Miracle-dz/UniFAR-FTUs huggingface dataset:
Eliminating Communication Bottlenecks in Consensus Protocols using NDN

Consensus protocols are widely used to build distributed fault-tolerance systems. Unfortunately, existing consensus protocols fail to address communication bottlenecks, and the load imbalance limits the system performance. Named Data Networking is a data-centric network architecture, supporting packet aggregation in the network layer. In this paper, we propose PAN, a weak leader consensus protocol for Named Data Networking. The main idea of PAN is to reduce the message processing load in the application layer and aggregate messages directly in the network layer to eliminate the communication bottleneck. PAN adopts a proactive replicating mechanism to solve the performance bottleneck caused by the replication of large commands. We implement a prototype of PAN in C++ and evaluate it on Mini-NDN. The results show that PAN balances the load well between replicas and the communication bottlenecks are alleviated. Moreover, PAN provides benefits in both throughput and latency compared with other consensus protocols over Named Data Networking.
Numerical Analysis of Deformation Characteristics of Elastic Inhomogeneous Rotational Shells at Arbitrary Displacements and Rotation Angles

Adequate mathematical models and computational algorithms are developed in this study to investigate specific features of the deformation processes of elastic rotational shells at large displacements and arbitrary rotation angles of the normal line. A finite difference method (FDM) is used to discretize the original continuum problem in spatial variables, replacing the differential operators with a second-order finite difference approximation. The computational algorithm for solving the nonlinear boundary value problem is based on a quasi-dynamic form of the ascertainment method with the construction of an explicit two-layer time-difference scheme of second-order accuracy. The influence of physical and mechanical characteristics of isotropic and composite materials on the deformation features of elastic spherical shells under the action of surface loading of “tracking” type is investigated. The results of the studies conducted have shown that the physical and mechanical characteristics of isotropic and composite materials significantly affect the nature of the deformation of the clamped spherical shell in both the subcritical and post-critical domains. The developed mathematical models and computational algorithms can be applied in the future to study shells of rotation made of hyperelastic (non-linearly elastic) materials and soft shells.
Luminescence properties of point defects in silica

The optical properties of point defects in as-grown natural silica are reviewed. Two emissions peaked at 4.2 eV ($\alpha_E$ band) and at 3.1 eV ($\beta$ band), related to an absorption band at 5.1 eV ($B_{2\beta}$), have been experimentally investigated on the basis of their temperature dependence and their kinetic decay. Our results allow to characterize the excitation pathway of these luminescence bands and to make clear the competition between the radiative relaxation rates and the phonon assisted intersystem crossing process linking the singlet and the triplet excited states from which $\alpha_E$ and $\beta$, respectively, originate. Finally, we discuss the role played by the disordered vitreous matrix in influencing the optical features of defects.
A Validation Study Involving Development of Model by Application of Artificial Intelligence in Screening and Prognosis of Breast Cancer

Introduction: Breast Cancer (BC) is a worldwide prevalent carcinoma with varying growth rates. It is also a heterogeneous condition with several clinical manifestations. There is a guideline for effective screening of BC, but the mammograms that are obtained for the same often return false negatives or may not effectively diagnose BC, especially at the early stages. The mortality rates due to BC is also significant and efficient screening may reduce more than 30% of mortality. The assessment and accurate determination of tumour growth is difficult due to the substantial failures of screening BC cases. Aims and Objectives: This current study intends to introduce methods of screening BC using an Artificial Intelligence capable machine learning system, mainly for accurate and efficient detection of BC and assessing its prognostic outcomes. Materials and Methods: The study comprises a cohort of 120 BC patients aged between 50 and 65 years old. The study involves the development of serial mammograms for detection of in-vivo growth rate and further assessment of immunohistochemical staining. The study also facilitates the development of a machine learning model for detecting BC cases from serial mammograms and several other factors. Statistical analyses have been conducted for effective significance tests between the newly developed and existing methods. Results: The newly developed method proved to be successful in accurately assessing several aspects of the tumour, including size, stage, grade, mitotic score, type of histology, Nottinham Prognostic Index (NPI) and many more. The newly developed method is more significant than the existing one in assessing clinico-pathological characteristics. The newly developed method has shown significantly better prognostic ability than the existing one (p = 0.0284). Kaplan-Meier Survival Curve has been plotted to analyze the growth of the tumour with its prognosis. Conclusion: The study has effectively presented the development of a prognostic model for Breast Cancer patients with the application of machine learning algorithms, which can be utilized in the screening of breast cancers and proper management of the same to improve its prognosis.
Development of a transdiagnostic, resilience-focused intervention for at-risk adolescents

Abstract Background Environmental adversity and subclinical symptoms of psychopathology in adolescents increase their risk for developing a future psychiatric disorder, yet interventions that may prevent poor outcomes in these vulnerable adolescents are not widely available. Aims To develop and test the feasibility and acceptability of a prevention-focused program to enhance resilience in high-risk adolescents. Method Adolescents with subclinical psychopathology living in a predominantly low-income, Latinx immigrant community were identified during pediatrician visits. A group-based intervention focused on teaching emotion recognition and regulation skills was piloted in three cohorts of adolescents (n = 11, 10, and 7, respectively), using a single arm design. The second and third iterations included sessions with parents. Results Eighty-eight percent of participants completed the program, which was rated as beneficial. Also, from baseline to end of treatment, there was a significant decrease in subclinical symptoms and a significant increase in the adolescents’ positive social attribution bias (all p < 0.05). Conclusions A resilience-focused intervention administered to high-risk adolescents was found to be feasible and acceptable to participants. Future work is needed to determine whether such a program can reduce the incidence of negative outcomes, such as the development of psychiatric disorders and related disability, in this population.
Optical Corrections to the Véron-Cetty and Véron Quasar Catalogue

Abstract Fixes are presented to be applied to the Véron-Cetty and Véron Quasar Catalogue, 13th edition. These are comprised of 39 de-duplications, 380 astrometric moves of 8 + arcsec of which 31 are over 10 arcmin, and 30 indicated de-listings.
UNIVERSAL BEHAVIOR OF X-RAY FLARES FROM BLACK HOLE SYSTEMS

X-ray flares have been discovered in black hole systems such as gamma-ray bursts, the tidal disruption event Swift J1644+57, the supermassive black hole Sagittarius A* at the center of our Galaxy, and some active galactic nuclei. Occurrences of X-ray flares are always accompanied by relativistic jets. However, it is still unknown whether or not there is a physical analogy among such X-ray flares produced in black hole systems spanning nine orders of magnitude in mass. Here, we report observed data of X-ray flares and show that they have three statistical properties similar to solar flares, including power-law distributions of their energies, durations, and waiting times, which can be explained by a fractal-diffusive, self-organized criticality model. These statistical similarities, together with the fact that solar flares are triggered by a magnetic reconnection process, suggest that all of the X-ray flares are consistent with magnetic reconnection events, implying that their concomitant relativistic jets may be magnetically dominated.
FORMATION OF BLACK HOLE AND ACCRETION DISK IN A MASSIVE HIGH-ENTROPY STELLAR CORE COLLAPSE

We present the first numerical result of fully general relativistic axisymmetric simulations for the collapse of a rotating high-entropy stellar core to a black hole and an accretion disk. The simulations are performed taking into account the relevant microphysics. We adopt as initial conditions a spherical core with constant electron fraction (Ye = 0.5) and entropy per baryon s = 8 kB, and angular velocity is superimposed. In the early phase, the core collapses in a homologous manner. Then it experiences a weak bounce due to the gas pressure of free nucleons. Because the bounce is weak, the core eventually collapses to a black hole. Subsequent evolution depends on initial angular velocity. When the rotation is not fast, a geometrically thin (but optically thick) accretion disk is formed, and shock waves are formed in the inner part of the disk. For the moderately rotating case, the thin accretion disk eventually expands to become a geometrically thick torus after sufficient accumulation of the thermal energy is generated at the shocks. Furthermore, convection occurs inside the torus. Neutrino luminosities vary violently with time because of the convective motion. For the rapidly rotating case, by contrast, a geometrically thick torus is formed soon after the black hole formation, and the convective activity is weak due to the presence of an epicyclic mode.
Comparison of Waria Conversion Registered in Padang City and Sungai Penuh City

This study aims to describe and explain the comparison of conversation registers used by transgender communities in two different cities, namely Padang City and Sungai Full City. This research is a qualitative research using descriptive method. This research was conducted in Padang City, West Sumatra Province and Sungai Penuh City, Jambi Province. The data of this research are utterances containing transgender registers in the city of Padang and the city of Sungai Penuh. The data in this study were collected using the tapping method that utilizes advanced techniques in the form of recording techniques and note-taking techniques. The findings of the study were that 160 transgender conversation register data were found in the City of Padang and the City of Sungai Penuh in terms of 2 domains, namely words, phrases and sentences. In the realm of words, it is divided into adjectives (adjectives), verbs (verbs), nouns (nouns) and greeting words. In the realm of phrases, it is divided into noun phrases, verb phrases, and adjective phrases. Overall, the similarities of the transgender registers of Padang City and Sungai Penuh City are very visible because they use the same vocabulary, namely from the vocabulary of waria in Indonesia. On the other hand, the comparison of conversation registers is clearly seen from the effect of using regional languages ​​attached to speakers and the places that become a thing in an area
Serving Multi-DNN Workloads on FPGAs: A Coordinated Architecture, Scheduling, and Mapping Perspective

Deep Neural Network (DNN) INFerence-as-a-Service (INFaaS) is the dominating workload in current data centers, for which FPGAs become promising hardware platforms because of their high flexibility and energy efficiency. The dynamic and multi-tenancy nature of INFaaS requires careful design in three aspects: multi-tenant architecture, multi-DNN scheduling, and multi-core mapping. These three factors are critical to the system latency and energy efficiency but are also challenging to optimize since they are tightly coupled and correlated. This paper proposes <bold>H3M</bold>, an automatic Design Space Exploration (DSE) framework to jointly optimize the <italic>architecture</italic>, <italic>scheduling</italic>, and <italic>mapping</italic> for serving INFaaS on cloud FPGAs. H3M explores: (1) the architecture design space with <italic><bold>H</bold>eterogeneous</italic> spatial <italic><bold>M</bold>ulti-tenant</italic> sub-accelerators, (2) layer-wise scheduling for <italic><bold>H</bold>eterogeneous</italic> <italic><bold>M</bold>ulti-DNN</italic> workloads, and (3) single-layer mapping to the <italic><bold>H</bold>omogeneous</italic> <italic><bold>M</bold>ulti-core</italic> architecture. H3M beats state-of-the-art multi-tenant DNN accelerators, Planaria and Herald, by up to 7.5× and 3.6× in Energy-Delay-Product (EDP) reduction on the ASIC platform. On the Xilinx U200 and U280 FPGA platforms, H3M offers 2.1-5.7× and 1.8-9.0× EDP reduction over Herald.
Photon polarization tensor in a magnetized plasma system

We investigate the photon polarization tensor at finite temperatures in the presence of a static and homogeneous external magnetic field. In our scheme, the summing of the Matsubara frequency is performed after Poisson resummation, which is easily completed and converges quickly. Moreover, the behaviors of finite Landau levels are presented explicitly. It shows a convergence while summing infinite Landau levels. Consequently, there is no necessity to truncate the Landau level in a numerical estimation. At zero temperature, the lowest Landau level (LLL) approximation is analytically satisfied for the vacuum photon polarization tensor. However, we examine that the LLL approximation is not enough for the thermal polarization tensor. The thermal tensor obtains non-trivial contributions from the finite-n Landau levels. And, photon spectra gains a large imaginary contribution in thermal medium, which is the so-called Landau damping. Finally, it is argued that the summation of Matsubara frequency is not commuted with Landau level ones, such conjecture is excluded in our calculations.
Universal quantum gates for hybrid systems assisted by quantum dots inside double-sided optical microcavities

We present some deterministic schemes to construct universal quantum gates, that is, controlled- NOT, three-qubit Toffoli, and Fredkin gates, between flying photon qubits and stationary electron-spin qubits assisted by quantum dots inside double-sided optical microcavities. The control qubit of our gates is encoded on the polarization of the moving single photon and the target qubits are encoded on the confined electron spins in quantum dots inside optical microcavities. Our schemes for these universal quantum gates on a hybrid system have some advantages. First, all the gates are accomplished with the success probability of 100% in principle. Second, our schemes require no additional qubits. Third, the control qubits of the gates are easily manipulated and the target qubits are perfect for storage and processing. Fourth, the gates do not require that the transmission for the uncoupled cavity is balanceable to the reflectance for the coupled cavity, in order to get a high fidelity. Fifth, the devices for the three universal gates work in both the weak coupling and the strong coupling regimes, and they are feasible in experiment.
Human Disease Prediction Using Machine Learning Classification Algorithms

The importance of healthcare system is growing and the pandemic has proved that the healthcare management is an important part of an individual's life. Most medical cases requires proper diagnoses in a prior consultation, and it is very important to get an accurate prediction of the disease. In this paper, we have taken some most common and very serious human diseases as an input in our dataset, after preprocessing, data cleaning, and using different machine learning classification algorithms such as Random Forest, Naïve Bayes, Ada Boost, Bagging Stacking, we found that the Machine learning classification algorithms can be a better option for the early prediction with more accuracy for the human diseases.
Biocultural heritage construction and community-based tourism in an important indigenous agricultural heritage system of the southern Andes

ABSTRACT Traditional agricultural systems reflect the close relationship between human communities and local ecosystems. The inheritance of knowledge, practices and beliefs, in which this relationship is materialised, or biocultural memory, is key for these systems’ conservation and adaptation to social-environmental changes. Heritage construction processes may be used in a bid to conserve and increase awareness of this inheritance. Tourism is one alternative but is not immune to controversy. Through a qualitative methodology and participatory action research, this study examines biocultural heritage construction in an Important Agricultural Heritage System (IAHS) in Mapuche-Pewenche territory in the southern Andes. Based on the community-based tourism experience of two campesino cooperatives, our study points out how local actors understand and interpret their heritage as well as the opportunities and challenges of showcasing it through tourism. We found that the inheritance is understood as the way of life associated with Mapuche rural culture and, particularly, agricultural practices that support local food systems with a strong identity component. In these experiences of community-based tourism, we identify opportunities and challenges for reinforcing biocultural memory and inheritance in an IAHS. We discuss tourism development in IAHS sites, putting the communities that inhabit and maintain them in a central position.
Scale breaking and fluid dynamics in a dilute two-dimensional Fermi gas

We study two observables related to the anomalous breaking of scale invariance in a dilute two dimensional Fermi gas, the frequency shift and damping rate of the monopole mode in a harmonic confinement potential. For this purpose we compute the speed of sound and the bulk viscosity of the two dimensional gas in the high temperature limit. We show that the anomaly in the speed of sound scales as $(2P-\rho c_s^2)/P\sim z/[\log(T/E_B)]^2$, and that the bulk viscosity $\zeta$ scales as $\zeta/\eta \sim z^2/[\log(T/E_B)]^6$. Here, $P$ is the pressure, $c_s^2$ is the speed of sound, $\eta$ is the shear viscosity, $z$ is the fugacity, and $E_B$ is the two-body binding energy. We show that our results are consistent with the experimental results of Vogt et al. [Phys. Rev. Lett. 108, 070404 (2012)]. Vogt et al. reported a frequency shift $\delta\omega/\omega$ of the order of a few percent, and a damping rate smaller than the background rate $\Gamma/\omega_0\sim 5%$.
Caste-specific quantitative genetics and phylogenetic signal analysis revealed the morphological adaptation of Asian weaver ant, Oecophylla smaragdina (Hymenoptera, Formicidae)

Insect caste development and their morphological divergence are not yet studied well, especially in ants. However, the role of developmental and genetic integration in evolution is contentious. In our study, we tried to reveal the quantitative genetics selection responses, phylogenetic signal, and evolutionary origin of weaver ant female castes (queen, major and minor). The widening and lengthening of the head region, as well as the well-developed mandibular process, are the major heritable characteristics found in the major worker ants. We hypothesized that these conserved and heritable characteristics may help the major worker ants for defense, foraging purposes and other nest-building function aspects. However, in the case of minor worker, small heads and the reduced mandibular process are the more heritable characteristics. Compared to worker ants, in queen, the highly heritable and conserved morphological character is well-developed thoracic regions and large-sized abdomen. It is interesting to note that there is no detectable phylogenetic signal across the female cast of the Asian weaver ants, which suggests that the caste development and morphological divergence are environmentally modulated not evolutionary conserved. From this study, we concluded that caste-specific morphological shape and size are highly conserved traits and these traits are modulated by their niche preferences. GP -1 decreased gradually from 55.33 to 1.01. These values show the genetic inheritance of shape changes represented as linear combinations of the landmark coordinates. In the eigenvalue, maximum heritability shape changes correspond to the first eigenvalues, and these shape changes were associated with PC1 of the phenotypic covariations. The low value of the eigenvector indicated minimal heritability.
H5-Bridge-Based Bowl-Shape Wireless Charger for Multiple Loads

This article proposes a five-coil bowl-shape wireless charger based on an H5 bridge inverter. Inside the bowl, the five coils are customized and placed at different charging areas, which are able to offer two power channels for fast charging and multiload charging, respectively. A five-switch H5 bridge inverter is used to feed the optimal voltage through its multimode operation, which helps enhance the efficiency under various load conditions. The zero voltage switching is discussed for all the switches and achieved under the worst case, which is justified by the harmonic analysis. Finally, a 50-W experimental prototype is built and measured under various load conditions, and the peak charging efficiency is 88%.
Conversion of Sugarcane Trash to Nanocrystalline Cellulose and Its Life Cycle Assessment

Sugarcane trash (SCT) is a promising, underutilized raw material for producing value-added bio-based materials. Nanocrystalline cellulose (NCC) production conditions were obtained from the experiment. On the other hand, bioethanol production conditions were retrieved from the secondary data. This study compared the environmental impact of SCT in NCC production to that of bioethanol. For NCC production, SCT was subjected to organosolv pretreatment (140, 160, or 180 °C) in a mixed solvent system (methyl isobutyl ketone (MIBK), ethanol, and water), bleached, and then hydrolyzed with different concentrations of sulfuric acid (50 and 58%) for varying times. Organosolv pretreatment at 180 °C removed 98.24 and 81.15% of the hemicellulose and lignin, respectively, resulting in 73.51 and 79.72% cellulose purity and recovery. In addition, bleaching increased the cellulose purity to 95.42%. Field Emission Transmission Electron Microscopy (FE-TEM) analysis showed that NCC's small 2:1 elliptical particles were found at the hydrolysis of 50% H2SO4 for 45 min. The X-ray diffraction (XRD) pattern revealed 70% crystalline index values for NCC obtained from 50% H2SO4 with 45 min retention times. Then, the optimum conditions of NCC production were used for LCA analysis (Sigmapro software). The analysis included global warming, marine ecotoxicity, fresh water, and human carcinogenic toxicity. NCC production's electricity consumption (freeze-dried step) was the highest environmental impact on LCA analysis.