bluuebunny/crossref_metadata_2025 huggingface dataset:
Use of social media in a national Tuberculosis Drug Resistance Survey: lessons from the first anti-tuberculosis drug resistance survey in Ghana
Authors: Sylverken Augustina Angelina , Owusu-Dabo Ellis , Kwarteng Alexander , Twumasi-Ankrah Sampson , Owusu Michael , Adu-Amoah Louis , Dumevi Rexford Mawunyo , Arthur Rejoice Agyeiwaa , Addofoh Nicholas , Dzata Francisca , Bonsu Frank
Published: September 2019

Background: The widespread use of social media applications on mobile phones indicate that smart phones have become more than just a simple medium for voice calling. Several studies have shown the potential benefit of these social media applications in discussing many health conditions. We report on tracking sample transport by public and private transport providers using WhatsApp during the first nationwide drug resistance tuberculosis (TB) survey in Ghana.

Methods: The survey was conducted between February 2016 and June 2017, and involved 33 TB diagnostic sites selected on the basis of a two-stage cluster randomized sampling design on both anticipated yield and probability proportional to size method. We engaged the services of privately and publicly owned vehicles’ union to transport samples to the Bacteriology department at the Kumasi Centre for Collaborative Research in Tropical Medicine laboratories for further laboratory processing.

We created a mobile social group platform (‘National TBDRS’) on WhatsApp consisting of two representatives from each site as well as other stakeholders. The purpose was to notify a laboratory team in Kumasi, on the following details of the sample: date and time of dispatch, driver’s name, car number, estimated time of arrival, and bus terminal name. 

Results: A total 3077 WhatsApp messages were received during the survey period. Of these, 2879 (93.57%) messages were related to the survey. We observed a positive correlation between the total number of messages received and the total number of well-packaged sputum samples sent (r=0.89, p=0.02). There were no major transport delays (11:44±03:50) and all samples arrived within a 3-day window from the survey sites.

Conclusions: Using WhatsApp as a platform of communication can aid in improving tracking of samples, enhance accountability of for example drivers handling the samples over at a road crossing and communication across health facilities.
Network-based Observability and Controllability Analysis of Dynamical Systems: the NOCAD toolbox
Authors: Leitold Dániel , Vathy-Fogarassy Ágnes , Abonyi János
Published: September 2019

The network science-based determination of driver nodes and sensor placement has become increasingly popular in the field of dynamical systems over the last decade. In this paper, the applicability of the methodology in the field of life sciences is introduced through the analysis of the neural network of Caenorhabditis elegans. Simultaneously, an Octave and MATLAB-compatible NOCAD toolbox is proposed that provides a set of methods to automatically generate the relevant structural controllability and observability associated measures for linear or linearised systems and compare the different sensor placement methods.
Setting the stage for strengthened annual monitoring of family planning program performance at the state/national level in Myanmar
Authors: Nwe Tin Khaing , Williamson Jessica , Sonneveldt Emily
Published: September 2019

Background: Although Myanmar has made good progress in family planning by increased contraceptive prevalence rate (CPR) from 41% in 2007 to 52.2% in 2016, it remains lower than the target of 60% by 2020. There are also huge disparities sub-nationally, ranging from 25% to 60%. While there is a strong need to monitor the progress of family planning program regularly at the national and sub-national level, Myanmar has limited surveys, data quality and methodological issues in its Health Management Information System (HMIS), and a scattered rollout of the Logistic Management Information System (LMIS).

Methods: To identify viable options for annual monitoring, four data sources: modelled contraceptive prevalence rate for modern methods (mCPR) estimates from Track20’s  Family Planning Estimation Tool (FPET); method-specific prevalence from the  2015-16 Myanmar Demographic and Health Survey (DHS); mCPR estimates and method prevalence from  HMIS and estimates of modern method use (EMU) based on commodity consumption data from LMIS, were compared for the years 2015-2017. Estimates of mCPR from HMIS were tested for accuracy based on whether they fell within the 95% confidence interval of mCPR estimates from the FPET for the corresponding years. EMU from LMIS was also tested for those years and states/regions where available.

Results: For annual tracking of mCPR, direct estimates of HMIS were considered carefully, as they were much higher than those of the DHS survey and were not matched by FPET results, except in Chin and Kayin. To monitor the method mix, HMIS data can be used as these are similar pattern with DHS in both national and State/Regional level except Chin and Kayin. LMIS could be used in annual tracking when there are high reporting rates and valid information of consumption.

Conclusions: Track20’s FPET is the method of choice to get valid information for annual monitoring of family planning program.
Herniation of the caecum and ascending colon through the foramen of Winslow: a case report and review
Authors: Sammut M , Barben C
Published: September 2019

Approximately 5% of intestinal obstruction cases are caused by internal herniation. Caecal herniation through the foramen of Winslow is considered a rare event. The management of caecal herniation remains challenging due to the lack of literature highlighting this pathology. A 66-year-old woman was admitted with a 24-hour history of epigastric pain radiating to the back. The pain was associated with nausea and vomiting of gastric contents. On examination, the abdomen was soft with mild tenderness but no signs of peritonism or distension. The abdominal x-ray and a computed tomography were in keeping with caecal volvulus and confirmed that the caecum was not in the right iliac fossa. In a midline laparotomy procedure, the ileum, caecum and ascending colon were noted to be herniating into the foramen of Winslow. A right hemicolectomy with a handsewn anastomosis was performed. The foramen of Winslow was not closed. No postoperative complications occurred.

A literature review showed a lack of similar cases with no agreed management consensus. The laparotomy approach is comparable to the laparoscopic approach and no caecal herniation recurrence after open/laparoscopic surgical procedures were identified. Awareness of caecal herniation allows early diagnosis and timely surgical management is needed in prevent patient morbidity and mortality.
Do citizens use storytelling or rational argumentation to lobby politicians
Authors: Holdo Markus , Öberg PerOla , Magnusson Simon
Published: September 2019

What should count as legitimate forms of reasoning in public deliberation is a contested issue. Democratic theorists have argued that storytelling may offer a more accessible form of deliberation for marginalised citizens than ‘rational argumentation’. We investigate the empirical support for this claim by examining Swedish citizens’ use of storytelling in written communication with the political establishment. We test whether stories are used frequently, as well as by whom, and how they are used. We find that storytelling is (1) rare, (2) not more frequent among people with nonmainstream views, and (3) used together with rational argumentation. In line with some previous research, we show that stories still play other important roles: authorising the author, undermining political opponents and, most often, further supporting arguments made in ‘rational’ form. The results suggest that people rely more on rational argumentation than storytelling when expecting interlocutors to be hostile to their views.
Algunas notas sobre la criminología cultural
Authors: Hayward Keith , Young Jock
Published: September 2019

En el presente artículo, los autores abordan algunas de las características principales de la criminología cultural, una perspectiva que ha tenido un notable desarrollo en los últimos años. En particular, definen la necesidad un nuevo enfoque «cultural» en la criminología contemporánea, en el marco de la Modernidad Tardía, que nos obliga a replantearnos tanto su objeto como su método de investigación. Esta propuesta, que se define como novedosa, busca trazar su genealogía en enfoques como el «naturalismo» de Matza, la fenomenología radical de Becker o la perspectiva crítica de la National Deviancy Conference, entre otros. De esta forma, los autores plantean la necesidad de disputar el campo criminológico con aquellas «criminologías» quedenominan «positivistas», «neoliberales» o «académicas». Por último, esbozan algunos ejemplos de este «nuevo/viejo» enfoque para la criminología.
Automated verification of query equivalence using satisfiability modulo theories
Authors: Zhou Qi , Arulraj Joy , Navathe Shamkant , Harris William , Xu Dong
Published: September 2019

Database-as-a-service offerings enable users to quickly create and deploy complex data processing pipelines. In practice, these pipelines often exhibit significant overlap of computation due to redundant execution of certain sub-queries. It is challenging for developers and database administrators to manually detect overlap across queries since they may be distributed across teams, organization roles, and geographic locations. Thus, we require automated cloud-scale tools for identifying equivalent queries to minimize computation overlap.

State-of-the-art algebraic approaches to automated verification of query equivalence suffer from two limitations. First, they are unable to model the semantics of widely-used SQL features, such as complex query predicates and three-valued logic. Second, they have a computationally intensive verification procedure. These limitations restrict their efficacy and efficiency in cloud-scale database-as-a-service offerings.

This paper makes the case for an alternate approach to determining query equivalence based on symbolic representation. The key idea is to effectively transform a wide range of SQL queries into first order logic formulae and then use satisfiability modulo theories to efficiently verify their equivalence. We have implemented this symbolic representation-based approach in EQUITAS. Our evaluation shows that EQUITAS proves the semantic equivalence of a larger set of query pairs compared to algebraic approaches and reduces the verification time by 27X. We also demonstrate that on a set of 17,461 real-world SQL queries, it automatically identifies redundant execution across 11% of the queries. Our symbolic-representation based technique is currently deployed on Alibaba's MaxCompute database-as-a-service platform.
Towards a unified framework for string similarity joins
Authors: Xu Pengfei , Lu Jiaheng
Published: September 2019

A similarity join aims to find all similar pairs between two collections of records. Established algorithms utilise different similarity measures, either syntactic or semantic, to quantify the similarity between two records. However, when records are similar in forms of a mixture of syntactic and semantic relations, utilising a single measure becomes inadequate to disclose the real similarity between records, and hence unable to obtain high-quality join results.

In this paper, we study a unified framework to find similar records by combining multiple similarity measures. To achieve this goal, we first develop a new similarity framework that unifies the existing three kinds of similarity measures simultaneously, including syntactic (typographic) similarity, synonym-based similarity, and taxonomy-based similarity. We then theoretically prove that finding the maximum unified similarity between two strings is generally
NP
-hard, and furthermore develop an approximate algorithm which runs in polynomial time with a non-trivial approximation guarantee. To support efficient string joins based on our unified similarity measure, we adopt the filter-and-verification framework and propose a new signature structure, called
pebble
, which can be simultaneously adapted to handle multiple similarity measures. The salient feature of our approach is that, it can judiciously select the best pebble signatures and the overlap thresholds to maximise the filtering power. Extensive experiments show that our methods are capable of finding similar records having mixed types of similarity relations, while exhibiting high efficiency and scalability for similarity joins. The implementation can be downloaded at https://github.com/HY-UDBMS/AU-Join.
Finding attribute-aware similar regions for data analysis
Authors: Feng Kaiyu , Cong Gao , Jensen Christian S. , Guo Tao
Published: September 2019

With the proliferation of mobile devices and location-based services, increasingly massive volumes of geo-tagged data are becoming available. This data typically also contains non-location information. We study how to use such information to characterize a region and then how to find a region of the same size and with the most similar characteristics. This functionality enables a user to identify regions that share characteristics with a user-supplied region that the user is familiar with and likes. More specifically, we formalize and study a new problem called the attribute-aware similar region search (
ASRS
) problem. We first define so-called composite aggregators that are able to express aspects of interest in terms of the information associated with a user-supplied region. When applied to a region, an aggregator captures the region's relevant characteristics. Next, given a query region and a composite aggregator, we propose a novel algorithm called
DS-Search
to find the most similar region of the same size. Unlike any previous work on region search,
DS-Search
repeatedly discretizes and splits regions until an split region either satisfies a drop condition or it is guaranteed to not contribute to the result. In addition, we extend
DS-Search
to solve the
ASRS
problem approximately. Finally, we report on extensive empirical studies that offer insight into the efficiency and effectiveness of the paper's proposals.
Arx
Authors: Poddar Rishabh , Boelter Tobias , Popa Raluca Ada
Published: September 2019

In recent years, encrypted databases have emerged as a promising direction that provides data confidentiality without sacrificing functionality: queries are executed on encrypted data. However, many practical proposals rely on a set of weak encryption schemes that have been shown to leak sensitive data. In this paper, we propose Arx, a practical and functionally rich database system that encrypts the data only with semantically secure encryption schemes. We show that Arx supports real applications such as ShareLaTeX with a modest performance overhead.
GRAIL
Authors: Paparrizos John , Franklin Michael J.
Published: September 2019

The analysis of time series is becoming increasingly prevalent across scientific disciplines and industrial applications. The effectiveness and the scalability of time-series mining techniques critically depend on design choices for three components responsible for (i) representing; (ii) comparing; and (iii) indexing time series. Unfortunately, these components have to date been investigated and developed independently, often resulting in mutually incompatible methods. The lack of a unified approach has hindered progress towards fast and accurate analytics over massive time-series collections. To address this major drawback, we present GRAIL, a generic framework to learn compact time-series representations that preserve the properties of a user-specified comparison function. Given the comparison function, GRAIL (i) extracts landmark time series using clustering; (ii) optimizes necessary parameters; and (iii) exploits approximations for kernel methods to construct representations in linear time and space by expressing each time series as a combination of the landmark time series. We extensively evaluate GRAIL for querying, classification, clustering, sampling, and visualization of time series. For these tasks, methods leveraging GRAIL's representations are significantly faster and at least as accurate as state-of-the-art methods operating over the raw time series. GRAIL shows promise as a new primitive for highly accurate, yet scalable, time-series analysis.
Buckle
Authors: Huynh Viet-Phi , Papotti Paolo
Published: September 2019

Fact checking is the task of determining if a given claim holds. Several algorithms have been developed to check facts with reference information in the form of knowledge bases. We demonstrate BUCKLE, an open-source benchmark for comparing and evaluating fact checking algorithms in a level playing field across a range of scenarios. The demo is centered around three main lessons. To start, we show how, by changing the properties of the training and test facts, it is possible to influence significantly the performance of the algorithms. We then show the role of the reference data. Finally, we discuss the performance for algorithms designed on different principles and assumptions, as well as approaches that address the
link prediction task
in knowledge bases.
Flare & lantern
Authors: Essertel Grégory , Tahboub Ruby Y. , Wang Fei , Decker James , Rompf Tiark
Published: September 2019

Running machine learning (ML) workloads at scale is as much a data management problem as a model engineering problem. Big performance challenges exist when data management systems invoke ML classifiers as user-defined functions (UDFs) or when stand-alone ML frameworks interact with data stores for data loading and pre-processing (ETL). In particular, UDFs can be precompiled or simply a black box for the data management system and the data layout may be completely different from the native layout, thus adding overheads at the boundaries. In this demo, we will show how bottlenecks between existing systems can be eliminated when their engines are designed around runtime compilation and native code generation, which is the case for many state-of-the-art relational engines as well as ML frameworks. We demonstrate an integration of Flare (an accelerator for Spark SQL), and Lantern (an accelerator for TensorFlow and PyTorch) that results in a highly optimized end-to-end compiled data path, switching between SQL and ML processing with negligible overhead.
UDAO
Authors: Zaouk Khaled , Song Fei , Lyu Chenghao , Sinha Arnab , Diao Yanlei , Shenoy Prashant
Published: September 2019

Big data analytics systems today still lack the ability to take user performance goals and budgetary constraints, collectively referred to as "objectives", and automatically configure an analytic job to achieve the objectives. This paper presents UDAO, a unified data analytics optimizer that can automatically determine the parameters of the runtime system, collectively called a job configuration, for general dataflow programs based on user objectives. UDAO embodies key techniques including
in-situ modeling
, which learns a model for each user objective in the same computing environment as the job is run, and
multi-objective optimization
, which computes a Pareto optimal set of job configurations to reveal tradeoffs between different objectives. Using benchmarks developed based on industry needs, our demonstration will allow the user to explore (1)
learned models
to gain insights into how various parameters affect user objectives; (2)
Pareto frontiers
to understand interesting tradeoffs between different objectives and how a configuration recommended by the optimizer explores these tradeoffs; (3)
end-to-end benefits
that UDAO can provide over default configurations or those manually tuned by engineers.
Raptor
Authors: Singla Samriddhi , Eldawy Ahmed , Alghamdi Rami , Mokbel Mohamed F.
Published: September 2019

With the increase in amount of remote sensing data, there have been efforts to efficiently process it to help ecologists and geographers answer queries. However, they often need to process this data in combination with vector data, for example, city boundaries. Existing efforts require one dataset to be converted to the other representation, which is extremely inefficient for large datasets. In this demonstration, we focus on the zonal statistics problem, which computes the statistics over a raster layer for each polygon in a vector layer. We demonstrate three approaches, vector-based, raster-based, and
raptor-based
approaches. The latter is a recent effort of combining raster and vector data without a need of any conversion. This demo will allow users to run their own queries in any of the three methods and observe the differences in their performance depending on different raster and vector dataset sizes.
Speedup your analytics
Authors: Lu Jiaheng , Chen Yuxing , Herodotou Herodotos , Babu Shivnath
Published: September 2019

Database and big data analytics systems such as Hadoop and Spark have a large number of configuration parameters that control memory distribution, I/O optimization, parallelism, and compression. Improper parameter settings can cause significant performance degradation and stability issues. However, regular users and even expert administrators struggle to understand and tune them to achieve good performance. In this tutorial, we review existing approaches on automatic parameter tuning for databases, Hadoop, and Spark, which we classify into six categories: rule-based, cost modeling, simulation-based, experiment-driven, machine learning, and adaptive tuning. We describe the foundations of different automatic parameter tuning algorithms and present pros and cons of each approach. We also highlight real-world applications and systems, and identify research challenges for handling cloud services, resource heterogeneity, and real-time analytics.
A lightweight and efficient temporal database management system in TDSQL
Authors: Lu Wei , Zhao Zhanhao , Wang Xiaoyu , Li Haixiang , Zhang Zhenmiao , Shui Zhiyu , Ye Sheng , Pan Anqun , Du Xiaoyong
Published: September 2019

Driven by the recent adoption of temporal expressions into SQL:2011, extensions of temporal support in conventional database management systems (a.b.a. DBMSs) have re-emerged as a research hotspot. In this paper, we present a lightweight yet efficient built-in temporal implementation in Tencent's distributed database management system, namely TDSQL. The novelty of TDSQL's temporal implementation includes: (1) a new temporal data model with the extension of SQL:2011, (2) a built-in temporal implementation with various optimizations, which are also applicable to other DBMSs, and (3) a low-storage-consumption in which only data changes are maintained. For the repeatability purpose, we elaborate the integration of our proposed techniques into MySQL. We conduct extensive experiments on both real-life dataset and synthetic TPC benchmarks by comparing TD-SQL with other temporal databases. The results show that TDSQL is lightweight and efficient.
DDSketch
Authors: Masson Charles , Rim Jee E. , Lee Homin K.
Published: September 2019

Summary statistics such as the mean and variance are easily maintained for large, distributed data streams, but order statistics (i.e., sample quantiles) can only be approximately summarized. There is extensive literature on maintaining quantile sketches where the emphasis has been on bounding the rank error of the sketch while using little memory. Unfortunately, rank error guarantees do not preclude arbitrarily large relative errors, and this often occurs in practice when the data is heavily skewed.

Given the distributed nature of contemporary large-scale systems, another crucial property for quantile sketches is mergeablility, i.e., several combined sketches must be as accurate as a single sketch of the same data. We present the first fully-mergeable, relative-error quantile sketching algorithm with formal guarantees. The sketch is extremely fast and accurate, and is currently being used by Datadog at a wide-scale.
Adapting TPC-C benchmark to measure performance of multi-document transactions in MongoDB
Authors: Kamsky Asya
Published: September 2019

MongoDB is a popular distributed database that supports replication, horizontal partitioning (sharding), a flexible document schema and ACID guarantees on the document level. While it is generally grouped with "NoSQL" databases, MongoDB provides many features similar to those of traditional RDBMS such as secondary indexes, an ad hoc query language, support for complex aggregations, and new as of version 4.0 multi-statement, multi-document ACID transactions.

We looked for a well understood OLTP workload benchmark to use in our own system performance test suite to establish a baseline of transaction performance to enable flagging performance regressions, as well as improvements as we continue to add new functionality. While there exist many published and widely used benchmarks for RDBMS OLTP workloads, there are none specifically for document databases.

This paper describes the process of adapting an existing traditional RDBMS benchmark to MongoDB query language and transaction semantics to allow measuring transaction performance. We chose to adapt the TPC-C benchmark even though it assumes a relational database schema and SQL, hence extensive changes had to be made to stay consistent with MongoDB best practices. Our goal did not include creating official TPC-C certifiable results, however, every attempt was made to stay consistent with the spirit of the original benchmark specification as well as to be compliant to all specification requirements where possible.

We discovered that following best practices for document schema design achieves better performance than using required normalized schema. All the source code used and validation scripts are published in github to allow the reader to recreate and verify our results.
Blockchain as a solution to the problem of illegal timber trade between Russia and China: SWOT analysis
Authors: VILKOV A. , TIAN G.
Published: September 2019

Prolific illegal timber trade between Russia and China cannot be stemmed by present certification schemes and Russian governmental strategies. Blockchain could present a new technological opportunity, simultaneously addressing illegal logging, regulating timber trade and meeting the
needs of environmentally-sensitive markets. SWOT analysis of blockchain applicability in Russian-Chinese timber trade is presented. Decentralisation based on smart contracts could ensure timber supply chain transparency through each log cryptographic encryption. However, it is considered complicated
as cryptocurrency (on which trade depends) is beyond the legislative sphere of both countries and energy demands are enormous. Beyond cryptocurrency prohibition, huge businesses and governments cannot accept blockchain for international trade because of transparency and cost risks. Digitalisation
through blockchain implementation could provide a highly transparent, non-editable system to handle decentralised big data characteristic of the forestry economy, realise Industry 4.0 and develop the "China-Mongolia-Russia" economic corridor. Fundamentally, a workable Russian-Chinese Government-Science-Business
model must be cultivated for effective blockchain implementation.
The contribution of community forestry to climate change adaptive capacity in tropical dry forests: lessons from Myanmar
Authors: LIN T. , HTUN K.T. , GRITTEN D. , MARTIN A.R.
Published: September 2019

While community forestry (CF) is increasingly promoted as a climate change adaptation strategy, few analyses have examined the contribution of CF to adaptive capacity. We used a sustainable livelihood approach and Ostrom's design principles for managing commons, to assess how CF confers
climate change adaptive capacity in two communities in Myanmar. Our findings indicate that CF provides tangible contributions to human and social capital, by increasing landless and female forest users' knowledge of forest management. However, CF has yet to enhance the physical, financial,
and natural capital within these communities. The major challenges preventing the enhancement of socioeconomic benefits include limited community participation and weak institutional systems for monitoring and conflict resolution. We argue that CF increases community engagement in natural
resource management, but in the absence of effective monitoring and decision-making, socioeconomic benefits to communities from CF programs may be limited. Our results elucidate important factors limiting the uptake and progress of CF as a viable climate change adaptation strategy in Southeast
Asia, and indicate that comparative research is needed to better understand the factors that influence CF efficacy in forest- and natural resource-dependent communities globally.
Solutions with Prescribed Local Blow-up Surface for the Nonlinear Wave Equation
Authors: Cazenave Thierry , Martel Yvan , Zhao Lifeng
Published: September 2019

We prove that any sufficiently differentiable space-like hypersurface ofℝ1+N{{\mathbb{R}}^{1+N}}coincides locally around any of its points with the blow-up surface of a finite-energy solution of the focusing nonlinear wave equation∂t⁢t⁡u-Δ⁢u=|u|p-1⁢u{\partial_{tt}u-\Delta u=|u|^{p-1}u}onℝ×ℝN{{\mathbb{R}}\times{\mathbb{R}}^{N}}, for any1≤N≤4{1\leq N\leq 4}and1<p≤N+2N-2{1<p\leq\frac{N+2}{N-2}}. We follow the strategy developed in our previous work (2018) on the construction of solutions of the nonlinear wave equation blowing up at any prescribed compact set. Here to prove blow-up on a local space-like hypersurface, we first apply a change of variable to reduce the problem to blowup on a small ball att=0{t=0}for a transformed equation. The construction of an appropriate approximate solution is then combined with an energy method for the existence of a solution of the transformed problem that blows up att=0{t=0}. To obtain a finite-energy solution of the original problem from trace arguments, we need to work withH2×H1{H^{2}\times H^{1}}solutions for the transformed problem.
Deconstructing Popular Mythologies about Millennials and Party Identification
Authors: Cluverius John , Dyck Joshua J.
Published: September 2019

Americans born before 1980, called Millennials, are repeatedly treated as a singular voting bloc, but much like the Baby Boomers, have been socialized across a series of very different elections. We develop a theory of millennial political socialization that argues that older Millennials are more tied to the Democratic party and more liberal than their younger counterparts. We use the 2016 Cooperative Congressional Election Study and an original survey of 1274 Americans conducted before the 2016 elections to test this theory. We find some support for our theory; in addition, we find that younger Millennials are socialized by issues of identity politics and culture – specifically on issues of immigration and the role of race in society. This implies a generation that largely favors Democrats, but whose Republicans are more culturally conservative than middle aged Republican voters.
Ab initio theory of the nitrogen-vacancy center in diamond
Authors: Gali Ádám
Published: September 2019

The nitrogen-vacancy (NV) center in diamond is a solid-state defect qubit with favorable coherence time up to room temperature, which could be harnessed in several quantum-enhanced sensor and quantum communication applications, and has a potential in quantum simulation and computing. The quantum control largely depends on the intricate details about the electronic structure and states of the NV center, the radiative and nonradiative rates between these states, and the coupling of these states to external spins, electric, magnetic, and strain fields, and temperature. This review shows how first-principles calculations contributed to understanding the properties of the NV center and briefly discusses the issues to be solved toward the full ab initio description of solid-state defect qubits.
Computational methods for NMR and MS for structure elucidation I: software for basic NMR
Authors: Valli Marilia , Russo Helena Mannochio , Pilon Alan Cesar , Pinto Meri Emili Ferreira , Dias Nathalia B. , Freire Rafael Teixeira , Castro-Gamboa Ian , Bolzani Vanderlan da Silva
Published: September 2019

Structure elucidation is an important and sometimes time-consuming step for natural products research. This step has evolved in the past few years to a faster and more automated process due to the development of several computational programs and analytical techniques. In this paper, the topics of NMR prediction and CASE programs are addressed. Furthermore, the elucidation of natural peptides is discussed.
The Effect of Intraspinal Micro Stimulation With Variable Stimulating Pattern in Adult Rat With Induction of Spinal Cord Injury in the Treatment of Spinal Cord Injuries
Authors: Hedayatzadeh Mohaddeseh , Kobravi Hamid Reza , Tehranipour Maryam
Published: September 2019

Background: Spinal cord injury is one of the diseases that, no specific treatment has yet found despite the variety of works that have done in this field. Different approaches to treat such injuries have investigated today. One of them is invasive intra-spinal interventions such as electrical stimulation. Therefore, in this study, the effect of the protocol for intra-spinal variable and fixed electrical stimulation has been investigated in order to recover from spinal cord injury. Methods: In the study, 18 Wistar male rats randomly divided into Three groups, including intraspinal electrical stimulation (IES), IES with variable pattern of stimulation (VP IES) and a sham group. Animals initially subjected to induced spinal cord injury. After one week, the animal movement was recorded on the treadmill during practice using a camera and angles of the ankle joint were measured using the Tracker software. Then, the obtained data were analyzed by nonlinear evaluations in the phase space. Results: The motion analyses and kinematic analyses were carried out on all groups. According to the achieved results, the gait dynamics of the VP IES group has the most conformity to the gait dynamics of the healthy group. Also, the best quality of the balance preservation observed in the VP IES group. Conclusion: It can be concluded that the IES with variable pattern of stimulation along with exercise therapy has significant gait restorative effects and increases the range of motion in rats with induced spinal cord injury.
Evaluating the Origin of the Brain Metastatic Tumors by Using DWI Parameters
Authors: Mousavi Farnoush , Faeghi Fariborz , Javadian Hamed , Haghighatkhah Hamidreza , Oraee-Yazdani Saeed
Published: September 2019

Background: Brain metastases are the most common tumors in the human central nervous system (CNS), with an occurrence 10 times higher than primary brain tumors in adults. A radiologist usually diagnoses these tumors. Typically, magnetic resonance imaging (MRI) has been used to evaluate the status and number of metastases, the design of surgical treatment or radiotherapy, and the response to treatment. This study aimed to consider the origin of metastatic tumors of the brain using diffusionweighted imaging sequence. Methods: In this study, 95 lesions observed in 51 patients with different types of brain metastasis who analyzed with standard brain MRI protocols such as T2-weighted fast spin-echo in sagittal, coronal and axial planes and T1-weighted spin-echo sequences before and after injection of contrast enhancement and diffusion-weighted imaging. The diffusion-weighted imaging included an echoplanar spin-echo sequence with two b values (0,1000 s/mm) and calculated apparent diffusion coefficient (ADC) maps. We measured the ADC-value on normalized ADC maps and compared them with different methods. ANOVA was used to compare ADC among all groups as well as T-test for every two groups. Results: The results showed that patients with lung cancer (squamous cell carcinoma, SCC) had the lowest mean ADC (658.70*10-3 mm2 /s) and breast cancer patients with the highest mean ADC(935.52*10-3 mm2 /s). This study demonstrated that most Brain metastases had low and intermediate ADC values. The analysis showed no significant difference among all groups. However, ADC values in breast cancer and kidney and lung (adenocarcinoma) were statistically higher in comparison to other groups. There were no critical discrepancies between ADC values in brain metastases from Breast cancer and lung cancer (adenocarcinoma) and kidney. Conclusion: It seems that evaluating the origin of the brain metastatic tumors by using diffusion imaging (DWI) parameters could be helpful to prevent invasive methods like biopsies in some situations. Although it needs more studies to achieve this purpose.
Modeling the Structural Relationship of Happiness Based on Psychological Well-Being With Self-efficacy Intermediation and Academic Self-regulation in University Students
Authors: Iri Yahya , Fakhri Mohammad Kazem , Hassanzadeh Ramazan
Published: September 2019

Background: Happiness is the degree of emotion that a person judges with his overall quality of life as an utterly desirable life. The purpose of this study was to model the structural relationship between happiness based on psychological well-being and self-efficacy and self-regulatory mediation among students at Farhangian University. Methods: This correlation study was carried out using structural equation modeling methods. The statistical population of this study included all undergraduate students at the Farhangian University of Golestan province who were studying in the academic year of 2016-17. By using the Morgan table, 280 people selected through multi-stage random cluster sampling. The data were collected using Savari and Arabzadeh’s educational self-regulatory scale, Sherer Self-efficacy Scale, Oxford Happiness Questionnaire, and Ryff’s psychological well-being questionnaire. Data analysis was performed using path analysis and structural equations with AMOS software. Results: The results showed that psychological well-being had a positive effect on happiness (P<0.02). Also, the pattern fit results showed that psychological well-being indirectly affects selfefficacy, and self-regulation has an indirect effect on happiness (P<0.001). Conclusion: The results of this study showed that there is a significant relationship between happiness and psychological well-being with self-efficacy and self-regulation mediation. Therefore, it is possible to raise the level of happiness and psychological well-being of students through the development of programs aimed at promoting self-efficacy and self-regulation of students.
Functional Reorganization of Local Circuit Connectivity in Superficial Spinal Dorsal Horn with Neuropathic Pain States
Authors: Gong Nian , Hagopian Garo , Holmes Todd C. , Luo Z. David , Xu Xiangmin
Published: September 2019

The spinal dorsal horn is the first relay structure coding for pain transmission and modulation. Previous anatomical and electrophysiological studies have examined spinal dorsal horn circuit connections and network activity. Further work is required to understand spinal cord sensory information processing that underlies pathological neuropathic pain states. Our previous studies suggest that peripheral nerve injury enhances presynaptic excitatory input onto spinal superficial dorsal horn neurons, which in turn contributes to pathologic nociception. The potential changes in local postsynaptic circuits in the dorsal horn that lead to pathologically heightened behavioral responses to pain remain largely unexplored. We combined whole-cell electrophysiological recordings with laser-scanning photostimulation to test whether peripheral nerve injury in the spinal nerve ligation (SNL) mouse model of neuropathic pain leads to alterations in the functional connectivity of spinal cord circuits including lamina II excitatory interneurons. Here we show that SNL enhances excitation and decreases inhibition to lamina II excitatory interneurons along with their increased glutamate-evoked excitability. The enhanced excitatory postsynaptic input and connectivity evoked by SNL eventually return to normal levels concurrently with the resolution of the neuropathic pain states. The physiological pattern highly correlates with mouse pain behaviors following SNL, supporting a neurophysiological mechanism of central sensitization and neuropathic pain that is functionally localized to the spinal dorsal horn. Together, these data support that SNL induces functional changes in synaptic input and connectivity to lamina II excitatory interneurons that code for pain perception, and thus provide new insights into the mechanism and locus of pain hypersensitivity.
Plastic/Animal/Addiction
Authors: Gingrich-Philbrook Craig
Published: September 2019

This essay traces the author's lifelong affection for plastic animals, ultimately describing it as participating in the demotion of animals to playthings and a dangerous contribution to plastic waste.
Development of Biomagz Based on Local Wisdom on Biodiversity Material in High School
Authors: Wahyuningsih Rina , Sukaesih Sri , Peniati Endah
Published: September 2019

This study aims to describe the types of learning resources used previously at SMA N 3 Salatiga, describe the feasibility of Biomagz Based on Local Wisdom, and test the effectiveness of Biomagz Based on Local Wisdom on learning outcomes and student’s environmental care attitude. The method used is research development (R & D). Products are validated by material and media validators, and revised before being tested. Small-scale trials (readability test) use 10 students from class X MIPA 1, while large-scale trials use class X MIPA 2 with the experimental design Pre-experimental Design with the type of Pre-test and Post-test One Group Design. The results of the study show the variety of learning resources used previously including biological, teacher, internet, biology books, and the environment around students. The Feasibility of Biomagz Based on Local Wisdom obtained an average score of 92.21% with very decent criteria. Large-scale trials with an average N-gain value 0.49 in the medium category, the average classical completeness is 85.29%, and the environment care attitude of students is based on the observation result of 92.9% with a high category and the result of the inter-student assessment is 86, 18% with a high category. Based on the results of this study, it can be concluded that Biomagz Based Local Wisdom is well worth and effective on learning outcomes and student’s environmental care attitude.
The Effectiveness of Blended Learning Implementation in Ecological Chapters Judging from the Understanding of Students' Concepts
Authors: Pitaloka Elok Dyah , Suyanto Slamet
Published: September 2019

The use of technology in the process of learning activities can create a new atmosphere in biology learning, namely direct learning and learning using quipper school online. Learning like this is known as blended learning. The class used for the study was taken through cluster random sampling technique namely X MIPA 2 (experimental class) which implements blended learning and X MIPA 3 (control class) which implements a scientific approach. The implementation of blended learning on the topic of ecology is expected to be effective towards understanding concepts. Blended learning is effective on understanding concepts in ecological discussion because they fulfill three indicators, namely: (1) the average posttest of the experimental class 74.95> the mean posttest of the control class is 64.98, (2) The value of understanding the concepts to the two classes shows a significant difference with the values significance of 0,000<0,05, (3) Mean value of N-Gain experimental class 0.52> N-Gain mean value of control class 0.32. Thus, the implementation of blended learning in the ecology chapter in terms of understanding the concept is said to be effective.
Limits to Genomic Divergence Under Sexually Antagonistic Selection
Authors: Kasimatis Katja R , Ralph Peter L , Phillips Patrick C
Published: September 2019

Since the autosomal genome is shared between the sexes, sex-specific fitness optima present an evolutionary challenge. While sexually antagonistic selection might favor different alleles within females and males, segregation randomly reassorts alleles at autosomal loci between sexes each generation. This process of homogenization during transmission thus prevents between-sex allelic divergence generated by sexually antagonistic selection from accumulating across multiple generations. However, recent empirical studies have reported high male-female FST statistics. Here, we use a population genetic model to evaluate whether these observations could plausibly be produced by sexually antagonistic selection. To do this, we use both a single-locus model with nonrandom mate choice, and individual-based simulations to study the relationship between strength of selection, degree of between-sex divergence, and the associated genetic load. We show that selection must be exceptionally strong to create measurable divergence between the sexes and that the decrease in population fitness due to this process is correspondingly high. Individual-based simulations with selection genome-wide recapitulate these patterns and indicate that small sample sizes and sampling variance can easily generate substantial male-female divergence. We therefore conclude that caution should be taken when interpreting autosomal allelic differentiation between the sexes.
Effects of pressure work on natural convection flow around a sphere with radiation heat loss
Authors: Akhter T. , Alim M. A. A.
Published: September 2019

The effects of pressure work with radiation heat loss on natural convection flow on a sphere have been investigated in this paper. The governing boundary layer equations are first transformed into a non-dimensional form and the resulting nonlinear partial differential equations are then solved numerically using finite-difference method with Keller-box scheme. We have focused our attention on the evaluation of shear stress in terms of local skin friction and rate of heat transfer in terms of local Nusselt number, velocity as well as temperature profiles. Numerical results have been shown graphically and tabular form for some selected values of parameters set consisting of radiation parameter Rd, pressure work parameter Ge, surface temperature parameter θw and the Prandtl number Pr.
Stability analysis in a delayed SIR epidemic model with a saturated incidence rate
Authors: Kaddar A.
Published: September 2019

We formulate a delayed SIR epidemic model by introducing a latent period into susceptible, and infectious individuals in incidence rate. This new reformulation provides a reasonable role of incubation period on the dynamics of SIR epidemic model. We show that if the basic reproduction number, denoted, R0, is less than unity, the diseasefree equilibrium is locally asymptotically stable. Moreover, we prove that if R0 > 1, the endemic equilibrium is locally asymptotically stable. In the end some numerical simulations are given to compare our model with existing model.
Asymptotic solution of the mathematical model of nonlinear oscillations of absolutely elastic inextensible weightless string
Authors: Krylovas A. , Lavcel-Budko O. , Miškinis P.
Published: September 2019

The mathematical model of nonlinear oscillations of weightless string is analyzed. To find an asymptotic solution of the problem, uniformly valid in a long interval of time, an averaged system of integral differential equations has been constructed. A method for constructing special approximations of its solutions is proposed.
Existence results for a class of (p,q) Laplacian systems
Authors: Afrouzi G. A. A. , Mirzapour M.
Published: September 2019

We establish the existence of a nontrivial solution for inhomogeneous quasilinear elliptic systems:−∆pu = λ a(x) u |u|γ−2 + α (α + β)–1 b(x) u |u|α−2 |v|β + f    in Ω,−∆qv = µ d(x) v |v|γ−2 + β (α + β)–1 b(x) |u|α v |v|β−2 + g    in Ω,(u,v) ∈ W01,p(Ω) × W01,q(Ω).Our result depending on the local minimization.