bluuebunny/crossref_metadata_2025 huggingface dataset:
Response of African Sorghum Genotypes for Drought Tolerance under Variable Environments
Authors: Yahaya Muhammad Ahmad , Shimelis Hussein , Nebié Baloua , Mashilo Jacob , Pop Georgeta
Published: February 2023

Sorghum (Sorghum bicolor (L.) Moench) is the main food staple for millions of people in Sub-Saharan Africa (SSA) and Asia. Sorghum is relatively drought tolerant and cultivated in arid and semi-arid regions under rain-fed production. However, severe drought stress often leads to crop loss and declined productivity. The development and deployment of high-yielding and drought-adapted genotypes is a cost-effective strategy for sustainable sorghum production globally. The objective of this study was to determine drought tolerance and genotype-by-environment interaction (GEI) effects on grain yields of a population of African sorghum genotypes to identify high-yielding and drought-adapted genotypes for direct production and also for use in breeding programs. Two hundred and twenty-five sorghum genotypes were evaluated under non-stressed (NS), pre-anthesis drought stress (PreADS), and post-anthesis drought stress (PoADS) conditions under field and greenhouse environments using a 15 × 15 alpha lattice design in two replicates. The three water regimes and two environments resulted in six testing environments. Data were collected on grain yield and drought tolerance parameters, and additive main effect and multiplicative interaction (AMMI) analysis were computed. The mean grain yield under NS, PreADS, and PoADS were 3.70, 1.76, and 2.58 t/ha, in that order. The best genotypes adapted to non-stressed environments were G09, and G109, whereas G114 and G56 were suitable for non-stressed and stressed conditions. G72 and G75 displayed the best performance in PreADS conditions only, whereas genotypes G210 and G12 were identified as high performers under PoADS only. The AMMI analysis revealed that genotype (G), environment (E), and GEI were significant (p < 0.05), which accounted for 38.7, 44.6, and 16.6% of the total explained variation in grain yield. AMMI 4 was the best-fitting model for grain yield. Based on AMMI 4 and the Best Linear Unbiased Estimates (BLUPs) calculations, genotypes G119 and G127 with a grain yield of 5.6 t/ha and 6.3 t/ha were selected as being suitable for non-stressed conditions. Genotypes G8 and G71 with BLUPs of 2.5 t/ha and 2.6 t/ha were best-suited for pre-anthesis drought stress conditions, whereas genotypes G115 and G120 with BLUPs of 4.2 t/ha and 4.3 t/ha are recommended for post-anthesis drought-prone environments, respectively. The identified sorghum genotypes are recommended for production in dry agro-ecologies of sub-Saharan Africa characterized by pre-and-post anthesis drought stress. In addition, the identified genotypes are valuable genetic resources to develop novel drought-tolerance material.
Impact of Futuristic Climate Variables on Weed Biology and Herbicidal Efficacy: A Review
Authors: Kumar Vipin , Kumari Annu , Price Andrew J. , Bana Ram Swaroop , Singh Vijay , Bamboriya Shanti Devi
Published: February 2023

Our changing climate will likely have serious implications on agriculture production through its effects on food and feed crop yield and quality, forage and livestock production, and pest dynamics, including troublesome weed control. With regards to weeds, climatic variables control many plant physiology functions that impact flowering, fruiting, and seed dormancy; therefore, an altered climate can result in a weed species composition shift within agro-ecosystems. Weed species will likely adapt to a changing climate due to their high phenotypic plasticity and vast genetic diversity. Higher temperatures and CO2 concentrations, and altered moisture conditions, not only affect the growth of weeds, but also impact the effectiveness of herbicides in controlling weeds. Therefore, weed biology, growth characteristics, and their management are predicted to be affected greatly by changing climatic conditions. This manuscript attempted to compile the available information on general principles of weed response to changing climatic conditions, including elevated CO2 and temperature under diverse rainfall patterns and drought. Likewise, we have also attempted to highlight the effect of soil moisture dynamics on the efficacy of various herbicides under diverse agro-ecosystems.
Severe Hypercapnia during Anaesthesia under Mechanical Ventilation in Two Paediatric Patients
Authors: Papastefanou Anastasia , Rioja Eva
Published: February 2023

A 2-month-old male 1.56 kg Yorkshire terrier (Case No. 1) and a 3-month-old male 2.3 kg Jack Russell Terrier (Case No. 2) were scheduled for ophthalmological surgery under general anaesthesia and neuromuscular blockade. For both patients, volume-controlled ventilation (VCV) was used with set tidal volumes (VT) of 13 mL/kg and 20 mL/kg for cases No. 1 and 2, respectively. The type of ventilator used did not take into account the intrinsic compliance of the breathing system; therefore, a significant part of the delivered VT was wasted in the expansion of the breathing system, and did not reach the patients, causing alveolar hypoventilation. Both cases developed low dynamic compliance (CD), and after a recruitment manoeuvre, EtCO2 of up to 116 mmHg and 197 mmHg were revealed for cases No. 1 and 2, respectively. The two cases had to be ventilated manually, using positive inspiratory pressures (PIP) of 20–25 mmHg, in order to improve alveolar ventilation and reduce the EtCO2, as adjustments to the VCV were ineffective. Both patients maintained an oxygen haemoglobin saturation between 94% and 100% throughout the procedure and they recovered well. Using a higher VT from the beginning, to compensate for the compliance of the breathing system, or the use of pressure-controlled ventilation (PCV), could have potentially helped to avoid these two incidences of severe hypercapnia.
Electroencephalographic and Cardiovascular Changes Associated with Propofol Constant Rate of Infusion Anesthesia in Young Healthy Dogs
Authors: Murillo Carla , Weil Ann B. , Moore George E. , Kreuzer Matthias , Ko Jeff C.
Published: February 2023

This study aimed to evaluate electroencephalography (EEG) and cardiovascular changes associated with propofol constant rate of infusion (CRI) anesthesia in dogs. Six dogs were each given propofol CRI to induce different anesthetic phases including induction (1 mg/kg/min for 10 min), and decremental maintenance doses of 2.4 mg per kg per min, 1.6 mg per kg per min, and 0.8 mg per kg per minute over 45 min. Processed EEG indices including patient state index (PSI), (burst) suppression ratio (SR), and spectral edge frequency (95%) were obtained continuously until the dogs recovered to sternal recumbency. The dogs were intubated and ventilated. Cardiovascular and EEG index values were compared between anesthetic phases. The PSI, SR, mean arterial blood pressure, and subjective anesthetic depth scores were highly correlated throughout anesthetic depth changes. The PSI decreased from 85.0 ± 17.3 at awake to 66.0 ± 29.0 at induction, and then sharply reduced to 19.7 ± 23.6 during maintenance and returned to 61.5 ± 19.2 at extubation. The SR increased from 15.4 ± 30.9% at induction to 70.9 ± 39.8% during maintenance and decreased to 3.4 ± 8.9% at extubation. We concluded that EEG indices can be used to aid in tracking ongoing brain state changes during propofol anesthesia in dogs.
Hepatic Transcriptome Analysis Reveals Genes, Polymorphisms, and Molecules Related to Lamb Tenderness
Authors: Listyarini Kasita , Sumantri Cece , Rahayu Sri , Islam Md. Aminul , Akter Syeda Hasina , Uddin Muhammad Jasim , Gunawan Asep
Published: February 2023

Tenderness is a key meat quality trait that determines the public acceptance of lamb consumption, so genetic improvement toward lamb with higher tenderness is pivotal for a sustainable sheep industry. However, unravelling the genomics controlling the tenderness is the first step. Therefore, this study aimed to identify the transcriptome signatures and polymorphisms related to divergent lamb tenderness using RNA deep sequencing. Since the molecules and enzymes that control muscle growth and tenderness are metabolized and synthesized in the liver, hepatic tissues of ten sheep with divergent phenotypes: five high- and five low-lamb tenderness samples were applied for deep sequencing. Sequence analysis identified the number of reads ranged from 21.37 to 25.37 million bases with a mean value of 22.90 million bases. In total, 328 genes are detected as differentially expressed (DEGs) including 110 and 218 genes that were up- and down-regulated, respectively. Pathway analysis showed steroid hormone biosynthesis as the dominant pathway behind the lamb tenderness. Gene expression analysis identified the top high (such as TP53INP1, CYP2E1, HSD17B13, ADH1C, and LPIN1) and low (such as ANGPTL2, IGFBP7, FABP5, OLFML3, and THOC5) expressed candidate genes. Polymorphism and association analysis revealed that mutation in OLFML3, ANGPTL2, and THOC5 genes could be potential candidate markers for tenderness in sheep. The genes and pathways identified in this study cause variation in tenderness, thus could be potential genetic markers to improve meat quality in sheep. However, further validation is needed to confirm the effect of these markers in different sheep populations so that these could be used in a selection program for lamb with high tenderness.
In Vitro Evaluation of Winged Bean (Psophocarpus tetragonolobus) Tubers as an Alternative Feed for Ruminants
Authors: Suntara Chanon , Sombuddee Napudsawun , Lukbun Saowalak , Kanakai Natdanai , Srichompoo Pachara , Chankaew Sompong , Khonkhaeng Benjamad , Gunun Pongsatorn , Gunun Nirawan , Polyorach Sineenart , Foiklang Suban , Cherdthong Anusorn
Published: February 2023

The purpose of the current study is to determine the effects of the replacement of cassava chips with winged bean (Psophocarpus tetragonolobus) tubers (WBTs) on gas production parameters, in vitro degradability, and ruminal fermentation in ruminant diets. The study was performed using a 3 × 4 factorial arrangements and was designed using a completely random method. Factor A employed three various roughage sources that were frequently used by locals to feed ruminants: Oryza sativa L. (a1), Brachiaria ruziziensis (a2), and Pennisetum purpureum (a3). The levels of WBTs substitutions for cassava chips at 0%, 33%, 66%, and 100% in the diet were selected as factor B. The experiment’s findings revealed that replacing the cassava chips in the diet with WBTs at levels of 66 and 100% enhanced the fermentation process by producing a high gas volume at 96 h when Ruzi grass (RZ) was used as the main source of roughage (p < 0.01). The interaction between the roughage source and WBTs showed that organic matter (OM) degradability improved markedly in the case of RZ grass in combination with WBTs at all levels. Both the total volatile fatty acids (TVFAs) at 8 h of incubation and the average value decreased when a complete substitution of casava chips with WBT (WBT 100%) was employed or when employing rice straw as the main source of roughage (p < 0.01). There was no interaction between WBTs and roughage source on the ammonia–nitrogen (NH3-N) concentration (ml/dL) and rumen microbial count (p > 0.05). In summary, WBTs can be used effectively when combined with grass (Ruzi and Napier). The implementation of WBTs as a novel alternative feed may effectively replace cassava chips without affecting rumen function.
Cannabidiol: Bridge between Antioxidant Effect, Cellular Protection, and Cognitive and Physical Performance
Authors: Jîtcă George , Ősz Bianca E. , Vari Camil E. , Rusz Carmen-Maria , Tero-Vescan Amelia , Pușcaș Amalia
Published: February 2023

The literature provides scientific evidence for the beneficial effects of cannabidiol (CBD), and these effects extend beyond epilepsy treatment (e.g., Lennox–Gastaut and Dravet syndromes), notably the influence on oxidative status, neurodegeneration, cellular protection, cognitive function, and physical performance. However, products containing CBD are not allowed to be marketed everywhere in the world, which may ultimately have a negative effect on health as a result of the uncontrolled CBD market. After the isolation of CBD follows the discovery of CB1 and CB2 receptors and the main enzymatic components (diacylglycerol lipase (DAG lipase), monoacyl glycerol lipase (MAGL), fatty acid amino hydrolase (FAAH)). At the same time, the antioxidant potential of CBD is due not only to the molecular structure but also to the fact that this compound increases the expression of the main endogenous antioxidant systems, superoxide dismutase (SOD), and glutathione peroxidase (GPx), through the nuclear complex erythroid 2-related factor (Nrf2)/Keep1. Regarding the role in the control of inflammation, this function is exercised by inhibiting (nuclear factor kappa B) NF-κB, and also the genes that encode the expression of molecules with a pro-inflammatory role (cytokines and metalloproteinases). The other effects of CBD on cognitive function and physical performance should not be excluded. In conclusion, the CBD market needs to be regulated more thoroughly, given the previously listed properties, with the mention that the safety profile is a very good one.
Changes in the Bioaccessibility of Antioxidants after Simulated In Vitro Digestion of Bioprocessed Spelt-Enhanced Wheat Bread
Authors: Mencin Marjeta , Markanovič Nika , Mikulič-Petkovšek Maja , Veberič Robert , Terpinc Petra
Published: February 2023

The aim of the study was to determine whether the partial replacement of wheat flour with bioprocessed spelt flour contributes to a higher bioaccessibility of the antioxidants in bread. The results showed that the type and amount of bioprocessed spelt flour in a bread recipe has a major impact on the extractable and bound TPC, the content of individual phenolics, their antioxidant activity, and their bioaccessibility as determined by in vitro digestion. Extractable p-coumaric and trans-ferulic acids in breads decreased after digestion, while extractable cis-ferulic and p-hydroxybenzoic acids increased. The bioaccessibility of TPC in the control bread (100% wheat flour), and in bread enriched with 5% “germinated + fermented” spelt flour (GFB5), did not differ. However, the digested GFB5 bread contained 5.2-times more extractable, and 1.3-times more bound, trans-ferulic acid than the digested control bread. trans-Ferulic acid showed the lowest bioaccessibility, up to 2.8%. In GFB2.5 and GFB5 breads, the bioaccessibility of p-coumaric, trans-ferulic, and cis-ferulic acids was higher than in other digested breads. PCA visualized the difference between the undigested and digested breads. The incorporation of germinated and fermented, or germinated and enzymatic, treated spelt flour in a white bread recipe could be an attractive way of providing consumers with nutritionally interesting foods.
Nodakenin Induces ROS-Dependent Apoptotic Cell Death and ER Stress in Radioresistant Breast Cancer
Authors: Kim Tae Woo
Published: February 2023

Angelica gigas exerts powerful anti-tumor and anti-cancer effects in various cancer cell types. However, there have been few studies regarding the anti-cancer effect of nodakenin, a bioactive compound of Angelica gigas, in vivo and in vitro on breast cancers. I found that nodakenin, in a concentration-dependent manner, inhibits breast cancer cell viability and decreases the tumor volume in mice. Additionally, nodakenin induces caspase-3-dependent apoptosis in breast cancer cells; however, the combination of Z-VAD-FMK and nodakenin suppresses the caspase-3-dependent apoptotic cell death. Furthermore, nodakenin mediates apoptotic cell death via the PERK-mediated signaling pathway and calcium (Ca2+) release, and nodakenin combined with thapsigargin induces synergistic cell death by inhibiting sarco/endoplasmic reticulum (ER) Ca2+-ATPase. However, knockdown of PERK or CHOP inhibits Ca2+ generation and caspase-dependent apoptosis in nodakenin-treated breast cancer cells. Nodakenin induces ROS and Ca2+ generation, ER stress, and apoptotic cell death; however, the knockdown of Nox4 inhibits ROS generation and ER stress- and caspase-dependent apoptotic cell death. In addition, nodakenin combined with radiation overcomes radioresistance in radioresistant breast cancer cells by suppressing epithelial–mesenchymal transition phenotypes, including the decrease in E-cadherin and the increase in N-cadherin and vimentin. Therefore, these findings indicate that nodakenin may be a novel therapeutic strategy for breast cancers.
Fatigue Behaviour of Concrete Using Siderurgical Aggregates
Authors: Tamayo Pablo , García Del Ángel Gilberto , Sainz-Aja José A. , Cimentada Ana I. , Setién Jesús , Polanco Juan A. , Thomas Carlos
Published: February 2023

The use of concrete with aggregates with reduced environmental impact, as is the case of concrete with siderurgical aggregates (recovered slags), will inevitably increase in the future, as a result of policies promoting development of more sustainable construction materials. These concretes offer an excellent response to static loads, but their behaviour under dynamic loads has not yet been studied. The aim of this study is to characterize the fatigue behaviour, in terms of fatigue limit, of a concrete with siderurgical aggregates by comparing it with an analogous conventional limestone concrete. This characterization was carried out using the Locati method, which stands out for its convenience, speed and low cost, with the feature of being carried out at a high frequency corresponding to the resonance frequency. Performing high-frequency tests has drastically reduced test times and thus costs. Likewise, the results obtained show that, using various criteria found in the literature, concrete with siderurgical aggregates has a higher fatigue limit in absolute terms (MPa), but a lower one in relative terms (% fc).
AI-Based Intelligent Monitoring System for Estrus Prediction in the Livestock Industry
Authors: Cho Youngjoon , Kim Jongwon
Published: February 2023

In order to improve a livestock breeding environment that considers securing safe cattle resources and improving productivity for the intelligent farm, we propose an animal-friendly and worker-friendly intellectual monitoring system with Artificial Intelligent (AI) technology. In order to secure safe cattle resources and increase productivity for the livestock industry, it is necessary to secure the self-activities of the cattle and predict the estrous state of target cattle as quickly as possible. For the prediction of the estrous state, it is necessary to continuously observe the cattle behavior by workers and quantify the behavior of the target cattle, but that is not easy for workers and needs a long period of continuous observation. We developed the intelligent monitoring system (IMS) with the ARM (Augmented Recognition Model) for the intelligent farm that can predict the estrus of target cattle and get activity data for individual cattle, and then the system was applied to a typical cattle farm for activity monitoring of the Korean cattle (Hanwoo). Therefore, we confirmed the target Hanwoo group with more than 400 activities among the Hanwoo groups using the ARM threshold. Thus, we verified the potential of the proposed system for tracking multiple similar objects.
Application of Machine Learning Predictive Models for Early Detection of Glaucoma Using Real World Data
Authors: Raju Murugesan , Shanmugam Krishna P. , Shyu Chi-Ren
Published: February 2023

Early detection of glaucoma is critically important for the prevention of irreversible blindness. We developed a predictive analytic framework through temporal data carpentry and applications of a suite of machine learning and logistic regression methods for the early prediction of glaucoma using electronic health records (EHR) from over 650 hospitals and clinics across the USA. Four different machine-learning classification methods were applied using the whole dataset for predictive analysis. The accuracy, sensitivity, specificity, and f1 score were calculated using five-fold cross-validation to train and refine the models. The XGBoost, multi-layer perceptron (MLP), and random forest (RF) performed comparably well based on the area under the receiver operating characteristics curve (AUC) score of 0.81 for predicting glaucoma one year before the onset of the disease compared to the logistic regression (LR) score of 0.73. This study suggests that the ML methods can capture potential pre-glaucoma patients in advance before the occurrence of clinical symptoms from their history of EHR encounters, thus possibly leading to earlier intervention and preventive treatment.
Generalized Image Captioning for Multilingual Support
Authors: Cho Suhyun , Oh Hayoung
Published: February 2023

Image captioning is a problem of viewing images and describing images in language. This is an important problem that can be solved by understanding the image, and combining two fields of image processing and natural language processing into one. The purpose of image captioning research so far has been to create general explanatory captions in the learning data. However, various environments in reality must be considered for practical use, as well as image descriptions that suit the purpose of use. Image caption research requires processing new learning data to generate descriptive captions for specific purposes, but it takes a lot of time and effort to create learnable data. In this study, we propose a method to solve this problem. Popular image captioning can help visually impaired people understand their surroundings by automatically recognizing and describing images into text and then into voice and is an important issue that can be applied to many places such as image search, art therapy, sports commentary, and real-time traffic information commentary. Through the domain object dictionary method proposed in this study, we propose a method to generate image captions without the need to process new learning data by adjusting the object dictionary for each domain application. The method proposed in the study is to change the dictionary of the object to focus on the domain object dictionary rather than processing the learning data, leading to the creation of various image captions by intensively explaining the objects required for each domain. In this work, we propose a filter captioning model that induces generation of image captions from various domains while maintaining the performance of existing models.
Multi-View Surgical Camera Calibration with None-Feature-Rich Video Frames: Toward 3D Surgery Playback
Authors: Obayashi Mizuki , Mori Shohei , Saito Hideo , Kajita Hiroki , Takatsume Yoshifumi
Published: February 2023

Mounting multi-view cameras within a surgical light is a practical choice since some cameras are expected to observe surgery with few occlusions. Such multi-view videos must be reassembled for easy reference. A typical way is to reconstruct the surgery in 3D. However, the geometrical relationship among cameras is changed because each camera independently moves every time the lighting is reconfigured (i.e., every time surgeons touch the surgical light). Moreover, feature matching between surgical images is potentially challenging because of missing rich features. To address the challenge, we propose a feature-matching strategy that enables robust calibration of the multi-view camera system by collecting a set of a small number of matches over time while the cameras stay stationary. Our approach would enable conversion from multi-view videos to a 3D video. However, surgical videos are long and, thus, the cost of the conversion rapidly grows. Therefore, we implement a video player where only selected frames are converted to minimize time and data until playbacks. We demonstrate that sufficient calibration quality with real surgical videos can lead to a promising 3D mesh and a recently emerged 3D multi-layer representation. We reviewed comments from surgeons to discuss the differences between those 3D representations on an autostereoscopic display with respect to medical usage.
Using Geogrid Encased Granular Columns for Embankment’s Slope Protection: 3D-Finite Difference Analysis
Authors: Jasim Omar Hamdi , Tonaroğlu Murat
Published: February 2023

The stability of the embankment’s slopes is a critical aspect of geotechnical engineering and it is essential to guarantee the effectiveness of the factor of safety to prevent any potential failures in the slope both during and post-construction. The current study consists of two parts; the first part is the study of the behavior of the geogrid-encased granular columns and their interaction with the soil at the shear surface generated by the slippage of the soil, while the second part is a study of the stability of slopes by changing several factors, including the area replacement ratio (Ar %) of the granular columns, the angle of the embankment slope (β), and different elastic modulus (Eg) of geogrid on the stability of an embankment. About 90 analyses were conducted on a clayey sand embankment over a clayey layer. The area replacement ratios (Ar %) were changed by using different values of the diameter of the column; from 50 to 100 cm. The angle of the embankment slope was changed from 28 to 36 degrees. Furthermore, three different values, 0.12, 2.625, and 6.552 GPa, of modulus of elasticity were used. The results show that increasing the modulus of elasticity of the geogrid increases the normalized shear strength and decreases the lateral displacement in the column. Furthermore, the factor of safety was increased as the stiffness ratio between the geogrid and the materials increased. However, the factor of safety was noted to decrease when the angle of the embankment slope was increased.
Key Quality Factors in Digital Competence Assessment: A Validation Study from Teachers’ Perspective
Authors: Guàrdia Lourdes , Maina Marcelo , Mancini Federica , Martinez Melo Montserrat
Published: February 2023

The progressive shift from a transmissive to a competence-based approach emphasises the need to design new models and tools for competence assessment. In order to address this need, this study, firstly, introduces the assessment model for digital competence in primary and secondary schools developed within the H2020 CRISS project. The Competence Assessment Model (CAM) (1) embraces the integration pedagogy approach in which competences are embedded within the curriculum and (2) provides competence assessment scenarios (CAS). Secondly, the study presents the results of the evaluation of its quality from the teachers’ perspective through an instrument designed on the basis of nine competence assessment quality criteria. The CAM was tested in a large-scale pilot study conducted in 535 primary and secondary schools across Europe. The outcomes show that the CAM mainly fulfills two out of the nine quality criteria: meaningfulness and authenticity. However, the exploratory factor analysis also reveals that all these quality criteria can be summarized into four key quality factors that more accurately describe how CAM is experienced in school teaching. Out of these, the most relevant is the (1) efficiency over time, student monitoring, support and evaluation. The three secondary factors identified are (2) fairness and cognitive complexity, (3) meaningfulness and authenticity and (4) reproducibility and transparency. The study provides a conceptual and methodological approach for the evaluation of Digital Competence in the school context. Most of all, it helps highlight four factors that, according to teaching staff, describe the quality of the proposed model when applied to daily teaching practices.
Study on the Properties of Cement-Based Cementitious Materials Modified by Nano-CaCO3
Authors: Pan Chonggen , Zang Jiawei , Chen Keyu , Ren Jingge
Published: February 2023

The effects of Nano-CaCO3 on the physical, mechanical properties and durability of cement-based materials were investigated in this paper. The mechanical property, durability and SEM microscopic tests of test blocks with different Nano-CaCO3 content were carried out. Results showed that Nano-CaCO3 could improve the flexural strength, compressive strength and impermeability of cement-based materials. When the content of Nano-CaCO3 is 2.0%, the strengthening effect of Nano-CaCO3 on the cement-based materials was optimized, and the flexural strength of cement-based materials after 3 d, 7 d and 28 d increased by 12.6%, 18% and 32.4%, respectively, compared with the reference group. When the content of Nano-CaCO3 exceeded 2.0%, the flexural strength of cement-based materials begins to decline with the increase of Nano-CaCO3 content. Similarly, when the content of Nano-CaCO3 reached 2.0%, the impermeability of the cement-based materials was also optimized, and the permeability height of the base group could be increases by 41.4%. At the early stage of hydration, the exothermic rate of cement with 2.0% Nano-CaCO3 content was higher than that of other contents. When the content of Nano-CaCO3 increased from 0 to 2.0%, the hydration exothermic rate increased gradually with the increase of Nano-CaCO3 content.
Power Allocation and User Grouping for NOMA Downlink Systems
Authors: Li Jun , Gao Tong , He Bo , Zheng Wenjing , Lin Fei
Published: February 2023

Non-orthogonal multiple access (NOMA) technology allows multiple users to use the same time-frequency resource to send signals, which can improve spectral efficiency and throughput. We study the problems of user grouping and power allocation in the downlink of a multi-carrier NOMA system. The sum rate is the optimization goal. A step-by-step optimization is adopted. Users are grouped first and then power is allocated. For user grouping, the user grouping method based on the maximum channel gain difference is improved to prevent users with similar channel gains from being grouped together. For power allocation, the deep learning power allocation algorithm is used among subcarriers. Then, the closed-form expressions of power allocation between multiplexed users are derived according to the minimum transmission rate constraint. The simulation results show that compared with the fractional transmit power allocation method and fixed power allocation method, the deep learning power allocation method improves the system sum rate by about 2.2% and 19%, respectively. The power allocation methods we propose improve the system sum rate by about 10% compared to the fractional transmit power allocation method used among subcarriers and between multiplexed users.
PSDFH: A Phase-Space-Based Depth from Hologram Extraction Method
Authors: Madali Nabil , Gilles Antonin , Gioia Patrick , Morin Luce
Published: February 2023

Object pre-localization from computer-generated holograms is still an open problem in the current state of the art. In this work, we propose the use of the hologram phase space representation to determine a set of regions of interest where the searched object can be located. The extracted regions can be used to pre-locate the object in 3D space and are further refined to produce a more accurate depth estimate. An iterative refinement method is proposed for 1D holograms and is extended in a parsimonious version for 2D holograms. A series of experiments are conducted to assess the quality of the extracted regions of interest and the sparse depth estimate produced by the iterative refinement method. Experimental results show that it is possible to pre-localize the object in 3D space from the phase space representation and thus to improve the calculation time by reducing the number of operations and numerical reconstructions necessary for the application of s (DFF) methods. Using the proposed methodology, the time for the application of the DFF method is reduced by half, and the accuracy is increased by a factor of three.
A Machine Vision-Based Algorithm for Color Classification of Recycled Wool Fabrics
Authors: Furferi Rocco , Servi Michaela
Published: February 2023

The development of eco-sustainable systems for the textile industry is a trump card for attracting expanding markets aware of the ecological challenges that society expects in the future. For companies willing to use regenerated wool as a raw material for creating plain, colored yarns and/or fabrics, building up a number of procedures and tools for classifying the conferred recycled materials based on their color is crucial. Despite the incredible boost in automated or semi-automated methods for color classification, this task is still carried out manually by expert operators, mainly due to the lack of systems taking into account human-related classification. Accordingly, the main aim of the present work was to devise a simple, yet effective, machine vision-based system combined with a probabilistic neural network for carrying out reliable color classification of plain, colored, regenerated wool fabrics. The devised classification system relies on the definition of a set of color classes against which to classify the recycled wool fabrics and an appositely devised acquisition system. Image-processing algorithms were used to extract helpful information about the image color after a set of images has been acquired. These data were then used to train the neural network-based algorithms, which categorized the fabric samples based on their color. When tested against a dataset of fabrics, the created system enabled automatic classification with a reliability index of approximately 83%, thus demonstrating its effectiveness in comparison to other color classification approaches devised for textile and industrial fields.
A Primer on CFD-DEM for Polymer-Filled Suspensions
Authors: Fernandes Célio , Ferrás Luís L. , Afonso Alexandre
Published: February 2023

This work reports on an evaluation of the computational fluid dynamics–discrete element method (CFD-DEM) numerical approach to study the behavior of polymer-filled suspensions in a parallel-plate rheometer. For this purpose, an open-source CFD-DEM solver is used to model the behavior of such suspensions considering different particle volume fractions and different types of fluid rheology. We first validate the numerical approach for the single-phase flow of the continuum phase (fluid phase) by comparing the fluid’s azimuthal velocity and shear stress components obtained from the open-source solver against the analytical expressions given in cylindrical coordinates. In addition, we compare the numerical torque given by the numerical procedure with analytical expressions obtained for Newtonian and power law fluids. For both cases, there is a remarkable agreement between the numerical and analytical results. Subsequently, we investigated the effects of the particle volume fraction on the rheology of the suspension. The numerical results agree well with the experimentally measured ones and show a yield stress phenomenon with the increase of the particle volume fraction.
Mask–Mediator–Wrapper: A Revised Mediator–Wrapper Architecture for Heterogeneous Data Source Integration
Authors: Dončević Juraj , Fertalj Krešimir , Brčić Mario , Krajna Agneza
Published: February 2023

This paper deals with the mediator–wrapper architecture and observes it in more modern aspects by relating it to architectural quanta. It is an important architectural pattern that enables a more flexible and modular architecture in opposition to monolithic architectures for data source integration systems. This paper identifies certain realistic and concrete scenarios where the mediator–wrapper architecture underperforms. These issues are addressed with the extension of the architecture via the mask component type. The mask component is detailed so it can be reasoned about without prescribing a concrete programming language or paradigm but still providing a working principle. The benefits of the new mask–mediator–wrapper architecture are analytically proven in relevant scenarios. The proof includes a software shift–cost analysis whose results quantitatively show the improvement of the mask–mediator–wrapper architecture over other mediator–wrapper architecture settings. One of the applications of the new architecture is envisioned for modern data sources integration systems backing big data processing.
Kernel Learning by Spectral Representation and Gaussian Mixtures
Authors: Pena-Llamas Luis R. , Guardado-Medina Ramon O. , Garcia Arturo , Mendez-Vazquez Andres
Published: February 2023

One of the main tasks in kernel methods is the selection of adequate mappings into higher dimension in order to improve class classification. However, this tends to be time consuming, and it may not finish with the best separation between classes. Therefore, there is a need for better methods that are able to extract distance and class separation from data. This work presents a novel approach for learning such mappings by using locally stationary kernels, spectral representations and Gaussian mixtures.
A Numerical Investigation of Sloshing in a 3D Prismatic Tank with Various Baffle Types, Filling Rates, Input Amplitudes and Liquid Materials
Authors: Erzan Topçu Elif , Kılıç Eyüp
Published: February 2023

Partially filled liquid-carrying tanks have been used in many engineering applications, such as ships, vehicle fuel tanks, rockets, and drink or petroleum tankers. Liquid sloshing is an exciting phenomenon that researchers are investigating because of its complex behavior specifications. In this study, the sloshing responses of a prismatic tank with the approximate volume of an automobile fuel tank under different laterally harmonic excitation amplitudes, baffle structures, filling rates, and different types of liquid were investigated numerically. The computational fluid dynamics method (CFD) was used to solve fluid dynamics equations, and the volume of fluid method was applied to simulate two-phase flow in the tank. A validation study was performed by a literature study. Later, the effect of large and small excitation amplitudes, filling rates and fluid types on sloshing behavior were investigated and comparatively analyzed in the tank system with various baffle types.
Correlating Disorder Microstructure and Magnetotransport of Carbon Nanowalls
Authors: Acosta Gentoiu Mijaela , García Gutiérrez Rafael , Alvarado Pulido José Joaquín , Montaño Peraza Javier , Volmer Marius , Vizireanu Sorin , Antohe Stefan , Dinescu Gheorghe , Rodriguez-Carvajal Ricardo Alberto
Published: February 2023

The carbon nanowalls (CNWs) grown by Plasma-Enhanced CVD reveal differences in the magnetotransport properties depending on the synthesis parameters. In this paper, we report the influence of the deposition temperature, which produces variations of the disorder microstructure of the CNWs. Relative low disorder leads to the weak localization with the transition to weak antilocalization. Higher disorder generates positive Hopping mechanism in low field with a crossover to a diffusion transport by graphene nanocrystallites. The samples reveal a similitude of the isoline density of the MR at a low temperature (<50 K), explained in the context of the magnetization. This effect is independent of the number of defects. We can achieve a desirable amount of control over the MT properties changing the CNWs’ microstructure.
On the Possibility of Forming a Corium Pool by Induction Heating in a Melt Trap of the Lava-B Facility
Authors: Skakov Mazhyn , Baklanov Viktor , Akaev Assan , Kukushkin Ivan , Bekmuldin Maxat , Toleubekov Kuanyshbek , Gradoboev Alexandr , Stepanova Olga
Published: February 2023

This paper presents the results of computational and physical studies on the production of corium and its retention in an MR’s melt trap of the Lava-B facility. A feature of the Lava-B facility used in the IAE NNC RK to study the processes occurring during a severe accident at a nuclear reactor, is the separation of the stages of the reactor core corium formation and its interaction with structural materials. The melting of materials takes place in an induction furnace with a hot crucible, after which it moves to a melt receiver (MR) in which the test object is located. In the case of studies of processes occurring outside the reactor vessel, this is a special trap, which is placed in the inductor to simulate decay heat. However, based on the conservative computational estimates, it was found that the inductor power in the MR can be sufficient to directly produce, melt, and, subsequently, maintain the corium in the liquid phase. In this regard, in order to optimize the experiments under controlled conditions, the authors came up with the idea to experimentally test the possibility of producing corium by induction heating directly in the MR’s melt trap. In addition, according to the authors, this method would obviate the problem of corium contact with the carbon environment of the melting furnace of the Lava-B facility. Previously, burden heating simulating corium was modeled on the computer using available parameters of the MR’s induction heater. Based on the numerical experiment, the conditions for physical modeling of the corium production in the MR’s melt trap were established. An analysis of the physical modeling showed that during the burden heating in the melt trap, its metal components became liquid, thus, forming a melt pool. However, in terms of this design of the trap, there were problems associated with the complete melting of all corium components, as well as with the integrity of the experimental device when forming the corium pool and during the actual physical modeling.
Bilateral Attention U-Net with Dissimilarity Attention Gate for Change Detection on Remote Sensing Imageries
Authors: Lee Jongseok , Wiratama Wahyu , Lee Wooju , Marzuki Ismail , Sim Donggyu
Published: February 2023

This study proposes a bilateral attention U-Net with a dissimilarity attention gate (DAG) for change detection on remote sensing imageries. The proposed network is designed with a bilateral dissimilarity encoding for the DAG calculation to handle reversible input images, resulting in high detection rates regardless of the order of the two input images for change detection. The DAG exploits all the combinations of joint features to avoid spectral information loss fed into an attention gate on the decoder side. The effectiveness of the proposed method was evaluated on the KOMPSAT-3 satellite images dataset and the aerial change detection dataset (CDD). Its performance was better than that of conventional methods (specifically, U-Net, ATTUNet, and Modified-UNet++) as it achieved average F1-score and kappa coefficient (KC) values of 0.68 and 66.93, respectively, for the KOMPSAT-3 dataset. For CDD, it achieved F1-score and KC values of 0.70 and 68.74, respectively, which are also better values than those achieved by conventional methods. In addition, we found that the proposed bilateral attention U-Net can provide the same changed map regardless of whether the image order is reversed.
Analysis of Thermally Induced Strain Effects on a Jointed Rock Mass through Microseismic Monitoring at the Acuto Field Laboratory (Italy)
Authors: Grechi Guglielmo , D’Angiò Danilo , Martino Salvatore
Published: February 2023

The study of the deformation of rock masses in response to near-surface thermal stresses is nowadays considered crucial in the field of geological risk mitigation. The superposition of heating and cooling cycles can influence the mechanical behavior of rock masses by inducing inelastic deformations that can trigger shallow slope instabilities, such as rockfalls and rock topples. This study reports the main outcomes obtained from the analysis of 20 month long microseismic monitoring at the Acuto field laboratory (Central Italy), where an integrated geotechnical and geophysical monitoring system has been operating since 2015. A preliminary event classification was performed through the analysis of time- and frequency-domain characteristic features of the extracted waveforms. Furthermore, the evolution of the local microseismicity was explored as a function of environmental factors (i.e., rock and air temperature, thermal gradients and ranges, and rainfalls) to highlight potential correlations. The here presented results highlight nontrivial insights into the role played by continuous near-surface temperature fluctuations and extreme thermal transients in influencing the stability of rock masses. In particular, the comparison of monitoring periods characterized by the most intense microseismic activity highlights a peculiar distribution of microseismicity during the heating and cooling phases of the rock mass in relation to different environmental conditions. These behaviors can be interpreted as the consequence of different driving mechanisms at the base of local failures.
Assessing the Impact of Resin Type, Post-Processing Technique, and Arch Location on the Trueness and Precision of 3D-Printed Full-Arch Implant Surgical Guides
Authors: Vara Rhea , Lin William , Low Jhi Kwan , Smith Derek , Grimm Antonio , Calvert Gareth , Tadakamadla Santosh Kumar , Alifui-Segbaya Frank , Ahmed Khaled E.
Published: February 2023

Objective: The purpose of this study was to assess the impact of photopolymer resin type, arch location, and post-processing techniques on the trueness and precision of three-dimensionally printed (3DP) full-arch surgical implant guides. Methods: Stereolithography reference images of an upper and lower surgical guide with six drill holes from a full-mouth rehabilitation clinical case were used. The files were imported into the Asiga MAX UV slicing software (Asiga Composer) where build orientation, print resolution, and support structures were added. A digital light processing 3D printer (MAX UV, Asiga Max) was used for printing the samples. The samples assessed were printed using two different, manufacturer-validated resins, DentaGuide (n = 35) and DentaClear (n = 20). The samples were subdivided and measured based on the post-processing technique used: handwashing (n = 20), sonication (n = 25), a mix of handwashing and sonication (n = 10), and post-curing using 385 nm UVA light with nitrogen (n = 50) or without nitrogen (n = 5). The diameter of each drill hole per guide was measured using a coordinate measuring machine (Absolute Arm 7-Axis, Hexagon) and compared with the reference STL to calculate each sample’s trueness (median error) and precision (interquartile range). The Mann–Whitney and Kruskal–Wallis tests were used for statistical analyses. Results: All samples demonstrated a dimensional error of <70 µm. No significant differences (p > 0.05) were observed between upper and lower arches and between post-processing techniques using nitrogen, irrespective of the use of hand- or ultrasonic washing. In contrast, DentaClear resin was significantly (p < 0.001) more accurate with a trueness of 26 µm and precision of 12 to 34 µm versus the DentaGuide at −31 µm and −54 to −17 µm, respectively. The samples post-cured without nitrogen were significantly (p < 0.05) the least accurate of all surgical guides, with a trueness of −42 µm and precision of −68 to −39 µm. Conclusion: The resin type and nitrogen post-processing are parameters that can significantly impact the accuracy of surgical guides. The tolerance of 3DP surgical guides needs to account for the dimensional changes occurring during the manufacturing process to minimise implant positioning errors.