bluuebunny/crossref_metadata_2025 huggingface dataset:
ASI EKSKLUSIF DAN ASUPAN ENERGI BERHUBUNGAN DENGAN KEJADIAN STUNTING PADA USIA 6 – 24 BULAN DI JAWA TENGAH
Authors: Nugraheni Dini , Nuryanto Nuryanto , Wijayanti Hartanti Sandi , Panunggal Binar , Syauqy Ahmad
Published: June 2020

Latar Belakang: Stunting merupakan gambaran dari status gizi yang kurang yang bersifat kronik. Banyak faktor yang mempengaruhi stunting. Penelitian ini bertujuan untuk mengetahui hubungan antara riwayat inisiasi menyusu dini (IMD), riwayat ASI eksklusif, riwayat asupan energi, dan riwayat asupan protein dengan kejadian stunting pada usia 6 – 24 bulan di provinsi Jawa Tengah. Metode : Penelitian ini menggunakan rancangan studi analitik observasional dengan pendekatan Cross-sectional. Penelitian ini merupakan analisis data sekunder yang berasal dari survey Pemantauan Status Gizi (PSG) provinsi Jawa Tengah tahun 2017. Sejumlah 3.776 sampel yang memenuhi kriteria inklusi yaitu berusia 6-24 bulan yang terdaftar pada data PSG provinsi Jawa Tengah tahun 2017. Data PSG meliputi data berat badan, panjang lahir, status gizi, riwayat ASI eksklusif, riwayat IMD, dan riwayat asupan zat gizi pada usia 6-24 bulan. Analisis statistik dengan univariat berupa distribusi frekuensi. Analisis bivariat menggunakan uji chi-square untuk mengetahui hubungan antar variabel. Uji regresi logistik untuk mengetahui besar risiko pada variabel bebas dengan kejadian stunting.Hasil: Prevalensi stunting usia 6-24 bulan di Jawa Tengah sejumlah 18,5%. Faktor kejadian stunting di provinsi Jawa Tengah adalah Asupan Energi (p=0,001 OR 1,495 95%CI : 1,178 – 1,897), dan riwayat ASI Eksklusif (p=0,006 OR 1,282 95%CI : 1,076 – 1,527). Simpulan: Riwayat ASI eksklusif dan riwayat asupan energi merupakan fakor kejadian stunting pada usia 6 -24 bulan di provinsi Jawa Tengah.
On querying historical evolving graph sequences
Authors: Ren Chenghui , Lo Eric , Kao Ben , Zhu Xinjie , Cheng Reynold
Published: June 2020

In many applications, information is best represented as graphs. In a dynamic world, information changes and so the graphs representing the information evolve with time. We propose that historical graph-structured data be maintained for analytical processing. We call a historical evolving graph sequence an EGS. We observe that in many applications, graphs of an EGS are large and numerous, and they often exhibit much redundancy among them. We study the problem of efficient query processing on an EGS and put forward a solution framework called FVF. Through extensive experiments on both real and synthetic datasets, we show that our FVF framework is highly efficient in EGS query processing.
RemusDB
Authors: Minhas Umar Farooq , Rajagopalan Shriram , Cully Brendan , Aboulnaga Ashraf , Salem Kenneth , Warfield Andrew
Published: June 2020

In this paper we present a technique for building a high-availability (HA) database management system (DBMS). The proposed technique can be applied to any DBMS with little or no customization, and with reasonable performance overhead. Our approach is based on Remus, a commodity HA solution implemented in the virtualization layer, that uses asynchronous virtual machine (VM) state replication to provide transparent HA and failover capabilities. We show that while Remus and similar systems can protect a DBMS, database workloads incur a performance overhead of up to 32% as compared to an unprotected DBMS. We identify the sources of this overhead and develop optimizations that mitigate the problems. We present an experimental evaluation using two popular database systems and industry standard benchmarks showing that for certain workloads, our optimized approach provides very fast failover (≤ 3 seconds of downtime) with low performance overhead when compared to an unprotected DBMS. Our approach provides a practical means for existing, deployed database systems to be made more reliable with a minimum of risk, cost, and effort. Furthermore, this paper invites new discussion about whether the complexity of HA is best implemented within the DBMS, or as a service by the infrastructure below it.
A subsequence matching with gaps-range-tolerances framework
Authors: Kotsifakos Alexios , Papapetrou Panagiotis , Hollmén Jaakko , Gunopulos Dimitrios
Published: June 2020

We propose a novel subsequence matching framework that allows for gaps in both the query and target sequences, variable matching tolerance levels efficiently tuned for each query and target sequence, and also constrains the maximum match length. Using this framework, a space and time efficient dynamic programming method is developed: given a short query sequence and a large database, our method identifies the subsequence of the database that best matches the query, and further bounds the number of consecutive gaps in both sequences. In addition, it allows the user to constrain the minimum number of matching elements between a query and a database sequence. We show that the proposed method is highly applicable to music retrieval. Music pieces are represented by 2-dimensional time series, where each dimension holds information about the pitch and duration of each note, respectively. At runtime, the query song is transformed to the same 2-dimensional representation. We present an extensive experimental evaluation using synthetic and hummed queries on a large music database. Our method outperforms, in terms of accuracy, several DP-based subsequence matching methods---with the same time complexity---and a probabilistic model-based method.
Accelerating queries with group-by and join by groupjoin
Authors: Moerkotte Guido , Neumann Thomas
Published: June 2020

Most aggregation queries contain both group-by and join operators, and spend a significant amount of time evaluating these two expensive operators. Merging them into one operator (the
groupjoin
) significantly speeds up query execution.

We introduce two main equivalences to allow for the merging and prove their correctness. Furthermore, we show experimentally that these equivalences can significantly speed up TPC-H.
Dissemination of models over time-varying data
Authors: Zhou Yongluan , Vagena Zografoula , Haustad Jonas
Published: June 2020

Dissemination of time-varying data is essential in many applications, such as sensor networks, patient monitoring, stock tickers, etc. Often, the raw data have to go through some form of pre-processing, such as cleaning, smoothing, etc, before being disseminated. Such pre-processing often applies mathematical or statistical models to transform the large volumes of raw, point-based data into a much smaller number of piece-wise continuous functions. In such cases, the necessity to distribute data models instead of raw data may arise. Nevertheless, model dissemination has received very little attention so far. In this paper, we attempt to fill this gap and propose a model-agnostic dissemination framework that can handle different models in a uniform manner. The dissemination infrastructure is built on top of a tree-based overlay network, reminiscent to the ones employed in publish/subscribe systems, which are known to scale well to the number of data producers and receivers. To adequately deal with the vast model variation and receivers' very different accuracy requirements on the models, we have developed optimized model routing algorithms, which are intended to minimize data traffic and avoid bottlenecks within the dissemination network. The extensive experimental evaluation over a prototype system that we have built shows that our methods are both effective and robust.
Efficient subgraph search over large uncertain graphs
Authors: Yuan Ye , Wang Guoren , Wang Haixun , Chen Lei
Published: June 2020

Retrieving graphs containing a query graph from a large graph database is a key task in many graph-based applications, including chemical compounds discovery, protein complex prediction, and structural pattern recognition. However, graph data handled by these applications is often noisy, incomplete, and inaccurate because of the way the data is produced. In this paper, we study subgraph queries over uncertain graphs. Specifically, we consider the problem of answering threshold-based probabilistic queries over a large uncertain graph database with the possible world semantics. We prove that problem is #P-complete, therefore, we adopt a
filtering-and-verification
strategy to speed up the search. In the
filtering
phase, we use a probabilistic inverted index, PIndex, based on subgraph features obtained by an optimal feature selection process. During the
verification
phase, we develop exact and bound algorithms to validate the remaining candidates. Extensive experimental results demonstrate the effectiveness of the proposed algorithms.
Efficient algorithms for finding optimal meeting point on road networks
Authors: Yan Da , Zhao Zhou , Ng Wilfred
Published: June 2020

Given a set of pointsQon a road network, anoptimal meeting point(OMP) query returns the point on a road networkG= (V,E) with the smallest sum of network distances to all the points inQ.This problem has many real world applications, such as minimizing the total travel cost for a group of people who want to find a location for gathering. While this problem has been well studied in the Euclidean space, the recently proposed state-of-the-art algorithm for solving this problem in the context of road networks is still not efficient. In this paper, we propose a new baseline algorithm for the OMP query, which reduces the search space from |Q| · |E| to |V| + |Q|. We also present two effective pruning techniques that further accelerate the baseline algorithm. Finally, in order to support spatial applications that involve large flow of queries and require fast response, an extremely efficient algorithm is proposed to find a high-quality near-optimal meeting point, which is orders of magnitude faster than the exact OMP algorithms. Extensive experiments are conducted to verify the efficiency of our algorithms.
Optimizing query answering under ontological constraints
Authors: Orsi Giorgio , Pieris Andreas
Published: June 2020

Ontological queries are evaluated against a database combined with ontological constraints. Answering such queries is a challenging new problem for database research. For many ontological modelling languages, query answering can be solved via query rewriting: given a conjunctive query and an ontology, the query can be transformed into a first-order query, called the
perfect rewriting
, that takes into account the semantic consequences of the ontology. Then, for every extensional database
D
, the answer to the query is obtained by evaluating the rewritten query against
D.
In this paper we present a new algorithm that computes the perfect rewriting of a conjunctive query w.r.t. a linear Datalog
±
ontology. Also, we provide an experimental comparison of our algorithm with existing rewriting techniques.
Private analysis of graph structure
Authors: Karwa Vishesh , Raskhodnikova Sofya , Smith Adam , Yaroslavtsev Grigory
Published: June 2020

We present efficient algorithms for releasing useful statistics about graph data while providing rigorous privacy guarantees. Our algorithms work on data sets that consist of relationships between individuals, such as social ties or email communication. The algorithms satisfy
edge differential privacy
, which essentially requires that the presence or absence of any particular relationship be hidden.

Our algorithms output approximate answers to
subgraph counting queries.
Given a query graph
H
, e.g., a triangle,
k
-star or
k
-triangle, the goal is to return the number of edge-induced isomorphic copies of
H
in the input graph. The special case of triangles was considered by Nissim, Raskhodnikova and Smith (STOC 2007), and a more general investigation of arbitrary query graphs was initiated by Rastogi, Hay, Miklau and Suciu (PODS 2009). We extend the approach of [NRS] to a new class of statistics, namely,
k
-star queries. We also give algorithms for
k
-triangle queries using a different approach, based on the higher-order local sensitivity. For the specific graph statistics we consider (i.e.,
k
-stars and
k
-triangles), we significantly improve on the work of [RHMS]: our algorithms satisfy a stronger notion of privacy, which does not rely on the adversary having a particular prior distribution on the data, and add less noise to the answers before releasing them.

We evaluate the accuracy of our algorithms both theoretically and empirically, using a variety of real and synthetic data sets. We give explicit, simple conditions under which these algorithms add a small amount of noise. We also provide the average-case analysis in the Erdős-Rényi-Gilbert
G
(
n
,
p
) random graph model.

Finally, we give hardness results indicating that the approach NRS used for triangles cannot easily be extended to
k
-triangles (and hence justifying our development of a new algorithmic approach).
Optimizing probabilistic query processing on continuous uncertain data
Authors: Peng Liping , Diao Yanlei , Liu Anna
Published: June 2020

Uncertain data management is becoming increasingly important in many applications, in particular, in scientific databases and data stream systems. Uncertain data in these new environments is naturally modeled by continuous random variables. An important class of queries uses complex selection and join predicates and requires query answers to be returned if their existence probabilities pass a threshold. In this work, we optimize threshold query processing for continuous uncertain data by (
i
) expediting joins using new indexes on uncertain data, (
ii
) expediting selections by reducing dimensionality of integration and using faster filters, and (
iii
) optimizing a query plan using a dynamic, per-tuple based approach. Evaluation results using real-world data and benchmark queries show the accuracy and efficiency of our techniques and significant performance gains over a state-of-the-art threshold query optimizer.
Efficient rank join with aggregation constraints
Authors: Xie Min , Lakshmanan Laks V. S. , Wood Peter T.
Published: June 2020

We show aggregation constraints that naturally arise in several applications can enrich the semantics of rank join queries, by allowing users to impose their application-specific preferences in a declarative way. By analyzing the properties of aggregation constraints, we develop efficient deterministic and probabilistic algorithms which can push the aggregation constraints inside the rank join framework. Through extensive experiments on various datasets, we show that in many cases our proposed algorithms can significantly outperform the naive approach of applying the state-of-the-art rank join algorithm followed by post-filtering to discard results violating the constraints.
Inspector gadget
Authors: Olston Christopher , Reed Benjamin
Published: June 2020

We consider how to monitor and debug query processing dataflows, in distributed environments such as
Pig/Hadoop.
Our work is motivated by a series of informal user interviews, which revealed that monitoring and debugging needs are both pressing and diverse. In response to these interviews, we created a framework for custom dataflow instrumentation, called
Inspector Gadget
(IG).

IG makes it easy to write a wide variety of monitoring and debugging behaviors, and attaches seamlessly to an existing, unmodified dataflow environment such as Pig. We have implemented a dozen user-requested tools in Inspector Gadget, each in just a few hundred lines of Java code. The performance overhead is modest in most cases.

Our Pig-based implementation of IG, called
Penny
, is slated for public release in mid-2011, in conjunction with the upcoming Apache Pig v0.9 release.
Online expansion of large-scale data warehouses
Authors: Cohen Jeffrey , Eshleman John , Hagenbuch Brian , Kent Joy , Pedrotti Christopher , Sherry Gavin , Waas Florian
Published: June 2020

Modern data warehouses store exceedingly large amounts of data, generally considered the crown jewels of an enterprise. The amount of data maintained in such data warehouses increases significantly over time---often at a continuous pace, e.g., by gathering additional data or retaining data for longer periods to derive additional business value, but occasionally also precipitously, e.g., when consolidating disparate data warehouses and Data Marts into a single database. Having to
expand
a data warehouse with 100's of TB of data by a substantial portion, e.g., 100% or more is a complex and disruptive maintenance operation as it typically involves some sort of dumping and reloading of data which requires substantial downtime.

In this paper we describe the methodology and mechanisms we developed in Greenplum Database to expand large-scale data warehouses in an
online
fashion, i.e., without noticeable downtime. At the core of our approach is a set of robust and transactionally consistent primitives that enable efficient data movement. Special emphasis was put on usability and control that lets an administrator tailor the expansion process to specific operational characteristics via priorities and schedules.

We present a number of experiments to quantify the impact of an on-going expansion on query workloads.
BROAD
Authors: Zhao Feng , Zhang Xiaolong , Tung Anthony K. H. , Chen Gang
Published: June 2020

Keyword search in databases has received a lot of attention in the database community as it is an effective approach for querying a database without knowing its underlying schema. However, keyword search queries often return too many results. One standard solution is to rank results such that the "best" results appear first. Still, this approach can suffer from redundancy problem where many high ranking results are in fact coming from the same part of the database and results in other parts of the database are missed completely.

In this demo, we propose the BROAD system which allows users to perform diverse, hierarchical browsing on keyword search results. Our system partitions the answer trees in the keyword search results by selectingkdiverse representatives from the trees, separating the answer trees intokgroups based on their similarity to the representatives and then recursively applying the partitioning for each group. By constructing summarized result for the answer trees in each of thekgroups, we provide a way for users to quickly locate the results that they desire.
DivDB
Authors: Vieira Marcos R. , Razente Humberto L. , Barioni Maria C. N. , Hadjieleftheriou Marios , Srivastava Divesh , Traina Caetano , Tsotras Vassilis J.
Published: June 2020

With the availability of very large databases, an exploratory query can easily lead to a vast answer set, typically based on an answer's relevance (i.e.,
top-k, tf-idf
) to the user query. Navigating through such an answer set requires huge effort and users give up after perusing through the first few answers, thus some interesting answers hidden further down the answer set can easily be missed. An approach to address this problem is to present the user with the most
diverse
among the answers based on some diversity criterion. In this demonstration we present DivDB, a system we built to provide query result diversification both for advanced and novice users. For the experienced users, who may want to test the performance of existing and new algorithms, we provide an SQL-based extension to formulate queries with diversification. As for the novice users, who may be more interested in the result rather than how to tune the various algorithms' parameters, the DivDB system allows the user to provide a "hint" to the optimizer on speed vs. quality of result. Moreover, novice users can use an interface to dynamically change the tradeoff value between relevance and diversity in the result, and thus visually inspect the result as they interact with this parameter. This is a great feature to the end user because finding a good tradeoff value is a very hard task and it depends on several variables (i.e., query parameters, evaluation algorithms, and dataset properties). In this demonstration we show a study of the DivDB system with two image databases that contain many images of the same object under different settings (e.g., different camera angle). We show how the DivDB helps users to iteratively inspect diversification in the query result, without the need to know how to tune the many different parameters of the several existing algorithms in the DivDB system.
Automatic workload driven index defragmentation
Authors: Narasayya Vivek , Park Hyunjung , Syamala Manoj
Published: June 2020

Queries that scan a B-Tree index can suffer significant I/O performance degradation due to index fragmentation. The task of determining if an index should be defragmented is challenging for database administrators (DBAs) since today's database engines offer no support for quantifying the impact of defragmenting an index on query I/O performance. Furthermore, DBMSs only support defragmentation at the granularity of an entire B-Tree, which can be very restrictive since defragmentation is an expensive operation and workloads typically access different ranges of an index non-uniformly. We have developed techniques to address the above two challenges, and implemented a prototype of automatic workload driven index defragmentation functionality in Microsoft SQL Server. We demonstrate this functionality by showing (a) how the system tracks the potential benefit of defragmenting an index on I/O performance at low overhead, (b) the ability to defragment a range of a B-Tree index online, and (c) how the cost/benefit trade-off can be controlled in a policy driven manner to enable automatic workload driven index defragmentation requiring minimal DBA intervention.
FuDoCS
Authors: Benouaret Karim , Benslimane Djamal , Hadjali Allel , Barhamgi Mahmoud
Published: June 2020

Modern enterprises are increasingly moving towards a service oriented architecture for data sharing by putting their data sources behind services, thereby providing an interoperable way to interact with their data. This class of services is known as DaaS (
Data-as-a-Service
) services. DaaS Composition is a powerful solution to answer the user's complex queries by combining primitive DaaS services. User preferences are a key aspect that must be considered in the service composition process. A more general and suitable approach to model preferences is based on fuzzy sets theory [3]. Fuzzy sets are very well suited to the interpretation of linguistic terms and constitute a convenient way for a user to express her/his preferences. For example, when expressing preferences about the price of a car, users often employ fuzzy terms like
rather cheap, affordable
, etc. However as DaaS services proliferate, a large number of candidate compositions that would use different (most likely competing) services may be used to answer the same query. Hence, it is important to set up an effective service composition framework that would identify and retrieve the most relevant services and return the top-
k
compositions according to the user preferences.
Resiliency-aware data management
Authors: Boehm Matthias , Lehner Wolfgang , Fetzer Christof
Published: June 2020

Computing architectures change towards massively parallel environments with increasing numbers of heterogeneous components. The large scale in combination with decreasing feature sizes leads to dramatically increasing error rates. The heterogeneity further leads to new error types. Techniques for ensuring resiliency in terms of robustness regarding these errors are typically applied at hardware abstraction and operating system levels. However, as errors become the normal case, we observe increasing costs in terms of computation overhead for ensuring robustness. In this paper, we argue that ensuring resiliency on the data management level can reduce the required overhead by exploiting context knowledge of query processing and data storage. Apart from reacting on already detected errors, this was mostly neglected in database research so far. We therefore give a broad overview of the background of resilient computing and existing techniques from the database perspective. Based on the lack of existing techniques on data management level, we raise three fundamental challenges of resiliency-aware data management and present example use cases. Finally, our vision of resiliency-aware data management opens many directions of future work. Fundamental research, including the partial reuse of underlying mechanisms, would allow data management systems to cope with future hardware characteristics by effectively and efficiently ensuring resiliency.
Data generation for application-specific benchmarking
Authors: Tay Y. C.
Published: June 2020

The Transaction Processing Council (TPC) has played a pivotal role in the database industry's growth over the last twenty-five years. However, its handful of domain-specific benchmarks are increasingly irrelevant to the multitude of data-centric applications, and its top-down process is slow.

This mismatch calls for a paradigm shift to a bottom-up community effort to develop tools for application-specific benchmarking. Such a development program would center around techniques for synthetically scaling (up or down) an empirical dataset. This engineering effort in turn requires the development of a database theory on attribute value correlation.
Exploration of deep web repositories
Authors: Zhang Nan , Das Gautam
Published: June 2020

With the proliferation of online repositories (e.g., databases or document corpora) hidden behind proprietary web interfaces, e.g., keyword-/form-based search and hierarchical/graph-based browsing interfaces, efficient ways of exploring contents in such hidden repositories are of increasing importance.

There are two key challenges: one on the proper understanding of interfaces, and the other on the efficient exploration, e.g., crawling, sampling and analytical processing, of very large repositories. In this tutorial, we focus on the fundamental developments in the field, including web interface understanding, crawling, sampling, and data analytics over web repositories with various types of interfaces and containing structured or unstructured data. Our goal is to encourage audience to initiate their own research in these exciting areas.
Panel discussion
Authors: Lazowska Ed
Published: June 2020

This session is intended as an open discussion between a small group of panelists and the conference attendees. What can we do as a community to increase the impact (whatever that means) of our research, especially with the rise in paper counts, write only conferences, over-specialization of ourselves and our students, migration of distinguished researchers to more development-oriented positions, etc.? More specifically: What should we look for in graduate applicants? What should be the balance between breadth and depth in graduate programs? Are there emerging high-impact areas on which there should be greater focus (e.g., visualization, scientific data management)? How do we make data management techniques (databases, data mining, machine learning) usable by the masses? How can we contribute to a data-centric view of everything science, engineering, the social sciences, commerce?
Programas de garantía externa de la calidad SEQCML. Evolución de las prestaciones analíticas de los laboratorios clínicos a lo largo de 30 años y comparación con otros programas
Authors: Perich Alsina Carmen , Ricós Carmen , Marqués Fernando , Minchinela Joana , Salas Angel , Martínez-Bru Cecilia , Boned Beatriz , Gómez-Rioja Rubén , Cortés Marià , González-Lao Elisabet , García Lario Jose Vicente , Tejedor Xavier , Bullich Sandra , Ventura Montserrat , González-Tarancón Ricardo , Fernández-Fernández Pilar , Ramón Francisco , Corte Zoraida , Llopis Maria Antonia , Díaz-Garzón Jorge , Simón Margarita , Fernández-Calle Pilar
Published: June 2020

Objetivos

El objetivo de este estudio es conocer la evolución de la prestación analítica de los laboratorios participantes en los programas EQA de la SEQCML durante los 30 años de funcionamiento y compararla con la prestación obtenida en otros programas EQA para saber si los resultados son similares.

Métodos

Se evalúan los resultados obtenidos durante este periodo, aplicando las especificaciones de la calidad derivadas de la VB y del estado del arte. Además, se realiza una comparación con los resultados obtenidos por otras organizaciones de programas EQA.

Resultados

Se observa que los laboratorios participantes en los programas EQA-SEQCML han mejorado su prestación durante los 30 años de experiencia y que las especificaciones derivadas de la variación biológica son alcanzables. La comparación entre programas EQA es difícil, debido a: la falta de accesibilidad y a las diferencias en el diseño de estos programas (materiales control, cálculos empleados y especificaciones analíticas establecidas).

Conclusiones

Los datos de este estudio ponen de manifiesto que para algunas magnitudes biológicas los resultados obtenidos en los programas todavía no están armonizados, aunque se estan realizando esfuerzos para alcanzar la armonización. Los organizadores de programas EQA deberían sumarse al esfuerzo de armonización, facilitando la información sobre sus resultados para permitir su comparación.
Advancing interpretation of stable isotope assignment maps: comparing and summarizing origins of known-provenance migratory bats
Authors: Campbell Caitlin J. , Fitzpatrick Matthew C. , Vander Zanden Hannah B. , Nelson David M.
Published: June 2020

Probability-of-origin maps deduced from stable isotope data are important for inferring broad-scale patterns of animal migration, but few resources and tools for interpreting and validating these maps exist. For example, quantitative tools for comparing multiple probability-of-origin maps do not exist, and many existing approaches for geographic assignment of individuals have not been validated or compared with respect to precision and accuracy. To address these challenges, we created and analyzed probability-of-origin maps using stable hydrogen isotope values from known-origin individuals of three species of migratory bat. We used a metric of spatial overlap to group individuals by areas of origin without a priori knowledge of such regions. The metric of spatial similarity allowed for quantitative comparison of geographic origins and grouping of individuals with similar origins. We then compared four approaches for inferring origins (cumulative-sum, odds-ratio, quantile-only, and quantile-simulation) across a range of thresholds and probable minimum distance traveled. The accuracy of geographic origins and minimum distance traveled varied across species at most threshold values for most approaches. The cumulative-sum and quantile-simulation approaches had generally higher precision at a given level of accuracy than the odds-ratio and quantile-only approaches, and many threshold values were associated with a relatively high degree (> 300 km) of variation in minimum distance traveled. Overall, these results reinforce the importance of validating assignment techniques with known-origin individuals when possible. We present the tools discussed as part of an R package, ‘isocat’ (“Isotope Origin Clustering and Assignment Tools”).
Attractors of variation in Hungarian inflectional morphology
Authors: Rácz Péter , Rebrus Péter , Törkenczy Miklós
Published: June 2020

We use algorithmic learning and statistical methods over a form frequency list (compiled from the Hungarian web corpus) to investigate variation in Hungarian verbal inflection. Our aims are twofold: (i) to give an adequate description of this variation, which has not been described in detail in the literature and (ii) to explore the range and depth of lexical attractors that potentially shape this variation. These attractors range from closely related ones, such as the shape of the word form or the behaviour of the verb’s paradigm, to broad ones, such as the behaviour of similar verbs or the phonotactics of related verb forms. We find that verbal variation is predominantly determined by similarity to related verb forms rather than by word shape or by word frequency. What is more, the effect of similarity is better approximated using inflected forms as opposed to base forms as points of comparison. This, in turn, supports a rich memory model of morphology and the mental lexicon.
Corrosion control of nuclear steam generators under normal operation and plant-outage conditions: a review
Authors: Rodríguez Martín A.
Published: June 2020

Nuclear steam generators (NSGs) are key components of nuclear power plants (NPPs) since their reliability affects the overall plant performance. Corrosion control of steam generators under operation and during plant outages is attained by proper design, adequate material selection and control of water chemistry in the entire secondary cooling circuit. This article reviews the types of steam generators, the materials used for their construction (with a special focus on tubing alloys), the corrosion processes that may occur under operation and the strategies to preserve steam generators and other components of the secondary cooling system from corrosion during plant outages.
Do sex-specific immunobiological factors and differences in angiotensin converting enzyme 2 (ACE2) expression explain increased severity and mortality of COVID-19 in males?
Authors: Vikse Jens , Lippi Giuseppe , Henry Brandon Michael
Published: June 2020

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome (SARS) coronavirus 2 (SARS-CoV-2), shares similarities with the former SARS outbreak, which was caused by SARS-CoV-1. SARS was characterized by severe lung injury due to virus-induced cytopathic effects and dysregulated hyperinflammatory state. COVID-19 has a higher mortality rate in men both inside and outside China. In this opinion paper, we describe how sex-specific immunobiological factors and differences in angiotensin converting enzyme 2 (ACE2) expression may explain the increased severity and mortality of COVID-19 in males. We highlight that immunomodulatory treatment must be tailored to the underlying immunobiology at different stages of disease. Moreover, by investigating sex-based immunobiological differences, we may enhance our understanding of COVID-19 pathophysiology and facilitate improved immunomodulatory strategies.
Approximation operators based on preconcepts
Authors: Wang Gang , Mao Hua
Published: June 2020

Using the notion of preconcept, we generalize Pawlak’s approximation operators from a one-dimensional space to a two-dimensional space in a formal context. In a formal context, we present two groups of approximation operators in a two-dimensional space: one is aided by an equivalence relation defined on the attribute set, and another is aided by the lattice theoretical property of the family of preconcepts. In addition, we analyze the properties of those approximation operators. All these results show that we can approximate all the subsets in a formal context assisted by the family of preconcepts using the above groups of approximation operators. Some biological examples show that the two groups of approximation operators provided in this article have potential ability to assist biologists to do the phylogenetic analysis of insects.
Serum Neopterin Levels and IDO Activity as Possible Markers for Presence and Progression of Hepatitis B
Authors: Koç Deniz Öğütmen , Özhan Yağmur , Acar Ebru Türköz , Bireroğlu Nilgün , Aslan Fatih , Keğin Murat , Sipahi Hande
Published: June 2020

Chronic Hepatitis B virus (HBV) is still one of the major reasons for liver related mortality and morbidity all around the world. This study aimed to investigate the possible relationship between the immune system activation and presence, as well as progression, of hepatitis B infection by monitoring the tryptophan degradation and serum neopterin levels in patients with HBV. 110 patients with HBV and 23 healthy subjects were included in the study. The patients had significantly higher neopterin levels and increased kynurenine to tryptophan ratios, which were most probably due to enhanced indoleamine 2,3-dioxygenase (IDO) activity compared to healthy control. A strong positive correlation was found between neopterin levels and IDO activity in patient group. Neopterin levels and IDO activity were markedly increased in patients with histological activity index (HAI) ≥4 compared to HAI<4, and a significant correlation was found between neopterin and HAI. Moreover, there was a significant correlation between albumin levels and IDO activity in HBV patients. These findings suggest that tryptophan degradation results from IFN-γ-induced IDO activation, likewise depletion of albumin synthesis in HBV patients may result from diminished tryptophan availability. In conclusion, based on the study results, serum neopterin levels and IDO activity could provide additional immunological information for monitoring liver histological activity and can be used as prognostic markers in HBV disease.
Discrete and asymptotic approximations for one stationary radiative–conductive heat transfer problem
Authors: Amosov Andrey A. , Krymov Nikita E.
Published: June 2020

Special discrete and asymptotic approximations are proposed for the boundary value problem describing a stationary radiative–conductive heat transfer in a system of absolutely black heat-conducting rods of circular cross-section. Results of numerical experiments are presented to confirm the efficiency of proposed approximations.
Hyperelastic membrane modelling based on data-driven constitutive relations
Authors: Salamatova Victoria Yu. , Liogky Alexey A.
Published: June 2020

We present data-driven modelling of membrane deformation by a hyperelastic nodal force method. We assume that constitutive relations are characterized by tabulated experimental data instead of the conventional phenomenological approach. As experimental data we use synthetic data from the bulge test simulation for neo-Hookean and Gent materials. The numerical study of descriptive and predictive capabilities of our approach demonstrates very good results of the data-driven modelling provided that the input tabulated data are expanded to a wider region of strain characteristics. Two methods for such expansion are suggested and numerically studied. Different loadings of hyperelastic membranes are successfully recovered by our approach.
Improvement of skeletal muscle insulin sensitivity by 1 week of SGLT2 inhibitor use
Authors: Goto Yuka , Otsuka Yoshie , Ashida Kenji , Nagayama Ayako , Hasuzawa Nao , Iwata Shimpei , Hara Kento , Tsuruta Munehisa , Wada Nobuhiko , Motomura Seiichi , Tajiri Yuji , Nomura Masatoshi
Published: June 2020

Background and Aims:

It is currently unclear whether sodium–glucose co-transporter 2 (SGLT2) inhibitor administration can improve the insulin sensitivity as well as rapidly reduce plasma glucose concentrations in humans during the early phase of treatment initiation. This study aimed to investigate the effect of SGLT2 inhibitor on insulin sensitivity in the early phase of treatment initiation.

Methods and Results

This single-center, open label, and single-arm prospective study recruited 20 patients (14 men) with type 2 diabetes mellitus (T2DM). We examined the patients’ metabolic parameters before and 1 week after SGLT2 inhibitor (10 mg/day of empagliflozin) administration. The glucose infusion rate (GIR) was evaluated using the euglycemic hyperinsulinemic glucose clamp technique. Changes in laboratory and anthropometric parameters before and after SGLT2 inhibitor administration were analyzed according to the change in the GIR. The BMI, body fat amount, skeletal muscle amount, systolic blood pressure, and triglyceride level significantly decreased along with the treatment, while urinary glucose level and log GIR value significantly increased. Notably, changes in the GIR after SGLT2 inhibitor administration, which indicated improvement in peripheral insulin sensitivity, were negatively correlated with T2DM duration and positively with reduction in fluctuation of daily plasma glucose profiles before and after treatment.

Conclusion

SGLT2 inhibitor improved insulin sensitivity in the skeletal muscle independent of anthropometric changes. Patients with short duration of T2DM and insulin resistance can be good candidates for short-term SGLT2 inhibitor administration to improve insulin sensitivity in the skeletal muscle.
Surgical Challenges of Heart Mate 3 Pump Implantation in Aneurysmally Changed Heart Ventricles
Authors: Terzic Dusko , Nestorovic Emilija , Markovic Dejan , Kovacevic Kostic Natasa , Djordjevic Aleksandar , Karan Radmila , Cubrilo Marko , Stojiljkovic Vladimir , Milićević Vladimir , Cumic Jelena , Putnik Svetozar
Published: June 2020

We presented surgical treatment of three patients indicated for implantation of a permanent mechanical circulatory support device and with the associated left ventricular aneurysms. In order to evade the left ventricular rupture, adverse thromboembolic events and provide safe implantation of the inflow cannula, LVAD HM3 implantation together with the reconstruction of the left ventricular aneurysmal wall was performed in two patients. Regarding the third patient, LVAD implantation upon the reconstruction of the left ventricular wall was abandoned because there was no safe location for placement of the inflow cannula.
Parent-Child Agreement on Postconcussion Symptoms in the Acute Postinjury Period
Authors: Gagnon Isabelle , Teel Elizabeth , Gioia Gerard , Aglipay Mary , Barrowman Nick , Sady Maegan , Vaughan Christopher , Zemek Roger ,   PEDIATRIC EMERGENCY RESEARCH CANADA (PERC) 5P TEAM
Published: June 2020

OBJECTIVES:

To evaluate parent-child agreement on postconcussion symptom severity within 48 hours of injury and examine the comparative predictive power of a clinical prediction rule when using parent or child symptom reporting.

METHODS:

Both patients and parents quantified preinjury and current symptoms using the Postconcussion Symptom Inventory (PCSI) in the pediatric emergency department. Two-way mixed, absolute measure intraclass correlation coefficients were calculated to evaluate the agreement between patient and parent reports. A multiple logistic regression was run with 9 items to determine the predictive power of the Predicting and Preventing Postconcussive Problems in Pediatrics clinical prediction rule when using the child-reported PCSI. Delong’s receiver operating characteristic curve analysis was used to compare the area under the curve (AUC) for the child-report models versus previously published parent-report models.

RESULTS:

Overall parent-child agreement for the total PCSI score was fair (intraclass correlation coefficient = 0.66). Parent-child agreement was greater for (1) postinjury (versus preinjury) ratings, (2) physical (versus emotional) symptoms, and (3) older (versus younger) children. Applying the clinical prediction rule by using the child-reported PCSI maintained similar predictive power to parent-reported PCSI (child AUC = 0.70 [95% confidence interval: 0.67–0.72]; parent AUC = 0.71 [95% confidence interval: 0.68–0.74]; P = .23).

CONCLUSIONS:

Overall parent-child agreement on postconcussion symptoms is fair but varies according to several factors. The findings for physical symptoms and the clinical prediction rule have high agreement; information in these domains are likely to be similar regardless of whether they are provided by either the parent or child. Younger children and emotional symptoms show poorer agreement; interviewing both the child and the parent would provide more comprehensive information in these instances.
Benzodiazepine Treatment and Fracture Risk in Young Persons With Anxiety Disorders
Authors: Bushnell Greta A. , Gerhard Tobias , Crystal Stephen , Olfson Mark
Published: June 2020

BACKGROUND:

Benzodiazepines are commonly prescribed to treat anxiety disorders and have been associated with falls and fractures in older adults. It is unknown whether benzodiazepines increase fracture risk in youth. We examined whether youth with anxiety disorders initiating benzodiazepine treatment have an increased risk of fractures compared with youth initiating selective serotonin reuptake inhibitors (SSRIs).

METHODS:

We used claims from commercially insured children (6–17 years) and young adults (18–24) with a recent anxiety disorder diagnosis, initiating benzodiazepines or SSRIs (2008–2016). Youth were followed until fracture, treatment discontinuation or switching, disenrollment, 3 months, or December 31, 2016. The primary end point was diagnostic codes for upper and lower limb fractures. Incident fracture rates, incident rate ratios (IRRs), and incident rate differences (IRDs) were estimated with propensity score inverse probability of treatment weighting.

RESULTS:

The cohort included 120 715 children and 179 768 young adults. In children, crude fracture rates during treatment were 33.1 per 1000 person-years (PYs) for benzodiazepine initiators and 25.1 per 1000 PYs for SSRI initiators. Adjusted IRR and IRD were 1.53 (95% confidence interval [CI]: 0.94–2.50) and 13.4 per 1000 PYs. Risk was heightened in children initiating long-acting benzodiazepines versus SSRIs (adjusted IRR = 2.30 [95% CI: 1.08–4.91]). Fracture rates were lower in young adults, with minimal differences between treatments (adjusted IRR = 0.85 [95% CI: 0.57–1.27]; adjusted IRD = −1.3 per 1000 PYs).

CONCLUSIONS:

An increased rate of fractures in children, but not young adults, with anxiety disorders initiating benzodiazepine treatment compared to SSRI treatment suggests a need for increased caution in the weeks after benzodiazepine initiation in children.
The Changes of University Students Academic Motivation over Time: the Relationship with Academic Achievement, Satisfaction with Studies and Psychological Well-Being
Authors: Rugevičius Mindaugas , Kairys Antanas , Čepienė Ramutė , Liniauskaitė Audronė , Brazdeikienė Liana , Žakaitis Povilas
Published: June 2020

One of the most important psychological factors related to the success of studies is the students’ academic motivation. This study examined one-year changes in academic motivation, students’ satisfaction, and psychological well-being. Three hypotheses formulated: (1) Students’ motivation will decrease over the year, but it will be possible to distinguish the groups of students that will have different changes of motivation. (2) The decrease in intrinsic motivation will be associated with lower academic achievement and lower satisfaction with studies. (3) The decrease in intrinsicmotivation will be associated with lower psychological well-being.The first measurement performed during the spring semester, the second performed 12 ± 1 months later. 232 fully completed two-measurement questionnaires were selected for the analysis. The sample included 52 men and 180 women. The Student Academic Motivation Scale (SAMS-21) was used to assess academic motivation, and the Lithuanian Psychological Well-being Scale for Young People (LPGS-J) was used to measure psychological well-being. It was found that during one-year academic motivation decreased and it showed very large individual differences.Changes in academic motivation, students’ satisfaction, and psychological well-being are interrelated, and changes in motivation allow one to predict study satisfaction and psychological well-being. The assumption that changes in motivation would predict students’ academic achievement not confirmed.