Miracle-dz/UniFAR-FTUs huggingface dataset:
Plasma bubble zonal velocity variations with solar activity in the Brazilian region

Abstract. A statistical study of the zonal drift velocities of the ionospheric plasma bubbles using experimental airglow data acquired at the low-latitude station Cachoeira Paulista (Geogr. 22.5° S, 45° W, dip angle 28° S) during the period of October to March, between 1980 and 1994, is presented here. This study is based on 109 nights of zonal plasma bubble velocity estimations as determined from bubbles signatures on the OI 630nm scanning photometer airglow data. The zonal velocity magnitudes of the plasma bubbles are investigated with respect to solar activity and local time. It is verified that these velocities tend to increase with the solar EUV flux, using the solar 10.7-cm radio flux as a proxy (F10.7). These velocities are seen to be larger during the solar maximum activity period than in the solar minimum period. As to the local time variation, they are seen to peak before midnight, in the 20:30-22:30 LT time frame, depending on the season. The all-data plot based on the 109 nights of airglow experiments shows that the plasma bubble mean zonal drift velocities tend to decrease with local time, but they peak at 22:25 LT, where the velocity magnitude reaches 127.4ms-1. The zonal drift variations with local time and solar flux are shown in Figs. 1 and 2, respectively.
Gamelan Melodic Phrase Representation based on The Question-and-Answer Segmentation Rule

A melodic phrase can be analogized as a conversation containing question-and-answer segments. Gamelan music, a Javanese traditional music, has a melodic phrase concept called padang-ulihan that has the characteristic of causality in the format of questioning and answering continuously and recursively starting from the beat level that expands to the bar and line levels. The concept needs to be mapped in the data rigidly so that the system can recognize it. Without applying the concept of a melodic phrase, the resulting melodic generation tends to meet the rules but lacks in melodic feel. This is the motivation to develop a symbolic question-and-answer segmentation-based model for the representation of Gamelan music melodies. The concept of the melodic phrase in Gamelan music is represented into question-and-answer segments recursively, which is then mapped into 11 sub-segments starting from beats, bars, and lines, in which all the sub-segments is formulated into seven types of marks using combinations of question, exclamation and asterisk marks. The proposed method can be used to generate a sequence of notations that meet the melodic phrase pattern which is still a problem in melodic generation.
Digital twin-assisted knowledge distillation framework for heterogeneous federated learning

In this paper, to deal with the heterogeneity in federated learning (FL) systems, a knowledge distillation (KD) driven training framework for FL is proposed, where each user can select its neural network model on demand and distill knowledge from a big teacher model using its own private dataset. To overcome the challenge of train the big teacher model in resource limited user devices, the digital twin (DT) is exploit in the way that the teacher model can be trained at DT located in the server with enough computing resources. Then, during model distillation, each user can update the parameters of its model at either the physical entity or the digital agent. The joint problem of model selection and training offloading and resource allocation for users is formulated as a mixed integer programming (MIP) problem. To solve the problem, Q-learning and optimization are jointly used, where Q-learning selects models for users and determines whether to train locally or on the server, and optimization is used to allocate resources for users based on the output of Q-learning. Simulation results show the proposed DT-assisted KD framework and joint optimization method can significantly improve the average accuracy of users while reducing the total delay.
Lithographically defined low dimensional SiGe nanostripes as silicon stressors

The introduction of strain in semiconductors is a well-known technique for increasing their conductivity and thus for enhancing the performance of silicon-based electronic devices. In the present work, we investigate the strain induced in the Si substrate by linear SiGe/Si structures with a width less than 100 nm. By varying the Ge content and geometrical parameters, it is possible to maximize the strain in the Si substrate without detrimental plastic relaxation in the SiGe stripes. The structures were defined by electron-beam lithography from strained SiGe deposited epitaxially by low-energy plasma-enhanced chemical vapor deposition. The strain in the heterostructures has been characterized by a combination of finite-element modeling, x-ray diffraction, and μRaman spectroscopy techniques. We show that nano-patterning induces an anisotropic strain relaxation in the SiGe stripe with a simultaneous strong compression of the Si substrate.
Critical Success Factor Using Career-Oriented Social Networking Site (CSNS) for Fresh Graduates

Many fresh graduates and job seekers have a challenge finding a job. Applications mobile or social media platforms have become very practical and professional providers of job vacancy information for those who want to hunt for jobs. Career-Oriented Social Network Site (CSNS) is a solution that is one of the platforms or applications that can help a job search for every job seeker. In this study, the platform CSNS will be evaluated through usability testing to determine user satisfaction. Moreover, the merging of several models to map behavioral intentions, social influences, and internal connections in using CSNS for job search. To obtain data on the factors that support the successful use of CSNS, data of 428 respondents who stated that they had been and were using CSNS collected using Purposive sampling method. The respondents who are come from Jabodetabek area in Indonesia answers online questionnaires via google form from May to June 2022. Two from seven hypothesis are rejected, there are the affect of trust to behavioral intention and affect of Error to Perceived Usefulness.
Ferroelectric and dielectric properties of ferrite-ferroelectric ceramic composites

Particulate composites of ferrite and ferroelectric phases with xNiFe2O4 (NF) and (1 − x)Pb0.988(Zr0.52Ti0.48)0.976Nb0. 024O3 (where x = 2, 10, 20, 30, 50, 70, and 100 wt. %) were prepared in situ by sol-gel method. The presence of a diphase composition was confirmed by X-ray diffraction while the microstructure of the composites was studied by scanning electron microscopy revealing a good mixing of the two phases and a good densification of the bulk ceramics. The dielectric permittivity shows usual dielectric dispersion behavior with increasing frequency due to Maxwell-Wagner interfacial polarization. AC conductivity measurements made in frequency range 1 Hz-1 MHz suggest that the conduction process is due to mixed polaron hopping. The effect of NF phase concentration on the P-E and M-H hysteresis behavior and dielectric properties of the composites was investigated. At low NF concentration a sharp ferro-paraelectric transition peak can be observed at around 360 °C while for higher NF concentrations a tre.
Approximate solutions to boundary layer problems in linear kinetic theory

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BGP-ELF: Enhancing BGP To Eliminate Routing Loops and Oscillations without Path Vectors

The policy mechanisms used in BGP are modified by substituting path vectors with path labels, which results in BGP-ELF (BGP Enhanced for Loop Freedom). BGP-ELF uses updates, queries, and replies based on path labels to attain multi-path loop-free and stable routing across autonomous systems without the need for path vectors. An autonomous system organized into clusters is required to elect a designated route reflector to ensure that no routing loops can be formed due to local preferences within clusters in the autonomous system. Well-known examples of systems in which EBGP and IBGP do not converge are used to illustrate the benefits of BGP-ELF.
J urnal M anajemen (E disi E lektronik )

Background. There are many cases of financial statement manipulation in practice which result in low financial statement integrity, unreliability and can mislead users. Therefore, research on the financial statement integrity (FSI), especially in the consumer goods industry, is important to study. The purpose. This research aims to provide evidence of the effect of ownership type, intellectual capital, audit quality and debt levels on the integrity of the financial statements of the consumer goods manufacturing industry in companies listed on the Indonesia Stock Exchange. Research methodology. Sample of this research is consumer goods manufacturing companies listed on the IDX. The six sub-sectors of the consumer goods industry are food and beverages, pharmaceuticals, cigarettes, cosmetics and household goods, household appliances and other consumer goods. The purposive sampling method was used to select the sample. The number of samples observed was 249 during 2017-2021. The analysis technique uses multiple regression tests. Findings. The results showed that domestic institutional ownership, foreign institutional ownership, government institusional ownership had a positive and significant effect on the FSI. Debt level and quality of audit proved to have a negative and significant effect on FSI. Individual ownership and intellectual capital had no effect on the FSI. Originality/Novelty. This research differentiates into 4 types of ownership, namely domestic, foreign, government, and individual ownership. It is still rare to research that distinguishes the 4 types of ownership. In addition, research specifically using consumer goods industry samples is still rare, even though there are cases of low financial report integrity in this industry. Creative Commons Attribution-ShareAlike 4.0 International License. 161 | Afrilia, Surifah Jurnal Manajemen (Edisi Elektronik)
Awareness-Constrained Discrete Choice in Multilayer Network Formation and Evolution

We introduce a generative model for multilayer networks consisting of awareness layers and active layers. Nodes themselves seek to build (or weight) links in active layers based on information available through their connections in awareness layers, including via discrete choice processes. For the generative network models we define, we use actor-based simulations and analytical approaches to examine the properties of resultant networks, such as degree distributions.
Performance Analysis of AI-based Learning Models on Leaf Disease Prediction

Diseases on the leaves of a plant have a great effect on agriculture. Around 70-75% of the Indians are totally dependent on agriculture. Diseases on plant leaves reduce the yield and quantity of the product. In this paper, the different analysis of methods are used to detect plant leaf diseases using various machine learning (ML) algorithms such as Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Naive-Bayes, Logistic Regression, Artificial Neural Network (ANN), Convolutional Neural Network (CNN), Back propagation, Genetic algorithm and Probabilistic Neural Network (PNN) was done. The SVM algorithm which is used to detect tomato plant leaf diseases gives 96% prediction whereas the Back Propagation algorithm which is used to detect groundnut leaf diseases obtained 97.41% prediction. Our work focuses on the analysis of various leaf disease detection techniques and also provides an overview of various image processing techniques. The main purpose of the paper is to support the identification of plant affected by various diseases. A comparative analysis of various leaf disease detection has been done in this paper.
Deep Beamforming for Joint Direction of Arrival Estimation and Source Detection

Direction of arrival (DoA) estimation is a well studied problem with several significant applications in radar, sonar, wireless communications, and audio signal processing. A majority of conventional algorithms for DoA estimation require prior knowledge of the number of transmitters and/or sufficient measurements for estimating the received signal covariance matrix. When these requirements are not satisfied, the performance of such algorithms degrades considerably. Recently, some deep learning-based approaches to direction of arrival estimation have been proposed. However, similar to conventional algorithms, most of these methods require the number of transmitters to be known a priori or require a large number of snapshots. We propose a new deep learning approach to DoA estimation. Our approach is inspired by conventional beamforming-based methods and identifies both the number of transmitting sources as well as their angular positions. We demonstrate empirically that our method outperforms conventional methods and a recently proposed deep learning approach in the low-SNR and low-snapshot regimes.
A pb-2 Ritz Formulation for Flexural Vibration of Shallow Cylindrical Shells of Rectangular Planform

Abstract This paper presents a free flexural vibration analysis of shallow cylindrical shells of rectangular planform with arbitrary combinations of free, simply supported and clamped boundaries. The pb-2 Ritz method previously used in the plate analysis by one of the authors is now extended to shallow shell studies. The Ritz approach, along with the in-plane and transverse displacements assumed in the form of orthogonal polynomials, is used to formulate the problems. Numerical results for the vibration frequencies for wide ranges of aspect ratio, shallowness ratio and thickness ratio are presented. Several selected contour plots of the mode shapes for six different combinations of boundary conditions are presented. As usual, the accuracy of the present method is illustrated by convergence tests and comparison with the well established results from the literature.
E-Service Quality, Trust and Perceived Value Impact on Customer Satisfaction

As an e-commerce application provider, customer satisfaction is an important factor to be considered by Shopee, where service performance can measure consumer satisfaction. This study aims to determine e-service quality, trust, and perceived value's role in customer satisfaction. The population used in this study are management students using the Shopee application at the University in Jakarta. The data collection used in this study is a questionnaire distributed to 320 respondents. The analysis method in this study is the associative method using multiple regression analysis tools and processed with SPSS 22. The results of this study show that e-service quality, trust, and perceived value simultaneously influence customer satisfaction.
Growth and optical properties of nanometer‐scale GaAs and InAs whiskers

The growth process, crystal structure, and optical properties of ultrathin GaAs and InAs wires (whiskers) as thin as 15–40 nm and about 2 μm long are reviewed and discussed. Experimental results for growing whiskers using Au as a growth catalyst during metalorganic vapor phase epitaxy (MOVPE) and the shape and growth direction of whiskers provide new insight into growth control of GaAs and InAs whiskers. The crystal structure of whiskers, Au behavior during MOVPE, and their growth mechanism are reviewed and discussed on the basis of transmission electron microscopic analysis. The photoluminescence spectra of GaAs wires are compared with those of a GaAs epitaxial layer, and the effect of surface treatment on the luminescence peak energy shift is discussed. The time dependent photoluminescence of GaAs wires is also discussed. The application of GaAs whiskers to light emitting devices is reviewed because a semiconductor wire structure employing quantum size effects is a very important element of electronic a.
The comparison of designs for sequential clinical trials with covariate information

Summary. The paper develops methods for the comparison of randomized rules of the biased coin type for the sequential allocation of treatments in a clinical trial. One important characteristic is the loss, which measures the increase in the variance of parameter estimates due to the imbalance caused by randomization. The other important characteristic is the selection biasmeasuring the probability of correctly guessing which treatment is to be allocated next. The combination of these two measures leads to the elucidation of admissible designs. Simulations provide clear plots of the behaviour of the designs and make it possible to distinguish good designs from those which are less good.
Annealing effect on the reduction of Fermi-level density of states in CoTiSb: NMR evidence

With the aim to examine the variation in the electronic properties of CoTiSb due to heat treatment, a comparative study of the as-cast and annealed samples using 59 Co nuclear magnetic resonance NMR spectroscopy was performed. All NMR observations clearly indicate a significant change in the local electronic characteristics for the annealed sample. The spin-lattice relaxation rate measurements further provide an estimate of Co-d Fermi-level density of states, NdEF, indicating a substantial reduction in NdEF for the specimen with heat treatment. This finding gives a microscopic interpretation for the larger electrical resistivity and Seebeck coefficient in the annealed half-Heusler alloys, as the samples with higher electrical resistivity and Seebeck coefficient usually are associated with lower carrier densities in the vicinity of the Fermi level.
Time-domain large-signal investigation on nonlinear interactions between an optical pulse and semiconductor waveguides

A time-domain large-signal model is developed to investigate nonlinear interactions between picosecond optical pulses and semiconductor active waveguide devices, including distributed-feedback and Fabry-Perot lasers, as well as optical amplifiers. The model predicts interesting phenomena such as transform-limited superluminal transmission and directional DFB amplification. The influence of electrical carrier dynamics and feedback from a Bragg grating and/or reflecting facets on output pulses are demonstrated. Moreover, it is found that the time delay of the reflected and transmitted pulses is strongly related to the Bragg grating parameters, as well as to carrier dynamics. As a consequence, careful attention should be paid when the notions of group refractive index and group velocity are to be used in device modeling.
Instabilities By Local Heating Below an Interface

Abstract Thermal lens oscillations, and associated hot-wire experiments, pertain to a class of instabilities produced when the free surface of a liquid is locally heated from below, generalizing to some extent the classical Bénard-Marangoni instabilities [1–8]. They provided a host of original observations, including what is seemingly the first evidence of a type-II intermittency in hydrodynamical experiments or the discovery of a new kind of propagating waves exhibiting a significant 1D-character. After two decades of study, this class of instabilities now receives a rather classical aspect [9] and deserves a review, which is presented in this paper. Beside the presentation of what is known and understood nowadays, the opportunity is taken to stress unsolved issues, therefore opening the way to future studies. This review completes and up-to-dates a previous one published one decade ago [10].
Effect of intensity modulated radiotherapy on lymphocytes in patients with esophageal squamous cell carcinoma and its clinical significance

Background Radiotherapy usually leads to a decrease in the total number of lymphocytes in patients with esophageal cancer. The factors that causing lymphopenia and the clinical significance of lymphopenia are studied in this article. Patients and methods 110 patients with esophageal squamous cell carcinoma who had undergo intensity-modulated radiation therapy were enrolled. Statistical methods were used to analyze the correlation between lymphopenia and total survival in patients with esophageal cancer during radiotherapy, and analyze the correlations between nutritional factors and lymphopenia. Results There were 11 patients with the lowest lymphocyte value with level 1-2 during radiotherapy, accounting for 10% of all the patients, and 110 patients with level 3-4, accounting for 90% of all the patient. In all the enrolled patients, the incidence of lymphocyte nadir G1, G2, G3 and G4 MinALC during radiotherapy accounted for 0.91%, 9.09%, 62.73% and 27.27%, respectively.KM survival analysis showed that the overall survival of patients in the group (MinALC ≤ 0.41×109/L) was significantly lower than that of the patients in the other group (MinALC>0.43×109/L). Nutritional indicators were positively correlated with the decline degree of lymphocytes. The minimal value of lymphocyte can predict the occurrence of grade 3-4 radiation pneumonitis. Conclusion Lymphopenia induced by radiotherapy can predict survival and radiation pneumonitis. Nutritional factors such as hemoglobin and albumin were positively correlated with total lymphocytes numbers induced by radiotherapy.
Hippocampal vulnerability to hyperhomocysteinemia worsens pathological outcomes of mild traumatic brain injury in rats

Background Mild traumatic brain injury (mTBI) generally resolves within weeks. However, 15-30% of patients present persistent pathological and neurobehavioral sequelae that negatively affect their quality of life. Hyperhomocysteinemia (HHCY) is a neurotoxic condition derived from homocysteine accumulation above 15 μM. HHCY can occur in diverse stressful situations, including those sustained by U.S. active-duty service members on the battlefield or during routine combat practice. Mild-TBI accounts for more than 80% of all TBI cases, and HHCY exists in 5-7% of the general population. We recently reported that moderate HHCY exacerbates mTBI-induced cortical injury pathophysiology, including increased oxidative stress. Several studies have demonstrated hippocampus vulnerability to oxidative stress and its downstream effects on inflammation and cell death. Objective This study aimed to assess the deleterious impact of HHCY on mTBI-associated hippocampal pathological changes. We tested the hypothesis that moderate HHCY aggravates mTBI-induced hippocampal pathological changes. Methods HHCY was induced in adult male Sprague-Dawley rats with a high methionine dose. Rats were then subjected to mTBI by controlled cortical impact under sustained HHCY. Blood plasma was assessed for homocysteine levels and brain tissue for markers of oxidative stress, blood-brain barrier integrity, and cell death. Endothelial cell ultrastructure was assessed by Electron Microscopy and working memory performance using the Y maze test. Results HHCY increased the hippocampal expression of nitrotyrosine in astroglial cells and decreased tight junction protein occludin levels associated with the enlargement of the endothelial cell nucleus. Furthermore, HHCY altered the expression of apoptosis-regulating proteins α-ii spectrin hydrolysis, ERK1/2, and AKT phosphorylation, mirrored by exacerbated mTBI-related hippocampal neuronal loss and working memory deficits. Conclusion Our findings indicate that HHCY is an epigenetic factor that modulates mTBI pathological progression in the hippocampus and represents a putative therapeutic target for mitigating such physiological stressors that increase severity.