Miracle-dz/UniFAR-FTUs huggingface dataset:
Short- and long-range ordering during the phase transition of the Zn6Sc 1/1 cubic approximant

Using in situ x-ray scattering and synchrotron radiation, we have experimentally elucidated the mechanism of the cubic to monoclinic phase transition in the Zn6Sc 1/1 approximant to an icosahedral quasicrystal. The high-temperature cubic phase is described as a bcc packing of a large Tsai-type icosahedral cluster whose center is occupied by an orientationally disordered Zn4 tetrahedron. A clear monoclinic distortion has been found to take place within 2 K around Tc = 157 K, in excellent agreement with the observed anomalies in the electrical resistivity and heat capacity. Also, a rapid variation of the super-structure reflection intensity is observed. The low-temperature monoclinic phase, as determined by single-crystal x-ray diffraction at 40 K, has been confirmed to consist of ordered Zn4 tetrahedra, oriented in an anti-parallel way along the [ 1 ̄ 01? > ] direction. Above Tc, a diffuse scattering signal is observed at the position of the super-structure reflections, which evidences that a short-range ordering of the Zn4 tetrahedra takes place. In a way similar to a second-order phase transition, the correlation length describing this short-range ordering increases rapidly when the temperature diminishes and almost diverges when the temperature is close to Tc, going from 200 Å at 220 K to reach the very large value of 1200 Å at 161 K. Finally, using single-crystal x-ray diffraction, the atomic structure of the low-temperature monoclinic super-structure (space group C2/c) could be solved. The ordering of the Zn4 tetrahedra is accompanied by a strong distortion of the surrounding shells.
Analysis And Formulation of Marketing Strategies in Third Party Logistics (3pl) to Increase Sales

Currently, the logistics business is one of the business sectors that has a high growth rate, this is in line with the increasing needs of people's lives accompanied by increasingly sophisticated technological developments. The Logistics Market in Indonesia in 2020 – 2024 shows a graph that continues to increase, meaning that the logistics business in Indonesia is always growing from year to year. ABC Company is the grandson of the Pertamina group and is a subsidiary of Pertamina Patra Niaga as a Commercial and Trading sub-holding. With this position, ABC is given the flexibility to do business with other sub-holdings but still in the corridor or core business in the logistics sector. Although the business that is targeted and engaged in still depends on the business potential of the parent company, in this case PT Pertamina group. However, ABC has not been able to capture the business potential that exists in the parent company because management does not get enough trust from the management of the parent company in managing work that is in accordance with the core/identity of ABC. Currently, the marketing strategy carried out by ABC is still not good. This can be proven by the fact that there is no other income and only depends on the operations of the parent company. There is no specific marketing strategy that can directly attract customers outside of the parent company PT. Pertamina is one of the reasons for the lack of income other than the parent company. In solving this problem, this study aims to formulate and analyze marketing strategies using external and internal analysis. Based on the results of the SWOT analysis, the company needs a strategy in the Defense category (W-T Combination) where the strategy is advertising, sales promotion, increasing focus on project channels and revitalizing the role of the HR Department.
Clustering-based Pattern Discovery in Lung Cancer Treatments

Lung cancer is the leading cause of cancer death. More than 238,340 new cases of lung cancer patients are expected in 2023, with an estimation of more than 127,070 deaths. Choosing the correct treatment is an important element to enhance the probability of survival and to improve patient's quality of life. Cancer treatments might provoke secondary effects. These toxicities cause different health problems that impact the patient's quality of life. Hence, reducing treatments toxicities while maintaining or improving their effectiveness is an important goal that aims to be pursued from the clinical perspective. On the other hand, clinical guidelines include general knowledge about cancer treatment recommendations to assist clinicians. Although they provide treatment recommendations based on cancer disease aspects and individual patient features, a statistical analysis taking into account treatment outcomes is not provided here. Therefore, the comparison between clinical guidelines with treatment patterns found in clinical data, would allow to validate the patterns found, as well as discovering alternative treatment patterns. In this work, we have analyzed a dataset containing lung cancer patients information including patients' data, prescribed treatments and their outcomes. Using a Chi-square test and K-Modes clustering algorithm in combination with Pattern Discovery metrics we identify patterns, within the clusters, based on cancer stage and treatment outcomes. Obtained results are analyzed based on statistical and clinical relevance and compared with lung cancer clinical guidelines. The comparison reveals that all patterns found coincide with clinical guidelines recommendations, assessing the validity of the proposed method for pattern discovery in a clinical dataset.
JiangJun: Mastering Xiangqi by Tackling Non-Transitivity in Two-Player Zero-Sum Games

This paper presents an empirical exploration of non-transitivity in perfect-information games, specifically focusing on Xiangqi, a traditional Chinese board game comparable in game-tree complexity to chess and shogi. By analyzing over 10,000 records of human Xiangqi play, we highlight the existence of both transitive and non-transitive elements within the game's strategic structure. To address non-transitivity, we introduce the JiangJun algorithm, an innovative combination of Monte-Carlo Tree Search (MCTS) and Policy Space Response Oracles (PSRO) designed to approximate a Nash equilibrium. We evaluate the algorithm empirically using a WeChat mini program and achieve a Master level with a 99.41\% win rate against human players. The algorithm's effectiveness in overcoming non-transitivity is confirmed by a plethora of metrics, such as relative population performance and visualization results. Our project site is available at \url{https://sites.google. com/view/jiangjun-site/}.
Ranking Aggregation, Inference, and Design

Ranking is a popular topic of recommendation system. One fundamental problem is ranking inference. Given user preference information, ranking inference aims to decide the list of the K most popular items. The essential part of ranking inference problem is how to utilize input information and draw the optimal ranking decision. Papers in various areas including machine learning, approximation algorithms, and operations research study ranking design from different angles (Ailon et al. [2005],Radlinski et al. [2008],Derakhshan et al. [2018]). The ideal preference information is supposed to incorporate comparison results between any two items, but we very often face more complicated situations: only partial preference information is available. For example, users browse videos on YouTube. They only click a couple of attractive videos and provide no data to less interesting ones. Therefore, YouTube can not get access to the full preference information. Ranking agents can also have different objectives. In the e-commerce context, rather than directly inferring ranking sequence by popularity, online retailers focus on objectives like maximizing click through rate, maximizing revenue, etc. In this report, we analyze some cutting-edge ranking methods which build on different information structures and model assumptions, especially those with approximation algorithm approaches. The presentation is intended for dissemination of new ideas from the theory of ranking aimed at a business audience. Our report is organized as follows. In section 2, we discuss the case where ranking agents have full access to user preference information. In section 3, we introduce the partial preference information case with additional choice mechanisms. In section 4, we extend the discussion to online learning algorithms without historical data. We conclude in section 5.
Place: A Short Introduction

List of Figures. Series Editors' Preface. Acknowledgements. 1. Introduction: Defining Place. Space and Place. Place and Landscape. Place as a Way of Understanding. The Remainder of the Book. 2. The Genealogy of Place. Regional Geography. Discovering Place: Humanistic Geography. Place as Home. Radical Human Geography and the Politics of Place. Place as 'Being--in--the--world' versus Place as Social Construct. Place, Practice and Process. Place, Openness and Change. The End of Place? Conclusion: Versions of Place. 3. Reading 'A Global Sense of Place'. Historial Context. Harvey on Place. A Global Sense of Place. Beyond Reactionary and Progressive Senses of Place. Conclusions. 4. Working with Place. Creating Places. In Place / Out--of--place Anachorism. Conclusions. 5. Place Resources. Key Books on Place. Key papers on Place. Introductory Texts on Place. Other Books and Papers on Place. Other Approaches to Place: Ecology, Planning, Architecture. Key Journals. Web Resources. Student Projects and Exercises. Bibliography. Index.
Changes to Pupils’ Competence Beliefs in Visual Arts in Lower Secondary Education: A Longitudinal Perspective

The present study examined the changes to pupils’ competence beliefs in the subject Visual Arts over three years of lower secondary education in a sample of 752 elementary school pupils in Zagreb, the capital of Croatia. Using a single item ‘How good are you in Visual arts? ’, pupils’ competence beliefs were measured three times, at the end of school year in the 5 th , 6 th and 7 th grades. Unconditional latent growth curve modelling (LGCM) revealed high initial values of competence beliefs and a significant but moderate decline over time. Inter-individual variability was observed for both intercept and slope. Growth trajectories of pupils’ competence beliefs for girls and boys suggest common developmental trends for both groups, but indicate somewhat lower initial values and greater variability of intercept for boys. Conditional LGCM revealed significant effects of pupils’ final subject grades in the 5 th grade on both intercept and slope, indicating that pupils who had higher final grades in Visual Arts also had higher initial competence beliefs and that these beliefs changed less over time. The effect of the subjective value of Visual Arts (utility value, intrinsic value, difficulty) on competence beliefs was found only for intercept. These predictors did not have effects on the rate of decline in competence beliefs over time
The Relation between Degrees of Belief and Binary Beliefs

Agents are often assumed to have degrees of belief (“credences”) and also binary beliefs (“beliefs simpliciter”). How are these related to each other? A much-discussed answer asserts that it is rational to believe a proposition if and only if one has a high enough degree of belief in it. But this answer runs into the “lottery paradox”: the set of believed propositions may violate the key rationality conditions of consistency and deductive closure. In earlier work, we showed that this problem generalizes: there exists no local function from degrees of belief to binary beliefs that satisfies some minimal conditions of rationality and non-triviality. “Locality” means that the binary belief in each proposition depends only on the degree of belief in that proposition, not on the degrees of belief in others. One might think that the impossibility can be avoided by dropping the assumption that binary beliefs are a function of degrees of belief. We prove that, even if we drop the “functionality” restriction, there still exists no local relation between degrees of belief and binary beliefs that satisfies some minimal conditions. Thus functionality is not the source of the impossibility; its source is the condition of locality. If there is any non-trivial relation between degrees of belief and binary beliefs at all, it must be a “holistic” one. We explore several concrete forms this “holistic” relation could take.
Country-Wise Open Energy Planning in High-Resolution with PyPSA-Earth

The energy transition is a major challenge that knows no borders and requires a systematic change in the energy production, consumption and transport. These challenges can be effectively tackled only through collaborative efforts. Accordingly, to simplify cooperation and increase transparency for policy and technical decision makers, researchers around the world are developing open modeling tools. However, due to the high complexity, the modeling tools are often tailored to specific problems using regional-specific data and focusing on few countries. Consequently, contributions are often scattered and highly inflexible, leading to duplication of work, missed collaborations, and inefficiencies. The recent PyPSA - Earth model is a promising tool that enables energy system modeling with flexible spatial and temporal resolution. Until now, it has only been validated for Nigeria and Africa, hence lacking proof of Earth coverage. In this study, we extend the PyPSA-Earth methodology to enable energy modeling for nearly every country on Earth. Novel data cleaning, merging and modeling tasks have been performed to reach global coverage. Results confirm that PyPSA-Earth now covers approximately 99% of the world's population and can generate high-resolution datasets for national energy studies. This work lays the foundations for future endeavors in flexible energy modeling of arbitrarily large regions.
Design and Analysis: A Researcher's Handbook

I. INTRODUCTION. 1. Experimental Design. II. SINGLE FACTOR EXPERIMENTS. 2. Sources of Variability and Sums of Squares. 3. Variance Estimates and F Ratio. 4. Analytical Comparisons Among Means. 5. Analysis of Trend. 6. Simultaneous Comparisons. 7. The Linear Model and Its Assumptions. 8. Effect Size and Power. 9. Using Statistical Software. III. FACTORIAL EXPERIMENTS WITH TWO FACTORS. 10. Introduction to the Factorial Design. 11. The Principal Two-Factor Effects. 12. Main Effects and Simple Effects. 13. The Analysis of Interaction Components. IV. NONORTHOGONALITY AND THE GENERAL LINEAR MODEL. 14. General Linear Model. 15. The Analysis of Covariance. V. WITHIN-SUBJECT DESIGNS. 16. The Single-Factor Within-Subject Design. 17. Further Within-Subject Topics. 18. The Two-Factor Within-Subject Design. 19. The Mixed Design: Overall Analysis. 20. The Mixed Design: Analytical Analyses. VI. HIGHER FACTORIAL DESIGNS AND OTHER EXTENSIONS. 21. The Overall Three-Factor Design. 22. The Three-Way Analytical Analysis. 23. Within-Subject and Mixed Designs. 24. Random Factors and Generalization. 25. Nested Factors. 26. Higher-Order Designs. Appendix A: Statistical Tables.
Collaborative Modeling and Visualizing of Business Ecosystems (Kollaboratives Modellieren und Visualisieren von Geschäftsökosystemen)

Companies today develop, produce, and distribute their products and services in complex and increasingly digital business ecosystems. The growing influence of these business ecosystems on a company’s success and failure is increasingly perceived by companies. A business ecosystem goes beyond the traditional value chain of suppliers, customers, and competitors. In addition to business partners at different levels of collaboration, it also includes potentially interesting companies and start-ups for future business relationships or public institutions that can influence the ecosystem through new regulations, laws or decrees. To gain a comprehensive picture of the company and its interaction with its environment, and to make informed ecosystem-related decisions, it is necessary for the company and responsible stakeholders to understand the elements of the business ecosystem and their relationships. Visualizations of business ecosystems are a way to support these decision makers. The different decision makers in a company have different requirements for modeling the continuously changing business ecosystem, including competitors, business partners, and market developments. To obtain a comprehensive picture of the business ecosystem, it is therefore important to involve the various departments and decision makers of a company in the modeling of the ecosystem and to identify the corresponding needs and requirements. This thesis addresses these challenges and begins with a structured literature review to identify definitions and types of business ecosystems and existing visualization tools. We then describe the relevance of ecosystem modeling. Our findings are based on three discussion rounds, eleven interviews, and an online survey, which we use to derive the requirements for a software-based business ecosystem modeling and visualization approach in practice. In the next step, we developed a process to collaborative model and visualize business ecosystems. We describe the process activities, necessary roles, and artifacts created in the process. To support this approach, we have developed an innovative tool that provides stakeholders with various interactive and tailored visualizations. The contribution of this work is a framework that supports collaborative modeling and visualization of business ecosystems. The developed prototype provides several interactive visualizations and interacts with a meta-model based information system that allows the continuous adaptation of data and view models. In this thesis, we describe two use cases: the firm-internal modeling of the business ecosystem and the publicly accessible tool use for modeling and visualizing an ecosystem, here using the example of mobility.
The role of the cytosolic HSP70 chaperone system in diseases caused by misfolding and aberrant trafficking of ion channels

Protein-folding diseases are an ongoing medical challenge. Many diseases within this group are genetically determined, and have no known cure. Among the examples in which the underlying cellular and molecular mechanisms are well understood are diseases driven by misfolding of transmembrane proteins that normally function as cell-surface ion channels. Wild-type forms are synthesized and integrated into the endoplasmic reticulum (ER) membrane system and, upon correct folding, are trafficked by the secretory pathway to the cell surface. Misfolded mutant forms traffic poorly, if at all, and are instead degraded by the ER-associated proteasomal degradation (ERAD) system. Molecular chaperones can assist the folding of the cytosolic domains of these transmembrane proteins; however, these chaperones are also involved in selecting misfolded forms for ERAD. Given this dual role of chaperones, diseases caused by the misfolding and aberrant trafficking of ion channels (referred to here as ion-channel-misfolding diseases) can be regarded as a consequence of insufficiency of the pro-folding chaperone activity and/or overefficiency of the chaperone ERAD role. An attractive idea is that manipulation of the chaperones might allow increased folding and trafficking of the mutant proteins, and thereby partial restoration of function. This Review outlines the roles of the cytosolic HSP70 chaperone system in the best-studied paradigms of ion-channel-misfolding disease – the CFTR chloride channel in cystic fibrosis and the hERG potassium channel in cardiac long QT syndrome type 2. In addition, other ion channels implicated in ion-channel-misfolding diseases are discussed.
Approximation Algorithms for the Highway Problem under the Coupon Model

When a store sells items to customers, the store wishes to decide the prices of items to maximize its profit. Intuitively, if the store sells the items with low (resp. high) prices, the customers buy more (resp. less) items, which provides less profit to the store. So it would be hard for the store to decide the prices of items. Assume that the store has a set V of n items and there is a set E of m customers who wish to buy the items, and also assume that each item i ∈ V has the production cost di and each customer ej ∈ E has the valuation vj on the bundle ej ⊆ V of items. When the store sells an item i ∈ V at the price ri, the profit for the item i is pi = ri - di. The goal of the store is to decide the price of each item to maximize its total profit. We refer to this maximization problem as the item pricing problem. In most of the previous works, the item pricing problem was considered under the assumption that pi ≥ 0 for each i ∈ V, however, Balcan, et al. [In Proc. of WINE, LNCS 4858, 2007] introduced the notion of “loss-leader, ” and showed that the seller can get more total profit in the case that pi < 0 is allowed than in the case that pi < 0 is not allowed. In this paper, we consider the line highway problem (in which each customer is interested in an interval on the line of the items) and the cycle highway problem (in which each customer is interested in an interval on the cycle of the items), and show approximation algorithms for the line highway problem and the cycle highway problem in which the smallest valuation is s and the largest valuation is l (this is called an [s, l]-valuation setting) or all valuations are identical (this is called a single valuation setting).
Fully dynamic update of arc‐flags

Best connections in real networks are usually found by applying Dijkstra's shortest paths algorithm. Unfortunately, networks deriving from real‐world applications are huge, yielding unsustainable times to compute shortest paths. Therefore, considerable research has been conducted in recent years to accelerate Dijkstra's algorithm on typical instances of transportation and communication networks, such as road networks. These efforts have led to the development of many so called speed‐up techniques, as for example Arc‐Flags. The main drawback of many of these techniques, including Arc‐Flags, is that they do not work well in the realistic dynamic scenarios where the networks change over time. In this article, we introduce a new data structure, named Road‐Signs, which is used to update the Arc‐Flags of a graph in fully dynamic scenarios. Road‐Signs can be used to compute Arc‐Flags, can be efficiently updated and does not require large space consumption for sparse networks. We develop a fully dynamic algorithm for updating Arc‐Flags, by updating Road‐Signs, each time that a modification occurs on an edge of the network. We show that this algorithm is better than recomputation from scratch of Arc‐Flags in terms of the affected parameters of the input, which makes this solution suitable to be efficient in practice. However, it is not better than recomputation from scratch in the worst case. We also propose an experimental study to evaluate the practical performance of the new dynamic algorithm. To this aim, we use real‐world road networks subject to sequences of weight change operations. Our experiments show a significant speed‐up in the updating phase with respect to the recomputation from scratch of Arc‐Flags.Copyright © 2014 Wiley Periodicals, Inc. NETWORKS, Vol. 63(3), 243–259 2014