Miracle-dz/UniFAR-FTUs huggingface dataset:
A numerical study on the melting behaviors of paraffin with and without Al2O3 nanoparticles Al2O3 nanopartiküllü ve nanopartikülsüz parafinin erime davranışları üzerine sayısal bir çalışma

One of the most effective methods of thermal energy storage is the use of Phase Change Materials (PCM). Paraffin, which is among the organic PCMs, is frequently used in thermal storage applications due to its easy accessibility and high heat storage capacity. However, it significantly limits the thermal charge / discharge (melting / solidification) rate of systems caused by their low thermal conductivity. There are many methods applied to enhance the thermal conductivity of paraffin. In this research, the melting processes of pure paraffin (Rubitherm RT50) and paraffin containing 10% Al2O3 nanoparticle in a rectangular melting area were numerically investigated. For comparison, the effect of increasing the wall temperature of the rectangular area to 65 ° C, 70 ° C and 75 ° C on the total melting time was investigated for both pure paraffin (melting temperature 50 ° C) and paraffin with nanoparticle additives. In this study, in which the Computational Fluid Dynamics (CFD) approach was used, ANSYS Fluent software was used to perform numerical analysis. Consequently it was determined that the use of Al2O3 nanoparticles improved the rate of paraffin heat transfer.
USE OF AGILE AND OPEN INNOVATION APPROACHES IN EXECUTING THE PROJECTS: A FIELD STUDY ON PROJECT MANAGERS

Agility and open innovation are two concepts that support each other as well as being approaches that contribute a lot to the project managers. While they seem to be different methodologies, the fact that particularly they are collaborative and knowledge-based approaches and that they aim to attain innovative outputs by looking at the events from similar perspectives bring the open innovation and agility close to each other. This study strived to measure the awareness of the project managers about agile and open innovation approaches in executing the projects. While it was observed in the study results that an awareness about and use of the two approaches started to form, it appeared that the projects in which these two approaches are used differed in a certain extent from each other
Vertical Mandibular and Trunk Symmetry in Indonesian Orthodontic Patients

Objective: To analyze differences in vertical mandibular and trunk symmetry in orthodontic patients. Material and Methods: This was a cross-sectional study of 129 growing orthodontic patients who sought orthodontic treatment at the Dental Hospital Universitas Sumatera Utara, Indonesia. Mandibular symmetry index was observed with pre-treatment panoramic radiography based on Kjellberg's technique and trunk symmetry was evaluated based on questionnaires and visual observation. Vertical mandibular asymmetry was decided if the index of asymmetry was lower than 93.7%. The bivariate analysis used the chi-squared and Fisher's exact tests, with a significance level of 5%. Results: There was a significant association between vertical mandibular and trunk symmetry (p<0.05). The prevalence odds ratio for the association with vertical mandibular asymmetry was 3.007 (95% CI = 1.016-8.905) for trunk asymmetry. Conclusion: The necessity to consider trunk symmetry could be included in orthodontics treatment of any malocclusion with vertical mandibular asymmetry that might require a multidisciplinary approach in the future.
Increasing the Fire Resistance of Particleboard Used in Architecture with Colophony Doped Boron Compounds

Mimaride goz onune alinmasi gereken onemli faktorlerden birisi de kullanilan malzemelerin yangin dayanimidir. Bu calismada, mimaride yaygin olarak kullanilan yonga levhalarin yangin dayanimlarinin artirilmasi amaclanmistir. Bu maksatla borlu bilesiklerin kolofan katkisi ile modifiye edilmesinden elde edilen yeni tip emprenye maddesi kullanilarak yanma direncinin artirilmasi hedeflenmistir. Bu kapsamda TS 642 ISO 554’e uygun oalrak hazirlanan yonga levha ornekleri ASTM-E 160-50’ye uygun olarak boyutlandirilmistir. Hazirlanan numunelerin yanma deneyleri ASTM-E 160-50 E’ye gore yapilmistir. Deneylerde yanma suresi, agirlik kaybi oranlari, AKY, KKY, KHY sicaklilari belirlenerek kontrol numuneleri ile karsilastirilmistir. Sonuc olarak yeni tip emprenye maddesininAKY, KKY sicaklik degerlerinde ortalama %5, KHY sicaklik degerlerinde % 1,8, agirlik kaybinda %0,5 dusus ve yanma suresinde %2 oraninda artis sagladigi olculmustur. Mimaride yangin riski yuksek olan yonga levha kullanim alanlarinda bu durum dikkate alinabilir.
Flood vulnerability and resilience: Exploring the factors that influence flooding in Sarawak

Flooding is the most common natural disaster in Malaysia, resulting in chaos and disruptions to social and economic activities, damage to roads and railway tracks, vehicles, affecting the level of properties, loss of life, and rise in vulnerability. In addition to natural causes, floods are mainly attributed to continuous heavy rainfall, rapid development, unplanned urbanization, poor drainage system, and environmental degradation. This annual occurrence of floods has given a big impact on the lives of humans and other living beings. Due to the negative effects of floods, we need to pay serious attention and take alternative ways to reduce this disaster. This study aimed to investigate the vulnerability factors and understand the concept of vulnerability and resilience to manage floods in Sarawak. The researcher primarily focused on reviewing the printed and documented material of disasters in order to find the vulnerability factors. Based on the findings, it can be concluded that nature, human, and governance factors, contributed mostly to floods. The present study shows that vulnerability reduction along with emergency preparedness can reduce flood damages and fatalities. The innovative technologies must have to be considered to reduce vulnerability and build resilience for sustainable disaster risk reduction.
Dynamic behavior of molten pool flow field for active laser welded-thick stainless steel plates

By combining numerical simulation and experimental investigation, this paper intensively investigated the influence rules of adding three active agents (SiO2, TiO2 and NaF) on the dynamic behaviors of flow field in the laser welding 304 stainless steel thick plate pool. First of all, the mathematical model of the activating laser welding stainless steel thick plate was constructed to numerically investigate the impact of active agents on the fluid flow in the pool. Secondly, based on the tungsten particle tracing principle test, the high speed camera system was adopted for real-time monitoring to investigate the mechanism of action of the active agents on the flow field in the pool. The results suggested that, the active agents partially affected the mode of fluid flow. The velocity vector from both sides of the pool to the center occurred on the pool surface, while vortex from the pool margin to the center occurred on the pool cross section. The phenomenon that the tracing tungsten particles moving from the pool margin to the center, it shows that the flow direction of the fluid changed after coating with the active agent, the fluid flew from the pool margin to the center. At the same time, the coating of active agents changed the flow velocity of fluid inside the pool, and SiO2 active agent has the most significant increase effect, the maximum velocity of fluid flow on the upper surface, the longitudinal and cross sections at the same position of the SiO2 active agent coated specimen increased by 25.8%, 8% and 33.8%, respectively, compared with that without the active agents.
The Italian Civil Code Network Analysis

The regulation of private law is a focal element in the metamorphosis of society, and by gaining a broader vision of the legal domain we might grasp novel or potentially hidden nuances and characteristics. In this work, we explore the Italian Civil Code (ICC) from an unprecedented perspective based on network analysis. We develop a text processing method to identify and extract article references from the ICC and, upon these, we define network models capturing their relation structures either at a book and corpus scale. The exploitation of the main structural features of these networks leads us to unveil meaningful patterns, holding within and across the books composing the ICC. Furthermore, by leveraging a community detection task, we investigate whether the formation of a community is related to the topic coherence of its assigned articles over the portions of books involved. Our findings reveal useful indicators that may help legal experts and practitioners enhance their knowledge from a novel perspective provided by the network of article references through the ICC.
Has the Pandemic Changed Moral Attitudes and Organizational Ethics in Knowledge Workers?

We explored the Moral Attitudes (MA) and Organizational Ethics (OETH) before and during the COVID-19 Pandemic in relation to the sex of Information Technology (IT) Knowledge Workers (KW) in regional, crossborder enterprises in Poland, a transition economy. Two dimensions of MA and three dimensions of OETH - Ethical Optimism (ETO), Corporate Social Responsibility (CSR), and Top Management Action (TMA) - were investigated. The analysis was carried out on data obtained from a random survey among KW representing mainly small and medium-sized enterprises in the cross-border region of Lower Silesia. Our research findings suggest that KW manifest high enough moral codes that do not correlate too strongly with OETH. Pandemic and sex, in general, affect the relationship between MA and OETH of KW in the transition economy. © AMCIS 2021.
Financial Innovation in the 21st Century: Evidence from U.S. Patents

We develop a unique dataset of 24 thousand U.S. finance patents granted over last two decades to explore the evolution and production of financial innovation. We use machine learning to identify the financial patents and extensively audit the results to ensure their reasonableness. We find that patented financial innovation is substantial and economically important, with the number of annual grants expanding from a few dozen in the 1990s to over 2000 in the 2010s. The subject matter of financial patents has changed, consistent with the industry’s shift in revenue and value-added towards household investors and borrowers. The surge in financial patenting was driven by information technology firms and others outside of financial sector, which collectively accounted for 69% of the awards. The location of innovation has shifted, with banks moving this activity from regions with tight financial regulation to more permissive ones. High-tech regions have attracted financial innovation by payments, IT, and other non-financial firms. Turning to the source of these ideas, while academic knowledge remained associated with more valuable patents, citations in finance patents to academic papers, especially in those by banks, fell sharply. Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber. org.
Stock Returns and Inflation Shocks in Weaker Economic Times

We show that the concurrent relation between quarterly stock returns and inflation shocks is economically and robustly significant only over weaker economic times, strongly negative prior to the late 1990s and strongly positive afterwards. Conversely, in the stronger economic times over our 1981 to 2017 sample, this stock-inflation relation is relatively much smaller and usually marginally negative. Our evidence suggests a role for two complementary channels. First, we find consistent state-dependent patterns in how inflation shocks are related to expected economic growth and/or the equity risk premium, indicating that inflation non-neutrality is stronger over weaker economic times. Second, our findings imply that the inflation signal about the underlying economic state intensifies during weaker economic times, due to the elevated economic-state uncertainty then. We also contribute by contrasting subjective (survey-based) vs. objective inflation shocks and by evaluating the relation between inflation shocks and forward equity yields.
A Review on MR Based Human Brain Parcellation Methods

Brain parcellations play a ubiquitous role in the analysis of magnetic resonance imaging (MRI) datasets. Over 100 years of research has been conducted in pursuit of an ideal brain parcellation. Different methods have been developed and studied for constructing brain parcellations using different imaging modalities. More recently, several data-driven parcellation methods have been adopted from data mining, machine learning, and statistics communities. With contributions from different scientific fields, there is a rich body of literature that needs to be examined to appreciate the breadth of existing research and the gaps that need to be investigated. In this work, we review the large body of in vivo brain parcellation research spanning different neuroimaging modalities and methods. A key contribution of this work is a semantic organization of this large body of work into different taxonomies, making it easy to understand the breadth and depth of the brain parcellation literature. Specifically, we categorized the existing parcellations into three groups: Anatomical parcellations, functional parcellations, and structural parcellations which are constructed using T1-weighted MRI, functional MRI (fMRI), and diffusion-weighted imaging (DWI) datasets, respectively. We provide a multi-level taxonomy of different methods studied in each of these categories, compare their relative strengths and weaknesses, and highlight the challenges currently faced for the development of brain parcellations.
Obfuscation-resilient Android Malware Analysis Based on Contrastive Learning

—Due to its open-source nature, Android operating system has been the main target of attackers to exploit. Malware creators always perform different code obfuscations on their apps to hide malicious activities. Features extracted from these obfus-cated samples through program analysis contain many useless and disguised features, which leads to many false negatives. To address the issue, in this paper, we demonstrate that obfuscation-resilient malware analysis can be achieved through contrastive learning. We take the Android malware classiﬁcation as an example to demonstrate our analysis. The key insight behind our analysis is that contrastive learning can be used to reduce the difference introduced by obfuscation while amplifying the difference between malware and benign apps (or other types of malware). Basedon the proposed analysis, we design a system that can achieve robust and interpretable classiﬁcation of Android malware. To achieve robust classiﬁcation, we perform contrastive learning on malware samples to learn an encoder that can automatically extract robust features from malware samples. To achieve interpretable classiﬁcation, we transform the function call graph of a sample into an image by centrality analysis. Then the corresponding heatmaps are obtained by visualization techniques. These heatmaps can help users understand why the malware is classiﬁed as this family. We implement IFDroid and perform extensive evaluations on two widely used datasets. Experimental results show that IFDroid is superior to state-of-the-art Android malware familial classiﬁcation systems. Moreover, IFDroid is capable of maintaining 98.2% true positive rate on classifying 8,112 obfuscated malware samples.
Existence of The Solution to The Quadratic Bilinear Equation Arising from A Class of Quadratic Dynamical Systems

A quadratic dynamical system with practical applications is taken into considered. This system is transformed into a new bilinear system with Hadamard products by means of the implicit matrix structure. The corresponding quadratic bilinear equation is subsequently established via the Volterra series. Under proper conditions the existence of the solution to the equation is proved by using a fixed-point iteration.
Effective field theories of topological crystalline insulators and topological crystals

We present a general approach to obtain effective field theories for topological crystalline insulators whose low-energy theories are described by massive Dirac fermions. We show that these phases are characterized by the responses to spatially dependent mass parameters with interfaces. These mass interfaces implement the dimensional reduction procedure such that the state of interest is smoothly deformed into a topological crystal, which serves as a representative state of a phase in the general classification. Effective field theories are obtained by integrating out the massive Dirac fermions, and various quantized topological terms are uncovered. Our approach can be generalized to other crystalline symmetry protected topological phases and provides a general strategy to derive effective field theories for such crystalline topological phases.
Assigning topics to documents by successive projections

Topic models provide a useful tool to organize and understand the structure of large corpora of text documents, in particular, to discover hidden thematic structure. Clustering documents from big unstructured corpora into topics is an important task in various areas, such as image analysis, e-commerce, social networks, population genetics. A common approach to topic modeling is to associate each topic with a probability distribution on the dictionary of words and to consider each document as a mixture of topics. Since the number of topics is typically substantially smaller than the size of the corpus and of the dictionary, the methods of topic modeling can lead to a dramatic dimension reduction. In this paper, we study the problem of estimating topics distribution for each document in the given corpus, that is, we focus on the clustering aspect of the problem. We introduce an algorithm that we call Successive Projection Overlapping Clustering (SPOC) inspired by the Successive Projection Algorithm for separable matrix factorization. This algorithm is simple to implement and computationally fast. We establish theoretical guarantees on the performance of the SPOC algorithm, in particular, near matching minimax upper and lower bounds on its estimation risk. We also propose a new method that estimates the number of topics. We complement our theoretical results with a numerical study on synthetic and semi-synthetic data to analyze the performance of this new algorithm in practice. One of the conclusions is that the error of the algorithm grows at most logarithmically with the size of the dictionary, in contrast to what one observes for Latent Dirichlet Allocation.
A stochastic reconstruction theorem

In a recent landmark paper, Khoa L\^e (2020) established a stochastic sewing lemma which since has found many applications in stochastic analysis. He further conjectured that a similar result may hold in the context of the reconstruction theorem within Hairer's regularity structures. The purpose of this article is to provide such a stochastic reconstruction theorem. We also discuss two variations of this theorem, motivated by different constructions of stochastic integration against white noise. Our formulation makes use of the distributional viewpoint of Caravenna--Zambotti (2021).
Kolmogorov bounds for decomposable random variables and subgraph counting by the Stein–Tikhomirov method

In his work \cite{Ti80}, Tikhomirov combined elements of Stein's method with the theory of characteristic functions to derive Kolmogorov bounds for the convergence rate in the central limit theorem for a normalized sum of a stationary sequence of random variables satisfying one of several weak dependency conditions. The combination of elements of Stein's method with the theory of characteristic functions is sometimes called \emph{Stein-Tikhomirov method}. \citet*{AMPS17} successfully used the Stein-Tikhomirov method to bound the convergence rate in contexts with non-Gaussian targets. \citet*{Ro17} used the Stein-Tikhomirov method to bound the convergence rate in the Kolmogorov distance for normal approximation of normalized triangle counts in the Erd\"os-R\'enyi random graph.
Adaptation of Quadruped Robot Locomotion with Meta-Learning

Animals have remarkable abilities to adapt locomotion to different terrains and tasks. However, robots trained by means of reinforcement learning are typically able to solve only a single task and a transferred policy is usually inferior to that trained from scratch. In this work, we demonstrate that meta-reinforcement learning can be used to successfully train a robot capable to solve a wide range of locomotion tasks. The performance of the meta-trained robot is similar to that of a robot that is trained on a single task.
Technical Report for Valence-Arousal Estimation in ABAW2 Challenge

In this work, we describe our method for tackling the valence-arousal estimation challenge from ABAW2 ICCV-2021 Competition. The competition organizers provide an in-the-wild Aff-Wild2 dataset for participants to analyze affective behavior in real-life settings. We use a two stream model to learn emotion features from appearance and action respectively. To solve data imbalanced problem, we apply label distribution smoothing (LDS) to re-weight labels. Our proposed method achieves Concordance Correlation Coefficient (CCC) of 0.591 and 0.617 for valence and arousal on the validation set of Aff-wild2 dataset.
Morpho-kinematic Properties of Wolf–Rayet Planetary Nebulae

The majority of planetary nebulae (PNs) show axisymmetric morphologies, whose causes are not well understood. In this work, we present spatially resolved kinematic observations of 14 Galactic PNs surrounding Wolf–Rayet ([WR]) and weak emission-line stars (wels), based on the Hα and [N ii] emission taken with the Wide Field Spectrograph on the Australian National University 2.3 m telescope. Velocity-resolved channel maps and position–velocity diagrams, together with archival Hubble Space Telescope (HST) and ground-based images, are employed to construct three-dimensional morpho-kinematic models of 12 objects using the program shape. Our results indicate that these 12 PNs mostly have elliptical morphologies, with either open or closed outer ends. The kinematic maps show the on-sky orientations of the interior shells in NGC 6578 and NGC 6629, as well as the compact (≤6″) PNs Pe 1-1, M 3-15, M 1-25, Hen 2-142, and NGC 6567, in agreement with the elliptically symmetric morphologies seen in high-resolution HST images. Point-symmetric knots in Hb 4 exhibit deceleration with distance from the central star, which could be due to shock collisions with the ambient medium. The velocity dispersion maps of Pe 1-1 also disclose the shock interaction between its collimated outflows and the interstellar medium. Collimated bipolar outflows are also visible in the position–velocity diagrams of M 3-30, M 1-32, and M 3-15, which are reconstructed by tenuous prolate ellipsoids extending upward from dense equatorial regions in the kinematic models. The formation of aspherical morphologies and collimated outflows in these PNs could be related to the stellar evolution of hydrogen-deficient [WR] and wels nuclei, which require further investigation.