bluuebunny/crossref_metadata_2025_split huggingface dataset:
WITHDRAWN: Novel Mystery of Double Slit/Cross-double Slit Experiments--- Curved Interference Pattern andInterference Pattern Depending on Orientation of Diaphragm
Authors: peng hui 
Published: July 2021

Abstract

Young’s double slit experiments express the mystery of quantum mechanics. To explore the mystery, varieties of the double slit and cross-double slit experiments were performed. In this article, we show novel mystery phenomena: (1) the characteristics of the interference patterns of the double slit and cross-double slit experiments depend on the orientation of the diaphragm used in the experiment, specifically on which axis the diaphragm rotates around, the rotating angle and how to rotate, clockwise or counterclockwise; and (2) in the cross-double slit experiments, the characteristics of the interference patterns also depend on which slit photons pass through; (3) unlike the regular double slit and regular cross-double slit experiments, in which the interference patterns are along the straight line, the interference patterns of the double slit/cross-double slit experiments can be along curve, and the curvatures depend on the orientations of the diaphragms of the double slit/cross-double slit. Those experiments show more mysteries of the double slit and cross-double slit experiments and provide comprehensive data for developing/testing a theoretical model.
Hydrothermal monazite trumps rutile: Applying U-Pb geochronology to evaluate complex mineralization ages of the Katbasu Au-Cu deposit, Western Tianshan, Northwest China
Authors: Zheng Jiahao , Shen Ping , Feng Wanyi 
Published: July 2021

Abstract
The Tianshan orogenic belt hosts several world-class gold deposits and is one of the largest gold provinces on Earth. The Katbasu Au-Cu deposit in the Chinese Western Tianshan is hosted in a granite intrusion. Previous researchers have shown that the main gold ores formed much later than the ore-hosting granite. However, the formation age of Cu mineralization and its possible link to Au mineralization remain poorly understood. This paper reports detailed mineralogical studies, combined with zircon U-Pb, in situ hydrothermal monazite as well as rutile U-Pb ages to constrain the timing of Cu mineralization and its possible link to Au mineralization. The two main ore types in the Katbasu deposit include Cu-Au ores with pyrite-chalcopyrite veins that crosscut the granite and Au ores with massive pyrite and quartz as the main minerals. The Cu-Au ores are spatially associated with diorite that intruded the granite, and they are overprinted by massive gold ores. Detailed mineralogical studies show that chalcopyrite is the main Cu-bearing mineral in the Cu-Au ores, and it is closely associated with some native gold, monazite, and rutile.
Secondary ion mass spectrometer (SIMS) U-Pb dating of zircon grains from the ore-hosting granite and mafic enclave yielded concordant ages of 354.1 ± 1.6 and 355.8 ± 1.7 Ma, respectively. The diorite that intruded the granite has a zircon U-Pb age of 352.0 ± 3.2 Ma. The trace element compositions of the monazite suggest they were formed by hydrothermal fluids rather than inherited from the ore-hosting granite. Hydrothermal monazite coexisting with chalcopyrite and native gold yielded a concordant age of 348.7 ± 2.3 Ma, and the W-rich hydrothermal rutile grains associated with the chalcopyrite yielded a U-Pb age of 345 ± 27 Ma, indicating an early Cu-Au mineralization event prior to the major Au mineralization (ca. 323–311 Ma). The formation time of early Cu-Au mineralization is consistent with the emplacement age of the diorite and may be of magmatic-hydrothermal origin, whereas the main Au has no genetic associations with magmatic rocks in the ore district and may belong to the orogenic type. Monazite geochronology provided a more reliable age constraint than rutile in the Katbasu Au-Cu deposit, and we suggest hydrothermal monazite has advantages over rutile in dating the complex mineralization ages of gold deposits.
PENGARUH SOSIALISASI PERPAJAKAN DAN SANKSI PERPAJAKAN TERHADAP KEPATUHAN WAJIB PAJAK UMKM E-COMMERCE
Authors: Maxuel Afeni , Primastiwi Anita 
Published: July 2021

ABSTRAK Penelitian ini bertujuan untuk menguji apakah sosialisasi perpajakan, kesadaran wajib pajak dan sanksi perpajakan berpengaruh terhadap kepatuhan wajib pajak UMKM e-commerce. Metode penelitian ini menggunakan metode deskriptif kuantitatif dan data primer dengan menggunakan kuesioner. Penelitian mengambil sampel pengusaha e-commerce yang ada di Indonesia. Teknik pengambilan sampel menggunakan purposive sampling. Pengumpulan data dilakukan dengan cara mengirimkan kuesioner melalui chat personal atau melalui e-mail dalam bentuk google form kepada pengusaha e-commerce. Jumlah kuesioner yang diolah adalah 100 kuesioner. Data dianalisis menggunakan analisis regresi linear berganda. Hasil penelitian ini menunjukkan bahwa sosialisasi perpajakan berpengaruh positif terhadap kepatuhan wajib pajak UMKM e-commerce sedangkan kesadaran wajib pajak dan sanksi perpajakan tidak berpengaruh signifikan terhadap kepatuhan wajib pajak UMKM e-commerce.Kata kunci: sosialisasi perpajakan, kesadaran wajib pajak, sanksi perpajakan, kepatuhan wajib pajak, umkm e-commerce. ABSTRACT This study aims to examine whether taxation socialization, awareness of taxpayers and tax sanctions affect the tax compliance of MSME e-commerce taxpayers. This research method uses quantitative descriptive methods and primary data using a questionnaire. The study took a sample of e-commerce entrepreneurs in Indonesia. The sampling technique uses purposive sampling. Data collection is done by sending questionnaires via personal chat or via e-mail in the form of Google forms to e-commerce entrepreneurs. The number of questionnaires processed was 100 questionnaires. Data were analyzed using multiple linear regression analysis. The results of this study indicate that taxation socialization has a positive effect on tax compliance of MSME e-commerce taxpayers while awareness of taxpayers and tax sanctions does not have a significant effect on tax compliance of MSME e-commerce taxpayersKeywords: taxation socialization, taxpayer awareness, tax sanction, taxpayer compliance, e-commerce SME
Using a grey multivariate model to predict impacts on the water quality of the Zhanghe River in China
Authors: Fan Feifei , Qiao Zhengran , Wu Lifeng 
Published: July 2021

Abstract
In order to assess the social factors affecting the water quality of the Zhanghe River and predict the potential impact of growth in primary, secondary, tertiary industries and population on water quality of the Zhanghe River in the next few years, a deformation derivative cumulative grey multiple convolution model (DGMC(1,N)) was applied. In order to improve the accuracy of the model, the accumulation of deformation derivatives is introduced, and the particle swarm optimization algorithm is used to solve the optimal order. The DGMC(1,N) model was compared with GM(1,2) and GM(1,1) models. The results show that the DGMC(1,N) model has the highest prediction accuracy. Finally, DGMC(1,N) model is used to predict the potential impact of growth in primary, secondary, tertiary industries and population on water quality in the Zhanghe River (using chemical oxygen demand (COD) as the water quality indicator).
Removal of psychoactive pharmaceuticals from wastewaters using microbial electrolysis cells producing hydrogen
Authors: Akagunduz Dilan , Cebecioglu Rumeysa , Ozdemir Murat , Catal Tunc 
Published: July 2021

Abstract
In this study, hydrogen production was analyzed along with methane and carbon dioxide generation using paroxetine, venlafaxine, and o-desmethylvenlafaxine (ODV) as substrates in single-chamber microbial electrolysis cells (MECs). Combinations of all three drugs were examined at concentrations of 750 ng/mL and 170 ng/mL. At the beginning of MEC operations using a 750 ng/mL mixture of drugs, there was no hydrogen or methane, but carbon dioxide was detected. When the concentration of the drug mixture was reduced to 170 ng/mL, MECs produced hydrogen and methane gas. Removal of the drugs during MEC operations was also analyzed using liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). Paroxetine, venlafaxine and ODV drugs were removed up to 99% by MECs. In conclusion, MECs could offer an alternative treatment method for wastewaters containing psychoactive pharmaceuticals with the added benefit of fuel hydrogen generation.
PCSK 9: A Link Between Inflammation and Atherosclerosis
Authors: Patriki Dimitri , Saravi Seyed Soheil Saeedi , Camici Giovanni G. , Liberale Luca , Beer Jürg H. 
Published: July 2021

:
Proprotein convertase subtilisin/Kexin 9 (PCSK 9) is revealed to be a key player in
lipid metabolism and, therefore, in the development and progression of atherosclerosis. PCSK
9 binds to the low-density lipoprotein (LDL) receptor, induces its degradation, and increases
circulating blood LDL. As a result, PCSK 9 inhibitors represent an essential pillar in cardiovascular
risk reduction therapies due to their highly sufficient LDL decreasing properties.
While the influence of PCSK 9 on lipid metabolism has been widely investigated, the full
pathophysiological spectrum of PCSK 9 is yet to be determined. Statins have already been
demonstrated to have beneficial anti-inflammatory effects. In this context, evidence suggests
that PCSK 9 also interferes with inflammatory processes, thereby contributing to the development
of atherosclerosis. As lipid metabolism on its own affects inflammatory processes, it
is difficult to distinguish between lipid-dependent and -independent inflammatory properties
of PCSK 9. A body of evidence has revealed that PCSK9 LDL-independently regulates the
secretion of pro-inflammatory cytokines and inflammation-underlying pathways in vascular
walls, whereas recent observations suggest that PCSK9 also interacts with lectin-like oxidized
LDL receptor-1 (LOX-1) and dampens inflammatory responses through LDL reduction. In
conclusion, this review provides mounting evidence indicating how PCSK9 promotes vascular
inflammation and subsequent atherosclerosis to shed light on the anti-inflammatory effects
of PCSK9 inhibitors in the prevention of atherosclerosis.
Recent Advances in Computer-aided Antiviral Drug Design Targeting HIV-1 Integrase and Reverse Transcriptase Associated Ribonuclease H
Authors: Xue Weiwei , Zhu Feng , Yang Fengyuan , Yang Jingyi , Zhang Zhao , Tu Gao , Yao Xiaojun 
Published: July 2021

:
Acquired immunodeficiency syndrome (AIDS) has been a chronic, life-threatening
disease for a long time. Though, a broad range of antiretroviral drug regimens is applicable
for the successful suppression of virus replication in human immunodeficiency virus type 1
(HIV-1) infected people. The mutation-induced drug resistance problems during the treatment
of AIDS forced people to continuously look for new antiviral agents. HIV-1 integrase (IN)
and reverse transcriptase associated ribonuclease (RT-RNase H), two pivotal enzymes in
HIV-1 replication progress, have gained popularity as druggable targets for designing novel
HIV-1 antiviral drugs. During the development of HIV-1 IN and/or RT-RNase H inhibitors,
computer-aided drug design (CADD), including homology modeling, pharmacophore, docking,
molecular dynamics (MD) simulation and binding free energy calculation, represent a
significant tool to accelerate the discovery of new drug candidates and reduce costs in antiviral
drug development. In this review, we summarized the recent advances in the design of single-
and dual-target inhibitors against HIV-1 IN or/and RT-RNase H as well as the prediction
of mutation-induced drug resistance based on computational methods. We highlighted the results
of the reported literatures and proposed some perspectives on the design of novel and
more effective antiviral drugs in the future.
Synthesis and Development of Indole Based 5-HT3 Receptor Antagonists
as Anti-Emetic Drugs in Oncology: An Update
Authors: Rivera-Fonseca Johana L. , González-Rivas Nelly , Unnamatla M. V. Basavanag , García-Eleno Marco A. , Reyes Horacio , López-Valdez L. Germán , Corona-Becerril David , Cuevas-Yañez Erick 
Published: July 2021

:
An important group of antiemetic drugs used in the treatment of nausea and vomiting
after chemotherapy containing an indole moiety in their structures, working as 5-
hydroxytryptamine type 3 serotonin receptor antagonist (5-HT3). This study focuses on compounds
bearing an indole core that present a 5-HT3 receptor antagonist activity, which have
been successfully used as antiemetic drugs for reducing chemotherapy adverse secondary effects
during cancer treatment. Their synthesis, biological activities, and some outstanding
characteristics are discussed, providing a general outlook towards the development of more
efficient antiemetic drugs.
Prediction Mechanism of Nevadensin as Antibacterial Agent against S.
sanguinis: In vitro and In silico Studies
Authors: Kurnia Dikdik , Shadrina Aldina Amalia Nur , Herdiyati Yetty , Wiani Ika , Satari Mieke Hemiawati 
Published: July 2021

Background:
Streptococcus sanguinis can contribute to tooth demineralization, which
can lead to dental caries. Antibiotics used indefinitely to treat dental caries can lead to bacterial
resistance. Discovering new antibacterial agents from natural products, like Ocimum basilicum,
will help combat antibiotic resistance. In silico analysis (molecular docking) can help determine
the lead compound by studying the molecular interaction between the drug and the target receptor
(MurA enzyme and DNA gyrase). It is a potential candidate for antibacterial drug development.

Objective:
The research objective is to isolate the secondary metabolite of O. basilicum extract that
exhibits activity against S. sanguinis through in vitro and in silico analysis.

Methods:
n-Hexane extract of O. basilicum was purified by combining column chromatography
with bioactivity-guided fractionation. The in vitro antibacterial activity against S. sanguinis was
determined using the disc diffusion and microdilution method, while molecular docking simulation
of nevadensin (1) with MurA enzyme and DNA gyrase was performed by using PyRx 0.8 program.

Results:
Nevadensin from O. basilicum was successfully isolated and characterized by
spectroscopic methods. This compound showed antibacterial activity against S. sanguinis with
MIC and MBC values of 3750 and 15000 μg/mL, respectively. In silico analysis showed that the
binding affinity to MurA was -8.5 Kcal/mol, and the binding affinity to DNA gyrase was -6.7
Kcal/mol. The binding of nevadensin-MurA is greater than fosfomycin-MurA. Otherwise,
Nevadensin-DNA gyrase has a weaker binding affinity than fluoroquinolone-DNA gyrase and
chlorhexidine-DNA gyrase.

Conclusion:
Nevadensin showed potential as a new natural antibacterial agent by inhibiting the
MurA enzyme rather than DNA gyrase.
KIAA0101 in Malignant Pleural Mesothelioma: A Potential Diagnostic
and Prognostic Marker
Authors: Liang Zongan , Lin Ping , Zhao Yuean , Li Xiaoqian 
Published: July 2021

Background:
Currently, there are no reliable diagnostic and prognostic markers for
Malignant Pleural Mesothelioma (MPM). The objective of this study was to identify hub genes that
could be helpful for diagnosis and prognosis in MPM by using bioinformatics analysis.

Materials and Methods:
The gene expression profiles were downloaded from the Gene Expression
Omnibus (GEO) database and The Cancer Genome Atlas (TCGA). Weighted Gene Co-expression
Network Analysis (WGCNA), LASSO regression analysis, Cox regression analysis, and Gene Set
Enrichment Analysis (GSEA) were performed to identify hub genes and their functions.

Results:
A total of 430 upregulated and 867 downregulated genes in MPM were identified based
on the GSE51024 dataset. According to the WGCNA analysis, differentially expressed genes were
classified into 8 modules. Among them, the pink module was most closely associated with MPM.
According to genes with GS > 0.8 and MM > 0.8, six genes were selected as candidate hub genes
(NUSAP1, TOP2A, PLOD2, BUB1B, UHRF1, KIAA0101) in the pink module. In the LASSO
model, three genes (NUSAP1, PLOD2, and KIAA0101) were identified with non-zero regression
coefficients and were considered as hub genes among the 6 candidates. The hub gene-based
LASSO model can accurately distinguish MPM from controls (AUC=0.98). Moreover, the high
expression level of KIAA0101, PLOD2, and NUSAP1 was associated with poor prognosis
compared to the low level in Kaplan–Meier survival analyses. After further multivariate Cox
analysis, only KIAA0101 (HR = 1.55, 95% CI = 1.05-2.29) was identified as an independent
prognostic factor among these hub genes. Finally, GSEA revealed that high expression of
KIAA0101 was closely associated with 10 signaling pathways.

Conclusion:
Our study identified several hub genes relevant to MPM, including NUSAP1,
PLOD2, and KIAA0101. Among these genes, KIAA0101 appears to be a useful diagnostic and
prognostic biomarker for MPM, which may provide new clues for MPM diagnosis and therapy.
Learning, Neurogenesis and Effects of Flavonoids on Learning
Authors: Almulla Asan Yalmaz Hasan , Mogulkoc Rasim , Baltaci Abdulkerim Kasim , Dasdelen Dervis 
Published: July 2021

Abstract:
Learning and memory are two of our mind's most magical abilities. Different brain regions
have roles to process and store different types of memories. The hippocampus is the part of the brain
responsible for receiving information and storing it in the neocortex. One of the most impressive characteristics
of the hippocampus is its capacity for neurogenesis which is a process, new neurons are
produced and then transformed into mature neurons and integrated into neural circuits. The neurogenesis
process in the hippocampus, an example of neuroplasticity in the adult brain, is believed to aid
hippocampal-dependent learning and memory. New neurons are constantly produced in the hippocampus
and integrated into the pre-existing neuronal network, this allows old memories already stored
in the neocortex to be removed from the hippocampus and replaced with new ones. Factors affecting
neurogenesis in the hippocampus may also affect hippocampal-dependent learning and memory. The
flavonoids can exert particularly powerful actions in mammalian cognition and improve hippocampaldependent
learning and memory by positively affecting hippocampal neurogenesis.
Cubosomes: Versatile Nanosized Formulation for Efficient Delivery of
Therapeutics
Authors: Kumar Amrish , Singhal Keshav , Kaushik Niranjan 
Published: July 2021

Abstract:
Cubosomes are bicontinuous cubic phase nanoparticles with a size range from 10-500
nm. They offer various advantages with some limitations at the production level, e.g., cubosomes
have the feature to encapsulate a large amount of the drug due to its large internal area owing to
cuboidal shape but limited in large scale production due to its high viscosity which is associated
with the problem in homogenization. This nanoparticulate formulation is compatible for administration
by various routes like oral, transdermal, topical, buccal, etc. The drug release mechanism from
cubosomes was reported to be dependent on the partition coefficient and diffusion process. Compared
with liposomes, cubosomes show many differences in various aspects like shape, size, ingredients,
and mode of action. The main ingredients for the preparation of cubosomes include lipids,
stabilizers, aqueous phase and therapeutic agents. Several methods have been reported for cubosomes,
including the top-down method, the bottom-up method and the adopted coarse method. For
the optimization of cubosomes, the key factors to be considered, which will affect the cubosomes
characteristics include the concentration of lipid, temperature and pH. At present, many research
groups are exploring the potential of cubosomes as biosensors and nanocarriers. Based on the latest
reports and research, this review illuminates the structure of the cubosomes, mechanism of the drug
release, different methods of preparation with factors affecting the cubosomes, application of cubosomes
in different sectors, differences from the liposomes, and their advantages.
Cervical Cancer Metastasis and Recurrence Risk Prediction Based on Deep Convolutional Neural Network
Authors: Ye Zixuan , Zhang Yunxiang , Liang Yuebin , Lang Jidong , Zhang Xiaoli , Zang Guoliang , Yuan Dawei , Tian Geng , Xiao Mansheng , Yang Jialiang 
Published: July 2021

Background:
Evaluating the risk of metastasis and recurrence of a cervical cancer patient is
critical for appropriate adjuvant therapy. However, current risk assessment models usually involve the
testing of tens to thousands of genes from patients’ tissue samples, which is expensive and timeconsuming.
Therefore, computer-aided diagnosis and prognosis prediction based on Hematoxylin and Eosin
(H&E) pathological images have received much attention recently.

Objective:
The prognosis of whether patients will have metastasis and recurrence can support accurate
treatment for patients in advance and help reduce patient loss. It is also important for guiding treatment
after surgery to be able to quickly and accurately predict the risk of metastasis and recurrence of a cervical
cancer patient.

Method:
To address this problem, we propose a hybrid method. Transfer learning is used to extract features,
and it is combined with traditional machine learning in order to analyze and determine whether
patients have the risks of metastasis and recurrence. First, the proposed model retrieved relevant patches
using a color-based method from H&E pathological images, which were then subjected to image preprocessing
steps such as image normalization and color homogenization. Based on the labeled patched
images, the Xception model with good classification performance was selected, and deep features of
patched pathological images were automatically extracted with transfer learning. After that, the extracted
features were combined to train a random forest model to predict the label of a new patched image.
Finally, a majority voting method was developed to predict the metastasis and recurrence risk of a patient
based on the predictions of patched images from the whole-slide H&E image.

Results:
In our experiment, the proposed model yielded an area under the receiver operating characteristic
curve of 0.82 for the whole-slide image. The experimental results showed that the high-level features
extracted by the deep convolutional neural network from the whole-slide image can be used to predict
the risk of recurrence and metastasis after surgical resection and help identify patients who might receive
additional benefit from adjuvant therapy.

Conclusion:
This paper explored the feasibility of predicting the risk of metastasis and recurrence from
cervical cancer whole slide H&E images through deep learning and random forest methods.
Withdrawal Notice: Identifying Genetic Related Neuroimaging Biomarkers of Alzheimer's Disease via Diagnosis-Guided Group Sparse Multitask Learning Method
Authors: Lin Anshi , Kong Wei , Wang Shuaiqun 
Published: July 2021

The article has been withdrawn at the request of the editor of the journal Current Bioinformatics CBIO due to
incoherent content:

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