bluuebunny/crossref_metadata_2025 huggingface dataset:
A Novel Secure and Robust Encryption Scheme for Medical Images
Authors: Chirakkarottu Siyamol , Mathew Sheena
Published: April 2020

Background:

Medical imaging encloses different imaging techniques and processes to
image the human body for medical diagnostic and treatment purposes. Hence it plays an important
role to improve public health. The technological development in biomedical imaging specifically
in X-ray, Computed Tomography (CT), nuclear ultrasound including Positron Emission Tomography
(PET), optical and Magnetic Resonance Imaging (MRI) can provide valuable information
unique to a person.

Objective:

In health care applications, the images are needed to be exchanged mostly over a wireless
medium. The diagnostic images with confidential information of a patient need to be protected
from unauthorized access during transmission. In this paper, a novel encryption method is proposed
to improve the security and integrity of medical images.

Methods:

Chaotic map along with DNA cryptography is used for encryption. The proposed
method describes a two-phase encryption of medical images.

Results:

The performance of the proposed method is also tested by various analysis metrics. The robustness
of the method against different noises and attacks is analyzed.

Conclusion:

The results show that the method is efficient and well suitable for medical images.
Synthesis of New Thioureas Derivatives and Evaluation of Their Efficacy as Proliferation Inhibitors in MCF-7 Breast Cancer Cells by Using 99mTc-MIBI Radiotracer
Authors: Hormati Ahmad , Shiran Jafar Abbasi , Molazadeh Mikaeil , Kaboudin Babak , Ahmadpour Sajjad
Published: April 2020

Background & Objective:

Anti-tumor activity of some thioureas derivatives is well
documented in literature and received considerable attention. The present study aims to synthesize
and characterize some novel thioureas and carbonylthioureas as anti-tumor agents for MCF-7
breast cancer cells in vitro and in vivo.

Materials and Methods:

Several 1-allyl-3-(substituted phenyl), N,N'-(phenylene) bis(3-
allyldithithiourea) and 1-cyclopropanecarbonyl-3-(substituted phenyl)-thioureas derivatives were
synthesized and confirmed by FT-IR spectroscopy, NMR and 13C-NMR. Anti-tumor activity of
these compounds was determined by various in vitro and in vivo assays including; MTT, tumor
volume measurement as well as,99mTc-MIBI tumor uptake in MCF-7 tumor bearing nude mice.

Results:

Among all of the synthesized compounds, some thioureas derivatives [3i] and [4b] at 100
nM concentration exhibited significant inhibitory effects on the proliferation of MCF-7 cell in vitro.
However, this inhibition was not observed in HUVEC human endothelial normal cells. In vivo
anti-tumor effects of the synthesized compounds on MCF-7 xenograft mouse models demonstrated
a reduction in the tumor volume for various concentrations between 2 to 10 mg/kg after 21 days.
These effects were comparable with Tamoxifen as standard anti-estrogen drug. According to the
99mTc-MIBI biodistribution result, treatment of MCF-7 bearing nude mice with both [3i] and [4b]
compounds at the maximum concentration (10 mg/kg) can lead to a significant decrease of 99mTc-
MIBI tumor uptake.

Conclusions:

Compounds [3i] and [4b] suppressed the growth of MCF-7 cells in the xenograft
nude mice at the doses that were well-tolerated. Our study suggests that these new compounds
with their significant anti-tumor effects, may serve as useful candidates for breast cancer therapy.
A Concise Review on Multidimensional Silver Nanoparticle Health Aids and Threats
Authors: Phaugat Parmita , Khansili Aparna , Nishal Suchitra , Kumari Beena
Published: April 2020

Nanoparticles (Np) are the 21st century material in supreme formulations due to their
unique properties and design. In review, systematic discussion of the synthesis, characterization,
bio-applications, and risks of AgNps (Silver Nanoparticles) especially highlighting anticancer activity
envisaging mechanisms as well as therapeutic approaches for cancer. Ag-Nps mainly possess
toxicological concern.

Benefits and Risk:

AgNps have beneficial approaches for cancer treatment and angiogenesisrelated
diseases like rheumatoid arthritis, atherosclerosis, diabetic psoriasis, retinopathy, endometriosis,
and adiposity.

Ag-Nps induced cytotoxicity through oxidative stress by the ROS (Reactive Oxygen Species) generation
could be measured as dependent on different properties, such as nanoparticle shape, size,
agglomeration, concentration, and aggregation.

Result:

The advancing nanotechnology-based therapy needs to be devised better, and it should
offload the hitches of prevailing treatment approaches. Essential studies are required to explain the
synergistic effect of two different cytotoxic agents.
GASPIDs Versus Non-GASPIDs - Differentiation Based on Machine Learning Approach
Authors: Ahmad Fawad , Ikram Saima , Ahmad Jamshaid , Ullah Waseem , Hassan Fahad , Khattak Saeed Ullah , Irshad Ur Rehman
Published: April 2020

Background:

Peptidases are a group of enzymes which catalyze the cleavage of peptide
bonds. Around 2-3% of the whole genome codes for proteases and about one-third of all known
proteases are serine proteases which are divided into 13 clans and 40 families. They are involved
in diverse physiological roles such as digestion, coagulation of blood, fibrinolysis, processing of
proteins and prohormones, signaling pathways, complement fixation, and have a vital role in the
immune defense system. Based on their functions, they can broadly be divided into two classes;
GASPIDs (Granule Associated Serine Peptidases involved in Immune Defense System) and Non-
GASPIDs. GASPIDs, in particular are involved in immune-associated functions i.e. initiating
apoptosis to kill virally infected and cancerous cells, cytokine modulation for the generation of
inflammatory responses, and direct killing of pathogens through phagosomes.

Methods:

In this study, sequence-based characterization of these two types of serine proteases is
performed. We first identified sequences by analyzing multiple online databases as well as by
analyzing whole genomes of different species from different orthologous and non-orthologous
species. Sequences were identified by devising a distinct criterion to differentiate GASPIDs from
Non-GASPIDs. The translated version of these sequences was then subjected to feature extraction.
Using these distinctive features, we differentiated GASPIDs from Non-GASPIDs by applying
multiple supervised machine learning models.

Results and Conclusion:

Our results show that, among the three classifiers used in this study,
SVM classifier coupled with tripeptide as feature method has shown the best accuracy in
classification of sequences as GASPIDs and Non-GASPIDs.
A Review of Protein Inter-residue Distance Prediction
Authors: Huang He , Gong Xinqi
Published: April 2020

Proteins are large molecules consisting of a linear sequence of amino acids. Protein
performs biological functions with specific 3D structures. The main factors that drive proteins to
form these structures are constraint between residues. These constraints usually lead to important
inter-residue relationships, including short-range inter-residue contacts and long-range interresidue
distances. Thus, a highly accurate prediction of inter-residue contact and distance
information is of great significance for protein tertiary structure computations. Some methods have
been proposed for inter-residue contact prediction, most of which focus on contact map prediction
and some reviews have summarized the progresses. However, inter-residue distance prediction is
found to provide better guidance for protein structure prediction than contact map prediction in
recent years. The methods for inter-residue distance prediction can be roughly divided into two
types according to the consideration of distance value: one is based on multi-classification with
discrete value and the other is based on regression with continuous value. Here, we summarize
these algorithms and show that they have obtained good results. Compared to contact map
prediction, distance map prediction is in its infancy. There is a lot to do in the future including
improving distance map prediction precision and incorporating them into residue-residue distanceguided
ab initio protein folding.
Supervised Learning in Spiking Neural Networks with Synaptic Delay Plasticity: An Overview
Authors: Lan Yawen , Li Qiang
Published: April 2020

Throughout the central nervous system (CNS), the information communicated between
neurons is mainly implemented by the action potentials (or spikes). Although the spike-timing
based neuronal codes have significant computational advantages over rate encoding scheme, the
exact spike timing-based learning mechanism in the brain remains an open question. To close this
gap, many weight-based supervised learning algorithms have been proposed for spiking neural
networks. However, it is insufficient to consider only synaptic weight plasticity, and biological
evidence suggest that the synaptic delay plasticity also plays an important role in the learning
progress in biological neural networks. Recently, many learning algorithms have been proposed to
consider both the synaptic weight plasticity and synaptic delay plasticity. The goal of this paper is
to give an overview of the existing synaptic delay-based learning algorithms in spiking neural
networks. We described the typical learning algorithms and reported the experimental results.
Finally, we discussed the properties and limitations of each algorithm and made a comparison
among them.
An Overview of Abdominal Multi-organ Segmentation
Authors: Li Qiang , Song Hong , Chen Lei , Meng Xianqi , Yang Jian , Zhang Le
Published: April 2020

The segmentation of multiple abdominal organs of the human body from images with
different modalities is challenging because of the inter-subject variance among abdomens, as well
as the complex intra-subject variance among organs. In this paper, the recent methods proposed for
abdominal multi-organ segmentation (AMOS) on medical images in the literature are reviewed.
The AMOS methods can be categorized into traditional and deep learning-based methods. First,
various approaches, techniques, recent advances, and related problems under both segmentation
categories are explained. Second, the advantages and disadvantages of these methods are
discussed. A summary of some public datasets for AMOS is provided. Finally, AMOS remains an
open issue, and the combination of different methods can achieve improved segmentation
performance.
Understanding the Pathogenesis, Therapeutic Targets/Drug Action and Pharmacogenetics of Type 2 Diabetes: Is there a Future for Personalised Medicine?
Authors: Engwa Godwill Azeh , Nweke Friday Nwalo , Karngong Gilbert Nfor , Afiukwa Celestine Azubuike , Nwagu Kingsley Ekene
Published: April 2020

Type 2 diabetes (T2D) is a chronic non-communicable disease that is of major health concern
with a steadily rising prevalence across the globe. It is a metabolic disorder characterized by high
blood glucose level either as a result of impaired insulin secretion and/or insulin action usually termed
insulin resistance. This disease is influenced by lifestyle/feeding habit changes and genetic factors that
cause physiological changes in glucose and lipid metabolism. As such, antidiabetic treatments have
targeted specific enzymes, receptors, transport proteins, hormones, transcription factors, etc. that are
related to glucose metabolism, fat metabolism, insulin secretion and insulin signalization. Genetic
variations due to mutations in certain target genes have been shown to influence the pathogenesis of
T2D but also these polymorphisms have been observed to alter the therapeutic efficacy of drugs as
well as their safety. Pharmacogenetic studies have been able to identify specific genetic variants of
target genes that affect the metabolism, therapeutic response and adverse effects of antidiabetic drugs
with the aim to translate the research findings to clinical practice. However, pharmacogenetic studies
have not fully been able to identify distinct genetic markers that can serve as biomarkers for genetic
screening, thus, limiting personalised medicine. As we advocate personalised medicine for the management
of T2D in the future, pharmacogenetic studies should lay emphasis on addressing challenges
of genetic screening and its translation to personalised therapy.
Characterizing the Binding of Angiotensin Converting Enzyme I Inhibitory Peptide to Human Hemoglobin: Influence of Electromagnetic Fields
Authors: Sadeghzadeh Farzaneh , Entezari Amir Arsalan , Behzadian Kiana , Habibi Kimia , Amiri-Tehranizadeh Zeinab , Asoodeh Ahmad , Saberi Mohammad Reza , Chamani Jamshidkhan
Published: April 2020

Background:

Drug-protein complexes is one of the crucial factors when analyzing the
pharmacokinetics and pharmacodynamics of a drug because they can affect the excretion, distribution,
metabolism and interaction with target tissues.

Objectives:

The aim of this study was to investigate the interaction of human hemoglobin (Hb) and
angiotensin I converting enzyme inhibitory peptide (ACEIP) in the absence and presence of different-
frequency electromagnetic fields (EMF).

Methods:

Various spectroscopic methods like fluorescence spectroscopy, ultraviolet, circular
dichroism and conductometry techniques were applied to investigate Hb-ACEIP interaction in the
absence and presence of EMF.

Result:

The presented spectroscopic studies indicated that EMF changed the interaction between
Hb and ACEIP. The a-helix content of Hb decreased upon binding to ACEIP and conductivity of
the solution enhanced upon binding. Based on Stern-Volmer equations, it could be stated that the
Hb-ACEIP affinity was higher in the presence of EMF.

Conclusion:

It can be concluded that for patients who use the drug to control blood pressure, a
low-frequency electromagnetic field would have a positive effect on the uptake of the drug.
Protein Markers in Osteoporosis
Authors: Porcelli Teresa , Pezzaioli Letizia , Delbarba Andrea , Maffezzoni Filippo , Cappelli Carlo , Ferlin Alberto
Published: April 2020

:

Osteoporosis is a systemic skeletal disease characterized by low bone mass and microarchitectural
deterioration of bone tissue. Biomarkers of bone turnover have been used for years in
bone disease management, especially to determine response to treatment. They are substances
found in biological fluids, produced during the bone remodelling process. Recently, new approaches
for the detection of bone physiology and pathology biomarkers have been proposed, among
which proteomics, with particular interest in osteoporosis. The objective of this manuscript is to review
current knowledge on proteomics applied to osteoporosis in vivo. The analysis of the 14
studies published to date showed a range of proteins whose expression is altered in patients with osteoporosis.
The relatively small number of papers depends mainly on high costs and technical limitations;
due to the difficulty to collect osteoclasts, most of the studies performed proteomics on peripheral
blood monocytes (PBMs), already accepted as an excellent osteoporosis cell model in
vivo. Among the identified proteins, the most promising are represented by Gelsolin (GSN), Annexin
A2 (ANXA2), and Prolyl 4-hydroxylase (P4HB). They have been related to bone mineral
density (BMD), sometimes in apparent disagreement (some upregulated and others downregulated
in patients with low BMD).

:

Finally, worthy of mention is the application of proteomics in the emerging field of microvesicles
(MVs); they are important messengers, widely present in body fluids, and have recently emerged
as novel targets for the diagnosis of multiple diseases, among which musculoskeletal diseases. In
conclusion, the proteomic field is relatively novel in osteoporosis and has a considerable but theoretical
potential; further investigations are needed in order to make proteome-derived markers applicable
to clinical practice.
Animal Models for the Evaluation of Theranostic Radiopharmaceuticals
Authors: Soyluoglu Selin , Durmus-Altun Gulay
Published: April 2020

Background:

Theranostic is a new field of medicine that combines diagnosis and patient-
specific targeted treatment. In the theranostic approach, it is aimed to detect diseased cells by using
targeted molecules using disease-specific biological pathways and then destroy them by cellular
irradiation without damaging other tissues. Diagnostic tests guide the use of specific therapeutic
agents by demonstrating the presence of the receptor/molecule on the target tissue. As the therapeutic
agent is administered to patients who have a positive diagnostic test, the efficacy of treatment in
these patients is largely guaranteed. As therapeutic efficacy can be predicted by therapeutic agents,
it is also possible to monitor the response to treatment. Many diagnostic and therapeutic procedures
in nuclear medicine are classified as theranostic. 131I treatment and scintigraphy are the best examples
of the theranostic application. Likewise, 177Lu / 90Y octreotate for neuroendocrine tumors,
177Lu PSMA for metastatic or treatment-resistant prostate cancer, 90Y SIRT for metastatic liver
cancer, and 223Ra for bone metastasis of prostate cancer are widely used. Moreover, nanoparticles
are one of the most rapidly developing subjects of theranostics. Diagnostic and therapeutic
agents that show fluorescent, ultrasonic, magnetic, radioactive, contrast, pharmacological drug or
antibody properties are loaded into the nanoparticle to provide theranostic use.

Methods:

This article reviewed general aspects of preclinical models for theranostic research, and
presented examples from the literature.

Conclusion:

To achieve successful results in rapidly accelerating personalized treatment research
of today, the first step is to conduct appropriate preclinical studies.
Eco-friendly Transformation of Waste Biomass to Biofuels
Authors: Parakh Pranav D. , Nanda Sonil , Kozinski Janusz A.
Published: April 2020

Background:

The development of viable alternative fuel sources is assuming a new urgency
in the face of climate change and environmental degradation linked to the escalating consumption
of fossil fuels. Lignocellulosic biomass is composed primarily of high-energy structural components
such as cellulose, hemicellulose and lignin. The transformation of lignocellulosic biomass to biofuels
requires the application of both pretreatment and conversion technologies.

Methods:

Several pretreatment technologies (e.g. physical, chemical and biological) are used to recover
cellulose, hemicellulose and lignin from biomass and begin the transformation into biofuels.
This paper reviews the thermochemical (e.g. pyrolysis, gasification and liquefaction), hydrothermal
(e.g. subcritical and supercritical water gasification and hydrothermal liquefaction), and biological
(e.g. fermentation) conversion pathways that are used to further transform biomass feedstocks into
fuel products.

Results:

Through several thermochemical and biological conversion technologies, lignocellulosic biomass
and other organic residues can produce biofuels such as bio-oils, biochar, syngas, biohydrogen,
bioethanol and biobutanol, all of which have the potential to replace hydrocarbon-based fossil fuels.

Conclusions:

This review paper describes the conversion technologies used in the transformation of
biomass into viable biofuels. Biofuels produced from lignocellulosic biomass and organic wastes are a
promising potential clean energy source with the potential to be carbon-neutral or even carbonnegative.
Investigation of Geographic and Macrolevel Variations in LGBTQ Patient Experiences: Longitudinal Social Media Analysis
Authors: Hswen Yulin , Zhang Amanda , Sewalk Kara C , Tuli Gaurav , Brownstein John S , Hawkins Jared B
Published: April 2020

Background

Discrimination in the health care system contributes to worse health outcomes among lesbian, gay, bisexual, transgender, and queer (LGBTQ) patients.

Objective

The aim of this study is to examine disparities in patient experience among LGBTQ persons using social media data.

Methods

We collected patient experience data from Twitter from February 2013 to February 2017 in the United States. We compared the sentiment of patient experience tweets between Twitter users who self-identified as LGBTQ and non-LGBTQ. The effect of state-level partisan identity on patient experience sentiment and differences between LGBTQ users and non-LGBTQ users were analyzed.

Results

We observed lower (more negative) patient experience sentiment among 13,689 LGBTQ users compared to 1,362,395 non-LGBTQ users. Increasing state-level liberal political identification was associated with higher patient experience sentiment among all users but had stronger effects for LGBTQ users.

Conclusions

Our findings highlight that social media data can yield insights about patient experience for LGBTQ persons and suggest that a state-level sociopolitical environment influences patient experience for this group. Efforts are needed to reduce disparities in patient care for LGBTQ persons while taking into context the effect of the political climate on these inequities.
Barriers and Facilitators to the Adoption of Mobile Health Among Health Care Professionals From the United Kingdom: Discrete Choice Experiment
Authors: Leigh Simon , Ashall-Payne Liz , Andrews Tim
Published: April 2020

Background

Despite the increasing availability of mobile health services, clinical engagement remains minimal.

Objective

This study aims to identify and weight barriers to and drivers of health app use among health care professionals (HCPs) from the United Kingdom.

Methods

A discrete choice experiment was conducted with 222 HCPs using a web-based survey between March 2019 and June 2019. Participants were recruited to take part via social media and asked to choose their preferred option of 2 hypothetical health apps to prescribe to a hypothetical patient or to prescribe neither. Choices were characterized by differing levels of patient age, cost, published evidence bases, whether they had a National Health Service (NHS) stamp of approval, personal familiarity with the technology, and whether they were recommended by a fellow HCP. The results were analyzed using a mixed logit model, with subgroup analyses to account for heterogeneity.

Results

We received 230 responses, a total of 96.5% (n=222/230) of respondents understood the survey task and passed the test of rationality. The median age was between 36 and 45 years, and 62.6% (n=139/222) of the health care providers responding to the survey had previously recommended the use of health apps to patients. Health apps were most likely to be prescribed to patients if they had an NHS stamp of approval or if they were recommended by another HCP (both P<.001). Published studies detailing clinical effectiveness were important (P<.001), but it would take five published studies to have the same impact on prescribing behavior as an NHS stamp of approval and two studies to be as convincing as having used the technology personally. Increasing patient age and costs resulted in significant reductions in digital health prescribing (P<.001), none more so than among allied health professionals. Willingness-to-pay for health apps increased by £124.61 (US $151.14) if an NHS stamp of approval was present and by £29.20 (US $35.42) for each published study. Overall, 8.1% (n=18/222) of respondents were reluctant to use health apps, always choosing the I would prescribe neither option, particularly among older HCPs, nurses, and those who do not use health apps personally. Subgroup analyses revealed significant differences in preferences among HCPs of differing ages and clinical backgrounds.

Conclusions

An NHS stamp of approval, published studies, and recommendations from fellow HCPs are significant facilitators of digital prescribing, whereas increasing costs and patient age are significant barriers to engagement. These findings suggest that demonstrating assurances of health apps and supporting both the dissemination and peer-to-peer recommendation of evidence-based technologies are critical if the NHS is to achieve its long-term digital transformation ambitions.
Creating COVID-19 Stigma by Referencing the Novel Coronavirus as the “Chinese virus” on Twitter: Quantitative Analysis of Social Media Data
Authors: Budhwani Henna , Sun Ruoyan
Published: April 2020

Background

Stigma is the deleterious, structural force that devalues members of groups that hold undesirable characteristics. Since stigma is created and reinforced by society—through in-person and online social interactions—referencing the novel coronavirus as the “Chinese virus” or “China virus” has the potential to create and perpetuate stigma.

Objective

The aim of this study was to assess if there was an increase in the prevalence and frequency of the phrases “Chinese virus” and “China virus” on Twitter after the March 16, 2020, US presidential reference of this term.

Methods

Using the Sysomos software (Sysomos, Inc), we extracted tweets from the United States using a list of keywords that were derivatives of “Chinese virus.” We compared tweets at the national and state levels posted between March 9 and March 15 (preperiod) with those posted between March 19 and March 25 (postperiod). We used Stata 16 (StataCorp) for quantitative analysis, and Python (Python Software Foundation) to plot a state-level heat map.

Results

A total of 16,535 “Chinese virus” or “China virus” tweets were identified in the preperiod, and 177,327 tweets were identified in the postperiod, illustrating a nearly ten-fold increase at the national level. All 50 states witnessed an increase in the number of tweets exclusively mentioning “Chinese virus” or “China virus” instead of coronavirus disease (COVID-19) or coronavirus. On average, 0.38 tweets referencing “Chinese virus” or “China virus” were posted per 10,000 people at the state level in the preperiod, and 4.08 of these stigmatizing tweets were posted in the postperiod, also indicating a ten-fold increase. The 5 states with the highest number of postperiod “Chinese virus” tweets were Pennsylvania (n=5249), New York (n=11,754), Florida (n=13,070), Texas (n=14,861), and California (n=19,442). Adjusting for population size, the 5 states with the highest prevalence of postperiod “Chinese virus” tweets were Arizona (5.85), New York (6.04), Florida (6.09), Nevada (7.72), and Wyoming (8.76). The 5 states with the largest increase in pre- to postperiod “Chinese virus” tweets were Kansas (n=697/58, 1202%), South Dakota (n=185/15, 1233%), Mississippi (n=749/54, 1387%), New Hampshire (n=582/41, 1420%), and Idaho (n=670/46, 1457%).

Conclusions

The rise in tweets referencing “Chinese virus” or “China virus,” along with the content of these tweets, indicate that knowledge translation may be occurring online and COVID-19 stigma is likely being perpetuated on Twitter.
Using WeChat, a Chinese Social Media App, for Early Detection of the COVID-19 Outbreak in December 2019: Retrospective Study (Preprint)
Authors: Wang Wenjun , Wang Yikai , Zhang Xin , Jia Xiaoli , Li Yaping , Dang Shuangsuo
Published: April 2020

BACKGROUND

A novel coronavirus, SARS-CoV-2, was identified in December 2019, when the first cases were reported in Wuhan, China. The once-localized outbreak has since been declared a pandemic. As of April 24, 2020, there have been 2.7 million confirmed cases and nearly 200,000 deaths. Early warning systems using new technologies should be established to prevent or mitigate such events in the future.

OBJECTIVE

This study aimed to explore the possibility of detecting the SARS-CoV-2 outbreak in 2019 using social media.

METHODS

WeChat Index is a data service that shows how frequently a specific keyword appears in posts, subscriptions, and search over the last 90 days on WeChat, the most popular Chinese social media app. We plotted daily WeChat Index results for keywords related to SARS-CoV-2 from November 17, 2019, to February 14, 2020.

RESULTS

WeChat Index hits for “Feidian” (which means severe acute respiratory syndrome in Chinese) stayed at low levels until 16 days ahead of the local authority’s outbreak announcement on December 31, 2019, when the index increased significantly. The WeChat Index values persisted at relatively high levels from December 15 to 29, 2019, and rose rapidly on December 30, 2019, the day before the announcement. The WeChat Index hits also spiked for the keywords “SARS,” “coronavirus,” “novel coronavirus,” “shortness of breath,” “dyspnea,” and “diarrhea,” but these terms were not as meaningful for the early detection of the outbreak as the term “Feidian”.

CONCLUSIONS

By using retrospective infoveillance data from the WeChat Index, the SARS-CoV-2 outbreak in December 2019 could have been detected about two weeks before the outbreak announcement. WeChat may offer a new approach for the early detection of disease outbreaks.
First things first: the much-needed domino effect for digital health adoption (Preprint)
Authors: Gross Christoph , Kvedar Joseph C.
Published: April 2020

UNSTRUCTURED

In this concise manuscript, we propose a novel point of view on how to approach the issue of digital health adoption.
Cooperative Law Policy: Historical Study Of Cooperative Settings In Indonesia
Authors: Kumaratih Cinantya , Tulus Sartono
Published: April 2020

The existence of cooperatives has an important meaning for the welfare state of Indonesia. As a nation that was colonized for a long time, cooperatives as one of the implementations of a people's economy became a systematic effort to correct the economic structure of a colonial style. In this study examines the legal policies of cooperative arrangements from various eras in Indonesia. This research is normative legal research with secondary data. This research shows that the existence and development of cooperatives experience ups and downs in their legal policies. The colonial period of cooperative arrangements merely regulates cooperatives in existence and makes cooperatives one of the business actors. During the independence period, the aim of cooperatives was as a people's economic movement which was expected to be able to equalize welfare. Unfortunately, cooperatives in the old and new order regimes were used as political tools to perpetuate government power. During the reform period, the regulation of cooperatives was getting worse because it made cooperatives like companies pursuing mere profits.
The Function of Legal Research in Formulation of Legislation
Authors: Lamada Victoria Tabita Majesty , Gumilang Tetania Retno
Published: April 2020

The formation of legislation is a condition in the framework of national law development which can only be realized if supported by good methods, which are binding on all institutions authorized to make regulations. Indonesia is a state of law that should implement good national legal development, which is carried out in a planned, integrated and sustainable manner in the national legal system. Law No. 12 of 2011 states that research is an important element in the formation of the legislation process. Because it is impossible if a draft legislation is formed before the existence of a legal investigation. This research discussed about the role of legal research in the formation of legislation, as well as what are the benefits of legal research itself. The conclusion is the formation of laws and regulations cannot occur if there is no legal research, because legal research is an internal problem solver in the process of establishing legislation. This legal research itself plays an active role in obtaining valid, correct, rational, and logical data. In addition, legal research is also useful for obtaining raw materials from all aspects, both juridical, socio-psychological, and philosophical that are accurate and complete.
Optimizing the Security of the Indonesian State through Strengthening International Cooperation between Indonesia and Malaysia in the Land Border
Authors: Partoga Edward Yohanes Yohanes , Setiyono Joko
Published: April 2020

Indonesia is an island nation consisting of land and sea areas. The constitutional foundation of Indonesia has regulated that the Unitary State of the Republic of Indonesia is an archipelagic nation characterized by an archipelago with territories whose boundaries and rights are determined by law. This is as regulated in Article 25 (A) of the 1945 Constitution of the Republic of Indonesia. The purpose of this research is the application of international cooperation between Indonesia and Malaysia in the land border area and the driving and inhibiting factors for international cooperation between Indonesia and Malaysia in the land border area. . The approach method used in this study is the Legal Research approach method. Implementation of International Cooperation between Indonesia and Malaysia in the Border Area, The application of international cooperation between Indonesia and Malaysia proves that there is an international interaction as a country that is close together in terms of geographical location. Drivers of factors and obstacles to international cooperation between Indonesia and Malaysia in the border of land areas. The role of the central, provincial and district / city government in developing border areas needs to be done appropriately and emphasizes three main points, namely: Regulators, Executors and Government facilitators as regulators are obliged to encourage structuring the rules that exist in the development and utilization of border areas in the decision making effort. Conclusion The application of the agreement made between Indonesia and Malaysia is a strategic step for the two countries to mutually reinforce sovereignty in the country's security efforts
The Influence Of Asset Management Towards Optimization Of State Assets In Working Units In The Denpasar High Court Region
Authors: Sriastiti Ni Luh Putu , Ningsih Ni Luh Anik Puspa , Yasa Putu Ngurah Suyatna
Published: April 2020

This study aims to analyze the effect of asset management which includes planning needs, inventory, identification, legal audit, asset valuation, utilization and monitoring of asset optimization in employees in charge of assets in the Denpasar High Court Regional Work Unit. The data used in this study are primary data obtained through questionnaires. The population in this study were all employees in the field of assets in the Denpasar High Court Regional Work Unit, amounting to 73 people. Determination of the sample using the census technique in which all populations are sampled. Data analysis technique uses Partial Least Square with the help of PLS software program. Based on the results of hypothesis testing it can be stated that the Requirement Planning significantly positive effect on asset optimization. Inventory does not have a significant positive effect on asset optimization. The identification of positive effect is not significant on asset optimization. Legal audit does not have a significant positive effect on asset optimization. Asset valuation has a positive and significant effect on asset optimization. Utilization has a positive and not significant effect on asset optimization. And monitoring has a positive and not significant effect on asset optimization.
Умножение
Authors: Гашков Сергей Борисович , Сергеев Игорь Сергеевич
Published: April 2020

В работе предпринимается обзор современного состояния теории быстрых алгоритмов умножения чисел и многочленов. Рассматривается процесс эволюции методов умножения от первых блочных алгоритмов Карацубы и Тоома 1960-х гг. к методам 1970-х гг., опирающимся на дискретное преобразование Фурье (ДПФ), и далее к новейшим методам, разработанным в 2007–2019 гг. Современные методы умножения сочетают использование специальных алгебраических структур, переход к приближенным вычислениям, особые формы преобразований Фурье: многомерное ДПФ, аддитивный аналог ДПФ. Эти и другие существенные для быстрых методов умножения концепции подробно рассматриваются в настоящем обзоре. Отдельно предусмотрено введение в теорию ДПФ с извлечением необходимых для изложения материала фактов. В заключительной части обзора приводятся краткие сведения о результатах в области параллельных алгоритмов умножения, аккуратных оценок сложности базовых методов умножения, алгоритмов умножения в реальном времени, мультипликативной сложности умножения многочленов над конечными полями. Отмечены модели вычислений, в которых умножение имеет линейную или квадратичную сложность.
Об одной теореме о среднем значении кратных тригонометрических сумм
Authors: Чубариков Владимир Николаевич
Published: April 2020

Доказана теорема о среднем для кратных тригонометрических сумм, обобщающая теорему Г. И. Архипова [12, 13]. Первая теорема подобного типа лежит в сердцевине метода И. М. Виноградова [2]. В работе найден вариант теоремы с "равноправными" длинами промежутков изменения переменных. Интересным приложением метода И. М. Виноградова являются оценки дзетовых сумм вида

$$

\sum_{n\leq P}n^{it}.

$$Подобным приложением теоремы о среднем, доказанной нами, служат оценки сумм вида$$\sum_{n\leq P_1}\dots\sum_{n\leq P_r}(n_1\dots n_r+k)^{it}, \sum_{n\leq P}\tau_s(n)(n+k)^{it}, \sum_{p\leq P}(p+k)^{it}.$$
Обобщение определения среднего
Authors: Почеревин Роман Владимирович
Published: April 2020

В статье приводится решение задачи нахождения общего вида среднего в случае отсутствия симметричности по всем переменным. В 1930 году А. Н. Колмогоров дал общий вид среднего значения. Он сформулировал четыре аксиомы среднего: непрерывность и монотонность по каждой переменной, симметричность по каждой переменной, равенство среднего от одинаковых значений этому значению и возможность замены некоторой группы значений их собственным средним без изменения общего среднего. Все переменные в теореме Колмогорова равноправны, это предполагает, что среднее является сиимметрической функцией по всем переменным. В. Н. Чубариковым была поставлена задача обобщения результата А. Н. Колмогорова на случай отсутствия симметричности по всем аргументам. Теперь переменные разбиваются на группы, и среднее будет симметрично отдельно по каждой из групп переменных. Если такая группа единственна, то исследуемое среднего удовлетворяет аксиомам А. Н. Колмогорова, поэтому результат статьи является обощением теоремы Колмогорова. В статье найден общий вид функции среднего в этой задаче, отмечена связь с равномерным распределением по модулю единица.
О многообразиях представлений некоторых свободных произведений циклических групп с одним соотношением
Authors: Беняш-Кривец Валерий Вацлавович , Адмиралова Александра Николаевна
Published: April 2020

В работе исследуются многообразия представлений двух классов конечно порожденных групп.Первый класс состоит из групп с копредставлением\begin{gather*}G = \langle a_1,\ldots,a_s,b_1,\ldots,b_k,x_1,\ldots,x_g\mid\\ a_1^{m_1}=\ldots=a_s^{m_s}= x_1^2\ldots x_g^2 W(a_1,\ldots,a_s,b_1,\ldots,b_k)=1\rangle,\end{gather*}где $g\ge 3$, $m_i\ge 2$ для $i=1,\ldots,s$ и$W(a_1,\ldots,a_s,b_1,\ldots,b_k)$ --- элемент в нормальной формев свободном произведении циклических групп $H=\langle a_1\mid a_1^{m_1}\rangle\ast\ldots\ast\langle a_s\mid a_s^{m_s}\rangle\ast\langle b_1\rangle\ast\ldots\ast\langle b_k\rangle$.

Второй класс состоит из групп с копредставлением$$G(p,q) = \langle a_1,\ldots,a_s,b_1,\ldots,b_k,x_1,\ldots,x_g,t\mid a_1^{m_1}=\ldots=a_s^{m_s}=1,\ tU^pt^{-1}=U^q \rangle,$$где $p$ и $q$ --- целые числа, такие, что $p>|q|\geq1$, $(p,q)=1$, $m_i\ge 2$ для $i=1,\ldots,s$, \linebreak $g\ge 3$,$U=x_1^2\ldots x_g^2W(a_1,\ldots,a_s,b_1,\ldots,b_k)$ и $W(a_1,\ldots,a_s,b_1,\ldots,b_k)$ --- элемент, определенный выше.

Найдены неприводимые компоненты многообразий представлений $R_n(G)$ и $R_n(G(p,q))$, вычислены их размерности и доказано, что каждая неприводимаякомпонента является рациональным многообразием.
Конечные циклические полукольца с полурешеточным сложением, заданным двухпорожденным идеалом натуральных чисел
Authors: Вечтомов Евгений Михайлович , Чупраков Дмитрий Вячеславович
Published: April 2020

В работе исследуются конечные циклические полукольца с~полурешеточным сложением, определенные как конечные циклические мультипликативные моноиды~$\langle S,\cdot \rangle$ с~введенной на них операцией сложения~$(+)$, так, что алгебраическая структура~$\langle S,+ \rangle$ является верхней полурешеткой и~выполняются законы дистрибутивности умножения относительно сложения.

Описано строение конечных циклических полуколец с~полурешеточной аддитивной операцией, заданной двухпорожденным идеалом полукольца целых неотрицательных чисел.

Результатом работы является теорема о строении циклических полуколец с~полурешеточной аддитивной операцией, заданной двухпорожденным идеалом полукольца целых неотрицательных чисел. Полученный результат, в частности, позволяет установить количество циклических полуколец, соответствующих каждому двухпорожденному идеалу полукольца целых неотрицательных чисел.

В работе используется аппарат идеалов полукольца целых неотрицательных чисел.Получены некоторые свойства идеалов полукольца целых неотрицательных чисел, определяющих структуру конечных циклических полуколец.

Работа дополняет исследования Е. М. Вечтомова и И. В. Орловой, где строение конечных циклических полуколец с~идемпотентным некоммутативным сложением описано через конечные циклические полуполя и~конечные циклические полукольца с~полурешеточным сложением.
An SVC controller for Power Quality Improvement of a Heavily Loaded Grid
Authors: Ali Faheem , Arbab Muhammad Naeem , Ahmed Gulzar , Ashraf Majid , Sarim Muhammad
Published: April 2020

Pakistan is faced with energy crises from the last two decades. Generation cannot balance the load demands of the electricity consumers. Power delivery systems are generally old-fashioned and overloaded. They are unable to provide consistent and uninterrupted supply to commercial, industrial, and domestic loads. Generally speaking, the Power Systems consist of loads that are inductive and resistive in nature. Heavy machinery, induction motors, and arc furnaces are heavily inductive in nature. Inductive loads when operated in a weak power system results in lagging VARs (Volt Ampere Reactive) and poor voltage regulation, which must be balanced by the same number of leading VARs in order to ensure unity power factor and thus helps in improving the voltage profile. At times the reactive VARs injected may not be sufficient to balance the VARs requires by the system, but still the power factor is improved up to some extent. In hot and humid climatic conditions, air-cooling system and chillers greatly burdens the grids. Such loads require excessive reactive VARs, and if not offered with ample reactive power, causes severe voltage drops in distribution system. To manage low voltages and power-factor, household users use automatic voltage regulators while industries connect capacitor banks. Voltage regulators control output voltage within the required limits at the expense of excessive line current from transformer, which may overburden it. Moreover, with each operation of tap changer, current rises which further intensifies line losses. Static capacitors provide stable voltage but repeated variations in load demands reliable and vigorous voltage regulation. This investigation aims to come up with a power quality improvement scheme which would deliver instantaneous control of power (reactive) with SVC (Static VAR Compensator) thus overcoming the shortcomings of step-wise banks of capacitors and or voltage regulators. Simulation work is carried out in MATLAB/SIMULINK and the results are compliance with IEEE Standards for SVCs. The device can offer steady state as well as dynamic VAR compensation under changing load conditions. Result showed considerable improvement both in terms of response time and power factor. Switching time has been improved to less than 1/10th fraction of a second which in previous simulations was 0.7 seconds approximately. Initial power factor without disturbance and without compensation was recorded to be 0.6 lagging, which after compensation was improved to 0.95 lagging. Similarly, in presence of disturbance without compensation the power factor fluctuated between 0.55 and 0.9 lagging, which after compensation was improved to 0.95 lagging and above throughout the course of operation.
X-Sand Filter: An X-Tolerant Response Compaction Technique for Faster-Than-At-Speed Testing
Authors: Ahmad Salman , Iqbal Kashif
Published: April 2020

Faster-than-at-speed testing provides an effective way of detecting small delay defects but at the cost of increased number of unknown logic values on longer paths of the circuit under test. For efficient testing, these unknown logic values need to be filtered out of the circuit under test output. In past, different compaction hardware schemes were presented to minimize these unknown logic values, all these schemes were effective in handling a limited number of unknown values arising due to design imperfections, processing problems manufacturing problems material problems etc. but no effective compaction scheme is available to handle large number of these logic values arising due to faster-than-at-speed testing. This paper presents “X-sand filter”, a compaction technique, an extension of already presented idea of “X-tolerant signature analysis”. Here, the idea of “X-tolerant signature analysis” with modifications has been applied and has attained a considerable improvement in the X-tolerance. X-sand filter is a hierarchical structure that handles gradual X-density reduction in an efficient manner. Simulation results obtained show that we can achieve up to 90 % reduction in the X-density if we use X-sand filter. Extensions to the work of X-sand filter can be carried out in future to enhance its capabilities and make its configuration more flexible in terms of layer designing.
Penggunaan Model Pembelajaran Two Stay Two Stray Sebagai Upaya Meningkatkan Prestasi Belajar Ekonomi
Authors: Samiati Ni Wayan
Published: April 2020

Penelitian ini dilaksanakan di SMA Negeri 1 Sukawati di kelas XI IPS 1 Semester II Tahun Pelajaran 2018/2019 yang kemampuan siswanya untuk mata pelajaran Ekonomi masih rendah. Tujuan penulisan penelitian tindakan kelas ini adalah untuk mengetahui apakah penggunaan Model Pembelajaran Two Stay Two Stray dapat meningkatkan prestasi belajar Ekonomi siswa kelas XI IPS 1 semester II tahun pelajaran 2018/2019. Metode pengumpulan datanya adalah tes prestasi belajar. Metode analisis datanya adalah deskriptif. Hasil yang diperoleh dari penelitian ini adalah penggunaan Model Pembelajaran Two Stay Two Stray dapat meningkatkan prestasi belajar siswa. Ini terbukti dari hasil yang diperoleh pada pada awalnya 67,43 setelah diberikan tindakan pada siklus I meningkat menjadi 72,43, dan pada siklus II meningkat lagi menjadi 80,76. Kesimpulan yang diperoleh dari penelitian ini adalah penggunaan Model Pembelajaran Two Stay Two Stray dapat meningkatkan prestasi belajar Ekonomi siswa kelas XI IPS 1 semester II tahun pelajaran 2018/2019.Kata Kunci: Model Pembelajaran Two Stay Two Stray, Prestasi. Belajar
Implementasi Model Pembelajran Kooperatif Tipe STAD dengan Media Gambar untuk Meningkatkan Prestasi Belajar IPS
Authors: Suantara I Made
Published: April 2020

Penelitian tindakan kelas ini dilaksanakan di SD Negeri 3 Ubud tahun pelajaran 2018/2019 semester II dengan tujuan untuk meningkatkan prestasi belajar IPS siswa kelas III A SD Negeri 3 Ubud melalui penerapan model pembelajaran Kooperatif tipe STAD dengan media gambar. Subjek penelitian ini adalah siswa kelas III A SD Negeri 3 Ubud yang berjumlah 34 orang dalam mata pelajaran IPS. Data tentang prestasi belajar siswa diperoleh dengan menggunakan metode tes dengan instrumanya yaitu berupa tes prestasi belajar. Data tersebut kemudian dianalisis dengan menggunakan teknik analisis deskriptif kuantitatif. Hasil penelitian ini adalah Penerapan model pembelajaran Kooperatif Tipe STAD dengan media gambar dapat meningkatkan prestasi belajar IPS siswa kelas III A SD Negeri 3 Ubud pada semester II tahun pelajaran 2018/2019. Skor rata-rata prestasi belajar siswa menunjukkan adanya peningkatan dari siklus I ke siklus II. Rata-rata kelas prestasi belajar pada awal pembelajaran hanya mencapai 60,00, siklus I meningkat menjadi 69,11 pada siklus II menjadi 78,52. Ketuntasan klaksikal awal hanya mencapai 26,47%, pada siklus I meningkat menjadi 73,52% dan pada siklus II menjadi 94,11%.  Kata Kunci: Model Pembelajaran Kooperatif tipe STAD, Media Gambar, Prestasi Belajar.