bluuebunny/crossref_metadata_2025 huggingface dataset:
PriSTE
Authors: Cao Yang , Xiao Yonghui , Xiong Li , Bai Liquan , Yoshikawa Masatoshi
Published: September 2019

Location privacy-preserving mechanisms (LPPMs) have been extensively studied for protecting a user's location in location-based services. However, when user's perturbed locations are released continuously, existing LPPMs may not protect users' sensitive
spatiotemporal event
, such as "visited hospital in the last week" or "regularly commuting between location 1 and location 2 every morning and afternoon" (it is easy to infer that locations 1 and 2 may be home and office). In this demonstration, we demonstrate PriSTE for protecting spatiotemporal event privacy in continuous location release. First, to raise users' awareness of such a new privacy goal, we design an interactive tool to demonstrate how accurate an adversary could infer a secret spatiotemporal event from a sequence of locations or even LPPM-protected locations. The attendees can find that some spatiotemporal events are quite risky and even these state-of-the-art LPPMs do not always protect spatiotemporal event privacy. Second, we demonstrate how a user can use PriSTE to automatically or manually convert an LPPM for location privacy into one protecting spatiotemporal event privacy in continuous location-based services. Finally, we visualize the trade-off between privacy and utility so that users can choose appropriate privacy parameters in different application scenarios.
DISPERS
Authors: Loudet Julien , Sandu-Popa Iulian , Bouganim Luc
Published: September 2019

Personal Data Management Systems (PDMS) advance at a rapid pace allowing us to integrate all our personal data in a single place and use it for our benefit and for the benefit of the community. This leads to a significant paradigm shift since personal data become massively distributed and opens an important question: how to query this massively distributed data in an efficient, pertinent and privacy preserving way? This demonstration proposes a fully-distributed PDMS called DISPERS, built on top of SEP2P, allowing users to securely and efficiently share and query their personal data. The demonstration platform graphically illustrates the query execution in details, showing that DISPERS leads to maximal system security with low and scalable overhead. Attendees are welcome to challenge the security provided by DISPERS using the proposed hacking tools.
ApproxML
Authors: Hasani Sona , Ghaderi Faezeh , Hasan Shohedul , Thirumuruganathan Saravanan , Asudeh Abolfazl , Koudas Nick , Das Gautam
Published: September 2019

Machine learning (ML) has gained a pivotal role in answering complex predictive analytic queries. Model building for large scale datasets is one of the time consuming parts of the data science pipeline. Often data scientists are willing to sacrifice some accuracy in order to speed up this process during the exploratory phase. In this paper, we propose to demonstrate ApproxML, a system that efficiently constructs approximate ML models for new queries from previously constructed ML models using the concepts of
model materialization
and
reuse
. ApproxML supports a variety of ML models such as generalized linear models for supervised learning, and K-means and Gaussian Mixture model for unsupervised learning.
FishStore
Authors: Chandramouli Badrish , Xie Dong , Li Yinan , Kossmann Donald
Published: September 2019

The last decade has witnessed a huge increase in data being ingested into the cloud from a variety of data sources. The ingested data takes various forms such as JSON, CSV, and binary formats. Traditionally, data is either ingested into storage in raw form, indexed ad-hoc using range indices, or cooked into analytics-friendly columnar formats. None of these solutions is able to handle modern requirements on storage: making the data available immediately for ad-hoc and streaming queries while ingesting at extremely high throughputs. We demonstrate FishStore, our open-source concurrent latch-free storage layer for data with flexible schema. FishStore builds on recent advances in parsing and indexing techniques, and is based on multi-chain hash indexing of dynamically registered
predicated subsets
of data. We find predicated subset hashing to be a powerful primitive that supports a broad range of queries on ingested data and admits a higher performance (by up to an order of magnitude) implementation than current alternatives.
GRANO
Authors: Wang Hanzhang , Nguyen Phuong , Li Jun , Kopru Selcuk , Zhang Gene , Katariya Sanjeev , Ben-Romdhane Sami
Published: September 2019

We demonstrate Grano
1
, an end-to-end anomaly detection and root cause analysis (or RCA for short) system for cloud-native distributed data platform by providing a holistic view of the system component topology, alarms and application events. Grano provides: a
Detection Layer
to process large amount of time-series monitoring data to detect anomalies at logical and physical system components; an
Anomaly Graph Layer
with novel graph modeling and algorithms for leveraging system topology data and detection results to identify the root cause relevance at the system component level; and an
Application Layer
that automatically notifies on-call personnel and presents real-time and on-demand RCA support through an interactive graph interface. The system is deployed and evaluated using eBay's production data to help on-call personnel to shorten the identification of root cause from hours to minutes.
Tuplex
Authors: Spiegelberg Leonhard F. , Kraska Tim
Published: September 2019

Spark became the defacto industry standard as an execution engine for data preparation, cleaning, distributed machine learning, streaming and, warehousing over raw data. However, with the success of Python the landscape is shifting again; there is a strong demand for tools which better integrate with the Python landscape and do not have the impedance mismatch like Spark. In this paper, we demonstrate
Tuplex
(short for
tuples
and
exceptions
), a Python-native data preparation framework that allows users to develop and deploy pipelines faster and more robustly while providing bare-metal execution times through code compilation whenever possible.
Machine learning meets big spatial data
Authors: Sabek Ibrahim , Mokbel Mohamed F.
Published: September 2019

The proliferation in amounts of generated data has propelled the rise of scalable machine learning solutions to efficiently analyze and extract useful insights from such data. Meanwhile, spatial data has become ubiquitous, e.g., GPS data, with increasingly sheer sizes in recent years. The applications of big spatial data span a wide spectrum of interests including tracking infectious disease, climate change simulation, drug addiction, among others. Consequently, major research efforts are exerted to support efficient analysis and intelligence inside these applications by either providing spatial extensions to existing machine learning solutions or building new solutions from scratch. In this 90-minutes tutorial, we comprehensively review the state-of-the-art work in the intersection of machine learning and big spatial data. We cover existing research efforts and challenges in three major areas of machine learning, namely, data analysis, deep learning and statistical inference, as well as two advanced spatial machine learning tasks, namely, spatial features extraction and spatial sampling. We also highlight open problems and challenges for future research in this area.
Combating fake news
Authors: Lakshmanan Laks V. S. , Simpson Michael , Thirumuruganathan Saravanan
Published: September 2019

Fake news is a major threat to global democracy resulting in diminished trust in government, journalism and civil society. The public popularity of social media and social networks has caused a contagion of fake news where conspiracy theories, disinformation and extreme views flourish. Detection and mitigation of fake news is one of the fundamental problems of our times and has attracted widespread attention. While fact checking websites such as snopes, politifact and major companies such as Google, Facebook, and Twitter have taken preliminary steps towards addressing fake news, much more remains to be done. As an interdisciplinary topic, various facets of fake news have been studied by communities as diverse as machine learning, databases, journalism, political science and many more.

The objective of this tutorial is two-fold. First, we wish to familiarize the database community with the efforts by other communities on combating fake news. We provide a panoramic view of the state-of-the-art of research on various aspects including detection, propagation, mitigation, and intervention of fake news. Next, we provide a concise and intuitive summary of prior research by the database community and discuss how it could be used to counteract fake news. The tutorial covers research from areas such as data integration, truth discovery and fusion, probabilistic databases, knowledge graphs and crowdsourcing from the lens of fake news. Effective tools for addressing fake news could only be built by leveraging the synergistic relationship between database and other research communities. We hope that our tutorial provides an impetus towards such synthesis of ideas and the creation of new ones.
Personal database security and trusted execution environments
Authors: Anciaux Nicolas , Bouganim Luc , Pucheral Philippe , Popa lulian Sandu , Scerri Guillaume
Published: September 2019

Smart disclosure initiatives and new regulations such as GDPR in the EU increase the interest for Personal Data Management Systems (PDMS) being provided to individuals to preserve their entire digital life. Consequently, the thorny issue of data security becomes more and more prominent, but highly differs from traditional privacy issues in outsourced corporate databases. Concurrently, the emergence of Trusted Execution Environments (TEE) changes the game in privacy-preserving data management with novel security models. This tutorial offers a global perspective of the current state of work at the confluence of these two rapidly growing areas. The goal is threefold: (1) review and categorize PDMS solutions and identify existing privacy threats and countermeasures; (2) review new security models capitalizing on TEEs and related privacy-preserving data management solutions relevant to the personal context; (3) discuss new challenges at the intersection of PDMS security and TEE-based data management.
SAP HANA goes private
Authors: Kessler Stephan , Hoff Jens , Freytag Johann-Christoph
Published: September 2019

Over the last 20 years, the progress of information technology has allowed many companies to generate, integrate, store, and analyze data of unprecedented size and complexity. In many cases, this data is personal data and how it can be used is therefore subject to laws that depend on the specific countries and application domains. For example, the General Data Protection Regulation (GDPR) introduced in the European Union imposes strict rules on how personal data can be processed.

Analyzing personal data can create tremendous value, but at the same time companies must ensure that they remain legally compliant. Unfortunately, existing systems offer only limited or no support at all for processing personal data in a
privacy-aware
manner. Approaches that have emerged from the academic and industrial research environments need to be integrated into large systems (like enterprise systems) in a manageable and scalable way. In many IT environments, it is also desirable and necessary to combine and to integrate personal data with other (non-personal) data in a seamless fashion.

In this paper, we present the first steps that SAP has taken to provide its database management system SAP HANA with privacy-enhanced processing capabilities, referred to in the following as SAP HANA Data Anonymization. Various goals on both the conceptual and technical levels were followed with the aim of providing SAP customers
today
with an
integrated
processing environment for personal and non-personal data.
Experiences with approximating queries in Microsoft's production big-data clusters
Authors: Kandula Srikanth , Lee Kukjin , Chaudhuri Surajit , Friedman Marc
Published: September 2019

With the rapidly growing volume of data, it is more attractive than ever to leverage approximations to answer analytic queries. Sampling is a powerful technique which has been studied extensively from the point of view of facilitating approximation. Yet, there has been no large-scale study of effectiveness of sampling techniques in big data systems. In this paper, we describe an in-depth study of the sampling-based approximation techniques that we have deployed in Microsoft's big data clusters. We explain the choices we made to implement approximation, identify the usage cases, and study detailed data that sheds insight on the usefulness of doing sampling based approximation.
Constant time recovery in Azure SQL database
Authors: Antonopoulos Panagiotis , Byrne Peter , Chen Wayne , Diaconu Cristian , Kodandaramaih Raghavendra Thallam , Kodavalla Hanuma , Purnananda Prashanth , Radu Adrian-Leonard , Ravella Chaitanya Sreenivas , Venkataramanappa Girish Mittur
Published: September 2019

Azure SQL Database and the upcoming release of SQL Server introduce a novel database recovery mechanism that combines traditional ARIES recovery with multi-version concurrency control to achieve database recovery in constant time, regardless of the size of user transactions. Additionally, our algorithm enables continuous transaction log truncation, even in the presence of long running transactions, thereby allowing large data modifications using only a small, constant amount of log space. These capabilities are particularly important for any Cloud database service given a) the constantly increasing database sizes, b) the frequent failures of commodity hardware, c) the strict availability requirements of modern, global applications and d) the fact that software upgrades and other maintenance tasks are managed by the Cloud platform, introducing unexpected failures for the users. This paper describes the design of our recovery algorithm and demonstrates how it allowed us to improve the availability of Azure SQL Database by guaranteeing consistent recovery times of under 3 minutes for 99.999% of recovery cases in production.
A morsel-driven query execution engine for heterogeneous multi-cores
Authors: Dursun Kayhan , Binnig Carsten , Cetintemel Ugur , Swart Garret , Gong Weiwei
Published: September 2019

Currently, we face the next major shift in processor designs that arose from the physical limitations known as the "dark silicon effect". Due to thermal limitations and shrinking transistor sizes, multi-core scaling is coming to an end. A major new direction that hardware vendors are currently investigating involves specialized and energy-efficient hardware accelerators (e.g., ASICs) placed on the same die as the normal CPU cores.

In this paper, we present a novel query processing engine called
SiliconDB
that targets such heterogeneous processor environments. We leverage the Sparc M7 platform to develop and test our ideas. Based on the SSB benchmarks, as well as other micro benchmarks, we compare the efficiency of
SiliconDB
with existing execution strategies that make use of co-processors (e.g., FPGAs, GPUs) and demonstrate speed-up improvements of up to 2x.
Smile
Authors: Cao Lei , Tao Wenbo , An Sungtae , Jin Jing , Yan Yizhou , Liu Xiaoyu , Ge Wendong , Sah Adam , Battle Leilani , Sun Jimeng , Chang Remco , Westover Brandon , Madden Samuel , Stonebraker Michael
Published: September 2019

In order to reduce the possibility of neural injury from seizures and sidestep the need for a neurologist to spend hours on manually reviewing the EEG recording, it is critical to automatically detect and classify "interictal-ictal continuum" (IIC) patterns from EEG data. However, the existing IIC classification techniques are shown to be not accurate and robust enough for clinical use because of the lack of high quality labels of EEG segments as training data. Obtaining high-quality labeled data is traditionally a manual process by trained clinicians that can be tedious, time-consuming, and error-prone. In this work, we propose Smile, an industrial scale system that provides an end-to-end solution to the IIC pattern classification problem. The core components of Smile include a visualization-based time series labeling module and a deep-learning based active learning module. The labeling module enables the users to explore and label 350 million EEG segments (30TB) at interactive speed. The multiple coordinated views allow the users to examine the EEG signals from both time domain and frequency domain simultaneously. The active learning module first trains a deep neural network that automatically extracts both the local features with respect to each segment itself and the long term dynamics of the EEG signals to classify IIC patterns. Then leveraging the output of the deep learning model, the EEG segments that can best improve the model are selected and prompted to clinicians to label. This process is iterated until the clinicians and the models show high degree of agreement. Our initial experimental results show that our Smile system allows the clinicians to label the EEG segments at will with a response time below 500 ms. The accuracy of the model is progressively improved as more and more high quality labels are acquired over time.
Access to information and local democracies: a case study of REDD+ and FLEGT/VPA in Cameroon
Authors: CARODENUTO S.
Published: September 2019

As technological advancements in forest monitoring – such as remote sensing and commodity supply chain tracking – allow for the generation and analysis of increasingly large datasets, forest policy makers and practitioners are looking for innovative yet practical ways for
information transparency to transform forest governance. Especially in tropical forest countries looking to address the continuing deforestation and forest degradation through climate finance commitments and timber trade agreements, the access to information agenda has been placed at the fore
of both the Reducing Emissions from Deforestation and forest Degradation (REDD+) process and the Forest Law Enforcement, Governance and Trade (FLEGT) Action Plan. This paper explores whether and how the proposed transparency agenda is having an impact (or not) in the Southwest Region of Cameroon.
Using semi-structured interviews with civil society organizations, this paper examines how information is currently disclosed in the forest sector and the status of REDD+ and FLEGT transparency agendas at the local level.
Why do logging companies adopt or reject forest certification in the Congo basin? Insights from Cameroon
Authors: NDOUMBE BEROCK I. , ONGOLO S.
Published: September 2019

This study aims to understand, through the example of Cameroon, why industrial logging companies adopt or avoid sustainable certification or labelling systems of their forest operations in the Congo Basin region. From a methodological standpoint, the research is based on a sample of
three empirical case studies of logging companies operating in Cameroon: an 'anti-certification' company (the model, due to the majority trend of non-certified logging companies in this region), a company in the process of certification (the intermediate case), and a certified company (the
marginal case, due to the scarcity of certified companies in the study area). While focusing on these three cases, we chose to avoid reifying the dominant case of anti-certification companies. Hence the choice of highlighting this majority trend by carrying out a comparative study with an
intermediate and a marginal case. The analysis of these three case studies reveals that the high cost of long term certification, the risks of patronage and cronyism in Patron-Client (customer-provider/boss) relationships that feature sustainable labelling processes are the main reasons for
the low level of commitment of logging companies to forest certification in Cameroon. At the end of the research, we recommend that other complementary and more specific research should focus on the flaws in patron-client relationships that characterize forest certification processes on the
one hand, and on the necessary conditions to avoid patronage and cronyisms risks or excesses in these relations on the other hand, especially in a poor governance context like Cameroon. Similarly, we encourage that new research be carried out to better understand whether and how transaction
and opportunity costs influence the decisions of industrial logging companies in favour of or against forest certification.
Hardy–Sobolev inequality with higher dimensional singularity
Authors: Thiam El Hadji Abdoulaye
Published: September 2019

For

N
≥
4

{N\geq 4}

, we let Ω be a smooth bounded domain of

ℝ
N

{\mathbb{R}^{N}}

, Γ a smooth closed submanifold of Ω of dimension k, with

1
≤
k
≤

N
-
2

{1\leq k\leq N-2}

, and h a continuous function defined on Ω.
We denote by

ρ
Γ

⁢

(
⋅
)

:=

dist
⁡

(
⋅
,
Γ
)

{\rho_{\Gamma}(\,\cdot\,):=\operatorname{dist}(\,\cdot\,,\Gamma)}

the distance function to Γ. For

σ
∈

(
0
,
2
)

{\sigma\in(0,2)}

, we study the existence of positive solutions

u
∈

H
0
1

⁢

(
Ω
)

{u\in H^{1}_{0}(\Omega)}

to the nonlinear equation

-

Δ
⁢
u

+

h
⁢
u

=

ρ
Γ

-
σ

⁢

u

2
*

⁢

(
σ
)

-
1

 

in 
⁢
Ω

,

-\Delta u+hu=\rho_{\Gamma}^{-\sigma}u^{2^{*}(\sigma)-1}\quad\text{in }\Omega,

where

2
*

⁢

(
σ
)

:=

2
⁢

(

N
-
σ

)

N
-
2

{2^{*}(\sigma):=\frac{2(N-\sigma)}{N-2}}

is the critical Hardy–Sobolev exponent. In particular, we prove the existence of solution under the influence of the local geometry of Γ and the potential h.
A Reduced Crouzeix–Raviart Immersed Finite Element Method for Elasticity Problems with Interfaces
Authors: Jo Gwanghyun , Kwak Do Young
Published: September 2019

The purpose of this paper is to develop a reduced Crouzeix–Raviart immersed finite element method (RCRIFEM) for two-dimensional elasticity problems with interface, which is based on the Kouhia–Stenberg finite element method (Kouhia et al. 1995) and Crouzeix–Raviart IFEM (CRIFEM) (Kwak et al. 2017).
We use a

P
1

{P_{1}}

-conforming like element for one of the components of the displacement vector, and a

P
1

{P_{1}}

-nonconforming like element for the other component.
The number of degrees of freedom of our scheme is reduced to two thirds of CRIFEM.
Furthermore, we can choose penalty parameters independent of the Poisson ratio.
One of the penalty parameters depends on Lamé’s second constant μ, and the other penalty parameter is independent of both μ and λ.
We prove the optimal order error estimates in piecewise

H
1

{H^{1}}

-norm, which is independent of the Poisson ratio.
Numerical experiments show optimal order of convergence both in

L
2

{L^{2}}

and piecewise

H
1

{H^{1}}

-norms for all problems including nearly incompressible cases.
Moral Foundations, System Justification, and Support for Trump in the 2016 Presidential Election
Authors: Weinschenk Aaron C. , Dawes Christopher T.
Published: September 2019

We examine the role of moral foundations and system justification in explaining support for Donald Trump in the 2016 general election using data from the 2016 Cooperative Congressional Election Survey. A number of important findings emerge. First, we find that there are important partisan and ideological differences when it comes to moral foundations and system justification. Second, we find that moral foundations predict support for Trump above and beyond traditional determinants of vote choice such as ideology, partisanship, religiosity, and demographic characteristics. Third, we find that a measure of political system justification is not related to vote choice in our sample. This casts doubt on the idea that support for Trump was mostly about protesting the political system. This paper adds to the growing body of research showing that psychological concepts and theories are important in understanding voter decision-making in the 2016 presidential election and in elections more generally.
High-risk behaviors and demographic features: a cross-sectional study among Iranian adolescents
Authors: Ghahremani Leila , Nazari Mahin , Changizi Maryam , Kaveh Mohamad Hossein
Published: September 2019

Background and objectives

High-risk behaviors are considered to be a serious threat among adolescents. This study aimed to investigate the frequency of unhealthy and high-risk behaviors and their relationship with demographic features in adolescents living in Shiraz, Iran.

Materials and methods

The present descriptive, cross-sectional study was conducted on 483 students in the 10th grade of high school. The data were collected using a demographic information form and a modified adolescents high-risk behaviors questionnaire. The reliability of the questionnaire was assessed using the test-retest method. Afterwards, the data were entered into the SPSS statistical software (IBM), version 22 and were analyzed using the chi-square (χ2) test, logistic regression analysis and one-way analysis of variance (ANOVA).

Results

High-risk health behaviors were significantly correlated to adolescents’ gender, parents’ occupations and education levels, length of residency in Shiraz and talking about important things with one’s parents (p < 0.03). Gender predicted 52% of variance of bullying behaviors at school [Exp(B) = 0.502, p < 0.03, 95% confidence interval (CI) = 0.261–0.996]. In fact, most high-risk behaviors were associated with gender (p < 0.001). Indeed, bullying was mostly reported in boys, while being hopeless or sad, suicide attempts and appropriate weight loss behaviors were mostly reported among girls. Additionally, the frequency of smoking cigarettes and using hookahs was higher among girls compared to boys (23.1% for smoking cigarettes and 39.6% for using hookahs). However, no significant correlation was observed between gender and smoking cigarettes and using hookahs (p > 0.704 for smoking cigarettes and p > 0.118 for using hookahs). The most prevalent high-risk behaviors were physical fighting (51.1%), being sad or hopeless (35.2%), alcohol abuse (26.7%), overweight (14.7%) and obesity (8.1%) in both genders. Based on the results, only 26.5% of the adolescents had sufficient physical activity. Besides, the adolescents’ weight scores were significantly correlated to eating green salads (p < 0.01), which was seen more among overweight adolescents.

Conclusion

The findings indicated that adolescents’ gender and their parents’ roles should be taken into consideration in designing health promotion programs, such as mental health and its related skills. This would eventually result in the prevention and reduction of unhealthy habits.
Catalytic Combustion of Chlorobenzene with VOx/CeO2 Catalysts： Influence of Catalyst Synthesis Method
Authors: Shi Qi , Long Hong-ming , Chun Tie-jun , Gao Zhi-fang
Published: September 2019

VOx/CeO2 catalysts with various nanostructure were synthesized by the hydrothermal method and used in catalytic combustion of chlorobenzene (CB) at a low temperature. XRD, BET, TEM, Raman, XPS, and H2-TPR were employed to reveal that catalysts VOx on CeO2 support had considerable activity for CB combustion. VOx/CeO2 catalysts prepared with ammonium to adjust pH value and added P123 as a surfactant, showed the highest CB conversion ratio of 60 % at 250 °C and 100 % at 400 °C. It showed that preparation method could infect the shape evolution and surface species during the synthesis. The new phase CeVO4 formed in VOx/CeO2 catalysts improved the catalysts efficiency by increasing oxygen vacancies.
Crocin treatment decreased pancreatic atrophy, LOX-1 and RAGE mRNA expression of pancreas tissue in cholesterol-fed and streptozotocin-induced diabetic rats
Authors: Bayatpoor Mohammad Ehsan , Mirzaee Saeed , Karami Abd Mohammad , Mohammadi Mohammad Taghi , Shahyad Shima , Bahari Zahra , Raouf Sarshoori Javad
Published: September 2019

Objective

Oxidative stress in diabetic mellitus is a consequence of oxidative stress, which plays a critical role in the pathogenesis of diabetic tissue damage. Receptors for advanced glycation end products and for oxidized low-density lipoproteins (LDL) have critical contribution in oxidative tissue damage. The present study investigated whether anti-diabetic effects of Crocin via modulation of mRNA expression of RAGE and LOX-1 receptors in diabetic rats.

Methods

In the current study, high-fat cholesterol (HFC) and streptozotocin (40 mg/kg) used to induce type II diabetes. Experimental groups as follows: (Group 1: control); (Group 2: control treatment [Crocin]); (Group 3: DM [STZ]); (Group 4: DM treatment [STZ + Crocin]); (Group 5; DM + HFC [STZ + HFC]); (Group 6; DM + HFC treatment [STZ + HFC + Crocin]). Crocin (20 mg/kg/day, i.p.) administered in treatment groups for 60 days. Serum glucose and cholesterol levels evaluated on days 5, 30 and 60 after induction of DM. Pancreatic tissue from all group removed on day 60 for histological and RT-PCR analysis.

Results

Application of Crocin significantly decreased serum cholesterol levels on day 60 after induction of DM in diabetic + HFC rats. Moreover, Crocin significantly decreased serum glucose levels on days 30 and 60 both in diabetic and diabetic + HFC rats. Crocin partially prevented the atrophic effects of STZ on both exocrine and endocrine parts of pancreas. Additionally, Crocin significantly decreased LOX-1 and RAGE mRNA expression OF pancreas in diabetic rats.

Conclusion

The current study suggested that Crocin suppressed atrophic change of the pancreas by decrease of LOX-1 and RAGE mRNA expression in diabetic rats.
A Sound-Sensitive Source of Alpha Oscillations in Human Non-Primary Auditory Cortex
Authors: Billig Alexander J. , Herrmann Björn , Rhone Ariane E. , Gander Phillip E. , Nourski Kirill V. , Snoad Beau F. , Kovach Christopher K. , Kawasaki Hiroto , Howard Matthew A. , Johnsrude Ingrid S.
Published: September 2019

The functional organization of human auditory cortex can be probed by characterizing responses to various classes of sound at different anatomical locations. Along with histological studies this approach has revealed a primary field in posteromedial Heschl's gyrus (HG) with pronounced induced high-frequency (70–150 Hz) activity and short-latency responses that phase-lock to rapid transient sounds. Low-frequency neural oscillations are also relevant to stimulus processing and information flow, however, their distribution within auditory cortex has not been established. Alpha activity (7–14 Hz) in particular has been associated with processes that may differentially engage earlier versus later levels of the cortical hierarchy, including functional inhibition and the communication of sensory predictions. These theories derive largely from the study of occipitoparietal sources readily detectable in scalp electroencephalography. To characterize the anatomical basis and functional significance of less accessible temporal-lobe alpha activity we analyzed responses to sentences in seven human adults (4 female) with epilepsy who had been implanted with electrodes in superior temporal cortex. In contrast to primary cortex in posteromedial HG, a non-primary field in anterolateral HG was characterized by high spontaneous alpha activity that was strongly suppressed during auditory stimulation. Alpha-power suppression decreased with distance from anterolateral HG throughout superior temporal cortex, and was more pronounced for clear compared to degraded speech. This suppression could not be accounted for solely by a change in the slope of the power spectrum. The differential manifestation and stimulus-sensitivity of alpha oscillations across auditory fields should be accounted for in theories of their generation and function.

SIGNIFICANCE STATEMENTTo understand how auditory cortex is organized in support of perception, we recorded from patients implanted with electrodes for clinical reasons. This allowed measurement of activity in brain regions at different levels of sensory processing. Oscillations in the alpha range (7–14 Hz) have been associated with functions including sensory prediction and inhibition of regions handling irrelevant information, but their distribution within auditory cortex is not known. A key finding was that these oscillations dominated in one particular non-primary field, anterolateral Heschl's gyrus, and were suppressed when subjects listened to sentences. These results build on our knowledge of the functional organization of auditory cortex and provide anatomical constraints on theories of the generation and function of alpha oscillations.
Transformation or Assimilation? Examining Identity and Organizational Tensions at Full Figured Fashion Week
Authors: Cox Joy , Gailliard Bernadette M. , Davis Shardé M.
Published: September 2019

Full Figured Fashion Week (FFFWeek) is a week-long event envisioned to be a countervailing force that challenges traditional body standards in the US fashion industry, showcasing plus-sized models and offering a safe space for fat bodies to commune and patronize plus size vendors. However, two years of participant observations with a critical lens has revealed how FFFWeek employed organizational decisions that demonstrate the complicated context of fashion and fatness, along with the ongoing struggle between body positive and fat accepting discourses, and the inner workings of capitalism and hegemony as an attempt to create social change.
Double-Sided Tape
Authors: Murray Fiona Alana
Published: September 2019

This essay brings together Amazon, consumer reviews, a science project, and ordinary objects in order to examine how affect works between and within them, both sticking them together and tearing them apart. This is a sticky tale with a speedy delivery.
Validity of Learning Media Based on Diamond Touch Cardboard with Think Pair Share Model and Student Respons On Excretory System Material
Authors: Khumaeroh Mega Siti , Ratnasari Jujun , Ramdhan Billyardi
Published: September 2019

This study aims to reseach and develop the use of Diamond Touch media with think Pair share models. The research held at Pondok Modern Assalam Putri, Sukabumi with 31 student. The feasibility of the media used and evaluated by media expert and small-scale trials, Diamond touch is a medium that can be used as a medium to achieve goals material in learning Biology, formal and non-formal education. The elements contained in Diamond Touch media are (1) learning messages or core material (2) cardboard tools for learning aids. The results of this study that Diamond touch media can be integrated with learning models namely Think Pair Share so that the learning process is not boring and Diamond touch media is very valid for use in learning. Analysis of validity test data obtained through questionnaires was performed using quantitative data processing formulas
The Implementation of High School Remedial Program on Regulation System Material in Palu City Based on School Status and Teachers’ Education Background
Authors: P Fildayana , Djukri P
Published: September 2019

This research aims to describe the implementation of a high school remedial program on regulation system materials in Palu City based on school status and teacher’s educational background. This research is descriptive research with a mono variable using the survey method. The subject of this research was biology teacher class XI and class XI students who followed the improvement program on system registration material. The variable of this research is qualitative descriptive research. The subject of this research was biology teacher class XI and class XI students who followed the improvement program on system registration material. Data collection techniques using observation, interview, and documentation techniques. Data analysis techniques add data reduction, data presentation, and verification. The validity of lottery data by technical triangulation and source triangulation. Data collection uses Human Instruments, interview guidelines for teachers, and interview guidelines for the student. The data were analyzed using the component analysis technique based on Miles and Huberman. The research result indicated that the implementation of the remedial program on regulation system materials at a public high school in Palu city is better than that of private high school. However, the implementation by teachers whose education background is educational is better than that of those whose educational background is non-educational.
Broad Promotes Neuroepithelial Stem Cell Differentiation in the Drosophila Optic Lobe
Authors: Zhou Yanna , Yang Yuqin , Huang Yanyi , Wang Hui , Wang Shengyu , Luo Hong
Published: September 2019

Brain development requires the generation of the right number, and type, of neurons and glial cells at the right time. The Drosophila optic lobe, like mammalian brains, develops from simple neuroepithelia; they first divide symmetrically to expand the progenitor pool and then differentiate into neuroblasts, which divide asymmetrically to generate neurons and glial cells. Here, we investigate the mechanisms that control neuroepithelial growth and differentiation in the optic lobe. We find that the Broad/Tramtrack/Bric a brac-zinc finger protein Broad, which is dynamically expressed in the optic lobe neuroepithelia, promotes the transition of neuroepithelial cells to medulla neuroblasts. Loss of Broad function causes neuroepithelial cells to remain highly proliferative and delays neuroepithelial cell differentiation into neuroblasts, which leads to defective lamina and medulla. Conversely, Broad overexpression induces neuroepithelial cells to prematurely transform into medulla neuroblasts. We find that the ecdysone receptor is required for neuroepithelial maintenance and growth, and that Broad expression in neuroepithelial cells is repressed by the ecdysone receptor. Our studies identify Broad as an important cell-intrinsic transcription factor that promotes the neuroepithelial-cell-to-neuroblast transition.
The effect of environmental tax on the survival of biological species in a polluted environment: a mathematical model
Authors: Agarwal S. , Devi S.
Published: September 2019

In this paper, a nonlinear mathematical model is proposed and analyzed for the survival of biological species affected by a pollutant present in the environment. It is considered that the emission of the pollutant into the environment is dynamic in nature and depends on the environmental tax imposed on the emitters. It is also assumed that the environmental tax is imposed to control the emission of pollutants only when the concentration level of pollutants in the environment crosses a limit over which the pollutants starts causing harm to the population under consideration. Criteria for local stability, global stability and permanence are obtained using theory of ordinary differential equations. Numerical simulations are carried out to investigate the dynamics of the system using fourth order Runge–Kutta Method. It is found that, as the emission rate of pollutants in the environment increases, the density of biological species decreases. It may also be pointed out that the biological species may even become extinct if the rate of emission of pollutants increases continuously. However, if some environmental taxes are imposed to control the rate of emission of these pollutants into the environment, the density of biological species can be maintained at a desired level.
Estimation of the finite population covariance using calibration
Authors: Plikusas A. , Pumputis D.
Published: September 2019

Estimators of the finite population covariance with several systems of weights are considered. New calibrated estimators of the finite population covariance (variance) are derived, using two and three weighting systems that are defined by various calibration equations and loss functions. The expressions of approximate variance for some of these estimators are presented. The estimators derived are compared by simulation. Finally, it is shown how the calibrated estimators of the covariance may be applied in regression estimation of the finite population total.
Existence and uniqueness theorem to a unimolecular heterogeneous catalytic reaction model
Authors: Ambrazevičius A.
Published: September 2019

A mathematical model for an unimolecular heterogeneous catalytic reaction is considered in the case when the reaction product slowly desorb and then diffuse away from the surface. This model is described by a coupled system of nonlinear parabolic and two ordinary differential equations. The existence and uniqueness theorems of classical solution are proved for this system.
On the convergence rates of Gladyshev’s Hurst index estimator
Authors: Kubilius K. , Melichov D.
Published: September 2019

This paper presents the convergence rates for a modified Gladyshev’s estimator of the Hurst index of the fractional Brownian motion.
Modeling nonlinear systems using multiple piecewise linear equations
Authors: Lowe G. K. K. , Zohdy M. A. A.
Published: September 2019

This paper describes a technique for modeling nonlinear systems using multiple piecewise linear equations. The technique provides a means for linearizing the nonlinear system in such a way as to not limit the large signal behavior of the target system. The nonlinearity in the target system must be able to be represented as a piecewise linear function. A simple third order nonlinear system is used to demonstrate the technique. The behavior of the modeled system is compared to the behavior of the nonlinear system.
N-distance tests of uniformity on the hypersphere
Authors: Bakshaev A.
Published: September 2019

In this paper we propose an application of N-distance theory for testing the hypothesis of uniformity on hypersphere S p − 1. The work is a continuation of our research started in [1, 2]. Particular attention is devoted to p = 2, 3 cases. A brief comparative Monte Carlo power study for proposed criteria is provided.
MHD natural convection in an inclined cavity filled with a fluid saturated porous medium with heat source in the solid phase
Authors: Mansour M. A. A. , Chamkha A. J. J. , Mohamed R. A. A. , Abd El-Aziz M. M. M. , Ahmed S. E. E.
Published: September 2019

A numerical investigation of unsteady magnetohydrodynamic free convection in an inclined square cavity filled with a fluid-saturated porous medium and with internal heat generation has been performed. A uniform magnetic field inclined with the same angle of the inclination of the cavity is applied. The governing equations are formulated and solved by a direct explicit finite-difference method subject to appropriate initial and boundary conditions. Two cases were considered, the first case when all the cavity walls are cooled and the second case when the cavity vertical walls are kept adiabatic. A parametric study illustrating the influence of the Hartmann number, Rayliegh number, the inclination angle of the cavity and the dimensionless time parameter on the flow and heat transfer characteristics such as the streamlines, isotherms and the average Nusselt number is performed. The velocity components at mid section of the cavity as well as the temperature profiles are reported graphically. The values of average Nusselt number for various parametric conditions are presented in tabular form.
A note on “Taylor–Couette flow of a generalized second grade fluid due to a constant couple”
Authors: Fetecau C. , Awan A. U. U. , Athar M.
Published: September 2019

In this brief note, we show that the unsteady flow of a generalized second grade fluid due to a constant couple, as well as the similar flow of Newtonian and ordinary second grade fluids, ultimately becomes steady. For this, a new form of the exact solution for velocity is established. This solution is presented as a sum of the steady and transient components. The required time to reach the steady-state is obtained by graphical illustrations.
Natural convection in a porous trapezoidal enclosure with magneto-hydrodynamic effect
Authors: Mamun M. A. H. A. H. , Islam Md. T. T. , Rahman Md. M. M.
Published: September 2019

The effects of magnetic force, acting vertically downward on natural convection within a porous trapezoidal enclosure saturated with an electrically conducting fluid have been investigated numerically. The bottom wall of the enclosure is subjected to a constant hot temperature and the top wall experiences a constant cold temperature whereas the remaining sidewalls are kept adiabatic. The physical problems are represented mathematically by different sets of governing equations along with the corresponding boundary conditions. By using Galerkin weighted residual method of finite element formulation, the non-dimensional governing equations are discritized. For natural convection in a porous medium the influential parameters are the modified Rayleigh number Ram, the fluid Rayleigh number Raf , the inclination angle of the sidewalls of the cavity γ, the rotational angle of the enclosure Φ and the Hartmann number Ha, through which different thermo-fluid characteristics inside the enclosure are obtained. In the present study, the obtained results are presented in terms of streamlines, isotherms and average Nusselt number along the hot wall. The result shows that with increasing Ha, the diffusive heat transfer become prominent even though the modified Rayleigh number increases. Optimum heat transfer rate is obtained at higher values of Ram in the absence of magnetic force.
Modeling the depletion of dissolved oxygen in a lake due to submerged macrophytes
Authors: Misra A. K. K.
Published: September 2019

In this paper a non-linear mathematical model for depletion of dissolved oxygen in a lake due to submerged macrophytes is proposed and analyzed. It is assumed that nutrients are continuously coming to the lake with a constant rate through water run off. In the modeling process five variables are considered, namely concentration of nutrients, density of algal population, density of macrophytes, density of detritus and concentration of dissolved oxygen. Equilibria of the model have been obtained and their stability discussed. The numerical simulation is also performed to support the obtained analytical results.
Modelling of glycaemia dynamics: impact of physical exercises
Authors: Švitra D. , Basov I. , Vilkytė R.
Published: September 2019

In this article the authors performed linear, nonlinear and numerical analysis of glycemic regulation mathematical model described by two differential equations with one delay argument. The results obtained in the linear analysis were used in numeric analysis while constructing stable periodic solutions applying the Runge–Kuto IV successive method in normal and diabetes cases. Impact of physical exercise on the dynamics of glucose and insulin was modelled as well while introducing two external periodical functions defining diet and physical exercise into the above mentioned model. We applied the simulation modelling program “Model Maker” for modelling.
Cover Vol. 10 (2), July 2018
Authors: Al-Iqtishad Jurnal
Published: September 2019

Cover Vol. 10 (2), July 2018
Mapping and Correlation Analysis of Efficiency and Profitability: The Case of Islamic Rural Bank in Indonesia
Authors: Warninda Titi Dewi , Hosen M. Nadratuzzaman
Published: September 2019

This research aims to analyze efficiency  and  profitability  of  Islamic  Rural  Banks  in  Indonesia  using Variable Returns to Scale model of Data Envelopment Analysis and efficiency-profitability matrix.  The  results  of  this  research  show  that  most  of  Islamic  Rural  Banks  are included in the Dog quadrant (high efficiency but low profitability) and Sleeper quadrant (low efficiency but high profitability). Meanwhile, the result of correlation analysis between efficiency and profitability indicates that efficiency has a negative correlation with profitability. Negative correlation of efficiency and profitability is in accordance with the result of efficiency-profitability matrix. The results of this research show that not all of Islamic Rural Bank which have high efficiency are also having high profitability.DOI:10.15408/aiq.v7i1.1354