bluuebunny/crossref_metadata_2025 huggingface dataset:
Pancreatic Neuroendocrine Tumors: What Is the Best Surgical Option?
Authors: Patrone Renato , Mongardini Federico Maria , Conzo Alessandra , Cacciatore Chiara , Cozzolino Giovanni , Catauro Antonio , Lanza Eduardo , Izzo Francesco , Belli Andrea , Palaia Raffaele , Flagiello Luigi , De Vita Ferdinando , Docimo Ludovico , Conzo Giovanni
Published: May 2024

Background: Pancreatic neuroendocrine tumors (pNETs) represent a rare subset of pancreatic cancer. Functional tumors cause hormonal changes and clinical syndromes, while non-functional ones are often diagnosed late. Surgical management needs multidisciplinary planning, involving enucleation, distal pancreatectomy with or without spleen preservation, central pancreatectomy, pancreaticoduodenectomy or total pancreatectomy. Minimally invasive approaches have increased in the last decade compared to the open technique. The aim of this study was to analyze the current diagnostic and surgical trends for pNETs, to identify better interventions and their outcomes. Methods: The study adhered to the PRISMA guidelines, conducting a systematic review of the literature from May 2008 to March 2022 across multiple databases. Several combinations of keywords were used (“NET”, “pancreatic”, “surgery”, “laparoscopic”, “minimally invasive”, “robotic”, “enucleation”, “parenchyma sparing”) and relevant article references were manually checked. The manuscript quality was evaluated. Results: The study screened 3867 manuscripts and twelve studies were selected, primarily from Italy, the United States, and China. A total of 7767 surgically treated patients were collected from 160 included centers. The mean age was 56.3 y.o. Enucleation (EN) and distal pancreatectomy (DP) were the most commonly performed surgeries and represented 43.4% and 38.6% of the total interventions, respectively. Pancreatic fistulae, postoperative bleeding, re-operation, and follow-up were recorded and analyzed. Conclusions: Enucleation shows better postoperative outcomes and lower mortality rates compared to pancreaticoduodenectomy (PD) or distal pancreatectomy (DP), despite the similar risks of postoperative pancreatic fistulae (POPF). DP is preferred over enucleation for the pancreas body–tail, while laparoscopic enucleation is better for head pNETs.
Strategic Use of Biodegradable Temporizing Matrix (BTM) in Wound Healing: A Case Series in Asian Patients
Authors: Chen Angela , Lin Tsuo-Wu , Chang Ke-Chung , Chang Dun-Hao
Published: May 2024

Skin and soft tissue reconstruction has long been based on the reconstructive ladder. However, a skin substitute has become popular due to its predictable outcomes, without donor-site morbidity. The biodegradable temporizing matrix (BTM; NovoSorb, PolyNovo Ltd., Port Melbourne, Australia) is a synthetic skin substitute that has recently gained its clinical application. Compared with those of other dermal templates, the clinical efficacy and performance of the BTM are not well established, especially among the Asian population. This study aims to share our experience and strategy of using BTM in various wound conditions. The data of patients who underwent skin and soft tissue reconstruction with BTM at a single institution between January 2022 and December 2023 were reviewed. The patient demographics, wound characteristics, surgical details, secondary procedures, and complications were recorded and analyzed. Postoperative 6-month photographs were collected and independently evaluated by two plastic surgeons and two wound care center nurses using the Manchester Scar Scale (MSS). This study included 37 patients, consisting of 22 males and 15 females with a mean age of 51.8 years (range, 18–86 years old). The wound etiologies included trauma (67.6%), necrotizing soft tissue infection (16.2%), burns (10.8%), toe gangrene (2.7%), and scar excision (2.7%). The average wound area covered by BTM was 50.6 ± 47.6 cm2. Among the patients, eight received concomitant flap surgery and BTM implantation, 20 (54.1%) underwent subsequent split-thickness skin grafts (STSG), and 17 had small wounds (mean: 21.6 cm2) healed by secondary intention. Infection was the most common complication, affecting six patients (n = 6 [16.2%]), five of whom were treated conservatively, and only one required debridement. Thirty-three patients (89.2%) had good BTM take, and only four had BTM failure, requiring further reconstruction. At the last follow-up, 35 out of the 37 patients (94.6%) achieved successful wound closure, and the total MSS score was 10.44 ± 2.94, indicating a satisfactory scar condition. The patients who underwent BTM grafting without STSG had better scar scores than those who received STSG (8.71 ± 2.60 vs. 11.18 ± 2.84, p = 0.039). In conclusion, the BTM is effective and feasible in treating various wounds, with relatively low complication rates, and it can thus be considered as an alternative for skin and soft tissue reconstruction. When combined with adipofasical flap reconstruction, it achieves a more comprehensive anatomical restoration.
Ecological Security Pattern Construction in Loess Plateau Areas—A Case Study of Shanxi Province, China
Authors: Fu Yongyong , Zhang Wenjia , Gao Feng , Bi Xu , Wang Ping , Wang Xiaojun
Published: May 2024

Strong soil erosion and increasing human activities have made Loess Plateau areas ecologically fragile regions. Constructing the ecological security pattern (ESP) is imperative to maintain their ecosystem functions and sustainable development. However, it is still challenging to establish the ESP in such an unstable and scattered ecological environment. In this study, we take Shanxi Province, which suffers severe ecological problems in Loess Plateau areas, as an example to construct the ESP in a pattern of “source-resistance-corridor”. The proposed methods include the following steps: (1) potential ecological sources are selected with important ecosystem functions based on contributions of soil and water conservation, habitat quality, and carbon storage; (2) ecological sources are determined by considering core areas at the landscape scale based on morphological spatial pattern analysis (MSPA) along with stability based on dynamic assessment on previous sources; (3) the comprehensive resistance surface is constructed by multiple resistance factors and remotely sensed nighttime light data; (4) ecological corridors are simulated and extracted based on circuit theory. As a result, the proposed ESP in our study area mainly includes 13,592 km2 of ecological sources, 8519.64 km of ecological corridors, and 277 ecological nodes. Meanwhile, an ecological framework of “two axes, three belts, and three zones” was proposed based on the optimization and reorganization of ecological components within the ESP. Our research lays a methodological and practical foundation for regional ESP construction and sustainable development in Loess Plateau areas.
Analysis of the Coupling Coordinated Development of the Water-Soil-Energy-Carbon System in Northwest China
Authors: Wang Min , An Yiming , Yang Rupu , Shan Xiaoyu , Li Liping , Feng Xiangzhao
Published: May 2024

The intricate interplay between water resources, land resources, energy systems, and carbon emissions has emerged as a prominent discourse in academic research. Nonetheless, there remains a dearth of comprehensive research dedicated to fostering environmentally friendly and low-carbon development through systematic integration and coordination efforts. This study aimed to fill this gap by integrating the coupling mechanism of the Water-Land-Energy-Carbon (WLEC) system, thereby constructing an evaluation index framework that assesses coordinated developments in Northwest China’s WLEC system. It scrutinizes the security levels within the Water-Land-Energy (WLE) subsystem while conducting quantitative analyses on the degrees of coupling coordination within the WLEC systems, alongside their associated hindering factors. The preliminary findings were as follows: Firstly, the safety development within the WLE system demonstrates a positive trend across Northwest China, with notable advancements primarily observed in the Qinghai and Gansu provinces. In 2021, all five Northwestern provinces exhibited moderate levels of safe development, except for the Qinghai province, which transitioned from moderate to robust. Secondly, the coupling coordination degree of the WLEC system across the five provinces has consistently illustrated an upward trajectory over the years. However, as of 2021, the system remains in a state characterized by marginal disorder. Notably, the Qinghai and Gansu provinces have shown particularly encouraging upward trends, with the Shaanxi province also making notable progress. Conversely, Xinjiang has declined since 2017 due to negative interactions between the subsystems of water, soil, energy, and carbon emissions. Thirdly, spatial variations exist in the distribution patterns between the provinces regarding the influence of obstructing factors on indicators related to coupled coordinated development, such as per capita arable land area, per capita energy consumption, per capita carbon emissions, per capita construction land area, and the proportion of groundwater water in the total amount of water supply, which demonstrated an increasing trend. These findings carry significant practical implications for actively and steadily promoting carbon peaking and carbon neutrality in Northwest China.
Epilactose as a Promising Butyrate-Promoter Prebiotic via Microbiota Modulation
Authors: Cardoso Beatriz B. , Amorim Cláudia , Franco-Duarte Ricardo , Alves Joana I. , Barbosa Sónia G. , Silvério Sara C. , Rodrigues Lígia R.
Published: May 2024

Epilactose is a disaccharide composed of galactose and mannose, and it is currently considered an “under development” prebiotic. In this study, we described the prebiotic potential of epilactose by in vitro fermentation using human fecal inocula from individuals following a Mediterranean diet (DM) or a Vegan diet (DV). The prebiotic effect of epilactose was also compared with lactulose and raffinose, and interesting correlations were established between metabolites and microbiota modulation. The production of several metabolites (lactate, short-chain fatty acids, and gases) confirmed the prebiotic properties of epilactose. For both donors, the microbiota analysis showed that epilactose significantly stimulated the butyrate-producing bacteria, suggesting that its prebiotic effect could be independent of the donor diet. Butyrate is one of the current golden metabolites due to its benefits for the gut and systemic health. In the presence of epilactose, the production of butyrate was 70- and 63-fold higher for the DM donor, when compared to lactulose and raffinose, respectively. For the DV donor, an increase of 29- and 89-fold in the butyrate production was obtained when compared to lactulose and raffinose, respectively. In conclusion, this study suggests that epilactose holds potential functional properties for human health, especially towards the modulation of butyrate-producing strains.
Integrating AI in Lipedema Management: Assessing the Efficacy of GPT-4 as a Consultation Assistant
Authors: Leypold Tim , Lingens Lara F. , Beier Justus P. , Boos Anja M.
Published: May 2024

The role of artificial intelligence (AI) in healthcare is evolving, offering promising avenues for enhancing clinical decision making and patient management. Limited knowledge about lipedema often leads to patients being frequently misdiagnosed with conditions like lymphedema or obesity rather than correctly identifying lipedema. Furthermore, patients with lipedema often present with intricate and extensive medical histories, resulting in significant time consumption during consultations. AI could, therefore, improve the management of these patients. This research investigates the utilization of OpenAI’s Generative Pre-Trained Transformer 4 (GPT-4), a sophisticated large language model (LLM), as an assistant in consultations for lipedema patients. Six simulated scenarios were designed to mirror typical patient consultations commonly encountered in a lipedema clinic. GPT-4 was tasked with conducting patient interviews to gather medical histories, presenting its findings, making preliminary diagnoses, and recommending further diagnostic and therapeutic actions. Advanced prompt engineering techniques were employed to refine the efficacy, relevance, and accuracy of GPT-4’s responses. A panel of experts in lipedema treatment, using a Likert Scale, evaluated GPT-4’s responses across six key criteria. Scoring ranged from 1 (lowest) to 5 (highest), with GPT-4 achieving an average score of 4.24, indicating good reliability and applicability in a clinical setting. This study is one of the initial forays into applying large language models like GPT-4 in specific clinical scenarios, such as lipedema consultations. It demonstrates the potential of AI in supporting clinical practices and emphasizes the continuing importance of human expertise in the medical field, despite ongoing technological advancements.
Evaluating Moisture Content in Immersion Vacuum-Cooled Sausages with Citrus Peel Extracts Using Hyperspectral Imaging
Authors: Feng Chao-Hui , Arai Hirofumi , Rodríguez-Pulido Francisco J.
Published: May 2024

The moisture content of immersion vacuum-cooled sausages with modified casings containing citrus fruit extracts under different storage conditions was studied using hyperspectral imaging (HSI) associated with chemometrics. Different pre-processing combinations were applied to improve the robustness of the model. The partial least squares regression model, employing the full reflectance spectrum with pre-treatment of the standard normal variate, showed calibration coefficients of determination (Rc2) of 0.6160 and a root mean square error of calibration (RMSEC) of 2.8130%. For the first time, prediction maps developed via HSI visualized the distribution of moisture content in the immersion vacuum-cooled sausages with unique modified casings in response to fluctuating storage conditions. The prediction maps showed exact parts with high water content, which will help us to monitor and prevent mold growth. The combination of HSI with multivariate analysis not only quantifies changes in moisture content but also visually represents them in response to various casing treatments under different storage conditions, illustrating the significant potential for real-time inspection and early mold detection in sausages within the processed meat industry.
Hydrostatic Equation of State of bcc Bi by Directly Solving the Partition Function
Authors: Tian Yue-Yue , Ning Bo-Yuan , Zhang Hui-Fen , Ning Xi-Jing
Published: May 2024

Body-centered cubic bismuth (Bi) is considered to be an enticing pressure marker, and, therefore, it is highly desirable to command its accurate equation of state (EOS). However, significant discrepancies are noted among the previous experimental EOSs. In the present work, an EOS of up to 300 GPa is theoretically obtained by solving the partition function via a direct integral approach (DIA). The calculated results nearly reproduce the hydrostatic experimental measurements below 75 GPa, and the deviations from the measurements gradually become larger with increasing pressure. Based on the ensemble theory of equilibrium state, the DIA works with high precision particularly in high-pressure conditions, so the hydrostatic EOS presented in this work is expected to be a reliable pressure standard.
Activity Calculation and Vacuum Separation Theoretical Research concerning Ag–Cu, Ag–Sb and Cu–Sb Binary Alloys
Authors: Li Qingsong , Tian Yang , Kong Lingxin , Yang Bin , Xu Baoqiang , Jiang Wenlong , Wang Lipeng
Published: May 2024

The Ag–Cu–Sb system is a key component of lead anode slime and boasts an exceptionally high economic recovery value. In this work, six models, including the Molecular Interaction Volume Model (MIVM), Modified Molecular Interaction Volume Model (M-MIVM), Wilson equation, Miedema model, Regular Solution Model (RSE) and Sub-Regular Solution Model (SRSE), are used to calculate the predicted values of the activity and its deviations with experimental data for binary alloys in the Ag–Cu–Sb system for the first time. The result reveals that the overall means of the average relative deviation and average standard deviation of the M-MIVM are 0.01501 and 3.97278%, respectively, which are about two to six times smaller than those of the other five models, indicating the stability and reliability of the M-MIVM. In the meantime, the predicted data of the Cu–Ag binary alloy at 1423 K, Sb–Ag binary alloy at 1250 K and Sb–Cu binary alloy at 1375 K calculated from the M-MIVM are more reliable and pass the Herington test. Then, the separation coefficient–composition (β–x), temperature–composition (T–x–y) and pressure–composition (P–x–y) of the Cu–Ag, Sb–Ag and Sb–Cu binary alloys are plotted based on the M-MIVM and vacuum theories, showing that the Cu–Ag binary alloy is relatively difficult to separate and that high temperatures or high copper contents are detrimental to obtaining high-purity silver. Meanwhile, theoretical data of the T–x–y diagram are consistent with the available experimental data. These results can guide vacuum separation experiments and industrial production concerning Ag–Cu, Ag–Sb and Cu–Sb binary alloys.
A Challenged Evaporite Paradigm?
Authors: Johnsen Hans Konrad , Hovland Martin Torvald , Rueslatten Hakon
Published: May 2024

The general subject of this article deals with the term salt. Salt deposits usually contain chlorides, sulphates/gypsum, borates, carbonates, etc., that are seemingly part of the same system. Even though this article mainly presents data and observations on chlorides, which are not easily explained by the present paradigm, it should also prove relevant for the formation of sulphates and other types of salts observed in major salt deposits. The paradigm explaining large salt deposits rests on two pillars governing salt formation and salt deformation. Salt formation is thought to occur vis solar evaporation of seawater in restricted basins. Salt deformation and forming of salt diapirs is thought to occur due to gravity-induced movements. Our review presents peer-reviewed and published data and observations from different authors within different disciplines that challenge the present evaporite paradigm. The current theory/paradigm rests on numerous observations and interpretations in support of it. Adding more observational interpretations in support of the paradigm will not nullify even one observation that contradicts or remains unexplained by the theory. The contradicting evidence must be explained within the present paradigm for it to survive. Significant observations of and within salt deposits are presented, as well as visual and geophysical observations of salinity in crusts and mantles in relevant tectonic settings. In our view, the omnipresent salinity observed in the subsurface needs to be understood and included in the description of a new salt formation mechanism in order to fully explain all features presented herein.
HDL-Cholesterol Subfraction Dimensional Distribution Is Associated with Cardiovascular Disease Risk and Is Predicted by Visceral Adiposity and Dietary Lipid Intake in Women
Authors: Sergi Domenico , Sanz Juana Maria , Trentini Alessandro , Bonaccorsi Gloria , Angelini Sharon , Castaldo Fabiola , Morrone Sara , Spaggiari Riccardo , Cervellati Carlo , Passaro Angelina ,   MEDIA HDL Research Group
Published: May 2024

HDL-cholesterol quality, including cholesterol distribution in HDL subfractions, is emerging as a key discriminant in dictating the effects of these lipoproteins on cardiovascular health. This study aims at elucidating the relationship between cholesterol distribution in HDL subfractions and CVD risk factors as well as diet quality and energy density in a population of pre- and postmenopausal women. Seventy-two women aged 52 ± 6 years were characterized metabolically and anthropometrically. Serum HDL-C subfractions were quantified using the Lipoprint HDL System. Cholesterol distribution in large HDL subfractions was lower in overweight individuals and study participants with moderate to high estimated CVD risk, hypertension, or insulin resistance. Cholesterol distribution in large, as opposed to small, HDL subfractions correlated negatively with insulin resistance, circulating triglycerides, and visceral adipose tissue (VAT). VAT was an independent positive and negative predictor of cholesterol distribution in large and small HDL subfractions, respectively. Furthermore, an increase in energy intake could predict a decrease in cholesterol levels in large HDL subfractions while lipid intake positively predicted cholesterol levels in small HDL subfractions. Cholesterol distribution in HDL subfractions may represent an additional player in shaping CVD risk and a novel potential mediator of the effect of diet on cardiovascular health.
Preterm Infants on Early Solid Foods and Neurodevelopmental Outcome—A Secondary Outcome Analysis of a Randomized Controlled Trial
Authors: Thanhaeuser Margarita , Eibensteiner Fabian , Gsoellpointner Melanie , Brandstetter Sophia , Fuiko Renate , Jilma Bernd , Berger Angelika , Haiden Nadja
Published: May 2024

There are no evidence-based recommendations regarding the introduction of solid foods in preterm infants. The objective of this study was to investigate whether age at the introduction of solid foods affects neurodevelopmental outcomes. This study focuses on analyzing secondary outcomes from a prospective trial involving very low birth weight infants who were randomly assigned to either an early (10–12th week corrected age) or a late (16–18th week corrected age) complementary feeding group. The study evaluated neurodevelopmental outcomes at one and two years of corrected age, as well as at three years and four months of uncorrected age by utilizing Bayley scales. In total, 89 infants were assigned to the early and 88 infants to the late group, all with a mean gestational age of 27 + 1 weeks. A linear mixed-effects model was used to compare neurodevelopmental outcomes across the study groups, taking into account variables such as gestational age at birth, sex, nutrition at discharge, parents’ highest education level, and high-grade intraventricular hemorrhage. The analysis did not reveal any significant differences between the groups. The timepoint of the introduction of solid foods had no impact on neurodevelopmental outcomes at one and two years of corrected age, and at three years and four months of uncorrected age.
Assessing Lifestyle Patterns and Their Influence on Weight Status in Students from a High School in Sibiu, Romania: An Adaptation of ISCOLE Questionnaires and the Child Feeding Questionnaire
Authors: Negrea Mihai Octavian , Negrea Gabriel Octavian , Săndulescu Gabriela , Neamtu Bogdan , Solomon Adelaida , Popa Mirela Livia , Stoia Oana , Domnariu Carmen Daniela , Teodoru Minodora
Published: May 2024

The escalation of global obesity is driving research to understand environmental influences on this process, particularly during vulnerable developmental stages such as childhood and adolescence. Efforts include the development of various structured data collection tools. We aimed to adapt a series of previously validated questionnaires from the International Study of Childhood Obesity, Lifestyle and the Environment (ISCOLE), the Child Feeding Questionnaire, and elements from the World Health Organization Childhood Obesity Surveillance Initiative (COSI) in order to assess local lifestyle patterns among Romanian high school students and their families that may predispose them to obesity. To this goal, an expert committee was formed as part of a research partnership to oversee the questionnaire’s translation and adaptation. It consisted of education and school management specialists, clinical research professionals, language experts, and public health experts. The adapted questionnaires were then applied to 114 students enrolled in the 9th and 10th grades attending a high school situated in Sibiu, and their parents. The variables measured were investigated for correlations with overweight and obesity and, as a secondary objective, academic performance. The study revealed several critical findings, including suboptimal sleep durations and physical activity levels among students, a significant amount of screen time, and correlations between weight status and physical activity, sedentary time, and maternal weight status and education levels. The adapted questionnaires proved to be effective tools in capturing the multifaceted factors implicated in adolescent obesity, providing a foundation for targeted interventions and broader public health strategies to address this issue.
Pilot-Study to Explore Metabolic Signature of Type 2 Diabetes: A Pipeline of Tree-Based Machine Learning and Bioinformatics Techniques for Biomarkers Discovery
Authors: Yagin Fatma Hilal , Al-Hashem Fahaid , Ahmad Irshad , Ahmad Fuzail , Alkhateeb Abedalrhman
Published: May 2024

Background: This study aims to identify unique metabolomics biomarkers associated with Type 2 Diabetes (T2D) and develop an accurate diagnostics model using tree-based machine learning (ML) algorithms integrated with bioinformatics techniques. Methods: Univariate and multivariate analyses such as fold change, a receiver operating characteristic curve (ROC), and Partial Least-Squares Discriminant Analysis (PLS-DA) were used to identify biomarker metabolites that showed significant concentration in T2D patients. Three tree-based algorithms [eXtreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), and Adaptive Boosting (AdaBoost)] that demonstrated robustness in high-dimensional data analysis were used to create a diagnostic model for T2D. Results: As a result of the biomarker discovery process validated with three different approaches, Pyruvate, D-Rhamnose, AMP, pipecolate, Tetradecenoic acid, Tetradecanoic acid, Dodecanediothioic acid, Prostaglandin E3/D3 (isobars), ADP and Hexadecenoic acid were determined as potential biomarkers for T2D. Our results showed that the XGBoost model [accuracy = 0.831, F1-score = 0.845, sensitivity = 0.882, specificity = 0.774, positive predictive value (PPV) = 0.811, negative-PV (NPV) = 0.857 and Area under the ROC curve (AUC) = 0.887] had the slight highest performance measures. Conclusions: ML integrated with bioinformatics techniques offers accurate and positive T2D candidate biomarker discovery. The XGBoost model can successfully distinguish T2D based on metabolites.
Inhibitory Effects on Staphylococcus aureus Sortase A by Aesculus sp. Extracts and Their Toxicity Evaluation
Authors: Olaru Octavian Tudorel , Nitulescu George Mihai , Codreanu Andreea Miruna , Calmuc Valentina-Andreea , Venables Luanne , van de Venter Maryna , Gird Cerasela Elena , Duta-Bratu Cosmina-Gabriela , Nitulescu Georgiana
Published: May 2024

A promising strategy for combating bacterial infections involves the development of agents that disarm the virulence factors of pathogenic bacteria, thereby reducing their pathogenicity without inducing direct lethality. Sortase A, a crucial enzyme responsible for anchoring virulence factors to the cell surface of several pathogenic bacteria, has emerged as a possible target for antivirulence strategies. A series of hippocastanum species (Aesculus pavia, A. parviflora, Aesculus x carnea, and A. hippocastanum) were used to prepare ethanol- and water-based extracts for assessing their effect on Staphylococcus aureus sortase A. The extracts were characterized through HPLC analysis, and their polyphenols content was determined using the Folin–Ciocalteu method. The specific toxicity profile was evaluated in Daphnia magna using the median lethal concentration (LC50) and against the fibroblast MRHF cell line. The half maximal inhibitory concentration (IC50) values on sortase A, determined after 30 min of incubation, ranged from 82.70 to 304.31 µg/mL, with the A. pavia water extract exhibiting the highest inhibitory effect. The assessment of the A. pavia water extract on human fibroblasts revealed no significant signs of toxicity, even at a concentration of 500 µg/mL. This reduced toxicity was further validated through the Daphnia assay. These findings highlight the low toxicity and the potential of this extract as a promising source of future development of bacteria antivirulence solutions.
Plant–Entomopathogenic Fungi Interaction: Recent Progress and Future Prospects on Endophytism-Mediated Growth Promotion and Biocontrol
Authors: Ahsan S. M. , Injamum-Ul-Hoque Md. , Das Ashim Kumar , Rahman Md. Mezanur , Mollah Md. Mahi Imam , Paul Narayan Chandra , Choi Hyong Woo
Published: May 2024

Entomopathogenic fungi, often acknowledged primarily for their insecticidal properties, fulfill diverse roles within ecosystems. These roles encompass endophytism, antagonism against plant diseases, promotion of the growth of plants, and inhabitation of the rhizosphere, occurring both naturally and upon artificial inoculation, as substantiated by a growing body of contemporary research. Numerous studies have highlighted the beneficial aspects of endophytic colonization. This review aims to systematically organize information concerning the direct (nutrient acquisition and production of phytohormones) and indirect (resistance induction, antibiotic and secondary metabolite production, siderophore production, and mitigation of abiotic and biotic stresses) implications of endophytic colonization. Furthermore, a thorough discussion of these mechanisms is provided. Several challenges, including isolation complexities, classification of novel strains, and the impact of terrestrial location, vegetation type, and anthropogenic reluctance to use fungal entomopathogens, have been recognized as hurdles. However, recent advancements in biotechnology within microbial research hold promising solutions to many of these challenges. Ultimately, the current constraints delineate potential future avenues for leveraging endophytic fungal entomopathogens as dual microbial control agents.
A SEPALLATA MADS-Box Transcription Factor, SlMBP21, Functions as a Negative Regulator of Flower Number and Fruit Yields in Tomato
Authors: Zhang Jianling , Dong Tingting , Hu Zongli , Li Jing , Zhu Mingku , Chen Guoping
Published: May 2024

MADS-box transcription factors act as the crucial regulators in plant organ differentiation. Crop yields are highly influenced by the flower number and fruit growth. However, flower identification is a very complex biological process, which involves many cascade regulations. The molecular mechanisms underlying the genetic regulation of flower identification in cultivated plants, such as tomato, are intricate and require further exploration. In this study, we investigated the vital function of a SEPALLATA (SEP) MADS-box gene, SlMBP21, in tomato sympodial inflorescence meristem (SIM) development for the conversion from SIMs to floral meristems (FMs). SlMBP21 transcripts were primarily accumulated in young inflorescence meristem, flowers, sepals, and abscission zones. The Ailsa Craig (AC++) tomato plants with suppressed SlMBP21 mRNA levels using RNAi exhibited a large increase in flower number and fruit yields in addition to enlarged sepals and inhibited abscission zone development. Scanning electron microscopy (SEM) revealed that the maturation of inflorescence meristems (IMs) was repressed in SlMBP21-RNAi lines. RNA-seq and qRT-PCR analyses showed that numerous genes related to the flower development, plant hormone signal transduction, cell cycle, and cell proliferation et al. were dramatically changed in SlMBP21-RNAi lines. Yeast two-hybrid assay exhibited that SlMBP21 can respectively interact with SlCMB1, SFT, JOINTLESS, and MC, which play key roles in inflorescence meristems or FM development. In summary, our data demonstrate that SlMBP21 functions as a key regulator in SIM development and the conversion from SIMs to FMs, through interacting with other regulatory proteins to control the expression of related genes.
Catalytic Pyrolysis of Polypropylene for Cable Semiconductive Buffer Layers
Authors: Meng Xiaokai , Yu Hua , Lu Zhumao , Jin Tao
Published: May 2024

With the progress of the power grid system, the coverage area of cables is widening, and the problem of cable faults is gradually coming to affect people’s daily lives. While the vast majority of cable faults are caused by the ablation of the cable buffer layer, polypropylene (PP), as a common cable buffer material, has pyrolysis properties that critically impact cable faults. Studying the semiconductive buffer layer of polypropylene (PP) and its pyrolysis properties allows us to obtain a clearer picture of the pyrolysis products formed during PP ablation. This understanding aids in the accurate diagnosis of cable faults and the identification of ablation events. In this study, the effects of temperature and catalyst (H-Zeolite Standard Oil Corporation Of New York (Socony) Mobil-Five (HZSM-5)) content on the PP thermolysis product distribution were studied by using an online tubular pyrolysis furnace-mass spectrometry (MS) experimental platform. The results showed that PP/40% HZSM-5 presented the highest thermolytic efficiency and relative yield of the main products at 400 °C.
Cellulose-Based Polyurethane Foams of Low Flammability
Authors: Szpiłyk Marzena , Lubczak Renata , Lubczak Jacek
Published: May 2024

Decreasing oil resources creates the need to search for raw materials in the biosphere, which can be converted into polyols suitable for obtaining polyurethane foams (PUF). One such low-cost and reproducible biopolymer is cellulose. There are not many examples of cellulose-derived polyols due to the sluggish reactivity of cellulose itself. Recently, cellulose and its hydroxypropyl derivatives were applied as source materials to obtain polyols, further converted into biodegradable rigid polyurethane foams (PUFs). Those PUFs were flammable. Here, we describe our efforts to modify such PUFs in order to decrease their flammability. We obtained an ester from diethylene glycol and phosphoric(III) acid and used it as a reactive flame retardant in the synthesis of polyol-containing hydroxypropyl derivative of cellulose. The cellulose-based polyol was characterized by infrared spectra (IR) and proton nuclear magnetic resonance (1H-NMR) methods. Its properties, such as density, viscosity, surface tension, and hydroxyl numbers, were determined. Melamine was also added to the foamed composition as an additive flame retardant, obtaining PUFs, which were characterized by apparent density, water uptake, dimension stability, heat conductance, compressive strength, and heat resistance at 150 and 175 °C. Obtained rigid PUFs were tested for flammability by determining oxygen index, horizontal flammability test, and calorimetric analysis. Obtained rigid PUFs showed improved flammability resistance in comparison with non-modified PUFs and classic PUFs.
Advances in Deep Learning Recognition of Landslides Based on Remote Sensing Images
Authors: Cheng Gong , Wang Zixuan , Huang Cheng , Yang Yingdong , Hu Jun , Yan Xiangsheng , Tan Yilun , Liao Lingyi , Zhou Xingwang , Li Yufang , Hussain Syed , Faisal Mohamed , Li Huan
Published: May 2024

Against the backdrop of global warming and increased rainfall, the hazards and potential risks of landslides are increasing. The rapid generation of a landslide inventory is of great significance for landslide disaster prevention and reduction. Deep learning has been widely applied in landslide identification due to its advantages in terms of its deeper model structure, high efficiency, and high accuracy. This article first provides an overview of deep learning technology and its basic principles, as well as the current status of landslide remote sensing databases. Then, classic landslide deep learning recognition models such as AlexNet, ResNet, YOLO, Mask R-CNN, U-Net, Transformer, EfficientNet, DeeplabV3+ and PSPNet were introduced, and the advantages and limitations of each model were extensively analyzed. Finally, the current constraints of deep learning in landslide identification were summarized, and the development direction of deep learning in landslide identification was analyzed. The purpose of this article is to promote the in-depth development of landslide identification research in order to provide academic references for the prevention and mitigation of landslide disasters and post-disaster rescue work. The research results indicate that deep learning methods have the characteristics of high efficiency and accuracy in automatic landslide recognition, and more attention should be paid to the development of emerging deep learning models in landslide recognition in the future.
Correcting an Off-Nadir to a Nadir Land Surface Temperature Using a Multitemporal Thermal Infrared Kernel-Driven Model during Daytime
Authors: Na Qiang , Cao Biao , Qin Boxiong , Mo Fan , Zheng Limeng , Du Yongming , Li Hua , Bian Zunjian , Xiao Qing , Liu Qinhuo
Published: May 2024

Land surface temperature (LST) is a fundamental parameter in global climate, environmental, and geophysical studies. Remote sensing is an essential approach for obtaining large-scale and frequently updated LST data. However, due to the wide field of view of remote sensing sensors, the observed LST with diverse view geometries suffers from inconsistency caused by the thermal radiation directionality (TRD) effect, which results in LST products being incomparable, especially during daytime. To address this issue and correct current off-nadir LSTs to nadir LSTs, a semi-physical time-evolved kernel-driven model (TEKDM) is proposed, which depicts multitemporal TRD patterns during the daytime. In addition, we employ a Bayesian optimization method to calibrate seven unknown parameters in the TEKDM. Validation results using the U.S. Climate Reference Network (USCRN) sites show that the RMSE (MBE) for GOES-16 and MODIS off-nadir LST products is reduced from 3.29 K (−2.0 K) to 2.34 K (−0.02 K), with an RMSE reduction of 0.95 K (29%) and a significant reduction in systematic bias. Moreover, the proposed method successfully eliminates the angular and temporal dependence of the LST difference between the satellite off-nadir LST and in situ nadir LST. In summary, this study presents a feasible approach for estimating the high-accuracy nadir LST, which can enhance the applicability of LST products in various domains.
Conditional Diffusion Model for Urban Morphology Prediction
Authors: Shi Tiandong , Zhao Ling , Liu Fanfan , Zhang Ming , Li Mengyao , Peng Chengli , Li Haifeng
Published: May 2024

Predicting urban morphology based on local attributes is an important issue in urban science research. The deep generative models represented by generative adversarial network (GAN) models have achieved impressive results in this area. However, in such methods, the urban morphology is assumed to follow a specific probability distribution and be able to directly approximate the distribution via GAN models, which is not a realistic strategy. As demonstrated by the score-based model, a better strategy is to learn the gradient of the probability distribution and implicitly approximate the distribution. Therefore, in this paper, an urban morphology prediction method based on the conditional diffusion model is proposed. Implementing this approach results in the decomposition of the attribute-based urban morphology prediction task into two subproblems: estimating the gradient of the conditional distribution, and gradient-based sampling. During the training stage, the gradient of the conditional distribution is approximated by using a conditional diffusion model to predict the noise added to the original urban morphology. In the generation stage, the corresponding conditional distribution is parameterized based on the noise predicted by the conditional diffusion model, and the final prediction result is generated through iterative sampling. The experimental results showed that compared with GAN-based methods, our method demonstrated improvements of 5.5%, 5.9%, and 13.2% in the metrics of low-level pixel features, shallow structural features, and deep structural features, respectively.
A Multi-Satellite Space Environment Risk Prediction and Real-Time Warning System for Satellite Safety Management
Authors: Kang Ning , Zhang Liguo , Zong Weiguo , Huang Pan , Zhang Yuqiang , Zhou Chen , Qiao Jian , Xue Bingsen
Published: May 2024

In response to the need for a space security situation assessment during orbit, the multi-satellite space environmental risk prediction and early warning system is based on the detection results of the space weather payload of the Fengyun 4A and 4B satellites, as well as the prediction results of the National Space Weather Center, for the first time. By comprehensively utilizing some open-source data, it is the first time that we have achieved a 24 h advanced prediction of the space environment high-energy proton, low-energy particle, and high-energy electron risks for the safety of the Fengyun-series high-orbit satellites, and a real-time warning of satellite single-event upset, surface charging, and deep charging risks. The automation system has preliminarily achieved an intelligent space risk assessment for the safety of multiple stationary meteorological satellites, effectively improving the application efficiency of the space environmental data and the products of Fengyun-series satellites. The business status is stable in operation, and the resulting error between the predicted results of various risk indices and the measured data was less than one level. The warning accuracy was better than 90%. This article uses the system for the first time, to use Fengyun satellite data to, accurately and in a timely manner, predict and warn us about the low-energy particles and surface charging high-risk levels of the Fengyun 4A and 4B satellites during the typical space weather event on 21 April 2023, in response to the impact of complex spatial environmental factors on the safety of Fengyun-series high-orbit satellites. The construction and operation of a multi-satellite space environmental risk prediction and early warning system can provide a reference for the safety work of subsequent satellite ground system operations.
Integrating Climate and Satellite Data for Multi-Temporal Pre-Harvest Prediction of Head Rice Yield in Australia
Authors: Clarke Allister , Yates Darren , Blanchard Christopher , Islam Md. Zahidul , Ford Russell , Rehman Sabih-Ur , Walsh Robert Paul
Published: May 2024

Precise and prompt predictions of crop yields are crucial for optimising farm management, post-harvest operations, and marketing strategies within the agricultural sector. While various machine learning approaches have been employed to forecast crop yield, their application to grain quality, particularly head rice yield (HRY), is less explored. This research collated crop-level HRY data across four seasons (2017/18–2020/21) from Australia’s rice-growing region. Models were developed using the XGBoost algorithm trained at varying time steps up to 16 weeks pre-harvest. The study compared the accuracy of models trained on datasets with climate data alone or paired with vegetative indices using two- and four-week aggregations. The results suggest that model accuracy increases as the harvest date approaches. The dataset combining climate and vegetative indices aggregated over two weeks surpassed industry benchmarks early in the season, achieving the highest accuracy two weeks before harvest (LCCC = 0.65; RMSE = 6.43). The analysis revealed that HRY correlates strongly with agroclimatic conditions nearer harvest, with the significance of vegetative indices-based features increasing as the season progresses. These features, indicative of crop and grain maturity, could aid growers in determining optimal harvest timing. This investigation offers valuable insights into grain quality forecasting, presenting a model adaptable to other regions with accessible climate and satellite data, consequently enhancing farm- and industry-level decision-making.
Relationship between Socioeconomic Status and Pro-Environmental Behavior: The Role of Efficacy Beliefs
Authors: Vrselja Ivana , Batinić Lana , Pandžić Mario
Published: May 2024

Efficacy beliefs are important determinants of human behavior. In the context of social cognitive theory, the perception of collective efficacy is closely related to the individual perception of self-efficacy, which is influenced by socio-structural factors such as socioeconomic status (SES). Surprisingly, the relationship between these variables has received little attention in the literature on environmental issues. Within the framework of social cognitive theory, the aim of this study was to investigate whether SES has a direct effect on pro-environmental behavior and whether it has an indirect effect via perceptions of self-efficacy and collective efficacy, in relation to climate change mitigation behavior. An online cross-sectional study was conducted using a quota sample of 1075 participants (51.9% women) aged 18–79 years. Participants reported their SES using objective and subjective measures, perceptions of their own and collective efficacy in mitigating climate change, and the frequency of their pro-environmental behaviors. Structural equation modeling revealed that the model with serial mediation effects of self-efficacy and collective efficacy between SES (both objective and subjective) and pro-environmental behaviors showed a good model fit. As expected, both objective and subjective SES had no direct effect on pro-environmental behavior. Surprisingly, neither objective nor subjective SES had an indirect effect (via efficacy beliefs) on pro-environmental behavior. However, both self-efficacy and collective efficacy were associated with pro-environmental behavior. These findings have practical implications for the development of strategies aimed at enhancing pro-environmental behavior.
Towards a Communication Ecology in the Life of Rural Senior Citizens: How Rural Public Spaces Influence Community Engagement
Authors: Feng Zhiyu , Li Longfei , Zhang Jingchun , Feng Xinqun
Published: May 2024

The dilemma of weak participation and non-participation of rural communities is a universal topic of global development. The rural public space is an important field for local residents to interact, communicate, and engage with each other, and is an important place for the sustainable development of rural areas. However, previous studies have neglected to understand the intrinsic connection between rural public space and community participation from the perspective of community communication ecology. Based on the concept of age-friendly communities, this study’s fieldwork in rural Shanghai, China, using the methodology of grounded theory, found that physical, social, and psychological factors all have an impact on community engagement among rural residents. Specifically, environmental quality, facility support, community networks, social participation, call to action, place attachment, spatial perception, and self-transformation are identified as the core elements that significantly influence community engagement among rural residents. This study further reveals that the multiple factors influencing community engagement among rural residents are complex and interdependent rather than operating independently. Spatial support, communicative triggers, and symbolic identification, respectively, operate at the technological level (physical–social factors), social level (social–psychological factors), and discursive level (psychological–physical factors) to promote community engagement among older adults in Chinese rural areas. Through this research, we hope to further the realization of rural civic engagement and the sustainability of local communities and to provide scholarly insights into the promotion of more equitable community life.