre against Newcastle disease vaccinations was not affected by the rearing system. In conclusion, the cage rearing system appeared to benefit performance, the incidence of FPD, physiological response, fear reactions, and intestinal population of E. coli in broiler chickens under the hot and humid tropical conditions. However, raising broilers on floor pens improves body weight and leg strength, and reduces the caecal Salmonellae population compared to caged broilers. HIGHLIGHTS Caged broilers have better feed efficiency and lower caecal Escherichia coli population and incidence of food-pad dermatitis than those on floor pens. Raising broilers on floor pens improves body weight and leg strength, and reduces the caecal Salmonellae population compared to caged broilers. Broilers on floor pens are more physiologically distressed than their caged counterparts.
Gravitational Wave Signatures of Black Hole Quasinormal Mode Instability.

Black hole (BH) spectroscopy has emerged as a powerful approach to extracting spacetime information from gravitational wave (GW) observed signals. Yet, quasinormal mode (QNM) spectral instability under small scale perturbations has been recently shown to be a common classical general relativistic phenomenon [J. L. Jaramillo et al., Phys. Rev. X 11, 031003 (2021)PRXHAE2160-330810.1103/PhysRevX.11. 031003]. This requires assessing its impact on the BH QNM spectrum, in particular on BH QNM overtone frequencies. We conclude (i) perturbed BH QNM overtones are indeed potentially observable in the GW waveform, providing information on small-scale environment BH physics, and (ii) their detection poses a challenging data analysis problem of singular interest for LISA astrophysics. We adopt a twofold approach, combining theoretical results from scattering theory with a fine-tuned data analysis on a highly accurate numerical GW ringdown signal. The former introduces a set of effective parameters (partially relying on a BH Weyl law) to characterize QNM instability physics. The latter provides a proof of principle demonstrating that the QNM spectral instability is indeed accessible in the time-domain GW waveform, though certainly requiring large signal-to-noise ratios. Particular attention is devoted to discussing the patterns of isospectrality loss under QNM instability, since the disentanglement between axial and polar GW parities may already occur within the near-future detection range.
Effects of chirality on single-file water permeability and diffusivity through single wall carbon nanotubes

In this work, molecular dynamics (MD) simulations of single-file water permeation through carbon nanotube (CNT) membranes have been performed and for a better understanding of the relationship between water transport performance of these biomimetic membranes and chirality of CNTs, the key parameters such as osmotic and diffusive permeability constants and diffusion coefficients are investigated. For this purpose, CNTs with approximately same diameters and different chirality from armchair to zigzag are used to perform 40 nanosecond MD simulations of these membranes. The resulting permeability and diffusivity characteristics of single-file CNT membranes showed that water permeability constant and diffusion coefficient increase by changing in the chirality of CNTs from armchair to zigzag, with approximately similar size in diameter. Finally, the presented results provide useful insights into the design of CNT water transporters with best performance.
Induction Motor Analysis by Considering Hysteresis Loops in Stator and Rotor

This article describes the characteristic calculation of induction motors with the same shaped rotor bars in equal spaces by considering hysteresis loops in stator and rotor cores. A fast calculation method based on the symmetrical bar shape is proposed to realize this calculation. The validity of the calculation is confirmed by experimental results. It is clarified that the accuracies of the calculated motor characteristics are improved by considering the reaction field caused by the hysteresis phenomenon and eddy currents in the core.