bluuebunny/crossref_metadata_2025 huggingface dataset:
The Musa Marker Database: A Comprehensive Genomic Resource for the Improvement of the Musaceae Family
Authors: Biswas Manosh Kumar , Biswas Dhiman , Yi Ganjun , Deng Guiming
Published: April 2024

Molecular markers, including Simple Sequence Repeat (SSR), Single Nucleotide Polymorphism (SNP), and Intron Length Polymorphism (ILP), are widely utilized in crop improvement and population genetics studies. However, these marker resources remain insufficient for Musa species. In this study, we developed genome-wide SSR, SNP, and ILP markers from Musa and its sister species, creating a comprehensive molecular marker repository for the improvement of Musa species. This database contains 2,115,474 SSR, 63,588 SNP, and 91,547 ILP markers developed from thirteen Musa species and two of its relative species. We found that 77% of the SSR loci are suitable for marker development; 38% of SNP markers originated from the genic region, and transition mutations (C↔T; A↔G) were more frequent than transversion. The database is freely accessible and follows a ‘three-tier architecture,’ organizing marker information in MySQL tables. It has a user-friendly interface, written in JavaScript, PHP, and HTML code. Users can employ flexible search parameters, including marker location in the chromosome, transferability, polymorphism, and functional annotation, among others. These distinctive features distinguish the Musa Marker Database (MMdb) from existing marker databases by offering a novel approach that is tailored to the precise needs of the Musa research community. Despite being an in silico method, searching for markers based on various attributes holds promise for Musa research. These markers serve various purposes, including germplasm characterization, gene discovery, population structure analysis, and QTL mapping.
An Optimized Protocol for Comprehensive Evaluations of Salt Tolerance in Crop Germplasm Accessions: A Case Study of Tomato (Solanum lycopersicum L.)
Authors: Chen Zheng , Li Xin , Zhou Rong , Hu Enmei , Peng Xianghan , Jiang Fangling , Wu Zhen
Published: April 2024

The comprehensive evaluation of crop germplasm serves to scientifically and objectively assess the quality of different genetic accessions against certain standards. Here, we propose an optimized approach to enhance the result’s stability when assessing salt tolerance in crop germplasm. This protocol was applied to a case study involving 249 tomato genotypes, systematically refining the processes involved in constructing an evaluation index system, data preprocessing, statistical method selection, and weight calculation. The optimization process reduced the system variance of salt tolerance evaluation results and achieved an 85.42% concordance with a classical approach, across a tomato population covering 241 genotypes, suggesting the improved stability and high accuracy of the optimized protocol. Moreover, an 83.82% consistency rate between pre- and post-optimization results also suggested the high accuracy of the optimized protocol. The enhanced stability was further confirmed by a secondary validation on a subpopulation (covering 39 genotypes), which demonstrated a consistency rate of 83.87% between the two populations. The study identified 8.43% of the evaluated germplasm as salt-tolerant accessions, providing valuable parental materials for breeding programs. The findings underscore the potential of our protocol for the precise identification of stress-resistant germplasm, contributing to the development of stress-tolerant crop varieties.
Comparative Evaluation of Diagnostic Methods for Subclinical Benign Prostatic Hyperplasia in Intact Breeding Male Dogs
Authors: Laurusevičius Tomas , Šiugždaitė Jūratė , Juodžiukynienė Nomeda , Kerzienė Sigita , Anskienė Lina , Jackutė Vaiva , Trumbeckas Darius , Van Soom Ann , Posastiuc Florin Petrisor , Žilinskas Henrikas
Published: April 2024

Benign prostatic hyperplasia (BPH) is an androgen-related non-neoplastic enlargement of the prostate gland that commonly affects both reproductive capabilities and the general health of intact dogs. The subclinical form of BPH can be challenging to diagnose due to a lack of clinical signs, even if rectal palpation is performed. Left untreated, this condition poses risks to the dogs’ health and breeding status. This study, involving 65 male dogs, aimed to investigate subclinical BPH through rectal palpation, ultrasonography, and analysis of canine prostatic-specific esterase (CPSE). Of the participants, 35 had subclinical BPH, and 30 served as a healthy control group. Dogs suspected of subclinical BPH, as determined by examination results from ultrasonography and CPSE analysis, underwent fine needle aspiration (FNA) guided by ultrasound to enhance diagnostic precision. Findings revealed distinct differences in rectal palpation and ultrasonography between subclinical BPH and healthy dogs. This study established diagnostic thresholds based on prostatic volume and CPSE values and proposed new thresholds for subclinical BPH. Additionally, results showed that prostate gland volume depended on the weight and the age of the dog. In conclusion, early detection of this condition is possible through various examinations, such as changes in ultrasound features, CPSE levels, and rectal palpation. All together, these methods can aid practitioners in early detection of BPH and assist with scheduling screening programs for dogs, ultimately promoting their overall health and reproductive well-being. In conclusion, we advocate for routine, non-invasive prostate screenings in breeding males, underlining the effectiveness of a combination of various multiple techniques for early subclinical BPH detection.
Emotion Recognition beyond Pixels: Leveraging Facial Point Landmark Meshes
Authors: Arabian Herag , Abdulbaki Alshirbaji Tamer , Chase J. Geoffrey , Moeller Knut
Published: April 2024

Digital health apps have become a staple in daily life, promoting awareness and providing motivation for a healthier lifestyle. With an already overwhelmed healthcare system, digital therapies offer relief to both patient and physician alike. One such planned digital therapy application is the incorporation of an emotion recognition model as a tool for therapeutic interventions for people with autism spectrum disorder (ASD). Diagnoses of ASD have increased relatively rapidly in recent years. To ensure effective recognition of expressions, a system is designed to analyze and classify different emotions from facial landmarks. Facial landmarks combined with a corresponding mesh have the potential of bypassing hurdles of model robustness commonly affecting emotion recognition from images. Landmarks are extracted from facial images using the Mediapipe framework, after which a custom mesh is constructed from the detected landmarks and used as input to a graph convolution network (GCN) model for emotion classification. The GCN makes use of the relations formed from the mesh along with the special distance features extracted. A weighted loss approach is also utilized to reduce the effects of an imbalanced dataset. The model was trained and evaluated with the Aff-Wild2 database. The results yielded a 58.76% mean accuracy on the selected validation set. The proposed approach shows the potential and limitations of using GCNs for emotion recognition in real-world scenarios.
Energy Efficiency Improvement in Reconfigurable Photovoltaic Systems: An Evaluation of Team Systems
Authors: Afzali Roohollah , Velasco-Quesada Guillermo
Published: April 2024

The main objective of this work is to evaluate the energy efficiency improvement obtained in grid-connected photovoltaic systems based on a dynamic reconfiguration strategy. The MIX and team reconfigurable photovoltaic system topologies have been considered since both minimize the operation of the inverters in low-load conditions. A numerical method is used to analyze the energy flows within the photovoltaic system, with a specific focus on the plant-oriented configuration. In this work, MIX systems are only presented briefly, while team reconfigurable photovoltaic systems are analyzed in more detail. This is because team systems can be implemented using conventional commercial inverters, electromechanical switches to redirect power flows, and a simple digital controller (as based on the Arduino platforms). The energy supplied to the grid by two grid-connected photovoltaic systems will be evaluated: one based on a classic non-reconfigurable strategy and another based on the team strategy. The measurement of the energy generated by these two systems, tested under various irradiance levels (emulating different climatic conditions), shows that reconfigurable systems always exhibit greater energy efficiency. However, this energy improvement can only be considered substantial in certain situations.
Prediction of Total Petroleum Hydrocarbons and Heavy Metals in Acid Tars Using Machine Learning
Authors: Tita Mihaela , Onutu Ion , Doicin Bogdan
Published: April 2024

Hazardous petroleum wastes are an inevitable source of environmental pollution. Leachates from these wastes could contaminate soil and potable water sources and affect human health. The management of acid tars, as a byproduct of refining and petrochemical processes, represented one of the major hazardous waste problems in Romania. Acid tars are hazardous and toxic waste and have the potential to cause pollution and environmental damage. The need for the identification, study, characterization, and subsequently either the treatment, valorization, or elimination of acid tars is determined by the fact that they also have high concentrations of hydrocarbons and heavy metals, toxic for the storage site and its neighboring residential area. When soil contamination with acid tars occurs, sustainable remediation techniques are needed to restore soil quality to a healthy production state. Therefore, it is necessary to ensure a rapid but robust characterization of the degree of contamination with hydrocarbons and heavy metals in acid tars so that appropriate techniques can then be used for treatment/remediation. The first stage in treating these acid tars is to determine its properties. This article presents a software program that uses machine learning to estimate selected properties of acid tars (pH, Total Petroleum Hydrocarbons—TPH, and heavy metals). The program uses the Automatic Machine Learning technique to determine the Machine Learning algorithm that has the lowest estimation error for the given dataset, with respect to the Mean Average Error and Root Mean Squared Error. The chosen algorithm is used further for properties estimation, using the R2 correlation coefficient as a performance criterion. The dataset used for training has 82 experimental points with continuous, unique values containing the coordinates and depth of acid tar samples and their properties. Based on an exhaustive search performed by the authors, a similar study that considers machine learning applications was not found in the literature. Further research is required because the method presented therein can be improved because it is dataset dependent, as is the case with every ML problem.
Optimizing Mobile Laser Scanning Accuracy for Urban Applications: A Comparison by Strategy of Different Measured Ground Points
Authors: Běloch Lukáš , Pavelka Karel
Published: April 2024

Mobile mapping systems are part of modern data collection in geodesy. It is one of many surveying methods where field collection is performed in a short time. Among their advantages are cost savings and better visualisation than classic surveying methods. This article is focused on accuracy determinations in urban built-up areas of mobile laser scanning using the Riegl VMX-2HA system. These areas, where there is a combination of dense housing and trees, are an integral part of cities. Their diversity and complexity make surveying by other surveying methods time-consuming and complicated. In particular, the GNSS RTK method encounters problematic locations where sky obscuration by surrounding elements reduces measurement accuracy. Data collection was performed on a test base in the city of Pilsen, Czech Republic. The base includes 27 control points and more than 100 checkpoints. Two sets of coordinates were created for the points; the first set is calculated using tied net adjustment and the second one is determined by RTK GNSS measurements. Point cloud calculations were processed in RiPROCESS software from Riegl, using different configurations and qualities of the control points. Each point cloud was analysed including the determination of point cloud deviations. This article is also dedicated to the identification of problematic spots, where measurement can be degraded. The results presented in this paper show the influence of the quality and different spacing of the control points on the point cloud, its accuracy compared to the precise points, and the global and local deformation of the point cloud. This work can be used as a basis for replacing classical surveying methods with a more efficient mobile laser scanning method.
Mechanical and Microstructural Changes in Expansive Soils Treated with Lime and Lignin Fiber from Paper Industry
Authors: Wang Taian , Wang Yejiao
Published: April 2024

Expansive soil exhibits significant swellings and shrinkages, which may result in severe damage or the collapse of structures built upon it. Calcium-based admixtures, such as lime, are commonly used to improve this problematic soil. However, traditional chemical additions can increase significant environmental stress. This paper proposes a sustainable solution, namely, the use of lignin fiber (LF) from the paper industry to partially replace lime as an amendment for expansive soils. Both the macroscopic and microscopic characteristics of the lignin fiber-treated expansive soil are extensively studied. The results show that the mechanical properties of expansive soil are improved by using lignin fiber alone. Under the condition of an optimal dosage of 8%, the compressive strength of lignin fiber-modified soil can reach 193 kPa, the shear strength is increased by 40% compared with the untreated soil, and the water conductivity is also improved with the increase in dosage. In addition, compared with 2% lime-modified soil, the compressive strength of 8% lignin fiber- and 2% lime composite-treated expansive soil increased by 50%, the cohesion increased by 12%, and the water conductivity decreased significantly. The microstructure analysis shows that at an 8% lignin fiber content, lignin fibers interweave into a network in the soil, which effectively enhances the strength and stability of the improved soil. Simultaneously, the fibers can form bridges across the adjacent micropores, leading to the merging of pores and transforming fine, dispersed micropores into larger, connected macropores. Lime promotes the flocculation of soil particles, forming larger aggregates and thus resulting in larger pores. The addition of fibers exerts an inhibitory effect on the flocculation reaction in the composite-improved soil. In conclusion, lignin fibers are an effective addition used to partially replace calcium admixture for the treatment of expansive soil, which provides a sustainable and environmentally friendly treatment scheme for reducing industrial waste.
Adaptation and Validation of Injection Rate Predictive Model for Solenoid Type Injectors with Different Nozzle Geometry
Authors: Rojas-Reinoso Edgar Vicente , Morales-Chauca Karen , Lara-Lara Jandry , Soriano José Antonio , García-Contreras Reyes
Published: April 2024

The present research analyses the injection rate of a direct rail injection diesel engine, focusing specifically on the influence of the nozzles and various operating conditions from real road tests on the rate of injection. A diesel injector test bench was used for feedback with real data from the test vehicle under real road conditions. An analysis of the behaviour of the injection rate was carried out using the zero-dimensional model. This model generated a predictive model that incorporated the five variables identified through a developed multivariate analysis of variance, showing a high correlation of dependence between variations in injection pressure, the diameter of the holes, and the number of holes with greater representativeness. The results obtained showed that the nozzle geometry and the physical properties of the fuel had a direct effect on the injection rate. This analysis enriches the understanding of fuel injection and its effects on diesel engine performance by providing an analysis of the system components that influence the injection rate and generating a simple tool to feed thermodynamic diagnostic models. The proposal model may be used as an input in thermodynamics predictive models and reduce the simulation load in computational fluid dynamics predictive models.
Sparse-View Artifact Correction of High-Pixel-Number Synchrotron Radiation CT
Authors: Huang Mei , Li Gang , Sun Rui , Zhang Jie , Wang Zhimao , Wang Yanping , Deng Tijian , Yu Bei
Published: April 2024

High-pixel-number synchrotron radiation computed tomography (CT) has the advantages of high sensitivity, high resolution, and a large field of view. It has been widely used in biomedicine, cultural heritage research, non-destructive testing, and other fields. The Nyquist sampling theorem states that when the detector’s pixels per row are increased, it requires more CT projections, resulting in a lengthened CT scan time and increased radiation damage. Sparse-view CT can significantly reduce radiation damage and improve the projection data acquisition speed. However, there is insufficient sparse projection data, and the slices reconstructed show aliasing artifacts. Currently, aliasing artifact correction processes more medical CT images, and the number of pixels of such images is small (mainly 512×512 pixels). This paper presents an aliasing artifact correction algorithm based on deep learning for synchrotron radiation CT with a high pixel number (1728×1728 pixels). This method crops high-pixel-number CT images with aliasing artifacts into patches with overlapping features. During the network training process, a convolutional neural network is utilized to enhance the details of the patches, after which the patches are reintegrated into a new CT slice. Subsequently, the network parameters are updated to optimize the new CT slice that closely approximates the full-view slice. To align with practical application requirements, the neural network is trained using only three samples to optimize network parameters and applied successfully to untrained samples for aliasing artifact correction. Comparative analysis with typical deep learning aliasing artifact correction algorithms demonstrates the superior ability of our method to correct aliasing artifacts while preserving image details more effectively. Furthermore, the effect of aliasing artifact correction at varying levels of projection sparsity is investigated, revealing a positive correlation between image quality after deep learning processing and the number of projections. However, the trade-off between rapid experimentation and artifact correction remains a critical consideration.
Technology Readiness Levels (TRLs) in the Era of Co-Creation
Authors: Yfanti Sofia , Sakkas Nikos
Published: April 2024

Technology readiness levels (TRLs) is a well-established and widely used approach for defining the readiness of new technology. It assesses technology maturity against specific benchmarks, ranging from level 1 (concept) to level 9 (market solution). Although this is a useful classification service that allows us to establish a common language, there are cases where we find that this conceptual approach cannot adequately highlight the maturity of certain innovative endeavors and effectively steer their development to higher TRLs. We will present an empirical case where the TRL approach presented a critical shortcoming in highlighting the true and effective readiness of a specific technological development and could not suggest the next natural step in ascending the maturity ladder. We will seek to generalize for the case of co-creation at large, analyze why co-creation may be poorly serviced by the current TRL model, and suggest an amendment that would allow the observed shortcomings of the traditional TRL approach to be overcome and its use extended into such co-creative settings, thus allowing stakeholders to enhance the effectiveness and impact of their collaborative innovation efforts.
Theoretical Spectra of Lanthanides for Kilonovae Events: Ho I-III, Er I-IV, Tm I-V, Yb I-VI, Lu I-VII
Authors: Nahar Sultana N.
Published: April 2024

The broad emission bump in the electromagnetic spectra observed following the detection of gravitational waves created during the kilonova event of the merging of two neutron stars in August 2017, named GW170817, has been linked to the heavy elements of lanthanides (Z = 57–71) and a new understanding of the creation of heavy elements in the r-process. The initial spectral emission bump has a wavelength range of 3000–7000 Å, thus covering the region of ultraviolet (UV) to optical (O) wavelengths, and is similar to those seen for lanthanides. Most lanthanides have a large number of closely lying energy levels, which introduce extensive sets of radiative transitions that often form broad regions of lines of significant strength. The current study explores these broad features through the photoabsorption spectroscopy of 25 lanthanide ions, Ho I-III, Er I-IV, Tm I-V, Yb I-VI, and Lu I-VII. With excitation only to a few orbitals beyond the ground configurations, we find that most of these ions cover a large number of bound levels with open 4f orbitals and produce tens to hundreds of thousands of lines that may form one or multiple broad features in the X-ray to UV, O, and infrared (IR) regions. The spectra of 25 ions are presented, indicating the presence, shapes, and wavelength regions of these features. The accuracy of the atomic data used to interpret the merger spectra is an ongoing problem. The present study aims at providing improved atomic data for the energies and transition parameters obtained using relativistic Breit–Pauli approximation implemented in the atomic structure code SUPERSTRUCTURE and predicting possible features. The present data have been benchmarked with available experimental data for the energies, transition parameters, and Ho II spectrum. The study finds that a number of ions under the present study are possible contributors to the emission bump of GW170817. All atomic data will be made available online in the NORAD-Atomic-Data database.
Development of a New Kombucha from Grape Pomace: The Impact of Fermentation Conditions on Composition and Biological Activities
Authors: Barakat Nathalie , Bouajila Jalloul , Beaufort Sandra , Rizk Ziad , Taillandier Patricia , El Rayess Youssef
Published: April 2024

Winemaking is one of the oldest biotechnology techniques in the world. The wine industry generates 20 million tons of by-products, such as wastewater, stalk, lees, pomace, and stems, each year. The objective of this research project is to valorize wine industry by-products by producing a functional beverage via the fermentation of grape pomace with the kombucha consortium. In this study, grape pomace kombucha was produced under different conditions, and the concentration of the added sucrose in addition to the fermentation duration and temperature were varied. Overall, fermentation was characterized by the consumption of sugars and the production of organic acids and ethanol. An improvement in the concentrations of the total polyphenols and anthocyanins was observed in the developed product (i.e., up to 100%). Moreover, an enhancement of the antioxidant potential by 100%, as well as increases of 50 to 75% in the anti-inflammatory and antidiabetic activities, was noted.
E-DQN-Based Path Planning Method for Drones in Airsim Simulator under Unknown Environment
Authors: Chao Yixun , Dillmann Rüdiger , Roennau Arne , Xiong Zhi
Published: April 2024

To improve the rapidity of path planning for drones in unknown environments, a new bio-inspired path planning method using E-DQN (event-based deep Q-network), referring to introducing event stream to reinforcement learning network, is proposed. Firstly, event data are collected through an airsim simulator for environmental perception, and an auto-encoder is presented to extract data features and generate event weights. Then, event weights are input into DQN (deep Q-network) to choose the action of the next step. Finally, simulation and verification experiments are conducted in a virtual obstacle environment built with an unreal engine and airsim. The experiment results show that the proposed algorithm is adaptable for drones to find the goal in unknown environments and can improve the rapidity of path planning compared with that of commonly used methods.
Pragmatic Communication Deficit and Functional Outcome in Patients with Right- and Left-Brain Damage: A Pilot Study
Authors: Spaccavento Simona , Caliendo Sofia , Galetta Roberta , Picciola Emilia , Losavio Ernesto , Glueckauf Robert
Published: April 2024

Pragmatic communication abilities refer to the capacity to use language in a social context. Despite evidence to the contrary, the left cerebral hemisphere of the majority of right handers has been considered exclusively specialized for control of language phonology, syntax and semantics, whereas the right hemisphere has been specialized for the control of language pragmatics. Many studies have shown the non-exclusivity of the left hemisphere for language skills. Communication deficits observed in these studies for patients with right hemisphere damage confirmed the necessity for integrity of the right hemisphere across a number of language components. The aim of this study is to investigate the specific role of the right and left hemispheres across several aspects of communication deficits, with particular attention given to the influence of these deficits on functional outcome. The second aim is to characterize possible correlations between pragmatic and other cognitive deficits. We evaluated 22 patients, 15 with left- and 7 with right-brain ischemic or hemorrhagic damage, using cognitive, pragmatic and language tests. We deployed the Right Hemisphere Language Battery–Santa Lucia and Montreal d’Evaluation de la Communication to assess pragmatic abilities. The results showed no statistically significant differences between patients with left- and right-brain damage, highlighting the importance of integration between the two hemispheres in the communication process. Multiple significant correlations were found between pragmatic abilities and cognitive tests assessing global cognitive functioning, pantomime expression and comprehension. Pragmatic deficits were also shown to correlate with functional cognitive outcome. It is important to assess pragmatic abilities in patients with cognitive deficits after both left and right stroke for tailoring neuropsychological intervention to mitigate pragmatic disabilities in functional outcomes.
Reading Skill Profiles in School-Aged Italian-Speaking Children: A Latent Profile Analysis Investigation into the Interplay of Decoding, Comprehension and Attentional Control
Authors: Pasqualotto Angela , Mazzoni Noemi , Benso Francesco , Chiorri Carlo
Published: April 2024

Our study examined the complex relationships among reading performance (decoding, comprehension) and language, visuo-spatial, and attentional control abilities in 115 Italian-speaking children. Latent profile analysis was used to identify distinct clusters of participants showcasing quantitative differences in decoding skills, including word, pseudo-word, text reading speed and accuracy. Then, we used this classification to investigate group differences in a variety of linguistic, working memory, and visuo-spatial tasks, as well as in reading comprehension skills, by means of multivariate and univariate tests. Our results reveal significant links between reading proficiency and several key factors: language skills, visuo-spatial abilities, and attentional control. These findings illuminate the nuanced impact of domain-general processes that govern a series of linguistic and visuo-perceptive subcomponents during reading tasks. Additionally, using dominance analysis, predictors of written text comprehension were identified. Our findings suggest that effective reading comprehension relies on a synergistic interplay of adequate reading speed, attentional control, working memory, and verbal fluency, accounting for 23% of the explained variance. This study highlights the multifaceted nature of reading proficiency and suggests that a broader perspective is necessary to fully understand reading development and support its improvement.
Home-Based Transcranial Direct Current Stimulation in Primary Progressive Aphasia: A Pilot Study
Authors: Neophytou Kyriaki , Williamson Kelly , Herrmann Olivia , Afthinos Alexandros , Gallegos Jessica , Martin Nadine , Tippett Donna C. , Tsapkini Kyrana
Published: April 2024

Background: This study aims to determine (a) if home-based anodal transcranial direct current stimulation (a-tDCS) delivered to the left supramarginal gyrus (SMG) coupled with verbal short-term memory/working memory (vSTM/WM) treatment (“RAM”, short for “Repeat After Me”) is more effective than sham-tDCS in improving vSTM/WM in patients with primary progressive aphasia (PPA), and (b) whether tDCS effects generalize to other language and cognitive abilities. Methods: Seven PPA participants received home-based a-tDCS and sham-tDCS coupled with RAM treatment in separate conditions in a double-blind design. The treatment task required participants to repeat word spans comprising semantically and phonologically unrelated words in the same and reverse order. The evaluation of treatment effects was carried out using the same tasks as in the treatment but with different items (near-transfer effects) and tasks that were not directly related to the treatment (far-transfer effects). Results: A-tDCS showed (a) a significant effect in improving vSTM abilities, measured by word span backward, and (b) a generalization of this effect to other language abilities, namely, spelling (both real words and pseudowords) and learning (retention and delayed recall). Conclusions: These preliminary results indicate that vSTM/WM intervention can improve performance in trained vSTM/WM tasks in patients with PPA, especially when augmented with home-based tDCS over the left SMG.
A Work Breakdown Structure for Estimating Building Life Cycle Cost Aligned with Sustainable Assessment—Application to Functional Costs
Authors: Vázquez-López Eduardo , Solís-Guzmán Jaime , Marrero Madelyn
Published: April 2024

The tools used for budgeting in the building design phase are still insufficient to address the life cycle of the building in terms of environmental and cost impacts. The main objective of this research is to define a model for extending existing cost databases to accommodate life cycle sustainability assessment. For this, current classification systems are reviewed and a case study has been analysed using the new approach. To this end, a new system of classification of construction information is proposed for the evaluation of early design costs, when data are scarce and the only information available refers to the gross interior area and the plot. The classification organizes the costs in a similar way to the sustainability assessment in EN-15643. A subcategory has been added for revenue, developer costs, and taxes at all stages of the lifecycle. The resulting classification is applied to the functional elements of a secondary school project. In the case study, construction costs represent 21% while the use stage accounts for 72% in a 100-year lifespan. The results show that, starting from generic cost bases, more complex costs and functional costs can be defined at different stages of the life cycle and adjusted to sustainability assessment standards.
Investigating the Factors Influencing the Strength of Cold-Formed Steel (CFS) Sections
Authors: Hussein Diyari B. , Hussein Ardalan B.
Published: April 2024

The utilization of cold-formed steel (CFS) sections in construction has become widespread due to their favorable attributes, including their lightweight properties, high strength, recyclability, and ease of assembly. To ensure their continued safe and efficient utilization, this review provides a comprehensive investigation into the factors influencing the strength of CFS members. This analysis encompasses design codes, prediction methodologies, material properties, and various structural configurations. This review uncovers discrepancies among existing design codes, particularly noting conservative predictions in AISI and AS/NZS standards for composite and built-up sections. Additionally, the effectiveness of prediction methods such as the direct strength method and effective width method varies based on specific structural configurations and loading conditions. Furthermore, this review delves into recent advancements aimed at enhancing fire resistance, connection design, and the composite behavior of CFS structures. The influence of factors such as eccentricity, sheathing materials, and bolt spacing on structural performance is also examined. This study underscores the crucial role of accurate prediction methods and robust design standards in ensuring the structural integrity and safety of CFS constructions. Through a comparative analysis, it is revealed that AISI and AS/NZS standards exhibit conservatism in predicting nominal buckling loads compared to experimental data. Conversely, a non-linear finite element analysis demonstrates a strong correlation with laboratory tests, offering a more accurate prediction of nominal buckling capacity. Overall, this review offers comprehensive insights aimed at optimizing CFS structural design practices. By identifying key areas for future research and development, this work contributes to the ongoing advancement of safe and efficient CFS construction applications.
Digital Twin Research on Masonry–Timber Architectural Heritage Pathology Cracks Using 3D Laser Scanning and Deep Learning Model
Authors: Luo Shengzhong , Wang Hechi
Published: April 2024

Due to various factors such as aging, natural environment erosion, and man-made destruction, architectural heritage has formed various diseases and cracks, especially in pathology cracks, which are the most typical masonry–timber architectural heritages, directly affecting the structural stability of masonry–timber buildings. This paper uses artificial intelligence and architecture and other multi-disciplinary research methods, taking James Jackson Gymnasium, a famous masonry–timber architectural heritage in Wuhan, as an example, using 3D laser scanning technology to obtain disease details and crack data of architectural heritage, using a Mask R-CNN model to detect crack area, using an FCN model to identify and calculate single cracks, and finally summarizing the type, location, and characteristics of cracks, analyzing the causes of cracks, and then putting forward corresponding hierarchical restoration strategies. The research results build a set of detection and repair systems of masonry–timber architectural heritage pathology cracks, which provide a set of accurate and objective pathology cracks data for architectural heritage protection and repair, and provide a reference for architectural heritage repair.
Evaluation of Aggregate Distribution Heterogeneity in 3D Printed Concrete by Means of X-ray CT
Authors: Yoshihara Rei , Nakase Kota , Hashimoto Katsufumi , Sugiyama Takafumi , Honda Yoshiki
Published: April 2024

The mechanical performance of a printed object in 3D concrete printing is influenced by the interfacial bonding strength between the deposited filaments. Hence, the physical properties of the layer interface and the influential factors have been studied. This study aims to clarify the mechanism of aggregate distribution heterogeneity as well as the influence of printing material extrusion speed on the heterogeneity inside the filament. A laboratory-scale material extruder is developed and used in this study. The aggregate distribution is evaluated in a quantitative manner with the cross-sectional image obtained by X-ray computed tomography. The images were taken in the deposited filament and the material extrusion nozzle for printing. Results show that large aggregate moves from the outside of the printing nozzle toward the center with increasing extrusion speed from 1.8 to 7.1 mm/s. As extrusion speed increases, it is inferred that a lubrication layer forms on the inner surface of the nozzle, causing the transition of material extrusion behavior from laminate flow to plug flow. Thus, the aggregate distribution appears differently inside the filament. This finding indicates that the magnitude of friction against the nozzle wall alters the die swell during discharge as well as the aggregate distribution before and after extrusion.
Numerical Investigation of Large-Diameter Bored Piles under High-Strain Dynamic Testing: A Case Study in New Alamein City
Authors: Salem Tarek N. , El-Saei Ahmed S. , Krajníková Katarína , Katunský Dušan , Hassan Rana
Published: April 2024

Large-diameter bored piles can safely transmit loads from structures by skin friction to the surrounding soil strata and end bearing at the bedrock layer, thereby providing a high compressive capacity. High-Strain Dynamic Testing (HSDT) provides a unique alternative technique to traditional Static Load Testing (SLT) for determining the static compressive resistance of the bored piles, considering its quicker performance and significant cost reductions. This article’s main objective is to numerically explore the performance of large-diameter bored piles during the HSDT and to understand their dynamic behavior under an axial compressive impact force. This research is based on testing pile foundations for reinforced concrete mixed-use towers in the coastal zone of New Alamein City, Egypt. The tested pile is a 1.20 m diameter bored pile. Numerical modeling is performed to simulate both the HSDT and the SLT for two piles at the same site. Non-linear axisymmetric finite element modeling is employed to validate both test records and develop some sort of matching between the two tests. As lumped models, the developed numerical models use the signal-matching process, which is conducted by varying and adopting the strength parameters and deformation characteristics of the ground or soil deposit and the soil–pile interface. The predicted load-displacement curves, developed from analyzing dynamic records employing the Modified Unloading Point (MUP) method, are consistent with the field records. The verified non-linear models are utilized to accomplish a comparative parametric analysis to better understand the drop-mass system aspects. The analysis results emphasize the significance of employing adequate impact energy (i.e., dropping height and mass) to move the pile top to a sufficient extent to mobilize its full resistance. However, a longer impact duration, i.e., larger mass, is more effective for achieving a deeper high-strain wave. The impact load should be developed by a larger drop mass with a lower drop height, not a smaller drop mass with a higher drop height. The results also indicate that, for relatively longer piles, the skin friction of the upper layers surrounding the pile shaft is fully mobilized, whereas the skin resistance of the lower layers is not fully mobilized, regarding the stress wave phenomenon effect. Finally, this study’s findings can be employed to develop guidelines and design procedures for the HSDT to be effectively performed on bored piles.
An Overview of Environmental Catalysis Mediated by Hydrogen Peroxide
Authors: Rigoletto Monica , Laurenti Enzo , Tummino Maria Laura
Published: April 2024

The use of hydrogen peroxide (produced in situ or ex situ) as the main agent in oxidative processes of environmental pollutant removal is widely studied. The degradation of water pollutants, such as dyes, pharmaceuticals, cosmetics, petroleum derivatives, and even pathogens, has been successfully obtained by different techniques. This review gives an overview of the more recent methods developed to apply oxidative processes mediated by H2O2 and other reactive oxygen species (ROS) in environmental catalysis, with particular attention to the strategies (Fenton-like and Bio-Fenton, photo- and electro-catalysis) and the materials employed. A wide discussion about the characteristics of the materials specifically studied for hydrogen peroxide activation, as well as about their chemical composition and morphology, was carried out. Moreover, recent interesting methods for the generation and use of hydrogen peroxide by enzymes were also presented and their efficiency and applicability compared with the Fenton and electro-Fenton methods discussed above. The use of Bio-Fenton and bi-enzymatic methods for the in situ generation of ROS seems to be attractive and scalable, although not yet applied in full-scale plants. A critical discussion about the feasibility, criticalities, and perspectives of all the methods considered completes this review.
Investigating the Long-Term Kinetics of Pd Nanoparticles Prepared from Microemulsions and the Lindlar Catalyst for Selective Hydrogenation of 3-Hexyn-1-ol
Authors: Tari Faeze , Hertle Sebastian , Wang Hongguang , Fischer Julian , van Aken Peter A. , Sottmann Thomas , Klemm Elias , Traa Yvonne
Published: April 2024

The effect of non-saturated corner and edge sites of Pd particles on the long-term selectivity of cis-3-hexen-1-ol in the hydrogenation of 3-hexyn-1-ol was studied in this work. Non-supported Pd agglomerates were synthesized through the microemulsion synthesis route and used at nalkynol/APd ratios between 0.08 and 21 mol/m2 for the catalytic conversion of 3-hexyn-1-ol for 20 h. The selectivity of the cis-hexenol product increased by reducing the quantity of Pd catalytic sites (increasing the nalkynol/APd ratio) without introducing any modifier or doping agent to poison the nonselective sites. Then, Pd aggregates with fused primary particles and, thus, fewer corner and edge sites were produced through thermal sintering of the agglomerates at 473–723 K. By comparing the catalytic performance of the agglomerates and aggregates, it was observed that at a rather similar kinetic behavior (99.99% conversion and 85–89% selectivity to cis-hexenol), the sintered aggregates could stay selective despite a catalytic surface area about seven times larger. This emphasizes the role of low-coordinated edge and corner sites on the final selectivity of the cis product and demonstrates that thermal sintering allows the number of non-selective sites to be reduced without any need for toxic or organic doping agents or modifiers.
Exploring Anti-Fibrotic Effects of Adipose-Derived Stem Cells: Transcriptome Analysis upon Fibrotic, Inflammatory, and Hypoxic Conditioning
Authors: Frommer Marvin L. , Langridge Benjamin J. , Beedie Alexandra , Jasionowska Sara , Awad Laura , Denton Christopher P. , Abraham David J. , Abu-Hanna Jeries , Butler Peter E. M.
Published: April 2024

Autologous fat transfers show promise in treating fibrotic skin diseases, reversing scarring and stiffness, and improving quality of life. Adipose-derived stem cells (ADSCs) within these grafts are believed to be crucial for this effect, particularly their secreted factors, though the specific mechanisms remain unclear. This study investigates transcriptomic changes in ADSCs after in vitro fibrotic, inflammatory, and hypoxic conditioning. High-throughput gene expression assays were conducted on ADSCs exposed to IL1-β, TGF-β1, and hypoxia and in media with fetal bovine serum (FBS). Flow cytometry characterized the ADSCs. RNA-Seq analysis revealed distinct gene expression patterns between the conditions. FBS upregulated pathways were related to the cell cycle, replication, wound healing, and ossification. IL1-β induced immunomodulatory pathways, including granulocyte chemotaxis and cytokine production. TGF-β1 treatment upregulated wound healing and muscle tissue development pathways. Hypoxia led to the downregulation of mitochondria and cellular activity.
A Novel Interaction of Slug (SNAI2) and Nuclear Actin
Authors: Zhuo Ling , Stöckl Jan B. , Fröhlich Thomas , Moser Simone , Vollmar Angelika M. , Zahler Stefan
Published: April 2024

Actin is a protein of central importance to many cellular functions. Its localization and activity are regulated by interactions with a high number of actin-binding proteins. In a yeast two-hybrid (Y2H) screening system, snail family transcriptional repressor 2 (SNAI2 or slug) was identified as a yet unknown potential actin-binding protein. We validated this interaction using immunoprecipitation and analyzed the functional relation between slug and actin. Since both proteins have been reported to be involved in DNA double-strand break (DSB) repair, we focused on their interaction during this process after treatment with doxorubicin or UV irradiation. Confocal microscopy elicits that the overexpression of actin fused to an NLS stabilizes complexes of slug and γH2AX, an early marker of DNA damage repair.
Study of the Gas Sensing Performance of Ni-Doped Perovskite-Structured LaFeO3 Nanospheres
Authors: Meng Fanli , Yu Zhenhua , Zhang Renze , Gao Hongliang , Yuan Zhenyu
Published: April 2024

This study synthesizes Ni-doped perovskite-structured LaFeO3 composite materials via a one-step hydrothermal method, characterizes the morphology and structure of the materials, and tests their gas sensing performance. The test results show that compared to pure LaFeO3 material, the gas sensing performance of Ni-doped LaFeO3 material is improved in all aspects. Specifically, LFO-Ni2% exhibits a response as high as 102 towards 100 ppm of triethylamine at 190 °C, along with better selectivity and stability. Furthermore, the gas sensing mechanism is investigated. On one hand, doping with an appropriate proportion of Ni can lead to the formation of more-complete and smaller-sized microsphere structures with pores. This is beneficial for the adsorption of oxygen from the air onto the material surface, as well as for the diffusion of the target gas to the surface of the material, thereby enhancing gas sensitivity performance. On the other hand, the doped Ni enters the interior of the LaFeO3 crystal, replacing some of the cations in LaFeO3, increasing the concentration of charge carriers in the material, and reducing the material’s resistance. The sample can adsorb more oxygen, promoting the reaction between adsorbed oxygen and the target gas, and thereby improving the gas sensitivity performance of the sample.
MicroRNAs in the Pathogenesis of Preeclampsia—A Case-Control In Silico Analysis
Authors: Kasimanickam Ramanathan , Kasimanickam Vanmathy
Published: April 2024

Preeclampsia (PE) occurs in 5% to 7% of all pregnancies, and the PE that results from abnormal placentation acts as a primary cause of maternal and neonatal morbidity and mortality. The objective of this secondary analysis was to elucidate the pathogenesis of PE by probing protein–protein interactions from in silico analysis of transcriptomes between PE and normal placenta from Gene Expression Omnibus (GSE149812). The pathogenesis of PE is apparently determined by associations of miRNA molecules and their target genes and the degree of changes in their expressions with irregularities in the functions of hemostasis, vascular systems, and inflammatory processes at the fetal–maternal interface. These irregularities ultimately lead to impaired placental growth and hypoxic injuries, generally manifesting as placental insufficiency. These differentially expressed miRNAs or genes in placental tissue and/or in blood can serve as novel diagnostic and therapeutic biomarkers.