bluuebunny/crossref_metadata_2025 huggingface dataset:
Another Image of Existence
Authors: Ferreira da Silva Denise , Desideri Valentina , Döcker Georg , Katsouraki Eve
Published: April 2022

Since 2015/2016, Denise Ferreira da Silva and Valentina Desideri have been engaging in a joint practice of so-called Poethical Readings, a device that engages the poetic and the ethical at the limits of the epistemology and ontology of the modern Subject. In this interview, Ferreira da Silva and Desideri provide insight into the singular and theatrical dynamics of Poetical Readings, as well as The Sensing Salon, a format for the collective exercise of Poethical Readings. They consider their practice with respect to the issue of power and the image of existence that undergirds modern politics, suggesting that Poethical Readings partake in the construction of a different image of existence no longer founded on the violent operations of the Subject. Having taken place in the autumn of 2020, that is, in the first year of the COVID-19 pandemic, the interview is framed by and addresses these issues through the discussion of the social ramifications of the corona crisis.
Brand-consumer relationship of female millennials toward K-beauty
Authors: Sari Adma , Sucherly  , Нasan Meydia , Marty Oesman Yevis
Published: April 2022

For the last decade, the Korean beauty market has skyrocketed in terms of sales. Despite differences in usage steps, culture, and geography, Korean beauty products are the fastest-growing market segment in Indonesia. In addition, they are aimed primarily at millennial consumers. Therefore, this study looked at the effect of the brand-consumer relationship on the experience of Korean beauty products in Indonesia. The research sample consisted of millennial female users. As a result, 255 valid responses were obtained. Using SEM Lisrel, the study revealed that all study hypotheses were accepted. All the variables had a significant influence on each other. Notably, brand commitment had the strongest impact, and it was significantly related to and contributed more to brand love. The contribution of this brand-consumer relationship stems from the fact that brand commitment is more consistent in achieving brand love than brand experience. Furthermore, it was found that brand experience is more subjective, resulting in irrational consumer behavior toward brand love.
Policy measures for economic resilience of Visegrad Group and Ukraine during the pandemic
Authors: Boiko Alina , Umantsiv Yurii , Cherlenjak Ivan , Prikhodko Volodymyr , Shkuropadska Diana
Published: April 2022

The COVID-19 pandemic has posed unprecedented healthcare and economic resilience challenges for the world. This study systematizes the policy measures taken by the Visegrad Group and Ukraine to support national economies in response to the pandemic. The paper is based on a grouping method to systematize the policy measures, and a tabular method to present the results of the policy measures classification. Following systematization results, the policy measures for ensuring the economic resilience under the pandemic are classified as quarantine and compensatory measures. Additionally, quarantine measures were classified into prohibitions, restrictions, and recommendations. Compensatory measures were classified by the type of policy and grouped according to the global dimension in periodization of the COVID-19 waves. The analysis of quarantine measures in Ukraine and Visegrad Group also shows that prohibitions had been used most frequently and for the longest time in Ukraine, particularly they included school closures, public transport closing, and restrictions on internal movement. Meanwhile, fiscal, macroprudential, and microprudential measures prevailed among the compensatory measures. Simultaneously, 38% of all fiscal measures were direct grants to households and enterprises. The largest number of various measures (78) were implemented in Poland, linking quarantine and compensatory measures. The least compensatory measures were implemented in Ukraine (19) and Slovakia (15). Overall, policy measures helped to avoid a worse scenario of pandemic impact but did not help to overcome the effects of the pandemic fully.
Impact of climate change on streamflow of Melka Wakena catchment, Upper Wabi Shebelle sub-basin, south-eastern Ethiopia
Authors: Fita Teshale , Abate Brook
Published: April 2022

Climate change is becoming a global concern, dictating the water resource availability of a certain region. This study focuses on the impact of climate change on the streamflow of the Melka Wakena reservoir in the Upper Wabi Shebelle sub-basin using a Soil Water Analysis Tool (SWAT). The climate model variables (precipitation and temperature) are obtained from the Coordinated Regional Downscaling Experiment (CORDEX-Africa) and applied under representative concentration pathway (RCP4.5) and (RCP8.5) scenarios. Bias correction was applied to the climate variables before transferring to the hydrological model (SWAT) to simulate discharge. The performance measures R2, NSE, and Percent Bias (PBIAS) for calibration and validation were 0.69, 0.65, and −5.10 and 0.65, 0.61, and −9.81, respectively. Streamflow was simulated for two consecutive periods from 2021 to 2050 and from 2051 to 2080 for both scenarios and compared with the base period from 1986 to 2015 to explore the impact of climate change on inflows to the reservoir. The result obtained showed that the precipitation was predicted to be mildly decreasing, whereas overall annual flow was projected to be insignificantly decreasing under RCP4.5 and RCP8.5 scenarios. The impact of climate change on the water resource of the study area was predicted to be a statistically insignificant reduction.
Study on optimization of coagulation-flocculation of fish market wastewater using bittern coagulant – response surface methodological approach
Authors: Bagastyo Arseto Yekti , Anggrainy Anita Dwi , Gatneh Syaima , Nurhayati Ervin , Susanti Diah , Widodo Erwin , Soehartanto Totok , Warmadewanthi IDAA
Published: April 2022

Bittern contains a high ionic strength that can be used as an alternative coagulant in wastewater treatment. The magnesium content in the bittern could promote the removal of suspended particles and nutrients as settleable precipitates. This would create a more compact and manageable sludge. This study investigates the performance of bittern as a coagulant for fish market wastewater treatment. The effectiveness of bittern was evaluated based on the efficiency of pollutants removal and the amount of residual magnesium. The experiments were performed using a standard jar test. Response surface methodology (RSM) based on a two-factor central composite design (CCD) was used to design the experiment. The parameters involved were pH (7.5, 9, and 10.5) and coagulant dose (0.5, 1.5, 2.5 mL L−1). The maximum removal efficiencies (i.e., 93.3% TSS, 87.5% COD, 37.6% ammonium, and 91.3% phosphate) were recorded at pH 10.5 and 1.5 mL L−1 dose of bittern, while the optimum results (desirability value of 0.929) may occur at pH 10.5 and a dose of 1.284 mL L−1. Approximately 51% of struvite and 48% of calcite precipitates were identified in the generated sludge, which can possibly be used as supplementary material in agrochemical industry with further treatment.
Synthesis of Ag/ZnO-AC composite photocatalyst: spectroscopic investigation, parameter optimization, synergistic effect and performance enhancement for cost-effective photocatalytic degradation of phenols and dyes
Authors: Shintre Surabhi N. , Wadhai Sachin , Thakur Pragati
Published: April 2022

A ternary photocatalyst composite-Silver decorated on ZnO supported with activated carbon (Ag/ZnO-AC) was investigated for the synthesis, characterization and UV assisted photocatalytic degradation of phenols and dyes present in wastewater. XPS and TEM revealed the elemental composition and formation of ternary Ag/ZnO-AC composite. Different operational parameters including the effect of calcination temperature, catalyst dose, initial concentration of pollutant and the effect of H2O2 and ethanol were studied. The photocatalytic activity was assessed for the degradation of p-Nitrophenol (PNP), o-Nitrophenol (ONP), and dye methyl orange (MO) under UV irradiation by ZnO, Ag/ZnO and Ag/ZnO-AC catalyst. The degradation for PNP, ONP and MO in presence of UV light were found to be in the order Ag/ZnO-AC>Ag/ZnO>ZnO. Improved degradation by Ag/ZnO-AC is attributed to high charge separation and greater adsorption of pollutant because of the combination of Ag and AC leading to a synergistic effect in the catalyst. Along with the high reusability, the composite catalyst Ag/ZnO-AC was found to be non-selective and cost-effective for the degradation of phenols as well as dyes. The as synthesized ternary composite Ag/ZnO-AC can be efficiently used as a photocatalyst for the degradation of recalcitrant and other deleterious contaminants present in wastewater.
Süveyş ve Panama Kanalı Çerçevesinde Kanal İstanbul’un Lojistik Potansiyelinin SWOT Analizi ile Değerlendirilmesi
Authors: Turğut Muhammed , Konbul Çağatay
Published: April 2022

Uluslararası ticaret, ülkeler açısından büyüme ve gelişmenin gerçekleşmesinde en önemli faktörlerden biridir. Küresel ticaretin kesintisiz gerçekleşmesinde ve başarıya ulaşmasında lojistik faaliyetler belirleyici olmaktadır. Lojistik faaliyetler içinde ise taşımacılık faaliyeti önemli bir yer tutmaktadır. Uluslararası ticarette önemli bir yere sahip olan taşımacılık faaliyetinin %85’ i denizyolu ile gerçekleşmektedir. Ülkelerinin birbirine bağlanmasında ve ticareti faaliyetlerde büyük orana sahip olan denizyolunun en önemli güzergâhları yapay ve doğal suyolları olarak nitelendirilen kanallar ve boğazlardır. Yapay su kanalları genel olarak mesafeden, zamandan ve lojistik maliyetlerden tasarruf etme amacıyla insan eliyle inşa edilmiş yollardır. Bu amaç doğrultusunda inşa edilen yapay su kanalları dünya ticaretine önemli katkı sağlamaktadır. Yapay su kanalları nakliye maliyetlerini düşürmede, tedarik sürelerini kısaltma ve enerji verimliliği sağlama açısından birçok avantaj oluşturmaktadır. Ayrıca yapay su kanalları sınırları içerisinde bulunan ülkelere ciddi gelir sağlamaktadır. Deniz taşımacılığını etkili kullanan ve konumu itibariyle jeopolitik öneme sahip olan ülkeler küresel ticarette söz sahibi olmaktadır. Türkiye’de sahip olduğu denizler, boğazlar ve limanlar sayesinde avantajlı bir durumdadır. Bu çalışmada küresel ticarette büyük bir yere sahip olan iki yapay su kanalı Süveyş ve Panama kanalı veriler ışığında incelenmiştir. Bu verilerin yanında mevcut İstanbul Boğazı istatistikleri de ele alınarak Kanal İstanbul’un lojistik potansiyeli değerlendirilmiştir.
Homomultimer Strategy for Improvement of Radiolabeled Peptides
and Antibody Fragments in Tumor Targeting
Authors: Ebrahimi Fatemeh , Hosseinimehr Seyed Jalal
Published: April 2022

A homomultimeric radioligand is composed of multiple identical ligands connected
to the linker and radionuclide to detect a variety of overexpressed receptors on
cancer cells. Multimer strategy holds great potential for introducing new radiotracers
based on peptide and monoclonal antibody (mAb) derivatives in molecular imaging and
therapy. It offers a reliable procedure for the preparation of biological-based targeting
with diverse affinities and pharmacokinetics. In this context, we provide a useful summary
and interpretation of the main results by a comprehensive look at multimeric radiopharmaceuticals
in nuclear oncology. Therefore, explanations for the strategy mechanisms
and the main variables affecting the biodistribution results will be explained. The
discussion is followed by highlights of recent work in the targeting of various types of receptors.
The consequences are expressed based on comparing some parameters between
monomer and multimer counterparts in each relevant section.
Ultramicronized Palmitoylethanolamide and Luteolin Supplement Combined
with Olfactory Training to Treat Post-COVID-19 Olfactory
Impairment: A Multi-Center Double-Blinded Randomized Placebo-
Controlled Clinical Trial
Authors: Di Stadio Arianna , D’Ascanio Luca , Vaira Luigi Angelo , Cantone Elena , De Luca Pietro , Cingolani Cristina , Motta Gaetano , De Riu Giacomo , Vitelli Federica , Spriano Giuseppe , De Vincentiis Marco , Camaioni Angelo , La Mantia Ignazio , Ferreli Fabio , Brenner Michael J.
Published: April 2022

Background:

Olfactory training is the only evidence-based treatment for post-viral olfactory
dysfunction. Smell disorders after SARS-CoV-2 infection have been attributed to neuroinflammatory
events within the olfactory bulb and the central nervous system. Therefore, targeting
neuroinflammation is one potential strategy for promoting recovery from post-COVID-19 chronic
olfactory dysfunction. Palmitoylethanolamide and luteolin (PEA-LUT) are candidate antiinflammatory/
neuroprotective agents.

Objective:

To investigate recovery of olfactory function in patients treated with PEA-LUT oral supplements
plus olfactory training versus olfactory training plus placebo.

Methods:

Multicenter double-blinded randomized placebo-controlled clinical trial was held. Eligible
subjects had prior COVID-19 and persistent olfactory impairment >6 months after follow-up
SARS-CoV-2 negative testing, without prior history of olfactory dysfunction or other sinonasal disorders.
Participants were randomized to daily oral supplementation with ultramicronized PEA-LUT
770 mg plus olfactory training (intervention group) or olfactory training with placebo (control).
Sniffin’ Sticks assessments were used to test the patients at baseline and 90 days.

Results:

A total of 185 patients, including intervention (130) and control (55) were enrolled. The intervention
group showed significantly greater improvement in olfactory threshold, discrimination,
and identification scores compared to controls (p=0.0001). Overall, 92% of patients in the intervention
group improved versus 42% of controls. Magnitude of recovery was significantly greater in the
intervention group versus control (12.8 + 8.2 versus mean 3.2 + 3), with >10-fold higher prevalence
of anosmia in control versus intervention groups at the 90-day endpoint.

Conclusion:

Among individuals with olfactory dysfunction post-COVID-19, combining PEA-LUT
with olfactory training resulted in greater recovery of smell than olfactory training alone.
Viruses Broaden the Definition of Life by Genomic Incorporation of Artificial
Intelligence and Machine Learning Processes
Authors: Stefano George B. , Kream Richard M.
Published: April 2022

Viruses have been classified as non-living because they require a cellular host to support
their replicative processes. Empirical investigations have significantly advanced our understanding of
the many strategies employed by viruses to usurp and divert host regulatory and metabolic processes to
drive the synthesis and release of infectious particles. The recent emergence of SARS-CoV-2 has permitted us to evaluate and discuss a potentially novel classification of viruses as living entities. The ability of SARS CoV-2 to engender comprehensive regulatory control of integrative cellular processes is
strongly suggestive of an inherently dynamic informational registry that is programmatically encoded
by linear ssRNA sequences responding to distinct evolutionary constraints. Responses to positive evolutionary constraints have resulted in a single-stranded RNA viral genome that occupies a threedimensional space defined by conserved base-paring resulting from a complex pattern of both secondary and tertiary structures. Additionally, regulatory control of virus-mediated infectious processes relies on extensive protein-protein interactions that drive conformational matching and shape recognition
events to provide a functional link between complementary viral and host nucleic acid and protein domains. We also recognize that the seamless integration of complex replicative processes is highly dependent on the precise temporal matching of complementary nucleotide sequences and their corresponding structural and non-structural viral proteins. Interestingly, the deployment of concerted transcriptional and translational activities within targeted cellular domains may be modeled by artificial intelligence (AI) strategies that are inherently fluid, self-correcting, and adaptive at accommodating temporal changes in host defense mechanisms. An in-depth understanding of multiple self-correcting AIassociated viral processes will most certainly lead to novel therapeutic development platforms, notably
the design of efficacious neuropharmacological agents to treat chronic CNS syndromes associated with
long-COVID. In summary, it appears that viruses, notably SARS-CoV-2, are very much alive due to
acquired genetic advantages that are intimately entrained to existential host processes via evolutionarily constrained AI-associated learning paradigms.
Anticancer Mechanism of D-limonene: An Updated Review and Therapeutic
Possibilities
Authors: Parija Tithi , Mandal Deepa
Published: April 2022

Background:

Despite remarkable advancement in screening, diagnosis, and treatment
modalities, cancer remains the second leading cause of death globally. Chemoprevention is considered
to be a potential strategy for dealing with cancer incidence and mortality. The present demand
for a less toxic well-tolerated natural anticancer compound that can be used for chemoprevention
has drawn the attention towards D-limonene, which is a monocyclic monoterpene found in citrus
oil. In recent years several in vitro and in vivo studies have supported the anticancer potential of
D-limonene in various cancers. Although these studies have highlighted its course of action through
immune modulation, anti-oxidant activity, apoptosis, autophagy, etc. various scientific pieces of
evidence support the fact that it targets multiple pathways to inhibit cancer.

Objective:

The current review focuses on the molecular mechanisms underlying the anticancer activity
of D-limonene and discusses its potential as a cost-effective chemopreventive and chemotherapeutic
drug alone or in combination with other drugs.

Methods:

Scientific databases like Web of Science, Scopus, PubMed, Google Scholar, PubMed
Central, etc. have been used to review new insights into the anticancer mechanism of D-limonene.

Conclusion:

In this review, we discussed the overall significance of the anticancer mechanisms of
D-limonene which include modulation of apoptosis, promotion of autophagy and inhibition of angiogenesis
and metastasis. D-limonene also inhibits oncogenic signaling molecules and related transcription
factors. Additionally, it also acts in combination with other anticancer compounds to
inhibit cancer.
Automated Cultivation System for Microalgae: Growth Factors and
Control
Authors: Chew Kit Wayne , Khor Jiun Gia , Lim Hooi Ren , Chia Wen Yi
Published: April 2022

Background:

Microalgae have been a hot research topic due to their various biorefinery
applications, particularly microalgae as potential alternative nutraceuticals and supplements
have a large and rapidly growing market. However, commercial production is limited due to high
processing cost, low efficiency, and scale up of biomass production.

Objective:

It is important to control the microalgae cultivation system with optimal parameters to
maximize biomass productivity. The growth factors, including pH, temperature, light intensity,
salinity, and nutrients, are discussed as these can significantly affect the cultivation. To monitor
and control these in real-time, an automated system incorporating advanced digital technologies
like sensors, controllers, artificial intelligence (AI), and the Internet of Things (IoT) could be applied.

Conclusion:

This perspective provides insights into the implementation of an automated microalgae
cultivation system that improves productivity, effectiveness, and efficiency.
Improved FCOS for Detecting Breast Cancers
Authors: Sun Desheng , Yuan Kehong , Wang Yingni , Lin Xiaona , Zhang Xuesheng , Ye Qingyu , Zhou Haiying , Zhang Renrong , Ge Shuang
Published: April 2022

Purpose:

Breast cancer ranks first among cancers affecting women's health. Our goal is to
develop a fast, high-precision, and fully automated breast cancer detection algorithm to improve the
early detection rate of breast cancer.

Methods:

We compare different object detection algorithms, including anchor-based and anchor-free
object detection algorithms for detecting breast lesions. Finally, we find that the fully convolutional onestage
object detection (FCOS) showed the best performance in the detection of breast lesions, which is
an anchor-free algorithm. 1) Considering that the detection of breast lesions requires the context information
of the ultrasound images, we introduce the non-local technique, which models long-range dependency
between pixels to the FCOS algorithm, providing the global context information for the detection
of the breast lesions. 2) The variety of shapes and sizes of breast lesions makes detection difficult.
We propose a new deformable spatial attention (DSA) module and add it to the FCOS algorithm.

Results:

The detection performance of the original FCOS is that the average precision (AP) for benign
lesions is 0.818, and for malignant lesions is 0.888. The FCOS with a non-local module improves the
performance of the breast detection; the AP of benign lesions was 0.819, and that of malignant lesions
was 0.894. Combining the DSA module with the FCOS improves the performance of breast detection;
the AP for benign lesions and malignant lesions is 0.840 and 0.899, respectively.

Conclusion:

We propose two methods to improve the FCOS algorithm from different perspectives to
improve its performance in detecting breast lesions. We find that FCOS combined with DSA is beneficial
in improving the localization and classification of breast tumors and can provide auxiliary diagnostic
advice for ultrasound physicians, which has a certain clinical application value.
Tensor Decomposition Based on Global Features and Sparse Structure for
Analyzing Cancer Multiomics Data
Authors: Yang Hang-Jin , Gao Ying-Lian , Kong Xiang-Zhen , Liu Jin-Xing
Published: April 2022

Background: There are correlations between the multiple types of data stored in the tensor
space. The matrix formed by the data in the high-dimensional space is of low rank. Therefore, the
potential association between genes and cancers can be explored in low-rank space. Tensor robust
principal component analysis (TRPCA) is used to extract information by obtaining coefficient tensors
with low-rank representation. In practical applications, global features and sparse structure are ignored,
which leads to incomplete analysis.

Objective: This paper proposes an adaptive reweighted TRPCA method (ARTRPCA) to explore cancer
subtypes and identify conjoint abnormally expressed genes (CAEGs).

Methods: ARTRCA analyzes data based on adaptive learning of primary information. Meanwhile,
the weighting scheme based on singular value updates is used to learn global features in low-rank
space. The reweighted I1 algorithm is based on prior knowledge, which is used to learn about sparse
structures. Moreover, the sparsity threshold of Gaussian entries has been increased to reduce the influence
of outliers.

Results: In the experiment of sample clustering, ARTRPCA has obtained promising experimental
results. The identified CAEGs are pathogenic genes of various cancers or are highly expressed in
specific cancers.

Conclusion: The ATRPCA method has shown excellent application prospects in cancer multiomics
data.
Role of Lysine-specific Demethylase 1 and Its Small Molecule Inhibitors in Glioblastoma
Multiforme Therapy
Authors: Mitra Rangan , Ayyannan Senthil Raja
Published: April 2022

Glioblastoma multiforme (GBM) is among the most critical and aggressive carcinomas of CNS, characterised
by poor prognosis, low survival rate and difficult clinical correlations. Current treatment opportunities have
proved to be insufficient due to high chemoresistance and relapse of the disease with enhanced malignancy. Molecular
diagnostics and epigenetic profiling of GBM have discovered several signaling pathways and cellular mediators, which
play key roles in triggering GBM phenotypic manifestations via somatic and genetic aberrations and recruitment of
GBM stem-like cells (GSCs). Lysine specific demethylase 1 (LSD1), a flavin-containing oxidoreductase encoded by
the KDM1A gene and containing the unique CoREST component, is an important histone-modifying enzyme
belonging to the histone demethylase (KDM) subfamily and is responsible for master regulation of several signaling
pathways in glioma cells. Pharmacological inhibition of LSD1, either individually or in a dual-targeted approach, is a
logical strategy for the management of GBM. The current review discusses the role of LSD1 in various epigenetic
modulations in differentiated glioma cells and GSCs. The 2D and 3D structural similarities/dissimilarities between
LSD1 and MAOs have been analysed and presented along with a detailed discussion on different chemical classes of
small molecule LSD1 inhibitors (both standalone and hybrid pharmacophores) that have shown promise in GBM
chemotherapy.
Recent Insights into Therapeutic Potential of Plant-Derived Flavonoids against
Cancer
Authors: Mohi-ud-din Roohi , Mir Reyaz Hassan , Sabreen Saba , Jan Rafia , Pottoo Faheem Hyder , Singh Inder Pal
Published: April 2022

Flavonoids, a class of polyphenolic secondary metabolites, are present in fruits, vegetables, beverages such
as wine and tea abundantly. Flavonoids exhibit a diverse array of pharmacological activities, including anticancer
activity, and are toxic to cancer cells but not harmful to healthy cells. Besides, humans and animals cannot synthesize
flavonoids, which leads to a dramatic increase in the consumption of plant flavonoids. Flavonoids consist of a 15-
carbon skeleton in C6-C3-C6 rings with divergent substitution patterns to form a series of compounds. Due to their
multi-faceted mechanism of action by modulating various signaling pathways associated with apoptosis, cellular proliferation,
inflammation, differentiation, metastasis, angiogenesis, they interrupt the initiation, promotion, and progression
of cancer. The present review highlights the Structural Activity Relationship (SAR) of flavonoids and recent insights
on the progress of natural flavonoids and their synthetic analogs as prospective drug candidates against cancer,
along with molecular mechanisms of action.
Reduction of Genotoxicity of Carbamazepine to Human Lymphocytes by
Pre-treatment with Vitamin B12
Authors: Khabour Omar F. , Hendawi Eman K. , Al-Eitan Laith N. , Alzoubi Karem H.
Published: April 2022

Background:

Carbamazepine (CBZ) is widely used as an anti-epileptic drug. Vitamin
B12 has been shown to protect against DNA damage caused by several mutagenic agents.

Objective:

This study aimed to investigate the effect of vitamin B12 on CBZ-induced genotoxicity
in cultured human lymphocytes.

Methods:

Sister chromatid exchanges (SCEs) and chromosomal aberrations (CAs) genotoxic assays
were utilized to achieve the study objective.

Results:

The results showed significantly higher frequencies of CAs and SCEs in the CBZ-treated
cultures (12 μg/mL) compared to the control group (P<0.01). The genotoxic effects of CBZ were
reduced by pre-treatment of cultures with vitamin B12 (13.5μg/ml, P<0.05). Neither CBZ nor vitamin
B-12 showed any effects on mitotic and proliferative indices.

Conclusion:

CBZ is genotoxic to lymphocyte cells, and this genotoxicity can be reduced by vitamin
B12.
Identification and Characterization of Novel Mutants of Nsp13 Protein among Indian SARS-CoV-2 Isolates
Authors: Kumari Deepa , Kumari Namrata , Kumar Sudhir , Sinha Prabhat Kumar , Shahi Shivendra Kumar , Biswas Nihar Ranjan , Kumar Abhay
Published: April 2022

Background:

SARS-CoV-2, the causative agent of COVID-19, has mutated rapidly, enabling it to adapt and evade the immune system of the host. Emerging SARS-CoV-2 variants with crucial mutations pose a global challenge in the context of therapeutic drugs and vaccines developing globally. There are currently no specific therapeutics or vaccines available to combat SARS-CoV-2 devastation. Concerning this, the current study aimed to identify and characterize the mutations found in the Nsp13 of SARS-CoV-2 in Indian isolates.

Methods:

In the present study, the Clustal omega tool was used for mutational analysis. The impact of mutations on protein stability, flexibility, and function was predicted using the DynaMut and PROVEAN tools. Furthermore, B-cell epitopes contributed by Nsp13 were identified using various predictive immunoinformatic tools.

Results:

Non-structural protein Nsp13 sequences from Indian isolates were analyzed by comparing them with the firstly reported Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) protein sequence in Wuhan, China. Out of 825 Nsp13 protein sequences, a total of 38 mutations were observed among Indian isolates. Our data showed that mutations in Nsp13 at various positions (H164Y, A237T, T214I, C309Y, S236I, P419S, V305E, G54S, H290Y, P53S, A308Y, and A308Y) have a significant impact on the protein's stability and flexibility. Moreover, the impact of Nsp13 mutations on protein function was predicted based on the PROVEAN score that indicated 15 mutants as neutral and 23 mutants as deleterious effects. Immunological parameters of Nsp13, such as antigenicity, allergenicity, and toxicity, were evaluated to predict the potential B-cell epitopes. The predicted peptide sequences were correlated with the observed mutants. Our predicted data showed that there are seven high-rank linear epitopes as well as 18 discontinuous B-cell epitopes based on immunoinformatic tools. Moreover, it was observed that out of the total 38 identified mutations among Indian SARS-CoV-2 Nsp13 protein, four mutant residues at positions 142 (E142), 245 (H245), 247 (V247), and 419 (P419) were localised in the predicted B cell epitopic region.

Conclusion:

Altogether, the results of the present in silico study might help to understand the impact of the identified mutations in Nsp13 protein on its stability, flexibility, and function.
CPAOR: Control Packet Aware On-demand Routing Protocol for WBANs
Authors: Raed Sara , Alabady Salah Abdulghani
Published: April 2022

Background & Objective:

The core problem of wireless body area network (WBAN)
nodes is their limited energy resource. Thus, an energy-efficient routing protocol is crucial to this type
of network. A major drawback of current routing protocols is that they do not consider the monitoring
of a large number of patients, which may be problematic in the event of disasters. In addition, most
routing algorithms fail to consider balancing energy consumption between nodes. Furthermore, routing
overhead (RO) and reduced complexity are required in this type of network.

Methods:

In this paper, we propose a control packet aware on-demand routing (CPAOR) protocol to
overcome the aforementioned drawbacks. The proposed protocol decreases the number of control
packets and adds awareness for the transmission of control packets, which can extend the network
lifetime.

Results and Discussion:

We analyze and examine the simulation results of the CPAOR protocol using
MATLAB in terms of energy consumption, the energy factor, RO, and changing the number of
nodes to more than 60 nodes. The CPAOR protocol demonstrates an improvement of 70.9% compared
to the DMQoS, ORACE-Net, and DLQoS protocols in terms of energy consumption. This finding
proves that the CPAOR protocol is an efficient routing protocol for WBANs.

Conclusion:

The CPAOR protocol has been proven to be an effective routing protocol for WBANs.
FAMILIA PTERIDACEAE
Authors:   Universidad Nacional Autónoma de México, Velázquez Montes Ernesto
Published: April 2022

La familia Pteridaceae es una de las más diversas de helechos, contiene entre 44 y 53 géneros y entre 950 y 1211 especies en el mundo. En México está representada por 32 géneros y alrededor de 218 especies. En la región de estudio se registran 16 géneros y 88 especies. Los primeros son: Adiantum, Anogramma, Aleuritopteris, Argyrochosma, Aspidotis, Astrolepis, Bommeria, Cheilanthes, Cheiloplecton, Hemionitis, Llavea, Mildella, Notholaena, Pellaea, Pityrogramma y Pteris.
Research for smart contract-based problem recommendation algorithm
Authors:   Department of Applied Software Engineering, University of Hanyang Cyber, Seoul, South Korea, Min Youn-A , Lim Dong-Kyun ,   Department of Applied Software Engineering, University of Hanyang Cyber, Seoul, South Korea
Published: April 2022

As a method for learners to learn independently in distance education, the need for a problem recommendation learning guide that effectively reflects a learning pattern based on learner data is increasing. In this paper, based on blockchain Ethereum smart contract technology, we analyze and present problem recommendation patterns for individual learners by filtering, collecting, and transparently managing multiple learner data that can occur in a distance education environment. In this study, various weighting factors were assigned to each learning situation. The optimal problem recommendation path is presented so that learners can solve problems based on weight-based learning factors in various learning situations. For the performance evaluation of this study, a similar learning environment was set up, and learning satisfaction, usefulness of problem recommendation guides, and learner data processing speed were analyzed. As a result of the performance evaluation, it was confirmed that the learning satisfaction improved by more than 15% compared to the existing learning environment in the proposed environment. In addition, it was confirmed that the learning data processing speed was improved by more than 17%.
Влияние температуры на электрофизические характеристики углеродосодержащих полимерных композитов
Authors: Зюзин А.М. , Карпеев А.А. , Янцен Н.В.
Published: April 2022

The influence of temperature on the electrophysical characteristics of polymer composites based on a matrix of ethylene vinyl acetate filled with carbon black (CB) is investigated. It is established that the most noticeable transformation of the temperature dependences of the resistivity ρ(T) after the first heating – cooling cycle occurs in composite samples saturated with peroxide. Saturation of the composite with peroxide and the crosslinking of macromolecules leads to the N-shaped character of the dependence ρ(T). The occurrence of hysteresis ρ(T) and its character indicate that in the studied composites, the process of crystallization of the polymer matrix has significantly less effect on the destruction of the conductive mesh formed as a result of agglomeration of CB particles compared with the processes accompanying melting.
Отрицательная обратная связь по току в ускоряющем промежутке в источниках электронов с плазменным катодом
Authors: Воробьёв М.С. , Москвин П.В. , Шин В.И. , Коваль Т.В. , Девятков В.Н. , Дорошкевич С.Ю. , Коваль Н.Н. , Торба М.С. , Ашурова К.Т.
Published: April 2022

Using the example of an electron source with a plasma cathode based on a low-pressure arc discharge with grid stabilization of the cathode/emission plasma boundary and an open anode/beam plasma boundary, a mechanism is described for increasing the electrical strength of a high-voltage accelerating gap by introducing a series negative current feedback (NCF) in the accelerating interval, which makes it possible to level out uncontrolled bursts of the beam current during its pulse. The introduction of NCF is achieved by using a special electrode in the space of the plasma emitter connected through a resistance to the anode of the arc discharge, and the main task of which is to intercept accelerated ions penetrating into the emitter from the high-voltage accelerating gap, due to which the current of electron emission from the arc discharge plasma decreases by a value proportional to the ion current in the accelerating gap. Since most sources and accelerators of electrons with plasma cathodes based on discharges of various types have a similar principle of operation, the use of this method will not only expand the limiting parameters of the generated electron beams, but also increase the stability of the operation of such electron sources, and, accordingly, beam irradiation of various materials and products.
Associations Between Addictive Behaviors, Individual Characteristics, and the Use of Gambling Services Within the World of Gaming: Cross-sectional Survey Study
Authors: Kisch Mark , Håkansson Anders
Published: April 2022

Background

Gambling within the world of gaming is an emerging phenomenon that may share common conceptual characteristics with traditional forms of gambling. The current literature suggests a higher degree of problematic behaviors in this gambling pattern, but studies are few, prompting for further research regarding individual characteristics and comorbid conditions associated with this activity.

Objective

The aim of the study is to investigate correlations between the use of gambling services within the world of gaming and individual characteristics and addictive behaviors including problem gambling.

Methods

A cross-sectional web survey was distributed to an existing panel of online respondents in Sweden. A total of 2001 respondents were included. Chi-square and Mann-Whitney U tests, followed by a logistic regression, were used in order to determine independent variables associated with gambling in the context of gaming.

Results

A total of 2.9% (58/1984) of respondents reported past-year gambling within gaming. Significant associations were found with male sex, younger age, history of treatment-seeking for alcohol problems, and higher Gaming Addiction Scale scores.

Conclusions

The demonstrated findings strengthen previously found associations between gambling in gaming and younger age, male sex, and problematic gaming behaviors. Additionally, the association with a history of treatment needs for alcohol problems adds to the previous impression of increased problem severity and comorbidity in within-gaming gamblers.
Crowdsourcing Medical Costs in Dermatology: Cross-sectional Study Analyzing Dermatologic GoFundMe Campaigns
Authors: Mark Erica , Sridharan Mira , Florenzo Brian , Schenck Olivia L , Noland Mary-Margaret B , Barbieri John S , Lipoff Jules B
Published: April 2022

Background

Crowdfunding for medical costs is becoming increasingly popular. Few previous studies have described the fundraising characteristics and qualities associated with success.

Objective

This study aimed to characterize and investigate the qualities associated with successful dermatological fundraisers.

Methods

This cross-sectional study of dermatological GoFundMe campaigns collected data, including demographic variables, thematic variables using an inductive qualitative method, and quantitative information. Linear regression examined the qualities associated with success, which are defined based on funds raised when controlling for campaign goals. Logistic regression was used to examine qualities associated with extremely successful campaigns, defined as those raising >1.5 times the IQR. Statistical significance was set at P<.05.

Results

A total of 2008 publicly available campaigns at the time of data collection were evaluated. Nonmodifiable factors associated with greater success included male gender, age 20-40 years, and White race. Modifiable factors associated with success included more updates posted to the campaign page, non–self-identity of the campaign creator, mention of a chronic condition, and smiling in campaign profile photographs.

Conclusions

Understanding the modifiable factors of medical crowdfunding may inform future campaigns, and nonmodifiable factors may have policy implications for improving health care equity and financing. Crowdfunding for medical disease treatment may have potential implications for medical privacy and exacerbation of existing health care disparities. This study was limited to publicly available GoFundMe campaigns. Potential limitations for this study include intercoder variability, misclassification bias because of the data abstraction process, and prioritization of campaigns based on the proprietary GoFundMe algorithm.
Natural Language Processing Methods and Bipolar Disorder: Scoping Review
Authors: Harvey Daisy , Lobban Fiona , Rayson Paul , Warner Aaron , Jones Steven
Published: April 2022

Background

Health researchers are increasingly using natural language processing (NLP) to study various mental health conditions using both social media and electronic health records (EHRs). There is currently no published synthesis that relates specifically to the use of NLP methods for bipolar disorder, and this scoping review was conducted to synthesize valuable insights that have been presented in the literature.

Objective

This scoping review explored how NLP methods have been used in research to better understand bipolar disorder and identify opportunities for further use of these methods.

Methods

A systematic, computerized search of index and free-text terms related to bipolar disorder and NLP was conducted using 5 databases and 1 anthology: MEDLINE, PsycINFO, Academic Search Ultimate, Scopus, Web of Science Core Collection, and the ACL Anthology.

Results

Of 507 identified studies, a total of 35 (6.9%) studies met the inclusion criteria. A narrative synthesis was used to describe the data, and the studies were grouped into four objectives: prediction and classification (n=25), characterization of the language of bipolar disorder (n=13), use of EHRs to measure health outcomes (n=3), and use of EHRs for phenotyping (n=2). Ethical considerations were reported in 60% (21/35) of the studies.

Conclusions

The current literature demonstrates how language analysis can be used to assist in and improve the provision of care for people living with bipolar disorder. Individuals with bipolar disorder and the medical community could benefit from research that uses NLP to investigate risk-taking, web-based services, social and occupational functioning, and the representation of gender in bipolar disorder populations on the web. Future research that implements NLP methods to study bipolar disorder should be governed by ethical principles, and any decisions regarding the collection and sharing of data sets should ultimately be made on a case-by-case basis, considering the risk to the data participants and whether their privacy can be ensured.
Integrating Google Trends Search Engine Query Data Into Adult Emergency Department Volume Forecasting: Infodemiology Study (Preprint)
Authors: Trevino Jesus , Malik Sanjeev , Schmidt Michael
Published: April 2022

BACKGROUND

The search for health information from web-based resources raises opportunities to inform the service operations of health care systems. Google Trends search query data have been used to study public health topics, such as seasonal influenza, suicide, and prescription drug abuse; however, there is a paucity of literature using Google Trends data to improve emergency department patient-volume forecasting.

OBJECTIVE

We assessed the ability of Google Trends search query data to improve the performance of adult emergency department daily volume prediction models.

METHODS

Google Trends search query data related to chief complaints and health care facilities were collected from Chicago, Illinois (July 2015 to June 2017). We calculated correlations between Google Trends search query data and emergency department daily patient volumes from a tertiary care adult hospital in Chicago. A baseline multiple linear regression model of emergency department daily volume with traditional predictors was augmented with Google Trends search query data; model performance was measured using mean absolute error and mean absolute percentage error.

RESULTS

There were substantial correlations between emergency department daily volume and Google Trends “hospital” (r=0.54), combined terms (r=0.50), and “Northwestern Memorial Hospital” (r=0.34) search query data. The final Google Trends data–augmented model included the predictors Combined 3-day moving average and Hospital 3-day moving average and performed better (mean absolute percentage error 6.42%) than the final baseline model (mean absolute percentage error 6.67%)—an improvement of 3.1%.

CONCLUSIONS

The incorporation of Google Trends search query data into an adult tertiary care hospital emergency department daily volume prediction model modestly improved model performance. Further development of advanced models with comprehensive search query terms and complementary data sources may improve prediction performance and could be an avenue for further research.
COVID-19 Return to Sport: NFL Injury Prevalence Analysis (Preprint)
Authors: Puga Troy B , Schafer Joshua , Agbedanu Prince N , Treffer Kevin
Published: April 2022

BACKGROUND

Sport injuries have been common among athletes across the globe for decades and have the potential to disrupt athletic careers, performance, and psyche. Many health professionals and organizations have undertaken injury mitigation strategies to prevent sport injuries through protective equipment, training protocols, and a host of other evidence-based practices. Many of these specialized training methods were disrupted due to protocols to mitigate the spread of COVID-19. This research examines the effects of the COVID-19 pandemic in relation to the prevalence of athletic injuries in the National Football League (NFL).

OBJECTIVE

During the COVID-19 pandemic, NFL teams and athletes across all levels of sport were reported to have reduced training in preparation for their seasons due to protocols to mitigate the spread of COVID-19. This study compares the prevalence of injury during the 2018, 2019, and 2020 NFL seasons, with the aim to determine the potential causes of the differences in injury prevalence.

METHODS

Official injury reports from each team were counted during the 17-week regular season of each year (2018, 2019, and 2020). The data were analyzed using an unpaired t test to compare the injury prevalence between each of the three seasons.

RESULTS

The 2018 season produced a total of 1561 injuries and a mean of 48.8 injuries per team. The 2019 season produced a total of 1897 injuries and a mean of 59.3 injuries per team, while the 2020 season produced a total of 2484 injuries and a mean of 77.6 injuries per team. An unpaired t test was performed using the data to compare the mean number of injuries per team during each of the seasons. Comparison of the 2020 season against the 2019 season showed a statistically significant difference (P<.001); comparison of the 2020 season to the 2018 season found a statistically significant difference (P<.001); and comparison between the 2019 and the 2018 seasons found a statistically significant difference (P=.03).

CONCLUSIONS

Although the 2019 and 2018 seasons showed a statistically significant difference (P=.03), this difference is not as large when we compare the 2020 seasons versus the 2019 (P<.001) and 2018 (P<.001) seasons. The astronomical increase in injury prevalence during the 2020 season over the previous years raises the possibility that there was a reduced physiological adaptation to stress, due to the limited amount of training as a result of the closure of practice facilities in order to slow the spread of COVID-19.