bluuebunny/crossref_metadata_2025 huggingface dataset:
Enhanced Performance of nZVI/MXene@CNTs for Rapid As(III) Removal from Aqueous Solutions
Authors: Li Shihai , Luo Siyuan , Wan Si , Wang Ping , Zhou Gang , Wang Wenming , Chen Runhua
Published: August 2022

Transition metal compounds demonstrated good performance in the removal of environmentally harmful contaminants, such as arsenic, while the aggregation propensity and poor chemical stability should be noticed. In this study, the nZVI/MXene@CNTs was adequately prepared by liquid reduction precipitation method for adsorption and oxidation of As(III) from the aqueous solution. The results of batch removal experiments showed that the maximum removal capacity of the nZVI/MXene@CNTs for As(III) was 443.32 mg/g with the pH = 3.0 at 25 °C. The effects of initial pH, dosage of materials and ionic strength on As(III) removal were explored. According to the various characterization analyses, the most plausible mechanisms of As(III) removal were the surface complexation, solid phase precipitation and the catalytic oxidation by the •OH. Furthermore, the nZVI/MXene@CNTs could be readily activated and reused via leaching with 0.1 M NaOH solution, due to the three-dimensional mesh intercalation structure. Therefore, it is a potential nanocomplex for removing and recovering As(III) from water with excellent capacity and environmental friendliness.
The Effect of Viscous Dampers on the Seismic Performance of Curved Viaducts with the Combined Use of Steel Stoppers
Authors: Kang Caixia , Tian Qin , Zhong Lianggen
Published: August 2022

Viaducts with roller bearings are subject to large displacement, which could lead to the collapse of the deck during earthquakes. This study attempts to prevent large displacements by installing steel stoppers at both sides of roller bearings. The efficiency of viscous damper stiffness on the seismic performance of curved viaducts with the combined use of steel stoppers at a spatial multipoint is evaluated. The pounding phenomena at steel stoppers are exactly simulated, considering the energy consumption by the modified Hertz-damp model. The overall performance of viaducts with different kinds of viscous dampers and different stopper values during serious earthquakes is evaluated. Application of viscous dampers and a stopper could reduce the possibility of deck unseating damage, relative displacement between superstructures, pounding forces at steel stoppers, and pier damage. Stopper value plays a more important role in pier damage than viscous dampers.
Oral-Systemic Health and Disorders: Latest Advances on Oral–Gut–Lung Microbiome Axis
Authors: Amato Alessandra
Published: August 2022

The human body hosts complex microbial communities, accounting for 100 trillion microbial symbionts, much more than human cells, aiding nutrition, counteracting pathogens, and collaborating with our immune system [...]
Seepage of Groundwater in an Underground Fractured Rock Mass and Its Sustainable Engineering Application
Authors: Wu Yue , Qiao Wei-Guo , Li Yan-Zhi , Fan Zhen-Wang , Zhang Shuai , Zhang Lei , Zhang Xiao-Li
Published: August 2022

Due to the existence of tiny cracks in rock, underground engineering has begun to consider how to divert a large amount of groundwater. To divert groundwater more effectively, it is necessary to master the seepage characteristics of fluids in the micropores of rocks. Based on rock samples obtained from an underground engineering site, this paper analyzes the microscopic pore structure of the rock through a combination of laboratory tests and numerical simulations and inputs this information into a computer model. The fluid seepage state in the rock under different conditions is simulated in the computer model, and parameters such as the fluid seepage velocity in the rock are obtained. Afterwards, it has been verified by engineering practice that the smallest remaining water inflow can reach 0.06‰. The results of this paper can effectively guide the discharge of groundwater to better manage water resources, greatly reduce the pollution of groundwater in construction and production environments, and reduce the pollution caused by grouting projects. Furthermore, the cleanliness and safety of underground engineering construction and production could be ensured.
UiO-66/Palygorskite/TiO2 Ternary Composites as Adsorbents and Photocatalysts for Methyl Orange Removal
Authors: Ioannidou Thaleia , Anagnostopoulou Maria , Papoulis Dimitrios , Christoforidis Konstantinos C. , Vasiliadou Ioanna A.
Published: August 2022

Metal–organic frameworks are recognized as a new generation of emerging porous materials in a variety of applications including adsorption and photocatalysis. The present study presents the development of ternary composite materials made through the coupling of UiO-66 with palygorskite (Pal) clay mineral and titanium dioxide (TiO2) applied as adsorbent and photocatalyst for the removal of methyl orange (MO) from aqueous solutions as a typical anionic dye. The prepared materials were characterized using XRD, ATR, DR UV/Vis, and TGA analysis. Detailed kinetic experiments revealed that the presence of the clay at low amounts in the composite outperformed the adsorption efficiency of pure UiO-66, increasing MO adsorption by ca. 8%. In addition, coupling Pal/UiO-66 with TiO2 for the production of ternary composites provided photocatalytic properties that resulted in complete removal of MO. This was not observed in the pure UiO-66, the Pal/UiO-66 composite, or the pure TiO2 material. This study presents the first example of clay mineral/MOF/TiO2 composites with improved performance in removing dyes from aqueous solutions and highlights the importance of coupling MOFs with low-cost clay minerals and photocatalysts for the development of multifunctional advanced composites.
Research on Rockburst Risk Level Prediction Method Based on LightGBM−TCN−RF
Authors: Ma Li , Cai Jiajun , Dai Xinguan , Jia Ronghao
Published: August 2022

Rockburst hazards pose a severe threat to mine safety. To accurately predict the risk level of rockburst, a LightGBM−TCN−RF prediction model is proposed in this paper. The correlation coefficient heat map combined with the LightGBM feature selection algorithm is used to screen the rockburst characteristic variables and establish rockburst predicted characteristic variables. Then, the TCN prediction model with a better prediction performance is selected to predict the rockburst characteristic variables at time t + 1. The RF classification model of rockburst risk level with a better classification effect is used to classify the risk level of rockburst characteristic variables at time t + 1. The comparison experiments show that the rockburst characteristic variables after screening allow a more accurate prediction. The overall RMSE and MAE of the TCN prediction model are 0.124 and 0.079, which are better than those of RNN, LSTM, and GRU by about 0.1–2.5%. The accuracy of the RF classification model for the rockburst risk level is 96.17%, which is about 20% higher than that of KNN and SVM, and the model accuracy is improved by 1.62% after parameter tuning by the PSO algorithm. The experimental results show that the LightGBM−TCN−RF model can better classify and predict rockburst risk levels at future moments, which has a certain reference value for rockburst monitoring and early warning.
CSS: Container Resource Manager Using System Call Pattern for Scientific Workflow
Authors: Song Chunggeon , Yu Heonchang , Lee Eunyoung
Published: August 2022

Multiple containers running scientific workflows in SMP-based high-performance computers generate some bottlenecks due to workload flexibility. To improve system resource utilization by minimizing these bottlenecks, vertical resource management is required to determine an appropriate resource usage policy according to the resource usage type of the container. However, the traditional methods have additional overhead for collecting monitoring metrics, and the structure of the resource manager is complex. In this paper, in order to compensate for these shortcomings, we propose CSS, a dynamic resource manager utilizing system call data collected for security purposes. The CSS utilizes the SBCC algorithm, which uses the number of futex system calls as a heuristic measure to determine the number of IO-intensive workload occurrences. In addition, the CTBRA algorithm is used to determine the range of resources to be allocated for each container and to perform actual resource allocation. We implemented a prototype of CSS and conducted experiments on NPB to analyze the performance of CSS with various types of large-scale tasks of a scientific workflow. As a result of the experiment, it showed a performance improvement of up to 7% compared with the environment where Linux cgroups were not applied. In addition, CANU performance analysis was performed to verify the effectiveness of applications used in the real world, and performance improvement of up to 4.5% was shown.
Deep Q-Learning Technique for Offloading Offline/Online Computation in Blockchain-Enabled Green IoT-Edge Scenarios
Authors: Heidari Arash , Jabraeil Jamali Mohammad Ali , Jafari Navimipour Nima , Akbarpour Shahin
Published: August 2022

The number of Internet of Things (IoT)-related innovations has recently increased exponentially, with numerous IoT objects being invented one after the other. Where and how many resources can be transferred to carry out tasks or applications is known as computation offloading. Transferring resource-intensive computational tasks to a different external device in the network, such as a cloud, fog, or edge platform, is the strategy used in the IoT environment. Besides, offloading is one of the key technological enablers of the IoT, as it helps overcome the resource limitations of individual objects. One of the major shortcomings of previous research is the lack of an integrated offloading framework that can operate in an offline/online environment while preserving security. This paper offers a new deep Q-learning approach to address the IoT-edge offloading enabled blockchain problem using the Markov Decision Process (MDP). There is a substantial gap in the secure online/offline offloading systems in terms of security, and no work has been published in this arena thus far. This system can be used online and offline while maintaining privacy and security. The proposed method employs the Post Decision State (PDS) mechanism in online mode. Additionally, we integrate edge/cloud platforms into IoT blockchain-enabled networks to encourage the computational potential of IoT devices. This system can enable safe and secure cloud/edge/IoT offloading by employing blockchain. In this system, the master controller, offloading decision, block size, and processing nodes may be dynamically chosen and changed to reduce device energy consumption and cost. TensorFlow and Cooja’s simulation results demonstrated that the method could dramatically boost system efficiency relative to existing schemes. The findings showed that the method beats four benchmarks in terms of cost by 6.6%, computational overhead by 7.1%, energy use by 7.9%, task failure rate by 6.2%, and latency by 5.5% on average.
Remote Sensing Image Segmentation of Mariculture Cage Using Ensemble Learning Strategy
Authors: Xu Lewei , Hu Zhuhua , Zhang Chong , Wu Wei
Published: August 2022

In harbour areas, the irrational layout and high density of mariculture cages can lead to a dramatic deterioration of the culture’s ecology. Therefore, it is important to analyze and regulate the distribution of cages using intelligent analysis based on deep learning. We propose a remote sensing image segmentation method based on the Swin Transformer and ensemble learning strategy. Firstly, we collect multiple remote sensing images of cages and annotate them, while using data expansion techniques to construct a remote sensing image dataset of mariculture cages. Secondly, the Swin Transformer is used as the backbone network to extract the remote sensing image features of cages. A strategy of alternating the local attention module and the global attention module is used for model training, which has the benefit of reducing the attention computation while exchanging global information. Then, the ensemble learning strategy is used to improve the accuracy of remote sensing cage segmentation. We carry out quantitative and qualitative analyses of remote sensing image segmentation of cages at the ports of Li’an, Xincun and Potou in Hainan Province, China. The results show that our proposed segmentation scheme has significant performance improvement compared to other models. In particular, the mIoU reaches 82.34% and pixel accuracy reaches 99.71%.
Reliability of Wu Huanqun’s Table Tennis Game Analysis Method in Authors’ Own Modification
Authors: Grycan Jerzy , Kołodziej Małgorzata , Bańkosz Ziemowit
Published: August 2022

The observation and analysis of the game or the player’s behavior and actions is a very important aspect of optimizing sports training in table tennis. The aim of this study was to present the applied method of observation, developed by Professor Wu Huanqun and modified by the authors, together with an assessment of its reliability. The method consists in observing the winning actions of a given player and the same actions of his opponent in parallel, on three levels of complexity. Levels 1, 2, and 3 are concerned with identifying increasingly detailed winning strokes and stroke combinations. To assess the reliability of the method, seven experts independently analyzed the men’s final game of the World Championship 2019. Kendall’s coefficient of concordance, with an χ2 significance test, was used to assess the compliance of the experts. Cronbach’s alpha was used to assess internal consistency. The obtained results indicate the high compliance and internal consistency (thus, high reliability) of the assessed method: the highest at the Level 1 observation level and the smallest, but significant, at Level 3. The performed statistical analysis indicates a high agreement between the experts’ opinions, which was taken as a measure of high reliability for the described method of observation.
Metal–Organic Frameworks as Powerful Heterogeneous Catalysts in Advanced Oxidation Processes for Wastewater Treatment
Authors: Fdez-Sanromán Antía , Rosales Emilio , Pazos Marta , Sanroman Angeles
Published: August 2022

Nowadays, the contamination of wastewater by organic persistent pollutants is a reality. These pollutants are difficult to remove from wastewater with conventional techniques; hence, it is necessary to go on the hunt for new, innovative and environmentally sustainable ones. In this context, advanced oxidation processes have attracted great attention and have developed rapidly in recent years as promising technologies. The cornerstone of advanced oxidation processes is the selection of heterogeneous catalysts. In this sense, the possibility of using metal–organic frameworks as catalysts has been opened up given their countless physical–chemical characteristics, which can overcome several disadvantages of traditional catalysts. Thus, this review provides a brief review of recent progress in the research and practical application of metal–organic frameworks to advanced oxidation processes, with a special emphasis on the potential of Fe-based metal–organic frameworks to reduce the pollutants present in wastewater or to render them harmless. To do that, the work starts with a brief overview of the different types and pathways of synthesis. Moreover, the mechanisms of the generation of radicals, as well as their action on the organic pollutants and stability, are analysed. Finally, the challenges of this technology to open up new avenues of wastewater treatment in the future are sketched out.
Poly (β-Cyclodextrin-co-citric Acid) Functionalized Natural Nanozeolite: An Eco-Friendly Platform for IB Delivery
Authors: Jahangard Novin , Baghbanian Seyed Meysam , Khaksarmaghami Samad
Published: August 2022

Zeolites, due to their porous nature and inherent pH-sensitive properties, are widely studied as drug delivery systems. However, natural zeolite pores are usually larger than drug molecules, which can cause rapid drug release. Consequently, to solve this problem, the zeolite structure must be modified to achieve controlled drug release. On the other hand, the preparation of nanoscale zeolites enables them to enter the living cell. To achieve these objectives, a natural nanozeolite was modified by poly (β-cyclodextrin-co-citric acid) (PCD-zeolite), and used for the loading and release of IB (IB). The PCD-zeolite was synthesized by heating a mixture of citric acid (CA), cyclodextrin (CD), and Na2HPO4; it was characterized by FT-IR, TGA, and TEM analyses. Due to the presence of hydroxyl and carboxyl groups in the PCD-zeolite structure, pH plays a vital role in the adsorbed IB; thus, the maximum adsorbed IB was observed at pH = 7. The in vitro release of IB from PCD-zeolite-IB in a phosphate buffer was examined; the PCD-zeolite containing IB (30 wt%) showed the highest release at pH = 3.6 within the first 3–48 h. As a result, the PCD-zeolite, by trapping IB, can improve its solubility and bioavailability. Moreover, the decrease in the dissolution rate of the polymer matrix in an acidic medium may also lower the toxicity of IB.
A Priori Estimates for the Solution of an Initial Boundary Value Problem of Fluid Flow through Fractured Porous Media
Authors: Alimbekova Nurlana , Berdyshev Abdumauvlen , Baigereyev Dossan
Published: August 2022

The paper studies a model of fluid flow in a fractured porous medium in which fractures are distributed uniformly over the volume. This model includes a nonlinear equation containing several terms with fractional derivatives in the sense of Caputo of order belonging to the interval 1,2. The relevance of studying this problem is determined by its practical significance in the oil industry, since most of the world’s oil reserves are in these types of reservoirs. The uniqueness of the solution to the problem in a differential form and its dependence on the initial data and the right-hand side of the equation is proved. A numerical method is proposed based on the use of the finite difference approximation for integer and fractional time derivatives and the finite element method in the spatial direction. A change of variables is introduced to reduce the order of the fractional derivatives. Furthermore, the fractional derivative is approximated by using the L1-method. The stability and convergence of the proposed numerical method are rigorously proved. The theoretical order of convergence is confirmed by the results of numerical tests for a problem of fluid flow in fractured porous media with a known exact solution.
Design of Type-3 Fuzzy Systems and Ensemble Neural Networks for COVID-19 Time Series Prediction Using a Firefly Algorithm
Authors: Melin Patricia , Sánchez Daniela , Castro Juan R. , Castillo Oscar
Published: August 2022

In this work, information on COVID-19 confirmed cases is utilized as a dataset to perform time series predictions. We propose the design of ensemble neural networks (ENNs) and type-3 fuzzy inference systems (FISs) for predicting COVID-19 data. The answers for each ENN module are combined using weights provided by the type-3 FIS, in which the ENN is also designed using the firefly algorithm (FA) optimization technique. The proposed method, called ENNT3FL-FA, is applied to the COVID-19 data for confirmed cases from 12 countries. The COVID-19 data have shown to be a complex time series due to unstable behavior in certain periods of time. For example, it is unknown when a new wave will exist and how it will affect each country due to the increase in cases due to many factors. The proposed method seeks mainly to find the number of modules of the ENN and the best possible parameters, such as lower scale and lower lag of the type-3 FIS. Each module of the ENN produces an individual prediction. Each prediction error is an input for the type-3 FIS; moreover, outputs provide a weight for each prediction, and then the final prediction can be calculated. The type-3 fuzzy weighted average (FWA) integration method is compared with the type-2 FWA to verify its ability to predict future confirmed cases by using two data periods. The achieved results show how the proposed method allows better results for the real prediction of 20 future days for most of the countries used in this study, especially when the number of data points increases. In countries such as Germany, India, Italy, Mexico, Poland, Spain, the United Kingdom, and the United States of America, on average, the proposed ENNT3FL-FA achieves a better performance for the prediction of future days for both data points. The proposed method proves to be more stable with complex time series to predict future information such as the one utilized in this study. Intelligence techniques and their combination in the proposed method are recommended for time series with many data points.
Liver Graft MicroRNAs Expression in Different Etiology of Acute Jaundice after Living Donor Liver Transplantation
Authors: Lin Shu-Hsien , Wu Kun-Ta , Wang Chih-Chi , Huang Kuang-Tzu , Chen Kuang-Den , Hsu Li-Wen , Eng Hock-Liew , Chiu King-Wah
Published: August 2022

Background: Acute jaundice remains a critical problem following liver transplantation. MicroRNAs (miRNAs) are involved in regulating gene expression related to various disease phenotypes and statuses. Aims: To differentiate acute jaundice etiology after living donor liver transplantation (LDLT), we examined the hepatic miRNA expression patterns in several liver graft pathologies. Methods: Eighty liver transplant recipients undergoing post-LDLT graft biopsy for the evaluation of acute jaundice were enrolled in this 1-year prospective study. Using a real-time quantitative reverse transcription-polymerase chain reaction profiling assay, we identified hepatic miRNA (miRNA-122, miRNA-301, miRNA-133a, and miRNA-21) signatures in various allografts pathologies. Results: Pathologic findings of the 80 recipients were as follows: acute cholangitis (AC), 37 (46%); acute rejection (AR), 20 (25%); recurrent hepatitis (RH), 12 (15%); non-specific pathological change, 6 (8%); and fatty change (FC), 5 (6%). None of these identified hepatic miRNAs expression pattern was significantly correlated with serum parameters, including neutrophil-lymphocyte ratio. In AC, hepatic miRNA-122, miRNA-301, miRNA-133a, and miRNA-21 expression was significantly downregulated (p < 0.05). MicroRNA-122 expression was elevated in cases of AR and RH (p < 0.05); miRNA-301 and miRNA-21 expression was higher in RH than in AC (p < 0.05); and miRNA-133a expression was higher in FC than in AR (p < 0.05). Conclusions: Our study suggests that specific hepatic miRNA expression patterns as a checklist may be useful for differential diagnosis of acute jaundice following liver transplantation.
YTHDF3 Is Involved in the Diapause Process of Bivoltine Bombyx mori Strains by Regulating the Expression of Cyp307a1 and Cyp18a1 Genes in the Ecdysone Synthesis Pathway
Authors: Chen Yanhua , Fan Bingyan , Yasen Ayinuer , Zhu Juan , Wang Meixian , Shen Xingjia
Published: August 2022

The variable diapause features of bivoltine silkworm (Bombyx mori) strains regulated by environmental signals in the embryonic stage are closely related to epigenetics. Previously, we showed that the expression of YTHDF3 is significantly different in the pupae of the bivoltine silkworm Qiufeng developed from eggs incubated at a normal temperature (QFHT, diapause egg producer) compared to those from eggs incubated at a low temperature (QFLT, nondiapause egg producer), indicating that the expression of diapause-associated genes is regulated by the m6A modification level. However, how YTHDF3 regulates the expression of diapause-related genes remains unclear. In this study, we observed that the knockdown of B. mori YTHDF3 resulted in delayed embryo development, while the overexpression of YTHDF3 resulted in the transformation of nondiapause-destined eggs into a mixture of diapause and nondiapause eggs. Further studies showed that YTHDF3, as a reading protein, can recognize the m6A site of Cyp307a1 and Cyp18a1 genes in the ecdysone synthesis pathway (ESP), and the overexpression of YTHDF3 affects the diapause traits of the silkworm by decreasing the stabilities of mRNAs of Cyp307a1 and Cyp18a1 and inhibiting their translation. The above results demonstrate that m6A modification mediates YTHDF3 to affect the expression levels of its target genes, Cyp307a1 and Cyp18a1, in the ESP to regulate diapause in bivoltine B. mori. This is the first report of the m6A methylation regulation mechanism in diapause in B. mori and provides new experimental data for clarifying the diapause regulation network.
Detecting Fear-Memory-Related Genes from Neuronal scRNA-seq Data by Diverse Distributions and Bhattacharyya Distance
Authors: Zhang Shaoqiang , Xie Linjuan , Cui Yaxuan , Carone Benjamin R. , Chen Yong
Published: August 2022

The detection of differentially expressed genes (DEGs) is one of most important computational challenges in the analysis of single-cell RNA sequencing (scRNA-seq) data. However, due to the high heterogeneity and dropout noise inherent in scRNAseq data, challenges in detecting DEGs exist when using a single distribution of gene expression levels, leaving much room to improve the precision and robustness of current DEG detection methods. Here, we propose the use of a new method, DEGman, which utilizes several possible diverse distributions in combination with Bhattacharyya distance. DEGman can automatically select the best-fitting distributions of gene expression levels, and then detect DEGs by permutation testing of Bhattacharyya distances of the selected distributions from two cell groups. Compared with several popular DEG analysis tools on both large-scale simulation data and real scRNA-seq data, DEGman shows an overall improvement in the balance of sensitivity and precision. We applied DEGman to scRNA-seq data of TRAP; Ai14 mouse neurons to detect fear-memory-related genes that are significantly differentially expressed in neurons with and without fear memory. DEGman detected well-known fear-memory-related genes and many novel candidates. Interestingly, we found 25 DEGs in common in five neuron clusters that are functionally enriched for synaptic vesicles, indicating that the coupled dynamics of synaptic vesicles across in neurons plays a critical role in remote memory formation. The proposed method leverages the advantage of the use of diverse distributions in DEG analysis, exhibiting better performance in analyzing composite scRNA-seq datasets in real applications.
Decoding Task-Based fMRI Data with Graph Neural Networks, Considering Individual Differences
Authors: Saeidi Maham , Karwowski Waldemar , Farahani Farzad V. , Fiok Krzysztof , Hancock P. A. , Sawyer Ben D. , Christov-Moore Leonardo , Douglas Pamela K.
Published: August 2022

Task fMRI provides an opportunity to analyze the working mechanisms of the human brain during specific experimental paradigms. Deep learning models have increasingly been applied for decoding and encoding purposes study to representations in task fMRI data. More recently, graph neural networks, or neural networks models designed to leverage the properties of graph representations, have recently shown promise in task fMRI decoding studies. Here, we propose an end-to-end graph convolutional network (GCN) framework with three convolutional layers to classify task fMRI data from the Human Connectome Project dataset. We compared the predictive performance of our GCN model across four of the most widely used node embedding algorithms—NetMF, RandNE, Node2Vec, and Walklets—to automatically extract the structural properties of the nodes in the functional graph. The empirical results indicated that our GCN framework accurately predicted individual differences (0.978 and 0.976) with the NetMF and RandNE embedding methods, respectively. Furthermore, to assess the effects of individual differences, we tested the classification performance of the model on sub-datasets divided according to gender and fluid intelligence. Experimental results indicated significant differences in the classification predictions of gender, but not high/low fluid intelligence fMRI data. Our experiments yielded promising results and demonstrated the superior ability of our GCN in modeling task fMRI data.
The Protective Role of Mature Defense Mechanisms on Satisfaction with Life in the COVID-19 Era: A Moderated Mediation Analysis
Authors: Gori Alessio , Topino Eleonora , Musetti Alessandro , Giannini Marco , Grotto Rosapia Lauro , Svicher Andrea , Di Fabio Annamaria
Published: August 2022

The COVID-19 pandemic significantly influenced people’s lives, with non-negligible consequences for the perception of well-being. This study sought to examine the effect of anxiety, post-traumatic impairment, and mature defenses on life satisfaction during the COVID-19 pandemic. One thousand three hundred thirty-nine Italian individuals (30% male; 70% female; Mage = 34.70; SD = 11.83) completed an online survey enclosing the Satisfaction with Life Scale, State-Trait Anxiety Inventory—Form X3, Impact of event scale—revised, and the Forty Item Defense Style Questionnaire. To test the hypothesized relationship, data were analyzed by applying a moderated-mediation analysis, a regression-based approach. Results showed that the negative effect of anxiety on life satisfaction was partially mediated by post-traumatic impairment, with a significant moderation effect of mature defenses on the relationship between post-traumatic impairment and life satisfaction. Specifically, with higher levels of mature defenses, the effects of post-traumatic impairment on consequences of the COVID-19 emergency on well-being. Furthermore, the protective role of mature defenses in facing post-traumatic impairment was shown. Such data may have applicative implications in different contexts in a management perspective of the different pandemic phases, contributing to more effective positive strength-based preventive actions to also support positive healthy organizations.
Thermal Modeling of a Historical Building Wall: Using Long-Term Monitoring Data to Understand the Reliability and the Robustness of Numerical Simulations
Authors: Panico Simone , Larcher Marco , Troi Alexandra , Baglivo Cristina , Congedo Paolo Maria
Published: August 2022

Thermal modeling of building components plays a crucial role in designing energy efficiency measures, assessing living comfort, and preventing building damages. The accuracy of the modeling process strongly depends on the reliability of the physical models and the correct selection of input parameters, especially for historic buildings where uncertainties on wall composition and material properties are higher. This work evaluates the reliability of building thermal modeling and identifies the input parameters that most affect the simulation results. A monitoring system is applied to a historic building wall to measure the temperature profile. The long-term dataset is compared with the result of a simulation model. A sensitivity analysis is applied for the determination of the influential input parameters. A two-step optimization is performed to calibrate the numerical model: the first optimization step is based on an optimized selection of the database materials, while the second optimization step uses a particle swarm algorithm. The results indicate that the output of the simulation model is largely influenced by the coefficients describing the coupling with the boundary conditions and by the thermal conductivities of the materials. Very good results are obtained already after the first optimization step (RMSE=0.75 °C) while the second optimization step improves further the agreement (RMSE=0.48 °C). The parameter values reported in the datasheets do not match those found through optimization. Even with extensive optimization using an algorithm, starting with monitoring data is insufficient to identify material parameter values.
Cementitious Insulated Drywall Panels Reinforced with Kraft-Paper Honeycomb Structures
Authors: Shahbazi Sepideh , Singer Nicholas , Majeed Muslim , Kavgic Miroslava , Foruzanmehr Reza
Published: August 2022

Standard building practices commonly use gypsum-based drywall panels on the interior wall and ceiling applications as a partition to protect the components of a wall assembly from moisture and fire to uphold the building code and ensure safety standards. Unfortunately, gypsum-based drywall panels have poor resistance to water and are susceptible to mold growth in humid climates. Furthermore, the accumulation of drywall in landfills can result in toxic leachate impacting the surrounding environment. A proposed solution to the pitfalls of gypsum-based drywall arises in its substitution with a new lightweight composite honeycomb sandwich panel. This study aimed to develop sandwich panels with improvements in flexural strength and thermal insulating properties through the combined use of cementitious binder mix and kraft-paper honeycomb structures. The proposed alternative is created by following standard practices outlined in ASTM C305 to create cement panels and experimenting with admixtures to improve the material performance in order to cater to a drywall panel application. The kraft-paper honeycomb structure is bonded to cured cementitious panels to create a composite “sandwich panel” assembly. The results indicate that the sample flexural strength performed well after 7 days and exhibited superior flexural strength at 28 days, while providing a substantial increase in R-value of 5.84 m2K/W when compared to gypsum-based panels, with an R-value of 5.41 m2K/W. In addition, the reinforced kraft-paper honeycomb with a thick core and addition of flax fibres to the cementitious boards possesses better thermal conductivity, with a reduction of 42%, a lower density, and a lower water vapour transmission in comparison to the thin kraft-paper honeycomb sandwich panel.
Adverse Prognostic Impact of Diagnostic Ureterorenoscopy in a Subset of Patients with High-Risk Upper Tract Urothelial Carcinoma Treated with Radical Nephroureterectomy
Authors: Yonese Ichiro , Ito Masaya , Waseda Yuma , Kobayashi Shuichiro , Toide Masahiro , Takazawa Ryoji , Koga Fumitaka
Published: August 2022

Background: We hypothesized that diagnostic ureterorenoscopy (URS) may adversely affect prognosis in a subset of patients with high-risk upper tract urothelial carcinoma (UTUC) undergoing radical nephroureterectomy (RNU). Methods: The present retrospective study included 143 patients with UTUC treated between 2010 and 2021 at two tertiary care hospitals, of whom 79 received URS prior to RNU. Subgroups were stratified by clinicopathological variables relevant to prognosis. The primary endpoint was to evaluate the prognostic impact of URS on overall survival (OS) and progression-free survival (PFS) after RNU. Results: During follow-up (median 54 months for survivors), 32 cases of all-cause mortality and 40 cases of progression were recorded. No significant difference was found in OS or PFS between patients with and without URS. Subgroup analysis demonstrated that URS was significantly associated with worse OS (p < 0.001) and PFS (p = 0.008) in 29 patients with non-papillary and ≥pT3 UTUC. Importantly, URS did not have any adverse effects on prognosis in 62 patients with papillary and ≤pT2 UTUC (p = 0.005). Conclusions: URS may adversely affect prognosis of UTUC patients, specifically non-papillary and ≥pT3 disease. URS may better be avoided in patients with high-risk UTUC features unless URS is necessary to diagnose UTUC. This study also corroborates the oncological safety of URS in those with low-risk UTUC.
Frequency and Prognostic Significance of Intertumoural Heterogeneity in Multifocal Jejunoileal Neuroendocrine Tumours
Authors: Jesinghaus Moritz , Poppinga Jelte , Lehman Bettina , Maurer Elisabeth , Ramaswamy Annette , Grass Albert , Di Fazio Pietro , Rinke Anja , Denkert Carsten , Bartsch Detlef K.
Published: August 2022

Background: A recent study found that multifocal jejunoileal neuroendocrine tumors (SI-NETs) are genetically unrelated synchronous neoplasms. So far, it is unclear if this finding of synchronous independent neoplasms is mirrored by heterogeneity of key morphological parameters of SI-NETs and how it affects patient survival. Methods: We separately assessed WHO grade (based on the Ki-67 index), expression of basal diagnostic markers (synaptophysin/chromogranin A/CDX2/serotonin), SSTR2a, and the contexture of the immunogenic microenvironment in 146 separate tumors from 28 patients with multifocal SI-NETs and correlated the results with clinicopathological factors and survival. Results: Synaptophysin and chromogranin A were strongly expressed in all tumors. WHO grade was concordant within all multifocal lesions in more than 80% of cases and the highest grade was usually found in the most advanced primary. Intertumoral expression of serotonin, SSTR2, and CDX2 was discrepant in 32%, 43%, and 50% of all patients, respectively. Neither heterogeneity of any of the aforementioned markers nor multifocality itself had any impact on patient survival (p = n.s.). Discussion: Multifocal SI-NET show considerable variability in some of the central diagnostic parameters. However, neither intertumoral heterogeneity of those parameters nor multifocality itself had any impact on patient survival, showing that extensive testing of all multifocal lesions is not necessarily required.
Multiparametric MRI for Staging of Prostate Cancer: A Multicentric Analysis of Predictive Factors to Improve Identification of Extracapsular Extension before Radical Prostatectomy
Authors: Triquell Marina , Regis Lucas , Winkler Mathias , Valdés Nicolás , Cuadras Mercè , Celma Ana , Planas Jacques , Morote Juan , Trilla Enrique
Published: August 2022

The correct identification of extracapsular extension (ECE) of prostate cancer (PCa) on multiparametric magnetic resonance imaging (mpMRI) is crucial for surgeons in order to plan the nerve-sparing approach in radical prostatectomy. Nerve-sparing strategies allow for better outcomes in preserving erectile function and urinary continence, notwithstanding this can be penalized with worse oncologic results. The aim of this study was to assess the ability of preoperative mpMRI to predict ECE in the final prostatic specimen (PS) and identify other possible preoperative predictive factors of ECE as a secondary end-point. We investigated a database of two high-volume hospitals to identify men who underwent a prostate biopsy with a pre-biopsy mpMRI and a subsequent RP. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of mpMRI in predicting ECE were calculated. A univariate analysis was performed to find the association between image staging and pathological staging. A multivariate logistic regression was performed to investigate other preoperative predictive factors. A total of 1147 patients were selected, and 203 out of the 1147 (17.7%) patients were classified as ECE according to the mpMRI. ECE was reported by pathologists in 279 out of the 1147 PS (24.3%). The PPV was 0.58, the NPV was 0.72, the sensitivity was 0.32, and the specificity was 0.88. The multivariate analysis found that PSA (OR 1.057, C.I. 95%, 1.016–1.100, p = 0.006), digital rectal examination (OR 0.567, C.I. 95%, 0.417–0.770, p = 0.0001), ratio of positive cores (OR 9.687, C.I. 95%, 3.744–25.006, p = 0.0001), and biopsy grade in prostate biopsy (OR 1.394, C.I. 95%, 1.025–1.612, p = 0.0001) were independent factors of ECE. The mpMRI has a great ability to exclude ECE, notwithstanding that low sensitivity is still an important limitation of the technique.
Super Enhancer-Regulated LINC00094 (SERLOC) Upregulates the Expression of MMP-1 and MMP-13 and Promotes Invasion of Cutaneous Squamous Cell Carcinoma
Authors: Piipponen Minna , Riihilä Pilvi , Knuutila Jaakko S. , Kallajoki Markku , Kähäri Veli-Matti , Nissinen Liisa
Published: August 2022

Long non-coding RNAs (lncRNAs) have emerged as important regulators of cancer progression. Super enhancers (SE) play a role in tumorigenesis and regulate the expression of specific lncRNAs. We examined the role of BRD3OS, also named LINC00094, in cutaneous squamous cell carcinoma (cSCC). Elevated BRD3OS (LINC00094) expression was detected in cSCC cells, and expression was downregulated by SE inhibitors THZ1 and JQ1 and via the MEK1/ERK1/2 pathway. Increased expression of BRD3OS (LINC00094) was noted in tumor cells in cSCCs and their metastases compared to normal skin, actinic keratoses, and cSCCs in situ. Higher BRD3OS (LINC00094) expression was noted in metastatic cSCCs than in non-metastatic cSCCs. RNA-seq analysis after BRD3OS (LINC00094) knockdown revealed significantly regulated GO terms Cell-matrix adhesion, Basement membrane, Metalloendopeptidase activity, and KEGG pathway Extracellular matrix–receptor interaction. Among the top-regulated genes were MMP1, MMP10, and MMP13. Knockdown of BRD3OS (LINC00094) resulted in decreased production of MMP-1 and MMP-13 by cSCC cells, suppressed invasion of cSCC cells through collagen I, and growth of human cSCC xenografts in vivo. Based on these observations, BRD3OS (LINC00094) was named SERLOC (super enhancer and ERK1/2-Regulated Long Intergenic non-protein coding transcript Overexpressed in Carcinomas). These results reveal the role of SERLOC in cSCC invasion and identify it as a potential therapeutic target in advanced cSCC.
The Shell Matters: Self-Organized CdS-ZnS/MnS-Core-Shell—Porphyrin-Polymer Nano-Assemblies for Photocatalysis
Authors: Wagner Maximilian , Gröhn Franziska
Published: August 2022

A facile synthesis of catalytically tunable core-shell CdS-ZnxMn1-xS-nanoparticles in conjunction with poly(acrylic acid) (PAA) and porphyrin in an aqueous solution is described in the following: The shell composition of the inorganic nanoparticles is varied to tune the optical properties and to optimize the catalytic activity. Further, the tetravalent cationic 5,10,15,20-tetrakis(4-trimethylammoniophenyl) porphyrin (TAPP) fulfills a triple functionality in the catalyst: as a photosensitizer, as an electrostatic linker connecting the nanoparticles and as a probe to investigate the surface composition of the II-VI semiconducting nanoparticles. Different nanoparticles with varying zinc sulfide/manganese sulfide shell ratios are tested with regard to their photocatalytic behavior by crocin bleaching. The results reveal that the shell composition can be a crucial key to optimize the catalytic activity, which can further be important in tuning the reactivity of related systems. Fundamentally, the stepwise multi-component self-assembly in an aqueous solution has been demonstrated to allow the tuning of optic and catalytic properties of core-shell nanoparticles, a general concept that may be widely applicable.
Maresin1 Suppresses High-Glucose-Induced Ferroptosis in Osteoblasts via NRF2 Activation in Type 2 Diabetic Osteoporosis
Authors: Zhang Zhanwei , Ji Chonghao , Wang Ya-Nan , Liu Shiyue , Wang Maoshan , Xu Xin , Zhang Dongjiao
Published: August 2022

Maresin1 (MaR1) is an endogenous pro-resolving lipid mediator produced from polyunsaturated fatty acids and is believed to have antioxidant and anti-inflammatory properties. The objective of this study was to estimate MaR1′s impact on type 2 diabetic osteoporosis (T2DOP) and its pharmacological mode of action. An in vitro high-glucose model of the osteoblast cell line MC3T3-E1 was constructed and stimulated with MaR1. Type 2 diabetic rats were used to establish in vivo models of calvarial defects and were treated in situ with MaR1. The results revealed that, aside from preventing mortality and promoting the osteogenic capacity of MC3T3-E1 cells, MaR1 increased nuclear factor erythroid-2 related factor 2 (NRF2) signaling as well as the activity of glutathione peroxidase 4 (GPX4) and cystine-glutamate antiporter (SLC7A11) and caused the restraint of ferroptosis under hyperglycemic stimulation. However, the therapeutic impact of MaR1 was significantly diminished due to NRF2-siRNA interference and the ferroptosis activator Erastin. Meanwhile, these results were validated through in vivo experiments. These findings imply that MaR1 activated the NRF2 pathway in vivo and in vitro to alleviate high-glucose-induced ferroptosis greatly. More crucially, MaR1 might effectively reduce the risk of T2DOP.
Modulating Chaperone-Mediated Autophagy and Its Clinical Applications in Cancer
Authors: Hubert Virginie , Weiss Sebastian , Rees Andrew Jackson , Kain Renate
Published: August 2022

Autophagy is a central mechanism for maintaining cellular homeostasis in health and disease as it provides the critical energy through the breakdown and recycling of cellular components and molecules within lysosomes. One of the three types of autophagy is chaperone-mediated autophagy (CMA), a degradation pathway selective for soluble cytosolic proteins that contain a targeting motif related to KFERQ in their amino acid sequence. This motif marks them as CMA substrate and is, in the initial step of CMA, recognised by the heat shock protein 70 (Hsc70). The protein complex is then targeted to the lysosomal membrane where the interaction with the splice variant A of the lysosomal-associated membrane protein-2 (LAMP-2A) results in its unfolding and translocation into the lysosome for degradation. Altered levels of CMA have been reported in a wide range of pathologies including many cancer types that upregulate CMA as part of the pro-tumorigenic phenotype, while in aging a decline is observed and associated with a decrease of LAMP-2 expression. The potential of altering CMA to modify a physiological or pathological process has been firmly established through genetic manipulation in animals and chemical interference with this pathway. However, its use for therapeutic purposes has remained limited. Compounds used to target and modify CMA have been applied successfully to gain a better understanding of its cellular mechanisms, but they are mostly not specific, also influence other autophagic pathways and are associated with high levels of toxicity. Here, we will focus on the molecular mechanisms involved in CMA regulation as well as on potential ways to intersect them, describe modulators successfully used, their mechanism of action and therapeutic potential. Furthermore, we will discuss the potential benefits and drawbacks of CMA modulation in diseases such as cancer.
Structure and Corrosion Resistance of Coatings Obtained by the Batch Double Hot Dip Method in Eutectoid ZnAl Bath with the Addition of Mg and Si
Authors: Kania Henryk
Published: August 2022

The article presents the results of the research determining the synergistic effect of Mg and Si additives in the ZnAl23 bath on the microstructure (SEM), growth kinetics, and corrosion resistance of coatings obtained by the batch double hot dip method. On the basis of the research on the chemical composition in micro-regions (EDS) and the research on the phase composition (XRD), the structural components of the coatings with a content of 3 and 6 wt.% Mg and 0.2–0.4 wt.% Si were identified. The corrosion resistance of the coatings was compared with that of the reference coating obtained in the ZnAl23Si0.4 bath in the neutral salt spray test (EN ISO 9227), and the test with sulfur dioxide in a humid atmosphere (EN ISO 6988). The parameters of electrochemical corrosion of the coatings were determined. This allowed for the conclusion that the addition of Mg and Si to the ZnAl23 bath improved the microstructural uniformity of the coating. In the area of the diffusion layer, the presence of the FeAl3 intermetallic phase was found, while in the outer layer the dendrite of the Al-rich solution with interdendritic spaces, where it locates areas of Zn-rich solution, eutectic Zn/MgZn2 or phase separation MgZn2 and Mg2Si are located. Additions of Mg and Si stabilize the kinetics of the coating’s growth, and its course is parabolic. The conducted corrosion tests showed better corrosion resistance of the coatings obtained in the bath with Mg addition compared to the reference coating obtained in the ZnAl23Si bath. The increase in corrosion resistance results from the presence of a more anodic MgZn2 phase, which, however, may be weakened by the presence of Mg2Si phase precipitates.