bluuebunny/crossref_metadata_2025 huggingface dataset:
Role of the Gut Microbiota in Osteoarthritis, Rheumatoid Arthritis, and Spondylarthritis: An Update on the Gut–Joint Axis
Authors: Longo Umile Giuseppe , Lalli Alberto , Bandini Benedetta , de Sire Roberto , Angeletti Silvia , Lustig Sebastien , Ammendolia Antonio , Budhiparama Nicolaas Cyrillus , de Sire Alessandro
Published: March 2024

Dysregulation of the gut microbiota and their metabolites is involved in the pathogenic process of intestinal diseases, and several pieces of evidence within the current literature have also highlighted a possible connection between the gut microbiota and the unfolding of inflammatory pathologies of the joints. This dysregulation is defined as the “gut-joint axis” and is based on the joint–gut interaction. It is widely recognized that the microbiota of the gut produce a variety of compounds, including enzymes, short-chain fatty acids, and metabolites. As a consequence, these proinflammatory compounds that bacteria produce, such as that of lipopolysaccharide, move from the “leaky gut” to the bloodstream, thereby leading to systemic inflammation which then reaches the joints, with consequences such as osteoarthritis, rheumatoid arthritis, and spondylarthritis. In this state-of-the-art research, the authors describe the connections between gut dysbiosis and osteoarthritis, rheumatoid arthritis, and spondylarthritis. Moreover, the diagnostic tools, outcome measures, and treatment options are elucidated. There is accumulating proof suggesting that the microbiota of the gut play an important part not only in immune-mediated, metabolic, and neurological illnesses but also in inflammatory joints. According to the authors, future studies should concentrate on developing innovative microbiota-targeted treatments and their effects on joint pathology as well as on organizing screening protocols to predict the onset of inflammatory joint disease based on gut dysbiosis.
Trimetazidine Improves Mitochondrial Dysfunction in SOD1G93A Cellular Models of Amyotrophic Lateral Sclerosis through Autophagy Activation
Authors: Salvatori Illari , Nesci Valentina , Spalloni Alida , Marabitti Veronica , Muzzi Maurizio , Zenuni Henri , Scaricamazza Silvia , Rosina Marco , Fenili Gianmarco , Goglia Mariangela , Boffa Laura , Massa Roberto , Moreno Sandra , Mercuri Nicola Biagio , Nazio Francesca , Longone Patrizia , Ferri Alberto , Valle Cristiana
Published: March 2024

Amyotrophic Lateral Sclerosis (ALS) is considered the prototype of motor neuron disease, characterized by motor neuron loss and muscle waste. A well-established pathogenic hallmark of ALS is mitochondrial failure, leading to bioenergetic deficits. So far, pharmacological interventions for the disease have proven ineffective. Trimetazidine (TMZ) is described as a metabolic modulator acting on different cellular pathways. Its efficacy in enhancing muscular and cardiovascular performance has been widely described, although its molecular target remains elusive. We addressed the molecular mechanisms underlying TMZ action on neuronal experimental paradigms. To this aim, we treated murine SOD1G93A-model-derived primary cultures of cortical and spinal enriched motor neurons, as well as a murine motor-neuron-like cell line overexpressing SOD1G93A, with TMZ. We first characterized the bioenergetic profile of the cell cultures, demonstrating significant mitochondrial dysfunction that is reversed by acute TMZ treatments. We then investigated the effect of TMZ in promoting autophagy processes and its impact on mitochondrial morphology. Finally, we demonstrated the effectiveness of TMZ in terms of the mitochondrial functionality of ALS-rpatient-derived peripheral blood mononuclear cells (PBMCs). In summary, our results emphasize the concept that targeting mitochondrial dysfunction may represent an effective therapeutic strategy for ALS. The findings demonstrate that TMZ enhances mitochondrial performance in motor neuron cells by activating autophagy processes, particularly mitophagy. Although further investigations are needed to elucidate the precise molecular pathways involved, these results hold critical implications for the development of more effective and specific derivatives of TMZ for ALS treatment.
Age-Related Effects on MSC Immunomodulation, Macrophage Polarization, Apoptosis, and Bone Regeneration Correlate with IL-38 Expression
Authors: Zhang Jiewen , Akiyama Kentaro , Mun Aung Ye , Tagashira Ryuji , Zou Tingling , Matsunaga Naoya , Kohno Teisaku , Kuboki Takuo
Published: March 2024

Mesenchymal stem cells (MSCs) are known to promote tissue regeneration and suppress excessive inflammation caused by infection or trauma. Reported evidence indicates that various factors influence the expression of MSCs’ endogenous immunomodulatory properties. However, the detailed interactions of MSCs with macrophages, which are key cells involved in tissue repair, and their regulatory mechanisms are not completely understood. We herein investigated how age-related immunomodulatory impairment of MSCs alters the interaction of MSCs with macrophages during bone healing using young (5-week old) and aged (50-week old) mice. To clarify the relationship between inflammatory macrophages (M1) and MSCs, their spatiotemporal localization at the bone healing site was investigated by immunostaining, and possible regulatory mechanisms were analyzed in vitro co-cultures. Histomorphometric analysis revealed an accumulation of M1 and a decrease in MSC number at the healing site in aged mice, which showed a delayed bone healing. In in vitro co-cultures, MSCs induced M1 apoptosis through cell-to-cell contact but suppressed the gene expression of pro-inflammatory cytokines by soluble factors secreted in the culture supernatant. Interestingly, interleukin 38 (Il-38) expression was up-regulated in M1 after co-culture with MSCs. IL-38 suppressed the gene expression of inflammatory cytokines in M1 and promoted the expression of genes associated with M1 polarization to anti-inflammatory macrophages (M2). IL-38 also had an inhibitory effect on M1 apoptosis. These results suggest that MSCs may induce M1 apoptosis, suppress inflammatory cytokine production by M1, and induce their polarization toward M2. Nevertheless, in aged conditions, the decreased number and immunomodulatory function of MSCs could be associated with a delayed M1 clearance (i.e., apoptosis and/or polarization) and consequent delayed resolution of the inflammatory phase. Furthermore, M1-derived IL-38 may be associated with immunoregulation in the tissue regeneration site.
Efficacy of Cold Atmospheric Plasma vs. Chemotherapy in Triple-Negative Breast Cancer: A Systematic Review
Authors: Almeida-Ferreira Catarina , Marto Carlos Miguel , Carmo Chrislaura , Almeida-Ferreira Joana , Frutuoso Cristina , Carvalho Maria João , Botelho Maria Filomena , Laranjo Mafalda
Published: March 2024

Breast cancer is a growing disease, with a high worldwide incidence and mortality rate among women. Among the various types, the treatment of triple-negative breast cancer (TNBC) remains a challenge. Considering the recent advances in cold atmospheric plasma (CAP) cancer research, our goal was to evaluate efficacy data from studies based on chemotherapy and CAP in TNBC cell lines and animal models. A search of the literature was carried out in the PubMed, Web of Science, Cochrane Library, and Embase databases. Of the 10,999 studies, there were fifty-four in vitro studies, three in vivo studies, and two in vitro and in vivo studies included. MDA-MB-231 cells were the most used. MTT, MTS, SRB, annexin-V/propidium iodide, trypan blue, and clonogenic assay were performed to assess efficacy in vitro, increasing the reliability and comprehensiveness of the data. There was found to be a decrease in cell proliferation after both chemotherapy and CAP; however, different protocol settings, including an extensive range of drug doses and CAP exposure times, were reported. For both therapies, a considerable reduction in tumor volume was observed in vivo compared with that of the untreated group. The treatment of TNBC cell lines with CAP proved successful, with apoptosis emerging as the predominant type of cellular death. This systematic review presents a comprehensive overview of the treatment landscape in chemotherapy and CAP regarding their efficacy in TNBC cell lines.
Editorial for the Special Issue “Latest Review Papers in Molecular Oncology 2023”
Authors: Stolfi Carmine
Published: March 2024

Human cancers are products of multistep processes resulting in abnormal cell growth and differentiation, along with a loss of apoptotic function, leading to the uncontrolled expansion of neoplastic cells and their spread to surrounding tissues and, ultimately, distant parts of the body [...]
The Biological Active Substances of Taraxacum officinale and Arctium lappa from the Siberian Federal District
Authors: Frolova Anna S. , Fokina Anna D. , Milentyeva Irina S. , Asyakina Lyudmila K. , Proskuryakova Larisa A. , Prosekov Alexander Y.
Published: March 2024

Currently, scientists are increasingly focusing on utilizing the natural flora of the planet to search for and isolate individual bioactive substances that prevent various diseases, contribute to increased life expectancy, and affect all major life-supporting systems in the human body. This study describes the examination of the composition of plant raw materials from the Siberian Federal District. The research focuses on plant specimens from the root parts of Taraxacum officinale and Arctium lappa, collected in the Kemerovo region. The study determines the contents of the water-soluble vitamins B and C in the research subjects. The investigation includes assessing antioxidant properties, antimicrobial activity, and flavonoid content in extracts based on plant raw materials. All samples show a high percentage of antioxidant activity, with the highest antioxidant activity for T. officinale at 85.51 and that for A. lappa at 88.97. The results indicate low antimicrobial activity against Escherichia coli (growth inhibition zone up to 15.5 mm). Plant extracts contain significant amounts of B-group vitamins, with pyridoxine in T. officinale (156.40 μg/mL) and thiamine (46.20 μg/mL) and pyridoxine (357.10 μg/mL) in Arctium lappa. Flavonoids (rutin and quercetin) are identified in T. officinale and A. lappa extracts based on the study results.
RNA Interference Reveals the Impacts of CYP6CY7 on Imidacloprid Resistance in Aphis glycines
Authors: Li Shuangyu , Yang Hongjia , Wang Yixiao , Wei Lisi , Lyu Jiawei , Shan Zhimeng , Zhang Xinxin , Fan Dong
Published: March 2024

Cytochrome P450 (CYP) is a group of important detoxification enzymes found in insects related to their resistance to insecticides. To elucidate the CYP6 family genes of P450, which are potentially related to imidacloprid resistance in Aphis glycines, the CYP6 cDNA sequences of A. glycines were studied. The transcriptome of A. glycines was constructed, and the CYP6 cDNA sequences of A. glycines were screened. Their relative expression levels in response to imidacloprid induction were examined through qRT-PCR, and the CYP6s with higher expression levels were used to study the detoxification of imidacloprid through RNA interference and a bioassay. Twelve CYP6s were obtained from the A. glycines transcriptome. These samples were named by the International P450 Nomenclature Committee and registered in GenBank. After 3, 6, 12, 24 and 48 h of induction with LC50 concentrations of imidacloprid, the relative expression levels of these CYP6s increased; the expression level of CYP6CY7 experienced the highest increase, being more than 3-fold higher than that of those of the non-imidacloprid-induced CYP6s. After RNA interference for CYP6CY7, the relative expression level of CYP6CY7 significantly decreased after 3, 6 and 12 h, while the corresponding P450 enzyme activity decreased after 12 and 24 h. The mortality of A. glycines due to imidacloprid treatment increased by 14.71% at 24 h. CYP6CY7 might detoxify imidacloprid in A. glycines. This study provides a theoretical basis for the further study of the mechanism of action of CYP6s and potential new methods for improving insecticidal efficacy.
Fire Resistance of Foamed Concrete for Discontinuous Partition Filling
Authors: Sulik Paweł , Kukfisz Bożena , Dowbysz Adriana , Oszczak-Nowińska Agata
Published: March 2024

Lightweight concrete exhibits many advantages over traditional concrete such as lower density and thermal conductivity and an easier, cheaper, less energy-consuming manufacturing process. In order to extend its applications, there is a need to study its behavior in fire situations. Due to that, the aim of this study was to assess the fire resistance of foam concrete, depending on its thickness and the foaming process applied. Fire resistance was assessed according to EN 1363-1. The results indicate the usefulness of foam concrete in terms of isolating fire temperatures for discontinuous partition filling that are consequently a real alternative to dedicated solutions in the field of passive fire protection. The density of foam concrete was shown to have a large effect on the ability to insulate fire temperatures with a standard material preparation process. It was also noted that changing the method to continuous foam feeding may result in the achievement of similar values while maintaining foam concrete low density.
Balancing Risks and Benefits: Sodium-Glucose Cotransporter 2 Inhibitors and the Risk of Diabetic Ketoacidosis
Authors: Kleinjan Jan P. , Blom Justin , van Beek André P. , Bouma Hjalmar R. , van Dijk Peter R.
Published: March 2024

Sodium-glucose cotransporter-2 inhibitors (SGLT2is) are a new class of drugs that have been proven beneficial in the management of diabetes, chronic kidney disease, and heart failure and in the mitigation of cardiovascular risk. The benefits of SGLT2i therapy have led to the rapid adoption of these drugs in clinical guidelines. Since the introduction of these drugs, concerns have arisen, as diabetic ketoacidosis (DKA) unexpectedly occurred in patients treated with SGLT2i. DKA is an infrequent but serious complication of SGLT2i therapy, and is potentially preventable. The risk factors for the development of SGLT2i-associated DKA are inappropriate dose reductions of insulin, the dietary restriction of carbohydrates, and factors that may increase insulin demand such as excessive alcohol intake and major surgery. Moreover, the risk of SGLT2i-associated DKA is higher in persons with type 1 diabetes. It is crucial that both patients and healthcare providers are aware of the risks of SGLT2i-associated DKA. In an effort to encourage safe prescribing of this effective class of drugs, we present two cases that illustrate the risks of SGLT2i therapy with regard to the development of DKA.
A Review on Material Selection Benchmarking in GeTe-Based RF Phase-Change Switches for Each Layer
Authors: Qu Sheng , Gao Libin , Wang Jiamei , Chen Hongwei , Zhang Jihua
Published: March 2024

The global demand for radio frequency (RF) modules and components has grown exponentially in recent decades. RF switches are the essential unit in RF front-end and reconfigurable systems leading to the rapid development of novel and advanced switch technology. Germanium telluride (GeTe), as one of the Chalcogenide phase-change materials, has been applied as an RF switch due to its low insertion loss, high isolation, fast switching speed, and low power consumption in recent years. In this review, an in-depth exploration of GeTe film characterization is presented, followed by a comparison of the device structure of directly heated and indirectly heated RF phase-change switches (RFPCSs). Focusing on the prototypical structure of indirectly heated RFPCSs as the reference, the intrinsic properties of each material layer and the rationale behind the material selection is analyzed. Furthermore, the design size of each material layer of the device and its subsequent RF performance are summarized. Finally, we cast our gaze toward the promising future prospects of RFPCS technology.
Cross-Linked Polyacrylic-Based Hydrogel Polymer Electrolytes for Flexible Supercapacitors
Authors: Shi Lanxin , Jiang Pengfei , Zhang Pengxue , Duan Nannan , Liu Qi , Qin Chuanli
Published: March 2024

Hydrogel polymer electrolytes (GPEs), as an important component of flexible energy storage devices, have gradually received wide attention compared with traditional liquid electrolytes due to their advantages of good mechanical, bending, and safety properties. In this paper, two cross-linked GPEs of poly(acrylic acid-co-acrylamide) or poly(acrylic acid-co-N-methylolacrylamide) with NaNO3 aqueous solution (P(AA-co-AM)/NaNO3 or P(AA-co-HAM)/NaNO3) were successfully prepared using radical polymerization, respectively, using acrylic acid (AA) as the monomer, N-methylolacrylamide (HAM) or acrylamide (AM) as the comonomer, and N, N-methylenebisacrylamide (MBAA) as the cross-linking agent. We investigated the morphology, glass transition temperature (Tg), ionic conductivities, mechanical properties, and thermal stabilities of the two GPEs. By comparison, P(AA-co-HAM)/NaNO3 GPE exhibits a higher ionic conductivity of 2.00 × 10−2 S/cm, lower Tg of 152 °C, and appropriate mechanical properties, which are attributed to the hydrogen bonding between the -COOH and -OH, and moderate cross-linking. The flexible symmetrical supercapacitors were assembled with the two GPEs and two identical activated carbon electrodes, respectively. The results show that the flexible supercapacitor with P(AA-co-HAM)/NaNO3 GPE shows good electrochemical performance with a specific capacitance of 63.9 F g−1 at a current density of 0.2 A g−1 and a capacitance retention of 89.4% after 3000 charge–discharge cycles. Our results provide a simple and practical design strategy of GPEs for flexible supercapacitors with wide application prospects.
Evaluation of Suitable Polymeric Matrix/Carriers during Loading of Poorly Water Soluble Drugs onto Mesoporous Silica: Physical Stability and In Vitro Supersaturation
Authors: Kapourani Afroditi , Katopodis Konstantinos , Valkanioti Vasiliki , Chatzitheodoridou Melina , Cholevas Christos , Barmpalexis Panagiotis
Published: March 2024

The application of mesoporous carriers in formulations of amorphous solid dispersions (ASDs) has been suggested to enhance the stability of amorphous drugs. However, mesoporous carriers do not demonstrate satisfactory inhibitory effects on the precipitation of active pharmaceutical ingredients (APIs), and the inclusion of an appropriate polymer within ASDs becomes imperative to maintaining drug supersaturation. The aim of this study was to evaluate ternary olanzapine (OLN) ASDs with Syloid 244FP and to find an appropriate polymeric carrier. The polymer’s selection criteria were based on the physical stability of the ASDs and the release rate of the drug from the systems. The polymers investigated were hydroxypropylmethyl cellulose (HPMC) and copovidone (coPVP). The formation of ASDs was achievable in all investigated cases, as demonstrated by the complete lack of crystallinity confirmed through both powder X-ray diffraction (pXRD) analysis and differential scanning calorimetry (DSC) for all developed formulations. The solvent shift method was employed to evaluate the ability of the studied carriers to inhibit the precipitation of supersaturated OLN. coPVP emerged as a more suitable precipitation inhibitor compared with HPMC and Syloid 244 FP. Subsequently, in vitro dissolution studies under non-sink conditions revealed a higher degree of supersaturation in ternary systems where coPVP was used as a polymeric carrier, as these systems exhibited, under the examined conditions, up to a 2-fold increase in the released OLN compared with the pure crystalline drug. Moreover, stability studies conducted utilizing pXRD demonstrated that ternary formulations incorporating coPVP and Syloid 244 FP maintained stability for an extended period of 8 months. In contrast, binary systems exhibited a comparatively shorter stability duration, indicating the synergistic effect of coPVP and Syloid 244 FP on the physical stability of the amorphous API. Attenuated total reflectance–Fourier transform infrared (ATR-FTIR) studies showed that the development of stronger molecular interactions can be provided as an explanation for this synergistic effect, as the formation of robust H-bonds may be considered responsible for inhibiting the precipitation of the supersaturated API. Therefore, the incorporation of coPVP into OLN ASDs with Syloid 244 FP is considered a highly promising technique for increasing the degree of OLN supersaturation in in vitro dissolution studies and improving the stability of systems.
The Body of the Artist, in the Body of Christ: Toward a Theology of the Embodied Arts
Authors: Bray Dennis P.
Published: March 2024

One insight at the heart of embodiment research is that the particular, material human body is the nexus of two loci: as an integration of sensory apparatuses, the body is the receptive locus of the world; at the same time, the body is the locus of responsive engagement with the world. Working from the framework of embodiment, this essay is a theological exploration of the arts, with particular attention given to the artist. The first half details two controlling ideas about the nature of embodiment and the arts: (i) the arts are necessarily embodied, and (ii) the Christian artist is in Christ’s body. Here I examine how the artwork and the artist are necessarily embodied—the body is the horizon on which the arts are possible. With these two controlling ideas in hand, the second half of the essay considers three implications: (i) the artist works in and for the church; (ii) the arts are a gift of the Holy Spirit; and (iii) the arts are a place where the church experiences the Spirit’s working. These implications yield, among other insights, the finding that Christ’s body is the horizon on which the Christian arts are possible.
Advancements in Utilizing Image-Analysis Technology for Crop-Yield Estimation
Authors: Yu Feng , Wang Ming , Xiao Jun , Zhang Qian , Zhang Jinmeng , Liu Xin , Ping Yang , Luan Rupeng
Published: March 2024

Yield calculation is an important link in modern precision agriculture that is an effective means to improve breeding efficiency and to adjust planting and marketing plans. With the continuous progress of artificial intelligence and sensing technology, yield-calculation schemes based on image-processing technology have many advantages such as high accuracy, low cost, and non-destructive calculation, and they have been favored by a large number of researchers. This article reviews the research progress of crop-yield calculation based on remote sensing images and visible light images, describes the technical characteristics and applicable objects of different schemes, and focuses on detailed explanations of data acquisition, independent variable screening, algorithm selection, and optimization. Common issues are also discussed and summarized. Finally, solutions are proposed for the main problems that have arisen so far, and future research directions are predicted, with the aim of achieving more progress and wider popularization of yield-calculation solutions based on image technology.
Assessing Tree Water Balance after Forest Thinning Treatments Using Thermal and Multispectral Imaging
Authors: Schrader-Patton Charlie , Grulke Nancy E. , Anderson Paul D. , Chaitman Jamieson , Webb Jeremy
Published: March 2024

The health of coniferous forests in the western U.S. is under threat from mega-drought events, increasing vulnerability to insects, disease, and mortality. Forest densification resulting from fire exclusion increases these susceptibilities. Silvicultural treatments to reduce stand density and promote resilience to both fire and drought have been used to reduce these threats but there are few quantitative evaluations of treatment effectiveness. This proof-of-concept study focused on such an evaluation, using field and remote sensing metrics of mature ponderosa pine (Pinus ponderosa Doug. Laws) in central Oregon. Ground metrics included direct measures of transpiration (sapflow), branch and needle measures and chlorosis; drone imagery included thermal (TIR) and five-band spectra (R, G, B, Re, NIR). Thermal satellite imagery was derived from ECOSTRESS, a space-borne thermal sensor that is on-board the International Space Station (ISS). All metrics were compared over 2 days at a time of maximum seasonal drought stress (August). Tree water status in unthinned, light, and heavy thinning from below density reduction treatments was evaluated. Tree crowns in the heavy thin site had greater transpiration and were cooler than those in the unthinned site, while the light thin site was not significantly cooler than either unthinned or the heavy thin site. There was a poor correlation (Adj. R2 0.10–0.13) between remotely sensed stand temperature and stand-averaged transpiration, and tree level temperature and transpiration (Adj. R2 0.04–0.19). Morphological attributes such as greater needle chlorosis and reduced elongation growth supported transpirational indicators of tree drought stress. The multispectral indices CCI and NDRE, along with the NIR and B bands, show promise as proxies for crown temperature and transpiration, and may serve as a proof of concept for an approach to evaluate forest treatment effectiveness in reducing tree drought stress.
Intelligent Detection Method for Satellite TT&C Signals under Restricted Conditions Based on TATR
Authors: Li Yu , Shi Xiaoran , Wang Xiaoning , Lu Yongqiang , Cheng Peipei , Zhou Feng
Published: March 2024

In complex electromagnetic environments, satellite telemetry, tracking, and command (TT&C) signals often become submerged in background noise. Traditional TT&C signal detection algorithms suffer a significant performance degradation or can even be difficult to execute when phase information is absent. Currently, deep-learning-based detection algorithms often rely on expert-experience-driven post-processing steps, failing to achieve end-to-end signal detection. To address the aforementioned limitations of existing algorithms, we propose an intelligent satellite TT&C signal detection method based on triplet attention and Transformer (TATR). TATR introduces the residual triplet attention (ResTA) backbone network, which effectively combines spectral feature channels, frequency, and amplitude dimensions almost without introducing additional parameters. In signal detection, TATR employs a multi-head self-attention mechanism to effectively address the long-range dependency issue in spectral information. Moreover, the prediction-box-matching module based on the Hungarian algorithm eliminates the need for non-maximum suppression (NMS) post-processing steps, transforming the signal detection problem into a set prediction problem and enabling parallel output of the detection results. TATR combines the global attention capability of ResTA with the local self-attention capability of Transformer. Experimental results demonstrate that utilizing only the signal spectrum amplitude information, TATR achieves accurate detection of weak TT&C signals with signal-to-noise ratios (SNRs) of −15 dB and above (mAP@0.5 > 90%), with parameter estimation errors below 3%, which outperforms typical target detection methods.
A Novel Remote Sensing-Based Modeling Approach for Maize Light Extinction Coefficient Determination
Authors: Costa-Filho Edson , Chávez José L. , Zhang Huihui
Published: March 2024

This study focused on developing a novel semi-empirical model for maize’s light extinction coefficient (kp) by integrating multiple remotely sensed vegetation features from several different remote sensing platforms. The proposed kp model’s performance was independently evaluated using Campbell’s (1986) original and simplified kp approaches. The Limited Irrigation Research Farm (LIRF) in Greeley, Colorado, and the Irrigation Innovation Consortium (IIC) in Fort Collins, Colorado, USA, served as experimental sites for developing and evaluating the novel maize kp model. Data collection involved multiple remote sensing platforms, including Landsat-8, Sentinel-2, Planet CubeSat, a Multispectral Handheld Radiometer, and an unmanned aerial system (UAS). Ground measurements of leaf area index (LAI) and fractional vegetation canopy cover (fc) were included. The study evaluated the novel kp model through a comprehensive analysis using statistical error metrics and Sobol global sensitivity indices to assess the performance and sensitivity of the models developed for predicting maize kp. Results indicated that the novel kp model showed strong statistical regression fitting results with a coefficient of determination or R2 of 0.95. Individual remote sensor analysis confirmed consistent regression calibration results among Landsat-8, Sentinel-2, Planet CubeSat, the MSR, and UAS. A comparison with Campbell’s (1986) kp models reveals a 44% improvement in accuracy. A global sensitivity analysis identified the role of the normalized difference vegetation index (NDVI) as a critical input variable to predict kp across sensors, emphasizing the model’s robustness and potential practical environmental applications. Further research should address sensor-specific variations and expand the kp model’s applicability to a diverse set of environmental and microclimate conditions.
Future Scenarios of Urban Nighttime Lights: A Method for Global Cities and Its Application to Urban Expansion and Carbon Emission Estimation
Authors: Kii Masanobu , Matsumoto Kunihiko , Sugita Satoru
Published: March 2024

As of 2018, approximately 55% of the world’s population resides in cities, and it is projected that this proportion will reach 68% by 2050. Population growth in urban areas leads to various impacts on society and the environment. In this study, we have developed a method for generating future scenarios of nighttime lights. What makes this method unique is its ability to (1) generate future gridded nighttime light intensity scenarios for cities, (2) generate future scenarios that preserve the distribution pattern of nighttime light intensity, and (3) generate scenarios that reflect urban policies. By applying this developed method, we have estimated nighttime light data for 555 cities worldwide and predicted future urban expansion and changes in carbon emissions for each SSP scenario. Consequently, both urban areas and carbon emissions are estimated to increase for the entire set of target cities, with patterns varying among cities and scenarios. This study contributes to the advancement of urban scenario research, including the estimation of future urban area expansion and carbon emissions.
Learning Point Processes and Convolutional Neural Networks for Object Detection in Satellite Images
Authors: Mabon Jules , Ortner Mathias , Zerubia Josiane
Published: March 2024

Convolutional neural networks (CNN) have shown great results for object-detection tasks by learning texture and pattern-extraction filters. However, object-level interactions are harder to grasp without increasing the complexity of the architectures. On the other hand, Point Process models propose to solve the detection of the configuration of objects as a whole, allowing the factoring in of the image data and the objects’ prior interactions. In this paper, we propose combining the information extracted by a CNN with priors on objects within a Markov Marked Point Process framework. We also propose a method to learn the parameters of this Energy-Based Model. We apply this model to the detection of small vehicles in optical satellite imagery, where the image information needs to be complemented with object interaction priors because of noise and small object sizes.
Convolutional Neural Network with Attention Mechanism and Visual Vibration Signal Analysis for Bearing Fault Diagnosis
Authors: Zhang Qing , Wei Xiaohan , Wang Ye , Hou Chenggang
Published: March 2024

Bearings, as widely employed supporting components, frequently work in challenging working conditions, leading to diverse fault types. Traditional methods for diagnosing bearing faults primarily center on time–frequency analysis, but this often requires expert experience for accurate fault identification. Conversely, intelligent fault recognition and classification methods frequently lack interpretability. To address this challenge, this paper introduces a convolutional neural network with an attention mechanism method, denoted as CBAM-CNN, for bearing fault diagnosis. This approach incorporates an attention mechanism, creating a Convolutional Block Attention Module (CBAM), to enhance the fault feature extraction capability of the network in the time–frequency domain. In addition, the proposed method integrates a weight visualization module known as the Gradient-Weighted Class Activation Map (Grad-CAM), enhancing the interpretability of the convolutional neural network by generating visual heatmaps on fault time–frequency graphs. The experimental results demonstrate that utilizing the dataset employed in this study, the CBAM-CNN achieves an accuracy of 99.81%, outperforming the Base-CNN with enhanced convergence speed. Furthermore, the analysis of attention weights reveals that this method exhibits distinct focus of attention under various fault types and degrees. The interpretability experiments indicate that the CBAM module balances the weight allocation, emphasizing signal frequency distribution rather than amplitude distribution. Consequently, this mitigates the impact of the signal amplitude on the diagnostic model to some extent.
Highly Sensitive Microwave Sensors Based on Open Complementary Square Split-Ring Resonator for Sensing Liquid Materials
Authors: Ds Chandu , Nagini K. B. S. Sri , Barik Rusan Kumar , Koziel Slawomir
Published: March 2024

This paper presents high-sensitivity sensors based on an open complementary square split-ring resonator and a modified open complementary split-ring resonator operating at 4.5 GHz and 3.4 GHz, respectively. The sensors are designed for the detection of multiple liquid materials, including distilled water, methanol, and ethanol. The liquid under test is filled in a glass container loaded using a pipette. Compared to the conventional OCSSRR, the modified OCSSRR with multiple rings exhibits a higher frequency shift of 1200 MHz, 1270 MHz, and 1520 MHz for ethanol, methanol, and distilled water, respectively. The modified sensor also demonstrates a high sensitivity of 308 MHz/RIU for ethanol concentration which is the highest among the existing microwave sensors. The sensors in this manuscript are suitable for multiple liquid-material-sensing applications.
IMU Auto-Calibration Based on Quaternion Kalman Filter to Identify Movements of Dairy Cows
Authors: Muñoz-Poblete Carlos , González-Aguirre Cristian , Bishop Robert H. , Cancino-Baier David
Published: March 2024

This work is focused on developing a self-calibration algorithm for an orientation estimation of cattle movements based on a quaternion Kalman filter. The accelerometer signals in the earth’s frame provide more information to confirm that the cow is performing a jump to mount another cow. To obtain the measurements in the earth’s frame, we propose a self-calibration method based on a strapdown inertial navigation system (SINS), which does not require intervention by the user once deployed in the field. The self-calibration algorithm uses a quaternion-based Kalman filter to predict the angular orientation with bias correction, and update it based on the measurements of accelerometers and magnetometers. The paper also depicts an alternate update to adjust the inclination using only the accelerometer measurements. We conducted experiments to compare the accuracy of the orientation estimation when the body moves similarly to cow mount movements. The comparison is between the proposed self-calibration algorithm with the IvenSense MPU9250 and Bosch BNO055 and the quaternion attitude estimation provided in the BNO055. The auto-calibrating algorithm presents a mean error of 0.149 rads with a mean consumption of 308.5 mW, and the Bosch algorithm shows an average error of 0.139 rads with a mean consumption of 307.5 mW. When we executed this algorithm in an MPU9250, the average error was 0.077 rads, and the mean consumption was 277.7 mW.
The Development of a Machine Learning-Based Carbon Emission Prediction Method for a Multi-Fuel-Propelled Smart Ship by Using Onboard Measurement Data
Authors: Lee Juhyang , Eom Jeongon , Park Jumi , Jo Jisung , Kim Sewon
Published: March 2024

Zero-carbon shipping is the prime goal of the seaborne trade industry at this moment. The utilization of ammonia and liquid hydrogen propulsion in a carbon-free propulsion system is a promising option to achieve net-zero emission in the maritime supply chain. Meanwhile, optimal ship voyage planning is a candidate to reduce carbon emissions immediately without new buildings and retrofits of the alternative fuel-based propulsion system. Due to the voyage options, the precise prediction of fuel consumption and carbon emission via voyage operation profile optimization is a prerequisite for carbon emission reduction. This paper proposes a novel fuel consumption and carbon emission quantity prediction method which is based on the onboard measurement data of a smart ship. The prediction performance of the proposed method was investigated and compared to machine learning and LSTM-model-based fuel consumption and gas emission prediction methods. The results had an accuracy of 81.5% in diesel mode and 91.2% in gas mode. The SHAP (Shapley additive explanations) model, an XAI (Explainable Artificial Intelligence), and a CO2 consumption model were employed to identify the major factors used in the predictions. The accuracy of the fuel consumption calculated using flow meter data, as opposed to power load data, improved by approximately 21.0%. The operational and flow meter data collected by smart ships significantly contribute to predicting the fuel consumption and carbon emissions of vessels.
An Integrated Fuzzy MCDM Method for Assessing Crisis Recovery Strategies in the Supply Chain
Authors: Magableh Ghazi M. , Mistarihi Mahmoud Z.
Published: March 2024

Making decisions and building strategies to enhance the supply chain are currently essential if companies want to keep up with modern advances and compete in both the local and global markets. However, the coronavirus pandemic heightened the necessity for decision making and the adoption of strategies for supply chain improvement and transformation to effectively deal with crises and ongoing change. This paper introduces a framework for recovery strategies to characterize the correlation at various stages among the key concerns of the supply chain because of COVID-19, recovery decisions, the areas of development, the strategic recovery plan, and the objectives of the recovery strategies to restore the supply chain (SC). This study used a combination of quantitative and qualitative techniques to identify possible areas for supply chain improvement and rank viable solutions. A combined fuzzy ANP–fuzzy TOPSIS method is proposed to prioritize and rank the areas of improvement. The results indicate that digitization and the utilization of emerging technology play critical roles in supply-chain recovery from disruptions and different current and future SC changes.
The Impact of Digital Development on Port Security Resilience—An Empirical Study from Chinese Provinces
Authors: Ren Xiaohong , Shen Jia , Feng Zhitao , Wang Xihuai , An Kaige
Published: March 2024

As the world transitions into the post-pandemic era, ports in various countries are experiencing increased activity, leading to significant challenges in ensuring traffic safety within port jurisdictions. It is essential to explore methods to improve port security resilience to maintain regular economic and trade exchanges. This article examines the influence of digital development on port security resilience. Firstly, the provincial digital development level score is objectively evaluated from the perspective of digital infrastructure, digital application, and digital industry development. Secondly, the port safety resilience score is assessed considering water traffic safety, rescue and recovery capabilities, and operational efficiency. Lastly, the focus is on 16 provinces in China’s coastal and Yangtze River Economic Belt, establishing provincial panel data from 2010 to 2019, and empirically analyzing the direct impact of digital development on the resilience of port security. The results indicate that digital development enhances the resilience of port security, with significant heterogeneity and long-term effects observed.
A Joint Electricity Market-Clearing Mechanism for Flexible Ramping Products with a Convex Spot Market Model
Authors: Gao Senpeng , Bai Xiaoqing , Shang Qinghua , Weng Zonglong , Wu Yinghe
Published: March 2024

A high proportion of renewable energy access makes the net load of the power system volatile and uncertain, increasing the demand for the ramping capacity of the power system. Traditional electricity spot markets compensate for the power imbalances caused by an insufficient ramping capacity through traditional flexibility services such as ancillary services and interconnection power. However, conventional flexibility services may lead to frequency deviations in the power system, increased response costs, spikes in electricity prices, and dramatic price volatility in the traditional spot market. To solve the above problems, this paper proposes an FRP and convex electricity spot market joint clearing (FCESMJC) market mechanism. The FCESMJC model can more accurately represent the relationship between electrical power output and the price of electricity and reduces the number of spikes in electricity prices. In addition, a novel FRP pricing method is proposed to compensate FRP market participants for their FRP costs more reasonably. Additionally, the difference in system performance is provided by comparing the energy prices, pricing method, clearing prices, and system costs in the FCESMJC method and the traditional electricity spot market. The FCESMJC system reduces the total system cost by 18.6% compared with the electricity spot market. Numerical experiments are simulated on the IEEE 14-bus test system to validate the superiority of the proposed model.
A Lagrangian Analysis of Tip Leakage Vortex in a Low-Speed Axial Compressor Rotor
Authors: Hou Jiexuan , Liu Yangwei , Tang Yumeng
Published: March 2024

A Lagrangian method is introduced to analyze the tip leakage vortex (TLV) behavior in a low-speed axial compressor rotor. The finite-time Lyapunov exponent (FTLE) fields are calculated based on the delayed detached-eddy simulation (DDES) results and identifying the FTLE ridges as Lagrangian coherent structures (LCSs). The computational method of the FTLE field in three-dimensional unsteady flow fields is discussed and then applied to the instantaneous flow fields at both the design and near-stall conditions. Results show that the accuracy of the particle trajectory and the density of the initial grid of the particle trajectory greatly affect the results of the FTLE field and, thus, the LCSs. Compared to the Eulerian Q method, which is calculated based on the symmetric and anti-symmetric components of the local velocity gradient tensor, the Lagrangian method has great potential in unraveling the mechanism of complex vortex structures. The LCSs show a transport barrier between the TLV and the secondary TLV, indicating two separate vortices. The aLCSs show the bubble-like and bar-like structure in the isosurfaces corresponding to the bubble and spiral breakdown patterns.
Analysis of Asymmetric Wear of Brake Pads on Freight Wagons despite Full Contact between Pad Surface and Wheel
Authors: Panchenko Sergii , Gerlici Juraj , Lovska Alyona , Ravlyuk Vasyl , Dižo Ján , Blatnický Miroslav
Published: March 2024

This article presents the results of a study focused on identifying the main causes of the asymmetric (clinodual) wear of composite brake pads on freight wagons. A new scientific approach to determining the clinodual wear of composite brake pads on freight wagons is proposed. It is established that the harmful abrasion of the pad occurs during the movement of the freight train due to an imperfection in the bogie-brake lever transmission. The causes of the non-normative frictional wear of composite brake pads were investigated. This kind of wear leads to the tilting and abutting of the upper end of the brake pads against the rotating wheel during train running. The results of geometric and kinetostatic studies of the “pad–wheel” tribotechnical pair are provided to establish the causes and consequences of the accelerated clinodual frictional wear of composite brake pads on pendulum suspension in the bogies of freight wagons. The conditions of rotation of the wheels during braking “for” and “against” the clockwise direction depending on the direction of the train are considered. A new approach to brake-pad-wear prediction depending on the mileage of wagons under operational conditions is proposed. The research conducted in this study contributes to the development of the mechanical parts of freight-wagon brakes, increasing the efficiency of brake operation and improving the safety of train traffic.
SARS-CoV-2-Specific Immune Responses in Vaccination and Infection during the Pandemic in 2020–2022
Authors: Inoue Wakana , Kimura Yuta , Okamoto Shion , Nogimori Takuto , Sakaguchi-Mikami Akane , Yamamoto Takuya , Tsunetsugu-Yokota Yasuko
Published: March 2024

To gain insight into how immunity develops against SARS-CoV-2 from 2020 to 2022, we analyzed the immune response of a small group of university staff and students who were either infected or vaccinated. We investigated the levels of receptor-binding domain (RBD)-specific and nucleocapsid (N)-specific IgG and IgA antibodies in serum and saliva samples taken early (around 10 days after infection or vaccination) and later (around 1 month later), as well as N-specific T-cell responses. One patient who had been infected in 2020 developed serum RBD and N-specific IgG antibodies, but declined eight months later, then mRNA vaccination in 2021 produced a higher level of anti-RBD IgG than natural infection. In the vaccination of naïve individuals, vaccines induced anti-RBD IgG, but it declined after six months. A third vaccination boosted the IgG level again, albeit to a lower level than after the second. In 2022, when the Omicron variant became dominant, familial transmission occurred among vaccinated people. In infected individuals, the levels of serum anti-RBD IgG antibodies increased later, while anti-N IgG peaked earlier. The N-specific activated T cells expressing IFN γ or CD107a were detected only early. Although SARS-CoV-2-specific salivary IgA was undetectable, two individuals showed a temporary peak in RBD- and N-specific IgA antibodies in their saliva on the second day after infection. Our study, despite having a small sample size, revealed that SARS-CoV-2 infection triggers the expected immune responses against acute viral infections. Moreover, our findings suggest that the temporary mucosal immune responses induced early during infection may provide better protection than the currently available intramuscular vaccines.
Experience in optimizing pharmacotherapy for prolonged postinfectious cough
Authors:   Federal State Budgetary Educational Institution of Higher Education «Mari State University », Yoshkar-Ola, Russia, Bontsevich R. A. ,   Federal State Autonomous Educational Institution of Higher Education «Belgorod State National Research University, Zavitkevich G. I. ,   Federal State Budgetary Educational Institution of Higher Education «Mari State University », Yoshkar-Ola, Russia, Maksimov M. L. ,   Kazan State Medical Academy, Kazan; Federal State Budgetary Educational Institution of Continuing Professional Education «Russian Medical Academy of Continuous Professional Education»,  Moscow, Russia
Published: March 2024

The paper describes the rationale for the method and the experience of optimizing pharmacotherapy for prolonged postinfectious cough using such drugs as budesonide, butamirate, levodropropizine, and animal fats.