bluuebunny/crossref_metadata_2025 huggingface dataset:
Experimental Study on Improvement Mechanism of Electric Heating-Assisted Cyclic Steam Stimulation of Horizontal Well
Authors: Zhang Jipeng , Wu Yongbin , Wang Chao , Lv Bolin , Jiang Youwei , Liu Pengcheng
Published: November 2022

To resolve the issues of the high porous medium flow resistance, low oil production rate, high oil decline rate, and low oil recovery factor for the cyclic steam stimulation (CSS) of horizontal wells in heavy oil reservoirs, the CSS method assisted by the electric heating (E-CSS) of horizontal wells was proposed in this study. Combining the heat from electric heating and steam during E-CSS, the analytical model of formation temperature rise was established for the three phases of electric-assisted CSS (i.e., injection, soaking, production), and physical experiments were carried out to compare the performance of conventional CSS and E-CSS. The experimental results were used to validate the analytical model and reveal the impact of the key electric heating mechanism on the horizontal CSS performance. Meanwhile, the typical well model was used to forecast the E-CSS potential. The results indicate that electric heating can achieve uniform heating in the steam injection phase, maintain heating around the wellbore in the soak phase, and reduce flow resistance and enhance oil output in the production phase. Forecasts of the typical well model indicate that electric heating can enhance the oil recovery factor by 9.4% and the oil-steam ratio from 0.14 to 0.23, implying a significant application potential in heavy oil reservoirs developed by horizontal CSS.
Hyperspectral Image Classification Using 3D Capsule-Net Based Architecture
Authors: Ryu Jihyoung , Jang Yeongmin
Published: November 2022

Convolution neural networks have received much interest recently in the categorization of hyperspectral images (HSI). Deep learning requires a large number of labeled samples in order to optimize numerous parameters due to the expansion of architecture depth and feature aggregation. Unfortunately, only few examples with labels are accessible, and the majority of spectral images are not labeled. For HSI categorization, the difficulty is how to acquire richer features with constrained training data. In order to properly utilize HSI features at various scales, a 3D Capsule-Net based supervised architecture is presented in this paper for HSI classification. First, the input data undergo incremental principal component analysis (IPCA) for dimensionality reduction. The reduced data are then divided into windows and given to a 3D convolution layer to get the shallow features. These shallow features are then used by 3D Capsule-Net to compute high-level features for classification of HSI. Experimental investigation on three common datasets demonstrates that the categorization performance by Capsule-Net based architecture exceeds a number of other state-of-the-art approaches.
Research on Generalized Hybrid Probability Convolutional Neural Network
Authors: Zhou Wenyi , Fan Hongguang , Zhu Jihong , Wen Hui , Xie Ying
Published: November 2022

This paper first studies the generalization ability of the convolutional layer as a feature mapper (CFM) for extracting image features and the classification ability of the multilayer perception (MLP) in a CNN. Then, a novel generalized hybrid probability convolutional neural network (GHP-CNN) is proposed to solve abstract feature classification with an unknown distribution form. To measure the generalization ability of the CFM, a new index is defined and the positive correlation between it and the CFM is researched. Generally, a fully trained CFM can extract features that are beneficial to classification, regardless of whether the data participate in training the CFM. In the CNN, the fully connected layer in the MLP is not always optimal, and the extracted abstract feature has an unknown distribution. Thus, an improved classifier called the structure-optimized probabilistic neural network (SOPNN) is used for abstract feature classification in the GHP-CNN. In the SOPNN, the separability information is not lost in the normalization process, and the final classification surface is close to the optimal classification surface under the Bayesian criterion. The proposed GHP-CNN utilizes the generalization ability of the CFM and the classification ability of the SOPNN. Experiments show that the proposed network has better classification ability than the existing hybrid neural networks.
Differential Effects of Resveratrol on HECa10 and ARPE-19 Cells
Authors: Leśniak Monika , Rokicki Dariusz , Synowiec Agnieszka , Filipiak-Duliban Aleksandra , Skopiński Piotr , Lewicka Aneta , Lewicki Sławomir
Published: November 2022

Age-related macular degeneration (AMD) and diabetic retinopathy are the leading cause of blindness in developed countries. Pathological angiogenesis has a causal role in these eye diseases. Resveratrol (RSV), a plant-derived polyphenol, has anti-proliferative and anti-angiogenic properties that could improve its management. Here, the effects of various concentrations of RSV (1, 5, 10, 50, 100 µM) were compared in two types of cell lines: HECa10 (endothelial cell line) and ARPE-19 (retinal pigment epithelial cell line). We assayed the impact on proliferation rate, viability, cell cycle progression, and secretion of selected proangiogenic factors VEGF and bFGF. We show that lower concentrations of RSV (1, 5, 10 µM) had no effect on proliferation, viability or cell cycle progression in HECa10 cells. However, higher concentrations (50, 100 µM) significantly enhanced the reduction in the cell number and stimulated apoptosis. In ARPE-19 cells, lower concentrations of RSV increased the rate of proliferation, while higher concentrations had no effect on proliferation and viability. Both ARPE-19 and HECa10 cell lines were affected to different degrees in the secretion of proangiogenic cytokines: reducing VEGF and enhancing bFGF secretion. These results suggest that RSV may be useful in the prevention or treatment of pathological angiogenesis in eye disorders.
De Novo Transcriptome Analysis of the Lizard Fish (Saurida elongata): Novel Insights into Genes Related to Sex Differentiation
Authors: Shan Binbin , Wang Liangming , Liu Yan , Yang Changping , Liu Manting , Sun Dianrong , Huang Pujiang
Published: November 2022

Among vertebrates, teleost fishes exhibit the largest array of sex-determining systems, resulting in many reproductive strategies. Screening these fish for sex-related genes could enhance our understanding of sexual differentiation. The lizardfish, Saurida elongata (Temminck & Schlegel, 1846), is a commercially important marine fish in tropical and subtropical seas of the northwest Pacific. However, little genomic information on S. elongata is available. In this study, the transcriptomes of three female and three male S. elongata were sequenced. A total of 49.19 million raw read pairs were generated. After identification and assembly, a total of 59,902 nonredundant unigenes were obtained with an N50 length of 2070 bp. Then, 38,016 unigenes (63.47% of the total) were successfully annotated through multiple public databases. A comparison of the unigenes of different sexes of S. elongata revealed that 22,507 unigenes (10,419 up-regulated in a female and 12,088 up-regulated in a male) were differentially expressed between sexes. Then, numerous candidate sex-related genes were identified, including dmrt2, dmrt4, foxl2, zps and starts. Furthermore, 23,941 simple sequence repeats (SSRs) were detected in SSR-containing sequences. This informative transcriptome analysis provides valuable data to increase the genomic resources of S. elongata.
Development of a Metasilencer Considering Flow in HVAC Systems
Authors: Kim Hyunsu , Kwon Yoonjung , Lee Sangwoo , Kim Juin , Park Dongchul
Published: November 2022

Although the driving noise of electric vehicles has been reduced compared with that of internal combustion engine vehicles, a new interior noise problem is emerging. It is crucial to reduce the noise of the heating, ventilation, and air conditioning (HVAC) system, which is one of the main causes of interior noise. Therefore, in this study, a metasilencer with an acoustic metasurface structure is presented. The metasilencer was designed to restrain the travel direction of the sound wave of the target frequency into a U-shaped configuration using an acoustic metasurface while considering the flow noise effect of the HVAC system. Acoustic analysis confirmed the noise reduction frequency range and refraction effect of the metasurface. The speaker test confirmed the noise reduction effect of the silencer. The same was also confirmed via HVAC tests, even in the presence of a flow.
Numerical Simulation and Application of Transient Electromagnetic Detection Method in Mine Water-Bearing Collapse Column Based on Time-Domain Finite Element Method
Authors: Guo Changfang , Tan Tingjiang , Ma Liuzhu , Chang Shuai , Zhao Ke
Published: November 2022

Mine floods caused by water-bearing collapse columns are one of the most significant types of coal mine disasters in advanced detection. The transient electromagnetic method (TEM), one of the most effective means, can detect the collapse column in coal mines. However, the research on TEM used on the ground is mainly limited to half-space that does not follow underground mining conditions. This research used the whole-space TEM to detect the water-bearing collapse columns in front of the roadway. Based on the time-domain finite element method (TDFEM) and actual coal-measure strata data, this paper built the whole-space geo-electric models, summarized response characteristics, and proposed “geometric gravity center” effect. The results showed that the simulation based on TDFEM could accurately reflect the TEM response law, and the advanced detection using TEM in a mine environment was consistent with the actual situation.
New Fractional Integral Inequalities Pertaining to Caputo–Fabrizio and Generalized Riemann–Liouville Fractional Integral Operators
Authors: Tariq Muhammad , Alsalami Omar Mutab , Shaikh Asif Ali , Nonlaopon Kamsing , Ntouyas Sotiris K.
Published: November 2022

Integral inequalities have accumulated a comprehensive and prolific field of research within mathematical interpretations. In recent times, strategies of fractional calculus have become the subject of intensive research in historical and contemporary generations because of their applications in various branches of science. In this paper, we concentrate on establishing Hermite–Hadamard and Pachpatte-type integral inequalities with the aid of two different fractional operators. In particular, we acknowledge the critical Hermite–Hadamard and related inequalities for n-polynomial s-type convex functions and n-polynomial s-type harmonically convex functions. We practice these inequalities to consider the Caputo–Fabrizio and the k-Riemann–Liouville fractional integrals. Several special cases of our main results are also presented in the form of corollaries and remarks. Our study offers a better perception of integral inequalities involving fractional operators.
Fixed Point Results for a Family of Interpolative F-Contractions in b-Metric Spaces
Authors: Konwar Nabanita , Debnath Pradip
Published: November 2022

In this paper, we introduce a new generalized concept, namely, extended interpolative Cirić–Reich–Rus-type F-contraction in b-metric space. In addition, we put forward the notion of interpolative Kannan-type F-contractions. Fixed point results for these new interpolative contraction mappings are established, and non-trivial examples involving finite and infinite sets are provided to validate the results.
Deep Eutectic Solvents for Biodiesel Purification in a Microextractor: Solvent Preparation, Selection and Process Optimization
Authors: Anđelović Sara , Božinović Marko , Ćurić Željka , Šalić Anita , Jurinjak Tušek Ana , Kučan Kristina Zagajski , Rogošić Marko , Radović Mia , Cvjetko Bubalo Marina , Zelić Bruno
Published: November 2022

The most important and commonly used process for biodiesel synthesis is transesterification. The main by-product of biodiesel synthesis by transesterification is glycerol, which must be removed from the final product. Recently, deep eutectic solvent (DES) assisted extraction has been shown to be an effective and sustainable method for biodiesel purification. In this study, biodiesel was produced by lipase-catalysed transesterification from sunflower oil and methanol. A total of 12 different eutectic solvents were prepared and their physical properties were determined. Mathematical models were used to define which physical and chemical properties of DES and to what extent affect the efficiency of extraction of glycerol from the biodiesel. After initial screening, cholinium-based DES with ethylene glycol as hydrogen bond donor was selected and used for optimization of extraction process conditions performed in a microsystem. To determine the optimal process conditions (temperature, biodiesel:DES volume ratio, residence time), the experimental three-level-three-factor Box-Behnken experimental design was used. In the end, a combination of a mathematical model and experimental results was used to estimate how many micro-extractors are necessary for the complete removal of glycerol.
Cellular Immuno-Profile in Septic Human Host: A Scoping Review
Authors: Zanza Christian , Caputo Giorgia , Tornatore Gilda , Romenskaya Tatsiana , Piccioni Andrea , Franceschi Francesco , Artico Marco , Taurone Samanta , Savioli Gabriele , Longhitano Yaroslava
Published: November 2022

Innate and adaptive immune system cells play a critical role in the host response to sepsis. Sepsis is a life-threatening disease characterized by apoptosis-induced depletion of immune cells and immunodepression, which contribute to morbidity and mortality. Many alterations in the expression of surface markers of neutrophils and monocytes have been described in septic patients. The aim of this study was to inspect the recently published literature to inform the clinician about the most up-to-date techniques for the study of circulating leukocytes. The impact on cell phenotypes and on the function of leukocytes of extracorporeal and non-blood purification treatments proposed for sepsis were also analyzed. We conducted a systematic review using Pubmed/Medline, Ovid/Willey, the Cochrane Library, the Cochrane Controlled Trials Register, and EMBASE, combining key terms related to immunological function in sepsis and selected the most relevant clinical trials and review articles (excluding case reports) published in the last 50 years. The most important alteration in neutrophils during sepsis is that they activate an anti-apoptotic survival program. In septic monocytes, a reduced characteristic expression of HLA-DR is observed, but their role does not seem to be significantly altered in sepsis. As regards adaptive immunity, sepsis leads to lymphopenia and immunosuppression in patients with septic shock; this process involves all types of T cells (CD4, CD8 and Natural Killer), except for regulatory T cells, which retain their function. Several promising therapies that target the host immune response are currently under evaluation. During the worldwide pandemic caused by SARS-CoV-2, it was useful to study the “cytokine storm” to find additional treatments, such as the oXiris® filter. This therapy can decrease the concentration of inflammatory markers that affect the severity of the disease.
High-Resolution Genetic Mapping Combined with Transcriptome Profiling Reveals That Both Target-Site Resistance and Increased Detoxification Confer Resistance to the Pyrethroid Bifenthrin in the Spider Mite Tetranychus urticae
Authors: De Beer Berdien , Vandenhole Marilou , Njiru Christine , Spanoghe Pieter , Dermauw Wannes , Van Leeuwen Thomas
Published: November 2022

Pyrethroids are widely applied insecticides in agriculture, but their frequent use has provoked many cases of resistance, in which mutations in the voltage-gated sodium channel (VGSC), the pyrethroid target-site, were shown to play a major role. However, for the spider mite Tetranychus urticae, it has also been shown that increased detoxification contributes to resistance against the pyrethroid bifenthrin. Here, we performed QTL-mapping to identify the genomic loci underlying bifenthrin resistance in T. urticae. Two loci on chromosome 1 were identified, with the VGSC gene being located near the second QTL and harboring the well-known L1024V mutation. In addition, the presence of an L925M mutation in the VGSC of a highly bifenthrin-resistant strain and its loss in its derived, susceptible, inbred line indicated the importance of target-site mutations in bifenthrin resistance. Further, RNAseq experiments revealed that genes encoding detoxification enzymes, including carboxyl/choline esterases (CCEs), cytochrome P450 monooxygenases and UDP-glycosyl transferases (UGTs), were overexpressed in resistant strains. Toxicity bioassays with bifenthrin (ester pyrethroid) and etofenprox (non-ester pyrethroid) also indicated a possible role for CCEs in bifenthrin resistance. A selection of CCEs and UGTs were therefore functionally expressed, and CCEinc18 was shown to metabolize bifenthrin, while teturUGT10 could glycosylate bifenthrin-alcohol. To conclude, our findings suggest that both target-site and metabolic mechanisms underlie bifenthrin resistance in T. urticae, and these might synergize high levels of resistance.
Potential Anticancer Activity of Pomegranate (Punica granatum L.) Fruits of Different Color: In Vitro and In Silico Evidence
Authors: Cortez-Trejo Maria C. , Olivas-Aguirre Francisco J. , Dufoo-Hurtado Elisa , Castañeda-Moreno Raquel , Villegas-Quintero Hassan , Medina-Franco José L. , Mendoza Sandra , Wall-Medrano Abraham
Published: November 2022

Pomegranate (PMG; Punica granatum L.) fruits possess a well-balanced nutrient/phytochemical composition, with proven adjuvant benefits in experimental cancer chemotherapy; however, such bioactivity could be affected by PMG’s phenogenotype (varietal). Here, the chemical and phytochemical (UPLC-DAD-MS2) composition, antioxidant capacity and anticancer potential [in vitro (MTT assay) and in silico (foodinformatics)] of three PMG fruits of different aryl color [red (cv. Wonderful), pink (cv. Molar de Elche), and white (cv. Indian)] were evaluated. The macro/micronutrient (ascorbic acid, tocols, carotenoids), organic acid (citric/malic), and polyphenol content were changed by PMG’s varietal and total antioxidant activity (ABTS, alcoholic > hexane extract) in the order of red > pink > white. However, their in vitro cytotoxicity was the same (IC50 > 200 μg.mL−1) against normal (retinal) and cancer (breast, lung, colorectal) cell lines. Sixteen major phytochemicals were tentatively identified, four of them with a high GI absorption/bioavailability score [Ellagic (pink), vanillic (red), gallic (white) acids, D-(+)-catechin (white)] and three of them with multiple molecular targets [Ellagic (52) > vanillic (32) > gallic (23)] associated with anticancer (at initiation and promotion stages) activity. The anticancer potential of the PMG fruit is phenogenotype-specific, although it could be more effective in nutraceutical formulations (concentrates).
Structural Basis of Sequential and Concerted Cooperativity
Authors: Morea Veronica , Angelucci Francesco , Tame Jeremy R. H. , Di Cera Enrico , Bellelli Andrea
Published: November 2022

Allostery is a property of biological macromolecules featuring cooperative ligand binding and regulation of ligand affinity by effectors. The definition was introduced by Monod and Jacob in 1963, and formally developed as the “concerted model” by Monod, Wyman, and Changeux in 1965. Since its inception, this model of cooperativity was seen as distinct from and not reducible to the “sequential model” originally formulated by Pauling in 1935, which was developed further by Koshland, Nemethy, and Filmer in 1966. However, it is difficult to decide which model is more appropriate from equilibrium or kinetics measurements alone. In this paper, we examine several cooperative proteins whose functional behavior, whether sequential or concerted, is established, and offer a combined approach based on functional and structural analysis. We find that isologous, mostly helical interfaces are common in cooperative proteins regardless of their mechanism. On the other hand, the relative contribution of tertiary and quaternary structural changes, as well as the asymmetry in the liganded state, may help distinguish between the two mechanisms.
Polysaccharide-Peptide from Trametes versicolor: The Potential Medicine for Colorectal Cancer Treatment
Authors: He Zhicheng , Lin Jian , He Yingying , Liu Shubai
Published: November 2022

The incidence and mortality of colorectal cancer have shown an upward trend in the past decade. Therefore, the prevention, diagnosis, and treatment of colorectal cancer still need our continuous attention. Finding compounds with strong anticancer activity and low toxicity is a good strategy for colorectal cancer (CRC) therapy. Trametes versicolor is a traditional Chinese medicinal mushroom with a long history of being used to regulate immunity and prevent cancer. Its extractions were demonstrated with strong cell growth inhibitory activity on human colorectal tumor cells, while the anticancer activity of them is not acted through a direct cytotoxic effect. However, the intricacy and high molecular weight make mechanistic research difficult, which restricts their further application as a medication in clinical cancer treatment. Recent research has discovered a small molecule polysaccharide peptide derived from Trametes versicolor that has a distinct structure after decades of Trametes versicolor investigation. Uncertain molecular weight and a complex composition are problems that have been solved through studies on its structure, and it was demonstrated to have strong anti-proliferation activity on colorectal cancer in vitro and in vivo via interaction with EGFR signaling pathway. It opens up new horizons for research in this field, and these low molecular weight polysaccharide peptides provide a new insight of regulation of colorectal cancer proliferation and have great potential as drugs in the treatment of colorectal cancer.
Multiple Sclerosis and MEN2 Neoplasia in a Female Patient: A Unique Co-Existence with Expanded Immunological Interest and Therapeutical Challenges, before and after Patient’s COVID-19 Infection
Authors: Markoglou Nikolaos , Simeakis George , Alevizaki Maria , Velonakis Georgios , Chatzistamatiou Theofanis , Spyropoulou-Vlachou Maria , Stavropoulos-Giokas Catherine , Stefanis Leonidas , Anagnostouli Maria
Published: November 2022

Multiple sclerosis (MS) and its various comorbidities that may be observed are of great interest due to the complexity of MS pathophysiology and all of the immunological changes that follow. The incidence of cancer in MS has been investigated for several years, as not only does it affect ongoing therapeutical decisions, but also, certain disease-modifying treatments (DMTs) may increase the risk of tumorigenesis. For the first time, we present a case of a female patient with pediatric-onset MS (POMS) and multiple endocrine neoplasia 2B (MEN2B) and analyze the immunological impact of these diseases on the therapeutical choice, under the umbrella of her COVID-19 infection and the SARS-CoV-2 pandemic as a whole. We also review the existing literature regarding the immunogenetic and immunological correlations between these two extremely rare diseases and discuss the most suitable treatment for our case, which seems to be an anti-CD20 agent due to a better outcome in putative MS worsening and tumor progression, when killer immunoglobulin-like receptors’ (KIR) expression is reduced in natural killer (NK) cells. We also broaden our concerns on this comorbidity issue, at the same time focusing on the future research needed in this unexplored field of the comorbidity of MS and cancers.
Membrane Blue Dual Protects Retinal Pigment Epithelium Cells/Ganglion Cells—Like through Modulation of Mitochondria Function
Authors: Grossini Elena , Venkatesan Sakthipriyan , Alkabes Micol , Toma Caterina , de Cillà Stefano
Published: November 2022

Although recent data highlight the greater protective effects exerted by Membrane Blue Dual (MBD), a precise analysis of the mechanisms of action is missing. We examined the effects of MBD with/without polyethylene glycol (PEG) on both human retinal pigment epithelial cells (ARPE-19) and retinal ganglion cells-like (RGC-5) cultured in the presence/absence of ultraviolet B (UVB) treatment on mitochondria function, oxidants, and apoptosis. In ARPE-19/RGC-5 cells either treated or not with UVB, the effects of MBD with/without PEG were evaluated by specific assays for viability, mitochondrial membrane potential and mitochondrial reactive oxygen species (mitoROS) release. Annexin V was used to detect apoptosis, whereas trypan blue and the scratch assay were used for proliferation/migration. In both physiologic conditions and in the presence of UVB, MBD with/without PEG increased cell viability, mitochondrial membrane potential, proliferation and migration in both ARPE-19 and RGC-5 cells. In general, the effects of MBD with PEG were greater than those caused by MBD without PEG. Our results suggest that, in particular, MBD with PEG is a safe and effective dye for vitreoretinal surgery through the modulation of mitochondrial function.
Angiotensin-Converting Enzyme 2-Based Biosensing Modalities and Devices for Coronavirus Detection
Authors: Gul Ijaz , Zhai Shiyao , Zhong Xiaoyun , Chen Qun , Yuan Xi , Du Zhicheng , Chen Zhenglin , Raheem Muhammad Akmal , Deng Lin , Leeansyah Edwin , Zhang Canyang , Yu Dongmei , Qin Peiwu
Published: November 2022

Rapid and cost-effective diagnostic tests for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are a critical and valuable weapon for the coronavirus disease 2019 (COVID-19) pandemic response. SARS-CoV-2 invasion is primarily mediated by human angiotensin-converting enzyme 2 (hACE2). Recent developments in ACE2-based SARS-CoV-2 detection modalities accentuate the potential of this natural host-virus interaction for developing point-of-care (POC) COVID-19 diagnostic systems. Although research on harnessing ACE2 for SARS-CoV-2 detection is in its infancy, some interesting biosensing devices have been developed, showing the commercial viability of this intriguing new approach. The exquisite performance of the reported ACE2-based COVID-19 biosensors provides opportunities for researchers to develop rapid detection tools suitable for virus detection at points of entry, workplaces, or congregate scenarios in order to effectively implement pandemic control and management plans. However, to be considered as an emerging approach, the rationale for ACE2-based biosensing needs to be critically and comprehensively surveyed and discussed. Herein, we review the recent status of ACE2-based detection methods, the signal transduction principles in ACE2 biosensors and the development trend in the future. We discuss the challenges to development of ACE2-biosensors and delineate prospects for their use, along with recommended solutions and suggestions.
Operational Risk Management of Public–Private Partnership Infrastructure Projects: A Bibliometric Literature Review
Authors: Jiang Weiling , Yang Qianying , Jiang Jie , Martek Igor , Gao Fanjie
Published: November 2022

Public–private partnerships (PPPs) are widely applied in the procurement of capital infrastructure, encompassing phases such as financing, design, construction, operation, and transfer. Of these, the operational phase of PPPs is particularly critical to project success given this is when revenues are generated, and costs recouped. However, the revenue stream will be exposed to numerous risks over the relatively long period of infrastructure operation. Management of PPP operational risk is therefore critical. Despite this importance, research dedicated to PPP operational risk management remains limited. Thus, this paper addresses this deficiency by systematically reviewing related studies and proposing an operational risk management framework. A qualitative bibliometric literature review is conducted on 60 papers pertinent to operational risk management, published across 12 peer review journals. Findings reveal that the industry lacks a systematic operational risk factor list, while the impacts of risks are rarely considered when allocating operational risk factors, and moreover that the research on the selection and efficacy of operational risk management strategies remains undeveloped. This study reveals where further efforts in the research of operational risk management of PPP infrastructure projects could be more fruitfully applied.
Numerical and Statistical Evaluation of the Performance of Carbon Fiber-Reinforced Polymers as Tunnel Lining Reinforcement during Subway Operation
Authors: Chango Ishola Valere Loic , Chen Jun
Published: November 2022

Ground vibrations during train operations have become a serious problem in recent years. Local residents often feel disturbed by the vibrations emanating from the railroad line. This inconvenience is particularly pronounced in loose areas traversed by subways. However, improving the mechanical properties of tunnels has been the subject of several studies. Among these works, the widely discussed fiber-reinforced polymer (FRP) is considered as a material that can be incorporated into the tunnel structure to increase stiffness, durability, and corrosion resistance. However, the function of FRP in the interaction between the soil and the tunnel during operation has scarcely been studied. In this study, the effectiveness of carbon fiber-reinforced polymers (CFRP) as reinforcement of tunnel lining on ground vibration is investigated. For this purpose, a nonlinear 3D finite element model was developed based on a subway section in Shanghai to simulate the dynamic behavior of the system. The moving subway load was modeled as a transient dynamic load via a DLOAD subroutine, in which the rail irregularities are taken into account. The numerical model was efficiently validated by field tests. Then, the efficiency of using CFRP as concrete reinforcement of the tunnel lining during the subway operation was investigated. In addition, a statistical analysis of the ground dynamic response depending on the CFRP bars properties is presented, evaluated, and discussed.
Feasibility Evaluation of Novel High-Damping Rubbers as Energy-Dissipation Material under Axial Dynamic Load for Damper Devices
Authors: Teh Tzyy Wooi , Tan Chee Ghuan , Jumaat Mohd Zamin
Published: November 2022

High-damping rubber (HDR) material has been widely used in bearings for seismic-isolation devices in structures. Nevertheless, HDR has not yet been developed in dampers to reduce the response of structures to earthquake excitations by dissipating the energy applied to the structures under direct axial load. The purpose of this paper was to evaluate the feasibility of using novel hyperelastic composite material (HECM), which is an HDR material, in experimental investigations to determine its damping ratio, compressibility, and elasticity behavior under axial dynamic load for the development of novel dampers in the future. First, a series of tests on HECM was conducted using the double-shear method to determine the most suitable sample for a purely dynamic compression test. Subsequently, the HECM was used in a device working as a scaled-down damper under both direct tension and compression dynamic load conditions, and pure direct compression dynamic load conditions were tested. Various thicknesses of the HECM (6, 8, and 10 mm) used in the testing damper were examined under a constant force with various frequencies of 0.01, 0.1, 0.25, and 0.5 Hz. The results show that the 10 mm thick HECM can provide a high damping ratio of 10% to 13% under axial conditions. Hence, this study is important for evaluating HECM, which has the potential for use in developing a full-scaled rubber damper system to resist axial force in the future. The damper is a novel rubber damper with high damping capability to dissipate energy under axial load. Furthermore, the damper can serve as an alternative choice that is more durable and overcomes the current weaknesses of passive dampers.
Seismic Energy Upgrading of an Existing Brick Masonry Building by a Cold-Formed Steel Envelope System
Authors: Davino Antonio , Longobardi Giovanna , Meglio Emilia , Dallari Andrea , Formisano Antonio
Published: November 2022

In recent years, new solutions have been studied in order to intervene on existing buildings made of load-bearing masonry or reinforced concrete, both from the seismic point of view and the energy one. In recent years, novel modern techniques using lightweight steel profiles made of steel or aluminium alloys, suitably coupled with heat-insulating panels, have been proposed for requalification of existing building stock. In this paper, the Resisto 5.9 system designed by the Progetto Sisma S.r.l. company was studied and applied as a retrofit system of an existing masonry building. First, this new system for seismic energy requalification of the build-up was presented, describing the basic components and the mounting phases. Subsequently, it has applied to a case study building made of full-brick masonry located in the municipality of Casalecchio di Reno, on the outskirts of Bologna in Northern Italy. Finally, the used coating system was designed for the examined building together with other seismic interventions applied to horizontal structures and foundations. The seismic benefits deriving from using the proposed envelope system and other seismic interventions were proved from the seismic viewpoint by linear dynamic and non-linear static analyses using the TreMuri analysis software. From modal analysis it was seen that the dynamic behaviour of the building with Resisto 5.9 is improved, with an increase of the participating mass (68% instead of 49% of the bare building) of the second mode in the longitudinal direction. Moreover, from pushover analysis it was noticed that the seismic safety factor has passed from 0.51 to 1.05 in the X-direction and from 0.78 to 1.27 in the Y-direction. In conclusion, it was demonstrated that Resisto 5.9, together with all the other planned interventions, is able to accomplish the seismic retrofitting of the studied building.
Viscosity Reduction and Mechanism of Aquathermolysis of Heavy Oil Co-Catalyzed by Bentonite and Transition Metal Complexes
Authors: Zhang Wangyuan , Li Qi , Li Yongfei , Dong Sanbao , Peng Sen , Chen Gang
Published: November 2022

At present, the research on aquathermolysis catalysts mainly focuses on the catalytic effect of external catalysts on the reaction, ignoring the fact that external catalysts will form complexes with in situ inorganic minerals after entering the reservoir. In this paper, we investigated the effects of transition metal complexes as external catalysts and bentonite as in situ catalysts on aquathermolysis, respectively. Meanwhile, the aquathermolysis reaction co-catalyzed by external and in situ catalysts was further investigated. The results show that the transition metal complexes exhibited good co-catalysis with bentonite. The viscosity reduction rate can reach 73.47% at 200 °C and 4 h with 0.1 wt.% of catalyst (NAD–Zn) addition. The addition of ethanol under the same reaction conditions will further increase the viscosity reduction rate to 84.59%. The results of thermogravimetric analysis, component analysis and boiling range analysis of heavy oil show that the heavy components in heavy oil are cracked into light components after the aquathermolysis. The results of elemental analysis show that the heteroatoms in the heavy oil were removed and the quality of the crude oil was improved. The results of GC–MS analysis of the model compounds showed that the process of aquathermolysis was mainly through the cleavage of C–C, C–N and C–S bonds to crack the macromolecules into small molecules, and then achieve the effect of viscosity reduction. The main mechanism of catalyst action is the acidic center on the surface of the bentonite and the coordination bonds formed by the transition metal complexes with the heteroatoms.
Video-Feedback Approach Improves Parental Compliance to Early Behavioral Interventions in Children with Autism Spectrum Disorders during the COVID-19 Pandemic: A Pilot Investigation
Authors: Aiello Stefania , Leonardi Elisa , Cerasa Antonio , Servidio Rocco , Famà Francesca Isabella , Carrozza Cristina , Campisi Agrippina , Marino Flavia , Scifo Renato , Baieli Sabrina , Corpina Flavio , Tartarisco Gennaro , Vagni David , Pioggia Giovanni , Ruta Liliana
Published: November 2022

In the field of autism intervention, a large amount of evidence has demonstrated that parent-mediated interventions are effective in promoting a child’s learning and parent caring skills. Furthermore, remote delivery treatments are feasible and can represent a promising opportunity to reach families at distance with positive results. Recently, the sudden outbreak of COVID-19 dramatically disrupted intervention services for autism and forced an immediate reorganization of the territory services toward tele-assisted intervention programs, according to professional and local resources. Our study aimed to conduct a retrospective pilot exploratory investigation on parental compliance, participation, and satisfaction in relation to three different telehealth intervention modalities, such as video feedback, live streaming, and psychoeducation, implemented in the context of a public community setting delivering early autism intervention during the COVID-19 emergency. We found that parents who attended video feedback expressed the highest rate of compliance and participation, while parental psychoeducation showed significantly lower compliance and the highest drop-out rate. Regardless of the tele-assistance modality, all the participants expressed satisfaction with the telehealth experience, finding it useful and effective. Potential benefits and advantages of different remote modalities with reference to parent involvement and effectiveness are important aspects to be taken into account and should be further investigated in future studies.
A Ranking Learning Model by K-Means Clustering Technique for Web Scraped Movie Data
Authors: Sarker Kamal Uddin , Saqib Mohammed , Hasan Raza , Mahmood Salman , Hussain Saqib , Abbas Ali , Deraman Aziz
Published: November 2022

Business organizations experience cut-throat competition in the e-commerce era, where a smart organization needs to come up with faster innovative ideas to enjoy competitive advantages. A smart user decides from the review information of an online product. Data-driven smart machine learning applications use real data to support immediate decision making. Web scraping technologies support supplying sufficient relevant and up-to-date well-structured data from unstructured data sources like websites. Machine learning applications generate models for in-depth data analysis and decision making. The Internet Movie Database (IMDB) is one of the largest movie databases on the internet. IMDB movie information is applied for statistical analysis, sentiment classification, genre-based clustering, and rating-based clustering with respect to movie release year, budget, etc., for repository dataset. This paper presents a novel clustering model with respect to two different rating systems of IMDB movie data. This work contributes to the three areas: (i) the “grey area” of web scraping to extract data for research purposes; (ii) statistical analysis to correlate required data fields and understanding purposes of implementation machine learning, (iii) k-means clustering is applied for movie critics rank (Metascore) and users’ star rank (Rating). Different python libraries are used for web data scraping, data analysis, data visualization, and k-means clustering application. Only 42.4% of records were accepted from the extracted dataset for research purposes after cleaning. Statistical analysis showed that votes, ratings, Metascore have a linear relationship, while random characteristics are observed for income of the movie. On the other hand, experts’ feedback (Metascore) and customers’ feedback (Rating) are negatively correlated (−0.0384) due to the biasness of additional features like genre, actors, budget, etc. Both rankings have a nonlinear relationship with the income of the movies. Six optimal clusters were selected by elbow technique and the calculated silhouette score is 0.4926 for the proposed k-means clustering model and we found that only one cluster is in the logical relationship of two rankings systems.
Correction: Deptuch et al. Molecular Dynamics and Kinetics of Isothermal Cold Crystallization in the Chiral Smectogenic 3F7FPhH6 Glassformer. Crystals 2021, 11, 1487
Authors: Deptuch Aleksandra , Jasiurkowska-Delaporte Małgorzata , Juszyńska-Gałązka Ewa , Drzewicz Anna , Zając Wojciech , Urbańska Magdalena
Published: November 2022

The compound investigated in the publication [...]
Vitamin D Status and Potential Therapeutic Options in Critically Ill Patients: A Narrative Review of the Clinical Evidence
Authors: Cutuli Salvatore L. , Cascarano Laura , Tanzarella Eloisa S. , Lombardi Gianmarco , Carelli Simone , Pintaudi Gabriele , Grieco Domenico L. , De Pascale Gennaro , Antonelli Massimo
Published: November 2022

Vitamin D covers roles of paramount importance in the regulation of multiple physiological pathways of the organism. The metabolism of vitamin D involves kidney–liver crosstalk and requires an adequate function of these organs, where vitamin D is progressively turned into active forms. Vitamin D deficiency has been widely reported in patients living in the community, being prevalent among the most vulnerable subjects. It has been also documented in many critically ill patients upon admission to the intensive care unit. In this context, vitamin D deficiency may represent a risk factor for the development of life-threatening clinical conditions (e.g., infection and sepsis) and worse clinical outcomes. Several researchers have investigated the impact of vitamin D supplementation showing its feasibility, safety, and effectiveness, although conflicting results have put into question its real benefit in critically ill patients. The existing studies included heterogeneous critically ill populations and used slightly different protocols of vitamin D supplementation. For these reasons, pooling up the results is difficult and not conclusive. In this narrative review, we described vitamin D physiology and the pathophysiology of vitamin D depletion with a specific focus on critically ill patients with liver dysfunction, acute kidney injury, acute respiratory failure, and sepsis.
New Classification Method for Independent Data Sources Using Pawlak Conflict Model and Decision Trees
Authors: Przybyła-Kasperek Małgorzata , Kusztal Katarzyna
Published: November 2022

The research concerns data collected in independent sets—more specifically, in local decision tables. A possible approach to managing these data is to build local classifiers based on each table individually. In the literature, many approaches toward combining the final prediction results of independent classifiers can be found, but insufficient efforts have been made on the study of tables’ cooperation and coalitions’ formation. The importance of such an approach was expected on two levels. First, the impact on the quality of classification—the ability to build combined classifiers for coalitions of tables should allow for the learning of more generalized concepts. In turn, this should have an impact on the quality of classification of new objects. Second, combining tables into coalitions will result in reduced computational complexity—a reduced number of classifiers will be built. The paper proposes a new method for creating coalitions of local tables and generating an aggregated classifier for each coalition. Coalitions are generated by determining certain characteristics of attribute values occurring in local tables and applying the Pawlak conflict analysis model. In the study, the classification and regression trees with Gini index are built based on the aggregated table for one coalition. The system bears a hierarchical structure, as in the next stage the decisions generated by the classifiers for coalitions are aggregated using majority voting. The classification quality of the proposed system was compared with an approach that does not use local data cooperation and coalition creation. The structure of the system is parallel and decision trees are built independently for local tables. In the paper, it was shown that the proposed approach provides a significant improvement in classification quality and execution time. The Wilcoxon test confirmed that differences in accuracy rate of the results obtained for the proposed method and results obtained without coalitions are significant, with a p level = 0.005. The average accuracy rate values obtained for the proposed approach and the approach without coalitions are, respectively: 0.847 and 0.812; so the difference is quite large. Moreover, the algorithm implementing the proposed approach performed up to 21-times faster than the algorithm implementing the approach without using coalitions.
Grid-Based Clustering Using Boundary Detection
Authors: Du Mingjing , Wu Fuyu
Published: November 2022

Clustering can be divided into five categories: partitioning, hierarchical, model-based, density-based, and grid-based algorithms. Among them, grid-based clustering is highly efficient in handling spatial data. However, the traditional grid-based clustering algorithms still face many problems: (1) Parameter tuning: density thresholds are difficult to adjust; (2) Data challenge: clusters with overlapping regions and varying densities are not well handled. We propose a new grid-based clustering algorithm named GCBD that can solve the above problems. Firstly, the density estimation of nodes is defined using the standard grid structure. Secondly, GCBD uses an iterative boundary detection strategy to distinguish core nodes from boundary nodes. Finally, two clustering strategies are combined to group core nodes and assign boundary nodes. Experiments on 18 datasets demonstrate that the proposed algorithm outperforms 6 grid-based competitors.