bluuebunny/crossref_metadata_2025 huggingface dataset:
Mechanical Properties of 3D-Printed Components Using Fused Deposition Modeling: Optimization Using the Desirability Approach and Machine Learning Regressor
Authors: Jatti Vijaykumar S. , Sapre Mandar S. , Jatti Ashwini V. , Khedkar Nitin K. , Jatti Vinaykumar S.
Published: November 2022

The fused deposition modelling (FDM) technique involves the deposition of a fused layer of material according to the geometry designed in the software. Several parameters affect the quality of parts produced by FDM. This paper investigates the effect of FDM printing process parameters on tensile strength, impact strength, and flexural strength. The effects of process parameters such as printing speed, layer thickness, extrusion temperature, and infill percentage are studied. Polyactic acid (PLA) was used as a filament material for printing test specimens. The experimental layout is designed according to response surface methodology (RSM) and responses are collected. Specimens are prepared for testing of these parameters as per ASTM standards. A mathematical model for each of the responses is developed based on the nonlinear regression method. The desirability approach, nonlinear regression, as well as experimental values are in close agreement with each other. The desirability approach predicted the tensile strength, impact strength, and flexural strength with a less percentage error of 3.109, 6.532, and 3.712, respectively. The nonlinear regression approach predicted the tensile strength, impact strength, and flexural strength with a less percentage error of 2.977, 6.532, and 3.474, respectively. The desirability concept and nonlinear regression approach resulted in the best mechanical property of the FDM-printed part.
Variation of Runoff and Runoff Components of the Lhasa River Basin in the Qinghai-Tibet Plateau under Climate Change
Authors: Xiang Xin , Ao Tianqi , Xiao Qintai
Published: November 2022

Quantitative analysis of changes in Lhasa River runoff components was significant to local water resources management. This study constructed the spatial processes in hydrology (SPHY) model in the Lhasa River Basin and optimized the model’s parameters using the hydrograph partitioning curves (HPC) method. The Lhasa River Basin’s precipitation and temperature were forecasted for 2020 to 2100 using the statistical downscaling model (SDSM) and two scenarios from the fifth generation of the Canadian earth system model (CanESM5) dataset, shared socioeconomic pathways 1-2.6 (SSP1-2.6) and shared socioeconomic pathways 2-4.5 (SSP2-4.5). This study analyzed the potential changes in Lhasa River runoff and components based on the future climate. The results showed that the Lhasa River runoff from 2010 to 2019 was composed of snowmelt runoff, glacier melt runoff, rainfall runoff, and baseflow, with the proportions of 15.57, 6.19, 49.98, and 28.26%, respectively. From 2020 to 2100, under the SSP1-2.6 scenario, the precipitation and average temperature increased by 0.76mm and 0.08 °C per decade. Under the SSP2-4.5 scenario, the increasing rate was 3.57 mm and 0.25 °C per decade. Due to the temperature increase, snowmelt and glacier melt runoff showed a decreasing trend. The decline rate of total runoff was 0.31 m3/s per year under the SSP1-2.6 scenario due to the decrease in baseflow. Under the SSP2-4.5 scenario, total runoff and rainfall runoff showed a clear increasing trend at an average rate of 1.13 and 1.16 m3/s per year, respectively, related to the significant increase in precipitation. These conclusions suggested that climate change significantly impacted the Lhasa River’s total runoff and runoff components.
Black Carbon Emission Prediction of Diesel Engine Using Stacked Generalization
Authors: Zhang Yongbo , Wen Miaomiao , Sun Ying , Chen Hui , Cai Yunkai
Published: November 2022

With the continuous growth of international maritime trade, black carbon (BC) emissions from ships have caused great harm to the natural environment and human health. Controlling the BC emissions from ships is of positive significance for Earth’s environmental governance. In order to accelerate the development process of ship BC emission control technologies, this paper proposes a BC emission prediction model based on stacked generalization (SG). The meta learner of the prediction model is Ridge Regression (RR), and the base learner combines four models: Extreme Gradient Boosting (XGB), Light Gradient Boosting Machine (LGB), Random Forest (RF), and Support Vector Regression (SVR). We used mutual information (MI) to measure the correlation between combustion characteristic parameters (CCPs) and BC emission concentration, and selected them as the features of the prediction model. The results show that the CCPs have a strong correlation with the BC emission concentration of the diesel engine under different working conditions, which can be used to describe the influence of the changes to the combustion process in the cylinder on the BC generation. The introduction of the stacked generalization method reconciles the inherent bias of various models. Compared with traditional models, the fusion model has achieved higher prediction accuracy on the same datasets. The research results of this paper can provide a reference for the research and development of ship black carbon emission control technologies and the formulation of relevant regulations.
Application of Large Time Step TVD High Order Scheme to Shallow Water Equations
Authors: Xu Renyi , Borthwick Alistair G. L. , Xu Bo
Published: November 2022

The numerical modeling of actual river floods faces three challenges related to computational efficiency, accuracy, and proper balancing of terms in the governing equations, all of which are discussed in this paper. Herein, a large time step (LTS) scheme is used to improve efficiency, a high order scheme is used to enhance accuracy, and specific treatment of the bed slope term achieves a well-balanced form of shallow water equations. The LTS scheme, originally proposed by LeVeque in 1998, has led to the development of highly efficient computational solvers of the shallow water equations (SWEs). This paper examines use of a total variation diminishing (TVD) high order scheme in conjunction with LTS. We first applied the scheme to the solution of the homogeneous 1D SWEs and obtained satisfactory results for three cases, even though small oscillations nevertheless occur when the CFL number is very large. The additional source term makes the issue more complicated and can introduce a spurious flow when the term is not correctly handled. Many methods have been developed in traditional differential schemes, but not all are fit for the TVD-LTS scheme; for example, the method of decomposing the source term into simple characteristic waves has proved infeasible. In this paper the TVD-LTS scheme was implemented for the first time for well-balanced SWEs containing bed slope source terms. We found that oscillations were not as suppressed as for the homogeneous SWEs when the TVD-LTS scheme was applied to the three cases of step Riemann problems (SRP) tested for CFL numbers 1 to 10. For free surface flow over a bed hump, the TVD-LTS scheme can only reach CFL number 4 before the solution breaks down.
Extreme Precipitation Strongly Impacts the Interaction of Skewness and Kurtosis of Annual Precipitation Distribution on the Qinghai–Tibetan Plateau
Authors: Guo Tong
Published: November 2022

Characterizing extreme precipitation precisely is crucial for predicting vegetation response to drought or storms. However, current precipitation generators in vegetation models do not simulate the occurrence and amount of extreme precipitation well. This study examined the effects of extreme precipitation on the skewness, kurtosis, and skewness–kurtosis interaction of annual precipitation distribution. The examination was based on theoretical calculations and monitoring data from 78 meteorological stations on the Qinghai–Tibetan Plateau (QTP). The results showed that extreme precipitation generally increased the skewness and kurtosis of annual precipitation distribution. A higher mean annual precipitation amplified the effects of precipitation extremes on promoting skewness and kurtosis in normal distribution scenarios. In contrast, these effects tended to be saturated for scenarios of higher mean annual precipitation in probability-based distributions. A reduction of dry days in a year markedly intensified the interaction of the skewness and the kurtosis, while the skewness–kurtosis interaction weakened with decreased maximum daily precipitation in a year. Moreover, the effect of extreme precipitation on the skewness–kurtosis interaction was stronger in arid or low-altitude areas. This study illustrates the fact that considering the skewness and kurtosis of annual precipitation distributions will be very helpful for simulating extreme precipitation on the QTP in the future. This will allow us to better understand the impact of climate change on alpine plants.
Comparative Study of Parameter Identification with Frequency and Time Domain Fitting Using a Physics-Based Battery Model
Authors: Zhao Yulong , Jossen Andreas
Published: November 2022

Parameter identification with the pseudo-two-dimensional (p2D) model has been an important research topic in battery engineering because some of the physicochemical parameters used in the model can be measured, while some can only be estimated or calculated based on the measurement data. Various methods, either in the time domain or frequency domain, have been proposed to identify the parameters of the p2D model. While the methods in each domain bring their advantages and disadvantages, a comprehensive comparison regarding parameter identifiability and accuracy is still missing. In this present work, some selected physicochemical parameters of the p2D model are identified in four different cases and with different methods, either only in the time domain or with a combined model. Which parameters are identified in the frequency domain is decided by a comprehensive analysis of the analytical expression for the DRT spectrum. Finally, the parameter identifiability results are analyzed and the validation results with two highly dynamic load profiles are shown and compared. The results indicate that the model with ohmic resistance and the combined method achieves the best performance and the average voltage error is at the level of 12 mV.
An Overview of Data Warehouse and Data Lake in Modern Enterprise Data Management
Authors: Nambiar Athira , Mundra Divyansh
Published: November 2022

Data is the lifeblood of any organization. In today’s world, organizations recognize the vital role of data in modern business intelligence systems for making meaningful decisions and staying competitive in the field. Efficient and optimal data analytics provides a competitive edge to its performance and services. Major organizations generate, collect and process vast amounts of data, falling under the category of big data. Managing and analyzing the sheer volume and variety of big data is a cumbersome process. At the same time, proper utilization of the vast collection of an organization’s information can generate meaningful insights into business tactics. In this regard, two of the popular data management systems in the area of big data analytics (i.e., data warehouse and data lake) act as platforms to accumulate the big data generated and used by organizations. Although seemingly similar, both of them differ in terms of their characteristics and applications. This article presents a detailed overview of the roles of data warehouses and data lakes in modern enterprise data management. We detail the definitions, characteristics and related works for the respective data management frameworks. Furthermore, we explain the architecture and design considerations of the current state of the art. Finally, we provide a perspective on the challenges and promising research directions for the future.
Solid PRF Serves as Basis for Guided Open Wound Healing of the Ridge after Tooth Extraction by Accelerating the Wound Healing Time Course—A Prospective Parallel Arm Randomized Controlled Single Blind Trial
Authors: Ghanaati Shahram , Śmieszek-Wilczewska Joanna , Al-Maawi Sarah , Neff Pauline , Zadeh Homayoun H. , Sader Robert , Heselich Anja , Rutkowski James L.
Published: November 2022

Systematic evaluations regarding the influence of PRF in ridge sealing are still lacking. To the best of our knowledge, this is the first systemic randomized, controlled, clinical approach dealing with the potential of a systematic applied solid PRF on soft tissue socket healing of molar and premolar extraction sockets with evaluation for up to 90 days. Qualitative and quantitative image analysis showed that PRF contributed to a significantly faster ridge sealing, within the period of 7–10 days in both tooth types. This led to a visibly less contraction at the PRF-treated group sites at day 90. Patients’ pain perception demonstrated no statistic significance between both groups (PRF vs. natural healing), but the patients in PRF group seemed to have had less pain throughout the observational period. It becomes evident that PRF is able to serve as a promotor of the secondary wound healing cascade. The guiding capacity of PRF accelerating the process of open ridge healing makes it possible to act as a natural growth factor drug delivery system, providing a more predictable guided open wound healing of the ridge with less contraction of the soft tissue, the latter being a key factor for the subsequent successful dental implantation and oral rehabilitation.
Effective Quality Breeding Directions—Comparison and Conservative Analysis of Hepatic Super-Enhancers between Chinese and Western Pig Breeds
Authors: Zhang Yi , Zhang Jinbi , Wang Caixia , Qin Xinxin , Zhang Yuge , Liu Jingge , Pan Zengxiang
Published: November 2022

The transcriptional initiation of genes is closely bound to the functions of cis-regulatory elements, including promoters, typical enhancers (TEs), and recently-identified super-enhancers (SEs). In this study, we identified these cis-regulatory elements in the livers of two Chinese (Meishan and Enshi Black) and two Western (Duroc and Large White) pig breeds using ChIP-seq data, then explored their similarities and differences. In addition, we analyzed the conservation of SEs among different tissues and species (pig, human, and mouse). We observed that SEs were more significantly enriched by transcriptional initiation regions, TF binding sites, and SNPs than other cis-elements. Western breeds included fewer SEs in number, while more growth-related QTLs were associated with these SEs. Additionally, the SEs were highly tissue-specific, and were conserved in the liver among humans, pigs, and mice. We concluded that intense selection could concentrate functional SEs; thus, SEs could be applied as effective detection regions in genomic selection breeding.
Discovery of Trace Amine-Associated Receptor 1 (TAAR1) Agonist 2-(5-(4′-Chloro-[1,1′-biphenyl]-4-yl)-4H-1,2,4-triazol-3-yl)ethan-1-amine (LK00764) for the Treatment of Psychotic Disorders
Authors: Krasavin Mikhail , Lukin Alexey , Sukhanov Ilya , Gerasimov Andrey S. , Kuvarzin Savelii , Efimova Evgeniya V. , Dorofeikova Mariia , Nichugovskaya Anna , Matveev Andrey , Onokhin Kirill , Zakharov Konstantin , Gureev Maxim , Gainetdinov Raul R.
Published: November 2022

A focused in-house library of about 1000 compounds comprising various heterocyclic motifs in combination with structural fragments similar to β-phenylethylamine or tyramine was screened for the agonistic activity towards trace amine-associated receptor 1 (TAAR1). The screening yielded two closely related hits displaying EC50 values in the upper submicromolar range. Extensive analog synthesis and testing for TAAR1 agonism in a BRET-based cellular assay identified compound 62 (LK00764) with EC50 = 4.0 nM. The compound demonstrated notable efficacy in such schizophrenia-related in vivo tests as MK-801-induced hyperactivity and spontaneous activity in rats, locomotor hyperactivity of dopamine transporter knockout (DAT-KO) rats, and stress-induced hyperthermia (i.p. administration). Further preclinical studies are necessary to evaluate efficacy, safety and tolerability of this potent TAAR1 agonist for the potential development of this compound as a new pharmacotherapy option for schizophrenia and other psychiatric disorders.
Emerging Role of YAP and the Hippo Pathway in Prostate Cancer
Authors: Koinis Filippos , Chantzara Evangelia , Samarinas Michael , Xagara Anastasia , Kratiras Zisis , Leontopoulou Vasiliki , Kotsakis Athanasios
Published: November 2022

The Hippo pathway regulates and contributes to several hallmarks of prostate cancer (PCa). Although the elucidation of YAP function in PCa is in its infancy, emerging studies have shed light on the role of aberrant Hippo pathway signaling in PCa development and progression. YAP overexpression and nuclear localization has been linked to poor prognosis and resistance to treatment, highlighting a therapeutic potential that may suggest innovative strategies to treat cancer. This review aimed to summarize available data on the biological function of the dysregulated Hippo pathway in PCa and identify knowledge gaps that need to be addressed for optimizing the development of YAP-targeted treatment strategies in patients likely to benefit.
A Robust Framework Combining Image Processing and Deep Learning Hybrid Model to Classify Cardiovascular Diseases Using a Limited Number of Paper-Based Complex ECG Images
Authors: Fatema Kaniz , Montaha Sidratul , Rony Md. Awlad Hossen , Azam Sami , Hasan Md. Zahid , Jonkman Mirjam
Published: November 2022

Heart disease can be life-threatening if not detected and treated at an early stage. The electrocardiogram (ECG) plays a vital role in classifying cardiovascular diseases, and often physicians and medical researchers examine paper-based ECG images for cardiac diagnosis. An automated heart disease prediction system might help to classify heart diseases accurately at an early stage. This study aims to classify cardiac diseases into five classes with paper-based ECG images using a deep learning approach with the highest possible accuracy and the lowest possible time complexity. This research consists of two approaches. In the first approach, five deep learning models, InceptionV3, ResNet50, MobileNetV2, VGG19, and DenseNet201, are employed. In the second approach, an integrated deep learning model (InRes-106) is introduced, combining InceptionV3 and ResNet50. This model is developed as a deep convolutional neural network capable of extracting hidden and high-level features from images. An ablation study is conducted on the proposed model altering several components and hyperparameters, improving the performance even further. Before training the model, several image pre-processing techniques are employed to remove artifacts and enhance the image quality. Our proposed hybrid InRes-106 model performed best with a testing accuracy of 98.34%. The InceptionV3 model acquired a testing accuracy of 90.56%, the ResNet50 89.63%, the DenseNet201 88.94%, the VGG19 87.87%, and the MobileNetV2 achieved 80.56% testing accuracy. The model is trained with a k-fold cross-validation technique with different k values to evaluate the robustness further. Although the dataset contains a limited number of complex ECG images, our proposed approach, based on various image pre-processing techniques, model fine-tuning, and ablation studies, can effectively diagnose cardiac diseases.
Bullous Pemphygoid and Novel Therapeutic Approaches
Authors: D’Agostino Giovanni Marco , Rizzetto Giulio , Marani Andrea , Marasca Samuele , Candelora Matteo , Gambini Daisy , Gioacchini Helena , De Simoni Edoardo , Maurizi Andrea , Campanati Anna , Offidani Annamaria
Published: November 2022

Bullous pemphigoid is a subepidermal blistering disease associated with autoantibodies (auto-ab) to BP180 and BP230 which affects elderly patients, predominately. Although it is a rare disease, bullous pemphigoid is the most common among the autoimmune bullous skin diseases. Systemic corticosteroids and immunosuppressants represent milestones in the treatment of patients suffering from bullous pemphigoid; however, therapeutic management of patients still represents a clinical challenge, owing to the chronic nature of the disease and to potential adverse effects related to the long-term use of systemic treatments. Recent discoveries on the pathogenesis of bullous pemphigoid have allowed investigation of new target therapies against selective pro-inflammatory mediators. These therapies appear to yield satisfactory results with fewer side effects in cases of refractory disease. The review discusses current evidence on these new therapeutic targets and specific drugs under investigation.
Osteoarthritis Pain in Old Mice Aggravates Neuroinflammation and Frailty: The Positive Effect of Morphine Treatment
Authors: Amodeo Giada , Franchi Silvia , Galimberti Giulia , Comi Laura , D’Agnelli Simona , Baciarello Marco , Bignami Elena Giovanna , Sacerdote Paola
Published: November 2022

Knee osteoarthritis is a common cause of pain and disability in old subjects. Pain may predispose to the development of frailty. Studies on mechanisms underlying pain in osteoarthritis models during aging are lacking. In this work, we used the monosodium iodoacetate model of osteoarthritis in adult (11-week-old) and old (20-month-old) C57BL/6J mice to compare hypersensitivity, locomotion, neuroinflammation, and the effects of morphine treatment. After osteoarthritis induction in adult and old mice, weight-bearing asymmetry, mechanical allodynia, and thermal hyperalgesia similarly developed, while locomotion and frailty were more affected in old than in adult animals. When behavioral deficits were present, the animals were treated for 7 days with morphine. This opioid counteracts the behavioral alterations and the frailty index worsening both in adult and old mice. To address the mechanisms that underlie pain, we evaluated neuroinflammatory markers and proinflammatory cytokine expression in the sciatic nerve, DRGs, and spinal cord. Overexpression of cytokines and glia markers were present in osteoarthritis adult and old mice, but the activation was qualitatively and quantitatively more evident in aged mice. Morphine was able to counteract neuroinflammation in both age groups. We demonstrate that old mice are more vulnerable to pain’s detrimental effects, but prompt treatment is successful at mitigating these effects.
Hyperlipoproteinemia(a) and Severe Coronary Artery Lesion Types
Authors: Ilina Larisa N. , Afanasieva Olga I. , Shiryaev Andrey A. , Vlasova Elina E. , Kurbanov Said K. , Afanasieva Marina I. , Ezhov Marat V. , Vasiliev Vladislav P. , Galyautdinov Damir M. , Pokrovsky Sergey N. , Akchurin Renat S.
Published: November 2022

Diffuse atherosclerosis and calcification of the coronary arteries (CA) create serious difficulties for coronary artery bypass grafting (CABG). The aim of this study was to compare demographic indicators, lipids, and clinical results one year after CABG in patients with different phenotypes of coronary artery (CA) disease. In total, 390 patients hospitalized for elective CABG were included in a single-center prospective study. Demographic data, lipids (total, low-density lipoprotein and high-density lipoprotein cholesterol, and triglycerides), and lipoprotein(a) (Lp(a)) concentrations were analyzed for all patients. Major adverse cardiovascular events (MACE) included myocardial infarction, stroke, percutaneous coronary intervention, and death from cardiac causes within one year after surgery. No significant outcome differences were found between the groups with diffuse vs. segmental lesions, nor the groups with and without calcinosis for all studied parameters except for Lp(a). Median Lp(a) concentrations were higher in the group of patients with diffuse compared to segmental lesions (28 vs. 16 mg/dL, p = 0.023) and in the group with calcinosis compared to the group without it (35 vs. 19 mg/dL, p = 0.046). Lp(a) ≥ 30 mg/dL was associated with the presence of diffuse lesions (OR = 2.18 (95% CI 1.34–3.54), p = 0.002), calcinosis (2.15 (1.15–4.02), p = 0.02), and its combination (4.30 (1.81–10.19), p = 0.0009), irrespective of other risk factors. The risk of MACE within one year after CABG was higher for patients with combined diffuse and calcified lesions vs. patients with a segmental lesion without calcinosis (relative risk = 2.38 (1.13–5.01), p = 0.02). Conclusion: Diffuse atherosclerosis and coronary calcinosis are associated with elevated Lp(a) levels, independent of other risk factors. The risk of MACE in the first year after surgery is significantly higher in patients with diffuse atherosclerosis and coronary calcinosis, which should be considered when prescribing postoperative treatment for such patients.
Comparison of Optical and Electrical Sensor Characteristics for Efficient Analysis of Attachment and Detachment of Aptamer
Authors: Park Yejin , Dang Thinh Viet , Jeong Uiseok , Kim Moon Il , Kim Jinsik
Published: November 2022

Nucleic acid aptamer-based research has focused on achieving the highest performance for bioassays. However, there are limitations in evaluating the affinity for the target analytes in these nucleic acid aptamer-based bioassays. In this study, we mainly propose graphene oxide (GO)-based electrical and optical analyses to efficiently evaluate the affinity between an aptamer and its target. We found that an aptamer-coupled GO-based chip with an electrical resistance induced by a field-effect transistor, with aptamers as low as 100 pM, can detect the target, thrombin, at yields as low as 250 pM within five minutes. In the optical approach, the fluorescent dye-linked aptamer, as low as 100 nM, was efficiently used with GO, enabling the sensitive detection of thrombin at yields as low as 5 nM. The cantilever type of mechanical analysis also demonstrated the intuitive aptamer–thrombin reaction in the signal using dBm units. Finally, a comparison of electrical and optical sensors’ characteristics was introduced in the attachment and detachment of aptamer to propose an efficient analysis that can be utilized for various aptamer-based research fields.
Two-Way Detection of COVID-19 Spike Protein and Antibody Using All-Dielectric Metasurface Fluorescence Sensors
Authors: Iwanaga Masanobu , Tangkawsakul Wanida
Published: November 2022

COVID-19 (or SARS-CoV-2) has deeply affected human beings worldwide for over two years, and its flexible mutations indicate the unlikeliness of its termination in a short time. Therefore, it is important to develop a quantitative platform for direct COVID-19 detection and human status monitoring. Such a platform should be simpler than nucleic acid amplification techniques such as polymerase chain reaction, and more reliable than the disposable test kits that are based on immunochromatography. To fulfill these requirements, we conducted proof-of-concept experiments for the quantitative detection of spike glycoprotein peptides and antibodies in one platform, i.e., all-dielectric metasurface fluorescence (FL) sensors. The high capability to enhance FL intensity enabled us to quantitatively measure the glycoproteins and antibodies more efficiently compared with the previous methods reported to date. Furthermore, the intrinsic limit of detection in the metasurface FL sensors was examined via confocal microscopy and found to be less than 0.64 pg/mL for glycoprotein peptides. Moreover, the sensors had a dynamic range more than five orders that of the target concentrations, indicating extremely high sensitivity. These two-way functions of the metasurface FL sensors can be helpful in reducing daily loads in clinics and in providing quantitative test values for proper diagnosis and cures.
Rapid Detection of Attomolar SARS-CoV-2 Nucleic Acids in All-Dielectric Metasurface Biosensors
Authors: Iwanaga Masanobu
Published: November 2022

Worldwide infection due to SARS-CoV-2 revealed that short-time and extremely high-sensitivity detection of nucleic acids is a crucial technique for human beings. Polymerase chain reactions have been mainly used for the SARS-CoV-2 detection over the years. However, an advancement in quantification of the detection and shortening runtime is important for present and future use. Here, we report a rapid detection scheme that is a combination of nucleic acid amplification and a highly efficient fluorescence biosensor, that is, a metasurface biosensor composed of a pair of an all-dielectric metasurface and a microfluidic transparent chip. In the present scheme, we show a series of proof-of-concept experimental results that the metasurface biosensors detected amplicons originating from attomolar SARS-CoV-2 nucleic acids and that the amplification was implemented within 1 h. Furthermore, this detection capability substantially satisfies an official requirement of 100 RNA copies/140 μL, which is a criterion for the reliable infection tests.
The Rejection Template of Working Memory Operates after Attention Capture
Authors: Lu Jiachen , Wang Jing , Li Weidong , Li Jingjing
Published: November 2022

Although scientists know that information stored in working memory guides visual attention, how this is accomplished is still under debate. Specifically, there is a dispute between the Biased Competition Model and Visual Attention Theory. The current study used two experiments to resolve this controversy based on previous research. Experiment 1 found that although inverse efficiency scores for High and Low numbers of memory distractors were both longer than the Baseline (no memory distractors), they did not significantly differ from each other. This indicated that memory might guide attention via a capture-then-global-inhibition process. Experiment 2 addressed the possibility that the findings resulted from the time needed to reject the interfering objects by requiring both memory-matching and memory-mismatching conditions to be rejected under a highlighted target. This result showed that the memory-matching condition resulted in longer search times than the memory-mismatching condition, indicating an attention-capture effect based on working memory. Together, the two experiments support the idea that when multiple memory-matching distractors in a search array first capture an individual’s attention, it then acts as a template that allows the individual to suppress all interfering items that containing memory information holds. This study supports the Biased Competition Model early on in visual search. However, the late stage of visual search supports the Visual Attention Theory. These advance our knowledge regarding the relationship between working memory content and attention.
Three-Dimensional Morphology and Watershed-Algorithm-Based Method for Pitting Corrosion Evaluation
Authors: Li Anbang , Ma Hongwang , Xu Shanhua
Published: November 2022

Pitting corrosion and stress concentration at rust pits are the principal reasons for severe degradation in fatigue performance of corroded steel structures. The accurate evaluation of rust pits on rough and uneven corrosion surfaces is the foundation of fatigue life estimation for corroded steel structures. In this paper, a new method for the identification, extraction, and evaluation of rust pits on the surface of corroded steel structures was proposed based on a three-dimensional morphology and watershed algorithm. An accelerated corrosion experiment was first executed to acquire corroded steel plates, and then surface profile measurements were conducted to obtain the three-dimensional morphology of the corroded steel surfaces. Furthermore, the surface topography data of the corroded steel surfaces were written into a gray matrix through coordinate transformation. Then, the gray matrix was successively filtered and gradient-mapped, and the watershed was calculated to obtain the pit mark matrix and pit depth matrix. A calculation method for the size and shape of rust pits was consequently developed, and a statistical analysis of the extraction results of the rust pits was also conducted. The results showed that rust pit density had a peak value at the corrosion duration of 3 months, and rust pit density showed a fluctuating process with corrosion duration that continued to increase until 15 months. The values of the depth diameter ratios of rust pits were concentrated in the range of 0.1~0.8. With corrosion duration increasing from 3 months to 4, 6, 8, 12, and 15 months, the distribution range of the depth diameter ratios of rust pits decreased at first and then increased, followed by decrease and, finally, increase. The width distribution of the rust pits was independent of the depth distribution of the rust pits. The values of the volume ratios were mostly distributed between π/12 and π/4, and the shapes of most rust pits were similar to half (ellipsoidal) spheres.
Evolution Process of Scientific Space: Spatial Analysis of Three Groups of Laboratories in History (16th–20th Century)
Authors: Zhang Xinwei , Cui Tong
Published: November 2022

Different disciplines need specialized spaces to ensure the smooth conduct of research, and the laboratory plays an important role as the physical carrier of knowledge production today. Reviewing history, it is found that the image of the laboratory and the organization of internal space have undergone great changes, which reflects people’s cognition of scientific practice in different periods. This study uses space syntax tools to analyze relationships between scientific research activities and spatial forms over time, preliminarily discussing laboratories’ spatial characteristics in different periods and the corresponding research modes. It is found that scientific research has undergone several phases, and the scientific paradigm deeply influences the spatial logic of scientific research buildings. The scientific research space in different periods presents unique syntactic results and topological structures, suggesting the trend of specialized research from closed to open and decentralization to centralization.
The Drivers, Barriers, and Enablers of Building Information Modeling (BIM) Innovation in Developing Countries: Insights from Systematic Literature Review and Comparative Analysis
Authors: Ariono Bernardus , Wasesa Meditya , Dhewanto Wawan
Published: November 2022

Building information modeling (BIM) has received significant attention in the last two decades from the architecture, engineering, and construction (AEC) industry. Despite the popular trend of BIM in developing countries, the adoption of this technology is still low. This paper aims to investigate the drivers, barriers, and enablers of BIM adoption in developing countries with regard to global challenges. A systematic literature review and an in-depth comparative qualitative analysis were conducted to accomplish the objective. Relevant articles from three major databases covering 20 years (2002–2022) of journal article publications were analyzed. The comparative study identified drivers, barriers, and enablers influencing BIM innovation in six developing countries from three different continents. Additionally, a critical review and analysis explored the importance of BIM’s innovation factors in developing countries. The stakeholders of AEC will benefit from insights offered by this study to prepare BIM implementation strategies effectively.
A Numerical Method for Solving Global Irradiance on the Facades of Building Stocks
Authors: Xing Haowei , Yang Yi , Chen Shuqin
Published: November 2022

Due to the influence of surrounding buildings on the radiation transfer process, the irradiance of individual buildings in building stocks is more uneven and different than that of individual buildings in open spaces. In view of the defect of the existing building surface irradiance calculation model in the sky radiation energy balance calculation, the complex surface reflection radiative transfer in diffuse irradiance, and complex processes, this paper combined the calculation of the complex surface narrow sky view, multiple reflections, and radiation characteristics of nonuniformity, and finally established the model for irradiance on the facade of a building stock (IFBS model) in a sheltered environment. The simulation results show that the IFBS model is superior to the traditional model in the calculation of sky diffuse irradiance and reflection irradiance of building stocks and is more suitable for the numerical calculation of the radiation transfer process of complex buildings.
Exploring the Sustainable Values of Smart Homes to Strengthen Adoption
Authors: Chang Soojung , Nam Kyeongsook
Published: November 2022

Despite numerous benefits and developments, smart home technology has not been widely adopted by mainstream users. The purpose of this study is to suggest user-centered smart home design strategies to promote smart home adoption. This study has the following research goals: First, it selects smart home design factors to promote adoption. Second, it examines the importance of how users perceive smart home design factors. To achieve the goals, a user survey was conducted in Korea. As a result, six items, including 38 subfactors, were suggested as smart home design strategies to promote adoption: (1) creating an automated residential environment, (2) guaranteeing service scalability and diversity, (3) increasing service accessibility, (4) improving the lifestyle balance of potential users, (5) securing long-term safety in relation to the use of systems and facilities, and (6) reducing environmental load. The differences in user perception regarding the importance of these factors were investigated. Based on a comprehensive understanding of smart home adoption, this study proposes sustainability values for the factors influencing smart home adoption as they focus on the ability of smart homes to address user burden in terms of physical and spatial changes, and also help to identify adaptations that can be incorporated to meet the diverse needs of users. The results of this study can improve the overall understanding of the process of adopting smart homes and provide reference material regarding user perceptions of the performance conditions, functional characteristics, and service operation and quality of smart homes.
Indoor Thermal and Ventilation Indicator on University Students’ Overall Comfort
Authors: Jia Lin-Rui , Li Qing-Yun , Chen Xi , Lee Chi-Chung , Han Jie
Published: November 2022

Thermal comfort (TC) and CO2 concentration significantly influence the overall indoor comfort sensations of building occupants. However, few studies have focused on educational buildings regarding both TC and CO2 concentration in tropical regions, and they also lack guidelines for short-term evaluation, which is essential for university classrooms. In this study, a mechanically ventilated university classroom was selected to investigate the 5 min-averaged comfort ranges for indoor parameters and the impacts of TC and variation of CO2 on student overall comfort. The real-time indoor environmental parameters were monitored, including indoor air temperature (Ta), mean radiant temperature (Tm), relative humidity (RH) and CO2 and air velocity (va); the operative temperature (Top) was calculated. Moreover, an online-based questionnaire survey related to thermal sensation (TS) and CO2-related air sensation (AS) was carried out. Linear and nonlinear regression models of comfort sensation predictions were obtained based on the questionnaires and corresponding measured indoor environmental data. The 5 min-averaged comfort ranges for Top, CO2 and RH are 21.5–23.8 °C, <1095 ppm and 47–63.5%, respectively. The comfort range of the TS and AS are 2.3–3.1 and 1–1.55, respectively. The result shows that students prefer a relatively cold indoor environment, as this improves their ability to tolerate bad indoor air quality (IAQ) with high CO2. A regression analysis indicated that AS is the most critical aspect, with a weight of 0.32, followed by TS, with 0.18. Finally, it was also found that individual weighting coefficients were not equivalent and differed across geographical locations and building types. Thus, obtaining the prediction models for a particular building is necessary. The results can give meaningful suggestions to adopt the appropriate operations for HVAC and improve indoor environmental quality in university buildings in tropical regions.
Experimental Study on the Overall Stability of Corroded H-Shaped Steel Beams
Authors: Luo Lisheng , Fu Houlin , Zhang Yongqiang , Xie Xinran
Published: November 2022

The degradation of the overall stability of corroded rolled H-shaped steel beams under bending conditions has not been extensively studied. In the present study, monotonic tensile tests and overall stability tests were conducted on seven rolled H-shaped steel beams that were subjected to electrochemical corrosion in order to discuss the influence of corrosion on the material’s mechanical properties and the overall stability of steel beams under bending conditions. The test results have indicated that the strength, the elastic modulus, and the elongation of the steel declined with an increase in the corrosion rate of the steel beams, and an obvious plastic deterioration phenomenon was observed. In addition, all of the steel beams with different degrees of corrosion were subjected to overall flexural–torsional buckling failure. The stiffness and the overall stability ultimate bearing capacity of the corroded steel beams decreased with the increase in the corrosion rate, and the overall stability of the test beams with a high design corrosion rate degraded significantly. Furthermore, by using the finite element numerical simulation analysis software ABAQUS, a double-reduction corrosion model of the sectional dimensions and the material’s mechanical properties was established. The overall stability ultimate bearing capacities of the steel beams that were subjected to three-point bending and the corresponding load–lateral displacement curves were analyzed. In addition, the finite element numerical simulation results were compared with the test results for verification. Subsequently, the influence of the initial bending on the overall stability ultimate bearing capacity of the steel beams was analyzed by virtue of the verified finite element model. This study will provide a test basis for the evaluation of the bearing capacity of existing rolled H-shaped steel members, as well as an experimental basis and finite element model reference for the follow-up study on the degradation of the mechanical properties of the corroded rolled steel members.
An Experimental Study of Granular Material Using Recycled Concrete Waste for Pavement Roadbed Construction
Authors: Al-Mosawe Hasan , Albayati Amjad , Wang Yu , Mashaan Nuha S.
Published: November 2022

Rapid worldwide urbanization and drastic population growth have increased the demand for new road construction, which will cause a substantial amount of natural resources such as aggregates to be consumed. The use of recycled concrete aggregate could be one of the possible ways to offset the aggregate shortage problem and reduce environmental pollution. This paper reports an experimental study of unbound granular material using recycled concrete aggregate for pavement subbase construction. Five percentages of recycled concrete aggregate obtained from two different sources with an originally designed compressive strength of 20–30 MPa as well as 31–40 MPa at three particle size levels, i.e., coarse, fine, and extra fine, were tested for their properties, i.e., the optimum moisture content density, Californian bearing ratio, and resilient modulus. A characterization of the resilient modulus of the mixes under complex stress conditions was performed. The characterized modulus model was used in the nonlinear analysis of the pavement structure under traffic loading using KENALYER software. Consequently, the two critical responses, i.e., the tensile strain at the bottom of the asphalt layer and the vertical compressive strain at the top of the subgrade, were computed and compared for the pavement structures with varying types and percentages of recycled concrete aggregate used in the subbase layer.
Polarizability of Kekulene, Septulene, and Nearest Non-Planar Polycyclic Aromatic Hydrocarbons
Authors: Lukmanov Timur , Akhmetov Arslan F. , Sabirov Denis Sh.
Published: November 2022

The polarizability of polycyclic aromatic hydrocarbons (PAHs) is an important property that relates to their abundance in natural environments. To assess the differences in the mean polarizability of planar and non-planar polycyclic aromatic hydrocarbons (PAHs), we computationally studied the PAH series of circulenes (kekulene C48H24, [13]circulene C52H26, and septulene C56H28), a number of the nearest helicenes, and their “expanded” isomers. We mean under “nearest” a close number of aromatic rings: 11 (C46H26), 12 (C50H28), 13 (C54H30), and 14 (C58H32). For these PAHs, we performed the quantum chemical calculations of thermodynamic and polarizability parameters with the PBE/3ζ density functional theory method, which is widely used in the theoretical chemistry of fullerenes and PAHs. The calculated mean polarizabilities (in Å3) ranged from 80.1 for [11]helicene to 135.5 for septulene, and while the circulenes and expanded helicenes had similar values, the mean polarizability of the normal helicenes was markedly lower. In all four pairs of helical PAHs, the expanded helicene was energetically considerably more favorable than its standard helicene isomer. Herewith, the ratio of their polarizabilities was equal to 1.3.
The Monocyte, a Maestro in the Tumor Microenvironment (TME) of Breast Cancer
Authors: Amer Hoda T. , Stein Ulrike , El Tayebi Hend M.
Published: November 2022

Breast cancer (BC) is well-known for being a leading cause of death worldwide. It is classified molecularly into luminal A, luminal B HER2−, luminal B HER2+, HER2+, and triple-negative breast cancer (TNBC). These subtypes differ in their prognosis; thus, understanding the tumor microenvironment (TME) makes new treatment strategies possible. The TME contains populations that exhibit anti-tumorigenic actions such as tumor-associated eosinophils. Moreover, it contains pro-tumorigenic populations such as tumor-associated neutrophils (TANs), or monocyte-derived populations. The monocyte-derived populations are tumor-associated macrophages (TAMs) and MDSCs. Thus, a monocyte can be considered a maestro within the TME. Moreover, the expansion of monocytes in the TME depends on many factors such as the BC stage, the presence of macrophage colony-stimulating factor (M-CSF), and the presence of some chemoattractants. After expansion, monocytes can differentiate into pro-inflammatory populations such as M1 macrophages or anti-inflammatory populations such as M2 macrophages according to the nature of cytokines present in the TME. Differentiation to TAMs depends on various factors such as the BC subtype, the presence of anti-inflammatory cytokines, and epigenetic factors. Furthermore, TAMs and MDSCs not only have a role in tumor progression but also are key players in metastasis. Thus, understanding the monocytes further can introduce new target therapies.