bluuebunny/crossref_metadata_2025 huggingface dataset:
The feeding preference and bite response between Microtus fortis and Broussonetia papyrifera
Authors: Wang Shuangye , Chen Zihao , Wang Mengxin , Zhang Meiwen , Zhang Chen , Huang Tian , Zhao Yunlin , Xu Zhenggang
Published: September 2024

Introduction

Broussonetia papyrifera is a dioecious plant that is rich in various metabolites and widely distribute in Asia. Microtus fortis is a rodent that often causes damage to crops, especially in the Dongting Lake region of China. There is a wide overlap in the distribution areas for the above species and the M. fortis feeds on the leaves of the B. papyrifera. Preliminary experiments have shown that the reproduction of M. fortis is inhibited after feeding on the leaves of the B. papyrifera.

Methods

In order to explore the potential of using B. papyrifera to develop botanical pesticides, we investigated the palatability and reactive substances. The feeding frequency of M. fortis on B. papyrifera leaves to that of on daily fodder and Carex brevicuspis that is the primary food for the wild population were compared. We also attempted to identify the responsive substances in B. papyrifera leaves that were bitten by M. fortis using metabolome analysis.

Results

In general, B. papyrifera leaves exhibited a stronger attraction to M. fortis. M. fortis foraged B. papyrifera leaves more frequently, and the intake was higher than that of the other two. Differential metabolites were screened by comparing normal leaves and leaves bitten by M. fortis, meanwhile with the intervention of clipped leaves. A total of 269 substances were screened, and many of these were involved in the biosynthesis of secondary metabolites, including terpenoids and alkaloids. These substances may be related to the defense mechanism of B. papyrifera against herbivores.

Discussion

These findings support further research examining animal–plant interactions and simultaneously provide insights into the utilisation of B. papyrifera resources and the management of rodents. The good palatability and the defense of B. papyrifera leaves suggest that they have the potential to contribute in development of plant rodenticide.
Temporal dynamics of coarticulatory cues to prediction
Authors: Lulaci Tugba , Söderström Pelle , Tronnier Mechtild , Roll Mikael
Published: September 2024

The temporal dynamics of the perception of within-word coarticulatory cues remain a subject of ongoing debate in speech perception research. This behavioral gating study sheds light on the unfolding predictive use of anticipatory coarticulation in onset fricatives. Word onset fricatives (/f/ and /s/) were split into four gates (15, 35, 75 and 135 milliseconds). Listeners made a forced choice about the word they were listening to, based on the stimulus gates. The results showed fast predictive use of coarticulatory lip rounding during /s/ word onsets, as early as 15 ms from word onset. For /f/ onsets, coarticulatory backness and height began to be used predictively after 75 ms. These findings indicate that onset times of the occurrence and use of coarticulatory cues can be extremely fast and have a time course that differs depending on fricative type.
Bacterial infections and outcomes of inpatients with COVID-19 in the intensive care unit during the delta-dominant phase: the worst wave of pandemic in Iran
Authors: Akbari Mojtaba , Dehghani Yeganeh , Shirzadi Mohammad , Pourajam Samaneh , Hosseinzadeh Majid , Sajadi Mahdi , Alenaseri Malihe , Siavash Mansour , Jafari Leila , Solgi Hamid
Published: September 2024

Background

Epidemiological data regarding the prevalence of bacterial multidrug-resistant (MDR) Gram-negative infections in patients with COVID-19 in Iran are still ambiguous. Thus, in this study we have investigated the epidemiology, risk factors for death, and clinical outcomes of bacterial infections among patients with COVID-19 in the intensive care unit (ICU).

Method

This retrospective cohort study included patients with COVID-19 hospitalized in the ICU of a university hospital in Iran between June 2021 and December 2021. We evaluated the epidemiological, clinical, and microbiological features, outcomes and risk factors associated with death among all COVID-19 patients. Data and outcomes of these patients with or without bacterial infections were compared. Kaplan–Meier plot was used for survival analyses.

Results

In total, 505 COVID-19 patients were included. The mean age of the patients was 52.7 ± 17.6 years and 289 (57.2%) were female. The prevalence of bacterial infections among hospitalized patients was 14.9%, most of them being hospital-acquired superinfections (13.3%). MDR Klebsiella pneumoniae and Staphylococcus aureus were the most common pathogens causing respiratory infections. Urinary tract infections were most frequently caused by MDR Escherichia coli and K. pneumoniae. The overall in-hospital mortality rate of COVID-19 patients was 46.9% (237/505), while 78.7% (59/75) of patients with bacterial infections died. Infection was significantly associated with death (OR 6.01, 95% CI = 3.03–11.92, p-value <0.0001) and a longer hospital stay (p < 0.0001). Multivariate logistic regression analysis showed that Age (OR = 1.04, 95% CI = 1.03–1.06, p-value <0.0001), Sex male (OR = 1.70, 95% CI = 1.08–2.70, p-value <0.0001), Spo2 (OR = 1.99, 95% CI = 1.18–3.38, p-value = 0.010) and Ferritin (OR = 2.33, 95% CI = 1.37–3.97, p-value = 0.002) were independent risk factors associated with in-hospital mortality. Furthermore, 95.3% (221/232) of patients who were intubated died.

Conclusion

Our findings demonstrate that bacterial infection due to MDR Gram-negative bacteria associated with COVID-19 has an expressive impact on increasing the case mortality rate, reinforcing the importance of the need for surveillance and strict infection control rules to limit the expansion of almost untreatable microorganisms.
Trajectories of cognitive function development and predictive factors in disabled middle-aged and older adults
Authors: Pang Jiaxue , Xu Yang , Liu Qiankun , Huang Juju , Li Pengyao , Ma Li , Zeng Chunlu , Ma Xiaoqing , Xie Hui
Published: September 2024

Objective

To explore the trajectories of cognitive function development and predictive factors in disabled middle-aged and older adults.

Methods

Utilizing data from 983 disabled middle-aged and older adults in the China Health and Retirement Longitudinal Study (CHARLS) from 2013 to 2020, latent growth mixture models were constructed to analyze the categories of cognitive function development trajectories and their predictive factors.

Results

The cognitive function trajectories of the disabled middle-aged and older adults were classified into three categories: rapid decline (32.6%), Slow decline (36.1%), and Stable (31.2%). Multinomial logistic regression analysis identified age, gender, residence, education, marital status, household income, sleep duration, depression, hearing ability, and social participation as predictors of these trajectories.

Conclusion

There is heterogeneity in the cognitive function development trajectories among disabled middle-aged and older adults. Healthcare professionals can implement targeted health management based on the characteristics of different groups to prevent the deterioration of cognitive function in this population.
Malignancies After Heart Transplantation
Authors: Stenman Caroline , Wallinder Andreas , Holmberg Erik , Karason Kristjan , Magnusson Jesper , Dellgren Göran
Published: September 2024

Heart transplant patients have an increased risk of developing cancer. Patients who underwent HTx between 1985 and 2017 were included. Detection of cancer was obtained by cross-checking the study population with the Swedish Cancer-Registry and the Cause-of-Death-Registry. A total of 664 patients were followed for a median of 7.7 years. In all, 231 malignancies were diagnosed in 138 patients. Compared to the general population the excess risk of cancer following HTx was 6.2-fold calculated as the standardized incidence ratio (SIR) and 2.9-fold after exclusion of non-melanoma skin cancer (NMSC). The most common malignancies were NMSC, non-Hodgins lymphoma, and lung cancer. There was no significant difference in overall survival between those with and without a history of cancer before HTx (p = 0.53). During a median follow-up of 7.7 years, 19% of HTx recipients developed cancer, 6.2-fold higher relative to the general population, and 2.9-fold higher when excluding NMSC. Risk factors for malignancies (excluding NMSC) included previous smoking, hypertension and prolonged ischemic time; and for NMSC, increasing age, seronegative CMV-donors, and azathioprine. A previous cancer in selected recipients results in similar survival compared to those without cancer prior to HTx.
Development of Lightweight 6 m Deployable Mesh Reflector Antenna Mechanisms Based on a Superelastic Shape Memory Alloy
Authors: Choi Jae-Seop , Park Tae-Yong , Chae Bong-Geon , Oh Hyun-Ung
Published: September 2024

This paper describes the design and experimental verification of a 6 m parabolic deployable mesh reflector antenna mechanism based on a superelastic shape memory alloy. This antenna mainly consists of a deployable primary reflector with a superelastic shape memory alloy-based hinge mechanism and a fixed-type secondary reflector mast, where a rotary-type holding and release mechanism and deployment speed control system are installed. The main feature of this antenna is the application of a superelastic shape memory alloy to the mechanism, which has the advantages of plastic deformation resistance, high damping, and fatigue resistance. A shape memory alloy is applied to the hinge mechanism of each primary reflector rib and to the rotary-type holding and release mechanism as a deployment mechanism. In addition, a superelastic shape memory alloy wire is applied to the antenna in the circumferential direction to maintain the curvature of the primary reflector. The effectiveness of the proposed mechanism design was verified through repeated deployment tests on models of the superelastic shape memory alloy-based hinge mechanism and the antenna system.
A Review of Recent Developments in Hybrid Rocket Propulsion and Its Applications
Authors: Wei Shih-Sin , Li Meng-Che , Lai Alfred , Chou Tzu-Hao , Wu Jong-Shinn
Published: September 2024

This paper extensively reviews hybrid rocket propulsion-related activities from combustion engine designs to launch tests. Starting with a brief review of rocket propulsion development history, a comparison among the three bi-propellant rocket propulsion approaches, and hybrid rocket engine design guidelines, a very thorough review related to hybrid rocket propulsion and its applications is presented in this paper. In addition to propellant choice, engine design also affects the hybrid rocket performance and, therefore, a variety of engine designs, considering, e.g., fuel geometry, swirl injection, ignition designs, and some innovative flow-channel designs are also explored. Furthermore, many fundamental studies on increasing hybrid rocket engine performances, such as regression rate enhancement, mixing enhancement, and combustion optimization, are also reviewed. Many problems that will be encountered for practical applications are also reviewed and discussed, including the O/F ratio shift, low-frequency instability, and scale-up methods. For hybrid rocket engine applications in the future, advanced capabilities and lightweight design of the hybrid rocket engine, such as throttling capability, thrust vectoring control concept, insulation materials, 3D-printing manufacturing technologies, and flight demonstrations, are also included. Finally, some active hybrid rocket research teams and their plans for flight activities are briefly introduced.
Design and Experimental Testing of Extended-Range Power Supply System for 15 Horsepower Electric Tractor
Authors: Wang Baochao , Lv Yanshi , Chu Xianggang , Wang Dongwei , Shang Shuqi
Published: September 2024

Electric tractors have many advantages, including high torque, excellent controllability, energy efficiency, a simple structure, and an electric interface for expansion. However, a significant limitation lies in their endurance. This study presents the design of an extended-range power supply system to ensure continuous endurance for an electric tractor. The objective is to provide a continuous power source for our self-developed electric tractor while preserving the benefits of electric propulsion. Extended-range power systems utilize a primary mover, typically an oil-fueled internal combustion engine, to drive the generator for electricity generation, and the generated AC-form electricity is subsequently converted into stable DC bus voltage by a power electronic converter. The hardware and control design of an extended-range power supply system are finalized and validated through experimental trials. The results demonstrate the system’s capability to sustain stable DC bus voltage amidst disruptions such as sudden load shifts and fluctuations in the prime mover’s speed. Even with a 50% sudden load change, the voltage drop is within 12% and can recover to ±3% within 4 s. The extended-range can be used alone without a battery to power the electric tractor, or it can used in parallel with other extended ranges or batteries for power sharing thanks to the droop control ability.
Future Reference Evapotranspiration Trends in Shandong Province, China: Based on SAO-CNN-BiGRU-Attention and CMIP6
Authors: Wang Yudong , Pang Guibin , Wang Tianyu , Cong Xin , Pan Weiyan , Fu Xin , Wang Xin , Xu Zhenghe
Published: September 2024

One of the primary factors in the hydrological cycle is reference evapotranspiration (ET0). The prediction of ET0 is crucial to manage irrigation water in agriculture under climate change; however, little research has been conducted on the trends of ET0 changes in Shandong Province. In this study, to estimate ET0 in the entire Shandong Province, 245 sites were chosen, and the monthly ET0 values during 1901–2020 were computed using the Hargreaves–Samani formula. A deep learning model, termed SAO-CNN-BiGRU-Attention, was utilized to forecast the monthly ET0 during 2021–2100, and the predictions were compared to two CMIP6 climate scenarios, SSP2-4.5 and SSP5-8.5. The hierarchical clustering results revealed that Shandong Province encompassed three homogeneous regions. The ET0 values of Clusters H1 and H2, which were situated in inland regions and major agricultural areas, were the highest. The SAO-CNN-BiGRU-Attention and SSP5-8.5 forecasting results generally displayed a monotonically growing trend during the forecast period in the three regions; however, the SAO-CNN-BiGRU-Attention model displayed a declining tendency at a few points. According to the SAO-CNN-BiGRU-Attention and SSP5-8.5 results, during 2091–2100, H1, H2, and H3 will reach their peaks; the SSP2-4.5 results show that H1, H2, and H3 will peak in 2031–2040. At the end of the forecast period, for Clusters H1, H2, and H3, the prediction rate of SAO-CNN-BiGRU-Attention increased by 1.31, 1.56%, and 1.80%, respectively, whereas SSP2-4.5’s prediction rate increased by 0.31%, 0.95%, and 1.57%, respectively, and SSP5-8.5’s prediction rate increased by 10.88%, 10.76%, and 10.69%, respectively. The prediction results of SAO-CNN-BiGRU-Attention were similar to those of SSP2-4.5 (R2 > 0.96). The SAO-CNN-BiGRU-Attention deep learning model can be used to forecast future ET0.
Intelligent Surface Recognition for Autonomous Tractors Using Ensemble Learning with BNO055 IMU Sensor Data
Authors: Thavitchasri Phummarin , Maneetham Dechrit , Crisnapati Padma Nyoman
Published: September 2024

This study aims to enhance the navigation capabilities of autonomous tractors by predicting the surface type they are traversing using data collected from BNO055 Inertial Measurement Units (IMU sensors). IMU sensor data were collected from a small mobile robot driven over seven different floor surfaces within a university environment, including tile, carpet, grass, gravel, asphalt, concrete, and sand. Several machine learning models, including Logistic Regression, K-Neighbors, SVC, Decision Tree, Random Forest, Gradient Boosting, AdaBoost, and XGBoost, were trained and evaluated to predict the surface type based on the sensor data. The results indicate that Random Forest and XGBoost achieved the highest accuracy, with scores of 98.5% and 98.7% in K-Fold Cross-Validation, respectively, and 98.8% and 98.6% in an 80/20 Random State split. These findings demonstrate that ensemble methods are highly effective for this classification task. Accurately identifying surface types can prevent operational errors and improve the overall efficiency of autonomous systems. Integrating these models into autonomous tractor systems can significantly enhance adaptability and reliability across various terrains, ensuring safer and more efficient operations.
Remote Prediction of Soybean Yield Using UAV-Based Hyperspectral Imaging and Machine Learning Models
Authors: Berveglieri Adilson , Imai Nilton Nobuhiro , Watanabe Fernanda Sayuri Yoshino , Tommaselli Antonio Maria Garcia , Ederli Glória Maria Padovani , de Araújo Fábio Fernandes , Lupatini Gelci Carlos , Honkavaara Eija
Published: September 2024

Early soybean yield estimation has become a fundamental tool for market policy and food security. Considering a heterogeneous crop, this study investigates the spatial and spectral variability in soybean canopy reflectance to achieve grain yield estimation. Besides allowing crop mapping, remote sensing data also provide spectral evidence that can be used as a priori knowledge to guide sample collection for prediction models. In this context, this study proposes a sampling design method that distributes sample plots based on the spatial and spectral variability in vegetation spectral indices observed in the field. Random forest (RF) and multiple linear regression (MLR) approaches were applied to a set of spectral bands and six vegetation indices to assess their contributions to the soybean yield estimates. Experiments were conducted with a hyperspectral sensor of 25 contiguous spectral bands, ranging from 500 to 900 nm, carried by an unmanned aerial vehicle (UAV) to collect images during the R5 soybean growth stage. The tests showed that spectral indices specially designed from some bands could be adopted instead of using multiple bands with MLR. However, the best result was obtained with RF using spectral bands and the height attribute extracted from the photogrammetric height model. In this case, Pearson’s correlation coefficient was 0.91. The difference between the grain yield productivity estimated with the RF model and the weight collected at harvest was 1.5%, indicating high accuracy for yield prediction.
Differentiated In-Row Soil Management in a High-Density Olive Orchard: Effects on Weed Control, Tree Growth and Yield, and Economic and Environmental Sustainability
Authors: Lodolini Enrico Maria , Palmieri Nadia , de Iudicibus Alberto , Lucchese Pompea Gabriella , Zucchini Matteo , Giorgi Veronica , Crescenzi Samuele , Mezrioui Kaies , Neri Davide , Ciaccia Corrado , Assirelli Alberto
Published: September 2024

Two different in-row soil management techniques were compared in the Olive Orchard Innovation Long-term experiment of the Council for Agricultural Research and Economics, Research Centre for Olive, Fruit, and Citrus Crops in Rome, Italy. Rows were managed with an in-row rotary tiller and with synthetic mulching using permeable polypropylene placed after cultivar Maurino olive trees planting. The effects of the two treatments were assessed through weed soil coverage and the growth of the olive trees. Results showed better agronomic performance associated with synthetic mulching. The weed control effect along the row of a young high-density olive orchard was higher with the synthetic mulching compared to hoeing. The effect of the synthetic mulching seemed to disappear when removed from the ground (spring 2023) since no significant differences were found for tree size and yield in the two tested in-row soil management systems at the end of 2023. Finally, the growth of the young olive trees (Trunk Cross Sectional Area, Height, and Canopy expansion) measured across the three years, was higher for the synthetic mulched row than the hoed one. The use of synthetic mulching along the row positively forced the vegetative growth of the young olive trees and anticipated the onset of fruit production compared to periodical hoeing: a significantly higher fruit production was registered three years after planting. Root diameter was higher under synthetic mulching one year after planting, and no differences were observed in the following sampling dates showing similar fluctuations linked to the seasonal growth pattern. The life cycle assessment and costing highlighted that the application of mulching had a higher eco- and economic-efficiency than the periodical in-row soil hoeing.
Crop Growth Analysis Using Automatic Annotations and Transfer Learning in Multi-Date Aerial Images and Ortho-Mosaics
Authors: Rana Shubham , Gerbino Salvatore , Akbari Sekehravani Ehsan , Russo Mario Brandon , Carillo Petronia
Published: September 2024

Growth monitoring of crops is a crucial aspect of precision agriculture, essential for optimal yield prediction and resource allocation. Traditional crop growth monitoring methods are labor-intensive and prone to errors. This study introduces an automated segmentation pipeline utilizing multi-date aerial images and ortho-mosaics to monitor the growth of cauliflower crops (Brassica Oleracea var. Botrytis) using an object-based image analysis approach. The methodology employs YOLOv8, a Grounding Detection Transformer with Improved Denoising Anchor Boxes (DINO), and the Segment Anything Model (SAM) for automatic annotation and segmentation. The YOLOv8 model was trained using aerial image datasets, which then facilitated the training of the Grounded Segment Anything Model framework. This approach generated automatic annotations and segmentation masks, classifying crop rows for temporal monitoring and growth estimation. The study’s findings utilized a multi-modal monitoring approach to highlight the efficiency of this automated system in providing accurate crop growth analysis, promoting informed decision-making in crop management and sustainable agricultural practices. The results indicate consistent and comparable growth patterns between aerial images and ortho-mosaics, with significant periods of rapid expansion and minor fluctuations over time. The results also indicated a correlation between the time and method of observation which paves a future possibility of integration of such techniques aimed at increasing the accuracy in crop growth monitoring based on automatically derived temporal crop row segmentation masks.
Natural Variability of Genomic Sequences of Mal d 1 Allergen in Apples as Revealed by Restriction Profiles and Homolog Polymorphism
Authors: Urbanová Lucia , Bilčíková Jana , Moravčíková Dagmar , Žiarovská Jana
Published: September 2024

Apples are a popular fruit worldwide, with many health and nutritional benefits. However, this fruit is also among those that, particularly in Central and Northern Europe, are allergenic due to the Mal d 1 allergen. Mal d 1 is a homologous allergen to Bet v 1—the main pollen allergen of birch. In this study, two different approaches were used to identify the natural length polymorphism of Bet v 1 homologs in apple varieties, with the aim of characterizing their effectiveness. BBAP (Bet v 1 based amplified polymorphism) and RFLP (restriction fragments length polymorphism) profiles were characterized and compared. RFLP analysis recognizes the genetic diversity of M. domestica Mal d 1 sequences at a relatively low level. In BBAP profiles, the genetic dissimilarity was up to 50%, which appears suitable for intraspecific fingerprinting and serves as an additional method for RFLP analysis. RFLP analysis was able to distinguish some varieties that BBAP could not, such as Sonet.
Preparation of Polyclonal Antibodies to Barley Granule-Bound Amylopectin Synthase Ia and Their Application in the Characterization of Interacting Proteins
Authors: Zhou Qiyan , Xi Boai , Shoaib Noman , Gao Yan , Cheng Zhenbin , Kumbhar Rizwan Ali , Feng Zongyun , Liu Yajie , Zhao Hui , Yu Guowu
Published: September 2024

The production of amylose is facilitated by granule-bound starch synthase (GBSS). Despite its importance, the specific protein interactions involving barley grain-bound starch synthase Ia (HvGBSSIa) remain poorly understood. To elucidate this, we engineered a pET-32a-HvGBSSIa prokaryotic expression vector for specific expression in E. coli Rosetta cells. A rabbit anti-HvGBSSIa polyclonal antibody was generated and employed to enrich HvGBSSIa-binding proteins from barley grains through immunoprecipitation. The isolated complexes were then resolved through SDS-PAGE, and the constituent proteins were identified using mass spectrometry coupled with database searches. Our results confirmed the successful preparation of a highly specific polyclonal antibody against HvGBSSI. Furthermore, differential expression of HvGBSSIa was assessed across various barley tissues and developmental stages of the grain, revealing peak expression at 25 days post-flowering. Proteins interacting with HvGBSSIa, including sucrose synthase and starch branching enzyme, were identified through co-immunoprecipitation. This study lays the groundwork for further detailed analyses of the HvGBSSIa protein complex in barley.
Genome-Wide Identification of MsICE Gene Family in Medicago sativa and Expression Analysis of the Response to Abiotic Stress
Authors: Wang Baiji , Liu Qianning , Xu Wen , Yuan Yuying , Tuluhong Muzhapaer , Yu Jinqiu , Cui Guowen
Published: September 2024

To predict the role of the MsICE gene family in the response to abiotic stress, in this study, bioinformatics analysis and real-time fluorescence quantitative PCR were performed. Alfalfa (Medicago sativa) is one of the most economically valuable crops globally. Inducer of CBF expression (ICE), which is part of the basic helix–loop–helix (bHLH) transcription factor (TF) family, acts as a key regulator of cold tolerance. Despite this, there is little information available about ICE genes in alfalfa. Therefore, we studied the function of ICE TFs in alfalfa. We identified 11 MsICE genes from the alfalfa genome and classified them into two groups. Analysis of the protein motif and gene structure revealed relatively high conservation among subgroups of the tightly clustered MsICE genes. Through synteny analysis, we detected duplication events in the MsICE gene family, suggesting that the ICE gene family was formed through fragment duplications. All the MsICE proteins were located in the nucleus according to subcellular localization predictions. The promoter cis-regulatory elements of MsICE genes are largely involved in light (Box 4), hormone (ABRE), and stress (MYB) responses. The MsICE01/MsICE07/MsICE09/MsICE10/MsICE11 genes contained MYB- and MYC-binding motifs, indicating an association with abiotic stress. The specific expression patterns of MsICE genes in leaves were revealed by examining their expression patterns in different tissues. These findings suggest that these genes may sense external environmental changes through leaves. Abiotic stress can cause striking upregulation of MsICE07 (PCA score: −4.03) and MsICE10 (PCA score: −4.05) expression. In this study, candidate genes associated with cold stress were identified, and subsequent molecular biological analyses allowed elucidation of the biological functions of these genes in alfalfa. This research provides a theoretical foundation for enhancing alfalfa yield and quality under cold conditions.
Comparison of Cranial Cruciate Ligament Rupture Incidence among Parous and Nulliparous Rottweiler Bitches: Evidence from a Lifetime Cohort Study Supporting a Paradigm of Pregnancy-Associated Protection against Subsequent Non-Reproductive Disease Outcomes
Authors: Carrillo Andres E. , Maras Aimee H. , Suckow Cheri L. , Chiang Emily C. , Waters David J.
Published: September 2024

Emerging evidence in women supports the notion that pregnancy may reset disease resistance, thereby providing protection against subsequent adverse health outcomes, but this hypothesis has not been adequately explored in domestic dogs. Cranial cruciate ligament (CCL) rupture is a degenerative orthopedic disease that frequently affects pet dogs, and its risk has been associated with disruption of the reproductive hormone axis. Our research team is conducting a lifetime cohort study of purebred Rottweilers in North America that have lived 30% longer than breed-average. Detailed medical and reproductive histories of 33 nulliparous and 32 parous Rottweilers were generated from questionnaires and review of medical records. Interviews with owners of bitches in the nulliparous group served to limit selection bias, confirming that in no instance was the reason for nulliparity based upon the owner’s suspicion that a bitch had a heightened risk for CCL rupture. The risk of CCL rupture associated with parity and other exposure variables was estimated using multivariate logistic regression. Overall, CCL rupture was diagnosed in 17 of 65 (26%) bitches. Median age at first litter and CCL rupture were 3.6 and 6.5 years, respectively. Compared to nulliparous, parous bitches had a significant 94% reduction in CCL rupture risk adjusted for duration of ovary exposure, overweight body condition, dietary pattern, habitual physical activity, and work/sport activity [ORadjusted (95% CI) = 0.06 (0.01–0.46); (p = 0.006)]. The observed parity-associated CCL rupture risk reduction remained robust in sensitivity analysis excluding six nulliparous bitches for which decision not to breed was based on diagnosis of hip or elbow dysplasia, conditions which may be genetically linked to CCL rupture [ORadjusted (95% CI) = 0.08 (0.01–0.58); (p = 0.01)]. This work sets the stage for replication studies in other canine populations that should begin to explore the mechanistic basis for parity-associated CCL rupture risk reduction and to pursue other non-reproductive health outcomes in bitches whose incidence or severity may be parity-sensitive.
Variation in the Diet of Hatchling Morelet’s Crocodile (Crocodylus moreletii) in the Wild
Authors: González-Solórzano Mariana , López-Luna Marco A. , Hernández-Salazar Laura T. , Bello-Sánchez Edgar Ahmed , Morales-Mávil Jorge E.
Published: September 2024

The relationship between diet and behavior is essential to understanding an animal’s strategies to obtain food, considering ontogenical changes. In reptiles, there is a relationship between the length of the individual and the size of the prey it consumes. Studies have focused on the ontogenetic changes in reptile diets from hatchling to adult, but only a few studies have focused on the transition from hatchling to juvenile. We aimed to describe and analyze the composition, variation, diversity, and overlap in the diet of hatchling Morelet’s crocodiles (Crocodylus moreletii) for three size intervals during the hatchling–juvenile transition. We captured 31 hatchling Morelet’s crocodiles in an urbanized lagoon in Tabasco. We performed stomach-flushing to determine the diet. Additionally, we estimated the volume, frequency of occurrence, and relative importance of diet items and analyzed the relationship between prey type and the total length of the individuals. The diversity of the hatchling prey suggests a generalist diet. We observed two items not previously described in the diet of hatchling crocodiles. In addition, we found differences in diet between the initial and final size intervals, as increases in the length of prey appeared that they did not consume when they were hatchlings. Our results contribute new information to the dietary changes that occur during the hatchling–juvenile transition.
Dosing Evaluation of Ceftazidime–Avibactam in Intensive Care Unit Patients Based on Pharmacokinetic/Pharmacodynamic (PK/PD) Modeling and Simulation
Authors: Zazo Hinojal , Aguazul Yuridia , Lanao José M.
Published: September 2024

P. aeruginosa is the most common microorganism involved in many ICU-acquired infections. A correct dosage regimen is pivotal to avoiding resistance development, worse outcomes and higher mortality rates. The aim of this study was to perform a pharmacokinetic–pharmacodynamic (PK/PD) evaluation of recommended dosing regimens of ceftazidime–avibactam (CAZ–AVI) in ICU patients with different degrees of renal function for a specific strain of Pseudomonas aeruginosa. A semi-mechanistic PK/PD model has been developed. It allows for the simulation of CAZ–AVI steady-state plasma level curves and the evolution of bacterial growth curves. The percentage of bacterial load reduction and the value of the recommended PK/PD indices have been taken into account to define the success or failure of the regimens. Probabilistic analysis was performed using Monte Carlo simulations of two populations: control and ICU. In both populations, dosing regimens endorsed for patients with CLcr higher than 10 mL/min reach the PK/PD indices recommended, T > MIC > 90% and Cmin/MIC > 1.3. While dosage regimens endorsed for patients with CLcr of 10 mL/min or lower fail (T > MIC < 60% and Cmin/MIC < 0.35). However, proposed dosing regimens based on shortening dosing intervals for these patients would be successful, increasing bacterial load reduction by almost 50% and reaching the proposed PK/PD indices. Therefore, CAZ–AVI dosing strategies based on model-informed precision dosing (MIPD) could directly influence the efficacy of results in ICU patients with renal insufficiency.
Focusing on the Basic Principles of Dialysis to Optimize Antibiotic Therapy during Renal Replacement Therapy in Critically Ill Patients
Authors: Mariano Filippo , Mella Alberto , Biancone Luigi
Published: September 2024

Bacterial infections frequently occur in patients in the ICU undergoing renal dialysis using extracorporeal procedures (KRT) that can be applied for different time periods, such as Prolonged Intermittent Renal Replacement Therapy (PIRRT) or Continuous Kidney Replacement Therapy (CKRT) [...]
10-Gingerol Increases Antioxidant Enzymes and Attenuates Lipopolysaccharide-Induced Inflammation by Modulating Adipokines in 3T3-L1 Adipocytes
Authors: Preciado-Ortiz María Elizabeth , Martínez-López Erika , Pedraza-Chaverri José , Medina-Campos Omar Noel , Rodríguez-Echevarría Roberto , Reyes-Pérez Samantha Desireé , Rivera-Valdés Juan José
Published: September 2024

Background: Obesity increases reactive oxygen species production and alters adipokines levels, resulting in a low-grade chronic inflammation state, which contributes to tissue metabolic dysfunction. 10-gingerol, a phenol present in ginger, has shown potential anti-obesogenic effects in vitro. However, the antioxidant and anti-inflammatory properties of 10-gingerol have not been approached. The aim of this study was to investigate the effects of 10-gingerol on antioxidant enzymes’ expression and adipokine production in 3T3-L1 adipocytes in response to lipopolysaccharide (LPS)-induced inflammation. Methods: 10-gingerol antioxidant capacity was assessed through Oxygen Radical Absorbance Capacity (ORAC) , Ferric Reducing Antioxidant Power (FRAP), and radical scavenging activity of 2,2-diphenyl-2-picrylhydrazyl (DPPH) assays. 3T3-L1 cells were differentiated and stimulated with 100 ng/mL LPSs. Then, 15 µg/mL 10-gingerol was added for 48 h. The mRNA expression and protein abundance of antioxidant enzymes were evaluated by qPCR and Western blot, respectively. Adipokine levels were determined by ELISA. Results: 10-gingerol showed low FRAP and DPPH values but a moderate ORAC value. Moreover, 10-gingerol increased Gpx1 and Sod1 but downregulated Cat expression. Additionally, 10-gingerol significantly increased CAT and GPx1 levels but not SOD-1. Finally, adiponectin and leptin concentrations were increased while resistin and tumor necrosis factor alpha (TNFα) were decreased by 10-gingerol. Conclusions: 10-gingerol presented antioxidant potential by increasing antioxidant enzymes and attenuated LPS-induced inflammation by modulating adipokines in 3T3-L1 adipocytes.
Exploring the Effectiveness of Shallow and L2 Learner-Suitable Textual Features for Supervised and Unsupervised Sentence-Based Readability Assessment
Authors: Kostadimas Dimitris , Kermanidis Katia Lida , Andronikos Theodore
Published: September 2024

Simplicity in information found online is in demand from diverse user groups seeking better text comprehension and consumption of information in an easy and timely manner. Readability assessment, particularly at the sentence level, plays a vital role in aiding specific demographics, such as language learners. In this paper, we research model evaluation metrics, strategies for model creation, and the predictive capacity of features and feature sets in assessing readability based on sentence complexity. Our primary objective is to classify sentences as either simple or complex, shifting the focus from entire paragraphs or texts to individual sentences. We approach this challenge as both a classification and clustering task. Additionally, we emphasize our tests on shallow features that, despite their simplistic nature and ease of use, seem to yield decent results. Leveraging the TextStat Python library and the WEKA toolkit, we employ a wide variety of shallow features and classifiers. By comparing the outcomes across different models, algorithms, and feature sets, we aim to offer valuable insights into optimizing the setup. We draw our data from sentences sourced from Wikipedia’s corpus, a widely accessed online encyclopedia catering to a broad audience. We strive to take a deeper look at what leads to greater readability classification in datasets that appeal to audiences such as Wikipedia’s, assisting in the development of improved models and new features for future applications with low feature extraction/processing times.
Diagnosing Dyslexia in Early School-Aged Children Using the LSTM Network and Eye Tracking Technology
Authors: Gomolka Zbigniew , Zeslawska Ewa , Czuba Barbara , Kondratenko Yuriy
Published: September 2024

Dyslexia, often referred to as a specific reading disability, affects many students around the world. It is a neurological disorder that affects the ability to recognise words, and it causes difficulties in writing and reading comprehension. Previous computer-based methods for the automatic detection of dyslexia in children have had low efficiency due to the complexity of the test administration process and the low measurement reliability of the attention measures used. This paper proposes the use of a student’s mobile device to record the spatio-temporal trajectory of attention, which is then analysed by deep neural network long short-term memory (LSTM). The study involved 145 participants (66 girls and 79 boys), all of whom were children aged 9 years. The input signal for the neural network consisted of recorded observation sessions, which were packets containing the child’s spatio-temporal attention trajectories generated during task performance. The training set was developed using stimuli from Benton tests and an expert opinion from a specialist in early childhood psychology. The coefficients of determination of R2∼0.992 were obtained for the proposed model, giving an accuracy of 97.7% for the test set. The ease of implementation of this approach in school settings and its non-stressful nature make it suitable for use with children of different ages and developmental stages, including those who have not yet learned to read. This enables early intervention, which is essential for effective educational and emotional support for children with dyslexia.
A Switching Observer for State-of-Charge Estimation of Reconfigurable Supercapacitors
Authors: Li Heng , Zhou Zitao , Hu Chao
Published: September 2024

While State-of-Charge (SOC) estimation for supercapacitors has been extensively studied, most research focuses on single units. However, the recent introduction of reconfigurable circuits significantly alters system dynamics, rendering existing SOC estimation techniques inadequate. This paper addresses this challenge by employing a switching systems approach to estimate the SOC of supercapacitors with reconfigurable circuits. We first establish an RC model for the supercapacitor integrated with the reconfigurable circuit and thoroughly analyze the state continuity and observability of the resulting switched system. Subsequently, we propose a switching observer and evaluate its convergence properties by comparing its performance against other observer techniques. Experimental validation on a hardware platform demonstrates the superiority of our proposed observer for accurate SOC estimation in this context.
Refined Prior Guided Category-Level 6D Pose Estimation and Its Application on Robotic Grasping
Authors: Sun Huimin , Zhang Yilin , Sun Honglin , Hashimoto Kenji
Published: September 2024

Estimating the 6D pose and size of objects is crucial in the task of visual grasping for robotic arms. Most current algorithms still require the 3D CAD model of the target object to match with the detected points, and they are unable to predict the object’s size, which significantly limits the generalizability of these methods. In this paper, we introduce category priors and extract high-dimensional abstract features from both the observed point cloud and the prior to predict the deformation matrix of the reconstructed point cloud and the dense correspondence between the reconstructed and observed point clouds. Furthermore, we propose a staged geometric correction and dense correspondence refinement mechanism to enhance the accuracy of regression. In addition, a novel lightweight attention module is introduced to further integrate the extracted features and identify potential correlations between the observed point cloud and the category prior. Ultimately, the object’s translation, rotation, and size are obtained by mapping the reconstructed point cloud to a normalized canonical coordinate system. Through extensive experiments, we demonstrate that our algorithm outperforms existing methods in terms of performance and accuracy on commonly used benchmarks for this type of problem. Additionally, we implement the algorithm in robotic arm-grasping simulations, further validating its effectiveness.
Generation of Large-Scale Plasma Jet with Excitation of Bipolar Nanosecond Pulse Voltage in Single-Spiral Electrode Configuration
Authors: Sun Wenxiao , Yu Qianqian , Li Yao , Yuan Hao , Yang Dezheng
Published: September 2024

In this study, a single-outer-spiral electrode with inductance of 20 μH is employed to couple the energy input of a bipolar nanosecond pulse for the purpose of generating a large-scale atmospheric pressure plasma jet. When the spiral electrode is wrapped around a plasma jet tube with a length of 35 cm, the electrical field can be optimized, resulting in a stable laminar flow field, and a plasma jet with a length and diameter larger than 14 cm and 1.2 cm can be generated. A comparative study of the bipolar and unipolar pulse excitation voltages is also conducted, showing that the maximum lengths of the plasma jet excited by a bipolar pulse voltage, positive pulse voltage, and negative are 14 cm, 10 cm, and 7 cm, respectively. The temporal and spatially resolved spectra of the plasma jets excited by both bipolar and unipolar pulses are investigated, respectively, and the main physiochemical processes of the active species and the plasma dynamics’ evolution are discussed.
A Division-of-Labour Approach to Traffic Light Scheduling
Authors: Raubenheimer Hendrik , Engelbrecht Andries
Published: September 2024

Traffic light scheduling is a critical aspect of traffic management with many recently developed solutions that incorporate computational intelligence approaches. This paper presents a traffic light scheduling algorithm based on a task allocation model that simulates the division of labour among insects in a colony, specifically ant colonies. The developed algorithm switches the green light based on a probability calculated every second from the traffic volume around the traffic light. The application of this algorithm to several benchmark simulated traffic scenarios shows optimal performance compared to five other traffic scheduling algorithms.
Dual-Channel Supply Chain of Agricultural Products under Centralised and Decentralised Decision-Making
Authors: Wang Yujia , Gao Benhe
Published: September 2024

The rise of rural e-commerce, accelerated by the COVID-19 pandemic, has driven agricultural development, resulting in a dual-channel model that combines offline supermarket docking with online e-commerce direct sales. Furthermore, given the perishable nature of most agricultural products, consumers exhibit a preference for high-quality logistics services. This paper analyses the dynamics of the agricultural supply chain, beginning with the “leading enterprises + farmers” production mode, and establishes two optimal decision-making models for online and offline dual-channel agricultural supply chains, incorporating logistics service levels. The first model considers centralised decision-making, where leading agricultural producers and community superstores make decisions simultaneously, aiming to maximise the overall profit of the supply chain. The second model addresses decentralised decision-making in which the producer, as the dominant player in a Stackelberg game, anticipates the reactions of retailers and sets the wholesale price, online sales price, and online logistics service level accordingly. Retailers, as followers, then determine the offline sales price and offline logistics service level based on the producer’s decisions. Finally, we conduct a sensitivity analysis of the proposed models. Our findings reveal that as consumer focus on logistics service levels increases, the overall profit of the supply chain improves, and as the unit logistics cost corresponding to the level of logistics service increases, the marginal benefits of decreasing profit brought about by the increase in unit logistics cost also decrease.
Control System Hardware Design, Analysis and Characterization of Electromagnetic Diaphragm Pump
Authors: Skupień Szymon , Kowol Paweł , Capizzi Giacomo , Sciuto Grazia Lo
Published: September 2024

In this article, a novel electromagnetic diaphragm pump design controlled by an Arduino NANO microcontroller is proposed to pump liquid inside the pumping chamber completely separated from mechanical and transmission parts. The prototype is primarily based on alternating the polarity of two electromagnets that attract or repel a permanent magnet located on a flexible diaphragm. The system hardware layout is completed by electronic components:. an Arduino NANO microcontroller created by Atmel, Headquarters San Jose, California. and display within the cabinet to control the polarization of the electromagnets and exhibit the temperature inside the pump. The electromagnetic pump and control system consist of innovative approaches as a solution for the treatment of unclean water and integration with solar panel systems. In addition, the measurement tests of the electromagnetic pump, including the temperatures of electromagnets and the quantity of the pumped liquid within the chamber, indicate a dependence on the selected speed of the electromagnet’s polarization. The electromagnetic pump achieves high efficiency as a combination of the temperature and the amount of liquid that can be regulated and controlled by the switching speed of the electromagnet’s polarization.