bluuebunny/crossref_metadata_2025 huggingface dataset:
Penggemblengan Sumber Islam Sebagai Manifestasi Utama Pembinaan Falsafah Kritikan Sastera Islam Sayyid Sayyid Abd al-Raziq: Analisis Karya Manhaj al-Islami fi al-Naqd al-Adabi (The Abolition of Islamic Sources as a Main Manifestation of the Philosophy of Islamic Literary Criticism Sayyid Sayyid Abd al-Raziq: Analysis of the Book of Manhaj al-Islami fi al-Naqd al-Adabi)
Authors: Muhammad Nawawi Mohd Adi Amzar , Zakaria Mohd Fahimi
Published: October 2021

This study aims to look at the fusion of Islamic sources applied by Sayyid Sayyid cAbd al-Raziq as his main work in developing a unique and distinctive Islamic literary philosophy. On the one side, it is his effort and reflection on the refinement of the philosophical framework of Islamic literature that is considered to be entirely non-Islamic and largely dependent on Western ideas. As a result there are significant contradictions in Islamic values and this has prompted al-Raziq to produce a work that refines these issues. This study applied qualitative methods in the design of content analysis by analyzing the primary source, Manhaj al-Islami fi al-Naqd al-Adabi. The findings of the study have found that al-Raziq has optimally used Islamic sources as his primary vehicle in producing a philosophy of literary criticism that is truly Islamic. This is reflected in his efforts through the fusion of Islamic sources including the Qur'an, Hadith and also ethical interpretations in the scope of his philosophical debates including al-Turath al-Islami, al-Turath al-Jahili and al-Turath al-Madi.
Bayesian Optimization LSTM/bi-LSTM Network With Self-Optimized Structure and Hyperparameters for Remaining Useful Life Estimation of Lathe Spindle Unit
Authors: Thoppil Nikhil M. , Vasu V. , Rao C. S. P.
Published: October 2021

An effective maintenance strategy to cut back maintenance costs and production loss with assured product quality has always been a major concern for industries. The Industry 4.0 era has built a wide acceptance for the predictive maintenance techniques in the remaining useful life (RUL) estimation of critical industrial systems. In this paper, long short-term memory (LSTM) and bidirectional-LSTM (bi-LSTM) deep neural architecture-based predictive algorithms are proposed for the RUL estimation of the lathe spindle unit. The deep learning algorithm is embedded within a Bayesian optimization algorithm for the self-optimization of its network structure and hyperparameters. The proposed deep learning algorithm is trained using lathe spindle health degradation data collected from an experimental accelerated run-to-failure test rig to evolve an RUL prediction model. The vibration signals representing lathe spindle health degradation from the health to faulty state are analyzed to extract time, frequency, and time-frequency domain features, which are then subjected to a neighborhood component analysis (NCA) based feature selection criteria. Finally, the selected relevant features are used to train the optimized LSTM/bi-LSTM network for RUL estimation. A comparison of the prediction results for Bayesian optimized LSTM/bi-LSTM network architectures and other prominent data-driven approaches are performed. The Bayesian optimized LSTM + bi-LSTM deep network architecture is observed to have the highest prediction accuracy for lathe spindle RUL estimation.
The depth of Jupiter’s Great Red Spot constrained by Juno gravity overflights
Authors: Parisi Marzia , Kaspi Yohai , Galanti Eli , Durante Daniele , Bolton Scott J. , Levin Steven M. , Buccino Dustin R. , Fletcher Leigh N. , Folkner William M. , Guillot Tristan , Helled Ravit , Iess Luciano , Li Cheng , Oudrhiri Kamal , Wong Michael H.
Published: October 2021

Measuring the depth of Jupiter’s storms

The atmosphere of Jupiter consists of bands of winds rotating at different rates, punctuated by giant storms. The largest storm is the Great Red Spot (GRS), which has persisted for more than a century. It has been unclear whether the storms are confined to a thin layer near the top of the atmosphere or if they extend deep into the planet. Bolton
et al
. used microwave observations from the Juno spacecraft to observe several storms and vortices. They found that the storms extended below the depths at which water and ammonia are expected to condense, implying a connection with the deep atmosphere. Parisi
et al
. analyzed gravity measurements taken while Juno flew over the GRS. They detected a perturbation in the planet’s gravitational field caused by the storm, finding that it was no more than 500 kilometers deep. In combination, these results constrain how Jupiter’s meteorology links to its deep interior. —KTS
Electrically switchable metallic polymer nanoantennas
Authors: Karst Julian , Floess Moritz , Ubl Monika , Dingler Carsten , Malacrida Claudia , Steinle Tobias , Ludwigs Sabine , Hentschel Mario , Giessen Harald
Published: October 2021

Switching a polymer

Electrically switchable metasurfaces and plasmonic materials will enable the development of active nanophotonic technology. Karst
et al
. show that a metallic polymer can be used for electrical switching of plasmonic nanoantenna resonances. The plasmonic resonance can be completely switched ON and OFF with switching speeds up to 30 hertz (video rate), low switching voltages of ±1 volt (complementary metal-oxide semiconductor compatible), and a switching contrast of 100%. The results could have applications in nanophotonic devices such as those used in augmented and virtual reality imaging applications. —ISO
The translational neuroscience of sleep: A contextual framework
Authors: Grandner Michael A. , Fernandez Fabian-Xosé
Published: October 2021

Sleep is entwined across many physiologic processes in the brain and periphery, thereby exerting tremendous influence on our well-being. Yet sleep exists in a social-environmental context. Contextualizing sleep health with respect to its determinants—from individual- to societal-level factors—would enable neuroscientists to more effectively translate sleep health into clinical practice. Key challenges and opportunities pertain to (i) recognizing and exploring sleep’s functional roles, (ii) clarifying causal mechanisms in relation to key outcomes, (iii) developing richer model systems, (iv) linking models to known contextual factors, and (v) leveraging advances in multisensory technology. Meeting these challenges and opportunities would help transcend disciplinary boundaries such that social-environmental considerations related to sleep would become an ever-greater presence in the clinic.
The simplest of slumbers
Authors: Pennisi Elizabeth
Published: October 2021

Evidence from evolutionarily ancient creatures is revealing that sleep is not just for the brain
Contiguous Genome Sequence of
Frankia
sp. Strain ArI3, Isolated from Root Nodules of Alnus rubra Bong
Authors: Bell Callum J. , Sena Johnny A. , Gifford Isaac S. , Berry Alison M.
Published: October 2021

We report the genome sequence of
Frankia
sp. strain ArI3, recovered as a single contig from one run of the Oxford Nanopore Technologies (ONT) MinION instrument. The genome has a G+C content of 72%, is 7,541,222 bp long, and contains 5,427 predicted protein-coding genes.
Refractory pain in a schizophrenic patient on clozapine
Authors: Asiimwe Edgar , DeFraites Emily , Feher Csilla
Published: October 2021

A 36-year-old man with schizophrenia, on two times per day clozapine, presented with a 2-year history of diffuse intermittent body pain.

Per chart review—and on presentation—his physical examination had been consistently unremarkable, without point-tenderness elicited at any major muscle groups or focal neurological deficits. Workup for myopathy, neuropathy and supratherapeutic clozapine levels had similarly been unrevealing.

Given that prior interventions had been unsuccessful in alleviating these symptoms, we queried whether clozapine might have been contributory. As a result, we adopted a previously described strategy of scheduling the bulk of patients’ medication during non-waking hours.

At 1-month follow-up, the patient reported about a 50% improvement in his symptoms. At 6-month follow-up, this improvement in symptoms had been sustained.

Our findings add to the limited anecdotal reports of this side effect whose true prevalence remains unknown. Timely recognition has the potential to promote adherence to therapy among patients in the maintenance phase.
Adherence to treatment and prevalence of side effects when medical abortion is delivered via telemedicine: a prospective observational cohort study during COVID-19
Authors: Reynolds-Wright John Joseph , Johnstone Anne , McCabe Karen , Evans Emily , Cameron Sharon
Published: October 2021

Background

The Scottish government introduced legislation during the COVID-19 outbreak to permit medical abortion at home with telemedicine. All women received an initial telephone consultation. For those choosing medical abortion, we provided self-administered medications to eligible women with pregnancies under 12 weeks’ gestation.

Aims

To assess adherence to the recommended abortion drug regimen, with particular focus on the number of misoprostol doses used and the interval between mifepristone and misoprostol administration and the induction–expulsion interval. Additionally, to evaluate use of analgesia, antiemetics and antibiotics, and the side effects, pain and bleeding profile of medical abortion at home.

Methods

We conducted a prospective cohort study of 663 women choosing medical abortion at home via telemedicine at an NHS abortion service in Edinburgh, Scotland between 1 April and 9 July 2020. Interviewer-administered questionnaires were completed at telephone follow-up 4 and 14 days following treatment. Outcome measures were self-reported and included use of mifepristone and misoprostol, induction–expulsion interval (time from misoprostol administration until expulsion of pregnancy), antiemetics, antibiotics, analgesia use, pain scores, rates of side effects, bleeding and preparedness for treatment.

Results

Among the respondents, 652/663 women (98%) answered at least one questionnaire, and 594/663 (89.6%) used both abortion medications as directed (24–72 hours between medications). The mean (SD) induction–expulsion interval was 4.3 (4.3) hours. Antiemetics were used by 611/663 (92%), 383/599 (64%) completed the course of prophylactic antibiotics, and 616/663 (93%) used analgesia, with mean (SD) worst-pain scores of 6.7 (2.2) out of 10. Regarding side effects, 510/663 (77%) experienced either nausea, vomiting, diarrhoea or headache, 101/663 (15%) experienced headache and 510/663 (77%) experienced bleeding that was heavier than a period; 554/663, (84%) felt prepared for their treatment by teleconsultation.

Conclusion

Patients are able to correctly self-administer abortion medications following a telemedicine consultation. Further research is required to optimise pain management and gastrointestinal side effects during medical abortion.
Following the thread: Mytilus mussel byssus as an inspired multi-functional biomaterial
Authors: Waite J. Herbert , Harrington Matthew J.
Published: October 2021

Over the last 15 years, the byssus of marine mussels (Mytilus spp.) has emerged as an important model system for the bio-inspired development and synthesis of advanced polymers and adhesives. But how did these seemingly inconsequential fibers that are routinely discarded in mussel hors d’oeuvres become the focus of intense international research. In the present review, we take a historical perspective to understand this phenomenon. Our purpose is not to review the sizeable literature of mussel-inspired materials, as there are numerous excellent reviews that cover this topic in great depth. Instead, we explore how the byssus became a magnet for bio-inspired materials science, with a focus on the specific breakthroughs in the understanding of composition, structure, function, and formation of the byssus achieved through fundamental scientific investigation. Extracted principles have led to bio-inspired design of novel materials with both biomedical and technical applications, including surgical adhesives, self-healing polymers, tunable hydrogels, and even actuated composites. Continued study into the byssus of Mytilid mussels and other species will provide a rich source of inspiration for years to come.
Intercropping organic field peas with barley, oats, and mustard improves weed control but has variable effects on grain yield and net returns
Authors: Bailey-Elkin Will , Carkner Michelle , Entz Martin H.
Published: October 2021

Interest in intercropping semi-leafless field peas (Pisum sativum L.) is increasing as a means of weed control in organic production. We evaluated field pea (cv. CDC Amarillo) grown alone or intercropped with three seeding rates of either barley (Hordeum vulgare L.), mustard (Brassica juncea L.), or oat (Avena sativa L.). A full seeding rate of field pea was used in each instance, resulting in an additive intercropping design. Each crop combination was conducted in a separate experiment, three times over two years (2019 and 2020) in Carman, MB. Measurements included crop and weed biomass production, grain yield and quality, and net return. Intercrops reduced weed biomass at maturity from 17% to 44% with barley and oat being more suppressive than mustard. Intercrops also reduced field pea yield from 6% to 26%, but increased field pea seed mass. Barley at the high seeding rate provided the most weed suppression per unit of field pea yield loss (2.62 kg of weed suppression per kg of field pea yield loss) compared with oat (1.29) and mustard (0.87). Barley and mustard intercrops decreased net return compared with monoculture field pea. Under low weed pressure (1150 kg·ha−1 weed biomass at maturity) and earlier seeding, oat intercrops reduced net return. However, under weedy conditions (2649 kg·ha−1) and later seeding, field pea-oat intercrops significantly increased net return. In conclusion, while all three intercrop mixtures reduced weed biomass, reductions in field pea yields were observed, and net return benefits were observed only in certain circumstances.
Computer Simulation on Polymer Micelles Combined Administration of Gambogic Acid and Curcumin as a Novel Anti-Cancer Drug Carrier
Authors: Wang Jinglei , Guo Mingrui , Lu Feifei , Pan Hao , Liu Mingxia , Lin Bin , Qu Na , Chen Lijiang
Published: October 2021

Purpose: The poor efficacy of traditional antitumor drugs in the treatment of cancer is mainly due to poor water solubility, systemic cytotoxicity, poor tumor targeting and other factors. In recent years, the nano-drug system has been widely studied in tumor therapy and drug targeting, but the design process requires repeated experiments, which are time consuming and laborious. In this context, we developed a novel synergistic co-delivery nanomicelle of gambogic acid and curcumin through molecular dynamics (MD) and dissipative particle dynamics (DPD) simulation.

Methods: The synergistic effect was verified by the comprehensive index, apoptosis, reactive oxygen species (ROS) detection, and apoptosis-related protein experiments. MD and DPD simulations were utilized to design micelles. According to the results, methoxypolyethylene glycol (mPEG)-gambogic acid (GA)-curcumin (CU) micelles were synthesized and prepared for the co-delivery of GA and curcumin, and then, the micelles were characterized and released in vitro. Finally, a cytotoxicity study of micelles was carried out to prove its anti-tumor effect.

Results: It was verified that the combined administration of GA and curcumin showed a synergistic effect in tumor cells (HepG2) and an antagonistic or weak synergistic effect in normal cells (BV2, HEK293). According to the design of computer simulation, mPEG-GA-CU micelles were synthesized and characterized. Cytotoxicity experiments proved that mPEG-GA-CU micelles are more toxic to HepG2 cells than BV2, HEK293 cells.

Conclusions: Studies have shown that the mPEG-GA-CU nanomicelles designed by computer simulation have the ability to co-deliver drugs, play a synergistic anti-tumor effect, and have great potential in further anti-cancer practical applications.
Knowledge-based systems for blockchain-based cognitive cloud computing model for security purposes
Authors: Zhang Honglei , Zang Zhenbo , Muthu BalaAnand
Published: October 2021

Today, artificial intelligence (AI) can use the most powerful edge computing systems in the Internet of Things (IoT) for finding the information extracted from vast sensory data such as cyber effects or models in physical environments for classification, identification, and prediction. Heterogeneous IoT devices produce isolated and dispersed information parts, and knowledge sharing and exchange in IoT intelligent applications with several selfish nodes are necessary for complex tasks. In both academia and business, IoT is driving a digital revolution. However, protection and IoT privacy problems are challenged. It offers comfort for everyday lives. Blockchain, a shared cryptographic database, is a promising IoT encryption solution for several manufacturing, finance, and trade sectors. The IoT-based blockchain architecture is an interesting contrast to the conventional, centralized paradigm that struggles to fulfill specific IoT requirements. New concepts for applying data and resources management protection procedures in distributed networks and cloud computing are introduced. Cloud management services can be linked to the application through blockchain technology and distributed leader, a stable cognitive information system that facilitates management operations and securing data. This document provides many ideas for applying personal and behavioral characteristics to security and cryptography protocols, blockchain based on the cognitive cloud computing (BC-CCC) pattern. The simulation result shows that the proposed strategy can significantly enhance data transmission rate (96.2%), security ratio (94.5%), throughput ratio (92.4%), scalability ratio (91.5%), trust rate (93.8%), data trading ratio (96.2%), and reduce storage cost rate (25.1%) compared to other existing methods.
Blastocyst Prediction of Day-3 Cleavage-Stage Embryos Using Machine Learning
Authors: Nguyen Dung P. , Pham Quan T. , Tran Thanh L. , Vuong Lan N. , Ho Tuong M.
Published: October 2021

Background: Embryo selection plays an important role in the success of in vitro fertilization (IVF). However, morphological embryo assessment has a number of limitations, including the time required, lack of accuracy, and inconsistency. This study determined whether a machine learning-based model could predict blastocyst formation using day-3 embryo images.

Methods: Day-3 embryo images from IVF/intracytoplasmic sperm injection (ICSI) cycles performed at My Duc Phu Nhuan Hospital between August 2018 and June 2019 were retrospectively analyzed to inform model development. Day-3 embryo images derived from two-pronuclear (2PN) zygotes with known blastocyst formation data were extracted from the CCM-iBIS time-lapse incubator (Astec, Japan) at 67 hours post ICSI, and labeled as blastocyst/non-blastocyst based on results at 116 hours post ICSI. Images were used as the input dataset to train (85%) and validate (15%) the convolutional neural network (CNN) model, then model accuracy was determined using the training and validation dataset. The performance of 13 experienced embryologists for predicting blastocyst formation based on 100 day-3 embryo images was also evaluated.

Results: A total of 1,135 images were allocated into training ([Formula: see text] 967) and validation ([Formula: see text] 168) sets, with an even distribution for blastocyst formation outcome. The accuracy of the final model for blastocyst formation was 97.72% in the training dataset and 76.19% in the validation dataset. The final model predicted blastocyst formation from day-3 embryo images in the validation dataset with an area under the curve of 0.75 (95% confidence interval [CI] 0.69–0.81). Embryologists predicted blastocyst formation with the accuracy of 70.07% (95% CI 68.12%–72.03%), sensitivity of 87.04% (95% CI 82.56%–91.52%), and specificity of 30.93% (95% CI 29.35%–32.51%).

Conclusions: The CNN-based machine learning model using day-3 embryo images predicted blastocyst formation more accurately than experienced embryologists. The CNN-based model is a potential tool to predict additional IVF outcomes.
Acetylenic Sulfones and Acetylenic Sulfonamide Analogs: A Novel and Preferable Antimicrobial Drugs Based on Computational Strategies
Authors: Varani Tania , Abdouss Majid , Azerang Parisa , Tahghighi Azar
Published: October 2021

This study was done to report virtual screening and molecular docking studies of sulfacetamide derivatives as new antimicrobial drugs, belonging to the pharmacological class of sulfonamides. For this purpose, sulfonamide functional groups from a library of chemical structures were converted into acetylenic sulfone and acetylenic sulfonamide functional groups to introduce a new class of antimicrobial drugs with mechanisms of action of dihydropteroate synthase inhibitors (DHPS). Initially, a library of compounds containing approximately 170 acetylenic sulfone ligands was created by similarity search method, and a library containing 170 acetylenic sulfonamide ligands was designed to be administered as new inhibitors. After designing, their molecular docking energies were calculated by three software programs including Arguslab4.0.1, AutoDock Vina and Molegro Virtual Docker and the results were compared in terms of binding energy. Although acetylenic sulfonamide compounds showed better results, acceptable results were observed in both groups of compounds. Adsorption, distribution, metabolism and excretion (ADME) properties of acetylenic sulfones/acetylenic sulfonamide analogs were also analyzed using the admetSAR program. These new derivatives can be used in drug improvement processes for the treatment of antibacterial infections after performing further studies.
Anomalous Dielectric Behavior in Co-Doped TiO2 Nanotubes: Effect of Oxygen Vacancy Mediated Defect Dipole Pairs
Authors: Vijayan P Pournami , Vijayan P Poornima , Chandran Anoop , George K. C.
Published: October 2021

Titanium dioxide (TiO2) nanotubes are considered to be unique in terms of their physical properties and high dielectric constant. The oxygen vacancies in TiO2 play a crucial role in the dielectric behavior, which can be tuned by doping with proper materials. Herein, the changes in the dielectric behavior, as well as defect concentration of TiO2 nanotubes by Cobalt (Co) doping, have been evaluated. For this purpose, Co-doped TiO2 nanotubes have been synthesized by using combined sol-gel and hydrothermal methods. By analyzing photoluminescence spectra, the intensities and positions of five emission peaks are clearly assigned. The PL peaks could be sensibly explained by various mechanisms, such as direct allowed transition, oxygen vacancies, and self-trapped excitons. The dielectric behavior of Co-doped TiO2 nanotubes with controlled oxygen vacancies is explained. The dielectric constant is particularly at its highest in higher Co-doped TiO2 nanotubes. The current investigation provides new insight into the mechanisms underlying the anomalous dielectric properties shown by Co-doped TiO2 nanotubes, as evident from the movement of oxygen vacancies. It demonstrates the influence of defect dipoles, 2CoTi—Vȯ••, in the anomalous dielectric behavior observed for Co-doped TiO2 nanotubes.
Ral GEF with the PH Domain and SH3 Binding Motif 1 Regulated by Splicing Factor Junction Plakoglobin and Pyrimidine Metabolism Are Prognostic in Uterine Carcinosarcoma
Authors: Guo Hongjun , Wang Siqiao , Xie Aiqing , Sun Wenhuizi , Wei Chenlu , Xian Shuyuan , Yin Huabin , Li Mingxiao , Sun Hanlin , Li Hong , Meng Tong , Zhang Jie , Huang Zongqiang
Published: October 2021

Uterine carcinosarcoma (UCS) is a highly invasive malignant tumor that originated from the uterine epithelium. Many studies suggested that the abnormal changes of alternative splicing (AS) of pre-mRNA are related to the occurrence and metastasis of the tumor. This study investigates the mechanism of alternative splicing events (ASEs) in the tumorigenesis and metastasis of UCS. RNA-seq of UCS samples and alternative splicing event (ASE) data of UCS samples were downloaded from The Cancer Genome Atlas (TCGA) and TCGASpliceSeq databases, several times. Firstly, we performed the Cox regression analysis to identify the overall survival-related alternative splicing events (OSRASEs). Secondly, a multivariate model was applied to approach the prognostic values of the risk score. Afterwards, a coexpressed network between splicing factors (SFs) and OSRASEs was constructed. In order to explore the relationship between the potential prognostic signaling pathways and OSRASEs, we fabricated a network between these pathways and OSRASEs. Finally, validations from multidimension platforms were used to explain the results unambiguously. 1,040 OSRASEs were identified by Cox regression. Then, 6 OSRASEs were incorporated in a multivariable model by Lasso regression. The area under the curve (AUC) of the receiver operator characteristic (ROC) curve was 0.957. The risk score rendered from the multivariate model was corroborated to be an independent prognostic factor (

P
<
0.001

). In the network of SFs and ASEs, junction plakoglobin (JUP) noteworthily regulated RALGPS1-87608-AT (

P
<
0.001

,

R
=
0.455

). Additionally, RALGPS1-87608-AT (

P
=
0.006

) showed a prominent relationship with distant metastasis. KEGG pathways related to prognosis of UCS were selected by gene set variation analysis (GSVA). The pyrimidine metabolism (

P
<
0.001

,

R
=
−
0.470

) was the key pathway coexpressed with RALGPS1. We considered that aberrant JUP significantly regulated RALGPS1-87608-AT and the pyrimidine metabolism pathway might play a significant part in the metastasis and prognosis of UCS.
Surface Defect Detection of Seals Based on K-Means Clustering Algorithm and Particle Swarm Optimization
Authors: Li Xiaoguang , Zhu Juan , Shi Haoran , Cong Zijian
Published: October 2021

As an important part of automobile, the quality and safety of automobile engine high-pressure oil circuit seal parts are an important indicator of the manufacturer’s production process. In order to improve the detection accuracy and efficiency of seal parts in the traditional production process, the defect detection method on the surface of the seal was studied. A K-Means clustering image segmentation algorithm based on particle swarm optimization was proposed. To detect the surface defects of seals, first, preprocess the seal image. Then, use the SURF algorithm to extract the feature points of the seal image. Finally, according to the particle swarm fitness variance function, select the insertion point calculated by combining particle swarm optimization and K-Means algorithm. Through iteration, optimize the initial clustering center of K-Means algorithm. The efficiency of K-Means algorithm clustering iteration is improved. The test verifies the applicability of the algorithm in the actual process, and it can be used to accurately detect seals. Experimental results show that the detection accuracy rate reaches 98%, which is highly applicable to the actual production.
Study on the Mechanism of Liuwei Dihuang Pills in Treating Parkinson’s Disease Based on Network Pharmacology
Authors: Lin Dongtao , Zeng Yudan , Tang Deyu , Cai Yongming
Published: October 2021

Background. Parkinson’s disease (PD) is a common neurodegenerative disease in middle‐aged and elderly people. Liuwei Dihuang (LWDH) pills have a good effect on PD, but its mechanism remains unclear. Network pharmacology is the result of integrating basic theories and research methods of medicine, biology, computer science, bioinformatics, and other disciplines, which can systematically and comprehensively reflect the mechanism of drug intervention in disease networks. Methods. The main components and targets of herbs in LWDH pills were obtained through Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). Its active components were screened based on absorption, distribution, metabolism, and excretion (ADME); the PD‐related targets were obtained from the Genecards, OMIM, TTD, and DRUGBANK databases. We used R to take the intersection of LWDH‐ and PD‐related targets and Cytoscape software to construct the drug‐component‐target network. Moreover, STRING and Cytoscape software was used to analyze protein–protein interactions (PPI), construct a PPI network, and explore potential protein functional modules in the network. The Metascape platform was used to perform KEGG pathway and GO function enrichment analyses. Finally, molecular docking was performed to verify whether the compound and target have good binding activity. Results. After screening and deduplication, 210 effective active ingredients, 204 drug targets, 4333 disease targets, and 162 drug‐disease targets were obtained. We consequently constructed a drug‐component‐targets network and a PPI‐drug‐disease‐targets network. The results showed that the hub components of LWDH pills were quercetin, stigmasterol, kaempferol, and beta‐sitosterol; the hub targets were AKT1, VEGFA, and IL6. GO and KEGG enrichment analyses showed that these targets are involved in neuronal death, G protein‐coupled amine receptor activity, reactive oxygen species metabolic processes, membrane rafts, MAPK signaling pathways, cellular senescence, and other biological processes. Molecular docking showed that the hub components were in good agreement with the hub targets. Conclusion. LWDH pills have implications for the treatment of PD since they contain several active components, target multiple ligands, and activate various pathways. The hub components possibly include quercetin, stigmasterol, kaempferol, and beta‐sitosterol and act through pairing with hub targets, such as AKT1, VEGFA, and IL6, to regulate neuronal death, G protein‐coupled amine receptor activity, reactive oxygen species metabolic process, membrane raft, MAPK signaling pathway, and cellular senescence for the treatment of PD.
On Laplacian Equienergetic Signed Graphs
Authors: Tao Qingyun , Tao Lixin
Published: October 2021

The Laplacian energy of a signed graph is defined as the sum of the distance of its Laplacian eigenvalues from its average degree. Two signed graphs of the same order are said to be Laplacian equienergetic if their Laplacian energies are equal. In this paper, we present several infinite families of Laplacian equienergetic signed graphs.
Electrochemical Deposition of U and RE Elements Using the Stirred Liquid Cadmium Cathode in LiCl-KCl Molten Salts
Authors: Kim Gha-Young , Lee Chang Hwa , Yoon Dalsung , Jang Junhyuk , Lee Sung-Jai
Published: October 2021

This study was conducted in an attempt to understand the effect of a stirred liquid cadmium cathode (LCC) on the electrodeposition of U and U/RE on Cd. For this purpose, a series of electrowinning tests were performed using an LCC equipped with a Cd stirrer. Initially, three runs of the U electrodeposition tests were conducted using LiCl-KCl-UCl3 at 500°C under a constant current. From the results obtained from the initial three runs, it was found that the maximum deposited amount of U was 7.4 wt% U/Cd. U dendrite formation on the LCC crucible was not observed across each of the three runs. Three additional runs were conducted using LiCl-KCl-UCl3-RECl3 to determine the extent of U/RE electrodeposition. The maximum number of moles of U + RE metals deposited was 0.07, a value estimated to be 2.14 times higher than the solubility limits exhibited by these metals in Cd. The results of this study show that the use of a Cd stirrer significantly improves the extent of U deposition.
Serum Calcium Level Combined with Platelet Count May Be Useful Indicators for Assisted Diagnosis of Extremity Posttraumatic Osteomyelitis: A Comparative Analysis
Authors: Liu Guan-qiao , Jiang Nan , Hu Yan-jun , Lin Qing-rong , Wang Lei , Yu Bin
Published: October 2021

Background. A previous study had reported that patients with osteomyelitis (OM) appeared to be more likely to develop hypocalcemia before and after surgery. Calcium sulfate (CS) is frequently used as a local antibiotic vehicle in the treatment of OM, which may also affect serum calcium level. However, whether changes of serum calcium level are caused by OM and/or local use of calcium sulfate remains unclear. Also, platelet (PLT) count plays a crucial predictive role in periprosthetic joint infections (PJIs), but its role in assisted diagnosis of OM is largely unknown. The purpose of this study was to determine whether serum calcium level and PLT count may be helpful in assisted diagnosis of PTOM. Methods. Between January 2013 and December 2018, we analyzed 468 consecutive patients (392 males and 76 females), including 170 patients with posttraumatic OM (PTOM), 130 patients with aseptic bone nonunion (ABN), and 168 patients recovered from fractures with requirement of implant removal set as controls. Preoperative serological levels of calcium, phosphorus, and PLT were detected, and comparisons were conducted among the above three groups. Additionally, correlations and receiver operating characteristic (ROC) curves were displayed to test whether calcium level and PLT can differentiate patients with ABN and PTOM. Results. Outcomes showed that the incidences of asymptomatic hypocalcemia (PTOM vs. ABN vs.

controls
=
22.94
%

vs. 6.92% vs. 8.82%,

χ

2

=
21.098

,

P
<
0.001

) and thrombocytosis (PTOM vs. ABN vs.

controls
=
35.3
%

vs. 13.84% vs. 12.35%,

χ

2

=
28.512

,

P
<
0.001

) were highest in PTOM patients. Besides, the mean serological levels of phosphorus in PTOM and ABN patients were significantly higher than those in the controls (

P
=
0.007

). The Area Under the Curve (AUC) of the ROC curve outcomes revealed that, with the combination of serum calcium level with PLT count, the predictive role was acceptable (AUC 0.730,

P
<
0.001

, 95% CI 0.681-0.780). Also, serological levels of calcium of 2.225 mmol/L and PLT count of

246.5
×

10

9

/
L

were identified as the optimal cut-off values to distinguish patients with and without PTOM. However, age- and gender-related differences in serum calcium levels (age,

P
=
0.056

; gender,

P
=
0.978

) and PLT count (age,

P
=
0.363

; gender,

P
=
0.799

) were not found to be statistically significant in any groups. In addition, no significant correlations were identified between serum calcium level and PLT count (

R
=
0.010

,

P
=
0.839

). Conclusions. Asymptomatic hypocalcemia and thrombocytosis appeared to be more frequent in this cohort with PTOM. Serological levels of calcium and PLT count may be useful biomarkers in screening patients suspected of PTOM.
MANF: A Novel Endoplasmic Reticulum Stress Response Protein—The Role in Neurological and Metabolic Disorders
Authors: Yu Yang , Liu Dan-yang , Chen Xue-shen , Zhu Ling , Wan Li-hong
Published: October 2021

The mesencephalic astrocyte‐derived neurotrophic factor (MANF), also named as arginine‐rich protein (ARP) or arginine‐rich mutated in early‐stage tumors (ARMET), is a novel evolutionary conserved protein related to unfolded protein response. Growing evidence suggests that MANF critically involves in many ER stress‐related diseases with a protective effect. Here, we review the function of MANF based on its structure in neurological and metabolic disorders and summarize its potential applications in disease diagnosis and therapies.
Global Existence and Blow-Up for the Classical Solutions of the Long-Short Wave Equations with Viscosity
Authors: Shi Jincheng , Xiao Shengzhong
Published: October 2021

We are concerned with the global existence of classical solutions for a general model of viscosity long-short wave equations. Under suitable initial conditions, the existence of the global classical solutions for the viscosity long-short wave equations is proved. If it does not exist globally, the life span which is the largest time where the solutions exist is also obtained.
Comprehensive Analysis of N6-Methyladenosine-Related lncRNA Signature for Predicting Prognosis and Immune Cell Infiltration in Patients with Colorectal Cancer
Authors: Zhao Zhan , Yang Ya-bing , Li Xin-yuan , Li Xu-Guang , Chu Xiao-dong , Lin Zheng-bin , Zhang Yi-ran , Guo Yan-guan , Ding Hui , Pan Yun-long , Wang Liang , Pan Jing-hua
Published: October 2021

Background. Colorectal cancer (CRC) is the third most common tumor worldwide. Aberrant N6-methyladenosine (m6A) modification can influence the progress of the CRC. Additionally, long noncoding RNA (lncRNA) plays a critical role in CRC and has a close relationship with m6A modification. However, the prognostic potential of m6A-related lncRNAs in CRC patients still remains to be clarified. Methods. We use “limma” R package, “glmnet” R package, and “survival” R package to screen m6A-related-lncRNAs with prognostic potential. Then, we comprehensively analysed and integrated the related lncRNAs in different TNM stages from TCGA database using the LASSO Cox regression. Meanwhile, the relationship between functional enrichment of m6A-related lncRNAs and immune microenvironment in CRC was also investigated using the TCGA database. A prognostic model was constructed and validated to determine the association between m6A-related lncRNAs in different TNM stages and the prognosis of CRC. Result. We demonstrated that three related m6A lncRNAs in different TNM stages were associated with the prognosis of CRC patients. Patients from the TCGA database were classified into the low-risk and the high-risk groups based on the expression of these lncRNAs. The patients in the low-risk group had longer overall survival than the patients in the high-risk group (

P
<
0.001

). We further constructed and validated a prognostic nomogram based on these genes with a C-index of 0.80. The receiver operating characteristic curves confirmed the predictive capacity of the model. Meanwhile, we also found that the low-risk group has the correlation with the dendritic cell (DC). Finally, we discovered the relationship between the m6A regulators and the three lncRNAs. Conclusion. The prognostic model based on three m6A-related lncRNAs exhibits superior predictive performance, providing a novel prognostic model for the clinical evaluation of CRC patients.
Network Intrusion Detection Model Based on Improved BYOL Self-Supervised Learning
Authors: Wang Zhendong , Li Zeyu , Wang Junling , Li Dahai
Published: October 2021

The combination of deep learning and intrusion detection has become a hot topic in today’s network security. In the face of massive, high-dimensional network traffic with uneven sample distribution, how to be able to accurately detect anomalous traffic is the primary task of intrusion detection. Most research on intrusion detection systems based on network anomalous traffic detection has focused on supervised learning; however, the process of obtaining labeled data often requires a lot of time and effort, as well as the support of network experts. Therefore, it is worthwhile investigating the development of label-free self-supervised learning-based approaches called BYOL which is a simple and elegant framework with sufficiently powerful feature extraction capabilities for intrusion detection systems. In this paper, we propose a new data augmentation strategy for intrusion detection data and an intrusion detection model based on label-free self-supervised learning, using a new data augmentation strategy to introduce a perturbation enhancement model to learn invariant feature representation capability and an improved BYOL self-supervised learning method to train the UNSW-NB15 intrusion detection dataset without labels to extract network traffic feature representations. Linear evaluation on UNSW-NB15 and transfer learning on NSK-KDD, KDD CUP99, CIC IDS2017, and CIDDS_001 achieve excellent performance in all metrics.
The Impact of China’s Lockdown Policy on the Incidence of COVID‐19: An Interrupted Time Series Analysis
Authors: Molefi Mooketsi , Tlhakanelo John T. , Phologolo Thabo , Hamda Shimeles G. , Masupe Tiny , Tsima Billy , Setlhare Vincent , Mashalla Yohana , Wiebe Douglas J.
Published: October 2021

Background. Policy changes are often necessary to contain the detrimental impact of epidemics such as those brought about by coronavirus disease (COVID‐19). In the earlier phases of the emergence of COVID‐19, China was the first to impose strict restrictions on movement (lockdown) on January 23rd, 2020. A strategy whose effectiveness in curtailing COVID‐19 was yet to be determined. We, therefore, sought to study the impact of the lockdown in reducing the incidence of COVID‐19. Methods. Daily cases of COVID‐19 that occurred in China which were registered between January 12th and March 30th, 2020, were extracted from the Johns Hopkins CSSE team COVID‐19 ArcGIS® dashboards. Daily cases reported were used as data points in the series. Two interrupted series models were run: one with an interruption point of 23 January 2020 (model 1) and the other with a 14‐day deferred interruption point of 6th February (model 2). For both models, the magnitude of change (before and after) and linear trend analyses were measured, and β‐coefficients reported with 95% confidence interval (CI) for the precision. Results. Seventy‐eight data points were used in the analysis. There was an 11% versus a 163% increase in daily cases in models 1 and 2, respectively, in the preintervention periods (p ≤ 0.001). Comparing the period immediately following the intervention points to the counterfactual, there was a daily increase of 2,746% (p < 0.001) versus a decline of 207% (p = 0.802) in model 2. However, in both scenarios, there was a statistically significant drop in the daily cases predicted for this data and beyond when comparing the preintervention periods and postintervention periods (p < 0.001). Conclusion. There was a significant decrease the COVID‐19 daily cases reported in China following the institution of a lockdown, and therefore, lockdown may be used to curtail the burden of COVID‐19.
A Sliding Window Data Compression Method for Spatial-Time DOA Estimation
Authors: Zhao Pin-Jiao , Hu Guo-Bing , Wang Li-Wei
Published: October 2021

This paper presents a sliding window data compression method for spatial-time direction-of-arrival (DOA) estimation using coprime array. The signal model is firstly formulated by jointly using the temporal and spatial information of the impinging sources. Then, a sliding window data compression processing is performed on the array output matrix to realize fast calculation of time average function, and the computational burden has been reduced accordingly. Based on the concept of sum and difference co-array (SDCA), the vectorized conjugate augmented MUSIC is adopted, with which more sources than twice of the physical sensors can be resolved. Additionally, the sparse array robustness to sensor failure has been evaluated by introducing the concept of essential sensors. The theoretical analysis and numerical simulations are provided to confirm the effectiveness performance of the proposed method.
Exploring the Molecular Mechanism of Action of Yinchen Wuling Powder for the Treatment of Hyperlipidemia, Using Network Pharmacology, Molecular Docking, and Molecular Dynamics Simulation
Authors: Ye Jiahao , Li Lin , Hu Zhixi
Published: October 2021

Background. Yinchen Wuling powder is often used to treat clinical hyperlipidemia, although its mechanism of action remains unclear. In this study, we aimed to investigate the active ingredients found in Yinchen Wuling powder and find its mechanism of action when treating hyperlipidemia, using a combination of network pharmacology, molecular docking, and molecular dynamics simulation approaches. Methods. The TCMSP database was used to obtain the principle active ingredients found in Yinchen Wuling powder and the NCBI and DisGeNet databases were used to obtain the main target genes involved in hyperlipidemia, and the intersectional targets were obtained by EXCEL. We also used Cytoscape 3.7.2 software to construct a “Traditional Chinese Medicine‐Active Ingredient‐Target” network and use STRING platform to conduct “protein‐protein interactional” (PPI) analyses on the intersection targets. Bioconductor software and RX 64 4.0.0 software were then used to perform GO functional enrichment analysis and KEGG pathway enrichment analysis on the targets. Molecular docking of core protein‐ligand interactions was modeled using AutoDock Vina software. A simulation of molecular dynamics was conducted for the optimal core protein‐ligand obtained by molecular docking using Amber18 software. Results. A total of 63 active ingredients were found in Yinchen Wuling powder, corresponding to 175 targets, 508 hyperlipidemia targets, and 55 intersection targets in total. Cytoscape 3.7.2 showed that the key active ingredients were quercetin, isorhamnetin, taxifolin, demethoxycapillarisin, and artepillin A. The PPI network showed that the key proteins involved were AKT1, IL6, VEGFA, and PTGS2. GO enrichment analysis found that genes were enriched primarily in response to oxygen levels and nutrient levels of the vesicular lumen and were associated with membrane rafts. These were mainly enriched in AGE‐RAGE (advanced glycation end products‐receptor for advanced glycation end products) signaling pathway in diabetic complications, fluid shear stress, and atherosclerosis, as well as other pathways. The molecular docking results indicated key binding activity between PTGS2‐quercetin, PTGS2‐isorhamnetin, and PTGS2‐taxifolin. Results from molecular dynamics simulations showed that PTGS2‐quercetin, PTGS2‐isorhamnetin, and PTGS2‐taxifolin bound more stably, and their binding free energies were PTGS2‐quercetin ‐29.5 kcal/mol, PTGS2‐isorhamnetin ‐32 kcal/mol, and PTGS2‐taxifolin ‐32.9 kcal/mol. Conclusion. This study is based on network pharmacology and reveals the potential molecular mechanisms involved in the treatment of hyperlipidemia by Yinchen Wuling powder.
Heterogeneity of Circulating Tumor Cell–Associated Genomic Gains in Breast Cancer and Its Association with the Host Immune Response
Authors: Kanwar Nisha , Balde Zaldy , Nair Ranju , Dawe Melanie , Chen Shiyi , Maganti Manjula , Atenafu Eshetu G. , Manolescu Sabrina , Wei Carrie , Mao Amanda , Fu Fred , Wang Dan , Cheung Alison , Yerofeyeva Yulia , Peters Rachel , Liu Kela , Desmedt Christine , Sotiriou Christos , Szekely Borbala , Kulka Janina , McKee Trevor D. , Hirano Naoto , Bartlett John M.S. , Yaffe Martin J. , Bedard Philippe L. , McCready David , Done Susan J.
Published: October 2021

Tumor cells that preferentially enter circulation include the precursors of metastatic cancer. Previously, we characterized circulating tumor cells (CTC) from patients with breast cancer and identified a signature of genomic regions with recurrent copy-number gains. Through FISH, we now show that these CTC-associated regions are detected within the matched untreated primary tumors of these patients (21% to 69%, median 55.5%, n = 19). Furthermore, they are more prevalent in the metastases of patients who died from breast cancer after multiple rounds of treatment (70% to 100%, median 93%, samples n = 41). Diversity indices revealed that higher spatial heterogeneity for these regions within primary tumors is associated with increased dissemination and metastasis. An identified subclone with multiple regions gained (MRG clone) was enriched in a posttreatment primary breast carcinoma as well as multiple metastatic tumors and local breast recurrences obtained at autopsy, indicative of a distinct early subclone with the capability to resist multiple lines of treatment and eventually cause death. In addition, multiplex immunofluorescence revealed that tumor heterogeneity is significantly associated with the degree of infiltration of B lymphocytes in triple-negative breast cancer, a subtype with a large immune component. Collectively, these data reveal the functional potential of genetic subclones that comprise heterogeneous primary breast carcinomas and are selected for in CTCs and posttreatment breast cancer metastases. In addition, they uncover a relationship between tumor heterogeneity and host immune response in the tumor microenvironment.

Significance:

As breast cancers progress, they become more heterogeneous for multiple regions amplified in circulating tumor cells, and intratumoral spatial heterogeneity is associated with the immune landscape.