bluuebunny/crossref_metadata_2025 huggingface dataset:
The Development of METAL-WRF Regional Model for the Description of Dust Mineralogy in the Atmosphere
Authors: Solomos Stavros , Spyrou Christos , Barreto Africa , Rodríguez Sergio , González Yenny , Neophytou Marina K. A. , Mouzourides Petros , Bartsotas Nikolaos S. , Kalogeri Christina , Nickovic Slobodan , Vukovic Vimic Ana , Vujadinovic Mandic Mirjam , Pejanovic Goran , Cvetkovic Bojan , Amiridis Vassilis , Sykioti Olga , Gkikas Antonis , Zerefos Christos
Published: October 2023

The mineralogical composition of airborne dust particles is an important but often neglected parameter for several physiochemical processes, such as atmospheric radiative transfer and ocean biochemistry. We present the development of the METAL-WRF module for the simulation of the composition of desert dust minerals in atmospheric aerosols. The new development is based on the GOCART-AFWA dust module of WRF-Chem. A new wet deposition scheme has been implemented in the dust module alongside the existing dry deposition scheme. The new model includes separate prognostic fields for nine (9) minerals: illite, kaolinite, smectite, calcite, quartz, feldspar, hematite, gypsum, and phosphorus, derived from the GMINER30 database and also iron derived from the FERRUM30 database. Two regional model sensitivity studies are presented for dust events that occurred in August and December 2017, which include a comparison of the model versus elemental dust composition measurements performed in the North Atlantic (at Izaña Observatory, Tenerife Island) and in the eastern Mediterranean (at Agia Marina Xyliatos station, Cyprus Island). The results indicate the important role of dust minerals, as dominant aerosols, for the greater region of North Africa, South Europe, the North Atlantic, and the Middle East, including the dry and wet depositions away from desert sources. Overall, METAL-WRF was found to be capable of reproducing the relative abundances of the different dust minerals in the atmosphere. In particular, the concentration of iron (Fe), which is an important element for ocean biochemistry and solar absorption, was modeled in good agreement with the corresponding measurements at Izaña Observatory (22% overestimation) and at Agia Marina Xyliatos site (4% overestimation). Further model developments, including the implementation of newer surface mineralogical datasets, e.g., from the NASA-EMIT satellite mission, can be implemented in the model to improve its accuracy.
Examining the Risk of Summertime Overheating in UK Social Housing Dwellings Retrofitted with Heat Pumps
Authors: Zahiri Sahar , Gupta Rajat
Published: October 2023

The UK government has announced its ten-point plan to annually install 600,000 low-carbon heat pumps by 2028. However, there is a lack of evidence showing potential overheating risk in dwellings retrofitted with heat pumps. This paper examines the prevalence and magnitude of summertime overheating across 24 naturally ventilated social housing dwellings retrofitted with ground source heat pumps (GSHPs). The dwellings are located in a socially deprived area in Oxford (UK). The empirical study included longitudinal monitoring of indoor temperatures in the living rooms and bedrooms during the non-heating seasons of 2021 and 2022 (May–September), which included a record-breaking heatwave in July 2022. Indoor temperature and CO2 levels in bedrooms were monitored across a subset of six dwellings alongside the monitoring of window opening state in three bedrooms to understand the effect of natural ventilation in removing excess heat. About 136 thermal comfort surveys were conducted to ascertain the subjective responses of residents. Overheating risk assessment was carried out using CIBSE static and adaptive methods, which revealed that summertime overheating was prevalent across half of the dwellings in the non-heating season of 2022, as compared to 17% overheated dwellings in 2021. Bungalows with upgraded cavity wall insulation and top floor flats facing south and south-west had a propensity to overheat. The variation in indoor temperature and CO2 levels across a small sample also indicated the relationship between overheating and residents’ behaviour. Given that the majority of the dwellings were occupied by retired elderly people with low incomes who are vulnerable to heat and cannot afford active forms of cooling, it is vital to deploy passive design measures, such as appropriate shading devices that are suitable for a heating-dominated climate and enhanced ventilation, as part of home energy retrofits. Implementing reversible heat pumps coupled with solar PVs can provide cooling during heatwaves while delivering low-carbon heat in the winter.
Ramsey Chains in Linear Forests
Authors: Chartrand Gary , Chatterjee Ritabrato , Zhang Ping
Published: October 2023

Every red–blue coloring of the edges of a graph G results in a sequence G1, G2, …, Gℓ of pairwise edge-disjoint monochromatic subgraphs Gi (1≤i≤ℓ) of size i, such that Gi is isomorphic to a subgraph of Gi+1 for 1≤i≤ℓ−1. Such a sequence is called a Ramsey chain in G, and ARc(G) is the maximum length of a Ramsey chain in G, with respect to a red–blue coloring c. The Ramsey index AR(G) of G is the minimum value of ARc(G) among all the red–blue colorings c of G. If G has size m, then k+12≤m<k+22 for some positive integer k. It has been shown that there are infinite classes S of graphs, such that for every graph G of size m in S, AR(G)=k if and only if k+12≤m<k+22. Two of these classes are the matchings mK2 and paths Pm+1 of size m. These are both subclasses of linear forests (a forest of which each of the components is a path). It is shown that if F is any linear forest of size m with k+12<m<k+22, then AR(F)=k. Furthermore, if F is a linear forest of size k+12, where k≥4, that has at most k−12 components, then AR(F)=k, while for each integer t with k−12<t<k+12 there is a linear forest F of size k+12 with t components, such that AR(F)=k−1.
Med-cDiff: Conditional Medical Image Generation with Diffusion Models
Authors: Hung Alex Ling Yu , Zhao Kai , Zheng Haoxin , Yan Ran , Raman Steven S. , Terzopoulos Demetri , Sung Kyunghyun
Published: October 2023

Conditional image generation plays a vital role in medical image analysis as it is effective in tasks such as super-resolution, denoising, and inpainting, among others. Diffusion models have been shown to perform at a state-of-the-art level in natural image generation, but they have not been thoroughly studied in medical image generation with specific conditions. Moreover, current medical image generation models have their own problems, limiting their usage in various medical image generation tasks. In this paper, we introduce the use of conditional Denoising Diffusion Probabilistic Models (cDDPMs) for medical image generation, which achieve state-of-the-art performance on several medical image generation tasks.
In Vivo Assessment of Laboratory-Grown Kidney Tissue Grafts
Authors: Chuang Tinghsien , Bejar Justin , Yue Zhiwei , Slavinsky Mary , Marciano Denise , Drummond Iain , Oxburgh Leif
Published: October 2023

Directed differentiation of stem cells is an attractive approach to generate kidney tissue for regenerative therapies. Currently, the most informative platform to test the regenerative potential of this tissue is engraftment into kidneys of immunocompromised rodents. Stem cell-derived kidney tissue is vascularized following engraftment, but the connection between epithelial tubules that is critical for urine to pass from the graft to the host collecting system has not yet been demonstrated. We show that one significant obstacle to tubule fusion is the accumulation of fibrillar collagens at the interface between the graft and the host. As a screening strategy to identify factors that can prevent this collagen accumulation, we propose encapsulating laboratory-grown kidney tissue in fibrin hydrogels supplemented with candidate compounds such as recombinant proteins, small molecules, feeder cells, and gene therapy vectors to condition the local graft environment. We demonstrate that the AAV-DJ serotype is an efficient gene therapy vector for the subcapsular region and that it is specific for interstitial cells in this compartment. In addition to the histological evaluation of epithelial tubule fusion, we demonstrate the specificity of two urine biomarker assays that can be used to detect human-specific markers of the proximal nephron (CD59) and the distal nephron (uromodulin), and we demonstrate the deposition of human graft-derived urine into the mouse collecting system. Using the testing platform described in this report, it will be possible to systematically screen factors for their potential to promote epithelial fusion of graft and host tissue with a functional intravital read-out.
Anti-COVID-19, Anti-Inflammatory, and Anti-Osteoarthritis Activities of Sesamin from Sesamum indicum L.
Authors: Huang Shu-Ming , Hsieh Cheng-Yang , Ting Jasmine U. , De Castro-Cruz Kathlia A. , Wang Ching-Chiung , Lee Chia-Jung , Tsai Po-Wei
Published: October 2023

During the COVID-19 (coronavirus disease 2019) outbreak, many people were infected, and the symptoms may persist for several weeks or months for recovering patients. This is also known as “long COVID” and includes symptoms such as fatigue, joint pain, muscle pain, et cetera. The COVID-19 virus may trigger hyper-inflammation associated with cytokine levels in the body. COVID-19 can trigger inflammation in the joints, which can lead to osteoarthritis (OA), while long-term COVID-19 symptoms may lead to joint damage and other inflammation problems. According to several studies, sesame has potent anti-inflammatory properties due to its major constituent, sesamin. This study examined sesamin’s anti-inflammatory, anti-osteoarthritis, and anti-COVID-19 effects. Moreover, in vivo and in vitro assays were used to determine sesamin’s anti-inflammatory activity against the RAW264.7 and SW1353 cell lines. Sesamin had a dose-dependent effect (20 mg/kg) in a monoiodoacetic acid (MIA)-induced osteoarthritis rat model. Sesamin reduced paw swelling and joint discomfort. In addition, the findings indicated that sesamin suppressed the expression of iNOS (inducible nitric oxide synthase) and COX-2 (cyclooxygenase-2) in the RAW264.7 cell line within the concentration range of 6.25–50 μM. Furthermore, sesamin also had a suppressive effect on MMP (matrix metalloproteinase) expression in chondrocytes and the SW1353 cell line within the same concentration range of 6.25–50 μM. To examine the anti-viral activity, an in silico analysis was performed to evaluate sesamin’s binding affinity with SARS-CoV-2 RdRp (severe acute respiratory syndrome coronavirus 2 RNA-dependent RNA polymerase) and human ACE2 (angiotensin-converting enzyme 2). Compared to the controls, sesamin exhibited strong binding affinities towards SARS-CoV-2 RdRp and human ACE2. Furthermore, sesamin had a higher binding affinity for the ACE2 target protein. This study suggests that sesamin shows potential anti-SARS-CoV-2 activity for drug development.
Recent Progress in Catalyst Development of the Hydrogenolysis of Biomass-Based Glycerol into Propanediols—A Review
Authors: Ma Lan , Liu Huimin , He Dehua
Published: October 2023

The use of biomass-based glycerol to produce chemicals with high added value is of great significance for solving the problem of glycerol surplus and thus reducing the production cost of biodiesel. The production of 1,2-propanediol (abbreviated as 1,2-PDO) and 1,3-propanediol (abbreviated as 1,3-PDO) via the hydrogenolysis of glycerol is one of the most representative and highest-potential processes for the comprehensive utilization of biomass-based glycerol. Glycerol hydrogenolysis may include several parallel and serial reactions (involving broken C–O and C–C bonds), and therefore, the catalyst is a key factor in improving the rate of glycerol hydrogenolysis and the selectivities of the target products. Over the past 20 years, glycerol hydrogenolysis has been extensively investigated, and until now, the developments of catalysts for glycerol hydrogenolysis have been active research topics. Non-precious metals, including Cu, Ni, and Co, and some precious metals (Ru, Pd, etc.) have been used as the active components of the catalysts for the hydrogenolysis of glycerol to 1,2-PDO, while precious metals such as Pt, Rh, Ru, Pd, and Ir have been used for the catalytic conversion of glycerol to 1,3-PDO. In this article, we focus on reviewing the research progress of the catalyst systems, including Cu-based catalysts and Pt-, Ru-, and Pd-based catalysts for the hydrogenolysis of glycerol to 1,2-PDO, as well as Pt-WOx-based and Ir-ReOx-based catalysts for the hydrogenolysis of glycerol to 1,3-PDO. The influence of the properties of active components and supports, the effects of promoters and additives, and the interaction and synergic effects between active component metals and supports are also examined.
A Pilot Study on the Association between Cardiovascular Risk Factors and Coronary Artery Calcification in a Group of Patients Investigated via Cardiac Computed Tomography in a European Country with High Cardiovascular Risk
Authors: Capisizu Adriana Sorina , Stanciu Silviu Marcel , Cuzino Dragos
Published: October 2023

(1) Background: Cardiovascular disease is the leading cause of mortality worldwide; the prevention and early detection of coronary artery disease are of critical importance; and the coronary artery calcium score is a powerful method in the assessment of coronary artery disease. Among European countries, Romania ranks as a country with a very high risk of cardiovascular diseases, but the data are limited in regard to the prevalence of the calcium score. (2) Methods: A retrospective study was conducted to establish the coronary calcium score in a group of patients investigated via cardiac CT and to determine the correlation with the presence of cardiovascular risk factors. (3) Results: According to the Agatston calcium score, 50% of the patients had a positive calcium score. High calcium scores above 400 UA were present in 12.6% of patients. Regarding the association between the presence of cardiovascular risk factors and the levels of coronary artery calcification, a mild level of calcification was associated with age over 50 years (X2 = 3.88, p = 0.04, OR = 3.25; 95% CI 0.94–11.14); a moderate level of calcification with the age of patients over 50 years (X2 = 6.54, p = 0.01, OR = 5.58; 95% CI 1.29–24.16), dyslipidemia (X2 = 7.28, p = 0.007, OR = 3.37; 95% CI 1.34–8.51), and arterial hypertension (X2 = 5.37, p = 0.02, OR = 2.88; 95% CI 1.14–7.27); a severe level of calcification with hypertension (X2 = 4.61, p = 0.03, OR = 7.03; 95% CI 0.90–54.81); and a very severe level of calcification with hypertension (X2 = 4.61, p = 0.03, OR = 7.03; 95% CI 0.90–54.81), smoking (X2 = 8.07, p = 0.004, OR = 4.44; 95% CI 1.47–13.44), and diabetes (X2 = 13.65, p = 0.001, OR = 6.59; 95% CI 2.5–20.18). (4) Conclusion: Half of the patients investigated by using cardiac CT had a calcium score of zero. Predictors for coronary calcium scores in relation to risk factors varied. For the very severe coronary calcification level, the strongest predictor was the presence of smoking and diabetes, which increased the odds for very severe calcification by 13.46 times. Patients who had multiple cardiovascular risk factors, hypertension, diabetes, and smoking were 9.18 times more likely to have very severe calcification.
CRISPR/Cas12a Collateral Cleavage Activity for Sensitive 3′–5′ Exonuclease Assay
Authors: Jeung Jae Hoon , Han Hyogu , Lee Chang Yeol , Ahn Jun Ki
Published: October 2023

This study presents a technique for detecting 3′–5′ exonuclease activity through the use of CRISPR/Cas12a. These enzymes, including 3′–5′ exonuclease (Exo III), perform crucial roles in various cellular processes and are associated with life expectancy. However, imbalances in their expression can increase susceptibility to diseases such as cancer, particularly under prolonged stress. In this study, an activator sequence of CRISPR/Cas12a was constructed on the 5′–end of a hairpin probe (HP), forming a blunt end. When the 3′–end of the HP was hydrolyzed with Exo III activity, the activator sequence of Cas12a was exposed, which led to collateral cleavage of the DNA signal probe and generated a fluorescent signal, allowing sensitive and highly specific Exo III detection. This detection principle relied on the fact that Exo III exclusively cleaves the 3′–end mononucleotide of dsDNA and does not affect ssDNA. Based on this strategy, Exo III activity was successfully assayed at 0.0073 U/mL, demonstrating high sensitivity. In addition, this technique was used to screen candidate inhibitors of Exo III activity.
Higher Prevalence of Nonsense Pathogenic DMD Variants in a Single-Center Cohort from Brazil: A Genetic Profile Study That May Guide the Choice of Disease-Modifying Treatments
Authors: Braga Vitor Lucas Lopes , Lima Danielle Pessoa , Mariano Tamiris Carneiro , Lima Pedro Lucas Grangeiro de Sá Barreto , Maia Ana Beatriz de Almeida , da Silva Meireles Wallace William , de Oliveira Pessoa Kécia Tavares , de Oliveira Cristiane Mattos , Ribeiro Erlane Marques , Nóbrega Paulo Ribeiro , Pessoa André Luiz Santos
Published: October 2023

Dystrophinopathies are muscle diseases caused by pathogenic variants in DMD, the largest gene described in humans, representing a spectrum of diseases ranging from asymptomatic creatine phosphokinase elevation to severe Duchenne muscular dystrophy (DMD). Several therapeutic strategies are currently in use or under development, each targeting different pathogenic variants. However, little is known about the genetic profiles of northeast Brazilian patients with dystrophinopathies. We describe the spectrum of pathogenic DMD variants in a single center in northeast Brazil. This is an observational, cross-sectional study carried out through molecular-genetic analysis of male patients diagnosed with dystrophinopathies using Multiplex Ligation-dependent Probe Amplification (MLPA) followed by Next-Generation Sequencing (NGS)-based strategies. A total of 94 male patients were evaluated. Deletions (43.6%) and duplications (10.6%) were the most recurring patterns of pathogenic variants. However, small variants were present in 47.1% of patients, most of them nonsense variants (27.6%). This is the largest South American single-center case series of dystrophinopathies to date. We found a higher frequency of treatment-amenable nonsense single-nucleotide variants than most previous studies. These findings may have implications for diagnostic strategies in less-known populations, as a higher frequency of nonsense variants may mean a higher possibility of treating patients with disease-modifying drugs.
Post-Diagnostic Support for Behaviour Changes in Young-Onset Dementia in Australia
Authors: Cadwallader Claire J. , Velakoulis Dennis , Loi Samantha M.
Published: October 2023

Behaviour changes (BCs) are common in young-onset dementia (YOD). Access to knowledgeable and age-appropriate support services is needed to assist with the appropriate management of BCs. We sought to investigate the types of YOD-related BCs that most commonly require support, the formal services being accessed for support, and the experiences of those seeking support in Australia. We employed a cross-sectional online questionnaire for individuals living with YOD as well as individuals providing informal or formal care for someone with YOD. Thirty-six questionnaire responses were recorded. Of the total sample, 83% reported YOD-related BCs requiring support, the most common being appetite/eating changes, followed by agitation/aggression and apathy/indifference. Seventy-six percent of these individuals had attempted to seek support from a formal service, with Dementia Australia, Dementia Support Australia, and general practitioners most commonly approached. Responses suggested that the support access pathway is suboptimal, with a lack of clarity about what services to approach for support and long wait times. Furthermore, 28% of participants had not gained access to support utilizing non-pharmacological strategies. Individuals who need support for YOD-related BCs demonstrated a high rate of help-seeking from formal support services; however, the support access pathway is slow, is difficult to navigate, and does not result in the best-practice management of BCs. Formal services resourced to provide efficient support with the implementation of behavioural strategies are needed, along with clear, accessible guidelines on the pathway to access them.
A Review of the Potential of Nuclear Factor [Erythroid-Derived 2]-like 2 Activation in Autoimmune Diseases
Authors: Ates Ilker , Yılmaz Ayşe Didem , Buttari Brigitta , Arese Marzia , Saso Luciano , Suzen Sibel
Published: October 2023

An autoimmune disease is the consequence of the immune system attacking healthy cells, tissues, and organs by mistake instead of protecting them. Inflammation and oxidative stress (OS) are well-recognized processes occurring in association with acute or chronic impairment of cell homeostasis. The transcription factor Nrf2 (nuclear factor [erythroid-derived 2]-like 2) is of major importance as the defense instrument against OS and alters anti-inflammatory activities related to different pathological states. Researchers have described Nrf2 as a significant regulator of innate immunity. Growing indications suggest that the Nrf2 signaling pathway is deregulated in numerous diseases, including autoimmune disorders. The advantageous outcome of the pharmacological activation of Nrf2 is an essential part of Nrf2-based chemoprevention and intervention in other chronic illnesses, such as neurodegeneration, cardiovascular disease, autoimmune diseases, and chronic kidney and liver disease. Nevertheless, a growing number of investigations have indicated that Nrf2 is already elevated in specific cancer and disease steps, suggesting that the pharmacological agents developed to mitigate the potentially destructive or transformative results associated with the protracted activation of Nrf2 should also be evaluated. The activators of Nrf2 have revealed an improvement in the progress of OS-associated diseases, resulting in immunoregulatory and anti-inflammatory activities; by contrast, the depletion of Nrf2 worsens disease progression. These data strengthen the growing attention to the biological properties of Nrf2 and its possible healing power on diseases. The evidence supporting a correlation between Nrf2 signaling and the most common autoimmune diseases is reviewed here. We focus on the aspects related to the possible effect of Nrf2 activation in ameliorating pathologic conditions based on the role of this regulator of antioxidant genes in the control of inflammation and OS, which are processes related to the progression of autoimmune diseases. Finally, the possibility of Nrf2 activation as a new drug development strategy to target pathogenesis is proposed.
Breaking (Fake) News: No Personal Relevance Effect on Misinformation Vulnerability
Authors: Ceccarini Francesco , Capuozzo Pasquale , Colpizzi Ilaria , Caudek Corrado
Published: October 2023

The massive spread of fake news (FN) requires a better understanding of both risks and protective psychological factors underlying vulnerability to misinformation. Prior studies have mostly dealt with news that do not bear any direct personal relevance to participants. Here, we ask whether high-stakes news topics may decrease vulnerability to FN. Data were collected during the national lockdown in Italy (COVID-19 news) and one year later (political news). We compared truth discrimination and overall belief for true news (TN) and FN concerning COVID-19 and political topics. Our findings indicate that psychological risk and protective factors have similar effects on truth discrimination, regardless of whether the news topic is highly or minimally personally relevant. However, we found different effects of psychological factors on overall belief, for high and low personal relevance. These results suggest that, given a high level of cognitive dissonance, individuals tend to rely on proximal or emotional sources of information. In summary, our study underscores the importance of understanding the psychological factors that contribute to vulnerability to misinformation, particularly in high-stakes news contexts.
Effects of Online Fan Community Interactions on Well-Being and Sense of Virtual Community
Authors: Kim Min Sung , Wang Soyoung , Kim Seongcheol
Published: October 2023

Activities in the digital economy driven by information technology have rapidly increased in scope and speed in the aftermath of COVID-19. Meanwhile, social isolation accelerated by quarantine measures has increased concerns about individuals’ mental health. However, little is known about the specific consequences of online interactions, especially when applied in online fan community-based relationships. Therefore, we examined the impact of loneliness in the context of COVID-19 on online interaction with other fans and parasocial relationships with celebrities on the Weverse platform. We also examined how these interactions influence mental well-being and the sense of virtual community. With 202 valid data samples acquired from global BTS fandom, this study conducted a partial least squares–structural equation modeling analysis. The empirical results demonstrate a significant positive relationship between loneliness and the extent of online interaction, while no significant impact on parasocial relationships was observed. Both online interaction and parasocial relationships were found to enhance both well-being and SOVC. However, these results were observed to differ between Weverse paid subscribers and free users.
Study of the Seismic Behavior of Simplified RCS Joints via Nonlinear Finite Element Analysis
Authors: Li Wei , Wang Zhexiong , Lin Xuchuan , Chen Lianmeng , Chen Baixi
Published: October 2023

Compared to more complex structures, simply configured reinforced concrete column–steel beam (RCS) composite structures have more promising application prospects, especially in regions with moderate–high seismic levels, due to their ease of construction. However, the current understanding of the seismic performance of simplified RCS joints is not sufficient. Validated by experimental results, a nonlinear finite element analysis (FEA) model was developed in this study to reveal the seismic behavior of simplified RCS joints. Six vital design parameters, namely axial load ratio, concrete strength, yield strengths of steel webs and flanges, and diameters of transverse and longitudinal reinforcements, were comprehensively studied. Research has shown that the axial compression ratio has a significant impact on the failure mode and bearing capacity of joints. When the concrete strength increases, the load-bearing capacity of the joints significantly increases, while the brittleness of high-strength concrete leads to a decrease in its deformation capacity. In addition, when the steel beam strength is constant, higher flange and web yield strengths have a limited influence on crack propagation and strain development. The stirrup reinforcement ratio and longitudinal reinforcement ratio play a significant role in inhibiting crack propagation and improving the bearing capacity, respectively. With the help of the numerical results, six theoretical models introduced by national codes and other researchers were compared. Among them, the modified model proposed by Kanno demonstrated the highest accuracy and was the most suitable for simply configured RCS joints.
Effect of Fractionation Process and Addition of Composite Crumb Rubber-Modified Asphalt on Road Performance Variability of Recycled Asphalt Mixtures with High Reclaimed Asphalt Pavement (RAP) Content
Authors: Wei Wenwu , Ji Chao , Song Honggang , Li Zhigang , Liu Zhen , Sun Lijun , Zhou Zhou
Published: October 2023

The application of reclaimed asphalt pavement (RAP) can help reduce resource waste and environmental pollution in road construction. However, so far, only a small percentage of RAP materials can be used in road construction. The key obstacles to the application of a recycled asphalt mixture (RAM) with high RAP content are the variability of RAP materials and the difficulty of fully rejuvenating aged asphalt. However, there is still a lack of research on the effect of the variability of RAP materials and recycled asphalt on the quality control of a RAM. Therefore, this study investigates the effects of sieve pretreatment of RAP material using 4.75 mm sieve mesh and the use of composite crumb rubber-modified asphalt (CCRMA) to reclaim aged asphalt on the road performance and frame variability of reclaimed asphalt mixtures. Therefore, this study investigates the effects of the fractionation process of RAP material using 4.75 mm sieve mesh and the use of CCRMA to reclaim aged asphalt on the road performance of a RAM. The results show that the fractionation process can effectively reduce the mitigation of RAP agglomeration and reduce the variability of gradation, which in turn reduces the variability of road performance. The incorporation of CCRMA can effectively improve the high-temperature stability performance and low-temperature cracking resistance. The dynamic stability and the fracture energy of the CRAM (RAM prepared using CCRMA) were four and one and a half times as large as that of the NAM (RAM prepared using base asphalt), respectively. The fractionation process of RAP material and the utilization of CCRMA could help reduce the variability of the RAM while improving the road performance of the RAM.
Bridge Condition Deterioration Prediction Using the Whale Optimization Algorithm and Extreme Learning Machine
Authors: Jiang Liming , Tang Qizhi , Jiang Yan , Cao Huaisong , Xu Zhe
Published: October 2023

To address the problem in model computations and the limited accuracy of current bridge deterioration prediction methods, this paper proposes a novel bridge deterioration prediction meth-od using the whale optimization algorithm and extreme learning machine (WOA-ELM). First, we collected a dataset consisting of 539 sets of bridge inspection data and determined the necessary influencing factors through correlation analysis. Subsequently, the WOA-ELM algorithm was applied to establish a nonlinear mapping relationship between each influencing factor and the bridge condition indicators. Furthermore, the extreme learning machine (ELM), back-propagation neural network (BPNN), decision trees (DT), and support vector machine (SVM) were employed for comparison to validate the superiority of the proposed method. In addition, this paper provides further substantiation of the model’s exceptional predictive capabilities across diverse bridge components. The results demonstrate the accurate predictive capability of the proposed method for bridge conditions. Compared with ELM, BPNN, DT, and SVM, the proposed method exhibits significant improvements in predictive accuracy, i.e., the correlation coefficient is increased by 4.1%, 11.4%, 24.5%, and 33.6%, and the root mean square error is reduced by 7.3%, 18.0%, 14.8%, and 18.1%, respectively. Moreover, the proposed method presents considerably enhanced generalization capabilities, resulting in the reduction in mean relative error by 11.6%, 15.3%, 6%, and 16.2%. The proposed method presents a robust framework for proactive bridge maintenance.
Determining the Critical Risk Factors of Implementing Public–Private Partnership in Water and Wastewater Infrastructure Facilities: Perspectives of Private and Public Partners in Iran
Authors: Moradi Shahdadi Leila , Aminnejad Babak , Sarvari Hadi , Chan Daniel W. M.
Published: October 2023

Due to the fact that risks can cause project delays and increase project implementation costs, successful construction project completion requires effective and holistic risk management. Identification and evaluation of critical risk factors (CRFs) associated with different types of projects are the most significant components of accurate risk management. This study aims to identify and evaluate the CRFs inherent with private–public partnership (PPP) projects specifically for the development of water and wastewater infrastructure (WWI) facilities in the developing country of Iran. In this line, a comprehensive literature analysis was undertaken to extract the CRFs in applying PPP projects for the development of infrastructure projects in developing countries in general. Then, four rounds of a Delphi survey were conducted to consolidate the major risks to the circumstances of Iran and WWI facilities. There were a total of 35 risks that were grouped into six categories. The main risks were then analyzed and ranked using the Measurement Alternatives and Ranking according to the Compromise Solution (MARCOS) technique. The overall ranking results of the various CRFs revealed that “lack of trust in government’s economic programs” risk was ranked first in terms of importance, followed by the risk of “delay in timely fund payment for project financing and credits,” and the risk of “delay in finalizing bank negotiations.” The overall ranking of the risks placed “economic changes, such as inflation, increase or decrease in prices, and exchange rate” risk in the bottom position. According to the risk ranking findings based on the opinions of private experts, “lack of commitment to the project schedule” was placed first. Conversely, experts from the public sector considered “choosing the wrong financing method” to be the most CRF. It is anticipated that the key research findings and effective recommendations of this study will considerably contribute to the smooth development and remarkable improvement of risk management in applying PPP for WWI facilities in developing countries while enhancing different stakeholders’ understanding of the CRFs for PPP projects, particularly towards WWI services in Iran.
Bonded Behavior of Hybrid-Bonded CFRP to Heat-Damaged Concrete Interface
Authors: Liu Guirong , Wang Yao , Qu Fulai , Guo Xu , Li Yang , Cheng Shengzhao
Published: October 2023

The reliable bond of CFRP to heat-damaged concrete is fundamental to ensuring cooperative working when the CFRP is applied for strengthening fire-damaged concrete structures. In this paper, the bond performance of hybrid-bonded (HB) CFRP to a heat-damaged concrete surface was investigated by using single shear tests. The concrete blocks were initially heat-damaged to temperatures of 100 °C, 200 °C, 300 °C, and 400 °C. The heat-damaged blocks were subsequently bonded with CFRP using the HB technique. The primary experiment parameters were the exposure temperature, the number of mechanical fasteners, and the bonded layers of CFRP. The test results show that the external-bonded (EB) and HB-CFRP joints with concrete exposed to a temperature of 400 °C were prone to fail with concrete shear-tension due to the decreased shear strength of concrete at high temperatures. The EB- and HB-CFRP joints with heat-damaged concrete anchored with no more than three fasteners present a higher bond than the reference joints with unheated concrete, while the HB-CFRP joints anchored with three fasteners provide a decreased bond capacity with the increase in exposure temperature. The utilization rate of single-layer CFRP joints with unheated concrete increased by 57.9%, 139.5%, and 136.8% with the mechanical fasteners in numbers of one, two, and three compared with the reference specimen. Accordingly, the bond capacity increased by 111.8%, 128.4%, and 186.7%. Finally, a model was proposed to estimate the bond strength of HB-CFRP joints with heat-damaged concrete.
Improved Edge Folding Algorithm for 3D Building Models Taking into Account the Visual Features
Authors: Bai Haoyuan , Shen Tao , Huo Liang , Wang Xiaoyu , Liu Xinyu
Published: October 2023

Simplifying 3D building models, effectively reducing model complexity and improving mapping efficiency, is an important part of 3D GIS. In order to address the problem that the simplification basis considered by most 3D building model data compression algorithms is mainly based on geometric features and fails to retain the visual features of the model, this paper proposed a half-folding simplification algorithm for 3D building models that took the visual features into account. The algorithm incorporated regional boundary constraints in the pre-processing stage to focus on preserving the boundary features of the model, and incorporated visual constraints, such as the vertex importance, edge length, and texture, in the calculation of the edge folding cost to construct a new error metric model. The simplification order was changed by redefining the edge folding cost, and a trade-off between compression rate and retention rate was made by using half-edge folding to maximise the retention of the visual features of the building. The experimental results showed that the algorithm could effectively reduce the number of elements drawn by the system and achieve a high level of detail information retention in the visual feature region of the model with a good visual representation.
Synthesis and Characterization of Sustainable Eco-Friendly Alkali-Activated High-Content Iron Ore Tailing Bricks
Authors: Kang Xiangyang , Li Yanman , Li Wei , Zhou Yuxian , Cui Jiarui , Cai Baohua , Zi Yong , Fang Jing , Chen Yongqing , Li Senlin , Kang Xin
Published: October 2023

With the development of urbanization, the demand for bricks continues to increase. However, traditional brick production methods result in significant energy consumption and environmental pollution. In Hebei Province, China, historical mineral extraction activities have left behind substantial iron ore tailings (IOT). With the objective of recycling IOT resources and promoting ecological restoration and sustainable development, the feasibility of producing alkali-activated bricks using iron ore tailings was explored. This study primarily utilized IOT supplemented with ground granulated blast-furnace slag (GGBS) to successfully synthesize sustainable eco-friendly alkali-activated high-content IOT bricks. Experimental investigations were conducted to explore the effects of the raw material mixing ratio, content, and modulus of the alkaline activator, molding pressure, and grain size distribution on the strength. The research demonstrated that the IOT: GGBS ratio of 85:15 met the requirements of the Chinese JC/T422-2007 MU25 standard, resulting in compressive and flexural strengths of 31.72 MPa and 2.83 MPa, respectively. Increasing the alkali activator content enhanced the brick strength, with an optimal alkali activator modulus of 1 M. Moreover, the molding pressure significantly improved brick strength and also enhanced the particle-to-particle contact density. Bricks prepared using finer particle size IOT exhibited higher compressive strength, whereas flexural strength remained relatively unaffected by particle size distribution. Furthermore, a comprehensive analysis of the microstructure and alkali activation mechanism of IOT-GGBS bricks was performed using XRD, SEM, FTIR, and AFM techniques. The results indicated that IOT primarily acted as an aggregate and partially participated in the reaction, whereas GGBS reacted extensively, generating C-S-H gel and C-A-H, providing robust bonding strength. Additionally, the increase in GGBS content led to the partial disintegration of some IOT particles, forming more stable aggregates under the influence of the C-S-H gel. This study offers theoretical guidance for the efficient utilization of IOT in construction materials, thereby contributing to the promotion of sustainable development and environmental conservation.
Treatment of Central Nervous System Tumors on Combination MR-Linear Accelerators: Review of Current Practice and Future Directions
Authors: Bryant John Michael , Doniparthi Ajay , Weygand Joseph , Cruz-Chamorro Ruben , Oraiqat Ibrahim M. , Andreozzi Jacqueline , Graham Jasmine , Redler Gage , Latifi Kujtim , Feygelman Vladimir , Rosenberg Stephen A. , Yu Hsiang-Hsuan Michael , Oliver Daniel E.
Published: October 2023

Magnetic resonance imaging (MRI) provides excellent visualization of central nervous system (CNS) tumors due to its superior soft tissue contrast. Magnetic resonance-guided radiotherapy (MRgRT) has historically been limited to use in the initial treatment planning stage due to cost and feasibility. MRI-guided linear accelerators (MRLs) allow clinicians to visualize tumors and organs at risk (OARs) directly before and during treatment, a process known as online MRgRT. This novel system permits adaptive treatment planning based on anatomical changes to ensure accurate dose delivery to the tumor while minimizing unnecessary toxicity to healthy tissue. These advancements are critical to treatment adaptation in the brain and spinal cord, where both preliminary MRI and daily CT guidance have typically had limited benefit. In this narrative review, we investigate the application of online MRgRT in the treatment of various CNS malignancies and any relevant ongoing clinical trials. Imaging of glioblastoma patients has shown significant changes in the gross tumor volume over a standard course of chemoradiotherapy. The use of adaptive online MRgRT in these patients demonstrated reduced target volumes with cavity shrinkage and a resulting reduction in radiation dose to uninvolved tissue. Dosimetric feasibility studies have shown MRL-guided stereotactic radiotherapy (SRT) for intracranial and spine tumors to have potential dosimetric advantages and reduced morbidity compared with conventional linear accelerators. Similarly, dosimetric feasibility studies have shown promise in hippocampal avoidance whole brain radiotherapy (HA-WBRT). Next, we explore the potential of MRL-based multiparametric MRI (mpMRI) and genomically informed radiotherapy to treat CNS disease with cutting-edge precision. Lastly, we explore the challenges of treating CNS malignancies and special limitations MRL systems face.
Epigenetic Profiling of PTPN11 Mutant JMML Hematopoietic Stem and Progenitor Cells Reveals an Aberrant Histone Landscape
Authors: Sinha Roshani , Dvorak Mai , Ganesan Ananthakrishnan , Kalesinskas Larry , Niemeyer Charlotte M. , Flotho Christian , Sakamoto Kathleen M. , Lacayo Norman , Patil Rachana Vinay , Perriman Rhonda , Cepika Alma-Martina , Liu Yunying Lucy , Kuo Alex , Utz Paul J. , Khatri Purvesh , Bertaina Alice
Published: October 2023

Juvenile myelomonocytic leukemia (JMML) is a deadly pediatric leukemia driven by RAS pathway mutations, of which >35% are gain-of-function in PTPN11. Although DNA hypermethylation portends severe clinical phenotypes, the landscape of histone modifications and chromatin profiles in JMML patient cells have not been explored. Using global mass cytometry, Epigenetic Time of Flight (EpiTOF), we analyzed hematopoietic stem and progenitor cells (HSPCs) from five JMML patients with PTPN11 mutations. These data revealed statistically significant changes in histone methylation, phosphorylation, and acetylation marks that were unique to JMML HSPCs when compared with healthy controls. Consistent with these data, assay for transposase-accessible chromatin with sequencing (ATAC-seq) analysis revealed significant alterations in chromatin profiles at loci encoding post-translational modification enzymes, strongly suggesting their mis-regulated expression. Collectively, this study reveals histone modification pathways as an additional epigenetic abnormality in JMML patient HSPCs, thereby uncovering a new family of potential druggable targets for the treatment of JMML.
Image-Based Deep Learning Detection of High-Grade B-Cell Lymphomas Directly from Hematoxylin and Eosin Images
Authors: Perry Chava , Greenberg Orli , Haberman Shira , Herskovitz Neta , Gazy Inbal , Avinoam Assaf , Paz-Yaacov Nurit , Hershkovitz Dov , Avivi Irit
Published: October 2023

Deep learning applications are emerging as promising new tools that can support the diagnosis and classification of different cancer types. While such solutions hold great potential for hematological malignancies, there have been limited studies describing the use of such applications in this field. The rapid diagnosis of double/triple-hit lymphomas (DHLs/THLs) involving MYC, BCL2 and/or BCL6 rearrangements is obligatory for optimal patient care. Here, we present a novel deep learning tool for diagnosing DHLs/THLs directly from scanned images of biopsy slides. A total of 57 biopsies, including 32 in a training set (including five DH lymphoma cases) and 25 in a validation set (including 10 DH/TH cases), were included. The DHL-classifier demonstrated a sensitivity of 100%, a specificity of 87% and an AUC of 0.95, with only two false positive cases, compared to FISH. The DHL-classifier showed a 92% predictive value as a screening tool for performing conventional FISH analysis, over-performing currently used criteria. The work presented here provides the proof of concept for the potential use of an AI tool for the identification of DH/TH events. However, more extensive follow-up studies are required to assess the robustness of this tool and achieve high performances in a diverse population.
Impact of Imaging Biomarkers and AI on Breast Cancer Management: A Brief Review
Authors: Saleh Gehad A. , Batouty Nihal M. , Gamal Abdelrahman , Elnakib Ahmed , Hamdy Omar , Sharafeldeen Ahmed , Mahmoud Ali , Ghazal Mohammed , Yousaf Jawad , Alhalabi Marah , AbouEleneen Amal , Tolba Ahmed Elsaid , Elmougy Samir , Contractor Sohail , El-Baz Ayman
Published: October 2023

Breast cancer stands out as the most frequently identified malignancy, ranking as the fifth leading cause of global cancer-related deaths. The American College of Radiology (ACR) introduced the Breast Imaging Reporting and Data System (BI-RADS) as a standard terminology facilitating communication between radiologists and clinicians; however, an update is now imperative to encompass the latest imaging modalities developed subsequent to the 5th edition of BI-RADS. Within this review article, we provide a concise history of BI-RADS, delve into advanced mammography techniques, ultrasonography (US), magnetic resonance imaging (MRI), PET/CT images, and microwave breast imaging, and subsequently furnish comprehensive, updated insights into Molecular Breast Imaging (MBI), diagnostic imaging biomarkers, and the assessment of treatment responses. This endeavor aims to enhance radiologists’ proficiency in catering to the personalized needs of breast cancer patients. Lastly, we explore the augmented benefits of artificial intelligence (AI), machine learning (ML), and deep learning (DL) applications in segmenting, detecting, and diagnosing breast cancer, as well as the early prediction of the response of tumors to neoadjuvant chemotherapy (NAC). By assimilating state-of-the-art computer algorithms capable of deciphering intricate imaging data and aiding radiologists in rendering precise and effective diagnoses, AI has profoundly revolutionized the landscape of breast cancer radiology. Its vast potential holds the promise of bolstering radiologists’ capabilities and ameliorating patient outcomes in the realm of breast cancer management.