bluuebunny/crossref_metadata_2025 huggingface dataset:
Region-wise analysis of beef cow movements in Japan
Authors: Murato Yoshinori , Hayama Yoko , Kondo Sonoko , Sawai Kotaro , Yamaguchi Emi , Yamamoto Takehisa
Published: February 2023

Animal movement is an important factor in the transmission of animal infectious diseases. A better understanding of movement patterns is therefore necessary for developing effective control measures against disease spread. In Japan, a cattle tracing system was established in 2003, following a bovine spongiform encephalopathy epidemic, and the information on all cattle movements has been stored in a national database maintained by the National Livestock Breeding Center. Using these data, we previously analyzed the movement of dairy cows, concluding that heterogeneities in cattle movement are associated with regional and seasonal factors. In the present study, we aimed to identify specific factors affecting the regional and seasonal movement patterns of beef cows in Japan. From April 2012 to March 2017, 797,553 farm-to-farm movement events were recorded. We analyzed movements by month and by cattle age and looked at the frequency of movement within and between seven regions spanning the national territory. Our results show that calf movement peaked at 9–10 months old; these movements were considered to be via the market and were frequent within and between regions. For inter-regional movements, Kyushu region was the top producer of calves for calf trading markets throughout Japan. With regard to intra-regional movements, round-trip movements for summer grazing were observed in May and October for cattle of various ages in the northern regions, especially Hokkaido and Tohoku. Moreover, the movements of Japanese Shorthorn breeds in Tohoku region exhibited consistent annual peaks in May and October/November, in accordance with their seasonal breeding practice. In the areas with high relative densities of dairy cows, such as Hokkaido, the shipping of newborn beef calves produced via embryo transfer to dairy cows was also observed. Overall, understanding the patterns of beef cow movement will help develop effective disease surveillance measures, such as pre-movement inspections focused on specific regions and types of movement.
Genetic diversity among reptilian orthoreoviruses isolated from pet snakes and lizards
Authors: Varga-Kugler Renáta , Ihász Katalin , Marton Szilvia , Kaszab Eszter , Marschang Rachel E. , Farkas Szilvia , Bányai Krisztián
Published: February 2023

Reovirus infections in reptiles are frequently detected and associated with various clinical diseases; yet, our knowledge about their genetic diversity and evolutionary relationships remains limited. In this study, we characterize at the genomic level five reptile origin orthoreovirus strains isolated from exotic snakes and lizards in Hungary and Germany. The genomic organization of the study strains was similar to that of the representative strains of reptile origin reoviruses belonging to species Reptilian orthoreovirus and Testudine orthoreovirus. Additionally, all five study strains clustered with the bush viper origin reference Reptilian orthoreovirus strain, 47/02. The nucleotide sequence divergence among strains fell from 56.64 to 99.36%. Based on genome segment constellations two well separated groups were observed, which may represent two genetic lineages of reptilian orthoreoviruses we tentatively referred here as genogroups, classifying two squamata origin strains with available whole genome sequences into genogroup I (GGI) and four strains into genogroup II (GGII). The representative GGI and GGII Reptilian orthoreovirus strains are characterized by moderate-to-high nucleotide and amino acid similarities within genogroups (range, 69.45 to 99.36% and 74.64 to 100.00%), whereas lower nucleotide and amino acid similarities (range, 56.64 to 77.24% and 54.53 to 93.85%) and different structures of the bicistronic S1 segment were found between genogroups. Further studies are needed to explore the genomic diversity among reptilian reoviruses of squamata origin; this would be critical to establish a robust classification system for these viruses and to see if interaction among members of distinct lineages may result in viable progenies with novel genetic features.
The metabolic differences of anestrus, heat, pregnancy, pseudopregnancy, and lactation in 800 female dogs
Authors: Ottka Claudia , Vapalahti Katariina , Arlt Sebastian P. , Bartel Alexander , Lohi Hannes
Published: February 2023

Introduction

Reproduction causes major hormonal and physiological changes to the female body. However, the metabolic changes occurring during canine reproduction are scarcely studied.

Methods

In this cross-sectional study, we assessed the metabolic effects of canine reproductive status using a 1H NMR metabolomics platform optimized and validated for canine use. The study population consisted of a total of 837 healthy, intact female dogs in breeding age, of which 663 dogs were in anestrus, 78 in heat, 43 were pseudopregnant, 15 were pregnant, and 38 were lactating. The differences in metabolite profiles between these states were studied by the Kruskal-Wallis test with post-hoc tests performed using the Dunn's test, and visualized by box plots and a heatmap. The ability of the metabolite profile to differentiate pregnant dogs from non-pregnant ones was assessed by creating a multivariate Firth logistic regression model using forward stepwise selection.

Results

Lactation, pregnancy and heat all were associated with distinct metabolic changes; pregnancy caused major changes in the concentrations of glycoprotein acetyls, albumin and creatinine, and smaller changes in several lipids, citrate, glutamine, and alanine. Pseudopregnancy, on the other hand, metabolically largely resembled anestrus. Lactation caused major changes in amino acid concentrations and smaller changes in several lipids, albumin, citrate, creatinine, and glycoprotein acetyls. Heat, referring to proestrus and estrus, affected cholesterol and LDL metabolism, and increased HDL particle size. Albumin and glycoprotein acetyls were the metabolites included in the final multivariate model for pregnancy detection, and could differentiate pregnant dogs from non-pregnant ones with excellent sensitivity and specificity.

Discussion

These results increase our understanding of the metabolic consequences of canine reproduction, with the possibility of improving maternal health and ensuring reproductive success. The identified metabolites could be used for confirming canine pregnancy.
The Burden of Suicide Mortality in Poland: A 20-Year Register-Based Study (2000–2019)
Authors: Pikala Małgorzata , Burzyńska Monika
Published: February 2023

Objectives: The aim of the study was to assess mortality trends due to suicide in Poland in the years 2000–2019 with the use of joinpoint regression.

Methods: The study analysed all suicide deaths in Poland in the years 2000–2019 (N = 113,355). Age-standardised death rates (SDRs), the annual percentage change (APC) and the average annual percentage change (AAPC) were determined.

Results: In the male group, SDR was 29.3 in 2000 and 21.6 in 2019, in the female group, SDR decreased from 5.2 to 3.0. In 2019, the highest SDR values were noted in the group aged between 45 and 64 years. The most common method of suicide was hanging. In 2019, odds ratios (OR) of death due to suicide for age groups 15–24 years vs. 65 years or above were 51.47 among men and 181.89 among women. With regards to primary vs. tertiary education, OR values were 1.08 and 0.25, respectively; for single vs. widowed individuals 8.22 and 12.35; while for rural vs. urban residents 1.60 and 1.15.

Conclusion: There is a need to implement educational programmes, primarily designed for young people.
FEM-BEM Vibroacoustic Simulations of Motion Driven Cymbal-Drumstick Interactions
Authors: Kaselouris Evaggelos , Paschalidou Stella , Alexandraki Chrisoula , Dimitriou Vasilis
Published: February 2023

The transient acoustic dynamics of a splash cymbal are investigated via the Finite Element Method-Boundary Element Method. Real three-dimensional motion data recorded from the interaction of drummer–drumstick–cymbal provide the initial and the loading conditions to the simulated interaction of the drumstick–cymbal Finite Element Models. Progressively intensified free strokes are used as loading conditions for both experiment and simulation. The velocity values of the moving drumstick in various drumming conditions are monitored, recorded, and analysed to provide input data into the time domain simulations. The synergy of motion capturing and numerical methods allows computing the sound generated by the combined interaction of the vibroacoustic behaviour of the cymbal with the motor-interaction of the performer. The proposed methodology promotes a novel perspective in musical instrument design, optimization, and manufacturing considering performance discrepancies intentionally introduced by performers.
An ANSYS/LS-DYNA Simulation and Experimental Study of Sectional Hob Type Laver Harvesting Device
Authors: Tang Jiahong , Li Xiuchen , Zhang Guochen , Lu Wei , Ni Shang , Sun Zhenyin , Li Haidong , Zhao Cheng , Zhang Hanbing , Zhang Qian , Mu Gang
Published: February 2023

To solve the problems of low net harvesting rate, high loss rate, and uneven stubble height during the harvest of laver, the laver (Porphyra yezoensis) was selected as the research object, the analysis of the cultivation mode, biomechanical characteristics, harvesting trajectory and force of laver were carried out. A sectional hob type harvesting device was designed. A rigid-flexible coupling model related to the interaction between the cutting mechanism and the laver was constructed based on ANSYS/LS-DYNA. The Box–Behnken design method was used to simulate the effects of different structural parameters and process parameters on the force of laver cutting, and the bench test of the laver harvesting device was carried out. The simulation results showed that the four factors that significantly affect the force exerted on the laver during cutting in proper order were cutter revolving speed, knife extension length, knife inclination angle and forward velocity. When the combination of the forward velocity, the cutter revolving speed, the knife extension length and inclination angle was 0.77 m/s, 900 r/min, 40 mm, and 110°, respectively, the cutting force on laver was the smallest, which was 4.21 N. The bench test of harvesting performance showed that the cutter revolving speed has a significant impact on the recovery rate, and the forward velocity has a significant impact on the loss rate. When the harvesting speed ratio was λ4 (the cutter revolving speed was 900 r/min and the forward velocity was 0.77 m/s), the net harvesting rate and the loss rate were 97.45% and 3.38%, respectively, and the cutting proportion of laver can reach 77.5%. The results of the study provide a theoretical basis for the development of harvesting for laver.
Weight Prediction of Landlly Pigs from Morphometric Traits in Different Age Classes Using ANN and Non-Linear Regression Models
Authors: Preethi Andrew Latha , Tarafdar Ayon , Ahmad Sheikh Firdous , Panda Snehasmita , Tamilarasan Kumar , Ruchay Alexey , Gaur Gyanendra Kumar
Published: February 2023

The present study was undertaken to identify the best estimator(s) of body weight based on various linear morphometric measures in Landlly pigs using artificial neural network (ANN) and non-linear regression models at three life stages (4th, 6th and 8th week). Twenty-four different linear morphometric measurements were taken on 279 piglets individually at all the stages and their correlations with body weight were elucidated. The traits with high correlation (≥0.8) with body weight were selected at different stages. The selected traits were categorized into 31 different combinations (single, two, three, four and five) and subjected to ANN modelling for determining the best combination of body weight predictors at each stage. The model with highest R2 and lowest MSE was selected as best fit for a particular trait. Results revealed that the combination of heart girth (HG), body length (BL) and paunch girth (PG) was most efficient for predicting body weight of piglets at the 4th week (R2 = 0.8697, MSE = 0.4419). The combination of neck circumference (NCR), height at back (HB), BL and HG effectively predicted body weight at 6 (R2 = 0.8528, MSE = 0.8719) and 8 (R2 = 0.9139, MSE = 1.2713) weeks. The two-trait combination of BL and HG exhibited notably high correlation with body weight at all stages and hence was used to develop a separate ANN model which resulted into better body weight prediction ability (R2 = 0.9131, MSE = 1.004) as compared to age-dependent models. The results of ANN models were comparable to non-linear regression models at all the stages.
Extracellular DNA of Fusarium oxysporum f. sp. cubense as a Priming Agent for Inducing the Resistance of Banana Plantlets
Authors: Meitha Karlia , Hanisia Ristag Hamida , Signorelli Santiago , Fauziah Tessa , Iriawati  , Esyanti Rizkita Rachmi
Published: February 2023

Fusarium wilt is one of the major causes of global losses in the banana industry. The application of extracellular DNA (eDNA) is explored as a natural fungicide. eDNA is categorized on the basis of the receiving cell’s perception, namely self and non-self. The application of self-eDNA in agriculture presents the potential for limiting the growth of pathogens, while non-self-eDNA, as a vaccine for plants. This study evaluated whether the eDNA from Fusarium oxysporum f. sp. cubense (Foc) could limit the growth of Foc itself (self-inhibition test) while increasing the resistance of banana plant (priming test). A self-inhibition test showed that the administration of 400 and 800 μg mL−1 eDNA inhibited Foc TR4 spore germination. A priming test was carried out on banana plantlets in the interaction medium containing eDNA Foc TR4 suspension with final concentrations of 40, 80, and 200 μg mL−1. After 24 h, the plantlets were infected with a suspension of 106 spore mL−1. Increased resistance was observed in plantlets treated with 200 μg mL−1 of Foc TR4 eDNA, as indicated by the decrease in leaf symptoms and rhizome discoloration. The accumulation of O2- and H2O2 was observed 24 h after priming as was a significant increase in the relative expression of CAT, PR1, and chitinase 1 genes on day 9 post-infection. In conclusion, eDNA Foc TR4 as a growth inhibitor of pathogen and a priming agent to the banana plantlets could be considered as a biofungicide candidate to induce the resistance of banana plants.
Delineation of Soil Management Zone Maps at the Regional Scale Using Machine Learning
Authors: Maleki Sedigheh , Karimi Alireza , Mousavi Amin , Kerry Ruth , Taghizadeh-Mehrjardi Ruhollah
Published: February 2023

Applying fertilizers to soil in a site-specific way that maximizes yields and minimizes environmental damage is an important goal. Developing soil management zones (MZs) is a suitable method for achieving sustainable agricultural production. Thus, this work aims to investigate MZs delineated based on the different soil properties using machine learning methods. To achieve these, 202 soil samples were collected at the agricultural land of pomegranate, pistachio, and saffron. A “random forest” model was applied to map soil properties based on environmental covariates. The predicted “Lin’s concordance correlation coefficient” values in validation soil properties varied from 0.65 to 0.79. The maps indicated low amounts of soil organic carbon, available potassium, available phosphate, and total nitrogen in most of the region. Furthermore, the study identified four different MZs according to relationships between soil properties and environmental covariates. Generally, the ranking of zones in terms of soil fertility was MZ4 > MZ1 > MZ3 > MZ2 based on the investigated soil properties and the soil quality (SQ) map. The five grades of SQ (i.e., very high, high, moderate, low, and very low) indicated that there was heterogeneous SQ in each MZ in the study area. There were 1.65 ha identified in MZ4 with very low SQ. This result is important in determining the amount of fertilizer to add to the soil in the different areas. It confirms the need for more specific regional management of agriculture lands in this region.
Antimicrobial Stewardship Program for Patients in the Hematological Department Receiving Carbapenem Therapy: A Single-Center and Interrupted Time Series Analysis
Authors: Suzuki Ayako , Yamaguchi Fumihiro , Maeda Masayuki , Hashiguchi Miyuki , Kabasawa Nobuyuki , Sasaki Jun , Sato Tokutada , Fuyama Masaki , Yamazaki Yohei , Endo Kei , Iwata Kae , Kobayashi Sei , Fujihara Hisato
Published: February 2023

As antibiotic resistance has become a global problem, the intervention of an antimicrobial stewardship team (AST) is warranted. In hematological disorders, infectious complications are crucial owing to abnormal neutrophil function and decreased cell-mediated immunity. Despite the widespread implementation of AST intervention, the effectiveness of stewardship practices for immunocompromised patients remains uncertain. We determined the effect of AST interventions on carbapenem therapy in the department of hematology. Patients admitted to the department and undergoing carbapenem therapy were enrolled. We compared carbapenem use between the pre-AST (April 2016–March 2018) and post-AST (April 2018–March 2021) periods. Factors associated with long-term carbapenem therapy were investigated. Overall, 515 episodes of carbapenem therapy in 264 patients in the department were evaluated. According to the interrupted time series analysis, the number of days of therapy decreased with AST intervention (β = −0.263, p = 0.011). In multivariate analysis, predictive factors associated with long-term carbapenem therapy (>8 days) were outpatient onset, chronic obstructive pulmonary disease, acute myeloid leukemia, multiple myeloma, and infection with resistant bacteria (such as extended spectrum β-lactamases and AmpC) (95% confidence interval, 1.030–2.818, 1.067–66.667, 1.057–2.782, 0.168–0.742, and 1.382–5.750, respectively). The AST intervention reduced carbapenem use in patients with hematological disorders.
Elevation of Pulmonary Artery Pressure in Newborns from High-Altitude Pregnancies Complicated by Preeclampsia
Authors: Salinas-Salmon Carlos E. , Murillo-Jauregui Carla , Gonzales-Isidro Marcelino , Espinoza-Pinto Vannia , Mendoza Silvia V. , Ruiz Rosario , Vargas Ronald , Perez Yuri , Montaño Jaime , Toledo Lilian , Badner Abraham , Jimenez Jesús , Peñaranda Javier , Romero Catherine , Aguilar Martha , Riveros-Gonzales Loyola , Arana Ivar , Villamor Eduardo
Published: February 2023

We hypothesized that fetal exposure to the oxidative stress induced by the combined challenge of preeclampsia (PE) and high altitude would induce a significant impairment in the development of pulmonary circulation. We conducted a prospective study in La Paz (Bolivia, mean altitude 3625 m) in which newborns from singleton pregnancies with and without PE were compared (PE group n = 69, control n = 70). We conducted an echocardiographic study in these infants at the median age of two days. The percentage of cesarean deliveries and small for gestational age (SGA) infants was significantly higher in the PE group. Heart rate, respiratory rate, and oxygen saturation did not vary significantly between groups. Estimated pulmonary arterial pressure and pulmonary vascular resistance were 30% higher in newborns exposed to PE and high altitude compared with those exposed only to high altitude. We also detected signs of right ventricular hypertrophy in infants subjected to both exposures. In conclusion, this study provides evidence that the combination of PE and pregnancy at high altitude induces subclinical alterations in the pulmonary circulation of the newborn. Follow-up of this cohort may provide us with valuable information on the potential increased susceptibility to developing pulmonary hypertension or other pulmonary and cardiovascular disorders.
Optimization of Ultrasound-Assisted Extraction of Chlorogenic Acid from Potato Sprout Waste and Enhancement of the In Vitro Total Antioxidant Capacity
Authors: Mangiapelo Luciano , Blasi Francesca , Ianni Federica , Barola Carolina , Galarini Roberta , Abualzulof Ghaid WA , Sardella Roccaldo , Volpi Claudia , Cossignani Lina
Published: February 2023

Potato sprouts, an underutilized by-product of potato processing, could be exploited for the recovery of caffeoyl-quinic acids (CQAs), a family of polyphenols with well-recognized biological activities. In this work, the predominant compound of this class, 5-CQA, was extracted by Ultrasound-Assisted Extraction (UAE) under conditions optimized by an Experimental Design. The investigated variables solid/solvent ratio (1:10–1:50 g/mL), water content in ethanol (30–100% v/v) and UAE time (5–20 min) highlighted a critical influence of the last two factors on the extraction efficiency: extracts richer in 5-CQA were obtained with lower water content (30%) and time (5 min). The addition of ascorbic acid (1.7 mM) as anti-browning agent to the extraction solvent improved the extraction efficiency of 5-CQA compared to acetic and citric acids (3158.71 μg/mL, 1766.71 μg/mL, 1468.20 μg/mL, respectively). A parallel trend for the three acids and an increase in 5-CQA recovery was obtained with the use of freeze-dried sprouts (4980.05 μg/mL, 4795.62, 4211.25 μg/mL, respectively). Total antioxidant capacity (TAC) in vitro demonstrated UAE being a more valuable technique than conventional maceration. Furthermore, three-times-higher values of TPC (7.89 mg GAE/g) and TAC (FRAP: 24.01 mg TE/g; DPPH: 26.20 mg TE/g; ABTS 26.72 mg TE/g) were measured for the optimized extract compared to the initial one. An HPLC-DAD method was applied to monitor 5-CQA recovery, while an LC-HRMS/MS investigation allowed us to perform analyte identity confirmation along with detection of the glycoalkaloids α-solanine and α-chaconine. This evidence underlines the necessity to develop purification strategies in order to maximize the potential of potato sprout waste as a source of 5-CQA.
Mitoferrin-1 Promotes Proliferation and Abrogates Protein Oxidation via the Glutathione Pathway in Glioblastoma
Authors: Ali Md Yousuf , Griguer Corinne E. , Flor Susanne , Oliva Claudia R.
Published: February 2023

Median overall survival is very low in patients with glioblastoma (GBM), largely because these tumors become resistant to therapy. Recently, we found that a decrease in the cytosolic labile iron pool underlies the acquisition of radioresistance. Both cytosolic and mitochondrial iron are important for regulating ROS production, which largely facilitates tumor progression and response to therapy. Here, we investigated the role of the mitochondrial iron transporters mitoferrin-1 (MFRN1) and mitoferrin-2 (MFRN2) in GBM progression. Analysis of The Cancer Genome Atlas database revealed upregulation of MFRN1 mRNA and downregulation of MFRN2 mRNA in GBM tumor tissue compared with non-GBM tissue, yet only the tumor expression level of MFRN1 mRNA negatively correlated with overall survival in patients. Overexpression of MFRN1 in glioma cells significantly increased the level of mitochondrial iron, enhanced the proliferation rate and anchorage-independent growth of these cells, and significantly decreased mouse survival in an orthotopic model of glioma. Finally, MFRN1 overexpression stimulated the upregulation of glutathione, which protected glioma cells from 4-hydroxynonenal-induced protein damage. Overall, these results demonstrate a mechanistic link between MFRN1-mediated mitochondrial iron metabolism and GBM progression. Manipulation of MFRN1 may provide a new therapeutic strategy for improving clinical outcomes in patients with GBM.
Photoinhibition and Photoprotective Responses of a Brown Marine Macroalga Acclimated to Different Light and Nutrient Regimes
Authors: Endo Hikaru , Moriyama Hikari , Okumura Yutaka
Published: February 2023

Plants and brown algae avoid photoinhibition (decline in photosystem II efficiency, Fv/Fm) caused by excess light energy and oxidative stress through several photoprotective mechanisms, such as antioxidant xanthophyll production and heat dissipation. The heat dissipation can be measured as non-photochemical quenching (NPQ) and is strongly driven by de-epoxidation of xanthophyll cycle pigments (XCP). Although NPQ is known to increase under high light acclimation and nutrient-deficient conditions, a few studies have investigated the combined effects of the conditions on both NPQ and associated xanthophyll-to-chlorophyll (Chl) a ratio. The present study investigated the photosynthetic parameters of the brown alga Sargassum fusiforme acclimated to three irradiance levels combined with three nutrient levels. Elevated irradiance decreased Fv/Fm but increased NPQ, XCP/Chl a ratio, and fucoxanthin/Chl a ratio, suggesting the photoprotective role of antioxidant fucoxanthin in brown algae. Reduced nutrient availability increased NPQ but had no effect on the other variables, including XCP/Chl a ratio and its de-epoxidation state. The results indicate that NPQ can be used as a sensitive stress marker for nutrient deficiency, but cannot be used to estimate XCP pool size and state.
An Improved CZT Algorithm for High-Precision Frequency Estimation
Authors: Xu Yan , Yi Huiyue , Zhang Wuxiong , Xu Hui
Published: February 2023

Estimating the frequencies of multiple superimposed exponentials in noise is an important problem due to its various applications in engineering. In order to obtain good inhibition of spectral leakage and improve the estimation accuracy, an improved Chirp-Z transform (CZT) algorithm is proposed for high-precision frequency estimation. Firstly, the proposed algorithm analyzes the characteristics of the CZT spectrum and utilizes the CZT spectrum to construct a bias correction factor for frequency bias estimation. Then, an expression between the bias correction factor and the frequency estimation error is derived to obtain a more accurate estimate of the frequency bias. Finally, the frequency estimate of the CZT is corrected by the estimated frequency bias so as to obtain a higher frequency estimation accuracy. Compared with the conventional CZT algorithm, the proposed improved CZT algorithm achieves a higher frequency estimation accuracy by correcting the frequency estimate of the CZT method using the estimated frequency bias. The proposed improved CZT algorithm is verified using simulation studies and experimental results, and the results show that it has a higher accuracy and better robustness than the existing methods.
SelfCCL: Curriculum Contrastive Learning by Transferring Self-Taught Knowledge for Fine-Tuning BERT
Authors: Dehghan Somaiyeh , Amasyali Mehmet Fatih
Published: February 2023

BERT, the most popular deep learning language model, has yielded breakthrough results in various NLP tasks. However, the semantic representation space learned by BERT has the property of anisotropy. Therefore, BERT needs to be fine-tuned for certain downstream tasks such as Semantic Textual Similarity (STS). To overcome this problem and improve the sentence representation space, some contrastive learning methods have been proposed for fine-tuning BERT. However, existing contrastive learning models do not consider the importance of input triplets in terms of easy and hard negatives during training. In this paper, we propose the SelfCCL: Curriculum Contrastive Learning model by Transferring Self-taught Knowledge for Fine-Tuning BERT, which mimics the two ways that humans learn about the world around them, namely contrastive learning and curriculum learning. The former learns by contrasting similar and dissimilar samples. The latter is inspired by the way humans learn from the simplest concepts to the most complex concepts. Our model also performs this training by transferring self-taught knowledge. That is, the model figures out which triplets are easy or difficult based on previously learned knowledge, and then learns based on those triplets in the order of curriculum using a contrastive objective. We apply our proposed model to the BERT and Sentence BERT(SBERT) frameworks. The evaluation results of SelfCCL on the standard STS and SentEval transfer learning tasks show that using curriculum learning together with contrastive learning increases average performance to some extent.
Bimodal Fusion Network with Multi-Head Attention for Multimodal Sentiment Analysis
Authors: Zhang Rui , Xue Chengrong , Qi Qingfu , Lin Liyuan , Zhang Jing , Zhang Lun
Published: February 2023

The enrichment of social media expression makes multimodal sentiment analysis a research hotspot. However, modality heterogeneity brings great difficulties to effective cross-modal fusion, especially the modality alignment problem and the uncontrolled vector offset during fusion. In this paper, we propose a bimodal multi-head attention network (BMAN) based on text and audio, which adaptively captures the intramodal utterance features and complex intermodal alignment relationships. Specifically, we first set two independent unimodal encoders to extract the semantic features within each modality. Considering that different modalities deserve different weights, we further built a joint decoder to fuse the audio information into the text representation, based on learnable weights to avoid an unreasonable vector offset. The obtained cross-modal representation is used to improve the sentiment prediction performance. Experiments on both the aligned and unaligned CMU-MOSEI datasets show that our model achieves better performance than multiple baselines, and it has outstanding advantages in solving the problem of cross-modal alignment.
Predicting Failure Probability in Industry 4.0 Production Systems: A Workload-Based Prognostic Model for Maintenance Planning
Authors: Converso Giuseppe , Gallo Mosè , Murino Teresa , Vespoli Silvestro
Published: February 2023

Maintenance of equipment is a crucial issue in almost all industrial sectors as it impacts the quality, safety, and productivity of any manufacturing system. Additionally, frequent production rescheduling due to unplanned and unintended interruptions can be very time consuming, especially in the case of centrally controlled systems. Therefore, the ability to estimate the likelihood that a monitored machine will successfully complete a predefined workload, taking into account both historical data from the machine’s sensors and the impending workload, may be essential in supporting a new approach to scheduling activities in an Industry 4.0 production system. This study proposes a novel approach for integrating machine workload information into a well-established PHM algorithm for Industry 4.0, with the aim of improving maintenance strategies in the manufacturing process. The proposed approach utilises a logistic regression model to assess the health condition of equipment and a neural network computational model to estimate its failure probability according to the scheduled workloads. Results from a prototypal case study showed that this approach leads to an improvement in the prediction of the likelihood of completing a scheduled job, resulting in improved autonomy of CPSs in accepting or declining scheduled jobs based on their forecasted health state, and a reduction in maintenance costs while maximising the utilisation of production resources. In conclusion, this study is beneficial for the present research community as it extends the traditional condition-based maintenance diagnostic approach by introducing prognostic capabilities at the plant shop floor, fully leveraging the key enabling technologies of Industry 4.0.
Influence of Resins on the Structure and Dynamics of SBR Compounds: A Solid-State NMR Study
Authors: Pierigé Michele , Nerli Francesca , Nardelli Francesca , Calucci Lucia , Cettolin Mattia , Giannini Luca , Geppi Marco , Martini Francesca
Published: February 2023

The tackifying effect of resins used in the tire industry highly depends on the compatibility and interaction strength with the rubber matrix. Here, uncured and cured styrene/butadiene rubber compounds, either in the presence or absence of a hydrocarbon aromatic tackifying resin, were studied by means of high-resolution and time-domain solid-state NMR (SSNMR) techniques to investigate resin/polymer interactions and the effect of the resin on the dynamics of polymer chains. 13C direct excitation and cross-polarization spectra, combined with low-field measurements of 1H T1 and analysis of 1H on-resonance free-induction decay, provided information on the dynamic heterogeneity of the samples and the degree of mixing between the resin and the rubber matrix. Moreover, 1H T1 and T1ρ relaxation times at variable temperatures were used to investigate the effect of resin on both segmental dynamics activated at the glass transition and collective polymer dynamics. SSNMR findings were discussed in relation to crosslink density and Tg data. The obtained results show that the resin is intimately mixed with the polymer, while maintaining its rigid character. A slowdown of segmental dynamics, related to an increase in Tg, was found as a consequence of resin addition, while no effect was evidenced on fragility and collective polymer dynamics.
Seismic Assessment of Historical Masonry Buildings at Different Scale Levels: A Review
Authors: Puncello Irene , Caprili Silvia
Published: February 2023

The relevant losses determined by recent earthquakes stressed the vulnerability of historical masonry constructions towards horizontal seismic actions, therefore highlighting the need for reliable approaches for the structural assessment and following retrofit. During the last decades, the scientific community has widely investigated the tools to analyse the performance of such structural typologies, resulting in a multitude of different methodologies depending on the building’s features and the goal of the analysis. The task is particularly challenging because of the frequently limited knowledge concerning the state of the art and the high structural complexity due to overlapped construction phases. A general literature review of the methods adopted for the structural assessment of historical masonry buildings is proposed in the present paper. The methods are grouped according to the operational scale, providing an overview of the current state of the art.
Numerical Analysis of Frost Heave and Thaw Settlement for Pipeline Buried in Frost-Susceptible Soil via Thermosiphons
Authors: Park Dong-Su , Shin Mun-Beom , Park Woo-Jin , Seo Young-Kyo
Published: February 2023

Seasonal frost or permafrost soils may encounter frost heave or thaw settlement resulting from atmospheric temperature changes and/or heat emanating from the resource-carrying pipeline. Notably, these soil movements can damage the pipeline. Thus, various ground stabilization methods have been developed to prevent the onset of these phenomena in frost-susceptible soils, and the application of thermosiphons is a representative method. Recently, a numerical analysis method called the thermosiphon model for a pipeline and thermosiphons in frost-susceptible soil has been developed; however, the study only focused on the ability to reduce frost heave of the soil using the thermosiphon. Therefore, here, numerical analysis was conducted to determine the performance of a buried pipeline according to frost heave and thaw settlement by applying the thermosiphon model via ABAQUS. For the novel numerical analysis, two scenarios are established: frost heave and thaw settlement. For each scenario, the behaviors of the frost-susceptible soil and pipeline are compared in four cases, distinguished by the arrangement of thermosiphons applied. The results indicate that according to the arrangement of the thermosiphons, the frost-heave and thaw-settlement behaviors are verifiably reduced by up to 62% and 82%, respectively, compared to when no thermosiphons are applied.
Dynamic Behaviors of a COVID-19 and Influenza Co-Infection Model with Time Delays and Humoral Immunity
Authors: Elaiw Ahmed M. , Alsulami Raghad S. , Hobiny Aatef D.
Published: February 2023

Co-infections with respiratory viruses were reported in hospitalized patients in several cases. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza A virus (IAV) are two respiratory viruses and are similar in terms of their seasonal occurrence, clinical manifestations, transmission routes, and related immune responses. SARS-CoV-2 is the cause of coronavirus disease 2019 (COVID-19). In this paper, we study the dynamic behaviors of an influenza and COVID-19 co-infection model in vivo. The role of humoral (antibody) immunity in controlling the co-infection is modeled. The model considers the interactions among uninfected epithelial cells (ECs), SARS-CoV-2-infected ECs, IAV-infected ECs, SARS-CoV-2 particles, IAV particles, SARS-CoV-2 antibodies, and IAV antibodies. The model is given by a system of delayed ordinary differential equations (DODEs), which include four time delays: (i) a delay in the SARS-CoV-2 infection of ECs, (ii) a delay in the IAV infection of ECs, (iii) a maturation delay of newly released SARS-CoV-2 virions, and (iv) a maturation delay of newly released IAV virions. We establish the non-negativity and boundedness of the solutions. We examine the existence and stability of all equilibria. The Lyapunov method is used to prove the global stability of all equilibria. The theoretical results are supported by performing numerical simulations. We discuss the effects of antiviral drugs and time delays on the dynamics of influenza and COVID-19 co-infection. It is noted that increasing the delay length has a similar influence to that of antiviral therapies in eradicating co-infection from the body.
Generalized Type 2 Fuzzy Differential Evolution Applied to a Sugeno Controller
Authors: Ochoa Patricia , Peraza Cinthia , Castillo Oscar , Melin Patricia
Published: February 2023

The papers using fuzzy logic have generated continuous improvements for applications, and an example of this is the use of generalized type 2 fuzzy systems in real-world problems. The key idea of this paper is to present a generalized type 2 fuzzy system for augmenting differential evolution with dynamic parameter variation in order to enhance its performance and convergence. A generalized type 2 Sugeno controller was implemented with the aim of enhancing the trajectory of a robot, and an analysis of the execution time and the errors obtained by ITAE, IAE, ITSE, ISEV, RMSE, and MSE is presented. In addition, a comparison with different levels of disturbance applied to the controller was performed with the goal of demonstrating the efficiency of a type 2 fuzzy system.
Hybrid Projective Synchronization of Fractional-Order Extended Hindmarsh–Rose Neurons with Hidden Attractors
Authors: Shi Xuerong , Wang Zuolei
Published: February 2023

In view of the diversity of stimulated current that neurons may experience, an extended Hindmarsh–Rose neuron model is proposed and the corresponding fractional-order neuron model, with no equilibrium point, is depicted. Additionally, various hidden attractors of the addressed neuron model are analyzed by changing system parameters and the order of fractional-order neuron system. Furthermore, hybrid projective synchronizations of the proposed neurons are investigated and schemes are obtained by designing suitable controllers according to fractional stability theory. Besides, the validity of the theoretical results is verified through numerical simulations. In short, the research results have potential application in revealing the dynamical behaviors of neuron system and controlling the behaviors of neuron into certain status.
A Method for Abnormal Battery Charging Capacity Diagnosis Based on Electric Vehicles Operation Data
Authors: Li Fang , Min Yongjun , Zhang Ying , Wang Chen
Published: February 2023

Overcharging due to an abnormal charging capacity is one of the most common causes of thermal runaway (TR). This study proposes a method for diagnosing abnormal battery charging capacity based on electric vehicle (EV) data. The proposed method can obtain the fault frequency and output the corresponding state of charge (SOC) when a fault occurs. First, a machine-learning-based data cleaning framework is developed to overcome the limitations of the interpolation method. Then, offline training is implemented, based on big vehicle operation data and an improved Gaussian process regression (GPR). Thereafter, online monitoring of the discrete capacity increment (DCI) is used to identify the abnormal charging capacity. The abnormal charging capacity fault is identified by the absolute error between the GPR outputs and the true DCI, and the thresholds are determined using a Box–Cox transformation with a value of 3σ. The diagnostic results indicate that the abnormal charging capacity of the TR vehicle is identified two months in advance, and the fault frequency of the abnormal and normal vehicles is 0.5221 and 0.0311, respectively. EV operation data and various methods are used to validate the robustness and applicability of the proposed method.
Intracellular Organization of Proteins and Nucleic Acids via Biomolecular Condensates in Human Health and Diseases
Authors: Gallo Raffaella
Published: February 2023

Eukaryotic cells are intracellularly divided into several compartments that provide spatiotemporal control over biochemical reactions. Phase separation of proteins and RNA is emerging as an important mechanism underlying the formation of intracellular compartments that are not delimited by membranes. These structures are also known as biomolecular condensates and have been shown to serve a myriad of cellular functions, such as organization of cytoplasm and nucleoplasm, stress response, signal transduction, gene regulation, and immune response. Here, the author will summarize our current understanding of intracellular phase separation, its biological functions, and how this phenomenon is regulated in eukaryotic cells. Additionally, the author will review recent evidence of the role of biomolecular condensates in the development of pathophysiological conditions, with special emphasis on cancer and immune signaling.
Three-Dimensional Computational Model Simulating the Initial Callus Growth during Fracture Healing in Long Bones: Application to Different Fracture Types
Authors: Naveiro José M. , Gracia Luis , Roces Jorge , Albareda Jorge , Puértolas Sergio
Published: February 2023

Bone fractures are among the most common and potentially serious injuries to the skeleton, femoral shaft fractures being especially severe. Thanks to recent advances in the area of in silico analysis, several approximations of the bone healing process have been achieved. In this context, the objective of this work was to simulate the initial phase of callus formation in long bones, without a pre-meshed domain in the 3D space. A finite element approach was computationally implemented to obtain the values of the cell concentrations along the whole domain and evaluate the areas where the biological quantities reached the thresholds necessary to trigger callus growth. A voxel model was used to obtain the 3D domain of the bone fragments and callus. A mesh growth algorithm controlled the addition of new elements to the domain at each step of the iterative procedure until complete callus formation. The implemented approach is able to reproduce the generation of the primary callus, which corresponds to the initial phase of fracture healing, independently of the fracture type and complexity, even in the case of several bone fragments. The proposed approach can be applied to the most complex bone fractures such as oblique, severely comminuted or spiral-type fractures, whose simulation remains hardly possible by means of the different existing approaches available to date.
Identification of a Novel Wnt Antagonist Based Therapeutic and Diagnostic Target for Alzheimer’s Disease Using a Stem Cell-Derived Model
Authors: Patil Manasi , Gamit Naisarg , Dharmarajan Arun , Sethi Gautam , Warrier Sudha
Published: February 2023

Currently, all the existing treatments for Alzheimer’s disease (AD) fail to stall progression due to longer duration of time between onset of the symptoms and diagnosis of the disease, raising the necessity of effective diagnostics and novel treatment. Specific molecular regulation of the onset and progression of disease is not yet elucidated. This warranted investigation of the role of Wnt signaling regulators which are thought to be involved in neurogenesis. The AD model was established using amyloid beta (Aβ) in human mesenchymal stem cells derived from amniotic membranes which were differentiated into neuronal cell types. In vivo studies were carried out with Aβ or a Wnt antagonist, AD201, belonging to the sFRP family. We further created an AD201-knockdown in vitro model to determine the role of Wnt antagonism. BACE1 upregulation, ChAT and α7nAChR downregulation with synapse and functionality loss with increases in ROS confirmed the neurodegeneration. Reduced β-catenin and increased AD201 expression indicated Wnt/canonical pathway inhibition. Similar results were exhibited in the in vivo study along with AD-associated behavioural and molecular changes. AD201-knockdown rescued neurons from Aβ-induced toxicity. We demonstrated for the first time a role of AD201 in Alzheimer’s disease manifestation, which indicates a promising disease target and biomarker.
Cytogenetics, Typification, Molecular Phylogeny and Biogeography of Bentinckia (Arecoideae, Arecaceae), an Unplaced Indian Endemic Palm from Areceae
Authors: Kadam Suhas K. , Mane Rohit N. , Tamboli Asif S. , Gavade Sandip K. , Deshmukh Pradip V. , Lekhak Manoj M. , Choo Yeon-Sik , Pak Jae Hong
Published: February 2023

Bentinckia is a genus of flowering plants which is an unplaced member of the tribe Areceae (Arecaceae). Two species are recognized in the genus, viz. B. condapanna Berry ex Roxb. from the Western Ghats, India, and B. nicobarica (Kurz) Becc. from the Nicobar Islands. This work constitutes taxonomic revision, cytogenetics, molecular phylogeny, and biogeography of the Indian endemic palm genus Bentinckia. The present study discusses the ecology, morphology, taxonomic history, distribution, conservation status, and uses of Bentinckia. A neotype was designated for the name B. condapanna. Cytogenetical studies revealed a new cytotype of B. condapanna representing 2n = 30 chromosomes. Although many phylogenetic reports of the tribe Areceae are available, the relationship within the tribe is still ambiguous. To resolve this, we carried out Bayesian Inference (BI) and Maximum Likelihood (ML) analysis using an appropriate combination of chloroplast and nuclear DNA regions. The same phylogeny was used to study the evolutionary history of Areceae. Phylogenetic analysis revealed that Bentinckia forms a clade with other unplaced members, Clinostigma and Cyrostachys, and together they show a sister relationship with the subtribe Arecinae. Biogeographic analysis shows Bentinckia might have originated in Eurasia and India.