bluuebunny/crossref_metadata_2025 huggingface dataset:
Pancreatic Ductal Adenocarcinoma and Nutrition: Exploring the Role of Diet and Gut Health
Authors: Gualtieri Paola , Cianci Rossella , Frank Giulia , Pizzocaro Erica , De Santis Gemma Lou , Giannattasio Silvia , Merra Giuseppe , Butturini Giovanni , De Lorenzo Antonino , Di Renzo Laura
Published: October 2023

The incidence of pancreatic cancer is increasing worldwide. The most common form is represented by pancreatic ductal adenocarcinoma (PDAC) which has been shown to be linked to chronic inflammation. Notably, the gut microbiota has emerged as a critical player in regulating immune responses and inflammation. Indeed, intestinal dysbiosis, characterized by an imbalance in the gut microbiota composition, can contribute to the initiation of chronic inflammation. Sterile chronic inflammation can occur, probably activated by the translocation of bacterial components, such as lipopolysaccharide (LPS), the major component of Gram-negative microbiota, with the consequent induction of innate mucosal immunity, through the activation of Toll-like receptors (TLRs). Furthermore, the interaction between LPS and TLRs could enhance cancer progression. Recent research has shed light on the pivotal role of nutrition, as a modifiable risk factor, in PDAC immunological processes, particularly focusing on the immuno-modulatory effects of the gut microbiota. Different dietary regimens, fiber intake, immunonutrients, and antioxidants have the potential to either exacerbate or mitigate chronic inflammation, thereby influencing the pathogenesis and natural history of PDAC. These dietary components may affect the gut microbiota composition and, consequently, the level of inflammation, either promoting or protecting against PDAC. In this review of reviews, we discuss the modulatory role of nutrition and the gut microbiota in PDAC’s immunological processes to explore a translational therapeutic approach that could improve the survival and quality of life of these patients.
Effects of an Eight Week Very Low-Calorie Ketogenic Diet (VLCKD) on White Blood Cell and Platelet Counts in Relation to Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) in Subjects with Overweight and Obesity
Authors: De Nucci Sara , Bonfiglio Caterina , Donvito Rosanna , Di Chito Martina , Cerabino Nicole , Rinaldi Roberta , Sila Annamaria , Shahini Endrit , Giannuzzi Vito , Pesole Pasqua Letizia , Coletta Sergio , Lanzilotta Elsa , Piazzolla Giuseppina , Cozzolongo Raffaele , Giannelli Gianluigi , De Pergola Giovanni
Published: October 2023

Obesity and metabolic dysfunction-associated steatotic liver disease (MASLD) are frequently associated conditions characterized by low-grade inflammation. Very low-calorie ketogenic diet (VLCKD) strategies are commonly used to simultaneously obtain weight loss and an improvement of liver steatosis. We evaluated the efficacy of 8 weeks’ VLCKD in decreasing the white blood cell (WBC) and platelet (PLT) counts, as well as liver steatosis and fibrosis, diagnosed using transient elastography (FibroScan). Metabolic and anthropometric parameters commonly associated with MASLD were also evaluated. This study included 87 participants; 58 women and 29 men aged between 18 and 64 years with overweight (18%) or obesity (82%), but not taking any medication. Anthropometric measurements, bioimpedance analysis, and biochemical assays were performed before and after the dietary intervention. BMI (kg/m2) (p-value < 0.001), waist circumference (cm) (p-value < 0.001), and fat mass (kg) (p-value < 0.001) were significantly decreased following VLCKD. After VLCKD, the FibroScan parameter CAP (db/m), which measures the accumulation of fatty liver, significantly decreased (p-value < 0.001), as did liver stiffness (kPA), the FibroScan parameter quantifying liver fibrosis (p-value < 0.05). Seemingly, WBC (p-value < 0.001) and PLT (p-value < 0.001) counts were lowered by VLCKD in the whole group; however, the decrease in WBC and platelet counts were significant only in patients with steatosis (CAP ≥ 215 dB/m). Fasting blood glucose (p-value < 0.001), insulin (p-value < 0.001), HbA1c (p-value < 0.001), triglycerides (p-value < 0.001), total cholesterol (p-value < 0.001), LDL-cholesterol (p-value < 0.001), HDL-cholesterol (p-value < 0.001); γGT (p-value < 0.001) blood levels and insulin resistance (as measured by HOMAIR) (p-value < 0.001); and systolic (p-value < 0.001), and diastolic (p-value < 0.001) blood pressure levels, were all significantly lower after VLCKD. In contrast, blood levels of vitamin D were higher following the diet (p-value < 0.001). We conclude that treating subjects with overweight and obesity with VLCKD is followed by a simultaneous reduction in WBCs and platelets, the expression of low-grade inflammation, and of liver steatosis and fibrosis. Therefore, we can hypothesize that VLCKD decreases general and liver low-grade inflammation, thus improving liver health.
Meta-Analysis of the Prevalence of Porcine Zoonotic Bacterial Pathogens in India: A 13-Year (2010–2023) Study
Authors: Rajkhowa Swaraj , Sonowal Joyshikh , Borthakur Udipta , Pegu Seema Rani , Deb Rajib , Das Pranab Jyoti , Sengar Gyanendra Singh , Gupta Vivek Kumar
Published: October 2023

The presence of bacterial pathogens such as Brucella spp., Clostridium spp., E. coli, Listeria monocytogenes, Salmonella spp., Staphylococcus spp., and Streptococcus suis not only hampers pig production but also carries significant zoonotic implications. The present study aims to conduct a comprehensive meta-analysis spanning over 13 years (2010–2023) to ascertain the prevalence of these zoonotic bacterial pathogens in Indian pig populations. The study seeks to synthesize data from diverse geographic regions within India and underscores the relevance of the One Health framework. A systematic search of electronic databases was meticulously performed. Inclusion criteria encompassed studies detailing zoonotic bacterial pathogen prevalence in pigs within India during the specified timeframe. Pertinent information including authors, publication year, geographical location, sampling techniques, sample sizes, and pathogen-positive case counts were meticulously extracted. The meta-analysis of zoonotic bacterial pathogens in Indian pig populations (2010–2023) unveiled varying prevalence rates: 9% Brucella spp., 22% Clostridium spp., 19% E. coli, 12% Listeria monocytogenes, 10% Salmonella spp. and Streptococcus suis, and 24% Staphylococcus spp. The application of random effects further revealed additional variability: 6% Brucella spp., 23% Clostridium spp., 24% E. coli, 14% Listeria monocytogenes, 10% Salmonella spp. and Streptococcus suis, and 35% Staphylococcus spp. Notably, the observed heterogeneity (I2) varied significantly from 87% to 99%. The meta-analysis findings underscore the pervasive nature of these diseases throughout India’s pig populations, accentuating the substantial impact of these pathogens on pig health and the potential for zoonotic transmission. The present study reinforces the importance of the adoption of a comprehensive One Health approach that acknowledges the intricate interplay between animal, human and environmental health.
Thiadiazolidinone (TDZD) Analogs Inhibit Aggregation-Mediated Pathology in Diverse Neurodegeneration Models, and Extend C. elegans Life- and Healthspan
Authors: Kakraba Samuel , Ayyadevara Srinivas , Mainali Nirjal , Balasubramaniam Meenakshisundaram , Bowroju Suresh , Penthala Narsimha Reddy , Atluri Ramani , Barger Steven W. , Griffin Sue T. , Crooks Peter A. , Shmookler Reis Robert J.
Published: October 2023

Chronic, low-grade inflammation has been implicated in aging and age-dependent conditions, including Alzheimer’s disease, cardiomyopathy, and cancer. One of the age-associated processes underlying chronic inflammation is protein aggregation, which is implicated in neuroinflammation and a broad spectrum of neurodegenerative diseases such as Alzheimer’s, Huntington’s, and Parkinson’s diseases. We screened a panel of bioactive thiadiazolidinones (TDZDs) from our in-house library for rescue of protein aggregation in human-cell and C. elegans models of neurodegeneration. Among the tested TDZD analogs, PNR886 and PNR962 were most effective, significantly reducing both the number and intensity of Alzheimer-like tau and amyloid aggregates in human cell-culture models of pathogenic aggregation. A C. elegans strain expressing human Aβ1–42 in muscle, leading to AD-like amyloidopathy, developed fewer and smaller aggregates after PNR886 or PNR962 treatment. Moreover, age-progressive paralysis was reduced 90% by PNR886 and 75% by PNR962, and “healthspan” (the median duration of spontaneous motility) was extended 29% and 62%, respectively. These TDZD analogs also extended wild-type C. elegans lifespan by 15–30% (p < 0.001), placing them among the most effective life-extension drugs. Because the lead drug in this family, TDZD-8, inhibits GSK3β, we used molecular-dynamic tools to assess whether these analogs may also target GSK3β. In silico modeling predicted that PNR886 or PNR962 would bind to the same allosteric pocket of inactive GSK3β as TDZD-8, employing the same pharmacophore but attaching with greater avidity. PNR886 and PNR962 are thus compelling candidate drugs for treatment of tau- and amyloid-associated neurodegenerative diseases such as AD, potentially also reducing all-cause mortality.
Investigation of the Impact of Saccharides on the Relative Activity of Trypsin and Catalase after Droplet and Spray Drying
Authors: Dieplinger Johanna , Moser Christina , König Gerhard , Pinto Joana T. , Paudel Amrit
Published: October 2023

While using saccharides as stabilizers for therapeutic protein drying is common, the mechanisms underlying the stabilization during drying remain largely unexplored. Herein, we investigated the effect of different saccharides, trehalose dihydrate (TD), dextran (DEX), and hydroxypropyl β-cyclodextrins (low substitution—HP and high substitution—HPB), on the relative activities of the enzymes trypsin and catalase during miniaturized drying (MD) or spray drying (SD). For trypsin, the presence of saccharides, especially HP, was beneficial, as it significantly improved the enzyme activity following MD. The HPB preserved trypsin’s activity during MD and SD. Adding saccharides during MD did not show a notable improvement in catalase activities. Increasing TD was beneficial during the SD of catalase, as indicated by significantly increased activity. Molecular docking and molecular dynamics simulations oftrypsin with HP or HPB revealed the influence of their substitution on the binding affinity for the enzyme. A higher affinity of HP to bind trypsin and itself was observed during simulations. Experimentally, activity reduction was mainly observed during MD, attributable to the higher droplet temperature during MD than during SD. The activities from the experiments and aggregation propensity from molecular modeling helped elucidate the impact of the size of protein and saccharides on preserving the activity during drying.
Curcumin as a Stabilizer of Macrophage Polarization during Plasmodium Infection
Authors: Cordeiro Maria Clara C. , Tomé Fernanda D. , Arruda Felipe S. , da Fonseca Simone Gonçalves , Nagib Patrícia R. A. , Celes Mara R. N.
Published: October 2023

Malaria is a parasitic infection responsible for high morbidity and mortality rates worldwide. During the disease, phagocytosis of infected red blood cells by the macrophages induces the production of reactive oxygen (ROS) and nitrogen species (RNS), culminating in parasite death. Curcumin (CUR) is a bioactive compound that has been demonstrated to reduce the production of pro-inflammatory cytokines and chemokines produced by macrophages but to reduce parasitemia in infected mice. Hence, the main purpose of this study is to investigate whether curcumin may interfere with macrophage function and polarization after Plasmodium berghei infection in vitro. In our findings, non-polarized macrophage (M0), classically activated (M1), and alternatively activated (M2) phenotypes showed significantly increased phagocytosis of infected red blood cells (iRBCs) when compared to phagocytosis of uninfected red blood cells (RBCs) 3 h after infection. After 24 h, M1 macrophages exposed to RBCs + CUR showed greater elimination capacity when compared to macrophages exposed to iRBCs + CUR, suggesting the interference of curcumin with the microbicidal activity. Additionally, curcumin increased the phagocytic activity of macrophages when used in non-inflammatory conditions (M0) and reduced the inducible nitric oxide synthase (iNOS) and arginase activities in all macrophage phenotypes infected (M0, M1, and M2), suggesting interference in arginine availability by curcumin and balance promotion in macrophage polarization in neutral phenotype (M0). These results support the view of curcumin treatment in malaria as an adjuvant, promoting a balance between pro- and anti-inflammatory responses for a better clinical outcome.
The Past, Present, and Future of Wheat Dwarf Virus Management—A Review
Authors: Pfrieme Anne-Kathrin , Will Torsten , Pillen Klaus , Stahl Andreas
Published: October 2023

Wheat dwarf disease (WDD) is an important disease of monocotyledonous species, including economically important cereals. The causative pathogen, wheat dwarf virus (WDV), is persistently transmitted mainly by the leafhopper Psammotettix alienus and can lead to high yield losses. Due to climate change, the periods of vector activity increased, and the vectors have spread to new habitats, leading to an increased importance of WDV in large parts of Europe. In the light of integrated pest management, cultivation practices and the use of resistant/tolerant host plants are currently the only effective methods to control WDV. However, knowledge of the pathosystem and epidemiology of WDD is limited, and the few known sources of genetic tolerance indicate that further research is needed. Considering the economic importance of WDD and its likely increasing relevance in the coming decades, this study provides a comprehensive compilation of knowledge on the most important aspects with information on the causal virus, its vector, symptoms, host range, and control strategies. In addition, the current status of genetic and breeding efforts to control and manage this disease in wheat will be discussed, as this is crucial to effectively manage the disease under changing environmental conditions and minimize impending yield losses.
Bacillus velezensis ZN-S10 Reforms the Rhizosphere Microbial Community and Enhances Tomato Resistance to TPN
Authors: Chen Enlei , Chao Shufen , Shi Bin , Liu Lu , Chen Mengli , Zheng Yongli , Feng Xiaoxiao , Wu Huiming
Published: October 2023

Tomato pith necrosis (TPN) is a highly destructive disease caused by species of the Pseudomonas genus and other bacteria, resulting in a significant reduction in tomato yield. Members of the genus Bacillus are beneficial microorganisms extensively studied in the rhizosphere. However, in most cases, the potential of Bacillus members in controlling TPN and their impact on the rhizosphere microbial composition remain rarely studied. In this study, Bacillus velezensis ZN-S10 significantly inhibited the growth of Pseudomonas viridiflava ZJUP0398-2, and ZN-S10 controlled TPN with control efficacies of 60.31%. P. viridiflava ZJUP0398-2 significantly altered the richness and diversity of the tomato rhizobacterial community, but pre-inoculation with ZN-S10 mitigated these changes. The correlation analysis revealed that ZN-S10 maybe inhibits the growth of nitrogen-fixing bacteria and recruits beneficial bacterial communities associated with disease resistance, thereby suppressing the occurrence of diseases. In summary, the comparative analysis of the rhizosphere microbiome was conducted to explore the impact of ZN-S10 on the composition of rhizosphere microorganisms in the presence of pathogenic bacteria, aiming to provide insights for further research and the development of scientific and eco-friendly control strategies for this disease.
Review of SHPB Dynamic Load Impact Test Characteristics and Energy Analysis Methods
Authors: Yang Yuchen , Li Qingwen , Qiao Lan
Published: October 2023

Since the split-Hopkinson pressure bar (SHPB) test technology was proposed, it has played an important role in the study of dynamic mechanical properties of materials under the impact of dynamic load. It is a major test technology for the study of dynamic mechanical properties of materials. The expansion of the range of materials studied has also posed a challenge to the SHPB test technique, requiring some improvements to the conventional SHPB test apparatus and analysis methods to meet the test conditions and ensure the accuracy of its results. Based on a systematic review of the development of the SHPB test technique and the test principles, the main factors that influence the test’s ability to meet the two basic assumptions at this stage are analyzed, and the ways to handle them are summarized. The stress wave dispersion phenomenon caused by the transverse inertia effect of the pressure bar means that the test no longer satisfies the one-dimensional stress wave assumption, while the pulse-shaping technique effectively reduces the wave dispersion phenomenon and also has the effect of achieving constant strain rate loading and promoting the dynamic stress equilibrium of the specimen. Impedance matching between the pressure bar and specimen effectively solves the problem of the test’s difficulty because the transmitted signal is weak, and the assumption that the stress/strain is uniformly distributed along the length of the specimen is not satisfied when studying low-wave impedance material with the conventional SHPB test device. The appropriate pressure bar material can be selected according to the value of the wave impedance of the test material. According to the wave impedance values of different materials, the corresponding suggestions for the selection of pressure bar materials are given. Moreover, a new pressure bar material (modified gypsum) for materials with very-low-wave impedance is proposed. Finally, for some materials (foamed concrete, aluminum honeycomb, porous titanium, etc.) that cannot meet the two basic assumptions of the test, the Lagrangian analysis method can be combined with SHPB test technology application. Based on the analysis and calculation of the energy conservation equation, the dynamic constitutive relationship of the materials can be obtained without assuming the constitutive relationship of the experimental materials.
Research on the Damage Model of Cold Recycled Mixtures with Asphalt Emulsion under Freeze-Thaw Cycles
Authors: Yang Ye , Sun Zongguang , Yang Yanhai , Wang Chonghua , Qi Lin
Published: October 2023

Cold recycled mixtures with asphalt emulsion (CRME) suffer the majority of damage from freezing and thawing cycles in seasonal freezing regions. However, an effective model for describing the internal damage evolution behavior of the CRME is still lacking. The objective of this study is to explore the performance of the destroy and damage model of the CRME subjected to freezing and thawing cycles with various water contents. The damage degree of performance at 60 °C and −10 °C, as well as the mechanical properties, were first analyzed in the laboratory. Then, the damage evolution models were established based on macroscopic properties, reliability, and damage theory. The results showed that the performance of the CRME decreased obviously as the number of freezing and thawing cycles increased; after 20 freezing and thawing cycles, the damage degree of 60 °C shear strength and 15 °C and −10 °C indirect tensile strength were 21.5%, 20.6%, and 19.8% at dry condition, but they were 34.9%, 31.8%, and 44.8% at half water saturation condition and 51.5%, 49.1%, and 56.1% at complete water saturation condition; the existence of water and the phase transition of water changed the failure characteristics of the CRME; the correlation coefficient of the damage model parameters was more than 0.98, so the damage evolution model could reveal the internal damage evolution law. Clearly, the freezing and thawing cycles accelerated the damage caused by CRME.
Edge Consistency Feature Extraction Method for Multi-Source Image Registration
Authors: Zhou Yang , Han Zhen , Dou Zeng , Huang Chengbin , Cong Li , Lv Ning , Chen Chen
Published: October 2023

Multi-source image registration has often suffered from great radiation and geometric differences. Specifically, grayscale and texture from similar landforms in different source images often show significantly different visual features, and these differences disturb the corresponding point extraction in the following image registration process. Considering that edges between heterogeneous images can provide homogeneous information and more consistent features can be extracted based on image edges, an edge consistency radiation-change insensitive feature transform (EC-RIFT) method is proposed in this paper. Firstly, the noise and texture interference are reduced by preprocessing according to the image characteristics. Secondly, image edges are extracted based on phase congruency, and an orthogonal Log-Gabor filter is performed to replace the global algorithm. Finally, the descriptors are built with logarithmic partition of the feature point neighborhood, which improves the robustness of the descriptors. Comparative experiments on datasets containing multi-source remote sensing image pairs show that the proposed EC-RIFT method outperforms other registration methods in terms of precision and effectiveness.
Spatio-Temporal Validation of GNSS-Derived Global Ionosphere Maps Using 16 Years of Jason Satellites Observations
Authors: Poniatowski Mateusz , Nykiel Grzegorz , Borries Claudia , Szmytkowski Jędrzej
Published: October 2023

Existing ionospheric models perform very well in mapping the calm state of the ionosphere. However, the problem is accurately determining the total electron content (TEC) for disturbed days. Knowledge of the exact electron density is essential for single−frequency receivers, which cannot eliminate the ionospheric delay. This study aims to investigate temporal and spatial variability in the distribution of TEC based on differences between maps of individual Ionospheric Associated Analysis Centers (IAACs) of the International GNSS Service (IGS) and aligned altimetry−TEC from 2005–2021. Based on the temporal distribution, we have observed a significant effect of solar activity on the mean and standard deviation behavior of the differences between global ionospheric maps (GIMs) and Jason−derived TEC. We determined the biases for the entire calculation period, through which it can be concluded that the upcg-Jason and igsg-Jason differences have the lowest standard deviation (±1.81 TECU). In addition, the temporal analysis made it possible to detect annual, semi−annual, and 117-day oscillations occurring in the Jason−TEC data, as well as 121-day oscillations in the GIMs. It also allowed us to analyze the potential sources of these cyclicities, solar and geomagnetic activity, in the case of the annual and semi−annual periodicities. When considering spatial variations, we have observed that the most significant average differences are in the intertropical areas. In contrast, the smallest differences were recorded in the southern hemisphere, below the Tropic of Capricorn (23.5°S). However, the slightest variations were noted for the northern hemisphere above the Tropic of Cancer (23.5°N). Our research presented in this paper allows a better understanding of how different methods of GNSS TEC approximation affect the model’s accuracy.
Annual and Interannual Variability in the Diffuse Attenuation Coefficient and Turbidity in Urbanized Washington Lake from 2013 to 2022 Assessed Using Landsat-8/9
Authors: Schulien Jennifer A. , Code Tessa , DeGasperi Curtis , Beauchamp David A. , Tonus Ellis Arielle , Litt Arni H.
Published: October 2023

Water clarity, defined in this study using measurements of the downwelling diffuse light attenuation coefficient (Kd) and turbidity, is an important indicator of lake trophic status and ecosystem health. We used in-situ measurements to evaluate existing semi-analytical models for Kd and turbidity, developed a regional turbidity model based on spectral shape, and evaluated the spatial and temporal trends in Lake Washington from 2013 to 2022 using Landsat-8/9 Operational Land Imager (OLI). We found no significant trends from 2013 to 2022 in Kd or turbidity when both the annual and full datasets were considered. In addition to the spring peak lasting from April through June, autumn Kd peaks were present at all sites, a pattern consistent with seasonal chlorophyll a and zooplankton concentrations. There existed no autumn peak in the monthly turbidity dataset, and the spring peak occurred two months before the Kd peak, nearly mirroring seasonal variability in the Cedar River discharge rates over the same period. The Kd and turbidity algorithms were thus each more sensitive to different sources of water clarity variability in Lake Washington.
Simultaneous Vehicle Localization and Roadside Tree Inventory Using Integrated LiDAR-Inertial-GNSS System
Authors: Fan Xianghua , Chen Zhiwei , Liu Peilin , Pan Wenbo
Published: October 2023

Autonomous driving systems rely on a comprehensive understanding of the surrounding environment, and trees, as important roadside features, have a significant impact on vehicle positioning and safety analysis. Existing methods use mobile LiDAR systems (MLS) to collect environmental information and automatically generate tree inventories based on dense point clouds, providing accurate geometric parameters. However, the use of MLS systems requires expensive survey-grade laser scanners and high-precision GNSS/IMU systems, which limits their large-scale deployment and results in poor real-time performance. Although LiDAR-based simultaneous localization and mapping (SLAM) techniques have been widely applied in the navigation field, to the best of my knowledge, there has been no research conducted on simultaneous real-time localization and roadside tree inventory. This paper proposes an innovative approach that uses LiDAR technology to achieve vehicle positioning and a roadside tree inventory. Firstly, a front-end odometry based on an error-state Kalman filter (ESKF) and a back-end optimization framework based on factor graphs are employed. The updated poses from the back-end are used for establishing point-to-plane residual constraints for the front-end in the local map. Secondly, a two-stage approach is adopted to minimize global mapping errors, refining accumulated mapping errors through GNSS-assisted registration to enhance system robustness. Additionally, a method is proposed for creating a tree inventory that extracts line features from real-time LiDAR point cloud data and projects them onto a global map, providing an initial estimation of possible tree locations for further tree detection. This method uses shared feature extraction results and data pre-processing results from SLAM to reduce the computational load of simultaneous vehicle positioning and roadside tree inventory. Compared to methods that directly search for trees in the global map, this approach benefits from fast perception of the initial tree position, meeting real-time requirements. Finally, our system is extensively evaluated on real datasets covering various road scenarios, including urban and suburban areas. The evaluation metrics are divided into two parts: the positioning accuracy of the vehicle during operation and the detection accuracy of trees. The results demonstrate centimeter-level positioning accuracy and real-time automatic creation of a roadside tree inventory.
Spring Phenology Outweighs Temperature for Controlling the Autumn Phenology in the Yellow River Basin
Authors: Yuan Moxi , Li Xinxin , Qu Sai , Wen Zuoshi , Zhao Lin
Published: October 2023

Recent research has revealed that the dynamics of autumn phenology play a decisive role in the inter-annual changes in the carbon cycle. However, to date, the shifts in autumn phenology (EGS) and the elements that govern it have not garnered unanimous acknowledgment. This paper focuses on the Yellow River Basin (YRB) ecosystem and systematically analyzes the dynamic characteristics of EGS and its multiple controls across the entire region and biomes from 1982 to 2015 based on the long-term GIMMS NDVI3g dataset. The results demonstrated that a trend toward a significant delay in EGS (p < 0.05) was detected and this delay was consistently observed across all biomes. By using the geographical detector model, the association between EGS and several main driving factors was quantified. The spring phenology (SGS) had the largest explanatory power among the interannual variations of EGS across the YRB, followed by preseason temperature. For different vegetation types, SGS and preseason precipitation were the dominant driving factors for the EGS in woody plants and grasslands, respectively, whereas the explanatory power for each driving factor on cultivated land was very weak. Furthermore, the EGS was controlled by drought at different timescales and the dominant timescales were concentrated in 1–3 accumulated months. Grasslands were more significantly influenced by drought than woody plants at the biome level. These findings validate the significance of SGS on the EGS in the YRB as well as highlight that both drought and SGS should be considered in autumn fall phenology models for improving the prediction accuracy under future climate change scenarios.
Simulation of Thermal Infrared Brightness Temperatures from an Ocean Color and Temperature Scanner Onboard a New Generation Chinese Ocean Color Observation Satellite
Authors: Qu Liqin , Liu Mingkun , Guan Lei
Published: October 2023

Since 2002, China has launched four Haiyang-1 (HY-1) satellites equipped with the Chinese Ocean Color and Temperature Scanner (COCTS), which can observe the sea surface temperature (SST). The planned new generation ocean color observation satellites also carry a sensor for observing the SST represented by the payload in this paper. We analyze the spectral brightness temperature (BT) difference between the payload and the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Terra for the thermal infrared channels (11 and 12 µm) based on atmospheric radiative transfer simulation. The bias and standard deviation (SD) of spectral BT difference for the 11 µm channel are −0.12 K and 0.15 K, respectively, and those for the 12 µm channel are −0.10 K and 0.03 K, respectively. When the total column water vapor (TCWV) decreases from the oceans near the equator to high-latitude oceans, the spectral BT difference of the 11 µm channel varies from a positive deviation to a negative deviation, and that of the 12 µm channel basically remains stable. By correcting the MODIS BT observation using the spectral BT differences, we produce the simulated BT data for the thermal infrared channels of the payload, and then validate it using the Infrared Atmospheric Sounding Interferometer (IASI) carried on METOP-B. The validation results show that the bias of BT difference between the payload and IASI is −0.22 K for the 11 µm channel, while it is −0.05 K for the 12 µm channel. The SD of both channels is 0.13 K. In this study, we provide the simulated BT dataset for the 11 and 12 µm channels of a payload for the retrieval of SST. The simulated BT dataset corrected may be used to develop SST-retrieval algorithms.
Volume Estimation of Stem Segments Based on a Tetrahedron Model Using Terrestrial Laser Scanning Data
Authors: You Lei , Chang Xiaosa , Sun Yian , Pang Yong , Feng Yan , Song Xinyu
Published: October 2023

Stem volume is a very important parameter in forestry inventory and carbon storage. The stem volume estimated by most existing methods deviates from its true value because the irregularity of the stem is usually overlooked. In this study, we propose a stem segment volume estimation based on the tetrahedron model using TLS data. First, the initial stem segment surface model, including the lower, upper, and outer triangular surface models, was gradually reconstructed. Next, the outer surface model was subdivided based on the edge subdivision. Then, a closed triangular surface model without self-intersection was obtained. Afterward, a tetrahedron model of the stem segment was generated using TetGen software (Version 1.6.0) for the triangular surface model. Finally, the stem segment volume was calculated by summing the volumes of all the tetrahedrons in the tetrahedron model. An experiment with 76 stem segments from different tree species with different parameters showed that the reconstructed stem segment surface model effectively reflected the geometrical features of the stem segment surface. Compared to the volume based on the simulated sectional measurement, the MAPE of the volume based on the tetrahedron model was 2.12%. The results demonstrated the validity of the presented method for stem surface reconstruction and stem volume estimation, and the volume based on the tetrahedron model was closer to the true value than that based on the sectional measurement.
A Review of GAN-Based Super-Resolution Reconstruction for Optical Remote Sensing Images
Authors: Wang Xuan , Sun Lijun , Chehri Abdellah , Song Yongchao
Published: October 2023

High-resolution images have a wide range of applications in image compression, remote sensing, medical imaging, public safety, and other fields. The primary objective of super-resolution reconstruction of images is to reconstruct a given low-resolution image into a corresponding high-resolution image by a specific algorithm. With the emergence and swift advancement of generative adversarial networks (GANs), image super-resolution reconstruction is experiencing a new era of progress. Unfortunately, there has been a lack of comprehensive efforts to bring together the advancements made in the field of super-resolution reconstruction using generative adversarial networks. Hence, this paper presents a comprehensive overview of the super-resolution image reconstruction technique that utilizes generative adversarial networks. Initially, we examine the operational principles of generative adversarial networks, followed by an overview of the relevant research and background information on reconstructing remote sensing images through super-resolution techniques. Next, we discuss significant research on generative adversarial networks in high-resolution image reconstruction. We cover various aspects, such as datasets, evaluation criteria, and conventional models used for image reconstruction. Subsequently, the super-resolution reconstruction models based on generative adversarial networks are categorized based on whether the kernel blurring function is recognized and utilized during training. We provide a brief overview of the utilization of generative adversarial network models in analyzing remote sensing imagery. In conclusion, we present a prospective analysis of forthcoming research directions pertaining to super-resolution reconstruction methods that rely on generative adversarial networks.
A Comparative Analysis of Conductance Probes and High-Speed Camera Measurements for Interfacial Behavior in Annular Air–Water Flow
Authors: Rivera Yago , Bidon Maxime , Muñoz-Cobo José-Luis , Berna Cesar , Escrivá Alberto
Published: October 2023

Different techniques are used to analyze annular flow, but the more interesting ones are those techniques that do not perturb the flow and provide enough resolution to clearly distinguish the interfacial phenomena that take place at the interface, especially the disturbance waves (DW) and the ripple waves (DW). The understanding of these events is important because it influences the heat and mass transfer taking place through the thin film formed near the walls in this flow regime. The laser-induced fluorescence (LIF) and the three-electrode conductance probe are two commonly used techniques to study experimentally annular flow phenomena. In this paper, a set of experiments at different temperatures of 20 °C, 30 °C and 40 °C and different liquid Reynolds numbers have been performed in the annular flow regime, the characteristic of the DW and RW as average height and frequency of these waves has been measured by both techniques LIF and conductance probes. In addition, we also measured the mean film thickness. It was found that the mean film thickness and the DW height are practically the same when measured by both techniques; however, the height of the RW is smaller when measured by the conductance probe and this difference diminishes when the temperature increases.
A Monoblock Light-Scattering Milk Fat Percentage and Somatic Cell Count Sensor for Use in Milking Systems
Authors: Shkirin Alexey V. , Astashev Maxim E. , Ignatenko Dmitry N. , Suyazov Nikolai V. , Chirikov Sergey N. , Kirsanov Vladimir V. , Pavkin Dmitriy Y. , Lobachevsky Yakov P. , Gudkov Sergey V.
Published: October 2023

A monoblock light-scattering sensor, which is capable of measuring the fat content of milk and indicating the excess by which the somatic cell count (SCC) is over the permissible level, has been developed for installation in dairy systems. In order for the sensor to perform measurements when the milking machine is working in the “milk plug” mode, a flow-through unit is designed in the form of a pipe with a lateral cylindrical branch, in which milk accumulates so as to eliminate large bubbles and achieve continuity of the milk flow. The operation of the sensor is based on the registration of the angular intensity distribution of light scattered in the transparent cylindrical segment of the tube branch. A semiconductor laser with a wavelength of 650 nm is used as a light source for determining scattering in milk. The angular distribution of the scattered light intensity (scattering indicatrix) is recorded using an axial photodiode array. The fat content is determined by the average slope of the measured scattering indicatrix in the range of scattering angles 72–162°. The SCC level is estimated from the relative deviation of the forward scatter intensity normalized to the backscatter intensity with respect to uninfected milk. The sensor has been tested on a Yolochka-type milking machine.
Comparing Nadir and Oblique Thermal Imagery in UAV-Based 3D Crop Water Stress Index Applications for Precision Viticulture with LiDAR Validation
Authors: Buunk Thomas , Vélez Sergio , Ariza-Sentís Mar , Valente João
Published: October 2023

Unmanned Aerial Vehicle (UAV) thermal imagery is rapidly becoming an essential tool in precision agriculture. Its ability to enable widespread crop status assessment is increasingly critical, given escalating water demands and limited resources, which drive the need for optimizing water use and crop yield through well-planned irrigation and vegetation management. Despite advancements in crop assessment methodologies, including the use of vegetation indices, 2D mapping, and 3D point cloud technologies, some aspects remain less understood. For instance, mission plans often capture nadir and oblique images simultaneously, which can be time- and resource-intensive, without a clear understanding of each image type’s impact. This issue is particularly critical for crops with specific growth patterns, such as woody crops, which grow vertically. This research aims to investigate the role of nadir and oblique images in the generation of CWSI (Crop Water Stress Index) maps and CWSI point clouds, that is 2D and 3D products, in woody crops for precision agriculture. To this end, products were generated using Agisoft Metashape, ArcGIS Pro, and CloudCompare to explore the effects of various flight configurations on the final outcome, seeking to identify the most efficient workflow for each remote sensing product. A linear regression analysis reveals that, for generating 2D products (orthomosaics), combining flight angles is redundant, while 3D products (point clouds) are generated equally from nadir and oblique images. Volume calculations show that combining nadir and oblique flights yields the most accurate results for CWSI point clouds compared to LiDAR in terms of geometric representation (R2 = 0.72), followed by the nadir flight (R2 = 0.68), and, finally, the oblique flight (R2 = 0.54). Thus, point clouds offer a fuller perspective of the canopy. To our knowledge, this is the first time that CWSI point clouds have been used for precision viticulture, and this knowledge can aid farm managers, technicians, or UAV pilots in optimizing the capture of UAV image datasets in line with their specific goals.
Monitoring Reclamation of Plant Biodiversity and Soil Parameters in an Area of Bauxite Mine Spoils (A Case Study of Greece)
Authors: Solomou Alexandra D. , Michopoulos Panagiotis , Mantakas George
Published: October 2023

In order to assess plant biodiversity in bauxite mine spoils, a fully randomized experiment was carried out with five treatments to find the ones that would best restore the soil and plant biodiversity in the spring seasons of 2020 and 2021. In the studied area, 68 plant species belonging to 54 genera with high ecological value that comprise the flora and represent 19 families were identified. Concerning the herbaceous plant species richness in several treatments, the highest value was calculated in the treatment of sludge (52 plant species), followed by the treatment of soil in the area (39), whereas the lowest plant species richness was recorded in the treatment of fertilization (27), the incorporation of soil with soils (26), and control (27), so our findings indicate that the area where sludge was applied showed the highest nutrient enrichment as well as the highest plant biodiversity, plant cover, and biomass. Apart from sludge, the mineral soil around the area was also composed of some materials that provided good results with regard to plant parameters. The main problems with the properties of the mine spoil material were the low organic matter content and the low clay percentage. The use of sludge, probably in combination with the soil around the area, might alleviate these problems. The plant parameters (Shannon diversity index, plant cover, and biomass) correlated positively and significantly with most of the macronutrients and micronutrients in soils.
Digital Maturity Assessment Model for the Organizational and Process Dimensions
Authors: Tubis Agnieszka A.
Published: October 2023

(1) Background: Ongoing research indicates that it is reasonable to separate a company’s digital maturity assessment by relating it to organization and process levels. The lack of such models in the literature should be considered a research gap. This article aims to present a model framework for assessing enterprise digital maturity that considers two dimensions—organizational and process. The organizational dimension reflects the overall level of digital transformation and refers to the implemented concepts, solutions, and management tools covering the entire enterprise structure. The process dimension focuses on the level of operational divisions. (2) Methods: Analyses were conducted according to the developed research procedure, which included five steps. The research used the following methods: a critical literature analysis, an analysis of the obtained results and their synthesis for the formulated model, and verification and validation of the developed assessment tool and procedure in a selected enterprise based on interviews with managers and direct observations. (3) Results: Based on the literature review, eleven digital maturity areas of the model were defined, and five levels of assessment were formulated for each area. A diagnostic tool for enterprise self-assessment consisting of 105 questions was also developed. (4) Conclusions: The developed model was positively reviewed by the managers of the assessment team that audited the selected enterprise based on it.
Examining the Role and Challenges of Sustainable Development Goals for the Universities in the United Arab Emirates
Authors: Singh Abhilasha , Blessinger Patrick
Published: October 2023

This study aims to explore the potential role of higher education institutions in the United Arab Emirates in driving the world’s progress toward achieving the United Nations Sustainable Development Goals (SDGs). The objectives of the study also include examining the challenges faced by the universities while integrating the SDG into their systems. This study adopted a mixed-method study design by conducting interviews with deans (15) and a survey with faculty members (350) of the universities in the UAE. The most pressing challenges reported were difficulties in the identification of priorities for the most impactful SDGs for universities, reduction of the environmental footprints of universities, the lack of sufficient collaboration and communication among universities, tracking the progress of SDGs in the absence of reporting protocols, impediments to participation from cultural and societal factors, bureaucratic hurdles, and political and economic influence over prioritization of SDGs in universities’ strategic planning. However, governmental change in economic and energy policy was highlighted as a favorable measure to accelerate the adoption of SDGs by the universities. Additionally, the results show that the scope of research and collaborative projects at the universities are limited and do not bring about any substantial change in society.
Transformative Experiences in Cycling Tourism: A Conceptual Framework
Authors: Rus Karina A. , Dezsi Ștefan , Ciascai Ovidiu R.
Published: October 2023

This research conducts an exhaustive thematic analysis to explore the prospects as well as to create a conceptual framework for transformative experiences in cycling tourism. Using rigorous familiarisation, block and file techniques, recurring themes and patterns are identified, revealing insights into shared characteristics and potential synergies between transformative tourism (TT) and cycling tourism (CT), contributing to a deeper understanding of the transformative power of cycling experiences within the broader context of tourism that should further aid in the integration of such transformative experiences in CT. The results show that both TT and CT represent distinctive yet interconnected typologies within the realm of tourism. Several similarities are presented from an almost-mirrored tourist profile, inclination towards sustainable and regenerative tourism, assimilation of slow-tourism, immersive and eudaimonic experiences, well-being, reflection, and personal development opportunities. Based on these insights, this research introduces an innovative integration of both concepts, offering a distinct and enriching tourism experience by enhancing the transformative power of cycling experiences. The article provides practical implications for industry practitioners involved in tourism design and management and opens avenues for future investigations vital to the commencement of this typology, such as the development of theoretical frameworks, innovative perspectives, and evidence-based recommendations for tourism stakeholders.