bluuebunny/crossref_metadata_2025_split huggingface dataset:
Bessel beam beating-based spontaneous Raman tomography enables high-contrast deep tissue Raman measurements
Authors: Huang Zhiwei , Shu Chi , Gong Li 
Published: October 2022

AbstractWe report on the development of a novel Bessel beam beating-based spontaneous Raman tomography (B3-SRT) technique for depth-resolved deep tissue Raman characterization without a need of mechanical depth-scan. To accomplish B3-SRT, we conceive a unique method by designing a coaxial Bessel beam beating excitation scheme associated with the Bessel beam collection configuration, such that the depth-resolved Raman information is encoded by the Bessel beam beatings generated, and then the depth-encoded Raman spectra along the Bessel beam excitation region are collected simultaneously by a Bessel-shaped collection optical designed. The depth-resolved Raman spectra can be rapidly retrieved using inverse fast Fourier transform. We demonstrated the ability of B3-SRT technique for high contrast deep tissue Raman measurements in a highly scattering two-layer tissue phantom (e.g., fat-bone tissue model). Compared with conventional confocal Raman microscopy, B3-SRT provides ~ 3.7-fold improvement in deep tissue Raman detection as well as ~ 2.6-fold improvement in deeper bone tissue Raman spectral contrast in the highly scattering fat-bone tissue phantom. It is anticipated that B3-SRT technique developed has potential to facilitate high contrast depth-resolved deep tissue Raman measurements in biomedical systems.
Microfabricated Polymer-Metal Biosensors For Multifarious Data Collection From Electrogenic Cellular Models
Authors: Didier Charles , Orrico Julia , Torres Omar Cepeda , Castro Jorge Manrique , Baksh Aliyah , Rajaraman Swaminathan 
Published: October 2022

AbstractBenchtop tissue cultures have become increasingly complex in recent years, as more “on-a-chip” biological technologies such as Microphysiological Systems (MPSs) work to incorporate cellular constructs that more accurately represent their respective biological systems. Such MPSs have begun providing major breakthroughs in biological research and are poised to shape the field in the coming decades. These biological systems necessitate integrated sensing modalities to procure complex, multiplexed datasets, with unprecedented combinatorial biological detail. In this work we expand on our polymer-metal biosensor approach by demonstrating a facile technology towards compound biosensing which are characterized through custom modeling approaches. Herein we develop a compound chip with 3D microelectrodes, 3D microfluidics, Interdigitated Electrodes (IDEs) and a micro-heater. The chip is subsequently tested using electrical/electrochemical characterization of 3D microelectrodes with 1kHz impedance and phase recordings, and IDE-based high frequency (~ 1MHz frequencies) impedimetric analysis of differential localized temperature recordings, both of which are modelled through equivalent electrical circuits for process parameter extraction. Additionally, a simplified antibody-conjugation strategy was employed for a similar IDE-based analysis of the implications for a key analyte (L-Glutamine) binding on the equivalent electrical circuit. Lastly, acute microfluidic perfusion modelling was performed to demonstrate ease of microfluidics integration into such a polymer-metal biosensor platform for potential complimentary localized chemical stimulation. Combined, our work demonstrates the design, development, and characterization of an accessibly designed, polymer-metal compound biosensor for electrogenic cellular constructs, geared towards comprehensive MPS data collection.
Social and Seismic Structural Vulnerability in Zihuatanejo, Guerrero, Mexico
Authors: Novelo-Casanova David A. , Suárez Gerardo 
Published: October 2022

Abstract
The spatial distribution of the social and seismic structural vulnerabilities in Zihuatanejo (ZIH), Guerrero, Mexico was estimated. Social vulnerability was assessed considering twelve indicators, including parameters such as access to health services, education, housing, employment, and unfavorable family conditions. Seismic structural vulnerability was estimated by characterizing the structural characteristics of local houses, assessing the type and age of construction, and the quality of building materials. Surveyed households were randomly selected from a statistically significant sample. Our findings indicate that in the western and eastern areas of ZIH the population has high and very high social vulnerability. The main factors that condition these high levels of social vulnerability are low-income female-headed families, and households with marginal access to information technology such as internet and telephone. Although seismic ground amplification in ZIH is relatively low, the areas to the west and southwest of the city are zones where the impact of strong earthquakes to constructions may be greater than in other areas. In particular, the districts of Lázaro Cárdenas, Benito Juárez, Cuauhtémoc, Emiliano Zapata, Las Mesas, Buenos Aires, Lomas del Quebrachal, and Lomas del Riscal would be affected. In general, houses susceptible to be damaged by the impact of an earthquake are in regions where the population is socially more vulnerable. More than 50% of the population and 30% of the houses have high and very high level of social and structural vulnerability. Our results provide information to the local and federal authorities to strengthen their civil protection and hazard mitigation plans.
Air traffic control forgetting prediction based on eye movement information and hybrid neural network
Authors: Jin Huibin , Gao Weipeng , Li Kun , Chu Mingjian 
Published: October 2022

Abstract
Control forgetting accounts for most of the current unsafe incidents. In the research field of radar surveillance control, how to avoid control forgetting to ensure the safety of flights is becoming a hot issue which attracts more and more attention. Meanwhile, aviation safety is substantially influenced by the way of eye movement. The exact relation of control forgetting to eye movement, however, still remains puzzling. Motivated by this, a control forgetting prediction method is proposed based on Convolutional Neural Networks and Long-Short Term Memory (CNN-LSTM). In this model, the eye movement characteristics are classified in terms of whether they are time-related, and then regulatory forgetting can be predicted by virtue of CNN-LSTM. The effectiveness of the method is verified by carrying out simulation experiments of eye movement during flight control. Results show that this method, using eye movement data, can provide control forgetting prediction with remarkably high accuracy. This work tries to explore an innovative way to associate control forgetting with eye movement, so as to guarantee the safety of civil aviation.
Using Generalized Structured Additive Regression Models to determine factors associated with and clusters for COVID-19 hospital deaths in South Africa
Authors: Maposa Innocent , Welch Richard , Ozougwu Lovelyn , Arendse Tracy , Mudara Caroline , Blumberg Lucille , Jassat Waasila 
Published: October 2022

Abstract
Background
The first case of COVID-19 in South Africa was reported in March 2020 and the country has since recorded over 3.6 million laboratory-confirmed cases and 100 000 deaths as of March 2022. Transmission and infection of SARS-CoV-2 virus and deaths in general due to COVID-19 have been shown to be spatially associated but spatial patterns in in-hospital deaths have not fully been investigated in South Africa. This study uses national COVID-19 hospitalization data to investigate the spatial effects on hospital deaths after adjusting for known mortality risk factors.
Methods
COVID-19 hospitalization data and deaths were obtained from the National Institute for Communicable Diseases (NICD). Generalized structured additive logistic regression model was used to assess spatial effects on COVID-19 in-hospital deaths adjusting for demographic and clinical covariates. Continuous covariates were modelled by assuming second-order random walk priors, while spatial autocorrelation was specified with Markov random field prior and fixed effects with vague priors respectively. The inference was fully Bayesian.
Results
The risk of COVID-19 in-hospital mortality increased with patient age, with admission to intensive care unit (ICU) (aOR = 4.16; 95% Credible Interval: 4.05–4.27), being on oxygen (aOR = 1.49; 95% Credible Interval: 1.46–1.51) and on invasive mechanical ventilation (aOR = 3.74; 95% Credible Interval: 3.61–3.87). Being admitted in a public hospital (aOR = 3.16; 95% Credible Interval: 3.10–3.21) was also significantly associated with mortality. Risk of in-hospital deaths increased in months following a surge in infections and dropped after months of successive low infections highlighting crest and troughs lagging the epidemic curve. After controlling for these factors, districts such as Vhembe, Capricorn and Mopani in Limpopo province, and Buffalo City, O.R. Tambo, Joe Gqabi and Chris Hani in Eastern Cape province remained with significantly higher odds of COVID-19 hospital deaths suggesting possible health systems challenges in those districts.
Conclusion
The results show substantial COVID-19 in-hospital mortality variation across the 52 districts. Our analysis provides information that can be important for strengthening health policies and the public health system for the benefit of the whole South African population. Understanding differences in in-hospital COVID-19 mortality across space could guide interventions to achieve better health outcomes in affected districts.
Experimental assessment of energy tower performance
Authors: mehdipour ramin , Habibi Mojtaba , Eydiyan Mohammad , Mohammadi Ehsan , Baniamerian Zahra 
Published: October 2022

Abstract
Solar energy is one of the most feasible options to produce energy in countries where unexploited desert areas or solar radiation are abundant. An energy tower is an effective system for electrical power generation that can perform more efficiently along with solar radiation. in this study, the efficiency of the energy tower system is investigated experimentally by an indoor fully adjustable apparatus. In this regard, a comprehensive set of influencing parameters like air velocity, humidity, and temperature and the effects of tower height on the performance of the energy tower is individually assessed. Based on the obtained results, by increasing humidification, the temperature difference increased between the inlet and outlet of the energy tower. In addition, the more the temperature difference between the inlet and outlet, the higher the airflow velocity in the outlet. The kinetic energy increases in the direction of airflow from top to bottom, and as the height of the tower lengthens, the kinetic energy enhances and subsequently increases the overall efficiency of the tower. Although the energy tower performs efficiently in the nighttime, airflow velocity increases averagely about 8% during the daytime and at the peak of the solar radiation, the airflow velocity enhances by 58% compared to nighttime.
How the COVID-19 pandemic influenced noise annoyance perception? A case study of Poznan, Poland
Authors: Felcyn Jan 
Published: October 2022

AbstractA worldwide COVID-19 spread effected in many limitations in social life and made people spend much more time at their homes. This phenomenon had its reflection in changes in traffic intensity, social activities and other aspects of our life, influencing also our perception of noise in the place of living. In this research, we wanted to find out how people rate noise annoyance while being at home during the 3rd wave of the pandemic in Poland in spring of 2021. We asked inhabitants of Poznań about their feelings and attitudes towards noise, we also wanted them to rate noise annoyance of several different noise sources both before and during a lockdown. Our study shows that almost 80% of respondents found the noise as annoying and only 11% of them thought that noise was less annoying during the pandemic. There was a statistically significant difference in ratings for aircraft noise and events – both of them were rated lower during a lockdown. Among people who felt that noise was less annoying, also road traffic noise was rated lower significantly. On the other hand, people who claimed that noise became more annoying boosted their ratings of neighbouring noise. All these facts support a theory that the pandemic had a direct and significant influence on our perception of noise.
Relationship between meteorological conditions and atmospheric PM2.5 in a uranium mining area and analysis of pollution sources
Authors: Liu Zhirong , Li Xing , Shi Sufeng , Huang Min , Li Zhuyao , Zhou Limin 
Published: October 2022

Abstract
Combining the special facilities of uranium mine with villages and towns, this paper analyzed the correlation between PM2.5 and atmospheric temperature, humidity, air pressure, wind speed and air index analyzed by PM2.5. Humidity, atmospheric pressure and air quality index were positively correlated with PM2.5 concentration, while temperature and wind speed were negatively correlated with PM2.5 concentration, while altitude had no correlation with PM2.5 concentration. The seasonal variation of PM2.5 concentration in this area was as follows: winter (31.5 ㎍/m3) > spring (25.78 ㎍/m3) > autumn (15.59 ㎍/m3) > summer (10.61 ㎍/m3). PMF model (orthogonal matrix factor analysis) was used to analyze various pollution sources. It was found that the contribution of various pollution sources was soil source (33.7%), combustion source (19.2%), traffic source (18.2%), industrial source (15.0%) and natural source (3.3%).
Processing of Pinus sylvestris into remarkable heat- insulating, thermally stable, and flame-retarded materials by combining the flame retardant impregnation and densification treatment
Authors: Xu Zhisheng , Zhao Wenjun , Feng Yuwei , Tang Xinyu , Yan Long 
Published: October 2022

Abstract
Flame retardant impregnation and densification treatment as wood modification techniques both can improve the fire safety of the wood. Here, these two techniques are applied to prepare flame-retarded wood, aiming at further fire hazard reduction of wood. The delignated Pinus sylvestris wood was impregnated with boric acid (BA) and graphene oxide (GO) solutions to form BA-GO protective layer, then densified to prepare densified flame-retarded wood named BGO-DW sample. The results reveal that the BGO-DW sample obtains a limiting oxygen index (LOI) value of 47.5%, accompanied by a 56.1% reduction in thermal conductivity and a 48.6% decrease in equilibrium backside temperature at 1200 s compared to natural wood. Besides, the peak heat release rate (PHRR) and total heat release (THR) values of the BGO-DW sample are 72.0% and 62.5% lower than those of natural wood, which can be ascribed to the shorter pyrolysis interval and lower peak mass loss rate, as supported by thermogravimetric (TG) analysis. The outstanding flame retardancy of the BGO-DW sample is attributed to the generation of char rich in C = C aromatic structure, C–O–C cross-linked structure, and B2O3 glassy structure via the dehydration, carbonization, and cross-linking reactions. These fascinating features of densified flame-retarded wood offer a new method to enhance the thermal stability, heat insulation, and flame retardancy of wood.
Dermokine mutations contribute to epithelial-mesenchymal transition and advanced melanoma through ERK/MAPK pathways
Authors: Imani Saber , Ma Wenqiong , Wu Zexiu , Maghsoudloo Mazaher , Ijaz Iqra , Shasaltaneh Marzieh Dehghan , Zhang Yuqin , Weng Qiao , Fu Junjiang , Wen QingLian 
Published: October 2022

Abstract
In the present study, the vulnerability associated with dermokine (DMKN), as a new trigger for the Epithelial-Mesenchymal Transition (EMT)-driven melanoma, was assessed based on a genome-wide genetic screening using transgenic. The results suggested a significantly higher DMKN expression in human Malignant Melanoma (MM), which was correlated with poor overall survival among melanoma patients, especially BRAF-mutated MM samples. Additionally, an in vitro knockdown of DMKN inhibited the cell proliferation, invasion, and apoptosis of MM cancer cells by activating ERK/MAPK signaling pathways and regulating STAT3 in downstream molecules. The interrogation of in vitro melanoma dataset and characterization of advanced melanoma samples revealed that DMKN downregulated the EMT-like transcriptional program through disrupting MET/EMT cortical actin, enhanced the expression of epithelial markers, and decreased that of mesenchymal markers. Whole-exome sequencing was presented with p.E69D and p.V91A DMKN mutations as novel somatic loss-of-function mutations. Further, the purposeful proof-of-principle modeled the interaction of ERK with p.E69D and p.V91A DMKN mutations in the ERK-MAPK kinase signaling that may be naturally associated with the EMT triggering during the melanomagenesis. These results provided preclinical evidence for the role of DMKN in shaping the EMT-like melanoma phenotype and introduced DMKN as a new exceptional responder to personalized MM therapy.
Erbium-doped (Pb 0.9 −Er 0.01 -Zr 0.09 ) and (Pb 0.9 -Er 0.01 -Zr 0.045 - Ti 0.045 ) nano-crystalline films and nano-rods ceramic synthesis by sol-gel technique for energy-storage application
Authors: Ibrahim Faiza , El-Desoky Mohamed 
Published: October 2022

Abstract
The development of dielectric constant materials for energy storage applications is in high demand. Lead zirconate and lead zirconate titanate doping with erbium thin films and bulk -based devices with variant dielectric constant were created in this work. Pb(0.9) )-Er0.01 Zr(0.09 (PEZ) and Pb0.9-Er0.01-Zr0.045-Ti0.045 (PEZT) thin films were produced on a glass substrate using a sol-gel doctor blade technique at low temperature. X-ray diffraction (XRD), transmission electron microscopy (TEM), and electron diffraction (ED) were used to examine the structure of the produced nanocrystals. PEZ and PEZT films had nanocrystals that were 9.5 nm and 15 nm in size, respectively, whereas PEZ and PEZT bulk nano-rods had 455 ± 5 nm in length and 45 ± 1 nm in diameter. The TEM and XRD results were found to be completely consistent in terms of particle size. Ferroelectric properties and dielectric characteristics were found to be frequency dependent. Dielectric experiments revealed that the dielectric constant was decreasing for bulk samples as compared to film samples. The residual polarization of the Er-doped PEZ and PEZT films was the highest, reaching 36.25 µC/cm2 and 69.79 µC/cm2, respectively, and the coercive fields were 43kV/cm and 45.43 kV/cm, respectively. On the other hand, PEZ and PEZT bulk samples had residual polarizations of 27.15 µC/cm2 and 37.29 µC/cm2, respectively, while having coercive fields of 32.3 kV/cm and 39.3 kV/cm, respectively. On the other hand, (PEZ) and (PEZT) samples may have potential use in energy storage applications.
LncRNAs Involved in the Regulation of Vascular Smooth Muscle Cell Proliferation and Migration in Atherosclerosis
Authors: Zhang Hua , Liu Lixin , Chen Xueying 
Published: October 2022

Abstract
Atherosclerosis (AS) is a major cause of coronary artery disease, cerebral infarction,and peripheral vascular disease.Vascular smooth muscle cells（VSMCs）are oneof the major cell types in the vessel wall, and the abnormal proliferation and migration functions of VSMCs are critical in the process and stability of atherosclerotic plaque formation.In recently, an increasing number of studies have demonstrated that LncRNAs play an important role in the development of atherosclerotic disease. The purpose of thispaper is to summarize the LncRNAs involved in regulating the proliferation and migration of VSMCs in atherosclerosis, and to provide a scientific basis for the prevention and treatment of atherosclerosis.
Deep Learning Based Diagnostic Quality Assessment of Choroidal OCT Features with Expert-Evaluated Explainability
Authors: Koidala Surya Prakash , Manne Shanmukh Reddy , Ozimba Kalah , Mohammed Abdul Rasheed , Bashar Sarforaz Bin , Mohammed Nasar Ibrahim , Selvam Amrish , Sahel Jose Alain , Chhablani Jay , Jana Soumya , Vupparaboina Kiran Kumar 
Published: October 2022

Abstract
Various vision-threatening eye diseases including age-related macular degeneration (AMD) and central serous chorioretinopathy(CSCR) are caused due to the dysfunctions manifested in the highly vascular choroid layer of the posterior segment of the eye.In the current clinical practice, screening choroidal structural changes is widely based on optical coherence tomography (OCT)images. Accordingly, to assist clinicians, several automated choroidal biomarker detection methods using OCT images aredeveloped. However, the performance of these algorithms is largely constrained by the quality of the OCT scan. Consequently,determining the quality of choroidal features in OCT scans is significant in building standardized quantification tools and henceconstitutes our main objective. This study includes a dataset of 1593 good and 2581 bad quality Spectralis OCT images gradedby an expert. Noting the efficacy of deep-learning (DL) in medical image analysis, we propose to train three state-of-the-artDL models: ResNet18, EfficientNet-B0 and EfficientNet-B3 to detect the quality of OCT images. The choice of these modelswas inspired by their ability to preserve the salient features across all the layers without information loss. To evaluate theattention of DL models on the choroid, we introduced color transparency maps (CTMs) based on GradCAM explanations.Further, we proposed two subjective grading scores: overall choroid coverage (OCC) and choroid coverage in the visibleregion(CCVR) based on CTMs to objectively correlate visual explanations vis-à-vis DL model attentions. We observed that theaverage accuracy and F-scores for the three DL models are greater than 96%. Further, the OCC and CCVR scores achievedfor the three DL models under consideration substantiate that they mostly focus on the choroid layer in making the decision. Inparticular, of the three DL models, EfficientNet-B3 is in close agreement with the clinician’s inference. The proposed DL-basedframework demonstrated high detection accuracy as well as attention on the choroid layer, where EfficientNet-B3 reportedsuperior performance. Our work assumes significance in bench-marking the automated choroid biomarker detection tools andfacilitating high-throughput screening. Further, the methods proposed in this work can be adopted for evaluating the attentionof DL-based approaches developed for other region-specific quality assessment tasks.