bluuebunny/crossref_metadata_2025 huggingface dataset:
Genetic study of Camelina sativa oilseed crop and selection of a new variety by the bulk method
Authors: Ghidoli Martina , Geuna Filippo , De Benedetti Stefano , Frazzini Sara , Landoni Michela , Cassani Elena , Scarafoni Alessio , Rossi Luciana , Pilu Salvatore Roberto
Published: May 2024

Camelina sativa, commonly referred to as camelina or false flax, has emerged as a promising cover crop with the potential to mitigate climate change—a pressing global challenge that demands urgent and sustainable solutions. Belonging to the Brassicaceae family and native to Europe and Central Asia, camelina is an oilseed crop known for its resilience in diverse climates, including arid and semi-arid regions, making it adaptable to various environments. A breeding program started from a study of six winter varieties and five spring varieties of camelina is described: these genetic materials were characterized by SSRs molecular markers and by GBS technique. Molecular data clearly showed all spring varieties were genetically similar and distinguishable from the winter varieties, which, in turn, clustered together. Using molecular data, parental varieties belonging to the two different clusters were selected to generate new genetic variability. The new variety obtained, selected through the bulk method based on three parameters: yield, earliness, and weight of 1000 seeds, has allowed the generation of the new genetic material provisionally named C1244. Chemical characterization was performed (bromatological and glucosinolates analysis) to better describe C1244 in comparison with benchmark varieties. The new variety exhibited early maturity, similar to spring varieties, making this genetic material promising for use in intercropping systems, a high weight of 1000 seeds (1.46 g) which improves and facilitates seeding/harvesting operations and a high oil content (33.62%) akin to winter varieties making it valuable for human and animal food purposes.
Genome-wide association study and genomic selection of flax powdery mildew in Xinjiang Province
Authors: Zhu Leilei , Li Gongze , Guo Dongliang , Li Xiao , Xue Min , Jiang Haixia , Yan Qingcheng , Xie Fang , Ning Xuefei , Xie Liqiong
Published: May 2024

Flax powdery mildew (PM), caused by Oidium lini, is a globally distributed fungal disease of flax, and seriously impairs its yield and quality. To data, only three resistance genes and a few putative quantitative trait loci (QTL) have been reported for flax PM resistance. To dissect the resistance mechanism against PM and identify resistant genetic regions, based on four years of phenotypic datasets (2017, 2019 to 2021), a genome-wide association study (GWAS) was performed on 200 flax core accessions using 674,074 SNPs and 7 models. A total of 434 unique quantitative trait nucleotides (QTNs) associated with 331 QTL were detected. Sixty-four loci shared in at least two datasets were found to be significant in haplotype analyses, and 20 of these sites were shared by multiple models. Simultaneously, a large-effect locus (qDI 11.2) was detected repeatedly, which was present in the mapping study of flax pasmo resistance loci. Oil flax had more QTL with positive-effect or favorable alleles (PQTL) and showed higher PM resistance than fiber flax, indicating that effects of these QTL were mainly additive. Furthermore, an excellent resistant variety C120 was identified and can be used to promote planting. Based on 331 QTLs identified through GWAS and the statistical model GBLUP, a genomic selection (GS) model related to flax PM resistance was constructed, and the prediction accuracy rate was 0.96. Our results provide valuable insights into the genetic basis of resistance and contribute to the advancement of breeding programs.
The dark side of personality functioning: associations between antisocial cognitions, personality functioning (AMPD), empathy and mentalisation
Authors: Rabl Luna , Maerz Jeff , Viviani Roberto , Labek Karin
Published: May 2024

Introduction

With the introduction of the new psychiatric diagnostic manuals, personality functioning has gained new prominence. Several studies have reported consistent findings that individual showing high levels of antisocial features are associated with alterations in interpersonal functioning domains such as empathy and mentalisation. The focus of the current study (N = 198) is to examine antisocial cognitions, as measured by the Scrambled Sentences Task (SST), and to what extent this approach can help to better understand the relationship between antisocial traits and personality functioning/empathy.

Method

We implemented a hypothesis-driven approach using logistic regression and a data-driven approach using machine learning to examine distinct but related measures of personality functioning as predictors of antisocial cognitions.

Results

Antisocial cognitions were associated with low interpersonal functioning as expected, but only when not adjusting for antisocial traits, which accounted for almost all the association. The data-driven analysis revealed that individual items assessing empathic concern in personality functioning scales (as opposed to the whole scores) explained low antisocial cognitions even when adjusting for antisocial traits.

Discussion

Antisocial cognitions appear to be associated to two distinct traits, the antisocial and a specific type of personality functioning. This finding is discussed in terms of the possible distinction between two motivational forces: to harm others/prioritize one’s advantage, and to help suffering others.
Protection motivation theory in predicting intentional behaviors regards schistosomiasis: a WeChat-based qualitative study
Authors: Wang Yi , Li Chengyuan , Zhang Jianfeng , Mao Yuanchun , Li Wei
Published: May 2024

Background

Modifications of behavior can help reduce the risk of transmission by disrupting the parasite life cycle. Behavior intension is a necessary intermediate step in behavior change. This study aimed to explore protection motivation theory (PMT) in predicting likelihood of engagement in protective behavior against infection with Schistosoma.

Methods

In China, a questionnaire for data collection was sent to users who followed the WeChat public account from June 2 to 6, 2023. Factors affecting intentional behavior of participants were analyzed using stepwise regression analysis and structural equation modeling.

Results

A total of 2,243 valid questionnaires were collected, with a mean age of 30 ± 8.4 years. Approximately 1,395 (62.2%) participants reported that they had been exposed to wild waters in daily work and life. About 51.0 and 50.7% of respondents reported never having been exposed to wild water in the last 3 and 6 months, respectively. Results indicated that prior knowledge of schistosomiasis was associated with the 7 PMT subconstructs, which then influenced future preventative behaviors.

Conclusion

Behavior intentionis a complicated and indispensable part of behavior change that is influenced by professional knowledge, socio-economic status, and personal characteristics. The effective dissemination of knowledge regards schistosomiasis should be strengthened to emphasize the effectiveness of protective measures against infection and severe disease.
Comparative analysis of machine learning versus traditional method for early detection of parental depression symptoms in the NICU
Authors: Sadjadpour Fatima , Hosseinichimeh Niyousha , Abedi Vida , Soghier Lamia M.
Published: May 2024

Introduction

Neonatal intensive care unit (NICU) admission is a stressful experience for parents. NICU parents are twice at risk of depression symptoms compared to the general birthing population. Parental mental health problems have harmful long-term effects on both parents and infants. Timely screening and treatment can reduce these negative consequences.

Objective

Our objective is to compare the performance of the traditional logistic regression with other machine learning (ML) models in identifying parents who are more likely to have depression symptoms to prioritize screening of at-risk parents. We used data obtained from parents of infants discharged from the NICU at Children’s National Hospital (n = 300) from 2016 to 2017. This dataset includes a comprehensive list of demographic characteristics, depression and stress symptoms, social support, and parent/infant factors.

Study design

Our study design optimized eight ML algorithms – Logistic Regression, Support Vector Machine, Decision Tree, Random Forest, XGBoost, Naïve Bayes, K-Nearest Neighbor, and Artificial Neural Network – to identify the main risk factors associated with parental depression. We compared models based on the area under the receiver operating characteristic curve (AUC), positive predicted value (PPV), sensitivity, and F-score.

Results

The results showed that all eight models achieved an AUC above 0.8, suggesting that the logistic regression-based model’s performance is comparable to other common ML models.

Conclusion

Logistic regression is effective in identifying parents at risk of depression for targeted screening with a performance comparable to common ML-based models.
Associations between peak expiratory flow and frailty in olderly individuals: findings from the China health and retirement longitudinal study
Authors: Wang Rui , Shi Wen , Zhou Wenlu , Xu Yawen , Wang Junjie
Published: May 2024

Purpose

Peak Expiratory Flow (PEF) is associated with a variety of adverse health outcomes in older adults; however, the relationship between PEF and frailty remains uncertain, and this study investigated the relationship between PEF and frailty within an olderly Asian demographic.

Methods

Data were sourced from the Chinese Health and Retirement Longitudinal Study (CHARLS). Individuals in the study, all 60 years or older, underwent baseline PEF assessments quantified as standardized residual (SR) percentile values. The evaluation of frailty was conducted based on the criteria established by Fried. Participants without frailty at the outset were tracked over a four-year period, during which the relationships between PEF and frailty were examined through logistic regression and discrete-time Cox regression analyses.

Results

Among 5,060 participants, cross-sectional analysis revealed that the prevalence of frailty was 2–3 times higher in the lower 10–49th and < 10th SR percentile groups compared to the 80–100th SR percentile group. The longitudinal study corroborated these results, showing an adjusted hazard ratio (HR) of 2.01 (95% CI, 1.15–3.51) for PEF SR percentiles below the 10th, in contrast to those between the 80th and 100th percentiles.

Conclusion

PEF independently predicts and determines frailty in older adults. Declines in PEF greater than expected are associated with the development of frailty. Subsequent studies are encouraged to delve deeper into the connection between respiratory function and frailty in diverse contexts.
Targeted dream incubation at a distance: the development of a remote and sensor-free tool for incubating hypnagogic dreams and mind-wandering
Authors: Bellaiche Lucas , Haar Horowitz Adam , McClay Mason , Bottary Ryan , Denis Dan , Chen Christina , Maes Pattie , Seli Paul
Published: May 2024

Hypnagogia—the transitional state between wakefulness and sleep—is marked by “hypnagogic dreams,” during which our brains tend to forge connections among concepts that are otherwise unrelated. This process of creating novel associations during hypnagogic dreams is said to contribute to enhancing creativity, learning, and memory. Recently, researchers have proposed that mind-wandering—a form of spontaneous thought that is freely moving and characterized by transitioning thought content—might be subserved by processes similar to those engaged during hypnagogia, and may serve similar creative functions. However, to date, the relationship between hypnagogia and mind-wandering remains poorly understood, which is likely due in part to the fact that research into hypnagogia requires time-consuming, cumbersome, and costly polysomnography. In light of this, the present study had two primary aims: first, to test a novel tool—called Dormio Light—for cueing and indexing hypnagogic dream content in a cost- and time-effective manner, with the ability for remote administration; second, to use this tool to examine any relations between hypnagogic dreams and mind-wandering (defined as “freely moving thought”). Participants (N = 80, with 34 females) completed a task in which our tool prompted them to engage in hypnagogia and, separately, mind-wandering, with instructions to think about a common everyday object (Tree or Fork) while experiencing these cognitive states. Following each state, participants reported thought content and completed phenomenological questionnaires. Providing an initial validation of our tool, we successfully cued hypnagogic and mind-wandering thought content that was specific to our cues (e.g., Tree), with our incubation-rate results comparable to those found in laboratory-based studies. Further, we found evidence for some phenomenological differences between hypnagogia and mind-wandering reports. Our study offers a novel, cost- and time-effective tool with which to remotely cue and index hypnagogia and mind-wandering, and sheds light on the relationship between hypnagogia and mind-wandering, thereby providing future directions for research into these two cognitive states.
Investigation of compound occurrence of storm surge and river flood in Mikawa Bay, Japan, using typhoon track ensemble experiments
Authors: Haruyama Kazuki , Toyoda Masaya , Kato Shigeru , Mori Nobuhito , Kim Sooyoul , Yoshino Jun
Published: May 2024

The risk of high river flow and peak storm surge superimposing in the estuary of small-and medium-sized rivers can be more severe during typhoon landfalls than at other times. In this study, 30 cases of typhoon track ensemble experiments for five rivers in Mikawa Bay, Japan, were evaluated using an atmospheric-river-ocean model. The results showed that storm surges coincided with high river flows when typhoons crossed the western side of Mikawa Bay, with the highest potential observed when typhoons passed northwest of the Bay. The average time discrepancy for the five rivers between the storm surge occurrence and increased river flow in the minimum time difference case was 48 min at the river mouth. Distinct trends in the time difference between a storm surge and river flow were observed for each river mouth. The order of time differences corresponded to the drainage area scale: Toyo (188 min), Umeda (112 min), Otowa (114 min), Sana (96 min), and Yagyu (88 min). Time difference trends also varied based on the distance between the typhoon center and each river mouth. For Toyo River, storm surges and high river flows did not substantially overlap, regardless of distance. However, for medium-and small-sized rivers, the time difference increased proportionally with the distance from the typhoon. The Yagyu River showed the highest potential for compound occurrence of a storm surge and river flood because of the synchronization of storm surge peaks and high river flow peaks, with a time difference of 1–2 h for small-and medium-sized rivers within 100 km2 of the basin.
Reliability-Based Topology Optimization with a Proportional Topology for Reliability
Authors: Kumkam Noppawit , Sleesongsom Suwin
Published: May 2024

This research proposes an efficient technique for reliability-based topology optimization (RBTO), which deals with uncertainty and employs proportional topology optimization (PTO) to achieve the optimal reliability structure. The recent technique, called proportional topology optimization for reliability (PTOr), uses Latin hypercube sampling (LHS) for uncertainty quantification. The difficulty of the double-loop nested problem in uncertainty quantification (UQ) with LHS can be alleviated by the power of PTO, enabling RBTO to be performed easily. The rigorous advantage of PTOr is its ability to accomplish topology optimization (TO) without gradient information, making it faster than TO with evolutionary algorithms. Particularly, for reliability-based topology design, evolutionary techniques often fail to achieve satisfactory results compared to gradient-based techniques. Unlike recent PTOr advancement, which enhances the RBTO performance, this achievement was previously unattainable. Test problems, including an aircraft pylon, reveal its performances. Furthermore, the proposed efficient framework facilitates easy integration with other uncertainty quantification techniques, increasing its performance in uncertainty quantification. Lastly, this research provides computer programs for the newcomer studying cutting-edge knowledge in engineering design, including UQ, TO, and RBTO, in a simple manner.
Smart Contracts as a Tool to Support the Challenges of Buying and Selling Coffee Futures Contracts in Colombia
Authors: Ordoñez Cristian Camilo , Organero Mario Muñoz , Ramirez-Gonzalez Gustavo , Corrales Juan Carlos
Published: May 2024

In Colombia, coffee futures contracts represent essential financial agreements that allow producers and buyers to establish prices, quality, and conditions for future transactions in the coffee market. Despite the evident benefits of stability and predictability, this practice faces significant sustainability challenges that threaten its long-term viability. One of the reasons is the significant lack of transparency in the supply chain. Farmers, affected by abrupt price fluctuations and adverse weather conditions such as the El Niño phenomenon, experience an increase in market prices, leading to the non-delivery of the final product, and contract breaches as they find better prices in the local market. In this context, smart contracts emerge as a promising technological solution to address these problems. These contracts enable the verification of each step in the process, from harvest to final sale, within a blockchain. Therefore, this research designs a smart contract managed through a platform called SmartBeanFutures, which records the clauses of futures contracts using the IERC721 framework, allowing the generation of a unique and non-repeatable asset. It aims to sell, promote, and manage coffee sale prices during the agreement’s signing, creating a transparent environment for chain actors. This proposal undergoes evaluation in a test environment, providing farmers access to the designed platform. Following the validation of the proposal, it was identified that over 74% would use this type of contract in their agricultural processes, highlighting that implementing this technology contributes to eliminating intermediaries in the chain and gives farmers more control over their participation in the market.
Combination of Chromatographic Analysis and Chemometric Methods with Bioactivity Evaluation of the Antibacterial Properties of Helichrysum italicum Essential Oil
Authors: Zeremski Tijana , Šovljanski Olja , Vukić Vladimir , Lončar Biljana , Rat Milica , Perković Vukčević Nataša , Aćimović Milica , Pezo Lato
Published: May 2024

Helichrysum italicum (immortelle) essential oil is one of the most popular essential oils worldwide and it has many beneficial properties, including antimicrobial. However, in this plant, the chemical diversity of the essential oil is very pronounced. The aim of this work was to process the GC-MS results of four samples of H. italicum essential oil of Serbian origin by chemometric tools, and evaluate the antimicrobial activity in vitro and in silico. Overall, 47 compounds were identified, the most abundant were γ-curcumene, α-pinene, and ar-curcumene, followed by α-ylangene, neryl acetate, trans-caryophyllene, italicene, α-selinene, limonene, and italidiones. Although the four samples of H. italicum essential oil used in this study were obtained from different producers in Serbia, they belong to the type of essential oil rich in sesquiterpenes (γ-curcumene and ar-curcumene chemotype). In vitro antimicrobial potential showed that five were sensitive among ten strains of tested microorganisms: Staphylococcus aureus, Listeria monocytogenes, Bacillus cereus, Saccharomyces cerevisiae, and Candida albicans. Therefore, these microorganism models were used further for in silico molecular docking through the mechanism of ATP-ase inhibitory activity. Results showed that among all compounds from H. italicum essential oil, neryl acetate has the highest predicted binding energy. Artificial neural network modeling (ANN) showed that two major compounds γ-curcumene and α-pinene, as well as minor compounds such as trans-β-ocimene, terpinolene, terpinene-4-ol, isoitalicene, italicene, cis-α-bergamotene, trans-α-bergamotene, italidiones, trans-β-farnesene, γ-selinene, β-selinene, α-selinene, and guaiol are responsible for the antimicrobial activity of H. italicum essential oil. The results of this study indicate that H. italicum essential oil samples rich in γ-curcumene, α-pinene, and ar-curcumene cultivated in Serbia (Balkan) have antimicrobial potential both in vitro and in silico. In addition, according to ANN modeling, the proportion of neryl acetate and other compounds detected in these samples has the potential to exhibit antimicrobial activity.
Antimicrobial Susceptibility of Canine and Feline Urinary Tract Infection Pathogens Isolated from Animals with Clinical Signs in European Veterinary Practices during the Period 2013–2018
Authors: Temmerman Robin , Berlamont Helena , El Garch Farid , Rose Markus , Simjee Shabbir , Meschi Sylvie , de Jong Anno
Published: May 2024

Bacterial urinary tract infections (UTIs) occur frequently in companion animals and are often treated with antibiotics. However, antimicrobial resistance can severely hamper treatment success. Therefore, antimicrobial susceptibility monitoring is key. UTI isolates were obtained from dogs and cats in two collection periods (ComPath II: 2013–2014 and ComPath III: 2017–2018) as part of CEESA’s ComPath programme. Susceptibility testing of the UTI isolates (2021 in total) was carried out at one central laboratory using agar and broth dilution methodology as recommended by the Clinical and Laboratory Standards Institute. Escherichia coli was the most frequently isolated bacterium in UTI in both dogs (46.9%, 43.1%) and cats (61.2%, 48.3%) across ComPath II and ComPath III, respectively. The percentage of resistance in E. coli was low (<10%) across both programmes in both dogs and cats except for trimethoprim-sulfamethoxazole (dogs ComPath III: 12.9%; cats ComPath II: 13.0%) and enrofloxacin (10.5%), marbofloxacin (11.4%), and doxycycline (98.8%) for dogs in ComPath III. Three (7.5%) of the 40 isolated S. aureus bacteria in total were MRSA and harboured mecA. The level of multidrug resistance (MDR) was generally low and ranged from 0.0% for feline coagulase-negative Staphylococcus spp. to 11.7% for canine Proteus spp., except for a peak of MDR observed in canine Klebsiella isolates from ComPath II (36.7%). Overall, antimicrobial resistance for most canine and feline UTI pathogens isolated during the ComPath II and ComPath III programmes was low (1–10%) to moderate (10–20%).
RND Efflux Pump Induction: A Crucial Network Unveiling Adaptive Antibiotic Resistance Mechanisms of Gram-Negative Bacteria
Authors: Novelli Marine , Bolla Jean-Michel
Published: May 2024

The rise of multi-drug-resistant (MDR) pathogenic bacteria presents a grave challenge to global public health, with antimicrobial resistance ranking as the third leading cause of mortality worldwide. Understanding the mechanisms underlying antibiotic resistance is crucial for developing effective treatments. Efflux pumps, particularly those of the resistance-nodulation-cell division (RND) superfamily, play a significant role in expelling molecules from bacterial cells, contributing to the emergence of multi-drug resistance. These are transmembrane transporters naturally produced by Gram-negative bacteria. This review provides comprehensive insights into the modulation of RND efflux pump expression in bacterial pathogens by numerous and common molecules (bile, biocides, pharmaceuticals, additives, plant extracts, etc.). The interplay between these molecules and efflux pump regulators underscores the complexity of antibiotic resistance mechanisms. The clinical implications of efflux pump induction by non-antibiotic compounds highlight the challenges posed to public health and the urgent need for further investigation. By addressing antibiotic resistance from multiple angles, we can mitigate its impact and preserve the efficacy of antimicrobial therapies.
Investigation of Frequency-Dependent Characteristics of Wire Rope under Tension Based on Transfer Function Method
Authors: Jeong Kwanghun , Kim Narae , Jeon Nahyun , Kim Haksung , Park Junhong
Published: May 2024

Wire rope is a complex structure made by twisting wires of various sizes in the longitudinal direction. It is used to support or move engineering structures and is subject to various tensions. Dynamic properties are important parameters to evaluate the resistance to bending deformation and vibration reduction of various structures. They are affected by the magnitude of tension. In this study, an experimental method for measuring the frequency-dependent characteristics of wire rope under tension is proposed. The study analyzed flexural wave propagation employing a vibration transfer function. Experimental results showed that the transfer function of wire rope under tension is affected by tension and bending stiffness. The Newton–Raphson method was employed to numerically measure wavenumbers of the wire rope. The bending stiffness and loss factor were determined from the wavenumbers. Changes in the bending stiffness and loss factor as the tension increased were explained by the dynamic behavior of the structure under tension. As the tension increased, the bending stiffness increased, and the loss factor decreased. Hysteresis analysis indicated that the energy dissipation of wire rope is greater than that of a steel beam due to the friction between the wires. Statistical analysis confirmed a significant correlation between dynamic characteristics and tension in wire rope.
Development of an ICT Laparoscopy System with Motion-Tracking Technology for Solo Laparoscopic Surgery: A Feasibility Study
Authors: Lee Miso , Oh Jinwoo , Kang Taegeon , Lim Suhyun , Jo Munhwan , Jeon Min-Jae , Lee Hoyul , Hwang Inhwan , Kang Shinwon , Moon Jin-Hee , Min Jae-Seok
Published: May 2024

The increasing demand for laparoscopic surgery due to its cosmetic benefits and rapid post-surgery recovery is juxtaposed with a shortage of surgical support staff. This juxtaposition highlights the necessity for improved camera management in laparoscopic procedures, encompassing positioning, zooming, and focusing. Our feasibility study introduces the information and communications technology (ICT) laparoscopy system designed to aid solo laparoscopic surgery. This system tracks a surgeon’s body motion using a controller, manipulating an embedded camera to focus on specific surgical areas. It comprises a camera module, a camera movement controller, and a motor within the main body, operating connected wires according to controller commands for camera movement. Surgeon movements are detected by an inertial measurement unit (IMU) sensor, facilitating precise camera control. Additional features include a foot pedal switch for motion tracking, a dedicated trocar for main body stability, and a display module. The system’s effectiveness was evaluated using an abdomen phantom model and animal experimentation with a porcine model. The camera responded to human movement within 100 ms, a delay that does not significantly affect procedural performance. The ICT laparoscopy system with advanced motion-tracking technology is a promising tool for solo laparoscopic surgery, potentially improving surgical outcomes and overcoming staff shortages.
Three-Dimensional Reconstruction of the Early Christian Temples of the Roman Fortress of Pitiunt
Authors: Glazov Konstantin , Trebeleva Galina , Abornev Ivan , Sakania Suram , Yurkov Vladlen , Yurkov Gleb
Published: May 2024

Since 2018, the authors have been working on reconstructing the exterior of the Great Pitiunt Roman fortress in 3D. This article presents the results of the visualization of the exterior and interior of the temple complex. During the study, the dimensions and plans of the site were analyzed, revealing discrepancies in various sources. To clarify the complex’s dimensions, aerial photography using UAV was conducted, and photogrammetric models, orthophoto, and digital surface models were created. The research also uncovered previously unrecorded architectural features. During the reconstruction of the temples, much attention was paid to the structural design of the buildings, connections and load distribution. Engineering calculations have been carried out for the clarification of the structural solutions. The article presents the results of a detailed reconstruction of the exterior, interior and structural features of Temple Nos. 1–4, based on preserved archaeological evidence, excavation results, contemporaneous Early Christian sites, and an analysis of the materials and technologies used at the time. The reconstruction of the mosaic floor of Temple No. 2 allowed a realistic visualization of the interior.
Constitutive Characteristics of Rock Damage under Freeze–Thaw Cycles
Authors: Li Yaoxin , Wang Zhibin , Cao Haiqing , Wu Tingyao
Published: May 2024

Freeze–thaw effect is one of the most important environmental conditions that rocks may be subjected to. Through laboratory model tests, the damage characteristics of rocks under the FTC were studied. Based on assuming that the strength of rocks subject to the FTC follows the Weibull distribution, the cumulative damage variable of the number of FTCs was introduced. A cumulative damage constitutive model of shear strength attenuation of rock that meets the Mohr–Coulomb criterion is established. The rationality and applicability of the proposed damage constitutive model are verified by comparing the results of rock shear strength parameters under cyclic freeze–thaw loads.
RETRACTED: Zhong et al. Fractal Behavior of Particle Size Distribution in the Rare Earth Tailings Crushing Process under High Stress Condition. Appl. Sci. 2018, 8, 1058
Authors: Zhong Wen , Yue Fucai , Ciancio Armando
Published: May 2024

The Applied Sciences Editorial office retracts the article “Fractal Behavior of Particle Size Distribution in the Rare Earth Tailings Crushing Process under High Stress Condition” [...]
Influence of Rock Slide Geometry on Stability Behavior during Reservoir Impounding
Authors: Zangerl Christian , Lechner Heidrun , Strauss Alfred
Published: May 2024

Assessing the stability behavior of deep-seated rock slides in the surroundings of large dam reservoirs requires an understanding of the geometry, the kinematics, the groundwater situation, and the rock mass and shear zone properties. This study focuses on the influence of rock slide geometry on stability evolution during initial reservoir impounding. Therefore, nine different rock slide models, mainly taken from published case studies with a well-explored geometry, were analyzed. Based on the assumption that the rock slides are close to limit equilibrium in a no-reservoir scenario, reservoir impounding causes a reduction in the factor of safety (FoS). The results show a large impact of the water level for rotational slides where the majority of the rock mass is located at the lower part of the slope. This results in a maximum reduction in the FoS of up to 12%. In contrast to this, translational rock slides are less affected by reservoir impounding. The stability analysis shows that the change in FoS is strongly controlled by the kinematics of the rock slide and the geometry near the foot of the slope. Consequently, a comprehensive in situ investigation of the geometry and kinematics is necessary in order to reliably assess the influence of initial reservoir impounding.
Novel Aluminum Alloy Tailored for Additive Manufacturing: Structural Characterization and Qualification Perspectives
Authors: Arena Maurizio , Mehta Bharat , Tirelli Tommaso , Ambrogiani Paolo , Castaldo Martina , Bengtsson Sven , Nyborg Lars
Published: May 2024

The recent advances achieved in additive manufacturing (AM) technology demonstrate the potential to realize customized metal components, ensuring weight reduction opportunities. These benefits make AM attractive for high-cost aerospace applications, especially where high geometric complexity is required. In the context of an EU research scenario, the H2020 MANUELA (Additive Manufacturing Using Metal Pilot Line) project promotes the development of new technologies for design optimization by enabling the application of novel materials in AM. This paper illustrates recent advances in a new aluminum alloy (Al-HS1) with high strength emphasizing all of the characterization steps at the coupon level. This material has been employed in the re-engineering of a conventional hydraulic manifold using a powder bed fusion-laser beam (PBF-LB) process. Both the simulations and structural tests allowed for proving its compliance and technological maturity with industrial standards and applicable airworthiness requirements.
Agroecological Transformation: Implementation of an Agroforestry System in a Construction Debris Area Focusing on Vegetables Development through Microbial Treatments
Authors: Rodrigues Thiago Fernandes , Itkes Marina Paes Machado , Brogiato Giovanne , Marques Victor Augusto Reis , Martins Valdir , Villarraga Carlos Orlando , Esposito Elisa
Published: May 2024

Soil microorganisms play an important role on plant development and the homogenization of soil microbiomes is harmful to agri-environments. It is essential that agricultural practices are carried out by taking soil microbiome preservation in consideration. Agroforestry systems are one of the most environmentally friendly agrosystems and its plant diversity directly influences the soil microbiome diversity. In this study, we tested the efficacy of the microbial consortium (MC) obtained from compost and the cyanobacteria Arthrospira platensis (Ap) compared with the application of the vermicompost tea (VT) and bokashi (Bk) in arugula, lettuce, beetroot, and carrot in two seasons in a recently implemented agroforestry system. We aimed to verify if MC and Ap could be new promising sustainable alternatives in vegetables production. The strategy can be broken down into three stages: (1) Green manure management: planting, cutting, griding, and incorporation in the soil, (2) agroforestry system implementation, and (3) treatment application in a completely randomized blocks design. The vegetables yield was measured. Nutritional traits and the plant root system were evaluated for arugula and lettuce. Greater plant yield, nutritional values, and plant root development were observed in the MC-treated plants; Ap and Bk had, in general, similar results. Our data show that both MC and Ap have potential to become a sustainable product for agricultural production.
Influence of Kluyveromyces lactis and Enterococcus faecalis on Obtaining Lactic Acid by Cheese Whey Fermentation
Authors: Gordillo-Andia Carlos , Almirón Jonathan , Barreda-Del-Carpio Jaime E. , Roudet Francine , Tupayachy-Quispe Danny , Vargas María
Published: May 2024

Cheese whey is a byproduct of the cheese industry that causes high levels of pollution in the environment, but its high lactose content means that it can be used as a source to obtain lactic acid. In this study, two strains, one belonging to a yeast and the other one to a bacteria (Kluyveromyces lactis and Enterococcus faecalis), were isolated from cheese whey and molecularly characterized, and the optimal growth conditions were determined. Then, using proteinized and deproteinized cheese whey, batch fermentation was carried out with the strains arranged in suspension and immobilized. The consumption of lactose and the production of lactic acid were measured through Brix degrees and acidity analysis. Afterwards, the lactic acid was purified, and its yield and physical and chemical characteristics were determined. It was proven that there were differences between each of the strains; arranged in free or encapsulated cells, the proteinized and deproteinized cheese wheys, under the same purification conditions, achieved different yields, colors, and densities of lactic acid. Immobilized Enterococcus faecalis had the highest yield (50.61 ± 34.94 g/L) using the deproteinized cheese whey compared to the immobilized Kluyveromyces lactis (35.70 ± 0.15 g/L) using the proteinized cheese whey.
CycleGAN-Driven MR-Based Pseudo-CT Synthesis for Knee Imaging Studies
Authors: Vallejo-Cendrero Daniel , Molina-Maza Juan Manuel , Rodriguez-Gonzalez Blanca , Viar-Hernandez David , Rodriguez-Vila Borja , Soto-Pérez-Olivares Javier , Moujir-López Jaime , Suevos-Ballesteros Carlos , Blázquez-Sánchez Javier , Acosta-Batlle José , Torrado-Carvajal Angel
Published: May 2024

In the field of knee imaging, the incorporation of MR-based pseudo-CT synthesis holds the potential to mitigate the need for separate CT scans, simplifying workflows, enhancing patient comfort, and reducing radiation exposure. In this work, we present a novel DL framework, grounded in the development of the Cycle-Consistent Generative Adversarial Network (CycleGAN) method, tailored specifically for the synthesis of pseudo-CT images in knee imaging to surmount the limitations of current methods. Upon visually examining the outcomes, it is evident that the synthesized pseudo-CTs show an excellent quality and high robustness. Despite the limited dataset employed, the method is able to capture the particularities of the bone contours in the resulting image. The experimental Mean Absolute Error (MAE), Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM), Zero-Normalized Cross Correlation (ZNCC), Mutual Information (MI), Relative Change (RC), and absolute Relative Change (|RC|) report values of 30.4638 ± 7.4770, 28.1168 ± 1.5245, 0.9230 ± 0.0217, 0.9807 ± 0.0071, 0.8548 ± 0.1019, 0.0055 ± 0.0265, and 0.0302 ± 0.0218 (median ± median absolute deviation), respectively. The voxel-by-voxel correlation plot shows an excellent correlation between pseudo-CT and ground-truth CT Hounsfield units (m = 0.9785; adjusted R2 = 0.9988; ρ = 0.9849; p < 0.001). The Bland–Altman plot shows that the average of the differences is low ((HUCT−HUpseudo−CT = 0.7199 ± 35.2490; 95% confidence interval [−68.3681, 69.8079]). This study represents the first reported effort in the field of MR-based knee pseudo-CT synthesis, shedding light to significantly advance the field of knee imaging.
The Role of Delays in the Performance of Blasting
Authors: Seccatore Jacopo , Vigna Stefano , Marin Tatiane , Cardu Marilena
Published: May 2024

When researching rock blasting, the design parameters typically used for analysis are the geometric and charging parameters. This study focuses on a different approach based on the effect of timing, specifically the role of delays in the initiation sequence. Data were obtained from the results of full-scale blasts. The experimental setting and location allowed us to consider all parameters, other than the number of delays, as constants. The experimental results were analyzed, relating the delay variables to the fragmentation and KPIs of downstream operations. It was found that increasing the number of delays per unit of blasted rock and reducing simultaneous adjacent holes produces finer fragmentation, reduces the amount of fines, facilitates secondary operations, and reduces the risk of flyrock.
SIRS Epidemic Models with Delays, Partial and Temporary Immunity and Vaccination
Authors: Chen-Charpentier Benito
Published: May 2024

The basic reproduction, or reproductive number, is a useful index that indicates whether or not there will be an epidemic. However, it is also very important to determine whether an epidemic will eventually decrease and disappear or persist as an endemic. Different infectious diseases have different behaviors and mathematical models used to simulated them should capture the most important processes; however, the models also involve simplifications. Influenza epidemics are usually short-lived and can be modeled with ordinary differential equations without considering demographics. Delays such as the infection time can change the behavior of the solutions. The same is true if there is permanent or temporary immunity, or complete or partial immunity. Vaccination, isolation and the use of antivirals can also change the outcome. In this paper, we introduce several new models and use them to find the effects of all the above factors paying special attention to whether the model can represent an infectious process that eventually disappears. We determine the equilibrium solutions and establish the stability of the disease-free equilibrium using various methods. We also show that many models of influenza or other epidemics with a short duration do not have solutions with a disappearing epidemic. The main objective of the paper is to introduce different ways of modeling immunity in epidemic models. Several scenarios with different immunities are studied since a person may not be re-infected because he/she has total or partial immunity or because there were no close contacts. We show that some relatively small changes, such as in the vaccination rate, can significantly change the dynamics; for example, the existence and number of the disease-free equilibria. We also illustrate that while introducing delays makes the models more realistic, the dynamics have the same qualitative behavior.
Exosomes in the Diagnosis of Neuropsychiatric Diseases: A Review
Authors: Wu Song , Shang Xinmiao , Guo Meng , Su Lei , Wang Jun
Published: May 2024

Exosomes are 30–150 nm small extracellular vesicles (sEVs) which are highly stable and encapsulated by a phospholipid bilayer. Exosomes contain proteins, lipids, RNAs (mRNAs, microRNAs/miRNAs, long non-coding RNAs/lncRNAs), and DNA of their parent cell. In pathological conditions, the composition of exosomes is altered, making exosomes a potential source of biomarkers for disease diagnosis. Exosomes can cross the blood–brain barrier (BBB), which is an advantage for using exosomes in the diagnosis of central nervous system (CNS) diseases. Neuropsychiatric diseases belong to the CNS diseases, and many potential diagnostic markers have been identified for neuropsychiatric diseases. Here, we review the potential diagnostic markers of exosomes in neuropsychiatric diseases and discuss the potential application of exosomal biomarkers in the early and accurate diagnosis of these diseases. Additionally, we outline the limitations and future directions of exosomes in the diagnosis of neuropsychiatric diseases.
Thai Oakleaf Lettuce Phenocopies a Phytochrome B Mutant
Authors: Cooper Cade , Folta Kevin M.
Published: May 2024

Photomorphogenic development in seedlings may be diagnostic of future plant performance. In this report, we characterize the Thai Oakleaf lettuce genotype, as it exhibited abnormalities in photomorphogenic development that were the most conspicuous under red light, including defects in hypocotyl growth inhibition, decreased cotyledon expansion, and constitutive shade avoidance tendencies. These observations are consistent with defects in red light sensing through the phytochrome B (phyB) photoreceptor system. This genotype is sold commercially as a heat-tolerant variety, which aligns with the evidence that phyB acts as a thermosensor.
Generation of Alzheimer’s Disease Model Derived from Induced Pluripotent Stem Cells with APP Gene Mutation
Authors: Kim Yena , Yun Binna , Ye Byoung Seok , Kim Bo-Young
Published: May 2024

Alzheimer’s disease (AD), the most common cause of dementia, is characterized by disruptions in memory, cognition, and personality, significantly impacting morbidity and mortality rates among older adults. However, the exact pathophysiological mechanism of AD remains unknown, and effective treatment options for AD are still lacking. Human induced pluripotent stem cells (iPSC) are emerging as promising platforms for disease research, offering the ability to model the genetic mutations associated with various conditions. Patient-derived iPSCs are useful for modeling neurodegenerative and neurodevelopmental disorders. In this study, we generated AD iPSCs from peripheral blood mononuclear cells obtained from a 65-year-old patient with AD carrying the E682K mutation in the gene encoding the amyloid precursor protein. Cerebral organoids derived from AD iPSCs recapitulated the AD phenotype, exhibiting significantly increased levels of tau protein. Our analysis revealed that an iPSC disease model of AD is a valuable assessment tool for pathophysiological research and drug screening.
Deep Learning-Based Surgical Treatment Recommendation and Nonsurgical Prognosis Status Classification for Scaphoid Fractures by Automated X-ray Image Recognition
Authors: Su Ja-Hwung , Tung Yu-Cheng , Liao Yi-Wen , Wang Hung-Yu , Chen Bo-Hong , Chang Ching-Di , Cheng Yu-Fan , Chang Wan-Ching , Chin Chu-Yu
Published: May 2024

Biomedical information retrieval for diagnosis, treatment and prognosis has been studied for a long time. In particular, image recognition using deep learning has been shown to be very effective for cancers and diseases. In these fields, scaphoid fracture recognition is a hot topic because the appearance of scaphoid fractures is not easy to detect. Although there have been a number of recent studies on this topic, no studies focused their attention on surgical treatment recommendations and nonsurgical prognosis status classification. Indeed, a successful treatment recommendation will assist the doctor in selecting an effective treatment, and the prognosis status classification will help a radiologist recognize the image more efficiently. For these purposes, in this paper, we propose potential solutions through a comprehensive empirical study assessing the effectiveness of recent deep learning techniques on surgical treatment recommendation and nonsurgical prognosis status classification. In the proposed system, the scaphoid is firstly segmented from an unknown X-ray image. Next, for surgical treatment recommendation, the fractures are further filtered and recognized. According to the recognition result, the surgical treatment recommendation is generated. Finally, even without sufficient fracture information, the doctor can still make an effective decision to opt for surgery or not. Moreover, for nonsurgical patients, the current prognosis status of avascular necrosis, non-union and union can be classified. The related experimental results made using a real dataset reveal that the surgical treatment recommendation reached 80% and 86% in accuracy and AUC (Area Under the Curve), respectively, while the nonsurgical prognosis status classification reached 91% and 96%, respectively. Further, the methods using transfer learning and data augmentation can bring out obvious improvements, which, on average, reached 21.9%, 28.9% and 5.6%, 7.8% for surgical treatment recommendations and nonsurgical prognosis image classification, respectively. Based on the experimental results, the recommended methods in this paper are DenseNet169 and ResNet50 for surgical treatment recommendation and nonsurgical prognosis status classification, respectively. We believe that this paper can provide an important reference for future research on surgical treatment recommendation and nonsurgical prognosis classification for scaphoid fractures.