Miracle-dz/UniFAR-FTUs huggingface dataset:
Scheduling of Identical Jobs with Bipartite Incompatibility Graphs on Uniform Machines. Computational Experiments

Abstract. In the paper we consider the problem of scheduling of unit-length jobs on 3 or 4 uniform parallel machines to minimize schedule length or total completion time. We assume that jobs are subject to some kind of mutual exclusion constraints, modeled by a bipartite graph of bounded degree. The edges of the graph correspond to pairs of jobs that cannot be processed on the same machine. Although the problem is generally NP-hard, we show that under some conditions imposed on machine speeds and the structure of incompatibility graph our problem can be solved to optimality in polynomial time. Theoretical considerations are accompanied by computer experiments with some particular model of scheduling.
HIGH-INTENSITY INTERVAL TRAINING IN PEOPLE WITH SPINAL CORD INJURY: A SYSTEMATIC REVIEW

ABSTRACT Objective: Analyze the effects of high-intensity interval training (HIIT) on cardiometabolic parameters, and cardiorespiratory fitness to compile the most used HIIT training types in adults with spinal cord injury (SCI). Methods: This is a systematic review of searches performed in the electronic databases PubMed / Medline, Science Direct, and Google Scholar. Studies included I) needed to apply HIIT training II) adults with SCI to analyze III) cardiometabolic aspects and cardiorespiratory fitness. Two independent reviewers selected the articles for inclusion, extracted their data, and assessed their methodological quality. Results: 654 studies were found. Thus, 12 studies, 11 pre- and post-intervention, and one control group (CG) with 106 participants were analyzed. Pre- and post-HIITT intervention results revealed significant improvement in cardiorespiratory fitness and cardiometabolic aspects (VO2peak, LDH, HDL, insulin resistance). In addition, GC results revealed significant improvement in cardiorespiratory fitness observed in the intervention group (HIIT) compared to the moderate-low intensity (GC) group. Seven studies used the arm ergometer as the primary exercise modality. Two studies described functional electrical stimulation (FES) performed with the arm ergometer plus electrical stimulation in the lower limbs. None reported heart rate dynamics during the study period. Conclusion: High-intensity interval training improves physical fitness and cardiometabolic health in adults with SCI. Evidence level II; Systematic Review of level II studies.
Testing for symmetric correlation matrices with applications to factor models

Factor models have been widely used in recent years to model high‐dimensional spatio‐temporal data. However, the validity of employing factor models in a specific application has received less attention. This article proposes test statistics for testing the symmetry in cross‐correlation matrices of a high‐dimensional stochastic process implied by exact factor models. A rejection of symmetry indicates that the use of an exact factor model is questionable. Both simulations and real examples are used to demonstrate the applications and to study the finite‐sample performance of the proposed test statistics. Empirical results show that the proposed test statistics are effective in identifying cases where exact factor models are not appropriate, providing valuable guidance for choosing factor models in a high‐dimensional setting.
Big Data y diferentes enfoques de clustering subespacial: De la promoción en redes sociales al mapeo genómico

En la era actual de las tecnologías de la información, la información es el factor más importante para determinar cómo progresarán los distintos paradigmas. Esta información debe extraerse de un enorme tesoro informático. El aumento de la cantidad de datos analizados e interpretados es consecuencia directa de la proliferación de plataformas de procesamiento más potentes, el incremento del espacio de almacenamiento disponible y la transición hacia el uso de plataformas electrónicas. En este trabajo se describe un estudio exhaustivo de Big Data, sus características y el papel que desempeña el algoritmo de clustering Subspace. La contribución más importante que hace este trabajo es que lee muchas investigaciones anteriores y luego hace una presentación exhaustiva sobre las diferentes formas en que otros autores han clasificado los métodos de clustering subespacial. Además, se han proporcionado, con una breve explicación, algoritmos significativos que pueden servir de referencia para cualquier desarrollo futuro.
Effects of Monetary Policy on Inflation in Ethiopia: Using ARDL Co-Integration Approach

: Although many studies on linkage between monetary policy and inflation have been done in both developing and advanced countries, Notably Ethiopia has not featured in the cross-country studies that have included some of the Sub-Saharan African countries. Similar studies in Ethiopia haven not been conducted by including all necessary variables. Therefore, the study is to empirically investigate the effects of monetary policy on inflation in the case of Ethiopia. The study covers the annual data from 1988 to 2021 using time series ARDL co-integration regression analysis. The consumer price index is used as a proxy of inflation. The empirical results suggest that money supply, the openness of trade and the real effective exchange rate exerts a positive and statistically significant effect on inflation, in the long run, and real gross domestic product and real lending rate have a negative and statistically significant effect on inflation in the long run. The estimate of the speed of adjustment coefficient found in this study indicates that about 21.4 per cent of the variation in the inflation from its equilibrium level is corrected within a year. Based on the findings of the empirical analysis, the study recommends that Spends the money to the economy should not exceed the country's production of goods and services. Government should implement major changes to ensure that more of the money in circulation is in the productive sector.
Contact maximal en caractéristique positive

RÉSUMÉ. — On fonde sur des arguments de calcul différentiel une théorie du contact maximal pour un anneau local complet contenant un corps. On en déduit que l'élimination par éclatements de centre permis des points proches d'une singularité algébroïde équivaut à l'élimination, par éclatements de centre régulier le long desquels elles sont équimultiples, des points de multiplicité trop élevée d'un certain nombre d'hypersurfaces bien choisies, résultat connu en caractéristique nulle
The value of multiparametric prediction scores in heart failure varies with the type of follow‐up after discharge: a comparative analysis

Multiple prediction score models have been validated to predict major adverse events in patients with heart failure. However, these scores do not include variables related to the type of follow‐up. This study aimed to evaluate the impact of a protocol‐based follow‐up programme of patients with heart failure regarding scores accuracy for predicting hospitalizations and mortality occurring during the first year after hospital discharge.
Implementation of the Finite Difference Time Domain algorithm for the analysis of terahertz waves

The aim of this report is to present results related to the application of the Finite Difference Time Domain (FDTD) method for the study of various devices at terahertz frequencies. The FDTD method has emerged as one of the most widely used numerical analysis methods used for electromagnetic simulations. The FDTD method can be used to solve numerous types of problems ranging from modelling the behaviour of microwave circuits, waveguides, and photonics to simulating terahertz devices and plasmas. In this study the FDTD approach is derived from first principles (finite differences) and explicit equations are shown based on Maxwell's equations. Furthermore, absorbing boundary conditions (ABCs) are discussed for the FDTD method. The algorithm is tested against a range of problems to ensure its validity and accuracy. The FDTD method is then applied for the numerical analysis of a range of devices at terahertz frequencies. The numerical results obtained from the application of the FDTD method to examine a microstrip circuit with filter loading and a Multi-mode Interference (MMI) coupler at terahertz frequencies are discussed in detail. Moreover, the results of the application of the FDTD method for the calculation of the dispersion characteristics of plasmonic waveguides are also presented. Finally, a summary of the work carried out is presented and an outline is given for future research which can be carried out by using the FDTD method for the study of terahertz frequency devices.
Bayesian Subset Selection for Reproductive Dispersion Linear Models

Abstract We propose a full Bayesian subset selection method for reproductive dispersion linear models, which bases on expanding the usual link function to a function that incorporates all possible subsets of predictors by adding indictors as parameters. The vector of indicator variables dictates which predictors to delete. An efficient MCMC procedure that combining Gibbs sampler and Metropolis-Hastings algorithm is presented to approximate the posterior distribution of the indicator variables. The promising subsets of predictors can be identified as those with higher posterior probability. Several numerical examples are used to illustrate the newly developed methodology.
Availability of Technological Learning Applications and Tools, Science Teachers’ Levels of Use of Online Teaching, and Their Stages of Concerns

Using descriptive-correlational research design, this study determined the relationship between the availability of technological learning applications and tools, and science teachers’ levels of use of online teaching, and their stages of concern. It was conducted at the Schools Division of Laoag City involving all elementary science teachers who are teaching online for the SY 2021-2022. Hence, the purposive sampling technique was used to determine the teachers involved in the study. Findings revealed that the respondents are young adult. The majority of them are female. Most of them are teaching Science for less than five years. Their mean years of teaching Science is 9.44. Majority of them have masters’ units and they have attended trainings and seminars related to online teaching. The respondents have the availability of technological learning applications and tools in online teaching. The teachers’ level of use of online teaching falls at Level V (Integration Stage) while the teachers’ stages of concern fall at Stage 0 (Awareness). Findings also revealed that only the teachers’ number of years teaching in Science is significantly related to their level of use of online teaching.
Running with Flapping Wings

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission. Acknowledgement The author would like to thank Ron Fearing for all of his assistance and guidance on this work, and Robert Full for the many discussions and suggestions for improving the results. Great thanks to Paul Birkmeyer for the use of DASH as a starting platform for this research, as well as the many design discussions and ideas generated, and to Ankur Mehta, for the use of the GINA mote. Finally, thank you to all of my colleagues in the Biomimetics Millisystems Lab for all of your comments and suggestions throughout the course of the work. DASH+Wings is a small hexapedal winged robot derived from the Dynamic Autonomous Sprawled Hexapod (DASH). Drawing inspiration from nature, DASH+Wings uses wing assisted running to enable increased mobility. It shows a great improvement over DASH in its ability to traverse smooth inclines. To understand the differences in the motion of DASH and DASH+Wings, they are fitted with the GINA mote, a small electronics package that contains a processor, IMU, and radio. The acceleration, velocity and position profile as the robots are running can be compared, and the differences in motion quantified. The accelerometer data can also be used to classify good versus poor running performance, and assist with proper tuning of the system.
Fully Symmetrical Hybrid PV Converter With Low Common-Mode Noise

Hybrid converters with multiports (simultaneous dc and ac outputs) are promising solutions to reduce conversion stages from solar energy to various loads, and thereby increasing the utilization of residential PV systems. Considering common-mode noises suppression and high reliability, this article proposes a fully symmetrical hybrid PV converter concept with two dc ports and one ac port. The proposed converter adopts symmetrical boost impedances at the low-voltage dc port and symmetrical synchronization rectifier switches at the high-voltage dc port. In addition, a symmetrical ac-decoupling inverter, i.e., highly efficient and reliable inverter concept (HERIC), operates as either a boost switch or an inverter to perform dc–dc and dc–ac conversions simultaneously. Combined with a dedicated modulation method with deadtime, the proposed converter has low leakage currents for grid-connected PV applications, low common-mode (CM) noise as a dc–dc converter, and flexible power control capability. Experiments have been carried out on a prototype to verify the effectiveness of the proposed converter.
Ultrathin and Bendable mm-Wave Chipless Tags Based on Grounded Periodic Surfaces

Depolarizing mm-wave chipless radio frequency identification (RFID) tags based on grounded dipole resonators characterized by an extremely thin profile are proposed. The use of a thin grounded substrate (below 0.15 mm) makes the tags bendable. The presence of the ground plane allows us to isolate the response of the tag from surrounding objects making the proposed configuration suitable for nonplanar lossy objects like filled water bottles or containers. The periodic surface configuration is employed to obtain a sufficiently large RCS to increase the read range of the tags. The proposed tags operate between 26 and 40 GHz, which allows us to achieve the miniaturization necessary for practical scenarios. Toward low cost, thermal printing fabrication is investigated taking lithographic one as a reference. The associated severe loss (introduced by both ultrathin substrate and thermal printing) and the rotation sensitivity of depolarizing label are discussed theoretically and well addressed experimentally. Rotation insensitivity up to 5° and long read range up to 150 cm are experimentally verified. The readability of the proposed ultrathin tags applied to filled bottles is successfully assessed by comparing the performance of tags with and without the ground plane.
DESIGN OF STUDENT SUCCESS PREDICTION APPLICATION IN ONLINE LEARNING USING FUZZY-KNN

Effective evaluation of student performance is crucial. Hence, many kinds of techniques are used such as statistics, physical examination and currently data mining techniques to evaluate student performance. Data mining techniques as known as Educational Data Mining (EDM) collect, process, report and used to find the unseen patterns in the student dataset. EDM uses machine learning techniques to dig out useful data from multiple levels of meaningful hierarchy. Various data from intelligent computer tutors, classic computer based educational systems, online classes, academic data in educational institution, and standar assesment can be process for EDM. This led universities include open and distance learning (ODL) to collect large volume of student and learning data in their learning management systems (LMS). Students in ODL are relatively familiar with LMS and many learning activities such as number of accessing materials, student participation in discussion forum recorded in LMS. The processes of using EDM to improve the quality of educational policy maker with data-based models have become a challange that institutions of higher education face today. Therefore, this study aims to design applications that predict student performance in online learning using machine learning techniques based on EDM. The machine learning technique used in this research is Fuzzy-KNN. Testing using Fuzzy-KNN produces an accuracy of 92.5%.
Even pseudonyms and throwaways delete their Reddit posts

Concerned researchers of user-generated content might want to avoid using, citing, or quoting sensitive content likely to be deleted by their authors, even when pseudonymous or using one-time “throwaway” accounts. At Reddit, how many authors actually delete their submissions, why, and are they concerned if their deletion end up elsewhere? I analyze the three most popular sensitive-topic subreddits (r/Advice, r/AmItheAsshole, and r/relationship_advice) and show that deleting submissions is common. Roughly half of submissions are deleted by their users, most within the first day and week. Interviews with 30 Redditors reveal that their motives for deletion include ensuring the “Internet doesn’t see them,” especially those who might “see it on my Reddit profile,” deciding their issue was resolved, receiving unhelpful or aggressive comments, and concluding their submission was no longer relevant. Most interviewees were not overly concerned about deleted submissions persisting elsewhere (e.g., social media, archives, and datasets) as long as it is not easily connected to their other activity or identity.
Self-trapped holes in β-Ga2O3 crystals

We have experimentally observed self-trapped holes (STHs) in a β-Ga2O3 crystal using electron paramagnetic resonance (EPR). These STHs are an intrinsic defect in this wide-band-gap semiconductor and may serve as a significant deterrent to producing usable p-type material. In our study, an as-grown undoped n-type β-Ga2O3 crystal was initially irradiated near room temperature with high-energy neutrons. This produced gallium vacancies (acceptors) and lowered the Fermi level. The STHs (i.e., small polarons) were then formed during a subsequent irradiation at 77 K with x rays. Warming the crystal above 90 K destroyed the STHs. This low thermal stability is a strong indicator that the STH is the correct assignment for these new defects. The S = 1/2 EPR spectrum from the STHs is easily observed near 30 K. A holelike angular dependence of the g matrix (the principal values are 2.0026, 2.0072, and 2.0461) suggests that the defect's unpaired spin is localized on one oxygen ion in a nonbonding p orbital aligned near the a direction in the crystal. The EPR spectrum also has resolved hyperfine structure due to equal and nearly isotropic interactions with 69,71Ga nuclei at two neighboring Ga sites. With the magnetic field along the a direction, the hyperfine parameters are 0.92 mT for the 69Ga nuclei and 1.16 mT for the 71Ga nuclei.We have experimentally observed self-trapped holes (STHs) in a β-Ga2O3 crystal using electron paramagnetic resonance (EPR). These STHs are an intrinsic defect in this wide-band-gap semiconductor and may serve as a significant deterrent to producing usable p-type material. In our study, an as-grown undoped n-type β-Ga2O3 crystal was initially irradiated near room temperature with high-energy neutrons. This produced gallium vacancies (acceptors) and lowered the Fermi level. The STHs (i.e., small polarons) were then formed during a subsequent irradiation at 77 K with x rays. Warming the crystal above 90 K destroyed the STHs. This low thermal stability is a strong indicator that the STH is the correct assignment for these new defects. The S = 1/2 EPR spectrum from the STHs is easily observed near 30 K. A holelike angular dependence of the g matrix (the principal values are 2.0026, 2.0072, and 2.0461) suggests that the defect's unpaired spin is localized on one oxygen ion in a nonbonding p orbital aligned near.
PERANCANGAN DAN IMPLEMENTASI SISTEM KONTROL UNTUK TEMPAT SAMPAH OTOMATIS MENGGUNAKAN ARDUINO DAN SENSOR ULTRASONIK

Internet-of-Things (IoT) merupakan teknologi yang mengintegrasikan berbagai peralatan dengan Internet. Salah satu pemanfaatan IoT adalah sistem kontrol elektronik pada berbagai peralatan rumah. Peralatan rumah dapat dilengkapi dengan mikrokontroler, sensor, dan aktuator, serta modul komunikasi, sehingga dapat dihubungkan ke internet dan dipantau dari jarak jauh. Salah satu peralatan atau objek yang ada di rumah adalah tempat sampah yang umumnya terbuat dari plastik, tetapi umumnya belum dapat dipantau dan dikontrol otomatis. Tujuan penelitian ini adalah untuk merancang sistem kontrol untuk membuka dan menutup tempat sampah secara otomatis menggunakan Arduino sebagai pengontrol sistem, sensor ultrasonik sebagai pendeteksi objek yang mendekat, motor servo yang berguna untuk menggerakkan tutup tempat sampah, dan buzzer serta LED sebagai indikator ketika terdapat objek yang mendekat. Hasil pengujian sistem menunjukkan bahwa tempat sampah dapat membuka tutupnya secara otomatis saat mendeteksi objek pada jarak paling jauh 50 cm dengan delay selama dua detik, dan kemudian akan tertutup secara otomatis ketika objek tersebut menjauh dari tempat sampah tersebut.
Impact of atomic-scale surface morphology on the size-dependent yield stress of gold nanoparticles

Size-dependent mechanical properties have been revealed for nanowires, nanopillars and nanoparticles. On the surfaces of these nanosized elements, discrete atomic-scale steps will be naturally generated, however their impact on the mechanical properties and deformation has seldom been a concern. In this paper, large-scale molecular dynamics simulations are conducted to calculate the yield stress of gold nanoparticles under compression. In addition to absolute particle size, atomic-scale surface morphology induces significant fluctuation of the yield stress. An analytical relation is advanced to predict the yield stress of nanoparticles accounting for the influence of both size and surface morphology, which agrees well with atomic simulations. This study illuminates an important mechanism in nanosized elements, atomic-scale surface steps.
Incorporating the New PRNG in Advance Encryption Standard

This manuscript explores the fusion of two well-known encryption algorithms, the Advanced Encryption Standard (AES) and the Rivest Cipher (RC4), resulting in a novel encryption algorithm called AES-RC4. AES-RC4 is a block cipher that combines the strengths of AES with a variant of RC4 called RC4-GF, developed by ourselves. RC4-GF incorporates additional steps compared to AES, resulting in a more intricate ciphertext generation process. The introduction of AES-RC4 brings forth a highly secure encryption technique with increased complexity in the ciphertext compared to traditional AES. By leveraging the combined capabilities of AES and the modified RC4-GF, AES-RC4 offers enhanced encryption strength and improved resistance against cryptographic attacks.
In vitro antioxidant activity and total phenolic content of Digera muricata leaves

In the present study quantification of total phenolic content and evaluation of in vitro antioxidant capability of five different extracts of Digera muricata was carried out by different assays. DPPH radical, superoxide radical, hydroxyl radical scavenging activity and metal chelating activity were calculated and compared with standard antioxidants. Reducing power of the extract was also determined. All extracts showed good free radical scavenging ability which gets enhanced with increasing concentration. Methanolic extract possessed highest scavenging ability and it has maximum phenolic content (41.87 mg/g GAE). Significant correlation was observed between antioxidant assays and total phenolic content indicating that phenolics may be contributing towards antioxidant activity. The results conclude that D. muricata extracts are a potential source of natural antioxidants and could show promise as therapeutic agent in preventing the progression of oxidative stress related degenerative disorders.