Miracle-dz/UniFAR-FTUs huggingface dataset:
PILAR: Studying and Mitigating the Influence of Configurations on Log Parsing

The significance of logs has been widely acknowledged with the adoption of various log analysis techniques that assist in software engineering tasks. Many log analysis techniques require structured logs as input while raw logs are typically unstructured. Automated log parsing is proposed to convert unstructured raw logs into structured log templates. Some log parsers achieve promising accuracy, yet they rely on significant efforts from the users to tune the parameters to achieve optimal results. In this paper, we first conduct an empirical study to understand the influence of the configurable parameters of six state-of-the-art log parsers on their parsing results on three aspects: 1) varying the parameters while using the same dataset, 2) keeping the same parameters while using different datasets, and 3) using different samples from the same dataset. Our results show that all these parsers are sensitive to the parameters, posing challenges to their adoption in practice. To mitigate such challenges, we propose PILAR (Parameter Insensitive Log Parser), an entropy-based log parsing approach. We compare PILAR with the existing log parsers on the same three aspects and find that PILAR is the most parameter-insensitive one. In addition, PILAR achieves the second highest parsing accuracy and efficiency among all the state-of-the-art log parsers. This paper paves the road for easing the adoption of log analysis in software engineer practices.
Inﬂuence of Miura-origami shapes on drag in turbulent ﬂows

This work uses data from direct numerical simulation (DNS) to examine the drag-reduction potential of diﬀerent surfaces generated from a Miura-origami basis—folded, creased material structures with no tearing. Miura surfaces span a wide set of possible realizations but presently are deployed to emulate optimized drag-reducing riblets. Flexibility of the Miura fold also permits modiﬁed surfaces that transform traditional straight riblets by including an additional streamwise wavelength, i.e., triangular riblets with streamwise waviness. As such, we report the drag-reduction characteristics of a set of Miura surfaces to identify optimal conﬁgurations. To build conﬁdence in our ﬁndings, code-to-code veriﬁcation is performed by comparing two ﬂow solvers that perform DNS of a separate, complex, highly skewed Miura-fold roughness topology. Comparing their respective output statistics, a good level of agreement is observed. Returning to the drag-reducing wavy riblets, turbulence quantities are collected to explore modulation of dynamical scales through premultiplied energy spectra. The literature shows that dynam-ically oscillating walls are able to deplete streaks in the streamwise turbulent ﬂuctuations, but until now the eﬃcacy of the passive analogue had been unknown. Further, alignment of near-wall structures with the wavy surface topology is visualized and quantiﬁed to reveal the wall-normal extent to which the wall may aﬀect turbulence. The primary ob-jective of this work establishes the potential for static wavy Miura surfaces to enhance drag reduction as compared to classical straight riblets. Drag decomposition reveals that the role of a thickening viscous region is responsible for the shift in observed performance. This is a ﬁrst step toward actuated dynamic origami surfaces in a drag-reduction context.
Klasifikasi Topik Berita Berbahasa Indonesia Menggunakan k-Nearest Neighbor

Abstrak Masyarakat Indonesia kini mulai beralih dari konsumsi berita dalam bentuk surat kabar ke berita online. Persentase konsumsi berita melalui online mencapai 96 persen berdasarkan riset lembaga Global GFK. Angka tertinggi dibandingkan dengan konsumsi berita melalui televisi sebesar 91 persen, surat kabar 31 persen dan radio sebesar 15 persen. Akan tetapi begitu banyak berita bisa menyulitkan kerja editor dalam mengategorikan setiap berita yang ada, oleh karena itu dibutuhkan suatu sistem yang bisa mengategorikan berita sesuai dengan kategori masing-masing. Pada penelitian ini bertujuan untuk membuat suatu sistem yang mampu mengategorikan setiap berita berdasar dari topik berita tersebut. Metode yang digunakan dalam mengklasifikasi berita adalah k-Nearest Neighbor (K-NN) yang merupakan algoritma klasifikasi sederhana namu memiliki performa yang tinggi. Pada penelitian ini perancangan sistem dilakukan proses pengumpulan dataset, preprocessing data, klafikasifikasi dengan k-nn, dan terakhir dilakukan pengujian system. Dalam penelitian ini system yang dibangun mampu menghasilkan performa micro average f1-measure sebesar 69,9% dengan nilai k=16. Kata Kunci: Klasifikasi Teks, Text Mining, K-Nearest Neighbors Abstract Indonesian society is now starting to roll out from news consumption in the form of newspapers to online news. The percentage of online news consumption reached 96 percent based on Global GFK research institute. The percent number is the reverse of the number of news stories. It will be very much news to complicate the work of editors in categorizing every news that there is, therefore required a system that can categorize the news according to their respective categories. In this study is for a system that is able to categorize any news based on the news topic. The method used in classifying news is k-Nearest Neighbor (K-NN) which is a simple content algorithm namu has high performance. In this research the system design is done the process of completion of dataset, preprocessing data, klafikasifikasi with k-nn, and last done by testing system. In this research the built system is able to produce the average micro performance of f1measure equal to 69,9% with value k = 16. Keywords: Classification Text, Text Mining, K-Nearest Neighbors
The Use of Artiﬁcial Intelligence on Indonesia Online Shopping Application in Relation to Customer Acceptance

The fast growth of digital technology has changed the way people shop online. Researchers and retailers need to know how people react to new technologies, especially artiﬁcial intelligence. The purpose of this study was to assess consumer perceptions of an AI device’s utility, usability, and purchase intention. In this study, we suggest the TAM’s expansion for use in the area of e-commerce. By adding a mediating component, trust, to the original variables of the technology acceptance model, the relationship between perceived usefulness, perceived ease of use, and customer purchasing intention will be adjusted. Using the technology acceptance model (TAM) as a theoretical foundation, this study examines customer trust and acceptability of Artiﬁcial Intelligence in online buying. The total number of respondents was 170, and SEM-AMOS was used to analyse the data, which comprised both the realibility test and structural equation modelling. The hypothesis was evaluated based on the results of second-order measurement model. The study’s ﬁndings indicate perceived usefulness, perceived ease of use have a direct inﬂuence on customer buying intention. In addition, the research showed the mediation inﬂuence of trust between perceived usefulness and perceived ease of use among consumer online buying. The results of this study that valuable implications for web shop owners to increase customer acceptance.
The Circulation and Sharing of High-Tech Talents and the Transnational Social Spaces Study Based on Stata Software

Stata is considered as an integrated and complete statistical software which offers its users to analyzing data, managing data and drawing professional diagrams.With the advent of information society, the advances and changes in science and technology are leading to growing requirements for innovation, and as a result, talents especially the high-tech talents have increasingly been contended by many countries. Nowadays, the flow of global high-tech talents has been changing from previous “Brain Drain”, which represents a unidirectional and linear model from underdeveloped countries to developed countries or regions, to “Brain Circulation”, a pattern owning bidirectional or multidirectional features. This paper will mainly use Stata software to conduct regression analysis with the aim of testing the correlation between brain drain and economic growth. In order to ensure the variable data utilized are relatively accurate, this paper has conducted stability test, multicollinearity test and correlation test. The findings are a growth in 1% in brain drain will result in 1.2% decrease in GDP per capita. It means the influence of Brain Drain is real and countries must pay adequate attention to. Combined the model of transnational social space, this paper theoretically expands the study on the influencing factors of Brain Circulation. It supplies a new perspective ofmigration system of talents and riches the study results of benefits-sharing mechanisms of global high-tech talents.
Improved Switched System Approach to Networked Control Systems With Time-Varying Delays

An improved switched system approach is proposed for the stability and stabilization of networked control systems with time-varying delays. The approach features a mode-dependent state feedback controller guaranteeing the exponential stability of the closed-loop system, which is implemented within the packet-based control framework. The effectiveness of the proposed approach is finally demonstrated experimentally by a networked inverted pendulum control system.
A Characteristic Statistic Based Femoral Contour Point-set Registration Algorithm

The point-set registration technology has been widely applied in the field of medical image registration. This paper proposed a characteristic statistic based femoral contour point-set registration algorithm, in order to overcome the flaw of getting into local extrema and of poor global performance in the iterative optimization process in existing registration algorithms. First, it uses the Gaussian mixture model to represent the correspondence of points between two point-sets, and selects the global parameter associated with the objective function as the characteristic statistical items. Then, it leverages the statistical variation in the optimization process to guide the optimal search, yielding the global optimal solution of statistical items, and realizing the registration of two point-sets. In the end, this algorithm is applied to solve the registration problem of femoral contour characteristic point-set. The experimental results reveal that the proposed registration method performs more effective, faster, and more accurate compared with Coherent Point Drift (CPD) algorithm.
A continuum model of lithium ion transport inside graphene

In this letter, we demonstrate the usage of a continuum equation in conjunction with Poisson equation and mean-field theory to investigate the ion transport and storage pattern of lithium ions between double-layer graphene. The majority of recent research on the ion transport for such batteries merely focuses on the effect of an external electric field acting on ions. Here, we emphasize the nanoscale mechanics of the graphene anode so that the forces between ions and the host material, and steric effects between lithium ions are incorporated. Under certain electric fields, multi-layers are formed between graphene sheets, and some related storage phenomenon is also investigated for potential applications in lithium ion battery and providing further understanding of ion transport inside biological channels.
Genetic features of representatives of Malus Mill. for the formation of identified collections and breeding use

For the active mobilization of bioresources of the leading agricultural fruit plants, especially apple (Malus × domestica Borkh.), and the inclusion of the best samples of the gene pool in the breeding, it is necessary to know their genetic characteristics according to the priority desired traits. The purpose of the study is to study the allelic polymorphism of the Md-PG1 in representatives of Malus Mill. to identify sources of long-term keeping of fruits and to form an identified collection of apple trees for breeding use. The studies were carried out in the Center for Collective Use «Research and Breeding Collection of Genetic Resources of Horticultural Crops»; generally accepted programs and methods of variety study and breeding of apple trees. Based on the data of molecular genetic analysis, carriers of the allelic combination AA for the Md-PG1 gene were identified - apple varieties: Smeralda, Egemen, Georgiya, hybrids 17/1-6-42 (Champion × Modi) and 17/2-5-15 (Renuartsiv × Carmen). The selected varieties and hybrid forms are promising in the process of creating domestic genetic resources with improved quality indicators, including a genetically determined increase in the shelf life of fruits.
Current-density functional theory for bosonic superfluids

A finite-temperature current-density functional theory for bosonic superfluids (sf-CDFT) in the thermal equilibrium state is proposed herein. In the sf-CDFT, hydrodynamic physical quantities, such as particle number density, current density, and the order parameter of the Bose–Einstein condensation, are chosen as the basic variables. This theory enables the simultaneous reproduction of the particle number and current densities of both the superfluid and normal fluid components with incorporating effects of the interaction between these components. Specifically, these components are determined by solving two single-particle equations, i.e., the Gross–Pitaevskii–Kohn–Sham and Kohn–Sham equations. Furthermore, using the continuity equation of superfluids, we present the sum rule for the exchange-correlation energy functional of the sf-CDFT, which is useful for developing the approximate form.
Direct measurement of the electron turbulence-broadening edge transport barrier to facilitate core–edge integration in tokamak fusion plasmas

The integration of a high-performance core and a dissipative divertor, or the so-called ‘core–edge integration,’ has been widely identified as a critical gap in the design of future fusion reactors. In this letter, we report, for the first time, direct experimental evidence of electron turbulence at the DIII-D H-mode pedestal that correlates with the broadening of the pedestal and thus facilitates core–edge integration. In agreement with gyrokinetic simulations, this electron turbulence is enhanced by high η e (η e = Ln /LT e, where Ln is the density scale length and LT e is the electron temperature scale length), which is due to a strong shift between the density and temperature pedestal profiles associated with a closed divertor. The modeled turbulence drives significant heat transport with a lower pressure gradient that may broaden the pedestal to a greater degree than the empirical and theoretically predicted pedestal width scalings. Such a wide pedestal, coupled with a closed divertor, enables us to achieve a good core–edge scenario that integrates a high-temperature low-collisionality pedestal (pedestal top temperature T e,ped > 0.8 keV and a pedestal top collisionality ν*ped < 1) under detached divertor conditions. This paves a new path toward solving the core–edge integration issue in future fusion reactors.
A Model Estimator for Noisy Compact Emission Recovery in Radio Synthesis Imaging

Reconstruction of a noisy compact emission must consider not only the point-spread function but also the effect of noise. However, the traditional threshold method in widely-used CLEAN-based algorithms finds it difficult to effectively prevent noise in the model image during noisy compact-emission reconstruction. This significantly limits the performance in noisy compact-emission reconstruction, such as deep field imaging. There are two major difficulties in the accurate reconstruction of a Stokes-I image of compact emission: first, the threshold method that has been used in practice is difficult to use to separate compact emission and noise; and second, over-subtraction makes it difficult for the reconstructed Stokes-I model image to remain positive. Therefore, a filter-based denoizing mechanism is introduced in the search phase of the model components to separate signal and noise so that the signal can be effectively extracted. The relatively larger loop gain for positive components means that the reconstructed model is in line with astrophysics. This will reduce the errors between the true sky image and the model image. The new model estimator is tested on a simulated JVLA observation with realistic source distributions from the VLA Low-Frequency Sky Survey project and the SKADS/SCubed simulation. The experiments show that it is very effective when used to separate signal and noise to lower the noise in the model image. This work explores the use of existing common software CASA to achieve high dynamic range imaging, which is an important step toward square kilometer array data processing.
The role of γ-aminobutyric acid and salicylic acid in heat stress tolerance under salinity conditions in Origanum vulgare L.

Origanum vulgare L. , a medicinal and aromatic herb, has been used for hundreds of years. This plant contains valuable chemical compounds that can be used as medicine for treatment. On the other hand, a gradual increase in the planet’s average temperature could negatively affect the growth and the composition of the O. vulgare. For this reason, in this study, the effect of two protective compounds, namely salicylic acid (SA) and gamma-aminobutyric acid (GABA), on temperature and salinity stress conditions was investigated. Oregano plants were grown at 23/12°C temperature as control and 27/16°C heat stress in the greenhouse (16/8 h photoperiod) for one months. The plants were treated with GABA and SA and subjected to salt stress for 30 days. Subsequently, the plant’s physiological, biochemical, and phytochemical characteristics were examined. The results showed that all studied traits (in control and treated samples) were significantly different at 27°C, from 23°C. In addition, the highest amount of thymol and carvacrol were detected from plants grown at 27°C. In regards to salinity, stressed- plants had less damage to membrane stability and H2O2 level, when treated with GABA or SA. This study revealed that both SA and GABA compounds had an exellent protective effect on temperature and salt stress on O. vulgare. Based on enzyme-pigment evaluations and secondary metabolites, SA showed a better protective effect on temperature effects and GABA in a saline environment. In general, using these compounds can provide better conditions for the growth and preservation of O. vulgare chemical compounds. However, it certainly requires more experiments to find the signal pathways involved in these processes.
Cell line-specific features of 3D chromatin organization in hepatocellular carcinoma

Liver cancer, particularly hepatocellular carcinoma (HCC), poses a significant global threat to human lives. To advance the development of innovative diagnostic and treatment approaches, it is essential to examine the hidden features of HCC, particularly its 3D genome architecture, which is not well understood. In this study, we investigated the 3D genome organization of four HCC cell lines—Hep3B, Huh1, Huh7, and SNU449—using in situ Hi-C and assay for transposase-accessible chromatin sequencing. Our findings revealed that HCC cell lines had more long-range interactions, both intra- and interchromosomal, compared to human mammary epithelial cells (HMECs). Unexpectedly, HCC cell lines displayed cell line-specific compartmental modifications at the megabase (Mb) scale, which could potentially be leveraged in determining HCC subtypes. At the sub-Mb scale, we observed decreases in intra-TAD (topologically associated domain) interactions and chromatin loops in HCC cell lines compared to HMECs. Lastly, we discovered a correlation between gene expression and the 3D chromatin architecture of SLC8A1, which encodes a sodium-calcium antiporter whose modulation is known to induce apoptosis by comparison between HCC cell lines and HMECs. Our findings suggest that HCC cell lines have a distinct 3D genome organization that is different from those of normal and other cancer cells based on the analysis of compartments, TADs, and chromatin loops. Overall, we take this as evidence that genome organization plays a crucial role in cancer phenotype determination. Further exploration of epigenetics in HCC will help us to better understand specific gene regulation mechanisms and uncover novel targets for cancer treatment.
How Nanotherapeutic Platforms Play a Key Role in Glioma? A Comprehensive Review of Literature

Abstract Glioblastoma (GBM), a highly aggressive form of brain cancer, is considered one of the deadliest cancers, and even with the most advanced medical treatments, most affected patients have a poor prognosis. However, recent advances in nanotechnology offer promising avenues for the development of versatile therapeutic and diagnostic nanoplatforms that can deliver drugs to brain tumor sites through the blood-brain barrier (BBB). Despite these breakthroughs, the use of nanoplatforms in GBM therapy has been a subject of great controversy due to concerns over the biosafety of these nanoplatforms. In recent years, biomimetic nanoplatforms have gained unprecedented attention in the biomedical field. With advantages such as extended circulation times, and improved immune evasion and active targeting compared to conventional nanosystems, bionanoparticles have shown great potential for use in biomedical applications. In this prospective article, we endeavor to comprehensively review the application of bionanomaterials in the treatment of glioma, focusing on the rational design of multifunctional nanoplatforms to facilitate BBB infiltration, promote efficient accumulation in the tumor, enable precise tumor imaging, and achieve remarkable tumor suppression. Furthermore, we discuss the challenges and future trends in this field. Through careful design and optimization of nanoplatforms, researchers are paving the way toward safer and more effective therapies for GBM patients. The development of biomimetic nanoplatform applications for glioma therapy is a promising avenue for precision medicine, which could ultimately improve patient outcomes and quality of life.
Insight from sirtuins interactome: topological prominence and multifaceted roles of SIRT1 in modulating immunity, aging, and cancer

The mammalian sirtuin family, consisting of SIRT1-SIRT7, plays a vital role in various biological processes, including cancer, diabetes, neurodegeneration, cardiovascular disease, cellular metabolism, and cellular homeostasis maintenance. Due to their involvement in these biological processes, modulating sirtuin activity seems promising to impact immune- and aging-related diseases, as well as cancer pathways. However, more understanding is required regarding the safety and efficacy of sirtuin-targeted therapies due to the complex regulatory mechanisms that govern their activity, particularly in the context of multiple targets. In this study, the interaction landscape of the sirtuin family was analyzed using a systems biology approach. A sirtuin protein-protein interaction network was built using the Cytoscape platform and analyzed using the NetworkAnalyzer and stringApp plugins. The result revealed the sirtuin family's association with numerous proteins that play diverse roles, suggesting a complex interplay between sirtuins and other proteins. Based on network topological and functional analysis, SIRT1 was identified as the most prominent among sirtuin family members, demonstrating that 25 of its protein partners are involved in cancer, 22 in innate immune response, and 29 in aging, with some being linked to a combination of two or more pathways. This study lays the foundation for the development of novel therapies that can target sirtuins with precision and efficacy. By illustrating the various interactions among the proteins in the sirtuin family, we have revealed the multifaceted roles of SIRT1 and provided a framework for their possible roles to be precisely understood, manipulated, and translated into therapeutics in the future.