bluuebunny/crossref_metadata_2025 huggingface dataset:
A novel prognostic scoring system combining the revised Tokuhashi score and the New England spinal metastasis score for preoperative evaluation of spinal metastases
Authors: Mavritsakis Dionisia , Amiot Louis-Philippe
Published: March 2024

Purpose

Numerous scoring systems have been developed in order to determine the prognosis of spinal metastases. Predicting as accurately as possible the life expectancy of patients with spinal metastatic disease is very important, as it's the decisive factor in selecting the optimal treatment for the patient. The Revised Tokuhashi score (RTS) and the New England Spinal Metastasis score (NESMS) are popular scoring systems used to determine the optimal treatment modality. However, they sometimes provide conflicting results. We propose a novel prognostic scoring system, which combines the RTS and NESMS scores in order to predict with greater accuracy the prognosis.

Methods

We retrospectively reviewed the data of 64 patients with spinal metastasis enrolled between 2012 and 2021 in the Department of Orthopedic Surgery-Spine, Hôpital Maisonneuve-Rosemont, Montréal, Que. The new score per patient was calculated as a combination of the RTS of each patient and the patient's corresponding NESMS. The new score was then compared to the actual patient survival period and divided into 3 categories: Low, Moderate and Good prognosis. We then compared the accuracy of our new score to RTS.

Results

In the Low Prognosis group, the reliability of predicting the prognosis was 51.9% in 27 patients. In the Moderate Prognosis group, the reliability of predicting the prognosis was 95.8% in 24 patients. In the Good Prognosis group, the reliability of predicting the prognosis was 100% in 13 patients. Our new score was found more accurate than RTS as the R2 parameter corresponding to the new score was significantly increased compared to the same parameter corresponding to the RTS score indicating a higher percentage of survival predictability for the new score as compared to the RTS score.

Conclusion

This study demonstrates that a new prognostic scoring system, which would combine the RTS and the NESMS, is promising in providing an improved accuracy for predicting the actual patient survival, especially for the moderate and good prognosis patients. An appropriate prospective investigation with a larger sample size should be conducted in order to further investigate the validity of this novel scoring system and its overall predictive value.
Evaluation of anti-Fel d 1 IgY ingredient for pet food on growth performance in kittens
Authors: Hedrick Erik D. , Matulka Ray A. , Conboy-Schmidt Lisa , May Kimberly A.
Published: March 2024

Introduction

The domestic cat (Felis catus) is one of the most common pets. Worldwide, approximately one in five adults are sensitive to cat allergens. The major cat allergen is the secretoglobulin Fel d 1, which is primarily produced in the salivary and sebaceous glands. Chickens produce IgY antibodies, which are similar in structure to mammalian IgG. When chickens are exposed to Fel d 1, anti-Fel d 1-specific IgY (AFD1) is produced and is naturally concentrated in egg yolk. The aim of this study was to evaluate the tolerability, effects on growth and food consumption, and potential adverse effects of a chicken egg product ingredient containing AFD1 in kittens.

Methods

This was a blinded, controlled study. Twenty-seven (27) eight-week old kittens were randomly assigned to three feeding groups containing 0 ppm AFD1 (Group 0), 8 ppm AFD1 (Group 1), and 16 ppm AFD1 (Group 2) for 84 days. Veterinary exams and bloodwork were performed on Day 42 and Day 84, and body weight and body condition score (BCS) were monitored weekly.

Results

Throughout the study, there were no signs of nutritional deficiency or adverse clinical events in any of the subjects. Administration of a chicken egg product ingredient containing AFD1 in the diet (whether in coating or combination of coating and top dress) had no significant effect on body weight nor food consumption, and all subjects maintained a healthy Body Condition Score (BCS) throughout the study. Moreover, there were no biologically significant differences in the mean clinical chemistry and hematology parameters.

Discussion

This study demonstrated that a diet formulated to contain up to 16  ppm AFD1, included in the coating and the top-dress of dry kitten food, was well tolerated, promoted adequate growth, and exhibited no adverse effects.
Data Mining Techniques for Endometriosis Detection in a Data-Scarce Medical Dataset
Authors: Caballero Pablo , Gonzalez-Abril Luis , Ortega Juan A. , Simon-Soro Áurea
Published: March 2024

Endometriosis (EM) is a chronic inflammatory estrogen-dependent disorder that affects 10% of women worldwide. It affects the female reproductive tract and its resident microbiota, as well as distal body sites that can serve as surrogate markers of EM. Currently, no single definitive biomarker can diagnose EM. For this pilot study, we analyzed a cohort of 21 patients with endometriosis and infertility-associated conditions. A microbiome dataset was created using five sample types taken from the reproductive and gastrointestinal tracts of each patient. We evaluated several machine learning algorithms for EM detection using these features. The characteristics of the dataset were derived from endometrial biopsy, endometrial fluid, vaginal, oral, and fecal samples. Despite limited data, the algorithms demonstrated high performance with respect to the F1 score. In addition, they suggested that disease diagnosis could potentially be improved by using less medically invasive procedures. Overall, the results indicate that machine learning algorithms can be useful tools for diagnosing endometriosis in low-resource settings where data availability and availability are limited. We recommend that future studies explore the complexities of the EM disorder using artificial intelligence and prediction modeling to further define the characteristics of the endometriosis phenotype.
Identification of Stress Responsive NAC Genes in Casuarina equisetifolia L. and Its Expression Analysis under Abiotic Stresses
Authors: Li Xiaomei , Li Nan , Wen Dandan , Yu Jianfeng , Hong Jiadu , Wu Mengjie , Cheng Longjun , Meng Shuai
Published: March 2024

NAC (NAM, ATAF and CUC)-like transcription factors, a class of plant-specific transcription factors, play a pivotal role in plant growth, development, metabolism, and stress response. Notably, a specific subclass of NAC family, known as SNAC (stress-responsive NAC), is particularly involved in the plant’s response to abiotic stress. As a very useful tree, Casuarina equisetifolia L. also has excellent stress resistance properties. To explore gene resources of C. equisetifolia which are associated with stress resistance and the molecular mechanisms that it employed is very helpful to its molecular-assisted breeding. In this study, 10 CeSNAC transcription factors were identified by constructing the phylogenetic tree of 94 CeNACs from the genome of C. equisetifolia L. together with 79 SNAC in different plant species. Phylogenetic tree analysis revealed that these 10 CeSNAC genes are classified into the ATAF (Arabidopsis transcription activation factor), NAP (NAC-like, activated by AP3/P1), and AtNAC3 subfamilies of the NAC family, all featuring the typical NAM (no apical meristem) domain, with the exception of CeSNAC7. In addition, all NAC transcription factors, except CeSNAC9, were localized in the nucleus. Examination of the CeSNAC promoter unveiled the presence of stress response elements such as a STRE (stress responsive element), an MBS (MYB binding site), an ABRE (abscisic acid responsive element) and a LTR (low temperature responsive element). Under various stress treatments, the majority of CeSNAC expressions exhibited induction in response to low temperature, drought, and high salt treatments, as well as ABA (abscisic acid) treatment. However, CeSNAC6, CeSNAC7, and CeSNAC9 were found to be inhibited specifically by drought treatment. Additionally, only CeSNAC3 and CeNAC9 expression was hindered while the rest of the CeSNAC expression were induced by MeJA (methyl jasmonate) treatment. These findings shed light on the relationship between different CeSNAC genes and their responses to abiotic stress conditions, providing valuable insights for further research into CeSNAC functions and aiding the development of stress-resistant varieties in C. equisetifolia.
An Evaluation System of the Modernization Level of Irrigation Districts with an Analysis of Obstacle Factors: A Case Study for North China
Authors: Fan Xichao , Qin Jingtao , Lv Mouchao , Jiang Mingliang
Published: March 2024

Irrigation districts are a pivotal infrastructure of agricultural water conservancy engineering. Implementing modernization will be the main task of large-scale irrigation districts for a considerable amount of time in the future. In this study, four typical large-scale irrigation districts in North China were investigated: the Renmin Shengliqu, Weishan, Shijin, and Zuncun irrigation districts. The concept of a modern irrigation district was deconstructed to establish an evaluation index system which includes four second-level indicators, twelve third-level indicators, and thirty fourth-level indicators. A hybrid approach based on AHP and OWA was used to quantify indicator weights used in group decision making. TOPSIS was introduced to measure the modernization level of the four irrigation districts. An obstacle factor diagnosis model was applied to search for key obstacle factors that will affect the modernization and improvement of the irrigation districts. The results showed that (1) the modernization levels of the Renmin Shengliqu, Weishan, Shijin, and Zuncun irrigation districts in 2020 and 2025 were 0.3916 and 0.5755, 0.3748 and 0.5396, 0.4493 and 0.6012, and 0.2343 and 0.6166, respectively. The evaluation results indicate that the four irrigation districts are still in the beginning phase (or even preparation phase) of the modernization process. (2) Eight indicators were identified as the main common obstacle factors for the four evaluated irrigation districts, including the irrigation water-use efficiency factor, the coverage proportion of information technology, the proportion of efficient water conservation irrigation areas, and so on. (3) There are two effective methods to enhance the modernization level of the four irrigation districts: improving water resource utilization efficiency and strengthening the management system with an emphasis on informatization. The present study can enrich the theoretical evaluation of irrigation districts and provide a scientific basis for the modernized construction and management of irrigation districts in China.
Repeated Cross-Sectional Survey of Ectoparasites in Sheep from Central Tunisia: Does Low Prevalence Indicate Good Hygiene or Resistance to Ectoparasites?
Authors: Elati Khawla , Daly Nesrine , Dhibi Mokhtar , Laaribi Hela , Rekik Mourad , Gharbi Mohamed
Published: March 2024

Sheep ectoparasites such as chewing lice, fleas and ticks are serious constraints to sheep productivity and are the cause of skin lesions in animals that decrease their market value. This study aims at investigating the ectoparasite fauna infesting small ruminants in the district of Sidi Bouzid (central Tunisia). A total of 1243 Barbarine and Queue Fine de l’Ouest (QFO) sheep were examined every two months for one year. Of the total animals examined, 74 were infested by at least 1 parasite group (5.95%). Three ectoparasite groups were identified as Psoroptes ovis (0.48%; 6/1243), ticks (5.3%; n = 66/1243) and one specimen of Ctenocephalides canis (0.08%; n = 1/1243). The most abundant tick among the 358 specimens was Rhipicephalus sanguineus sensu lato (n = 337; 94.1%), followed by Hyalomma impeltatum (n = 7/358; 1.9%), H. dromedarii (n = 7/358; 1.9%), H. excavatum (n = 5/358; 1.4%) and only two specimens of H. scupense (n = 2/358; 0.55%). The sheep herds showed low infestation prevalence by ectoparasite over the year, with a significant difference according to the seasons (p < 0.05). A higher infestation prevalence was recorded in March (14.36%). Barbarine sheep breed showed significantly higher infestation prevalence (16.8%) compared to QFO (0.8%) (p < 0.01). There were no differences in infestation prevalence according to sex of the animal or age groups. Knowledge of the ectoparasite population harboured by sheep, its activity dynamics and risk factors is required to develop effective ectoparasite control options. The low prevalence of ectoparasite infestation in sheep reported here may be due to possible genetic resistance or simply to successful hygiene measures implemented by farmers.
Short- and Long-Term Storage of Non-Domesticated European Mouflon (Ovis aries musimon) Cumulus–Oocyte Complexes Recovered in Field Conditions
Authors: Temerario Letizia , Cicirelli Vincenzo , Martino Nicola Antonio , Carbonari Alice , Burgio Matteo , Frattina Lorenza , Lacalandra Giovanni Michele , Rizzo Annalisa , Dell’Aquila Maria Elena
Published: March 2024

Reproductive biotechnologies can be used as a supporting tool, through gamete conservation and in vitro embryo production, in the preservation of invaluable and irreplaceable animal genetic resources. In the present study, immature mouflon cumulus–oocyte complexes (COCs) collected from ovariectomized female ovaries underwent short- or long-term conservation (24 h maintained in Earle’s/Hank’s (EH) medium or vitrification) under field conditions and afterwards transported to the laboratory where they were cultured for in vitro maturation (IVM) and assessed for oocyte meiotic competence and bioenergetic–oxidative status. Utilization of both storage techniques led to COC morphology preservation, as well as cumulus expansion and oocyte meiotic resumption after the IVM procedure. Quantitative bioenergetic–oxidative parameters were reduced in vitrified oocytes compared with EH ones. Immature COC storage needs to be optimized in both domesticated and non-domesticated sheep as a part of the strategy to avoid the loss of valuable genotypes of these animal species.
Exosomal Dynamics and Brain Redox Imbalance: Implications in Alzheimer’s Disease Pathology and Diagnosis
Authors: Bir Aritri , Ghosh Arindam , Chauhan Aman , Saha Sarama , Saini Adesh K. , Bisaglia Marco , Chakrabarti Sasanka
Published: March 2024

Oxidative burden plays a central role in Alzheimer’s disease (AD) pathology, fostering protein aggregation, inflammation, mitochondrial impairment, and cellular dysfunction that collectively lead to neuronal injury. The role of exosomes in propagating the pathology of neurodegenerative diseases including AD is now well established. However, recent studies have also shown that exosomes are crucial responders to oxidative stress in different tissues. Thus, this offers new insights and mechanistic links within the complex pathogenesis of AD through the involvement of oxidative stress and exosomes. Several studies have indicated that exosomes, acting as intracellular communicators, disseminate oxidatively modified contents from one cell to another, propagating the pathology of AD. Another emerging aspect is the exosome-mediated inhibition of ferroptosis in multiple tissues under different conditions which may have a role in neurodegenerative diseases as well. Apart from their involvement in the pathogenesis of AD, exosomes enter the bloodstream serving as novel noninvasive biomarkers for AD; some of the exosome contents also reflect the cerebral oxidative stress in this disease condition. This review highlights the intricate interplay between oxidative stress and exosome dynamics and underscores the potential of exosomes as a novel tool in AD diagnosis.
Adaptive Fuzzy Sliding Mode Control and Dynamic Modeling of Flap Wheel Polishing Force Control System
Authors: Hong Qi , Zhou Tianyi , Qi Junde
Published: March 2024

Polishing force is one of the key process parameters in the polishing process of blisk blades, and its control accuracy will affect the surface quality and processing accuracy of the workpiece. The contact mechanism between the polishing surface and flap wheel was analyzed, and the calculation model of the polishing force and nonlinear dynamic model of the polishing force control system was established. Considering the influence of friction characteristics, parameter perturbation, and nonlinear dead zone on the control accuracy of the polishing force system, an adaptive fuzzy sliding mode controller (AFSMC) was designed. AFSMC uses a fuzzy system to adaptively approximate the nonlinear function terms in the sliding mode control law, adopts an exponential approach law in the switching control part of the sliding mode control (SMC), and designs the adaptive law for adjustable parameters in the fuzzy system based on the Lyapunov Theorem. Simulation and experimental results show that the designed AFSMC has a fast dynamic response, strong anti-interference ability, and high control accuracy, and it can reduce SMC high-frequency chatter. Polishing experiments show that compared with traditional PID, AFSMC can improve the form and position accuracy of the blade by 42% and reduce the surface roughness by 50%.
Application of Enhanced YOLOX for Debris Flow Detection in Remote Sensing Images
Authors: Ma Shihao , Wu Jiao , Zhang Zhijun , Tong Yala
Published: March 2024

Addressing the limitations, including low automation, slow recognition speed, and limited universality, of current mudslide disaster detection techniques in remote sensing imagery, this study employs deep learning methods for enhanced mudslide disaster detection. This study evaluated six object detection models: YOLOv3, YOLOv4, YOLOv5, YOLOv7, YOLOv8, and YOLOX, conducting experiments on remote sensing image data in the study area. Utilizing transfer learning, mudslide remote sensing images were fed into these six models under identical experimental conditions for training. The experimental results demonstrate that YOLOX-Nano’s comprehensive performance surpasses that of the other models. Consequently, this study introduces an enhanced model based on YOLOX-Nano (RS-YOLOX-Nano), aimed at further improving the model’s generalization capabilities and detection performance in remote sensing imagery. The enhanced model achieves a mean average precision (mAP) value of 86.04%, a 3.53% increase over the original model, and boasts a precision rate of 89.61%. Compared to the conventional YOLOX-Nano algorithm, the enhanced model demonstrates superior efficacy in detecting mudflow targets within remote sensing imagery.
Exploring Key Parameters in Adsorption for Effective Fluoride Removal: A Comprehensive Review and Engineering Implications
Authors: de Carvalho Costa Letícia Reggiane , Jurado-Davila Ivone Vanessa , Oliveira Júlia Toffoli De , Nunes Keila Guerra Pacheco , Estumano Diego Cardoso , de Oliveira Robson Alves , Carissimi Elvis , Féris Liliana Amaral
Published: March 2024

Water pollution, particularly from elevated fluoride ion (F−) concentrations, is a significant challenge in many developing countries, particularly those relying on groundwater. The stable form of fluoride, F−, poses health risks, leading to concerns about various diseases and harmful effects. Despite global efforts, high F− concentrations (>1.5 mg L−1) persist in numerous countries, requiring effective and sustainable removal methods. Adsorption, known for its simplicity, cost-effectiveness, and efficiency, stands out as a promising technique for F− removal from drinking water. Successful commercial implementation necessitates the optimization of separation conditions. This systematic literature review focuses on the adsorption process for F− removal, exploring parameters such as temperature, adsorbent particle size, pH, adsorbent mass, and co-existing ions for efficient removal. Observations indicate that, despite the utilization of a diverse range of adsorbents, several limitations persist. These include low adsorption capacity, a sluggish adsorption rate, a restricted pH range, and high associated costs. The mechanistic understanding of adsorption and the ongoing development of novel adsorbents remain focal points for future research. Additionally, there is a need to explore alternative kinetic models grounded in statistical factors and give due consideration to thermodynamic studies.
Effects of AM/PM Diets on Laying Performance, Egg Quality, and Nutrient Utilisation in Free-Range Laying Hens
Authors: Jahan Afsana A. , Dao Thi Hiep , Morgan Natalie K. , Crowley Tamsyn M. , Moss Amy F.
Published: March 2024

Laying hen nutrient requirements change throughout the day, due to the cyclic nature of egg formation. Generally, more energy and protein are required in the morning when the albumen is deposited around the yolk, and more calcium is required in the evening when the eggshell is formed. The aim of this study was to determine if feeding laying hens diets tailored to their specific nutritional and physiological requirements throughout the day, by feeding higher levels of protein and energy in the morning and higher levels of calcium in the evening, is more beneficial than feeding one diet all day. Hy-Line Brown laying hens (n = 360) were housed in free-range floor pens (18 pens with 20 hens/pen) from 34 to 53 weeks of age (WOA). Half of the birds (n = 180, nine replicate pens) were fed a conventional layer hen diet all day (control) and the remaining birds (n = 180, nine replicate pens) were fed an AM diet from 08:00 h to 16:00 h and PM diet from 16:00 h to 08:00 h (AM/PM). From 39 WOA, hens were given access to an outdoor range from 09:00 h to 18:00 h via pop holes. Egg weight and hen-day egg production were measured daily, and feed consumption and the feed conversion ratio (FCR) were measured weekly. Hen weight and egg size uniformity were determined at 43 and 53 WOA, and egg quality was measured at 53 WOA. A total of 72 hens (4 hens/pen, 36 hens/treatment) were euthanised at 53 WOA to determine ileal apparent energy and nitrogen digestibility. A cost–benefit analysis for the study period, based on feed costs and egg mass, was calculated. Overall, the results showed that the AM/PM treatment increased egg mass by 2.15% (60.4 vs. 59.1 g/hen/day, p = 0.086) and improved feed efficiency by 8.34% (2.231 vs. 2.436 kg feed/kg egg, p = 0.030) compared with the control. A higher yolk colour score was observed in eggs from hens on the AM/PM treatment (p = 0.002), but no other significant effects of the treatments on egg quality were observed. Ileal digestible energy and digestible nitrogen coefficient were lower in hens on the AM/PM treatment compared with the control treatment (both p < 0.001). However, the AM/PM treatment was attributed to a lower feed cost to egg mass compared with the control treatment (p < 0.001). In conclusion, using an AM/PM feeding strategy was found to be economically beneficial.
Radiological Measurement of Sella Turcica Dimensions in Different Skeletal Patterns in Romanian Patients
Authors: Szuhanek Camelia-Alexandrina , Uzun Anca-Patricia , Galuscan Atena , Alexa Vlad Tiberiu , Romanec Liviu-Cristian , Feştilă Dana-Gabriela
Published: March 2024

(1) Background: The purpose of this study was to evaluate the morphology and linear dimensions of sella turcica in Romanian participants from all three skeletal classes to see whether there were any differences. (2) Method: We examined 90 lateral cephalometric radiographs of patients aged 12 and older and divided them into skeletal classes I, II, and III (30 participants in each). Sella turcica linear measurements such as length, depth, and anteroposterior diameter were measured and studied. To see the nature of our data, Q–Q plots tests were performed. By examining these tests performed for each variable belonging to a particular class, it can be noted that the points are fairly well distributed along some lines, meaning that the data are normally distributed. An Anova test with Bonferroni correction was used to compare the mean values of the examined parameters between the classes. Also, to observe the correlation between our experimental data, the Pearson correlation coefficient was calculated. (3) Results: In all three skeletal classes, the average length of the sella was 8.98 mm ± 1.470, the average depth was 7.99 mm ± 1.081, and the average diameter was 10.29 mm ± 1.267. For all examined linear dimensions, there was a statistically significant difference between class I and class III subjects and between class II and class III subjects (p < 0.001). The morphology of sella turcica was found to be normal in 51.1% of instances, representing the majority across all skeletal classes. In the Romanian population, sella turcica has shown a significant amount of variation. Class III subjects had larger sella dimensions, whereas class II subjects had smaller values. (4) Conclusions: The measurements and morphology of the sella analysed in the present research can serve as standards for subsequent research concerning the sella turcica region in individuals from Romania.
An Improved Sparrow Search Algorithm for the Optimization of Variational Modal Decomposition Parameters
Authors: Du Haoran , Wang Jixin , Qian Wenjun , Zhang Xunan
Published: March 2024

Variational modal decomposition (VMD) is frequently employed for both signal decomposition and extracting features; however, the decomposition outcome is influenced by the quantity of intrinsic modal functions (IMFs) and the specific parameter values of penalty factors. To tackle this issue, we propose an algorithm based on the Halton sequence and the Laplace crossover operator for the sparrow search algorithm–VMD (HLSSA-VMD) to fine-tune the parameters of VMD. First, the population initialization by the Halton sequence yields higher-quality initial solutions, which effectively addresses the issue of the algorithm’s sluggish convergence due to overlapping and the lack of diversity of the initial solutions. Second, the introduction of the Laplace crossover operator (LX) to perturb the position of the best individual in each iteration helps to prevent the algorithm from becoming ensnared in a local optimum and improves the convergence speed of the algorithm. Finally, from the simulation of 17 benchmark test functions, we found that the HLSSA exhibited superior convergence accuracy and accelerated convergence pace, as well as better robustness than the particle swarm optimization (PSO) algorithm, the whale optimization algorithm (WOA), the multiverse optimization (MVO) algorithm, and the traditional sparrow search algorithm (SSA). In addition, we verified the effectiveness of the HLSSA-VMD algorithm on two simulated signals and compared it with PSO-VMD, WOA-VMD, MVO-VMD, and SSA-VMD. The experimental findings indicate that the HLSSA-VMD obtains better parameters, confirming the superiority of the algorithm.
Special Issue: Artificial Intelligence Technology in Medical Image Analysis
Authors: Szilágyi László , Kovács Levente
Published: March 2024

Artificial intelligence (AI) technologies have significantly advanced the field of medical imaging, revolutionizing diagnostic and therapeutic processes [...]
GCN–Informer: A Novel Framework for Mid-Term Photovoltaic Power Forecasting
Authors: Zhuang Wei , Li Zhiheng , Wang Ying , Xi Qingyu , Xia Min
Published: March 2024

Predicting photovoltaic (PV) power generation is a crucial task in the field of clean energy. Achieving high-accuracy PV power prediction requires addressing two challenges in current deep learning methods: (1) In photovoltaic power generation prediction, traditional deep learning methods often generate predictions for long sequences one by one, significantly impacting the efficiency of model predictions. As the scale of photovoltaic power stations expands and the demand for predictions increases, this sequential prediction approach may lead to slow prediction speeds, making it difficult to meet real-time prediction requirements. (2) Feature extraction is a crucial step in photovoltaic power generation prediction. However, traditional feature extraction methods often focus solely on surface features, and fail to capture the inherent relationships between various influencing factors in photovoltaic power generation data, such as light intensity, temperature, and more. To overcome these limitations, this paper proposes a mid-term PV power prediction model that combines Graph Convolutional Network (GCN) and Informer models. This fusion model leverages the multi-output capability of the Informer model to ensure the timely generation of predictions for long sequences. Additionally, it harnesses the feature extraction ability of the GCN model from nodes, utilizing graph convolutional modules to extract feature information from the ‘query’ and ‘key’ components within the attention mechanism. This approach provides more reliable feature information for mid-term PV power prediction, thereby ensuring the accuracy of long sequence predictions. Results demonstrate that the GCN–Informer model significantly reduces prediction errors while improving the precision of power generation forecasting compared to the original Informer model. Overall, this research enhances the prediction accuracy of PV power generation and contributes to advancing the field of clean energy.
New Method to Study the Effectiveness of Mining Equipment: A Case Study of Surface Drilling Rigs
Authors: Gutiérrez-Diez Juan C. , Castañón Ana M. , Bascompta Marc
Published: March 2024

The sustainable development of mining processes requires a deep knowledge of the effectiveness of mining equipment and is quite complex to analyze due to the intrinsic characteristics of the mining industry. In this regard, its measurement and control can lead to appropriate management, improving the mining processes’ efficiency, increasing safety levels, and reducing environmental impacts. This paper developed a new methodology to study the effectiveness of equipment in mining processes, researching the impacts of process management, process control, operating conditions, operational mining schedule, and maintenance programs on the effectiveness of drilling rig fleets using two actual coal mines located in the northwest of Spain and data collected over 10 years. Thus, a new method, called Overall Mining Equipment Effectiveness (OMEE), was developed, verifying its appropriateness and flexibility to analyze the effectiveness of mining equipment by examining the availability rate, utilization rate, and productivity index.
Development and Evaluation of an Image Processing-Based Kinesthetic Learning System
Authors: Yıldız Deniz , Fidan Uğur , Yıldız Mehmet , Er Büşra , Ocak Gürbüz , Güngör Fatih , Ocak İjlal , Akyildiz Zeki
Published: March 2024

This study aims to develop an interactive language learning game and explore its efficacy for English language learners. A computer-generated playground was projected onto a large classroom floor (4 × 3 m) with a wide-angle projection device. A Kinect depth camera determined the spatial positions of the playground and the positions of the students’ heads, feet, and bodies. Then, we evaluated the system’s effect on English education through pre- and post-tests. While there was no significant difference between the groups in terms of achievement in the pre-tests, the experimental group exhibited significantly greater improvement in the post-tests (F: 14.815, p < 0.001, η2p: 0.086). Also, both groups demonstrated significant learning gains in post-tests compared to pre-tests (F: 98.214, p < 0.001, η2p: 0.383), and the group x time interaction of the experimental group increased more in percentage (32.32% vs. 17.54%) compared to the control group (F: 9.166, p < 0.003, η2p: 0.055). Qualitative data from student views indicated enhanced learning pace, vocabulary acquisition, enjoyment of the learning process, and increased focus. These findings suggest that a kinesthetic learning environment can significantly benefit English language learning in children.
A Generalized Nonlinear Beam Element for Slender RC Members Using a Polygonization Section Approach—Part I: Theoretical Formulation
Authors: Sfondylis Dimitris K. , Sfakianakis Manolis G.
Published: March 2024

A mathematical model for RC beam elements is presented that falls into the category of distributed inelasticity models discretizing the cross-section in polygons (trapezoids, triangles). The models falling into these categories are considered to be able to describe in the best manner the inelastic behavior of the element across its whole clear length, since its response results from the numerical integration of the stiffnesses of its cross-sections, while presenting an ideal combination of accuracy, simplicity, and computational cost. The behavior of the cross-section is described through the constitutive relationships σ–ε of its materials for cyclic loading. The main objectives for the development of the proposed mathematical model are as follows: (a) the increased accuracy of the results compared to existing experimental ones; (b) the limitless generalization of its application, regarding of the cross-section shape; and (c) the elimination of the numerical problems presented by the application of other related models, a fact that leads to their impractical use in real three-dimensional structures. The proposed model falls under the category of distributed inelasticity models. This paper focuses on its initial version, which targets slender beam elements with negligible shear and bond-slip effects (i.e., with ribbed bars, sufficiently anchored). Thus, it is applicable to 2D and 3D framed structures that fulfill these conditions, while its modular structure allows for future adjustments for the inclusion of other effects.
Impact of the Sea Effect on Sudden Fog on the Western Coast of the Bohai Sea: A Case Study
Authors: Tian Meng , Wu Bingui , Wang Jing , Yang Jianbo , Jin Zhenhua , Guo Yang , Liu Hailing
Published: March 2024

The term “sea effect” generally refers to the process of air mass modification after cold air flows above a warm sea surface. Affected by the sea effect, small-scale and sudden fogs have occasionally been observed on the western coast of the Bohai Sea. A more in-depth study of this type of fog is crucial for ensuring the safety of maritime and aerial traffic routes in this region. This study investigated the formation mechanism of this specific type of fog on the morning of 17 October 2007, utilizing both meteorological stations and 255 m tower observations, combined with the results of the Weather Research and Forecasting model (WRF). It is demonstrated that Bohai Sea evaporation and the associated water vapor advection played crucial roles in the formation of fog along the west coast of the Bohai Sea. The cold return flow became more moist as it passed over the warm Bohai Sea, which was the primary contributor to triggering regional fog on the western coast. A moisture budget analysis revealed that water vapor from the Bohai Sea intruded into its western coast along an eastward trajectory, dominating the oscillations in the net moisture flux. The eastern water vapor flux significantly increased at 17:00 on the 16th (Local time, LST), reaching its peak at 21:00. Correspondingly, the fog water growth rate began to increase at 23:00 on the 16th, reaching its maximum at 03:00 on the 17th. A sensitivity experiment on evaporation further indicated that the Bohai sea effect played a decisive role in fog formation. With a tenfold reduction in evaporation from the Bohai Sea and subsequent significant weakening of water vapor advection, the simulated fog along the western coast of the Bohai Sea completely disappeared. Understanding the formation mechanism of this type of fog is beneficial for refining forecasting focal points, thereby enhancing forecast accuracy in a targeted manner.
Identifying Strategies for Effective Biodiversity Preservation and Species Status of Chilean Amphibians
Authors: Vidal Marcela A. , Henríquez Nayadet , Torres-Díaz Cristian , Collado Gonzalo , Acuña-Rodríguez Ian S.
Published: March 2024

Resources are limited in global biodiversity conservation efforts, which emphasizes the significance of setting conservation priorities. Using standardized criteria, we evaluated 58 amphibian species in Chile to determine their conservation priority (CP). Species with insufficient historical data had their values marked as missing. With a median value of p = 1.67, the results demonstrated CP values ranging from p = 0.48 to p = 3.0, classifying species into priority and non-priority groups. Four levels were established for the priority categories: no priority, low priority, medium priority, and high priority. Additionally, the Telmatobiidae and Alsodidae families were identified as two more priority families. Notably, the species with the highest priority were found to be T. halli, T. fronteriensis, T. philippii, T. chusmisensis, A. pehuenche, and Alsodes tumultuosus, where T. philippii and T. fronteriensis have equal priority for conservation at the national level according to the conservation priority analysis. Eight priority families—the Alsodidae, Batrachylidae, Bufonidae, Ceratophryidae, Leptodactylidae, Rhinodermatidae, and Telmatobiidae—were determined, and 14 species—or 24% of the species examined—need further study. Based on the conservation priority analysis, the species T. fronteriensis and T. philippii share the highest priority for conservation at the national level (p = 2.50). With 70% of the amphibians under study being threatened mainly by habitat loss, pollution, and emerging diseases, the creation of conservation categories made the threat assessment process easier. Due to a lack of information on geographic distribution and abundance, quantitatively classifying amphibians in Chile remains difficult. The analysis of conservation priorities and potential extinction threats informs appropriate management strategies.
Reagentless Glucose Biosensor Based on Combination of Platinum Nanostructures and Polypyrrole Layer
Authors: German Natalija , Popov Anton , Ramanaviciene Almira
Published: March 2024

Two types of low-cost reagentless electrochemical glucose biosensors based on graphite rod (GR) electrodes were developed. The electrodes modified with electrochemically synthesized platinum nanostructures (PtNS), 1,10-phenanthroline-5,6-dione (PD), glucose oxidase (GOx) without and with a polypyrrole (Ppy) layer—(i) GR/PtNS/PD/GOx and (ii) GR/PtNS/PD/GOx/Ppy, respectively, were prepared and tested. Glucose biosensors based on GR/PtNS/PD/GOx and GR/PtNS/PD/GOx/Ppy electrodes were characterized by the sensitivity of 10.1 and 5.31 μA/(mM cm2), linear range (LR) up to 16.5 and 39.0 mM, limit of detection (LOD) of 0.198 and 0.561 mM, good reproducibility, and storage stability. The developed glucose biosensors based on GR/PtNS/PD/GOx/Ppy electrodes showed exceptional resistance to interfering compounds and proved to be highly efficient for the determination of glucose levels in blood serum.
Emotion Regulation and Self-Efficacy: The Mediating Role of Emotional Stability and Extraversion in Adolescence
Authors: Doménech Pablo , Tur-Porcar Ana M. , Mestre-Escrivá Vicenta
Published: March 2024

The feeling of emotional self-efficacy helps people understand how to handle positive and negative emotions. Emotion regulation is the process that helps people control their emotions so that they can adapt to the demands of the environment. This study has a twofold aim. First, it examines the relationships among emotion regulation, the personality traits of extraversion and emotional stability, and the feeling of emotional self-efficacy for positive and negative emotions in an adolescent population. Second, it examines the mediating role of personality traits (extraversion and emotional stability) in the relationship between emotion regulation and emotional self-efficacy for positive and negative emotions. The participants were 703 adolescents (49.9% male and 50.1% female) aged between 15 and 18 years (M = 15.86, SD = 0.30). Significant relationships were observed among emotion regulation, the personality traits of extraversion and emotional stability, and emotional self-efficacy for positive and negative emotions. The structural equation model confirmed the direct link between emotion regulation and emotional self-efficacy and mediation by the personality traits of extraversion and emotional stability. This study confirms that emotional self-efficacy is connected to the emotion regulation strategies that adolescents use. Effective emotion regulation encourages self-perception and emotional coping. The results are discussed in connection to previous research.
Building a Better Defense: Expanding and Improving Natural Killer Cells for Adoptive Cell Therapy
Authors: Maia Andreia , Tarannum Mubin , Lérias Joana R. , Piccinelli Sara , Borrego Luis Miguel , Maeurer Markus , Romee Rizwan , Castillo-Martin Mireia
Published: March 2024

Natural killer (NK) cells have gained attention as a promising adoptive cell therapy platform for their potential to improve cancer treatments. NK cells offer distinct advantages over T-cells, including major histocompatibility complex class I (MHC-I)-independent tumor recognition and low risk of toxicity, even in an allogeneic setting. Despite this tremendous potential, challenges persist, such as limited in vivo persistence, reduced tumor infiltration, and low absolute NK cell numbers. This review outlines several strategies aiming to overcome these challenges. The developed strategies include optimizing NK cell expansion methods and improving NK cell antitumor responses by cytokine stimulation and genetic manipulations. Using K562 cells expressing membrane IL-15 or IL-21 with or without additional activating ligands like 4-1BBL allows “massive” NK cell expansion and makes multiple cell dosing and “off-the-shelf” efforts feasible. Further improvements in NK cell function can be reached by inducing memory-like NK cells, developing chimeric antigen receptor (CAR)-NK cells, or isolating NK-cell-based tumor-infiltrating lymphocytes (TILs). Memory-like NK cells demonstrate higher in vivo persistence and cytotoxicity, with early clinical trials demonstrating safety and promising efficacy. Recent trials using CAR-NK cells have also demonstrated a lack of any major toxicity, including cytokine release syndrome, and, yet, promising clinical activity. Recent data support that the presence of TIL-NK cells is associated with improved overall patient survival in different types of solid tumors such as head and neck, colorectal, breast, and gastric carcinomas, among the most significant. In conclusion, this review presents insights into the diverse strategies available for NK cell expansion, including the roles played by various cytokines, feeder cells, and culture material in influencing the activation phenotype, telomere length, and cytotoxic potential of expanded NK cells. Notably, genetically modified K562 cells have demonstrated significant efficacy in promoting NK cell expansion. Furthermore, culturing NK cells with IL-2 and IL-15 has been shown to improve expansion rates, while the presence of IL-12 and IL-21 has been linked to enhanced cytotoxic function. Overall, this review provides an overview of NK cell expansion methodologies, highlighting the current landscape of clinical trials and the key advancements to enhance NK-cell-based adoptive cell therapy.
Effect of Temperature, Vacuum Condition and Surface Roughness on Oxygen Boost Diffusion of Ti–6Al–4V Alloy
Authors: Xu Yujie , Jiang Yong , Xie Jinyang , Xu Qingchen , Fei Hao , Lu Yilan , Gong Jianming
Published: March 2024

Oxygen boost diffusion (OBD) is an effective technology for improving the surface hardness of titanium and its alloys. In this present paper, the effect of temperature, vacuum condition and surface roughness on oxygen boost diffusion of Ti–6Al–4V alloy are studied. Test results show that OBD processing can be achieved at a low temperature and over long times, as well as at a high temperature and over short times. By comparing processing efficiency and mechanical properties, high temperatures and short times are preferred for OBD treatment. The influence of vacuum conditions on oxygen vacuum diffusion is significant. Under low vacuum degree conditions, relatively high oxygen content not only corrodes the OBD layer but also leads to spalling of the outmost surface of the OBD layer and the remaining oxide layer. High surface roughness can induce cracking not only in the oxide layer during the oxidation process but also in the outmost surface of the OBD layer during the vacuum diffusion process.
Ovarian Cancer in the Older Manitoban Population—Treatment Tolerance and Cancer-Related Outcomes: A Manitoba Ovarian Cancer Outcomes (MOCO) Group Study
Authors: Roberts Lesley F. , Lambert Pascal , Nachtigal Mark W. , Altman Alon D. , Dean Erin
Published: March 2024

Background: In Canada, individuals with gynecologic reproductive organs (ovaries, fallopian tubes, uterus) over the age of 70 comprise a large proportion of epithelial ovarian cancer patients. These patients often have co-morbidities, polypharmacy, or decreased functional status that may impact treatment initiation and tolerance. Despite this, there is limited evidence to guide treatment for older patients diagnosed with ovarian epithelial carcinoma. Methods: This is a retrospective study with data from Manitoba, Canada. The data were obtained from the Manitoba Ovarian Cancer Database, the Manitoba Cancer Registry, and electronic health records. All individuals with epithelial ovarian, fallopian tube, or peritoneal cancer diagnosed between 2009 and 2018 were identified. Patients aged > 70 at the time of diagnosis were included in the study cohort. Results: Four hundred and forty individuals were included. The majority had advanced stage disease (56%). Moreover, 59% of patients received no chemotherapy. Of the patients who received chemotherapy, 20% received <2 cycles and 21% required a dose reduction due to toxicity. Univariable and multivariable analysis identified advanced stage (p < 0.001), treatment modality (p < 0.001), and advanced age at diagnosis (p < 0.001) with poorer overall survival. Conclusions: Our study demonstrated a high rate of chemotherapy dose reduction and discontinuation in the elderly epithelial ovarian cancer population. Further research is needed to identify risk factors for treatment discontinuation and intolerance in this population.
Shallow Hard-Bottom Benthic Assemblages of South Bay (Antarctic Peninsula): An Update 40 Years Later
Authors: Morales Sol , Cárdenas César A. , Bravo-Gómez Diego , Lagger Cristian
Published: March 2024

This work completes and updates the information about the diversity and distribution of benthic assemblages in an Antarctic fjord (South Bay, Antarctic Peninsula) 40 years after the first and only community-level study was conducted there. To determine the community changes, a photographic survey was conducted at four sites with different substrate inclinations along a bathymetric gradient of 5–20 m depth. In total, 160 photoquadrats were analyzed, resulting in a total area of 40 m2. Sixty taxa represented by 12 phyla were identified, of which eight phyla corresponded to animals. The remaining species corresponded to macroalgae and benthic diatoms, both taxa presenting the highest coverages of the entire study area. The highest richness and diversity values were obtained at greater depths and at the sites with the steepest slopes. Here, we discuss the role of substrate inclination and depth in the structure of the benthic assemblages concerning possible variations in the presence and frequency of physical disturbances (e.g., ice disturbance and sedimentation). The abundances, densities, and distributions of all species found are detailed, updating the ecological data of the benthic ecosystem of this Antarctic fjord from the previously published assessment four decades ago. In a continent where rapid environmental changes are being experienced due to climate-induced processes, we discuss the first massive record of benthic diatoms in this fjord and the striking absence of the sea urchin Sterechinus neumayeri, an abundant species from previous records from the early 1980s.