bluuebunny/crossref_metadata_2025 huggingface dataset:
Management Strategy of Slow-Release Nitrogen Fertilizers for Direct-Sown Cotton after Wheat Harvest
Authors: Lu Yi , Xu Jingli , Liu Zhenyu , Chen Yuan , Zhang Xiang , Chen Dehua
Published: March 2024

The direct-sown cotton after wheat harvest (DSCWH) cropping system has attracted wide attention due to reduced labor inputs compared to transplanting. However, the management strategy of slow-release nitrogen is unclear in such a system. This study aims to investigate the impact of different timings and dosages of slow-release nitrogen fertilizer on the yield, biomass accumulation and distribution, and nitrogen absorption and nitrogen utilization in the DSCWH cropping system. This study was investigated at the experimental farm of Yangzhou University, China in 2020 and 2021, with the short-season cotton variety “Zhongmian 50” used as experimental material. Three dosages of the slow-release nitrogen fertilizer (45 kg·ha−1, 90 kg·ha−1, and 135 kg·ha−1) were applied at two stages of growth (two-leaf and four-leaf). The results showed that applying a 90 kg·ha−1 dosage at the two-leaf stage achieved the highest yield, which was increased by 12.6% compared to the no-fertilization control. Applying 90 kg·ha−1 of the slow-release nitrogen at the two-leaf stage promoted biomass accumulation, especially in reproductive organs, and this increase in biomass of reproductive organs was attributed to optimum nitrogen accumulation in reproductive organs (80~140 kg·ha−1). In addition, when 90 kg·ha−1 was applied at the two-leaf stage, there was a significant enhancement in nitrogen recovery efficiency (NRE), nitrogen agronomic use efficiency (NAE), and nitrogen physiological efficiency (NPE), with increases of 7.2% to 13.0%, 5.7% to 5.8%, and 5.6% to 6.5%, respectively. These results revealed that applying slow-release nitrogen fertilizer with the optimal dosage at the seedling stage could significantly enhance nitrogen use efficiency, nitrogen accumulation and partitioning, and biomass accumulation and distribution, which ultimately resulted in a higher lint yield in DSCWH. Therefore, to optimize yield and NUE, 90 kg·ha−1 slow-release nitrogen applied at the two-leaf stage would be recommended in the direct-sown cotton after wheat harvest cropping system.
Herbicidal Potential of the Natural Compounds Carvacrol, Thymol, Eugenol, p-Cymene, Citral and Pelargonic Acid in Field Conditions: Indications for Better Performance
Authors: Torres-Pagán Natalia , Muñoz Marta , Barbero Sara , Mamone Roberta , Peiró Rosa , Carrubba Alessandra , Sánchez-Moreiras Adela M. , Gómez de Barreda Diego , Verdeguer Mercedes
Published: March 2024

In recent years, interest in natural products with herbicidal activity as new tools for integrated weed management has increased. The European Union is demanding a reduction in the number of herbicides used, forbidding use of the most toxic ones, despite the problem of weed resistance increasing. Pelargonic acid (PA) is the only natural herbicide available in Spain. In this work, two field assays were performed with the natural compounds carvacrol (CAR), citral (CIT), eugenol (EUG), thymol (THY), p-cymene (P-CYM), (PA), and the combination of PA with CIT—all except P-CYM formulated by Seipasa—to test their herbicidal efficacy in real conditions. They were compared with commercial PA, glyphosate (GLY) and oxyfluorfen (OXY). In both experiments, GLY achieved the best weed control. Considering the natural herbicides, PA formulated by Seipasa and PA plus CIT were the most effective. From both experiments, some conclusions can be extracted for better herbicidal performance of natural products: (1) use products on sensitive weed species, (2) treat weeds at earlier phenological stages, (3) find the active doses in field conditions, (4) cover weeds well when treating, (5) ensure adequate formulation of products, and (6) develop a strategy for correct application.
Explainable Classification of Patients with Primary Hyperparathyroidism Using Highly Imbalanced Clinical Data Derived from Imaging and Biochemical Procedures
Authors: Samaras Agorastos-Dimitrios , Tsimara Maria , Voidila Sofia , Papandrianos Nikolaos , Zampakis Petros , Moustakidis Serafeim , Papageorgiou Elpiniki , Kalogeropoulou Christina
Published: March 2024

Primary hyperthyroidism (PHPT) is a common endocrine disorder characterized by hypercalcemia and elevated parathyroid hormone (PTH) levels. The most common cause is a single parathyroid adenoma, though the rest of the cases are due to multiglandular disease [double adenoma/hyperplasia]. The main focus driving this work is to develop a computer-aided classification model relying on clinical data to classify PHPT instances and, at the same time, offer explainability for the classification process. A highly imbalanced dataset was created using biometric and clinical data from 134 patients (six total features, 20.2% multiglandular instances). The features used by the current study are age, sex, max diameter index, number of deficiencies, Wisconsin index, and the reference variable indicating the type of PHPT. State-of-the-art machine learning (ML) classification algorithms were used in order to create trained prediction models and give predicted classifications based on all features/indexes. Of the ML models considered (Support Vector Machines, CatBoost, LightGBM, and AdaBoost), LightGBM was able to procure the best performing prediction model. Given the highly imbalanced nature of the particular dataset, oversampling was opted for, so as to increase prediction robustness for both classes. The ML model’s performance was then evaluated using common metrics and stratified ten-fold validation. The significance of this work is rooted in two axes: firstly, in the incorporation of oversampling to smooth out the highly imbalanced dataset and offer good prediction accuracy for both classes, and secondly, in offering an explainability aspect to an otherwise black-box ML prediction model. The maximum achievable accuracy for adenoma is 86.9% and for multigland disease 81.5%. Summarizing the above, this study demonstrates the potential for an ML approach to improve the diagnosis of PHPT and also highlights the importance of explainable artificial intelligence (AI).
DBSTGNN-Att: Dual Branch Spatio-Temporal Graph Neural Network with an Attention Mechanism for Cellular Network Traffic Prediction
Authors: Cai Zengyu , Tan Chunchen , Zhang Jianwei , Zhu Liang , Feng Yuan
Published: March 2024

As network technology continues to develop, the popularity of various intelligent terminals has accelerated, leading to a rapid growth in the scale of wireless network traffic. This growth has resulted in significant pressure on resource consumption and network security maintenance. The objective of this paper is to enhance the prediction accuracy of cellular network traffic in order to provide reliable support for the subsequent base station sleep control or the identification of malicious traffic. To achieve this target, a cellular network traffic prediction method based on multi-modal data feature fusion is proposed. Firstly, an attributed K-nearest node (KNN) graph is constructed based on the similarity of data features, and the fused high-dimensional features are incorporated into the graph to provide more information for the model. Subsequently, a dual branch spatio-temporal graph neural network with an attention mechanism (DBSTGNN-Att) is designed for cellular network traffic prediction. Extensive experiments conducted on real-world datasets demonstrate that the proposed method outperforms baseline models, such as temporal graph convolutional networks (T-GCNs) and spatial–temporal self-attention graph convolutional networks (STA-GCNs) with lower mean absolute error (MAE) values of 6.94% and 2.11%, respectively. Additionally, the ablation experimental results show that the MAE of multi-modal feature fusion using the attributed KNN graph is 8.54% lower compared to that of the traditional undirected graphs.
Excitonic Evolution in WS2/MoS2 van der Waals Heterostructures Turned by Out-of-Plane Localized Pressure
Authors: Kong Weihu , Ren Zeqian , Chen Peng , Cui Jinxiang , Chen Yili , Wu Jizhou , Li Yuqing , Liu Wenliang , Li Peng , Fu Yongming , Ma Jie
Published: March 2024

In this study, we explore the exciton dynamics in a WS2/MoS2 van der Waals (vdW) heterostructure under varying pressures by integrating a laser-confocal photoluminescence (PL) spectroscope and an atomic force microscope (AFM). For the WS2/MoS2 heterostructure, the exciton emission belonging to MoS2 is too weak to be distinguished from the PL spectra. However, upon contact with a Si probe, the emission intensity of WS2 excitons significantly decreases from 34,234 to 6560, thereby matching the intensity level of MoS2. This alteration substantially facilitates the exploration of interlayer excitonic properties within the heterostructures using PL spectroscopy. Furthermore, the Si probe can apply out-of-plane localized pressure to the heterostructure. With increasing pressure, the emission intensity of the WS2 trions decreases at a rate twice that of other excitons, and the exciton energy increases at a rate of 0.1 meV nN−1. These results elucidate that the WS2 trions are particularly sensitive to the out-of-plane pressure within a WS2/MoS2 vdW heterostructure.
Untargeted and Oxylipin-Targeted Metabolomics Study on the Plasma Samples of Primary Open-Angle Glaucoma Patients
Authors: Xu Jianming , Fu Changzhen , Sun Yaru , Wen Xin , Chen Chong-Bo , Huang Chukai , Ng Tsz Kin , Liu Qingping , Zhang Mingzhi
Published: March 2024

Purpose: to determine the metabolomics profiles in the plasma samples of primary open-angle glaucoma (POAG) patients. Methods: The plasma samples from 20 POAG patients under intraocular pressure (IOP)-lowering medication treatment and 20 control subjects were subjected to the untargeted metabolomics analysis, among which 10 POAG patients and 10 control subjects were further subjected to the oxylipin-targeted metabolomics analysis by liquid chromatography–mass spectrometry analysis. The prediction accuracy of the differentially abundant metabolites was assessed by the receiver operating characteristic curves. Pathway analysis and correlation analysis on the differentially abundant metabolites and clinical and biochemical parameters were also conducted. Results: Untargeted metabolomics profiling identified 33 differentially abundant metabolites in the POAG patients, in which the metabolism of linoleic acid, α-linolenic acid, phenylalanine, and tricarboxylic acid cycle were enriched. The correlation analysis indicated that the differentially abundant metabolites were associated with central corneal thickness, peripapillary retinal nerve fiber layer thickness, visual field defects, and lymphocytes. The oxylipin-targeted metabolomics analysis identified 15-keto-Prostaglandin F2 alpha, 13,14-Dihydro-15-keto-prostaglandin D2, 11-Dehydro-thromboxane B2, 8,9-Epoxyeicosatrienoic acid, and arachidonic acid to be significantly decreased in the POAG patients and enriched in the arachidonic acid (AA) pathway. Conclusions: This study revealed that the metabolites in the arachidonic acid metabolism pathway are differentially abundant, suggesting high IOP may not be the only detrimental factor for optic nerve cell damage in this group of POAG patients. Lipid metabolism instability-mediated alterations in oxylipins and AA pathways may be important in POAG, suggesting that oxidative stress and immune-related inflammation could be valuable directions for future therapeutic strategies.
Uterine Commensal Peptostreptococcus Species Contribute to IDO1 Induction in Endometrial Cancer via Indoleacrylic Acid
Authors: Wang Qiong , Liu Yaqiong , Chen Weiwei , Chen Sha , Su Minting , Zheng Yanqin , Liu Wenjie , Li Li , Zeng Liang , Shi Quan , He Juan , Qian Yuanmin , Xuan Xingcui , Wen Qirong , Lash Gendie E. , Shi Kun
Published: March 2024

Microbial dysbiosis has an increasingly appreciated impact on carcinogenesis, and the cervicovaginal microbiome plays a critical role in microenvironmental inflammation. Here, we investigated the involvement of the female genital tract Peptostreptococcus species in gynecological cancer via indoleacrylic acid (IAA). IAA production from Peptostreptococcus species and the effect of bacterial culture on tumor growth in vivo were examined. The impact of IAA on cytokine production and indoleamine-2,3-dioxygenase 1 (IDO1) expression in an endometrial cancer (EC) cell line, as well as their effect on Treg and Teff cells, and M1 and M2 macrophage populations were examined in EC patients and tumor-grafted mice. Clinically, Peptostreptococcus species abundance, IAA, and IDO1 expression were verified in EC patients. The results showed that IAA production was induced in the uteri of BALB/c nude mice by Peptostreptococcus species transplantation, and the intratumoral injection of a conditioned medium from Peptostreptococcus cultures into tumor-grafted mice promoted tumor growth. IL-10 expression was upregulated by IAA; IFN-γ expression was increased by IL-10. IFN-γ induced IDO1 expression in the EC cell line. The co-culture of IDO1-expressing EC cells with peripheral blood mononuclear cells upregulated the Treg proportion and decreased the M1/M2 ratio. Clinically, P. anaerobius was more abundant amongst the uterine microbiota of EC patients than the control. The IAA, IDO1, and kynurenine/tryptophan ratios were all higher in EC tissue, and the M1/M2 ratio was lower. Our study sheds light on the link between IDO1 induction and uterine Peptostreptococcus dysbiosis and provides a potential rationale for the role of Peptostreptococcus species in immune tolerance induction in type I endometrial cancer.
Potential Immunohistochemical Biomarkers for Grading Oral Dysplasia: A Literature Review
Authors: Zdrojewski Jakub , Nowak Monika , Nijakowski Kacper , Jankowski Jakub , Scribante Andrea , Gallo Simone , Pascadopoli Maurizio , Surdacka Anna
Published: March 2024

Oral cancer is a prevalent global health issue, with significant morbidity and mortality rates. Despite available preventive measures, it remains one of the most common cancers, emphasising the need for improved diagnostic and prognostic tools. This review focuses on oral potentially malignant disorders (OPMDs), precursors to oral cancer, specifically emphasising oral epithelial dysplasia (OED). The World Health Organisation (WHO) provides a three-tier grading system for OED, and recent updates have expanded the criteria to enhance diagnostic precision. In the prognostic evaluation of OED, histological grading is presently regarded as the gold standard; however, its subjectivity and unreliability in anticipating malignant transformation or recurrence pose notable limitations. The primary objective is to investigate whether specific immunohistochemical biomarkers can enhance OED grading assessment according to the WHO classification. Biomarkers exhibit significant potential for comprehensive cancer risk evaluation, early detection, diagnosis, prognosis, and treatment optimisation. Technological advancements, including sequencing and nanotechnology, have expanded detection capabilities. Some analysed biomarkers are most frequently chosen, such as p53, Ki-67, cadherins/catenins, and other proteins used to differentiate OED grades. However, further research is needed to confirm these findings and discover new potential biomarkers for precise dysplasia grading and minimally invasive assessment of the risk of malignant transformation.
Women with Gaucher Disease
Authors: Meijon-Ortigueira Maria del Mar , Solares Isabel , Muñoz-Delgado Cecilia , Stanescu Sinziana , Morado Marta , Pascual-Izquierdo Cristina , Villalon Blanco Lucía , Belanger Quintana Amaya , Menéndez-Conde Covadonga Pérez , Morales-Conejo Montserrat , Villarrubia-Espinosa Jesús
Published: March 2024

Gaucher disease is an inherited disorder in which there is a deficiency of the enzyme glucocerebrosidase, which leads to the accumulation of glucosylceramide. Although much scientific evidence is now available, there is still limited data on the impact on the different life stages of women with this disease. Among other alterations, a delay in menarche has been described, although it has not been related to fertility problems. Menorrhagia is relatively frequent, being related to the presence of thrombocytopenia, thrombocytopathies or coagulation disorders. On the other hand, pregnancy planning is an increasingly frequent concern. All patients should undergo genetic counseling, and it is important to monitor the appearance or worsening of organomegaly, bone and hematologic abnormalities to establish clinical and therapeutic recommendations. Management during the puerperium will depend on the evolution of gestation, and, during the lactation period, the potential appearance of bone complications should be assessed. An early onset of menopause, compared to the general population, has also been described, which may accelerate the development of osteopenia. Finally, although the usual screening protocols for neoplasms are currently being performed, it is recommended to watch for early signs of liver or renal neoplasms when examining the results of imaging tests performed during evaluations for this disease.
Pituitary–Adrenal Axis and Peripheral Immune Cell Profile in Long COVID
Authors: Alijotas-Reig Jaume , Anunciacion-Llunell Ariadna , Esteve-Valverde Enrique , Morales-Pérez Stephanie , Rivero-Santana Sergio , Trapé Jaume , González-García Laura , Ruiz Domingo , Marques-Soares Joana , Miro-Mur Francesc
Published: March 2024

In Long COVID, dysfunction in the pituitary–adrenal axis and alterations in immune cells and inflammatory status are warned against. We performed a prospective study in a cohort of 42 patients who suffered COVID-19 at least 6 months before attending the Long COVID unit at Althaia Hospital. Based on Post-COVID Functional Status, 29 patients were diagnosed with Long COVID, while 13 were deemed as recovered. The hormones of the pituitary–adrenal axis, adrenocorticotropin stimulation test, and immune cell profiles and inflammatory markers were examined. Patients with Long COVID had significantly lower EuroQol and higher mMRC scores compared to the recovered individuals. Their symptoms included fatigue, myalgia, arthralgia, persistent coughing, a persistent sore throat, dyspnoea, a lack of concentration, and anxiety. We observed the physiological levels of cortisol and adrenocorticotropin in individuals with or without Long COVID. The results of the adrenocorticotropin stimulation test were similar between both groups. The absolute number of neutrophils was lower in the Long COVID patients compared to recovered individuals (p < 0.05). The total count of B lymphocytes remained consistent, but Long COVID patients had a higher percentage of mature B cells compared to recovered participants (p < 0.05) and exhibited a higher percentage of circulating resident memory CD8+ T cells (p < 0.05) and Treg-expressing exonucleases (p < 0.05). Our findings did not identify adrenal dysfunction related to Long COVID, nor an association between adrenal function and clinical symptoms. The data indicated a dysregulation in certain immune cells, pointing to immune activation. No overt hyperinflammation was observed in the Long COVID group.
Autonomous Robotic System to Prune Sweet Pepper Leaves Using Semantic Segmentation with Deep Learning and Articulated Manipulator
Authors: Giang Truong Thi Huong , Ryoo Young-Jae
Published: March 2024

This paper proposes an autonomous robotic system to prune sweet pepper leaves using semantic segmentation with deep learning and an articulated manipulator. This system involves three main tasks: the perception of crop parts, the detection of pruning position, and the control of the articulated manipulator. A semantic segmentation neural network is employed to recognize the different parts of the sweet pepper plant, which is then used to create 3D point clouds for detecting the pruning position and the manipulator pose. Eventually, a manipulator robot is controlled to prune the crop part. This article provides a detailed description of the three tasks involved in building the sweet pepper pruning system and how to integrate them. In the experiments, we used a robot arm to manipulate the pruning leaf actions within a certain height range and a depth camera to obtain 3D point clouds. The control program was developed in different modules using various programming languages running on the ROS (Robot Operating System).
Research on Collapse Risk Assessment of Karst Tunnels Based on BN Self-Learning
Authors: Sun Jinglai , Wang Yan , Wu Xu , Wang Xinling , Fang Hui , Su Yue
Published: March 2024

The high risk of collapse is a key issue affecting the construction safety of karst tunnels. A risk assessment method for karst tunnel collapse based on data-driven Bayesian Network (BN) self-learning is proposed in this study. The finite element calculation is used to analyze the distribution law of the plastic zone of the tunnel and the karst cave surrounding rock under different combinations of parameters, and a four-factor three-level data case database is established. Through the self-learning of the BN database, a Bayesian Network model of karst tunnel collapse risk assessment with nodes of four types of karst cave parameters is established. The specific probability distribution state and sensitivity of the parameters of different types of karst caves under the condition of whether the tunnel and the karst cave plastic zone are connected or not are studied. The research results show that the distance and angle of the karst cave are the main influencing parameters of the tunnel collapse probability, and the diameter and number of the karst cave are the secondary influencing parameters. Among them, the distance, diameter, and number of karst caves are proportional to the probability of tunnel collapse, and the most unfavorable orientation of karst caves is 45° above the tunnel. When the tunnel passes through the karst area, it should avoid the radial intersection with the karst cave at the arch waist while staying away from the karst cave. The results of this work can provide a reference for the construction safety of karst tunnels under similar conditions.
Catalytic and Capacitive Properties of Hierarchical Carbon–Nickel Nanocomposites
Authors: Hammud Hassan H. , Aljamhi Waleed A. , Al-Hudairi Dolayl E. , Parveen Nazish , Ansari Sajid Ali , Prakasam Thirumurugan
Published: March 2024

Hierarchically graphitic carbon that contained nickel nanoparticles (HGC-Ni (1), (2), and (3)) were prepared by the pyrolysis of three metal complexes as follows: nickel 2,2′-biyridine dichloride, nickel terephthalate 2,2′-bipyridine, and nickel phenanthroline diaqua sulfate, respectively, in the presence of anthracene or pyrene. SEM indicated that the structure of the HGC-Ni samples consisted of nickel nanoparticles with a diameter of 20–500 nm embedded in a thin layer of a hierarchical graphitic carbon layer. The EDAX of HGC-Ni indicated the presence of nickel, carbon, and nitrogen. Chlorine, oxygen, and sulfur were present in (1), (2), and (3), respectively, due to the differences in their complex precursor type. XRD indicated that the nanoparticles consisted of Ni(0) atoms. The turnover frequency (TOF) for the reduction of p-nitrophenol (PNP) increased for catalysts HGC-Ni (3), (2), and (1) and were 0.0074, 0.0094, and 0.0098 mg PNP/mg catalyst/min, respectively. The TOF for the reduction of methyl orange (MO) increased for catalysts (3), (1), and (2) and were 0.0332, 0.0347, and 0.0385 mg MO/mg catalyst/min, respectively. Thus, nickel nano-catalysts (1) and (2) provided the highest performance compared to the nano-catalysts for the reduction of PNP and MO, respectively. The first-order rate constant (min−1) of HGC-Ni (3), with respect to the reduction of PNP, was 0.173 min−1, while the first-order rate constant (min−1) for the reduction of MO by HGC-Ni (1) was 0.404 min−1. HGC-Ni (3) had the highest number of cycles with respect to PNP (17.9 cycles) and MO (22.8 cycles). The catalysts were regenerated efficiently. HGC-Ni exhibited remarkable electrochemical capacitance characteristics in the present study. This material achieved a notable specific capacitance value of 320.0 F/g when measured at a current density of 2 A/g. Furthermore, its resilience was highlighted by its ability to maintain approximately 86.8% of its initial capacitance after being subjected to 2500 charge and discharge cycles. This finding suggests that this HGC-Ni composite stands out not only for its high capacitive performance but also for its durability, making it an attractive and potentially economical choice for energy-storage solutions in various technological applications.
Metal Oxide-Based Sensors for Ecological Monitoring: Progress and Perspectives
Authors: Tereshkov Mykhail , Dontsova Tetiana , Saruhan Bilge , Krüger Svitlana
Published: March 2024

This paper aims to provide a large coverage of recent developments regarding environmental monitoring using metal oxide-based sensors. Particular attention is given to the detection of gases such as H2, COx, SOx, NOx, and CH4. The developments and analyses of the design of sensors and types of metal oxide sensing materials are emphasized. The sensing mechanisms and peculiarities of metal oxides used in chemoresistive sensors are provided. The main parameters that affect the sensitivity and selectivity of metal oxide sensors are indicated and their significance to the sensor signal is analyzed. Modern data processing algorithms, employed to optimize the measurement process and processing of the sensor signal, are considered. The existing sensor arrays/e-nose systems for environmental monitoring are summarized, and future prospects and challenges encountered with metal oxide-based sensor arrays are highlighted.
Extension of Cubic B-Spline for Solving the Time-Fractional Allen–Cahn Equation in the Context of Mathematical Physics
Authors: Fatima Mubeen , Agarwal Ravi P. , Abbas Muhammad , Mohammed Pshtiwan Othman , Shafiq Madiha , Chorfi Nejmeddine
Published: March 2024

A B-spline is defined by the degree and quantity of knots, and it is observed to provide a higher level of flexibility in curve and surface layout. The extended cubic B-spline (ExCBS) functions with new approximation for second derivative and finite difference technique are incorporated in this study to solve the time-fractional Allen–Cahn equation (TFACE). Initially, Caputo’s formula is used to discretize the time-fractional derivative, while a new ExCBS is used for the spatial derivative’s discretization. Convergence analysis is carried out and the stability of the proposed method is also analyzed. The scheme’s applicability and feasibility are demonstrated through numerical analysis.
Collective Creativity and Complexity in Urban Laboratories: El Campo de Cebada
Authors: Martín-Mariscal Amanda , Fernández-Valderrama Luz
Published: March 2024

Cities are complex systems requiring urban design models that balance order and disorder. Collective creativity initiatives engage citizens in these processes, empowering bottom-up approaches that prioritize people and social well-being within urban development. This paper investigates an ‘Urban Laboratory’ as a case study, examining the potential of collective creativity to address urban complexity. The successful and ongoing project ‘El Campo de Cebada’ in Madrid, Spain, demonstrates how a community transformed a vacant lot into a vibrant social hub. The phases of this study include case selection, data collection, data analysis, and presentation of the results. This study identifies key enabling factors, including agents, management, social dynamics, infrastructure, and actions. These insights offer a methodological framework for designing future collaborative, resilient, and inclusive urban spaces, addressing the complex needs of communities within our cities.
Use of Dynamic Spinal Instruments (Dynesys) in Adult Spinal Deformities According to Silva–Lenke and Berjano–Lamartina Classifications
Authors: Akgun Mehmet Yigit , Ucar Ege Anil , Gedik Cemil Cihad , Gunerbuyuk Caner , Hekimoglu Mehdi , Cerezci Onder , Oktenoglu Tunc , Sasani Mehdi , Ates Ozkan , Ozer Ali Fahir
Published: March 2024

Background: Adult spinal deformities (ASD) present complex challenges in spine surgery. The diverse nature of these deformities requires a comprehensive understanding of their classification and treatment options. Traditional approaches, such as fusion and rigid stabilization are associated with complications, including screw loosening, breakage, proximal junctional kyphosis (PJK), and pseudoarthrosis. Dynamic stabilization techniques have emerged as promising alternatives, to reduce these complications and preserve spinal motion. Objective: This study investigated the effectiveness of dynamic stabilization using the Dynesys system in the surgical treatment of adult degenerative spinal deformities, with a particular emphasis on their classification. Methods: ASDs were classified according to the Berjano–Lamartina (BL) and Silva–Lenke (SL) classifications. We analyzed the efficacy of the Dynesys system in enhancing sagittal balance, radiological parameters, and clinical outcomes in this context. Results: Dynamic stabilization of patients with ASDs using the Dynesys system significantly improved the visual analog scale and Oswestry Disability Index scores and decreased the complication rates. Patients with BL types 2, 3, and 4 experienced a significant improvement in sagittal balance followed by sagittal vertical axis measurements (p = 0.045, p = 0.015, and p < 0.0001, respectively). Conclusion: The SL and BL classifications, which were originally developed for rigid spinal stabilization, can be applied in dynamic stabilization. Furthermore, dynamic stabilization using the Dynesys system can be used as an alternative to rigid stabilization in SL levels 2 and 3, and BL types 1, 2, and 3, and in some patients with type 4 ASDs.
Quantitative CT Texture Analysis of COVID-19 Hospitalized Patients during 3–24-Month Follow-Up and Correlation with Functional Parameters
Authors: Fanni Salvatore Claudio , Volpi Federica , Colligiani Leonardo , Chimera Davide , Tonerini Michele , Pistelli Francesco , Pancani Roberta , Airoldi Chiara , Bartholmai Brian J. , Cioni Dania , Carrozzi Laura , Neri Emanuele , De Liperi Annalisa , Romei Chiara
Published: March 2024

Background: To quantitatively evaluate CT lung abnormalities in COVID-19 survivors from the acute phase to 24-month follow-up. Quantitative CT features as predictors of abnormalities’ persistence were investigated. Methods: Patients who survived COVID-19 were retrospectively enrolled and underwent a chest CT at baseline (T0) and 3 months (T3) after discharge, with pulmonary function tests (PFTs). Patients with residual CT abnormalities repeated the CT at 12 (T12) and 24 (T24) months after discharge. A machine-learning-based software, CALIPER, calculated the CT percentage of the whole lung of normal parenchyma, ground glass (GG), reticulation (Ret), and vascular-related structures (VRSs). Differences (Δ) were calculated between time points. Receiver operating characteristic (ROC) curve analyses were performed to test the baseline parameters as predictors of functional impairment at T3 and of the persistence of CT abnormalities at T12. Results: The cohort included 128 patients at T0, 133 at T3, 61 at T12, and 34 at T24. The GG medians were 8.44%, 0.14%, 0.13% and 0.12% at T0, T3, T12 and T24. The Ret medians were 2.79% at T0 and 0.14% at the following time points. All Δ significantly differed from 0, except between T12 and T24. The GG and VRSs at T0 achieved AUCs of 0.73 as predictors of functional impairment, and area under the curves (AUCs) of 0.71 and 0.72 for the persistence of CT abnormalities at T12. Conclusions: CALIPER accurately quantified the CT changes up to the 24-month follow-up. Resolution mostly occurred at T3, and Ret persisting at T12 was almost unchanged at T24. The baseline parameters were good predictors of functional impairment at T3 and of abnormalities’ persistence at T12.
Pediatric Sedation in Dutch Dental Clinics: The Influence of Guideline Modifications on Adverse Events
Authors: Hill Jonah M. , Vogel Daphne Y. S. , Spek Bea , de Jong Catharine J. , Krikken Janneke B. , Veerkamp Jaap S. J.
Published: March 2024

Background: Dental fear and uncooperative behavior can hinder dental treatment quality. Pediatric Procedural Sedation and Analgesia (PPSA) is used to facilitate treatment when the coping capacity is exceeded. Out-of-hospital PPSA has been associated with more adverse outcomes compared to when it is used in hospital-based settings. The updated Dutch PPSA guidelines have increased costs and raised concerns about the accessibility of specialized high-quality dental care for children in the Netherlands. This study aimed to investigate the impact of the updated 2017 guidelines on the occurrence rate of adverse events during PPSA in twelve Dutch dental clinics. Methods: The data of 25,872 children who were treated at twelve dental clinics between 1997 and 2019 were analyzed. A logistic two-level mixed-effects model was used to estimate the updated guidelines’ impacts on adverse events. Results: The OR of the occurrence rate of an adverse event adjusted for age, weight, and duration of treatment was 0.75 (95% CI 0.64–0.89) after the implementation of the updated guidelines. This outcome was significant with p = 0.001, indicating a protective effect. Conclusions: Our findings demonstrate that there was a significant reduction in adverse events after the implementation of the updated guideline and highlight the importance of adhering to evidence-based practices in out-of-hospital dental clinics.
Yield Prediction Using NDVI Values from GreenSeeker and MicaSense Cameras at Different Stages of Winter Wheat Phenology
Authors: Zsebő Sándor , Bede László , Kukorelli Gábor , Kulmány István Mihály , Milics Gábor , Stencinger Dávid , Teschner Gergely , Varga Zoltán , Vona Viktória , Kovács Attila József
Published: March 2024

This work aims to compare and statistically analyze Normalized Difference Vegetation Index (NDVI) values provided by GreenSeeker handheld crop sensor measurements and calculate NDVI values derived from the MicaSense RedEdge-MX Dual Camera, to predict in-season winter wheat (Triticum aestivum L.) yield, improving a yield prediction model with cumulative growing degree days (CGDD) and days from sowing (DFS) data. The study area was located in Mosonmagyaróvár, Hungary. A small-scale field trial in winter wheat was constructed as a randomized block design including Environmental: N-135.3, P2O5-77.5, K2O-0; Balance: N-135.1, P2O5-91, K2O-0; Genezis: N-135, P2O5-75, K2O-45; and Control: N, P, K 0 kg/ha. The crop growth was monitored every second week between April and June 2022 and 2023, respectively. NDVI measurements recorded by GreenSeeker were taken at three pre-defined GPS points for each plot; NDVI values based on the MicaSense camera Red and NIR bands were calculated for the same points. Results showed a significant difference (p ≤ 0.05) between the Control and treated areas by GreenSeeker measurements and Micasense-based calculated NDVI values throughout the growing season, except for the heading stage. At the heading stage, significant differences could be measured by GreenSeeker. However, remotely sensed images did not show significant differences between the treated and Control parcels. Nevertheless, both sensors were found suitable for yield prediction, and 226 DAS was the most appropriate date for predicting winter wheat’s yield in treated plots based on NDVI values and meteorological data.
Rural Research and Development Corporations’ Connection to Agricultural Industry School Partnerships
Authors: O’Dea Molly , Cosby Amy , Manning Jaime K. , McDonald Nicole , Harreveld Bobby
Published: March 2024

The Australian Government has prioritized science, technology, engineering, and mathematics (STEM) education in recent years to ensure that the country has an adequate future workforce. The agriculture industry is a major employer with a diverse range of occupations heavily focused on STEM. Many students do not realize the career opportunities in the sector, which is currently facing severe workforce shortages. Industry school partnerships (ISPs) have been identified as one creative model to improve students’ knowledge of an industry and aspirations for associated careers. Whilst ISPs have been implemented in the STEM context, limited research understands how industry organizations are involved in, influence, and interconnect with ISPs. Australia’s Rural Research and Development Corporations (RRDCs) are legislated agricultural industry bodies and were selected to investigate due to the value ISPs could provide to this STEM-focused industry with workforce shortages. This qualitative case study analyzed data from the most current RRDC strategic and annual operating plans as of 27 July 2023 and semi-structured interviews with an employee(s) in a position relevant to student education of all 15 RRDCs in 2022. The key findings were that ISPs were considered part of the solution to address industry sustainability, though RRDCs were commonly only informally involved. Collaboration between industry partners, facilitators, and teachers at strategic and management levels and across commodities was essential. RRDCs were found to be strongly connected to ISP ecosystems through their role in research and development. We argue that RRDCs are positioned as essential stakeholders with the scope to improve agricultural ISP ecosystems as part of their role in driving agricultural innovation. These findings support the application of ecological systems theory to agricultural ISPs and help us to understand these structures. This paper aims to help those creating ISPs to consider and understand all stakeholders, including industry bodies, to deliver quality future partnerships that benefit both STEM sectors and primary and secondary student education.
Recognition of Ethylene Plasma Spectra 1D Data Based on Deep Convolutional Neural Networks
Authors: Li Baoxia , Chen Wenzhuo , Bian Shaohuang , A Lusi , Tang Xiaojiang , Liu Yang , Guo Junwei , Zhang Dan , Yang Cheng , Huang Feng
Published: March 2024

As a commonly used plasma diagnostic method, the spectral analysis methodology generates a large amount of data and has a complex quantitative relationship with discharge parameters, which result in low accuracy and time-consuming operation of traditional manual spectral recognition methods. To quickly and efficiently recognize the discharge parameters based on the collected spectral data, a one-dimensional (1D) deep convolutional neural network was constructed, which can learn the data features of different classes of ethylene plasma spectra to obtain the corresponding discharge parameters. The results show that this method has a higher recognition accuracy of higher than 98%. This model provides a new idea for plasma spectral diagnosis and its related application.
Reinforcement Learning-Based Event-Triggered Active-Battery-Cell-Balancing Control for Electric Vehicle Range Extension
Authors: Flessner David , Chen Jun , Xiong Guojiang
Published: March 2024

Optimal control techniques such as model predictive control (MPC) have been widely studied and successfully applied across a diverse field of applications. However, the large computational requirements for these methods result in a significant challenge for embedded applications. While event-triggered MPC (eMPC) is one solution that could address this issue by taking advantage of the prediction horizon, one obstacle that arises with this approach is that the event-trigger policy is complex to design to fulfill both throughput and control performance requirements. To address this challenge, this paper proposes to design the event trigger by training a deep Q-network reinforcement learning agent (RLeMPC) to learn the optimal event-trigger policy. This control technique was applied to an active-cell-balancing controller for the range extension of an electric vehicle battery. Simulation results with MPC, eMPC, and RLeMPC control policies are presented along with a discussion of the challenges of implementing RLeMPC.
Effect of Cumulative Spirulina Intake on Broiler Meat Quality, Nutritional and Health-Related Attributes
Authors: Spínola Maria P. , Costa Mónica M. , Prates José A. M.
Published: March 2024

This work aimed to assess how different cumulative levels of Spirulina (Arthrospira platensis) intake influence individual broiler meat quality parameters, nutritional value and health-related traits. The data analysed showed varying cumulative Spirulina intake levels, ranging from 3.46 to 521 g/bird, with large changes in meat traits. The key findings indicate that Spirulina intake significantly enhances meat colour, primarily due to its rich carotenoid content. However, this enhancement shows a saturation effect at higher intake levels, where additional Spirulina does not further improve the colour. Regarding the meat nutritional profile, Spirulina increases beneficial n − 3 polyunsaturated fatty acids and reduces lipid oxidation. These effects on meat, however, are not linear and become more complex at higher microalga intake levels. Regarding meat sensory attributes, moderate Spirulina levels positively influence flavour and texture. Still, higher levels may lead to changes not universally preferred by meat consumers, highlighting the need for balanced Spirulina inclusion in diets. Optimal Spirulina cumulative intake levels must be identified to balance meat’s nutritional benefits with consumer preferences. Additionally, ensuring Spirulina’s purity and adherence to regulatory standards is essential for consumer safety and market access. These findings provide valuable insights for poultry nutritionists and the food industry, emphasising the necessity of a balanced approach to Spirulina’s incorporation in poultry diets.
Changes in the Soil Organic Carbon of Grasslands in the High Andes of Peru after Their Conversion to Croplands and Their Environmental Controls
Authors: Medina Quispe Paolo Rivaldo , Arizapana-Almonacid Marco Aurelio , Nosetto Marcelo Daniel
Published: March 2024

The high-Andean grasslands of Peru provide a wide range of goods and services, not only locally, but also regionally and globally. However, land-use change and global warming are threatening these ecosystems, of which soil organic carbon (SOC) is a key element affecting their sustainability. In this study, we have analyzed the variation of SOC stocks to a depth of 20 cm in 16 paired cropland and grassland sites located in the Sullccapallcca stream micro-watershed (elevation > 3600 m.a.s.l., Ayacucho, Peru). We have also analyzed the environmental controls on the SOC stocks and their variation with land-use change. We found that the studied high-Andean grasslands store high SOC contents (247 Tn SOC ha−1), whose spatial variability was partially explained by the slope of the terrain (r2 = 0.26, p < 0.05). Despite the higher NDVI, the conversion of these grasslands into croplands decreased the SOC stock by 39 Tn SOC ha−1 on average, a decrease that was more pronounced when the initial SOC content of the grassland was higher (r2 = 0.60, p < 0.05). This study provides the first evidence of the effects of land-use change on the SOC in the region, although the mechanisms involved still need to be investigated.
RETRACTED: Wang et al. Panoramic Manifold Projection (Panoramap) for Single-Cell Data Dimensionality Reduction and Visualization. Int. J. Mol. Sci. 2022, 23, 7775
Authors:   IJMS Editorial Office
Published: March 2024

The Int [...]
Psychosocial Impact of a True-Positive, False-Positive, or Inconclusive Newborn Bloodspot Screening Result: A Questionnaire Study among Parents
Authors: van den Heuvel Lieke M. , van der Pal Sylvia M. , Verschoof-Puite Rendelien K. , Klapwijk Jasmijn E. , Elsinghorst Ellen , Dekkers Eugènie , van der Ploeg Catharina P. B. , Henneman Lidewij
Published: March 2024

Expansion of newborn bloodspot screening (NBS) can increase health gain for more children but also increases the number of false-positive and uncertain results. The impact of abnormal and inconclusive NBS results on parental well-being and healthcare utilization was investigated. A questionnaire was sent to Dutch parents receiving an abnormal or inconclusive NBS result five weeks (T1) and four months (T2) post-NBS and compared to parents with a normal result (controls). In total, 35 true-positive (TP), 20 false-positive (FP), and 57 inconclusive (IC) participants and 268 controls filled out T1; 19 TP, 14 FP, 27 IC, and 116 controls filled out T2. Participants showed positive attitudes towards NBS. FP participants more often considered NBS less reliable. TP and FP participants experienced more negative emotions regarding the test result compared to controls at both T1 and T2, and IC only at T1. Parent-reported child vulnerability and perceptions of the newborn’s health status and of parenthood showed no differences. TP and FP participants reported more healthcare utilization at T1, and mainly TP at T2. TP and IC participants showed more emergency department visits at T1. The findings can be used to improve NBS programs and optimize support for families with various NBS results.
Bus Lane Design Based on Actual Traffic Loads and Climate Conditions
Authors: Del Serrone Giulia , Di Mascio Paola , Loprencipe Giuseppe , Vita Lorenzo , Moretti Laura
Published: March 2024

Bus lanes play a crucial role in urban areas as their primary objective is to increase public transport efficiency and help traffic and public transit systems flow more smoothly. This study starts with traffic and climate monitoring to verify asphalt bus lanes in Rome, Italy, according to the Italian Pavement Design Catalogue published in 1995. KENLAYER software calculated the stress-strain conditions under real traffic loads (i.e., hourly passages of urban buses, considering their axle load and seat occupancy rate), typical subgrade bearing capacity (i.e., resilient modulus equal to 90 MPa), current climate conditions, and road material properties. Then, the Mechanistic-Empirical Pavement Design Guide (MEPDG) was used to verify the response of the pavement structure. The fatigue verification of bound materials resulted in damage values much lower than 1 at the end of the 20-year service life (i.e., 0.12 with the Asphalt Institute and 0.31 with the Marchionna law, respectively) and highlights that the Italian catalogue’s sheets are overdesigned. On the other hand, the rutting verification according to MEPDG is not satisfied after an 11-year service life (i.e., the total rutting is equal to 1.50 cm), forcing frequent and expensive maintenance of wearing and binder courses. Therefore, the results confirm the validity of the Italian catalogue for fatigue service life and suggest the need for high-performance asphalt to prevent early rutting due to bus traffic increasing by load and frequency in previous decades.