bluuebunny/crossref_metadata_2025 huggingface dataset:
Bird-Strike Analysis on Hybrid Composite Fan Blade: Blade-Level Validation
Authors: Yella Gruhalakshmi , Jadhav Prakash , Lande Chhaya
Published: May 2023

Bird strikes have long been a source of concern for all airlines across the world. It is the most significant design criterion for aircraft engine fan blades. As it is not practical to manufacture and test aviation engines repeatedly for minor design modifications, simulation analysis can be used to investigate strategies to reduce the influence of a bird strike on a jet engine by employing proper design and manufacturing processes for blades. This study proposes using two fibers (hybrid) instead of the single-fiber composite blade presently in use to address delamination problems. As an idea validation test, the coupon-level analysis results are validated using a four-point bend test of similar-size coupons. Following this validation, dynamic analysis is used to investigate the impact behavior of a rectangular plate subjected to a bird strike. The current research focuses on analyzing bird strikes on a hybrid composite fan blade using blade-level models. This study concentrates on the position of the bird’s impact and the joint region length of two materials. The results show that the joint region with a 40% length of glass composite shows the optimum level of normalized interlaminar shear strain in all three impact locations.
Establishment and Calibration of Discrete Element Model for Buckwheat Seed Based on Static and Dynamic Verification Test
Authors: Li Guichuan , Li Haiyu , Li Xuan , Gong Zhichao , Yang Qinghua , Huang Yuxiang , Fu Zuoli
Published: May 2023

Aiming at the lack of accurate and reliable discrete element simulation parameters for the design of buckwheat metering devices and seeders based on the discrete element simulation method, an accurate buckwheat seed model was obtained by calibrating the discrete element simulation parameters. In this study, buckwheat seed particle models were established based on the manual and automatic filling methods. In order to improve the accuracy of the models, discrete element simulation parameters were calibrated, and the static cylinder-lifting test and dynamic seed-metering test were used to verify the simulation results. A 3D model of buckwheat seed was obtained using the CT scanning method, and a manual filling 7-sphere particle model and an automatic filling multi-sphere particle model were established. The physical parameters and contact parameters were measured using the uniaxial compression test, the drop test, and the friction coefficient measurement test. The Plackett–Burman test and steepest ascent path were used to obtain the optimal parameter combination based on the static cylinder-lifting test. We conducted dynamic seed-metering tests using the two particle models under the optimal parameter combination. The results show that, compared with the measured values of stacking angle, the relative errors of the simulation values of the manual filling 7-sphere and automatic filling 36-sphere particle models are 1.04% and 0.50%, respectively. When the rotation speed range of the seeding wheel is 20~60 r/min, the average relative errors between the simulated value and the measured value are 15.85% and 4.69%, respectively. When the effective working length range of the seeding wheel is 20~40 mm, the average relative errors between the simulated value and the measured value are 22.18% and 9.07%, respectively. Regardless of whether the manual filling 7-sphere or the automatic filling 36-sphere particle model of buckwheat seed was used for static motion parameter simulation or dynamic motion simulation, the automatic filling 36-sphere particle model has a higher accuracy. The buckwheat seed particle model established in this study will provide support for the design of buckwheat special seed-metering devices and improve the quality of buckwheat mechanized sowing operation.
Digestate Not Only Affects Nutrient Availability but Also Soil Quality Indicators
Authors: García-López Ana María , Delgado Antonio , Anjos Ofélia , Horta Carmo
Published: May 2023

Digestate contains many essential nutrients for crops, including nitrogen (N) and phosphorus (P), and it can alter the biogeochemical cycle of nutrients and soil functionality. This work aimed to assess the fertilizing effects of digestate on chemical and biological soil properties in a field experiment in eastern Portugal with two horticultural crops involving nine treatments: control without fertilization; mineral N fertilization with 85 kg ha−1; fertilization with digestate (DG) with increasing N rates (85, 170, 255, or 340 kg N ha−1); and fertilization with different combinations of digestate plus mineral N (DG at 85 or 170 kg N plus 60 kg mineral N ha–1 or DG at 170 kg N plus 25 kg mineral N ha–1). In addition to N, digestate supplied significant amounts of P, Ca, K, and Mg and significantly increased soil Olsen P, mineral N, and organic C. At high doses, it decreased phosphatase and β-glucosidase activities, as well as fungi and bacterial biomass, compared to the control or mineral N fertilization, and it also negatively affected soil P and C cycling capacity and microbial biomass. The organic to total N ratio and the N to P ratio in digestate are crucial properties for evaluating its agronomic management as fertilizer.
Genome-Wide Identification of NAC Genes Associated with Bast Fiber Growth in Ramie (Boehmeria nivea L.)
Authors: Zeng Zheng , Liu Chan , Zhang Xueyu , Zhu Siyuan , Wang Yanzhou , Liu Touming
Published: May 2023

NAM, ATAF, and CUC (NAC) proteins are plant-specific transcription factors that play crucial roles in fiber growth by regulating the secondary wall thickening. In this study, a systematical investigation of NAC genes was performed in the genome of ramie, an important fiber crop, resulting in a total of 60 ramie NAC genes identified. Phylogenetic analysis of these 60 NAC members in conjunction with 111 Arabidopsis NAC proteins identified 11 subfamilies, three of which showed considerable contraction in the ramie genome. Ten ramie NAC genes were identified to encode the orthologs of Arabidopsis NAC regulators involved in the control of secondary wall biosynthesis. Of these ten genes, most showed relatively high expression in the stems, and eight displayed a differential expression between the barks from the top and middle section of the stems where fiber growth is under different stages. Furthermore, the overexpression of three of these ten NAC genes significantly promoted fiber growth in transgenic Arabidopsis. These results indicated that these ten NAC genes were associated with the fiber growth of ramie. This study provided an important basis for researching the regulatory mechanism of fiber growth.
Soil Aggregates and Aggregate-Associated Carbon and Nitrogen in Farmland in Relation to Long-Term Fertilization on the Loess Plateau, China
Authors: Wang Jinjin , Sun Xu , Zhang Yuqing , Fang Yujing , Zhan Yizhe , Guo Ru , Qian Rui , Cai Tie , Liu Tiening , Jia Zhikuan , Chen Xiaoli , Ren Xiaolong
Published: May 2023

Soil aggregation plays a critical role in the maintenance of soil structure and crop productivity. Fertilization influences soil aggregation, especially by regulating soil organic carbon (SOC) and total nitrogen (TN) contents in aggregate fractions. Here, we conducted a fixed-site field experiment to quantify the effect of five N application rates: 0, 75, 150, 225, and 300 kg·N·ha−1, denoted as N0, N75, N150, N225, and N300, respectively, on soil aggregate stability, aggregate-associated SOC and TN sequestration and crop productivity. Soil aggregates were divided into >0.25 (>5, 5–2, 2–1, 1–0.5, 0.5–0.25) and <0.25 mm through wet and dry sieving methods. The results showed that long-term fertilization increased the proportion of macro-aggregates (>0.25 mm), decreased the proportion of micro-aggregates (<0.25 mm), and improved the aggregates stability. Compared with N0, the proportion of micro-aggregates in N225 was significantly decreased by 66.45% under wet sieving, while the proportion of >5 mm macro-aggregates in N225 was significantly increased by 19.24% under dry sieving (p < 0.05). With the increase in N application rate, the bulk SOC and TN contents first increased and then decreased, and the SOC and TN of N225 were significantly increased by 17.75% and 72.33% compared with N0 (p < 0.05). More specifically, fertilization promoted the distribution and enrichment of SOC and TN in macro-aggregates and reduced the C/N of the micro-aggregates and the contribution of SOC and TN in the micro-aggregates. Compared with N0, the contribution rate of macro-aggregates to SOC and TN of N225 under wet sieving was significantly increased by 84.13 and 17.18%, respectively, while the C/N of micro-aggregates of N225 under wet and dry sieving methods was significantly decreased by 45.95 and 31.74%, respectively (p < 0.05). Moreover, fertilization improved the yield, and N225 significantly increased the total yield by 80.68% compared with N0 (p < 0.05). In conclusion, N225 was the suitable N application for improving soil aggregate stability, carbon and nitrogen sequestration, and crop productivity on the Loess Plateau, China.
Untargeted UHPLC-MS Metabolomics Reveals the Metabolic Perturbations of Helicoverpa armigera under the Stress of Novel Insect Growth Regulator ZQ-8
Authors: Liu Caiyue , Yang Lin , Jin Fuqiang , Yin Yuelan , Xie Zizheng , Yang Longfei , Zhao Sifeng , Zhang Guoqiang , Yang Desong , Han Xiaoqiang
Published: May 2023

According to the previous research of our group, we found compound ZQ-8 ((1S,2R,4S)-1,3,3-trimethylbicyclo [2.2.1]heptan-2-yl-4-(tert-butyl)benzoate). This compound showed a strong growth inhibitory effect on Helicoverpa armigera by inhibiting chitinase 2 and endochitinase. To further understand the mechanism of ZQ-8 interfering with the growth and development of H. armigera, ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS) was utilized to analyze the metabolomics of the epidermis and viscera of H. armigera after ZQ-8 stress. The results revealed that the content of most metabolites was down-regulated after ZQ-8 treatment. Through the analysis of metabolic pathways, it was found that ZQ -8 mainly interfered with energy metabolism and amino acid biosynthesis pathways, which may be one of the important factors in which ZQ-8 caused the death of H. armigera larvae. Furthermore, ZQ-8 not only inhibits chitin degradation but also inhibits chitin synthesis in vivo. These findings provide new insights into a better understanding of the mechanism of action of ZQ-8.
Effects of a High-Concentrate Diet on the Blood Parameters and Liver Transcriptome of Goats
Authors: Wang Yusu , Li Qiong , Wang Lizhi , Liu Yuehui , Yan Tianhai
Published: May 2023

The objective of this study was to determine the effect of high-concentrate diets on the blood parameters and liver transcriptome of goats. Eighteen goats were allocated into three dietary treatments: the high level of concentrate (HC) group, the medium level of concentrate (MC) group, and the low level of concentrate (LC) group. The blood parameters and pathological damage of the gastrointestinal tract and liver tissues were measured. In hepatic portal vein blood, HC showed higher LPS, VFAs, and LA; in jugular vein blood, no significant differences in LPS, VFAs, and LA were recorded among groups (p > 0.05). Compared to the LC and MC groups, the HC group showed significantly increased interleukin (IL)-1β, IL-10, TNF-α, and diamine oxidase in jugular vein blood (p < 0.05). Liver transcriptome analysis discovered a total of 1269 differentially expressed genes (DEGs) among the three groups and most of them came from the HC vs. LC group. There were 333 DEGs up-regulated and 608 down-regulated in the HC group compared to the LC group. The gene ontology enrichment analysis showed that these DEGs were mainly focused on the regulation of triacylglycerol catabolism, lipoprotein particle remodeling, and cholesterol transport. The Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed that the liver of the HC group enhanced the metabolism of nutrients such as VFAs through the activation of AMPK and other signaling pathways and enhanced the clearance and detoxification of LPS by activating the toll-like receptor signaling pathway. A high-concentrate diet (HCD) can significantly promote the digestion of nutrients; the liver enhances the adaptability of goats to an HCD by regulating the expression of genes involved in nutrient metabolism and toxin clearance.
Bull Semen Obtained on Beef Farms by Electroejaculation: Sperm Quality in the First Two Hours of Storing with Different Extenders and Holding Temperatures
Authors: Pernas Santiago , Fernandez-Novo Aitor , Barrajon-Masa Clara , Mozas Patricia , Pérez-Villalobos Natividad , Martín-Maldonado Bárbara , Oliet Agustín , Astiz Susana , Pérez-Garnelo Sonia S.
Published: May 2023

Sperm quality decreases over time, so bull semen may need to be preserved after field collection. However, the effect of handling such semen samples from commercial farms and placing them in very short–term storage has not been elucidated. Therefore, ejaculate from 25 bulls from 1 dairy and 14 beef cattle farms were collected under farm conditions and evaluated for semen quality during the first two hours after collection. Two commercial extenders (AndroMed® and BIOXcell®) and two different storage temperatures (5 °C and room temperature) were used to evaluate the influence on semen quality and sperm kinetics in ejaculates grouped into three evaluation times, based on time since collection (Time 1: <75 min, n = 7; Time 2: 75–105 min, n = 11; and Time 3: 105–120 min, n = 7). Classical semen parameters, sperm motion kinetics by CASA and colony-forming units were assessed. The differences between both extenders in curvilinear and straight–line velocities (VCL and VSL) for the different time groups (Time 2 and Time 3) were statistically significant for p < 0.05. AndroMed® showed lower VSL, straightness and linearity in sperm compared to BIOXcell® (p < 0.05). In conclusion, AndroMed® induced more curvilinear movement, while BIOXcell® stimulated straighter motility.
Canine Mammary Tumor Histopathological Image Classification via Computer-Aided Pathology: An Available Dataset for Imaging Analysis
Authors: Burrai Giovanni P. , Gabrieli Andrea , Polinas Marta , Murgia Claudio , Becchere Maria Paola , Demontis Pierfranco , Antuofermo Elisabetta
Published: May 2023

Histopathology, the gold-standard technique in classifying canine mammary tumors (CMTs), is a time-consuming process, affected by high inter-observer variability. Digital (DP) and Computer-aided pathology (CAD) are emergent fields that will improve overall classification accuracy. In this study, the ability of the CAD systems to distinguish benign from malignant CMTs has been explored on a dataset—namely CMTD—of 1056 hematoxylin and eosin JPEG images from 20 benign and 24 malignant CMTs, with three different CAD systems based on the combination of a convolutional neural network (VGG16, Inception v3, EfficientNet), which acts as a feature extractor, and a classifier (support vector machines (SVM) or stochastic gradient boosting (SGB)), placed on top of the neural net. Based on a human breast cancer dataset (i.e., BreakHis) (accuracy from 0.86 to 0.91), our models were applied to the CMT dataset, showing accuracy from 0.63 to 0.85 across all architectures. The EfficientNet framework coupled with SVM resulted in the best performances with an accuracy from 0.82 to 0.85. The encouraging results obtained by the use of DP and CAD systems in CMTs provide an interesting perspective on the integration of artificial intelligence and machine learning technologies in cancer-related research.
Pleiotropic Signaling by Reactive Oxygen Species Concerted with Dietary Phytochemicals and Microbial-Derived Metabolites as Potent Therapeutic Regulators of the Tumor Microenvironment
Authors: Murai Toshiyuki , Matsuda Satoru
Published: May 2023

The excessive generation of reactive oxygen species (ROS) plays a pivotal role in the pathogenesis of diseases. ROS are central to cellular redox regulation and act as second messengers to activate redox-sensitive signals. Recent studies have revealed that certain sources of ROS can be beneficial or harmful to human health. Considering the essential and pleiotropic roles of ROS in basic physiological functions, future therapeutics should be designed to modulate the redox state. Dietary phytochemicals, microbiota, and metabolites derived from them can be expected to be developed as drugs to prevent or treat disorders in the tumor microenvironment.
Metabolic Functions of Biliverdin IXβ Reductase in Redox-Regulated Hematopoietic Cell Fate
Authors: Bahou Wadie F. , Marchenko Natalia , Nesbitt Natasha M.
Published: May 2023

Cytoprotective heme oxygenases derivatize heme to generate carbon monoxide, ferrous iron, and isomeric biliverdins, followed by rapid NAD(P)H-dependent biliverdin reduction to the antioxidant bilirubin. Recent studies have implicated biliverdin IXβ reductase (BLVRB) in a redox-regulated mechanism of hematopoietic lineage fate restricted to megakaryocyte and erythroid development, a function distinct and non-overlapping from the BLVRA (biliverdin IXα reductase) homologue. In this review, we focus on recent progress in BLVRB biochemistry and genetics, highlighting human, murine, and cell-based studies that position BLVRB-regulated redox function (or ROS accumulation) as a developmentally tuned trigger that governs megakaryocyte/erythroid lineage fate arising from hematopoietic stem cells. BLVRB crystallographic and thermodynamic studies have elucidated critical determinants of substrate utilization, redox coupling and cytoprotection, and have established that inhibitors and substrates bind within the single-Rossmann fold. These advances provide unique opportunities for the development of BLVRB-selective redox inhibitors as novel cellular targets that retain potential for therapeutic applicability in hematopoietic (and other) disorders.
Effects of Leading Signals on Metrics of Control Quality Indicators
Authors: Kephart Richard , Plamowski Sebastian , Domański Paweł D.
Published: May 2023

The paper demonstrates the influence of leading variables on the quality evaluation of the operation of univariate control loops of a multi-loop control system used in a 1000 MW power unit. We analyse the course of the setpoint and process values, the calculated value of the control signal and the disturbances values and leading variables. The variables that determine the operating point of the object are used as leading variables. In the case of a power unit, the main leading variable is the power setpoint at which the unit operates. The power setpoint determines the flow of fuel, air and steam—the values of these variables were also considered in the control qualityassessment. Methods based on the characteristics of control signals and error values (residual) are used in the loop control quality assessment. Basic metrics, such as mean error, mean absolute error and mean squared error, are used to analyse the control error. In addition, statistical measures in the form of higher degree moments are applied using the difference in their estimations. The study indicates that once the leading signal values are taken into account during the assessment, the risk of incorrectly interpreting decreased values for the considered indicators is minimized. It is shown that it is important to consider the values of leading variables because they determine the operating point. Particular attention is paid to changes in the leading values since they affect the process conditions. This paper discusses mechanisms that could allow control quality to be monitored both under stable operating conditions and during operating point changes. It is shown that even relatively simple metrics can give very good results when leading signals are considered.
Semi-Supervised Learning for Robust Emotional Speech Synthesis with Limited Data
Authors: Zhang Jialin , Wushouer Mairidan , Tuerhong Gulanbaier , Wang Hanfang
Published: May 2023

Emotional speech synthesis is an important branch of human–computer interaction technology that aims to generate emotionally expressive and comprehensible speech based on the input text. With the rapid development of speech synthesis technology based on deep learning, the research of affective speech synthesis has gradually attracted the attention of scholars. However, due to the lack of quality emotional speech synthesis corpus, emotional speech synthesis research under low-resource conditions is prone to overfitting, exposure error, catastrophic forgetting and other problems leading to unsatisfactory generated speech results. In this paper, we proposed an emotional speech synthesis method that integrates migration learning, semi-supervised training and robust attention mechanism to achieve better adaptation to the emotional style of the speech data during fine-tuning. By adopting an appropriate fine-tuning strategy, trade-off parameter configuration and pseudo-labels in the form of loss functions, we efficiently guided the learning of the regularized synthesis of emotional speech. The proposed SMAL-ET2 method outperforms the baseline methods in both subjective and objective evaluations. It is demonstrated that our training strategy with stepwise monotonic attention and semi-supervised loss method can alleviate the overfitting phenomenon and improve the generalization ability of the text-to-speech model. Our method can also enable the model to successfully synthesize different categories of emotional speech with better naturalness and emotion similarity.
Early Predictability of Grasping Movements by Neurofunctional Representations: A Feasibility Study
Authors: Jakubowitz Eike , Feist Thekla , Obermeier Alina , Gempfer Carina , Hurschler Christof , Windhagen Henning , Laves Max-Heinrich
Published: May 2023

Human grasping is a relatively fast process and control signals for upper limb prosthetics cannot be generated and processed in a sufficiently timely manner. The aim of this study was to examine whether discriminating between different grasping movements at a cortical level can provide information prior to the actual grasping process, allowing for more intuitive prosthetic control. EEG datasets were captured from 13 healthy subjects who repeatedly performed 16 activities of daily living. Common classifiers were trained on features extracted from the waking-state frequency and total-frequency time domains. Different training scenarios were used to investigate whether classifiers can already be pre-trained by base networks for fine-tuning with data of a target person. A support vector machine algorithm with spatial covariance matrices as EEG signal descriptors based on Riemannian geometry showed the highest balanced accuracy (0.91 ± 0.05 SD) in discriminating five grasping categories according to the Cutkosky taxonomy in an interval from 1.0 s before to 0.5 s after the initial movement. Fine-tuning did not improve any classifier. No significant accuracy differences between the two frequency domains were apparent (p > 0.07). Neurofunctional representations enabled highly accurate discrimination of five different grasping movements. Our results indicate that, for upper limb prosthetics, it is possible to use them in a sufficiently timely manner and to predict the respective grasping task as a discrete category to kinematically prepare the prosthetic hand.
Applying the DEMATEL−ANP Fuzzy Comprehensive Model to Evaluate Public Opinion Events
Authors: Wang Hua , Luo Ling , Liu Tao
Published: May 2023

Network public opinion is a mirror reflecting people’s will, and evaluating its urgency can help to find hidden social crises. Research on public opinion in the field of machine learning usually focuses on micro-sentiment judgment, which is unable to offer support for the evaluation of public opinion events without additional data, and research from the perspective of artificial weighting has the disadvantage of the confusion of explanation. Judging the urgency of public opinion events is usually based on human perception, which is fuzzy and conforms to the attribute of fuzzy mathematics. Therefore, the index system in this paper was constructed in line with five principles, from which the weights were scientifically evaluated by integrating the DEMATEL and ANP model, and fuzzy mathematics was applied to determine the urgency level of public opinion. The result has three-fold significance. First, the index system constructed was more closely linked. Second, the integration of the DEMATEL and ANP weight calculating model took the interdependence of indicators fully into account. Third, fuzzy mathematics provided support for determining the public opinion crisis level, especially in the absence of immediate dissemination data.
A Three-Dimensional Elastoplastic Constitutive Model for Geomaterials
Authors: Tian Dongshuai , Zheng Hong
Published: May 2023

The Mohr-Coulomb (M-C) failure criterion has been a popular choice for geotechnical analysis because of its simplicity and ease of use. The fact that the M-C criterion disregards the intermediate principal stress’s impact is a significant drawback. As a result, the M-C criterion is only applied to materials under biaxial stress. This paper presents a three-dimensional version of the M-C criterion. The proposed criterion, called the Generalized Mohr-Coulomb (GMC) criterion, considers the intermediate principal stress’s effect, in addition to inheriting the original M-C criterion’s benefits. We obtained the conditions that the strength parameters must satisfy when the GMC criterion fulfills the π plane’s convexity. The GMC criterion can better describe geotechnical materials’ strengths under general stress conditions. Based on an implicit algorithm, the user material subroutine (UMAT) of the three-dimensional GMC model was developed in ABAQUS using the Fortran programming language. The established elastoplastic model’s validity and the program’s accuracy were examined using numerical simulation. Finally, a numerical simulation of a three-dimensional tunnel excavation under various working conditions was performed. The calculation results from the GMC model are precise and have some engineering-related practical significance.
Hysteresis in Organic Electrochemical Transistors: Relation to the Electrochemical Properties of the Semiconductor
Authors: Shameem Raufar , Bongartz Lukas M. , Weissbach Anton , Kleemann Hans , Leo Karl
Published: May 2023

The ability to bridge ionic and electronic transport coupled with large volumetric capacitance renders organic electrochemical transistors (OECTs) ideal candidates for bioelectronic applications. Adopting ionic-liquid-based solid electrolytes extends their applicability and facilitates large-area printable productions. However, OETCs employing solid electrolytes tend to show a pronounced hysteresis in the transfer curve. A detailed understanding of the hysteresis is crucial for their accurate characterizations and reliable applications. Here, we demonstrated fully photopatternable poly(3,4-ethylenedioxythiophene):tosylate (PEDOT:Tos)- based OECTs incorporating the ionic liquid [EMIM][EtSO4] in a solid electrolyte (SE). The PEDOT:Tos films deposited through vapor phase polymerization (VPP) were annealed for different durations after the polymerization step. Upon rinsing with ethanol and the deposition of the SE, the OECTs made of these films showed impressive bias stress stability under prolonged operation cycles, a high switching ratio, a low threshold voltage, and a high transconductance. Furthermore, by taking transfer measurements with different sweep rates, we revealed two distinct regimes of hysteresis: kinetic hysteresis and non-kinetic hysteresis. We observed pronounced changes in these regimes after annealing. Finally, impedance spectroscopy exhibited that the PEDOT:Tos turned from a Faradaic to a non-Faradaic response through annealing, explaining the observed hysteresis changes in both regimes.
On the Evaluation of Complex Networks Designs for an Energy-Efficient IP/WDM Core Network
Authors: Hammadi Ali A. , Nasralla Zaid H.
Published: May 2023

As the Internet grows in capacity, the energy consumption of Information and Communication Technologies (ICT) are significantly increasing. Significant research efforts on energy conservation have been devoted to devise different technological solutions to address raised concerns surrounding the power consumption of networking equipment and its impact firstly on the emission of greenhouse gases and secondly on electricity bills. In this work, we investigate energy-efficient physical topologies for NSF IP over wavelength-division multiplexing (WDM) network for the purpose of minimizing energy consumption by redesigning its current physical connectivity. We implement different network topologies, such as implementing the small-world, scale-free (SFN), and random networks on the NSF network, then evaluate and compare its physical properties and network power consumption with the current NSF topology design using a mixed-integer linear programming model, all with the aim of minimizing the network total power consumption. The evaluation shall optimize and minimize the embodied energy consumption of network equipment in the IP and optical layers. Results have demonstrated that the implementation of the proposed energy-minimized topology designs can significantly improve the node’s clustering coefficient, reduce network’s diameter, and reduce energy consumption of the NSF IP over WDM network to 28% if compared with the current design implementation.
Influence of Stray Current on Fastening System Components in Urban Railway Tracks
Authors: Vranešić Katarina , Lakušić Stjepan , Serdar Marijana
Published: May 2023

Urban railway tracks are the primary modes of transportation in many cities worldwide. Track vehicles mostly use DC from overhead lines, and rails are used as return conductors. Because it is challenging to fully insulate the rail and ensure high rail-to-ground resistance, current leaks from the rail to the lower part of the track. This current is referred to as stray current. To determine the detrimental effects of stray current on the rail and fastening system components, we performed a laboratory simulation of the stray current on four real-scale samples of the entire rail with all fastening components. The difference among these four samples was the type of fastening system used. Tests were performed under dry condition and at different water levels. After testing, the samples were visually inspected. Under dry conditions, corrosion occurred on the elements in contact with the concrete, and under immersed conditions, the current leaked from all components of the fastening system directly into the water, causing harmful local deterioration. The characteristics of the fastening systems are defined to satisfy other parameters, but not to prevent stray currents and ensure high rail-to-ground resistance. The aim of this study was to demonstrate the effects of stray current on the rail and fastening system and to prove the importance of providing adequate drainage of the track and using a fastening system that is insulated and does not allow the current to leak from the rail.
Resource Management in FlexSim Modelling: Addressing Drawbacks and Improving Accuracy
Authors: Deng Jyhjeng
Published: May 2023

The use of resources is an excellent concept for solving the contradiction problem in the Theory of Inventive Problem Solving (TRIZ; Russian acronym) methodology. However, it is always assumed that a proposed solution that uses external resources is elegant and perfect. This paper presents an example of simulation 3D modelling using FlexSim, which shows that the use of external resources can give rise to inaccurate waiting times in a queue. This paper provides an alternative process flow model in FlexSim to remove this drawback and show that, when solving the contradiction problem in TRIZ using external resources, one needs to consider the function replacement of an object and consideration should also be given to the measurement of the performance of other objects. To the best of our recalled knowledge, this paper is probably the first attempt to apply the resource concept to the simulation model. Three levels of resource are developed through the contradiction matrix of a technical contradiction in the default usage of resources in the simulation model. These resources can progressively reduce the measurement errors in waiting time and are easily ignored by simulation programmers.
Multi-Hop Question Generation with Knowledge Graph-Enhanced Language Model
Authors: Li Zhenping , Cao Zhen , Li Pengfei , Zhong Yong , Li Shaobo
Published: May 2023

The task of multi-hop question generation (QG) seeks to generate questions that require a complex reasoning process that spans multiple sentences and answers. Beyond the conventional challenges of what to ask and how to ask, multi-hop QG necessitates sophisticated reasoning from dispersed evidence across multiple sentences. To address these challenges, a knowledge graph-enhanced language model (KGEL) has been developed to imitate human reasoning for multi-hop questions.The initial step in KGEL involves encoding the input sentence with a pre-trained GPT-2 language model to obtain a comprehensive semantic context representation. Next, a knowledge graph is constructed using the entities identified within the context. The critical information in the graph that is related to the answer is then utilized to update the context representations through an answer-aware graph attention network (GAT). Finally, the multi-head attention generation module (MHAG) is performed over the updated latent representations of the context to generate coherent questions. Human evaluations demonstrate that KGEL generates more logical and fluent multi-hop questions compared to GPT-2. Furthermore, KGEL outperforms five prominent baselines in automatic evaluations, with a BLEU-4 score that is 27% higher than that of GPT-2.
Assessment of the Impact of Anthropogenic Drainage of Raised Peat-Bog on Changing the Physicochemical Parameters and Migration of Atmospheric Fallout Radioisotopes in Russia’s Subarctic Zone (Subarctic Zone of Russia)
Authors: Yakovlev Evgeny , Orlov Alexander , Kudryavtseva Alina , Zykov Sergey , Zubov Ivan
Published: May 2023

This paper reports on the research results of the radioactivity levels and upward dispersion of radionuclides of atmospheric fallout 210Pb, 137Cs, 241Am and 234,238U as well as key physicochemical parameters in a peat deposit subjected to drainage in 1969–1971. It was found that drainage of the peat bog led the natural moisture content to shrink in the peat. Active aeration in the peat deposit, accompanied by the growth of Eh, raises the strength of oxidative transformation processes of the organic part of the peat, leading to higher levels of peat degradation and major variations in the elemental content. Changes in these parameters affect the behaviour of radionuclides in the peat section. Thus, in contrast to the sites with a natural hydrological regime, within the dried peat deposit a geochemical barrier of sorption type is not formed, capable of retaining a significant proportion of 137Cs. In this connection, there is an acceleration of 137Cs migration. In addition, changes in the hydrological regime led to the predominance of vascular plants with a more developed root system than that of sphagnum, which also contributed to a more intense transfer of 137Cs by the root system up the section. The findings of 210Pb dating of the dried peat bog showed a significantly lower peat accumulation rate compared to the natural bog massif (0.15 ± 0.02 vs. 0.48 ± 0.08 cm/year). A factor examination of the dataset demonstrated that the leading role in the distribution of radionuclides belongs to redox and acid-base conditions, which have changed significantly after draining the peat deposit.
Wave-Shaped Microstructure Cancer Detection Sensor in Terahertz Band: Design and Analysis
Authors: Khan Md Rezaul Hoque , Chowdhury Atiqul Alam , Islam Mohammad Rakibul , Hosen Md Sanowar , Mim Mhamud Hasan , Nishat Mirza Muntasir
Published: May 2023

For the quick identification of diverse types of cancer/malignant cells in the human body, a new hollow-core optical waveguide based on Photonic Crystal Fiber (PCF) is proposed and numerically studied. The refractive index (RI) differs between normal and cancerous cells, and it is through this distinction that the other crucial optical parameters are assessed. The proposed cancer cell biosensor’s guiding characteristics are examined in the COMSOL Multiphysics v5.5 environment. The Finite Element Method (FEM) framework is used to quantify the display of the suggested fiber biosensor. Extremely fine mesh elements are additionally added to guarantee the highest simulation accuracy. The simulation results on the suggested sensor model achieve a very high relative sensitivity of 99.9277%, 99.9243%, 99.9302%, 99.9314%, 99.9257% and 99.9169%, a low effective material loss of 8.55×10−5 cm−1, 8.96×10−5 cm−1, 8.24×10−5 cm−1, 8.09×10−5 cm−1, 8.79×10−5 cm−1, and 9.88×10−5 cm−1 for adrenal gland cancer, blood cancer, breast cancer type-1, breast cancer type-2, cervical cancer, and skin cancer, respectively, at a 3.0 THz frequency regime. A very low confinement loss of 6.1×10−10 dB/cm is also indicated by the simulation findings for all of the cancer cases that were mentioned. The straightforward PCF structure of the proposed biosensor offers a high likelihood of implementation when used in conjunction with these conventional performance indexes. So, it appears that this biosensor will create new opportunities for the identification and diagnosis of various cancer cells.
Multi-Feature Fusion Method for Chinese Shipping Companies Credit Named Entity Recognition
Authors: He Lin , Wang Shengnan , Cao Xinran
Published: May 2023

Shipping Enterprise Credit Named Entity Recognition (NER) aims to recognize shipping enterprise credit entities from unstructured shipping enterprise credit texts. Aiming at the problem of low entity recognition rate caused by complex and diverse entities and nesting phenomenon in the field of shipping enterprise credit, a deep learning method based on multi-feature fusion is proposed to improve the recognition effect of shipping enterprise credit entities. In this study, the shipping enterprise credit dataset is manually labeled using the BIO labeling model, combining the pre-trained model Bidirectional Encoder Representations from Transformers (BERT) and bidirectional gated recurrent unit (BiGRU) with conditional random field (CRF) to form the BERT-BiGRU-CRF model, and changing the input of the model from a single feature vector to a multi-feature vector (MF) after stitching character vector features, word vector features, word length features, and part-of-speech (pos) features; BiGRU is introduced to extract the contextual features of shipping enterprise credit texts. Finally, CRF completes the sequence annotation task. According to the experimental results, using the BERT-MF-BiGRU-CRF model for NER of shipping enterprise credit text data, the F1 Score (F1) reaches 91.7%, which is 8.37% higher than the traditional BERT-BiGRU-CRF model. The experimental results show that the BERT-MF-BiGRU-CRF model can effectively perform NER for shipping enterprise credit text data, which is helpful to construct a credit knowledge graph for shipping enterprises, while the research results can provide references for complex entities and nested entities recognition in other fields.
Electron Impact Ionization Cross-Section Maxima of Atoms
Authors: dos Santos Antônio Carlos Fontes , Tőkési Károly
Published: May 2023

Using measured cross-sections and polarizability data, an empirical scaling law is extracted for the electron collision single-ionization cross-section maxima of neutral atoms. We found that the cross sections scale linearly with the target’s static polarizability. We confirm this observation using our present three-body classical trajectory Monte Carlo simulations.
Special Issue for the 10th Anniversary of Axioms: Logic
Authors: Castillo Oscar
Published: May 2023

Published for the first time in 2012, Axioms is celebrating its 10th anniversary [...]
Fruit Juice Consumption, Body Mass Index, and Adolescent Diet Quality in a Biracial Cohort
Authors: Moore Lynn L. , Zhou Xinyi , Wan Li , Singer Martha R. , Bradlee M. Loring , Daniels Stephen R.
Published: May 2023

Fruit juice consumption during childhood remains controversial. Here, we evaluated the association between preadolescent 100% fruit juice intake and later adolescent diet quality and body mass index (BMI). We used prospective data over 10 years from the National Growth and Health Study for 1921 black and white girls, ages 9–10 years at baseline, for analyses of diet quality, and 2165 girls for BMI analyses. Statistical analyses included repeated measures analysis of variance and logistic regression models. Girls who drank ≥1.0 cup/day of fruit juice in preadolescence consumed 0.44 cup/day more total fruit in later adolescence than non-juice-drinking girls (p < 0.0001). White and black girls who drank ≥1.25 cups/day in preadolescence were 2.62 (95% CI: 1.35–5.08) and 2.54 (1.27–5.07) times more likely, respectively, to meet the Dietary Guidelines for whole fruit by later adolescence than those with the lowest juice intakes. Further, fruit juice consumption was positively associated with diet quality scores. Overall, girls consuming ≥1.25 cups/day of juice had a BMI in late adolescence that was 1.7 kg/m2 lower than that of non-juice-drinking girls. In conclusion, early adolescent fruit juice intake was positively associated with subsequent whole fruit consumption, better diet quality, and lower BMI in later adolescence.
Empowering Hand Rehabilitation with AI-Powered Gesture Recognition: A Study of an sEMG-Based System
Authors: Guo Kai , Orban Mostafa , Lu Jingxin , Al-Quraishi Maged S. , Yang Hongbo , Elsamanty Mahmoud
Published: May 2023

Stroke is one of the most prevalent health issues that people face today, causing long-term complications such as paresis, hemiparesis, and aphasia. These conditions significantly impact a patient’s physical abilities and cause financial and social hardships. In order to address these challenges, this paper presents a groundbreaking solution—a wearable rehabilitation glove. This motorized glove is designed to provide comfortable and effective rehabilitation for patients with paresis. Its unique soft materials and compact size make it easy to use in clinical settings and at home. The glove can train each finger individually and all fingers together, using assistive force generated by advanced linear integrated actuators controlled by sEMG signals. The glove is also durable and long-lasting, with 4–5 h of battery life. The wearable motorized glove is worn on the affected hand to provide assistive force during rehabilitation training. The key to this glove’s effectiveness is its ability to perform the classified hand gestures acquired from the non-affected hand by integrating four sEMG sensors and a deep learning algorithm (the 1D-CNN algorithm and the InceptionTime algorithm). The InceptionTime algorithm classified ten hand gestures’ sEMG signals with an accuracy of 91.60% and 90.09% in the training and verification sets, respectively. The overall accuracy was 90.89%. It showed potential as a tool for developing effective hand gesture recognition systems. The classified hand gestures can be used as a control command for the motorized wearable glove placed on the affected hand, allowing it to mimic the movements of the non-affected hand. This innovative technology performs rehabilitation exercises based on the theory of mirror therapy and task-oriented therapy. Overall, this wearable rehabilitation glove represents a significant step forward in stroke rehabilitation, offering a practical and effective solution to help patients recover from stroke’s physical, financial, and social impact.
Nanocurcumin Release from Self-Cured Acrylic Resins; Effects on Antimicrobial Action and Flexural Strength
Authors: Soleymanijadidi Parsa , Moradi Meysam , Hamedirad Fahimeh , Ghanavati Zahra , Maleki Dizaj Solmaz , Salatin Sara
Published: May 2023

The placement of orthodontic appliances into the oral area can lead to infection, inflammatory and gingival collapse. Using an antimicrobial and anti-inflammatory material in the matrix of orthodontic appliance may help to reduce these issues. This study aimed to assess the release pattern, the antimicrobial action and the flexural strength of self-cured acrylic resins after adding different weight percentages of curcumin nanoparticles (nanocurcumin). In this in-vitro study, 60 acrylic resin samples were divided into five groups (n = 12) based on the weight percentage of curcumin nanoparticles added to the acrylic powder (0 for control, 0.5, 1, 2.5, and 5%). Then, the dissolution apparatus was used for the release assessment of nanocurcumin form the resins. For antimicrobial action assessment, the disk diffusion method was used and a three-point bending test was performed with a speed of 5 mm/min to determine the flexural strength. Data were analyzed using one-way analysis of variance (ANOVA) and Post-Hoc Tukey tests (with p < 0.05 as significant level). The microscopic images showed the homogeny distribution of nanocuricumin in self-cured acrylic resins in varied concentrations. The release pattern showed a two-step release pattern for all concentrations of nanocurcumin. The one-way ANOVA outcomes indicated that adding curcumin nanoparticles to self-cured resin increased the diameter of the inhibition zones for the groups against Streptococcus mutans (S. mutans) significantly (p < 0.0001). Additionally, as the weight percentage of curcumin nanoparticles increased, the flexural strength decreased (p < 0.0001). However, all strength values were higher than the standard value (50 MPa). No significant difference was detected between the control group and the group with 0.5 percent (p = 0.57). Considering the proper release pattern and the potent antimicrobial activity of curcumin nanoparticles, then the preparing self-cured resins containing curcumin nanoparticles can be beneficial for antimicrobial aims without damaging the flexural strength to use in orthodontic removable applications.
Analysis of the Robotic-Based In Situ Bioprinting Workflow for the Regeneration of Damaged Tissues through a Case Study
Authors: Fortunato Gabriele Maria , Sigismondi Sofia , Nicoletta Matteo , Condino Sara , Montemurro Nicola , Vozzi Giovanni , Ferrari Vincenzo , De Maria Carmelo
Published: May 2023

This study aims to critically analyse the workflow of the in situ bioprinting procedure, presenting a simulated neurosurgical case study, based on a real traumatic event, for collecting quantitative data in support of this innovative approach. After a traumatic event involving the head, bone fragments may have to be removed and a replacement implant placed through a highly demanding surgical procedure in terms of surgeon dexterity. A promising alternative to the current surgical technique is the use of a robotic arm to deposit the biomaterials directly onto the damaged site of the patient following a planned curved surface, which can be designed pre-operatively. Here we achieved an accurate planning-patient registration through pre-operative fiducial markers positioned around the surgical area, reconstructed starting from computed tomography images. Exploiting the availability of multiple degrees of freedom for the regeneration of complex and also overhanging parts typical of anatomical defects, in this work the robotic platform IMAGObot was used to regenerate a cranial defect on a patient-specific phantom. The in situ bioprinting process was then successfully performed showing the great potential of this innovative technology in the field of cranial surgery. In particular, the accuracy of the deposition process was quantified, as well as the duration of the whole procedure was compared to a standard surgical practice. Further investigations include a biological characterisation over time of the printed construct as well as an in vitro and in vivo analysis of the proposed approach, to better analyse the biomaterial performances in terms of osteo-integration with the native tissue.