bluuebunny/crossref_metadata_2025 huggingface dataset:
TaGSim
Authors: Bai Jiyang , Zhao Peixiang
Published: February 2022

Computing similarity between graphs is a fundamental and critical problem in graph-based applications, and one of the most commonly used graph similarity measures is graph edit distance (GED), defined as the minimum number of graph edit operations that transform one graph to another. Existing GED solutions suffer from severe performance issues due in particular to the NP-hardness of exact GED computation. Recently, deep learning has shown early promise for GED approximation with high accuracy and low computational cost. However, existing methods treat GED as a global, coarse-grained graph similarity value, while neglecting the type-specific transformative impacts incurred by different types of graph edit operations, including node insertion/deletion, node relabeling, edge insertion/deletion, and edge relabeling. In this paper, we propose a
type-aware
graph similarity learning and computation framework, TaGSim
(T
ype
-a
ware
G
raph
Sim
ilarity), that estimates GED in a fine-grained approach
w.r.t.
different graph edit types. Specifically, for each type of graph edit operations, TaGSim models its unique transformative impacts upon graphs, and encodes them into high-quality, type-aware graph embeddings, which are further fed into type-aware neural networks for accurate GED estimation. Extensive experiments on five real-world datasets demonstrate the effectiveness and efficiency of TaGSim, which significantly outperforms state-of-the-art GED solutions.
xFraud
Authors: Rao Susie Xi , Zhang Shuai , Han Zhichao , Zhang Zitao , Min Wei , Chen Zhiyao , Shan Yinan , Zhao Yang , Zhang Ce
Published: February 2022

At online retail platforms, it is crucial to actively detect the risks of transactions to improve customer experience and minimize financial loss. In this work, we propose xFraud, an explainable fraud transaction prediction framework which is mainly composed of a detector and an explainer. The xFraud detector can effectively and efficiently predict the legitimacy of incoming transactions. Specifically, it utilizes a heterogeneous graph neural network to learn expressive representations from the informative heterogeneously typed entities in the transaction logs. The explainer in xFraud can generate meaningful and human-understandable explanations from graphs to facilitate further processes in the business unit. In our experiments with xFraud on real transaction networks with up to 1.1 billion nodes and 3.7 billion edges, xFraud is able to outperform various baseline models in many evaluation metrics while remaining scalable in distributed settings. In addition, we show that xFraud explainer can generate reasonable explanations to significantly assist the business analysis via both quantitative and qualitative evaluations.
Provenance-based data skipping
Authors: Niu Xing , Glavic Boris , Liu Ziyu , Li Pengyuan , Gawlick Dieter , Krishnaswamy Vasudha , Liu Zhen Hua , Porobic Danica
Published: February 2022

Database systems use static analysis to determine upfront which data is needed for answering a query and use indexes and other physical design techniques to speed-up access to that data. However, for important classes of queries, e.g., HAVING and top-k queries, it is impossible to determine up-front what data isrelevant.To overcome this limitation, we develop provenance-based data skipping (PBDS), a novel approach that generates provenance sketches to concisely encode what data is relevant for a query. Once a provenance sketch has been captured it is used to speed up subsequent queries. PBDS can exploit physical design artifacts such as indexes and zone maps.
An experimental evaluation and investigation of waves of misery in r-trees
Authors: Xing Lu , Lee Eric , An Tong , Chu Bo-Cheng , Mahmood Ahmed , Aly Ahmed M. , Wang Jianguo , Aref Walid G.
Published: February 2022

Waves of misery
is a phenomenon where spikes of many node splits occur over short periods of time in tree indexes. Waves of misery negatively affect the performance of tree indexes in insertion-heavy workloads. Waves of misery have been first observed in the context of the B-tree, where these waves cause unpredictable index performance. In particular, the performance of search and index-update operations deteriorate when a wave of misery takes place, but is more predictable between the waves. This paper investigates the presence or lack of waves of misery in several R-tree variants, and studies the extent of which these waves impact the performance of each variant. Interestingly, although having poorer query performance, the Linear and Quadratic R-trees are found to be more resilient to waves of misery than both the Hilbert and R*-trees. This paper presents several techniques to reduce the impact in performance of the waves of misery for the Hilbert and R*-trees. One way to eliminate waves of misery is to force node splits to take place at regular times before nodes become full to achieve deterministic performance. The other way is that upon splitting a node, do not split it evenly but rather at different node utilization factors. This allows leaf nodes not to fill at the same pace. We study the impact of two new techniques to mitigate waves of misery after the tree index has been constructed, namely Regular Elective Splits (RES, for short) and Unequal Random Splits (URS, for short). Our experimental investigation highlights the trade-offs in performance of the introduced techniques and the pros and cons of each technique.
Points-of-interest relationship inference with spatial-enriched graph neural networks
Authors: Chen Yile , Li Xiucheng , Cong Gao , Long Cheng , Bao Zhifeng , Liu Shang , Gu Wanli , Zhang Fuzheng
Published: February 2022

As a fundamental component in location-based services, inferring the relationship between points-of-interests (POIs) is very critical for service providers to offer good user experience to business owners and customers. Most of the existing methods for relationship inference are not targeted at POI, thus failing to capture unique spatial characteristics that have huge effects on POI relationships. In this work we propose PRIM to tackle POI relationship inference for multiple relation types. PRIM features four novel components, including a weighted relational graph neural network, category taxonomy integration, a self-attentive spatial context extractor, and a distance-specific scoring function. Extensive experiments on two real-world datasets show that PRIM achieves the best results compared to state-of-the-art baselines and it is robust against data sparsity and is applicable to unseen cases in practice.
SAFE
Authors: Chan Tsz Nam , Ip Pak Lon , U Leong Hou , Choi Byron , Xu Jianliang
Published: February 2022

Kernel density visualization (KDV) has been the de facto method in many spatial analysis tasks, including ecological modeling, crime hotspot detection, traffic accident hotspot detection, and disease outbreak detection. In these tasks, domain experts usually generate multiple KDVs with different bandwidth values. However, generating a single KDV, let alone multiple KDVs, is time-consuming. In this paper, we develop a share-and-aggregate framework, namely SAFE, to reduce the time complexity of generating multiple KDVs given a set of bandwidth values. On the other hand, domain experts can specify bandwidth values on the fly. To tackle this issue, we further extend SAFE and develop the exact method SAFE
all
and the 2-approximation method SAFE
exp
which reduce the time complexity under this setting. Experimental results on four large-scale datasets (up to 4.33M data points) show that these three methods achieve at least one-order-of-magnitude speedup for generating multiple KDVs in most of the cases without degrading the visualization quality.
Unsupervised time series outlier detection with diversity-driven convolutional ensembles
Authors: Campos David , Kieu Tung , Guo Chenjuan , Huang Feiteng , Zheng Kai , Yang Bin , Jensen Christian S.
Published: February 2022

With the sweeping digitalization of societal, medical, industrial, and scientific processes, sensing technologies are being deployed that produce increasing volumes of time series data, thus fueling a plethora of new or improved applications. In this setting, outlier detection is frequently important, and while solutions based on neural networks exist, they leave room for improvement in terms of both accuracy and efficiency. With the objective of achieving such improvements, we propose a diversity-driven, convolutional ensemble. To improve accuracy, the ensemble employs multiple basic outlier detection models built on convolutional sequence-to-sequence autoencoders that can capture temporal dependencies in time series. Further, a novel diversity-driven training method maintains diversity among the basic models, with the aim of improving the ensemble's accuracy. To improve efficiency, the approach enables a high degree of parallelism during training. In addition, it is able to transfer some model parameters from one basic model to another, which reduces training time. We report on extensive experiments using real-world multivariate time series that offer insight into the design choices underlying the new approach and offer evidence that it is capable of improved accuracy and efficiency.
Efficient and effective data imputation with influence functions
Authors: Miao Xiaoye , Wu Yangyang , Chen Lu , Gao Yunjun , Wang Jun , Yin Jianwei
Published: February 2022

Data imputation has been extensively explored to solve the missing data problem. The dramatically rising volume of missing data makes the training of imputation models computationally infeasible in real-life scenarios. In this paper, we propose an efficient and effective data imputation system withinfluence functions, named EDIT, which quickly trains a parametric imputation model with representative samples under imputation accuracy guarantees. EDIT mainly consists of two modules, i.e., animputation influence evaluation(IIE) module and arepresentative sample selection(RSS) module. IIE leverages the influence functions to estimate the effect of (in)complete samples on the prediction result of parametric imputation models. RSS builds a minimum set of the high-effect samples to satisfy a user-specified imputation accuracy. Moreover, we introduce a weighted loss function that drives the parametric imputation model to pay more attention on the high-effect samples. Extensive experiments upon ten state-of-the-art imputation methods demonstrate that, EDIT adopts only about 5% samples to speed up the model training by 4x in average with more than 11% accuracy gain.
What is the price for joining securely?
Authors: Maliszewski Kajetan , Quiané-Ruiz Jorge-Arnulfo , Traub Jonas , Markl Volker
Published: February 2022

Protection of personal data has been raised to be among the top requirements of modern systems. At the same time, it is now frequent that the owner of the data and the owner of the computing infrastructure are two entities with limited trust between them (e. g., volunteer computing or the hybrid-cloud). Recently, trusted execution environments (TEEs) became a viable solution to ensure the security of systems in such environments. However, the performance of relational operators in TEEs remains an open problem. We conduct a comprehensive experimental study to identify the main bottlenecks and challenges when executing relational equi-joins in TEEs. For this, we introduce TEEbench, a framework for unified benchmarking of relational operators in TEEs, and use it for conducting our experimental evaluation. In a nutshell, we perform the following experimental analysis for eight core join algorithms: off-the-shelf performance; the performance implications of data sealing and obliviousness; sensitivity and scalability. The results show that all eight join algorithms significantly suffer from different performance bottlenecks in TEEs. They can be up to three orders of magnitude slower in TEEs than on plain CPUs. Our study also indicates that existing join algorithms need a complete, hardware-aware redesign to be efficient in TEEs, and that, in secure query plans, managing TEE features is equally important to join selection.
Efficient temporal pattern mining in big time series using mutual information
Authors: Ho Van Long , Ho Nguyen , Pedersen Torben Bach
Published: February 2022

Very large time series are increasingly available from an ever wider range of IoT-enabled sensors deployed in different environments. Significant insights can be gained by mining temporal patterns from these time series. Unlike traditional pattern mining, temporal pattern mining (TPM) adds event time intervals into extracted patterns, making them more expressive at the expense of increased time and space complexities. Existing TPM methods either cannot scale to large datasets, or work only on pre-processed temporal events rather than on time series. This paper presents our Frequent Temporal Pattern Mining from Time Series (FTPMfTS) approach providing: (1) The end-to-end FTPMfTS process taking time series as input and producing frequent temporal patterns as output. (2) The efficient Hierarchical Temporal Pattern Graph Mining (HTPGM) algorithm that uses efficient data structures for fast support and confidence computation, and employs effective pruning techniques for significantly faster mining. (3) An approximate version of HTPGM that uses mutual information, a measure of data correlation, to prune unpromising time series from the search space. (4) An extensive experimental evaluation showing that HTPGM outperforms the baselines in runtime and memory consumption, and can scale to big datasets. The approximate HTPGM is up to two orders of magnitude faster and less memory consuming than the baselines, while retaining high accuracy.
Incremental partitioning for efficient spatial data analytics
Authors: Vu Tin , Eldawy Ahmed , Hristidis Vagelis , Tsotras Vassilis
Published: February 2022

Big spatial data has become ubiquitous, from mobile applications to satellite data. In most of these applications, data is continuously growing to huge volumes. Existing systems for big spatial data organize records at either the record-level or block-level. Systems that use record-level structures include key-value stores and LSM-Tree stores, which support insert and delete operations and they are optimized for highly-selective queries. On the other hand, systems like GeoSpark that use block-level structures (e.g. 128 MB each) are more efficient for analytical queries, but they cannot incrementally maintain the partitioned data and do not support delete operations. This paper proposes a general framework that enables block-level systems to incrementally maintain spatial partitions, in the presence of bulk insertions and deletions, in distributed file system (DFS) blocks. We first formally study the incremental spatial partitioning problem for big data and demonstrate its NP-hardness. Then, we propose a cost model to estimate the performance of queries on the partitioned data and the effect of modifying it as the data grows. After that, we provide three different implementations of the incremental partitioning framework. Comprehensive experiments on large real datasets show that our proposed partitioning algorithms outperforms state-of-the-art spatial partitioning methods.
Lux
Authors: Lee Doris Jung-Lin , Tang Dixin , Agarwal Kunal , Boonmark Thyne , Chen Caitlyn , Kang Jake , Mukhopadhyay Ujjaini , Song Jerry , Yong Micah , Hearst Marti A. , Parameswaran Aditya G.
Published: February 2022

Exploratory data science largely happens in computational notebooks with dataframe APIs, such as pandas, that support flexible means to transform, clean, and analyze data. Yet, visually exploring data in dataframes remains tedious, requiring substantial programming effort for visualization and mental effort to determine what analysis to perform next. We propose Lux, an
always-on
framework for accelerating visual insight discovery in dataframe workflows. When users print a dataframe in their notebooks, Lux recommends visualizations to provide a quick overview of the patterns and trends and suggests promising analysis directions. Lux features a high-level language for generating visualizations on demand to encourage rapid visual experimentation with data. We demonstrate that through the use of a careful design and three system optimizations, Lux adds no more than two seconds of overhead on top of pandas for over 98% of datasets in the UCI repository. We evaluate Lux in terms of usability via interviews with early adopters, finding that Lux helps fulfill the needs of data scientists for visualization support within their dataframe workflows. Lux has already been embraced by data science practitioners, with over 3.1k stars on Github.
Posthumanist Cultural Studies: Taking the Nonhuman Seriously
Authors: Cord Florian
Published: February 2022

In recent years, there has been a pronounced (re-)turn to questions of ontology, matter, and realism in the humanities and social sciences. What all these theoretical formations have in common is their profound challenge to human exceptionalism. Taken together, these approaches have productively been described as constituting a “nonhuman turn.” This article is a theoretical exploration of the relationship between the intellectual and political practice of Cultural Studies on the one hand and the nonhuman turn on the other. For this purpose, it brings both “into encounter” (Donna Haraway), investigating points of affinity, tension, and compatibility. The essay argues that such a theoretical encounter could prove to be tremendously fruitful, both intellectually and politically, and that Cultural Studies should thus take a genuine interest in these new approaches, engage with them, put them to the test, and, when needed, “translate” and “re-articulate” them. The result could be a Cultural Studies for the Anthropocene which would have a lot to contribute to the critical (cultural/political/social/economic) struggles being fought today.
Network Dynamic for Experimental Learning Cycle and Innovation Process: A Conceptual Model
Authors: Zhu Siwei
Published: February 2022

This study develops a conceptual model of network dynamics on innovation by integrating observations and insights from a world-leading innovation company with concepts and theories from the relevant literature. This study first defines the two stages of the innovation process – early-stage and late-stage and unpacks two types of network activities – knowledge networks and social networks. This work then suggests that the experimental learning cycle with failures spontaneously stimulates network activities to become cognitively activated in the innovation process and incorporates six testable propositions. This study illuminates the idea of Learning by Networking and demonstrates that inventors constitute the reality about what knowledge involves and which people act and intentionally create network dynamics for each task, thus merging these streams as a sequential phenomenon.
Reflection on Wolf Schmid's Narratological Model and Historical Narrative
Authors: Šuch Juraj , Jančovič Ivan
Published: February 2022

This contribution responds to the ongoing discussion about the narrativity of history and looks at some differences between fictive and historical narrative. The objective of this contribution is to further elaborate on the ideas of narrative transformations developed by Wolf Schmid, focusing particularly on historical narratives. The authors see differences between both kinds of narrative, especially on the level of reference (which is in line with the views of D. Cohn, P. Ricouer and L. Doležel). The problem of fiction and reference is illustrated by Schmid's four tiered narratological model, especially on the level of happening. In fiction, this tier (of happening) is inferred backwards based on the presentation of the narration. This tier is positioned (excluded in absentia) so the elements of the narrative can be selected. In historical narrative happening has a different status and precedes both the story and the text. Although the shape of the past is related to the presentation of the narrative, it is not determined by nor reduced to it. The authors of this contribution describe the specific character and aspects of narrative transformation in the writing process.
Ideological Struggle in Social Processes Through the Lens of Héctor P. Agosti's Political Thinking
Authors: Dinušová Dominika
Published: February 2022

The study focuses on the theoretical underpinnings of the ideological struggle in social processes as seen through the lens of the Argentinian philosopher Héctor P. Agosti's political philosophy. It discusses the impact of Agosti's interpretation of ideology in social struggle the usefulness of his conclusions for later practical developments in Latin America. The aim of the study is to describe the key aspects of Agosti's view of culture and ideology and to identify specific features of his approach with a view to determining how and to what extent Agosti's political thought contributed to subsequent theories and practice. The following aspects are analysed: understanding culture as a contradictory process in dynamic social development, the role of the intellectual in the social struggle for ideological hegemony and specific features of Agosti's approach to developments in revolutionary thought in revolutionary thought in the Latin America.
An Exploration of Women’s Social Position in Primary and Middle School Textbooks in Pakistan
Authors: Alam Jan , Badshah Ikram
Published: February 2022

Textbooks play a strong part in constructing gender roles and status in society. Thus, the images, lessons, and stories of gender portrayed in textbooks affect the perception of prevalent masculine behavior. To develop an insight into the phenomena, this article analyzes the institutionalized patriarchy and patriarchal values embedded in the Urdu and English National Book Foundation textbooks for grades 5, 6, and 7. The study used content analysis techniques to decode the tone, juggling of meanings, pictorial representation, topic selection, word selection, number of pages devoted to each topic, and gender placement of Urdu and Social Studies textbooks. The study explored whether women are portrayed as followers of men and men as having a leadership role. The mother is predominantly presented as a housewife who stays at home, cleaning and cooking all day. While the father goes to work every day and comes home and relaxes after a hard day’s work. Such placement of gendered roles has an effect on the thinking of young students and they internalize the idea that such roles are a natural part of their personality. Moreover, the books reflect a reality which is more male-oriented, while female representations are lacking in the dominant reality.
Examining the Father-Child Relationship: A Theoretical Framework for Creating a Methodology
Authors: Fucsková Zuzana , Babinčák Peter , Kačmárová Monika
Published: February 2022

In Slovakia and the Czech Republic, little attention is paid to the father-child relationship. The aim of this theoretical study is to introduce methods for assessing the father-child relationship in early childhood. There are two methodologies for assessing sensitive and challenging play by fathers – the Sensitive and Challenging Interaction Play Scale – SCIP (Grossmann et al., 2002) and the quality of the father-child activation relationship – Risky Situation – RS (Paquette & Bigras, 2010). The study describes the SCIP and offers a theoretical definition of the basic constructs tackled in the SCIP methodology. The paper then describes the new RS procedure. Special attention is paid to activation theory, which forms the basis of the RS procedure. Finally, the paper contains suggestions for future in-depth investigations of the father’s role using adequate tools that take into consideration the uniqueness of the father-child relationship. The need to validate existing methods – also within Slovak culture – is emphasized.
Emotionally Engaged Parent Versus Professional Teacher: Strategies for Maintaining Borders Between the Dual Teacher-Parent Role in School
Authors: Hargašová Lucia
Published: February 2022

The paper presents findings on primary teachers’ and other school actors’ constructions of the teacher and parental role. Specifically, it focuses on strategies for maintaining borders between the personal (parent) and professional (teacher) roles in school environments in Slovakia. We approached the concepts of role and identity from the perspective of social constructivism and symbolic interactionism. Thirty-one interviews and focus groups with school actors were analysed using critical discourse analysis. In the next step, discourses on managing the dual role were analysed using thematic analysis. Results show participants described regulating or restricting verbal, emotional and behavioural expression, and engaged in favouritism avoidance as strategies for separating out the roles. All point to the need to eliminate favouritism as a key meaning in the construction of the teacher role through impartialness and parental role as favourably inclined to create inter-role conflict. We stress the importance of exploring teacher and parental roles in various circumstances in order to obtain a complex picture of negotiating these roles in everyday life.
Grain boundary diffusion and segregation of Ge in Cu: Radiotracer measurements in different kinetic regimes
Authors: Lohmann M. , Divinski S. , Herzig Chr.
Published: February 2022

Grain boundary (GB) solute diffusion of Ge in Cu polycrystals was systematically investigated by the radiotracer serial sectioning technique using 68Ge and 71Ge isotopes. The diffusion measurements were carried out under conditions of Harrison’s B- (923–626 K) and C- (576–451 K) type diffusion regimes. In the B-type diffusion regime, the triple product P = s
δ
D
gb (s is the segregation factor and δ the GB width) was found to follow the Arrhenius law P = 4:0 × 10-16 × exp(-58.6 kJ mol-1/RTÞ m3s-1, where R is the universal gas constant and T the temperature. Measurements in the C-regime directly yielded the GB diffusion coefficient D
gb, D
gb = 2.8 × 10-6 × exp(-84.8 kJ mol-1/RTÞ m2s-1. Combining the obtained P and D
gb values and assuming δ ≌ 5 × 10-10 m, the GB segregation factor for Ge in Cu was determined to follow an Arrhenius dependence s = 0.29 exp(26 kJmol-1/RTÞ. The determined segregation coefficients s are discussed together with previous results on solute segregation in Cu and Ag, and it is concluded that the well-known Hondros relation, which relates segregation and bulk solute solubility, can generally be used only for a qualitative estimation of the segregation ability. Furthermore, the obtained results for the triple product s
δ
D
gb and the directly measured D
gb values are discussed in relation to previous GB diffusion measurements of some other solutes in Cu and Ag in the B- and C-regimes.
Dislocation structure and crystallite size distribution in plastically deformed Ti determined by X-ray peak profile analysis
Authors: Gubicza J. , Dragomir I. C. , Ribárik G. , Baik S. C. , Zhu Y. T. , Valiev R. Z. , Ungár T.
Published: February 2022

Ultrafine-grained titanium produced by equal channel angular pressing and subsequent cold rolling is studied by X-ray diffraction. It is found that a texture exists in which the hexagonal basal planes are parallel to the longitudinal axis of the billet. The crystallite size distribution and the dislocation structure are determined by X-ray diffraction peak profile analysis. The median and the variance of the crystallite size distribution are obtained as m = 39 nm and σ = 0.14, respectively. The dislocation model of anisotropic broadening of peak profiles enables to determine the active slip systems. It was found that all three possible hexagonal Burgers vectors of dislocations exist, with the composition of 66%  type, 33%  type and 1%  type.
Contribution of dislocation substructures developed during cold rolling to the formation of rolling textures in Al–Mg alloys
Authors: Endou Seiichi , Inagaki Hirosuke
Published: February 2022

In order to investigate the mechanism of the development of rolling textures in Al –Mg alloys, hot bands of high-purity Al, Al-3 wt. %Mg and Al-5 wt. %Mg alloys were solution-treated at 450 °C and cold-rolled by varying rolling reductions up to 97%. Rolling textures of these specimens were investigated with the orientation distribution function analysis. Comparisons of the results of the texture analysis with those of the hardness measurement and transmission electron microscopy observations revealed that, in all specimens, the texture development occurred mainly at the later half of work hardening, i. e., at rolling reductions above 80 %, where dislocation substructures were well developed. In pure Al, in which well defined, elongated cell structures were developed, {112}<111> and {123}<634> components developed remarkably, whereas in the Al-5% Mg alloys, in which only dense dislocation tangles and ill defined small cells were developed, the development of {112}<111> and {123}<634> components was strongly suppressed. All these observations thus suggested that the development of rolling textures was strongly affected by the development of dislocation substructures, which occurred concurrently during rolling, and that the formation of elongated cell structures was more favorable for the development of rolling textures. In cold rolling, elongated cell structures may be the final form of dislocation substructures, providing both mechanical stability and orientation stability.
Controlled change in the plastic working conditions of metals in the plane state of strain
Authors: Bochniak Włodzimierz
Published: February 2022

In the investigations on plastic forming of Cu, Al and Pb, under conditions of plane state of strain, priority has been given to variants with a change in the loading scheme (modified channel die test). It has been found that a direct consequence of the application of such a procedure is a temporary, considerable decrease of the flow stress and its subsequent increase to a value exceeding that attained in a standard test. The reasons for such a behavior have been analysed.
Textures and precipitates in Ti-stabilized interstitial-free steel
Authors: Shin Eunjoo , Seong Baek-Seok , Kang Hee-Jae , Huh Moo-Young
Published: February 2022

Samples of titanium-stabilized interstitial-free steel were coiled at 600 and 700 °C. The effect of the coiling temperature on the formation of textures and precipitates during coiling, cold rolling and recrystallization annealing was studied by means of neutron texture measurements, small angle neutron scattering analysis and transmission electron microscopy observations. Whereas coiling at the lower temperature resulted in an insufficient scavenging of carbon in solid solution, coiling at the higher temperature promoted scavenging of carbon in solid solution, and consequently the formation of a large number of precipitates. The large amount of carbon in solid solution caused the retardation of softening in the cold-rolled sample during annealing below 700 °C. Upon annealing above 700 °C the impact of the coiling temperature on grain size and precipitates was not observed. The samples coiled at different temperatures exhibited a nearly identical cold rolling texture. However, the cold-rolled sample having a large amount of carbon in solid solution displayed a weak recrystallization texture.
Kinetics of the discontinuous precipitation of a liquid phase in Cu–In alloys
Authors: Gautam S. K. , Gupta S. P.
Published: February 2022

The morphology and growth kinetics of the discontinuous precipitation of liquid and depleted solid phases from a supersaturated solid solution has been studied. The transformation was carried out in the two-phase (liquid + solid α) field in the temperature range 996–1050 K in two Cu– In alloys containing 8.9 and 9.5 at.% In. A lamellar structure consisting of alternate lamellae of α and liquid phases has been observed to grow from the grain boundaries of the supersaturated α solid solution. The nucleation of the liquid droplets occurred at the grain boundary and a thin layer of liquid formed between the droplets. The liquid film started migrating resulting in the development of a lamellar structure. In both alloys the growth rate increased with increasing temperature of transformation but the interlamellar spacing decreased with increasing transformation temperature. The growth kinetics was analyzed using the models of Cahn and Petermann and Hornbogen and from a mass balance using Fick’s first law. From the diffusivity and activation energy values it can be concluded that the growth of the cellular structure occurs by solute transport through the liquid film.
Influence of homogenization on the processing map for hot working of as-cast Mg–2Zn–1Mn alloy
Authors: Sivakesavam O. , Prasad Y. V. R. K.
Published: February 2022

Processing maps have been developed for hot deformation of Mg–2Zn– 1Mn alloy in as-cast condition and after homogenization with a view to evaluate the influence of homogenization. Hot compression data in the temperature range 300 – 500 °C and strain rate range 0.001 – 100 s– 1were used for generating the processing map. In the map for the as-cast alloy the domain of dynamic recrystallization occurring at 450 °C and 0.1 s–1has merged with another domain occurring at 500 °C and 0.001 s– 1representing grain boundary cracking. The latter domain is eliminated by homogenization and the dynamic recrystallization domain expanded with a higher peak efficiency occurring at 500 °C and 0.05 s–1. The flow localization occurring at strain rates higher than 5 s–1is unaffected by homogenization.
Some characteristics of electrospark deposition
Authors: Lešnjak Andrej , Tušek Janez
Published: February 2022

The paper deals with some characteristics of electrospark deposition. A relevant device and the process are described, the material transfer is shown schematically, and the average droplet mass, the thickness of deposited layer, and the layer roughness are determined. Two types of substrate (tool steel, austenitic stainless steel), two types of shielding gas, (Ar, He), and three types of filler material, (WC, TiC, Stellite 6) were used. With some deposits, chemical analyses of deposit surfaces were performed and with some others through-thickness chemical analyses. Among the final conclusions the most important one is that the addition of a shielding gas results in a considerable increase in deposit quality. The device manufacturer, however, recommends deposition without the addition of a shielding gas.
Neurofeedback and neural self-regulation: a new perspective based on allostasis
Authors: Mirifar Arash , Keil Andreas , Ehrlenspiel Felix
Published: February 2022

The field of neurofeedback training (NFT) has seen growing interest and an expansion of scope, resulting in a steadily increasing number of publications addressing different aspects of NFT. This development has been accompanied by a debate about the underlying mechanisms and expected outcomes. Recent developments in the understanding of psychophysiological regulation have cast doubt on the validity of control systems theory, the principal framework traditionally used to characterize NFT. The present article reviews the theoretical and empirical aspects of NFT and proposes a predictive framework based on the concept of allostasis. Specifically, we conceptualize NFT as an adaptation to changing contingencies. In an allostasis four-stage model, NFT involves (a) perceiving relations between demands and set-points, (b) learning to apply collected patterns (experience) to predict future output, (c) determining efficient set-points, and (d) adapting brain activity to the desired (“set”) state. This model also identifies boundaries for what changes can be expected from a neurofeedback intervention and outlines a time frame for such changes to occur.
Quand l’éventail du désaccord laisse parler au-delà des paroles: Etude historico-sémiotique de la légende du Coup de l’Eventail
Authors: Khelil Lamya
Published: February 2022

Le présent travail de recherche retrace la scène mythique du Coup de l’éventail qui opposa le Dey d’Alger Hussein Pacha et le Consul français Pierre Deval en 1827. Nous examinons dans quelle mesure l’interprétation dudit incident pourrait entraver le recours à la sémiotique dans les études historiographiques en reposant sur les théories sémiotiques de Greimas, de Fontanille et de Zilberberg. L’analyse sémiotique des iconographies représentant l’incident a révélé à quel point ce dernier ne pourrait se désubjectiviser bien que Greimas ait déjà proposé de jumeler les deux étapes l’archivage et l’analyse qui devraient être menés par un actant collectif dans le but d’atteindre une «désubjectivisation totalitaire» des faits. S’ajoutant à cela la problématique du découpage temporel qui persiste, l’historien serait incapable d’étudier les modèles de transformation dans le même temps et dans le même ordre car les transformations jouissent d’un caractère irréversible. Or, les signes historiques sont exempts de virtualité, ce qui remet en cause l’intégrité du signe historique. Greimas espérait aboutir à travers le concept de simulacre à une forme du passé narrativisée et débrayée, l’énonciation va ainsi permettre de doter les éléments hétérogènes abondants du passé d’une valeur énonciative mais cela reste difficile à réaliser. Nous reconnaissons néanmoins que le ne pas pouvoir savoir épistémique est un composant légitime de l’incident historique.
Bidirectional volatility transmission between stocks and bond in East Asia – The quantile estimates based on wavelets
Authors: Živkov Dejan , Kovačević Jelena , Stankov Biljana , Stefanović Zoran
Published: February 2022

This paper investigates the volatility spillover effect between the national stock and bond markets in the five East Asian emerging countries. We use wavelet signal decomposing technique, GARCH models with different distribution functions and quantile regression. We find that the spillover effect is much higher in more turbulent times, than in calm periods, whereby this effect is stronger from stocks to 10Y bonds, thanvice-versa, and it applies for all the countries. Using wavelet signals, we determine that, in most cases, the volatility transmission is higher in short-term horizon, than in midterm and long-term. The effect is stronger in countries with the less developed financial markets (Thailand, Indonesia and Malaysia) than in countries with more developed financial markets (China and Korea), and this is particularly evident in direction from stock to bond markets. Wavelet coherence indicates low volatility correlation in short time-horizons and relatively high correlation in midterm and long-term, which applies for all selected countries. Wavelet cross-correlation indicates that volatility spillover shocks predominantly transmit from bond markets to stock market in more developed China and Korea, whereas volatility shocks from stock market spill over towards bond market in less developed Thailand and Indonesia in very short-time horizon (2–4 days).
Antioxidant and antimicrobial potential of Ganoderma lucidum and Trametes versicolor
Authors: Mustafin Kairat , Bisko Nina , Blieva Raushan , Al-Maali Galeb , Krupodorova Tatyana , Narmuratova Zhanar , Saduyeva Zhazira , Zhakipbekova Aigerim
Published: February 2022

Objectives

The majority of research programs had been focused on extract from the fruiting body. However, fungal mycelium obtained by submerged cultivation also has higher pharmacological potential. The aim of this study was investigation of the antioxidant and antimicrobial potential of Ganoderma lucidum and Trametes versicolor fungal mycelium biomass obtained by submerged cultivation and liquid fluid.

Methods

The antioxidant activity was evaluated by comparing the oxidation kinetics of the reduced form of 2,6-dichlorophenolindophenol with atmospheric oxygen in the presence/absence of biological samples. A criterion for evaluating for assessing the antioxidant activity was the values of the inhibition constant of the oxidation reaction. Antimicrobial activity of the fungal extracts was performed by agar disc diffusion method.

Results

A comparative analysis of antioxidant potential of G. lucidum and T. versicolor mycelium biomass and liquid fluid was conducted for the first time. It was found that antioxidant activity of fungal biomass depends on the cultivation time. The most active were the fractions obtained on the 21st day of fungal cultivation. Fungal extracts were more effective against Gram-positive bacteria compared to Gram-negative bacteria, micromycete and yeasts.

Conclusions

The results showed that submerged cultivation of mushrooms has significant industrial potential.
Dimorphism of MnHAsO4(H2O): natural monoclinic krautite and its synthetic triclinic modification
Authors: Weil Matthias , Kolitsch Uwe , Stürzer Tobias
Published: February 2022

The crystal structure of natural krautite, MnHAsO4(H2O), was re-evaluated from a cotype specimen, confirming the previously reported monoclinic symmetry for this mineral (space group P21, Z = 8, a = 8.0093(5), b = 15.9372(10), c = 6.8065(4) Å, β = 96.534(2)° at room temperature, 5662 structure factors, 302 parameters, R1 = 0.0295, wR2 = 0.0770). Although hydrogen atoms could not be located from the single crystal X-ray diffraction study, the higher accuracy and precision of the results allowed to derive the hydrogen-bonding scheme (O⋯O = 2.55–2.90 Å) in the crystal structure of krautite. Crystals of synthetic MnHAsO4(H2O) were grown by mixing aqueous solutions of NH4H2AsO4 and MnSO4 and keeping the formed gel at 105 °C for several days. The obtained triclinic crystals were systematically and polysynthetically twinned by contact on (010). Separation of reflections from two individual domains made it possible to determine and refine the crystal structure (space group

P

1
‾

$P\overline{1}$

, Z = 8, a = 8.0105(16), b = 15.991(4), c = 6.8029(12) Å, α = 92.635(8), β = 96.534(2), γ = 90.151(8)° at room temperature, 7226 structure factors, 255 parameters, R1 = 0.0445, wR2 = 0.1381). The triclinic polymorph of MnHAsO4(H2O) does not show a direct group-subgroup relation with monoclinic krautite. Triclinic MnHAsO4(H2O) is closely related with other triclinic M
IIHAsO4(H2O) (M = Co, Cu, Zn, Mg) mineral phases. Quantitative structural comparisons between the five M
IIHAsO4(H2O) compounds revealed a high similarity between the Mn and Co members, and between the Zn and Mg members, respectively. Subtle distinctions between the two pairs are ascribed to a different hydrogen-bonding scheme. Although the Cu member has a similar hydrogen-bonding scheme as the Mn and Co pair, its structural similarity with triclinic MnHAsO4(H2O) is low due to the strain of the crystal structure caused by the Jahn-Teller distortions of the [CuO6] octahedra.
Design of Buried Equipment for the Collection of Urban Solid Waste
Authors: da Costa J. D. C. , Campilho R. D. S. G. , Silva F. J. G. , Sánchez-Arce I. J.
Published: February 2022

Waste recovery systems are implemented around the world. These systems play a highly important role in the integrated waste management process. The constant technological evolution of this type of equipment aims to answer to global and European standards that increasingly require a reduction in the deposition of waste in landfills and a progressive growth of the recycling levels per capita. To allow the insertion of waste equipment in places where there are several limitations, such as the available space and the urban environment, buried equipment for the storage of waste appeared. This equipment has a large storage capacity, and because they are completely buried underground, only permanent deposition top bins are visible. This work was developed with the aim of improving buried underground waste disposal equipment, including the devices to comply with safety regulations and automated opening/closing mechanisms. The complete equipment can be divided into three parts: the liner, the buried structure, and the interface with the depositor of waste (through the deposition top bin). Because many of the available solutions are empirically based designs, there is a high margin to improve competitiveness, which reaches greater proportions in a scenario of economies of scale. The main equipment concept is presented, and structural analysis is accomplished by the finite element method, allowing for improved equipment to be proposed that replaces the current solution. Prototype fabrication/testing and cost analysis are also performed. A proposal to revise the current modular structure is finally presented, which allows for a cost and weight reduction of 6 % and 15 %, respectively.
Learning Evaluation of Writing Descriptive Text with Think Pair Share Model in Seventh Grade Students with Introvert Personality
Authors: Masykuroh Zummala Rizqi , Zulaeha Ida
Published: February 2022

Learning to write descriptive texts which is in accordance to the 2013 curriculum and the development of the 21st century has demanded students to be more productive, creative, innovative, and affective through integrated knowledge of attitudes, skills, and knowledge. Learning to write descriptive texts cannot be separated from the personality of students, namely introvert personality. Evaluation of learning by using a learning model that is appropriate to the introvert personality type is important. The purpose of this study was to evaluate the effectiveness of writing descriptive text learning with the think pair share model in VII grade students with introvert personality. This research used one-group pretest-posttest design. The results of the research based on the paired t-test with a significance value of 0.000 showed that there was a significant difference between the results of the initial test and the final test of writing descriptive text. Significant differences were experienced by introvert students, as there was an increase in the average score of the initial test from 68.07 and the average score of the final test of 80.38.
Technological conditions synchronous operation of united power system of Ukraine and neighboring ENTSO-E-member power systems
Authors:   Institute of General Energy of the National Academy of Sciences of Ukraine, 172 Antonovycha str., Kyiv, 03150, Ukraine, Denisov V.A., , Chuprina L.V. ,   Institute of General Energy of the National Academy of Sciences of Ukraine, 172 Antonovycha str., Kyiv, 03150, Ukraine
Published: February 2022

A large-scale reform of relations in the electricity sector, which has been taking place in recent years in Ukraine, is explained by the desire of integration into European Union, and these prescripts, in particular, by the Law of Ukraine “On ratification of the Association Agreement between Ukraine and the European Union”. One of the important steps towards Ukraine's integration into the EU is the accession of the United Power System (UPS) to the Association of Transmission System Operators of Continental Europe (ENTSO-E) for which, in particular, in July 2019, a new electricity market model was introduced in Ukraine, built on principles compatible with the EU, currently functioning in accordance with the provisions of the Law of Ukraine "On the Electricity Market of Ukraine" and by-laws, in particular, "Market Rules", "Market rules" for the day ahead and intraday market ". The conditions of parallel operation of the UPS of Ukraine with the energy systems of neighboring countries that are part of ENTSO-E are considered, in particular, the structure of generating capacities, characteristic graphs of electrical loads, the presence and capacity of interstate power transmission lines and the value of the maximum allowable import and export capacity. The data presented can be used as input information for modeling the operating modes of the generating capacities of individual power systems, ensuring the readiness to integrate the power system of Ukraine with the power system of Continental Europe ENTSO-E and serve as the basis for modeling the synchronous functioning of the UPS of Ukraine in parallel operation with the power systems of neighboring countries. Keywords: energy system, ENTSO-E, technological conditions