bluuebunny/crossref_metadata_2025 huggingface dataset:
Gaps between Rice Actual and Potential Yields Based on the VPM and GAEZ Models in Heilongjiang Province, China
Authors: Pu Luoman , Jiang Junnan , Ma Menglu , Huang Duan
Published: February 2024

Heilongjiang Province is a significant region for grain production and serves as a crucial commodity grain production base in China. In recent years, due to the threat of declining cropland quality and quantity, coupled with the increasingly prominent demand for grain, there is an urgent need to enhance rice yields in Heilongjiang Province. It is imperative to accurately identify the gaps between actual and potential grain yields and effectively implement yield-enhancing measures in regions with significant yield gaps. This study aimed to determine the rice reproductive periods of Heilongjiang Province for 2000, 2010, and 2020, estimate the rice actual yields using the Vegetation Photosynthesis Model (VPM), simulate the rice potential yields based on the Global Agro-Ecological Zones (GAEZ) Model, and then identify the rice yield gaps at the pixel level by calculating the rice absolute yield gap (AYG) and relative yield gap (RYG). Additionally, yield-enhancing measures were proposed for regions with significant yield gaps. The results were as follows. (1) The rice reproductive periods of Heilongjiang Province for 2000, 2010, and 2020 were determined as days 153~249, days 145~249, and days 137~249. (2) The mean rice actual yield and potential yields decreased by 1222 and 5941 kg ha−1 during the 2000–2020 period, respectively, and the total actual and potential production increased by 3.75 and 1.70 million tons in Heilongjiang Province, respectively. (3) The rice AYG and RYG in the Sanjiang Plain region, such as Jixi City, Hegang City, and Jiamusi City were relatively large compared to other regions for the three years, and the rice yield gaps continued to decrease during the 2000–2020 period. (4) With regard to the Sanjiang Plain region with a large rice yield gap, this study proposes measures to narrow the rice yield gap by establishing ecological protection forests on cropland, transforming low- and middle-yielding fields, increasing agricultural science and technology inputs, selecting better rice cultivars, etc., which are important for ensuring food security.
SARS-CoV-2: A Glance at the Innate Immune Response Elicited by Infection and Vaccination
Authors: Manfrini Nicola , Notarbartolo Samuele , Grifantini Renata , Pesce Elisa
Published: February 2024

The COVID-19 pandemic caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has led to almost seven million deaths worldwide. SARS-CoV-2 causes infection through respiratory transmission and can occur either without any symptoms or with clinical manifestations which can be mild, severe or, in some cases, even fatal. Innate immunity provides the initial defense against the virus by sensing pathogen-associated molecular patterns and triggering signaling pathways that activate the antiviral and inflammatory responses, which limit viral replication and help the identification and removal of infected cells. However, temporally dysregulated and excessive activation of the innate immune response is deleterious for the host and associates with severe COVID-19. In addition to its defensive role, innate immunity is pivotal in priming the adaptive immune response and polarizing its effector function. This capacity is relevant in the context of both SARS-CoV-2 natural infection and COVID-19 vaccination. Here, we provide an overview of the current knowledge of the innate immune responses to SARS-CoV-2 infection and vaccination.
Aeromonas spp. in Freshwater Bodies: Antimicrobial Resistance and Biofilm Assembly
Authors: Nascimento Maria , Rodrigues Joao , Matias Rui , Jordao Luisa
Published: February 2024

Aeromonas spp. are environmental bacteria able to infect animals and humans. Here, we aim to evaluate the role of biofilms in Aeromonas persistence in freshwater. Aeromonas were isolated from water and biofilm samples and identified by Vitek-MS and 16S rRNA sequencing. Antibiotic susceptibility profiles were determined according to EUCAST, and a crystal violet assay was used to assess biofilm assembly. MTT and the enumeration of colony-forming units were used to evaluate biofilm and planktonic Aeromonas susceptibility to chlorination, respectively. Identification at the species level was challenging, suggesting the need to improve the used methodologies. Five different Aeromonas species (A. salmonicida, A. hydrophila, A. media, A. popoffii and A. veronii) were identified from water, and one species was identified from biofilms (A. veronii). A. veronnii and A. salmonicida presented resistance to different antibiotics, whith the highest resistance rate observed for A. salmonicida (multiple antibiotic resistance index of 0.25). Of the 21 isolates, 11 were biofilm producers, and 10 of them were strong biofilm producers (SBPs). The SBPs presented increased tolerance to chlorine disinfection when compared with their planktonic counterparts. In order to elucidate the mechanisms underlying biofilm tolerance to chlorine and support the importance of preventing biofilm assembly in water reservoirs, further research is required.
Co-Administration of High-Dose Nebulized Colistin for Acinetobacter baumannii Bacteremic Ventilator-Associated Pneumonia: Impact on Outcomes
Authors: Andrianopoulos Ioannis , Kazakos Nikolaos , Lagos Nikolaos , Maniatopoulou Theodora , Papathanasiou Athanasios , Papathanakos Georgios , Koulenti Despoina , Toli Eleni , Gartzonika Konstantina , Koulouras Vasilios
Published: February 2024

Acinetobacter baumannii (A. baumannii) is a difficult-to-treat (DTR) pathogen that causes ventilator-associated pneumonia (VAP) associated with high mortality. To improve the outcome of DTR A. Baumannii VAP, nebulized colistin (NC) was introduced with promising but conflicting results on mortality in earlier studies. Currently, NC is used at a much higher daily dose compared to the past. Nevertheless, there is little evidence on the effect of high-dose NC on the outcomes of A. baumannii VAPs, especially in the current era where the percentage of colistin-resistant A. baumannii strains is rising. We conducted a retrospective study comparing bacteremic A. baumannii VAP patients who were treated with and without NC co-administration and were admitted in the Intensive Care Unit of University Hospital of Ioannina from March 2020 to August 2023. Overall, 59 patients (21 and 38 with and without NC coadministration, respectively) were included. Both 28-day and 7-day mortalities were significantly lower in the patient group treated with NC (52.4% vs. 78.9%, p 0.034 and 9.5% vs. 47.4%, p 0.003, respectively). Patients treated with NC had a higher percentage of sepsis resolution by day 7 (38.1% vs. 13.5%, p 0.023) and were more likely to be off vasopressors by day 7 (28.6% vs. 8.1%, p 0.039). The addition of NC in the treatment regime of A. baumannii VAP decreased mortality.
TNF-α Levels Are Increased in Patients with Subjective Cognitive Impairment and Are Negatively Correlated with β Amyloid-42
Authors: Serafini Sara , Ferretti Gabriella , Monterosso Paola , Angiolillo Antonella , Di Costanzo Alfonso , Matrone Carmela
Published: February 2024

The role of tumor necrosis factor-α (TNF-α) in Alzheimer’s disease (AD) has recently become a topic of debate. TNF-α levels increase in the blood of patients with AD, and amyloid beta (Aβ) plaques contain TNF-α deposits. The therapeutic efficacy of blocking TNF-α in patients with AD remains controversial as it is mostly based on preclinical studies. Thus, whether and how TNF-α contributes to amyloidogenic processes in AD is still an open question to be addressed. We analyzed plasma TNF-α and Aβ42 levels in patients with subjective cognitive impairment (SCI), mild cognitive impairment (MCI), and AD, and in healthy volunteers (HLT). In addition, we performed correlation analysis to evaluate whether changes in plasma TNF-α levels correlate with cognitive decline, Aβ42 levels, age, and BMI, which are all factors considered to contribute to or predispose individuals to AD. We found that TNF-α and Aβ42 plasma levels were higher in patients with AD than in HLT individuals. High TNF-α levels were also observed in patients with SCI, in whom TNF-α and Aβ42 levels were negatively correlated. Notably, TNF-α did not affect the amyloidogenic pathway in human microglial cultures exposed to 48 h of incubation, although it did trigger neuroinflammatory processes. These results imply that high TNF-α levels are more likely to be a clinical condition linked to AD than are direct contributors. Nonetheless, elevated levels of TNF-α in early-stage patients, like those with SCI and MCI, may provide a distinguishing feature for identifying clinical profiles that are at risk of having a poorer outcome in AD and could benefit from tailored therapies.
An Experimental Study on the Sealing Mechanism of a Karst Pipeline by Dynamic Water Grouting
Authors: Liu Jie , Liu Shuai , Wang Mingyuan , Peng Bo
Published: February 2024

Aiming at the problem of water burst plugging in karst pipelines, in this paper, a new type of waterborne epoxy resin magnetic self-polymerization grouting material (WEMS) suitable for karst pipeline water burst plugging was developed, and a visual simulation test device for karst pipeline water burst grouting plugging was designed and built. Through the orthogonal test of grouting plugging, the influence of different factors on the effect of grouting plugging was analyzed, and the shear mechanism of magnetic slurry magnetization plugging was also analyzed. The results showed that (i) the best grouting sealing performance was achieved when the new WEMS had a water–cement ratio of 0.35–0.55 and Fe3O4 powder misery of 20–40%. (ii) The primary relationship between the factors affecting the dynamic water flow rate and slurry retention is Fe3O4 power ratio > plugging length > water–cement ratio. (iii) The relationship equation was established between the shear strength of magnetic self-polymerizing slurry and the magnetic field strength, blocking length, and slurry ratio.
Critical Study Quality Management for the Anti-Seepage System in Macau’s Landfill Area
Authors: Li Zhaobin , Tang Waifan , Mak Shulun , Li Qingwen , Chen Haolin , Hong Qianqian
Published: February 2024

This paper delves into the Macau landfill’s anti-seepage system project quality management, highlighting its environmental significance. We summarize global research and provide an overview of the project, emphasizing the importance of quality control across phases. We focus on monitoring, evaluation, and inspection methods to ensure quality objectives. Our findings contribute to environmental preservation and sustainability.
Integrating Merkle Trees with Transformer Networks for Secure Financial Computation
Authors: Wang Xinyue , Lin Weifan , Zhang Weiting , Huang Yiwen , Li Zeyu , Liu Qian , Yang Xinze , Yao Yifan , Lv Chunli
Published: February 2024

In this paper, the Merkle-Transformer model is introduced as an innovative approach designed for financial data processing, which combines the data integrity verification mechanism of Merkle trees with the data processing capabilities of the Transformer model. A series of experiments on key tasks, such as financial behavior detection and stock price prediction, were conducted to validate the effectiveness of the model. The results demonstrate that the Merkle-Transformer significantly outperforms existing deep learning models (such as RoBERTa and BERT) across performance metrics, including precision, recall, accuracy, and F1 score. In particular, in the task of stock price prediction, the performance is notable, with nearly all evaluation metrics scoring above 0.9. Moreover, the performance of the model across various hardware platforms, as well as the security performance of the proposed method, were investigated. The Merkle-Transformer exhibits exceptional performance and robust data security even in resource-constrained environments across diverse hardware configurations. This research offers a new perspective, underscoring the importance of considering data security in financial data processing and confirming the superiority of integrating data verification mechanisms in deep learning models for handling financial data. The core contribution of this work is the first proposition and empirical demonstration of a financial data analysis model that fuses data integrity verification with efficient data processing, providing a novel solution for the fintech domain. It is believed that the widespread adoption and application of the Merkle-Transformer model will greatly advance innovation in the financial industry and lay a solid foundation for future research on secure financial data processing.
SqueezeNet: An Improved Lightweight Neural Network for Sheep Facial Recognition
Authors: Hao Min , Sun Quan , Xuan Chuanzhong , Zhang Xiwen , Zhao Minghui
Published: February 2024

To quickly realize facial identity recognition in sheep, this paper proposes a lightweight detection algorithm based on SSD with a self-constructed dataset. Firstly, the algorithm replaces the VGG16 backbone of SSD with the lightweight neural network SqueezeNet, creating a lightweight hybrid network model. Secondly, an ECA mechanism is introduced at the front end of the pooling layer with a parameter volume of 12 × 1000 into the feature extraction network. Lastly, the smoothL1 loss function is replaced with the BalancedL1 loss function. The optimal model size has been reduced from the original SSD’s 132 MB to 35.8 MB. The average precision is 82.39%, and the mean frame rate is 66.11 frames per second. Compared to the baseline SSD model, the average precision has improved by 2.17%, the model volume has decreased by 96.2 MB, and the detection speed has increased by 7.13 frames per second. Using the same dataset on different target detection models for comparison tests, the average accuracy mean values are improved by 2.17%, 3.63%, and 1.30% compared to the SSD model, Faster R-CNN model, and Retinanet model, respectively, which substantiates a better overall performance compared to the pre-improvement model. This paper proposes an improved model that significantly reduces the model size and its computation while keeping the model performance at a high level, providing a methodological reference for the digitization of livestock farming.
Effect of Essential Oil Components on the Activity of Steroidogenic Cytochrome P450
Authors: Sharma Katyayani , Lanzilotto Angelo , Yakubu Jibira , Therkelsen Søren , Vöegel Clarissa Daniela , Du Toit Therina , Jørgensen Flemming Steen , Pandey Amit V.
Published: February 2024

Endocrine-disrupting chemicals (EDCs) may impact the development of prostate cancer (PCa) by altering the steroid metabolism. Although their exact mechanism of action in controlling tumor growth is not known, EDCs may inhibit steroidogenic enzymes such as CYP17A1 or CYP19A1 which are involved in the production of androgens or estrogens. High levels of circulating androgens are linked to PCa in men and Polycystic Ovary Syndrome (PCOS) in women. Essential oils or their metabolites, like lavender oil and tea tree oil, have been reported to act as potential EDCs and contribute towards sex steroid imbalance in cases of prepubertal gynecomastia in boys and premature thelarche in girls due to the exposure to lavender-based fragrances. We screened a range of EO components to determine their effects on CYP17A1 and CYP19A1. Computational docking was performed to predict the binding of essential oils with CYP17A1 and CYP19A1. Functional assays were performed using the radiolabeled substrates or Liquid Chromatography–High-Resolution Mass Spectrometry and cell viability assays were carried out in LNCaP cells. Many of the tested compounds bind close to the active site of CYP17A1, and (+)-Cedrol had the best binding with CYP17A1 and CYP19A1. Eucalyptol, Dihydro-β-Ionone, and (−)-α-pinene showed 20% to 40% inhibition of dehydroepiandrosterone production; and some compounds also effected CYP19A1. Extensive use of these essential oils in various beauty and hygiene products is common, but only limited knowledge about their potential detrimental side effects exists. Our results suggest that prolonged exposure to some of these essential oils may result in steroid imbalances. On the other hand, due to their effect on lowering androgen output and ability to bind at the active site of steroidogenic cytochrome P450s, these compounds may provide design ideas for novel compounds against hyperandrogenic disorders such as PCa and PCOS.
Age-Dependent Activation of Purinergic Transmission Contributes to the Development of Epileptogenesis in ADSHE Model Rats
Authors: Fukuyama Kouji , Motomura Eishi , Okada Motohiro
Published: February 2024

To explore the developmental processes of epileptogenesis/ictogenesis, this study determined age-dependent functional abnormalities associated with purinergic transmission in a genetic rat model (S286L-TG) of autosomal-dominant sleep-related hypermotor epilepsy (ADSHE). The age-dependent fluctuations in the release of ATP and L-glutamate in the orbitofrontal cortex (OFC) were determined using microdialysis and ultra-high-performance liquid chromatography with mass spectrometry (UHPLC-MS). ATP release from cultured astrocytes was also determined using UHPLC-MS. The expressions of P2X7 receptor (P2X7R), connexin 43, phosphorylated-Akt and phosphorylated-Erk were determined using capillary immunoblotting. No functional abnormalities associated with purinergic transmission could be detected in the OFC of 4-week-old S286L-TG and cultured S286L-TG astrocytes. However, P2X7R expression, as well as basal and P2X7R agonist-induced ATP releases, was enhanced in S286L-TG OFC in the critical ADSHE seizure onset period (7-week-old). Long-term exposure to a modest level of P2X7R agonist, which could not increase astroglial ATP release, for 14 d increased the expressions of P2X7R and connexin 43 and the signaling of Akt and Erk in astrocytes, and it enhanced the sensitivity of P2X7R to its agonists. Akt but not Erk increased P2X7R expression, whereas both Akt and Erk increased connexin 43 expression. Functional abnormalities, enhanced ATP release and P2X7R expression were already seen before the onset of ADSHE seizure in S286L-TG. Additionally, long-term exposure to the P2X7R agonist mimicked the functional abnormalities associated with purinergic transmission in astrocytes, similar to those in S286L-TG OFC. Therefore, these results suggest that long-term modestly enhanced purinergic transmission and/or activated P2X7R are, at least partially, involved in the development of the epileptogenesis of ADSHE, rather than that of ictogenesis.
Addressing a Pre-Clinical Pipeline Gap: Development of the Pediatric Acute Myeloid Leukemia Patient-Derived Xenograft Program at Texas Children’s Hospital at Baylor College of Medicine
Authors: Stevens Alexandra M. , Terrell Maci , Rashid Raushan , Fisher Kevin E. , Marcogliese Andrea N. , Gaikwad Amos , Rao Pulivarthi , Vrana Chelsea , Krueger Michael , Loken Michael , Menssen Andrew J. , Cook Jacqueline A. , Keogh Noah , Alozie Michelle , Oviedo Hailey , Gonzalez Alan K. , Ilangovan Tamilini , Kim Julia , Sandhu Sohani , Redell Michele S.
Published: February 2024

The survival rate of pediatric acute myeloid leukemia (pAML) is currently around 60%. While survival has slowly increased over the past few decades, the development of novel agents likely to further improve survival for this heterogeneous patient population has been limited by gaps in the pAML pre-clinical pipeline. One of the major hurdles in evaluating new agents for pAML is the lack of pAML patient-derived xenograft (PDX) models. Unlike solid tumors and other types of leukemias, AML is notoriously hard to establish in mouse models, likely due in part to the need for specific human microenvironment elements. Our laboratory at TCH/BCM addressed this gap by establishing a systematic PDX workflow, leveraging advanced immunodeficient hosts and capitalizing on our high volume of pAML patients and close coordination between labs and clinical sections. Patients treated at TCH are offered the chance to participate in specimen banking protocols that allow blood and bone marrow collection as well as the collection of relevant clinical data. All patients who consent and have samples available are trialed for PDX development. In addition, samples from the Children’s Oncology Group (COG) are also trialed for PDX generation. Serially transplanting PDX models are validated using short tandem repeat (STR) and characterized using both targeted DNA/RNA next generation sequencing and RNAseq. As of March 2023, this systematic approach has resulted in 26 serially transplanting models. Models have been shared with requesting labs to facilitate external pAML pre-clinical studies. Available PDX models can be located through the BCM PDX Portal. We expect our growing PDX resource to make a significant contribution to expediting the testing of promising novel therapeutics for pAML.
Diagnostic Value of Fasting and Bedtime Saliva Pepsin Measurements in Laryngopharyngeal Reflux
Authors: Lechien Jerome R. , Bobin Francois
Published: February 2024

Background: The pepsin test is an emerging non-invasive diagnostic approach for laryngopharyngeal reflux (LPR). The aim of this study was to investigate the diagnostic value of multiple salivary pepsin tests for detecting LPR. Methods: Patients with suspected LPR and asymptomatic individuals were consecutively recruited from January 2020 to November 2022. Patients benefited from hypopharyngeal–esophageal impedance-pH monitoring (HEMII-pH) and fasting and bedtime saliva collections to measure oral pepsin. The sensitivity, specificity, and positive (PPV) and negative (NPV) predictive values were calculated considering fasting, bedtime, and the highest values of the pepsin tests at ≥16, ≥36, ≥45, and ≥100 ng/mL cutoffs. Results: The pepsin test was adequately performed in 147 LPR patients and 32 controls. The pepsin tests were 81.6%, 74.8%, and 61.5% sensitive at cutoffs of ≥16, ≥45, and ≥100 ng/mL, respectively. The PPVs were 93.0%, 94.0%, and 94.8%, respectively. The highest specificity (81.8%) was found for the fasting pepsin test at a cutoff of 100 ng/mL. The highest sensitivity (81.6%) was found by considering the highest measured pepsin test at the ≥16 ng/mL threshold. The measurement of fasting saliva pepsin was associated with the highest sensitivity and specificity value. At ≥16 ng/mL, 27 patients had negative findings, indicating that 18.4% (27/147) of the true positive cases were missed by considering the highest pepsin test. The receiver operating characteristic curve reported that a cutoff of 21.5 was 76.9% sensitive and 62.5% specific, while the PPV and NPV were 91.1% and 38.2%, respectively. Conclusions: The consideration of the highest concentration of the fasting and bedtime saliva pepsin collections at a cutoff of 21.5 was associated with the best detection rate and sensitivity of the pepsin tests.
Ankyloglossia in Children, a Cause of Obstructive Sleep Apnoea: Case Report of Paediatric Ankyloglossia and Sleep Apnoea: DISE Resolves the Mystery
Authors: Valderrama-Penagos Johanna Ximena , Rodríguez Alcalá Laura , Plaza Guillermo , Baptista Peter , Garcia Iriarte Maria Teresa , Correa Eduardo J. , O’Connor-Reina Carlos
Published: February 2024

Tongue mobility is an obstructive sleep apnoea (OSA) marker and myofunctional therapy (MFT) target. For this reason, all paediatric patients with sleep-disordered breathing should require a combined functional assessment from an ear, nose, and throat (ENT) specialist and a phonoaudiologist to confirm or rule out the presence of ankyloglossia. To our knowledge, this is the first case of a 13-year-old girl diagnosed with severe OSA and a significant decrease of 94% in her apnoea index (AI), requiring frenotomy with an immediate postoperative change in the tongue position. A drug-induced sleep endoscopy (DISE) was performed before and immediately postfrenotomy, and the anatomical changes provoked by this surgery during sleep were confirmed for the first time.
Trends in Longer-Term Corrosion Loss of Magnesium Alloys
Authors: Melchers Robert
Published: February 2024

The corrosion of magnesium alloys is often considered to differ in behaviour and development with time from most other metals and alloys because they show evolution of hydrogen right from first exposure. However, data extracted from the open literature indicate that magnesium alloys develop corrosion mass-loss trends with time that are consistent with the so-called bimodal pattern, which is topologically similar to those of other alloys. Examples are given of such trending for magnesium alloys under immersion, half-tide and various atmospheric exposure conditions. The critical roles of corrosion pitting and its development into localised corrosion are discussed. For high-purity magnesium alloys, the transition to longer-term corrosion, which is rate-controlled by the hydrogen evolution cathodic reaction, occurs quickly, within days. Comments are made about the application of measurements of hydrogen evolution and of electrochemical methods to make rapid estimates of shorter-term corrosion rates.
Bilocal Field Theory for Composite Scalar Bosons
Authors: Hill Christopher T.
Published: February 2024

We give a bilocal field theory description of a composite scalar with an extended binding potential that reduces to the Nambu–Jona-Lasinio (NJL) model in the pointlike limit. This provides a description of the internal dynamics of the bound state and features a static internal wave function, ϕ(r→), in the center-of-mass frame that satisfies a Schrödinger–Klein–Gordon equation with eigenvalues m2. We analyze the “coloron” model (single perturbative massive gluon exchange) which yields a UV completion of the NJL model. This has a BCS-like enhancement of its interaction, ∝Nc the number of colors, and is classically critical with gcritical remarkably close to the NJL quantum critical coupling. Negative eigenvalues for m2 lead to spontaneous symmetry breaking, and the Yukawa coupling of the bound state to constituent fermions is emergent.
A Novel Alternating μ-Law Companding Algorithm for PAPR Reduction in OFDM Systems
Authors: Tu Yung-Ping , Zhan Zi-Teng , Huang Yung-Fa
Published: February 2024

Orthogonal frequency division multiplexing (OFDM) inherits multi-carrier systems’ inevitable high peak-to-average power ratio (PAPR) problem. In this paper, a novel alternating companding technique is proposed to combat the harassment of high PAPR. The sequential μ-law companding (SULC) and a tone with a lower PAPR result in only partial tones needing companding. The SULC scheme’s PAPR and bit error rate (BER) performance has been balanced and improved. However, the computational complexity is still too high to be implemented. Therefore, this study sorted the transmission signals according to their amplitudes. Then, all the tones are divided into two groups by estimating the rough companding amount (around 54% of the subcarriers), using traditional parallel companding for the first group and the other group only by partial μ-law companding. This alternating μ-law companding (AULC) is proposed to improve the PAPR performance and simultaneously reduce complexity. Simulation results show that the proposed AULC method appreciably reduces the PAPR by about 5 dB (around 45%) compared with the original μ-law at complementary cumulative distribution function (CCDF) equal to 10−4. Moreover, it only requires a moderate complexity to outperform the other companding schemes without sacrificing the BER performance in the OFDM systems.
Sediment Response after Wildfires in Mountain Streams and Their Effects on Cultural Heritage: The Case of the 2021 Navalacruz Wildfire (Avila, Spain)
Authors: Ortega-Becerril Jose A. , Suarez Clara , Vázquez-Tarrío Daniel , Garrote Julio , Gomez-Heras Miguel
Published: February 2024

The 2021 Navalacruz wildfire occurred in a mountainous area in the Sistema Central (Spain). Despite having an average low severity index (dNBR), the loss of vegetation cover associated with the fire was responsible for a high rate of sedimentation in the rivers and streams. Additionally, the burned area affected up to 60 cultural heritage sites, including archaeological and ethnological sites, and damage ranged from burnt pieces of wood to the burial of archaeological sites. In the present work, we document and analyze the post-fire evolution in several rivers and streams. This is based on a field survey of infiltration rates, hydrodynamic modeling, and the study of channel morphological changes. Our analysis revealed how the first post-fire rains caused the mobilization and transport of ashes. This created hydrophobicity in the soils, resulting in large amounts of materials being transported to rivers and streams by subsequent medium- and low-magnitude storms. A hydrological and hydraulic model of the study catchments under pre- and post-fire conditions suggests that these trends are a consequence of a post-fire increase in flow rates for similar rainfall scenarios. In this respect, our estimates point at a significant increase in sediment transport capacities associated with this post-fire increase in flow rates. The combination of locally steep slopes with high-severity fire patches, and a considerable regolith (derived from pre-fire weathering), resulted in a series of cascading responses, such as an exacerbated supply of sand to the drainage network and the triggering of debris flows, followed by erosion and entrenchment.
Generational Differences in Food Choices and Consumer Behaviors in the Context of Sustainable Development
Authors: Makowska Marta , Boguszewski Rafał , Hrehorowicz Arleta
Published: February 2024

(1) Background: This study examines diverse food choices and sustainable consumption behavior across four generations of Poles: Baby Boomers, Generation X, Generation Y, and Generation Z. (2) Methods: The research employed an online survey with a quota sample of 1000 individuals, representing the Polish population in terms of gender, residence, and education (categorized into two groups). (3) Results: For Poles, the crucial factors in food selection were product quality (69.0%), price (68.6%), and information about the product’s composition (41.0%). Older cohorts (Baby Boomers and Generation X) prioritized food quality, while younger generations (Generation Y and Generation Z) emphasized price. Statistically significant differences emerged between generations regarding the product’s country of origin, with older generations emphasizing its importance more. The oldest group (Baby Boomers) considered ecological certification most important. As much as 85.9% of Poles checked product expiration dates while buying products, and 82.8% bought only as much as they needed. Baby Boomers most often exhibited these two behaviors and can be considered the most responsible among all generations. (4) Conclusions: This article highlights the importance of comprehensive sustainability efforts in the context of food choices. It takes into account the socio-cultural and historical circumstances of each generation that influence their consumer habits.
Optimization and Characterization of Interspecific Hybrid Crude Palm Oil Unaué HIE OxG Nanoparticles with Vegetable By-Products as Encapsulants
Authors: Assunção Larissa Santos , Oliveira de Souza Carolina , Shahidi Fereidoon , Santos Oliveira Tainara , Assis Denilson de Jesus , Pereira Santos Luis Fernandes , Nunes Itaciara Larroza , Machado Bruna Aparecida Souza , Ferreira Ribeiro Camila Duarte
Published: February 2024

Interspecific hybrid crude palm oil (HCPO) HIE OxG derived from crossbred African oil palm (Elaeis guineensis) and American Caiaué (Elaeis oleifera) is prominent for its fatty acid and antioxidant compositions (carotenoids, tocopherols, and tocotrienols), lower production cost, and high pest resistance properties compared to crude palm oil. Biodegradable and sustainable encapsulants derived from vegetable byproducts were used to formulate HCPO nanoparticles. Nanoparticles with hybrid crude palm oil and jackfruit seed flour as a wall material (N-JSF) and with hybrid crude palm oil and jackfruit axis flour as a wall material (N-JAF) were optimized using a 22 experimental design. They exhibited nanoscale diameters (<250 nm) and were characterized based on their zeta potential, apparent viscosity, pH, color, and total carotenoid content. The nanoparticles demonstrated a monodisperse distribution, good uniformity, and stability (polydispersity index < 0.25; zeta potentials: N-JSF −19.50 ± 1.47 mV and N-JAF −12.50 ± 0.17 mV), as well as high encapsulation efficiency (%) (N-JSF 86.44 ± 0.01 and N-JAF 90.43 ± 1.34) and an optimal carotenoid retention (>85%). These nanoparticles show potential for use as sustainable and clean-label HCPO alternatives in the food industry.
Non-Destructive Evaluation of the Physiochemical Properties of Milk Drink Flavored with Date Syrup Utilizing VIS-NIR Spectroscopy and ANN Analysis
Authors: Elamshity Mahmoud G. , Alhamdan Abdullah M.
Published: February 2024

A milk drink flavored with date syrup produced at a lab scale level was evaluated. The production process of date syrup involves a sequence of essential unit operations, commencing with the extraction, filtration, and concentration processes from two cultivars: Sukkary and Khlass. Date syrup was then mixed with cow’s and camel’s milk at four percentages to form a nutritious, natural, sweet, and energy-rich milk drink. The sensory, physical, and chemical characteristics of the milk drinks flavored with date syrup were examined. The objective of this work was to measure the physiochemical properties of date fruits and milk drinks flavored with date syrup, and then to evaluate the physical properties of milk drinks utilizing non-destructive visible–near-infrared spectra (VIS-NIR). The study assessed the characteristics of the milk drink enhanced with date syrup by employing VIS-NIR spectra and utilizing a partial least-square regression (PLSR) and artificial neural network (ANN) analysis. The VIS-NIR spectra proved to be highly effective in estimating the physiochemical attributes of the flavored milk drink. The ANN model outperformed the PLSR model in this context. RMSECV is considered a more reliable indicator of a model’s future predictive performance compared to RMSEC, and the R2 value ranged between 0.946 and 0.989. Consequently, non-destructive VIS-NIR technology demonstrates significant promise for accurately predicting and contributing to the entire production process of the product’s properties examined.
A Hybrided Method for Temporal Variable-Order Fractional Partial Differential Equations with Fractional Laplace Operator
Authors: Wang Chengyi , Yi Shichao
Published: February 2024

In this paper, we present a more general approach based on a Picard integral scheme for nonlinear partial differential equations with a variable time-fractional derivative of order α(x,t)∈(1,2) and space-fractional order s∈(0,1), where v=u′(t) is introduced as the new unknown function and u is recovered using the quadrature. In order to get rid of the constraints of traditional plans considering the half-time situation, integration by parts and the regularity process are introduced on the variable v. The convergence order can reach O(τ2+h2), different from the common L1,2−α schemes with convergence rate O(τ2,3−α(x,t)) under the infinite norm. In each integer time step, the stability, solvability and convergence of this scheme are proved. Several error results and convergence rates are calculated using numerical simulations to evidence the theoretical values of the proposed method.
Correction: Arimori et al. Association between Lifestyle Factors and Weight Gain among University Students in Japan during COVID-19 Mild Lockdown: A Quantitative Study. Healthcare 2023, 11, 2630
Authors: Arimori Haruka , Abiru Norio , Morimoto Shimpei , Nishino Tomoya , Kawakami Atsushi , Kamada Akie , Kobayashi Masakazu
Published: February 2024

In our published publication [...]
Enhanced Recovery after Surgery (ERAS) Implementation and Barriers among Healthcare Providers in France: A Cross-Sectional Study
Authors: Clet Augustin , Guy Marin , Muir Jean-François , Cuvelier Antoine , Gravier Francis-Edouard , Bonnevie Tristan
Published: February 2024

The implementation of Enhanced Recovery After Surgery (ERAS) is a challenge for healthcare systems, especially in case of patients undergoing major surgery. Despite a proven significant reduction in postoperative complications and hospital lengths of stay, ERAS protocols are inconsistently used in real-world practice, and barriers have been poorly described in a cohort comprising medical and paramedical professionals. This study aims to assess the proportion of French healthcare providers who practiced ERAS and to identify barriers to its implementation amongst those surveyed. We conducted a prospective cross-sectional study to survey healthcare providers about their practice of ERAS using an online questionnaire. Healthcare providers were contacted through hospital requests, private hospital group requests, professional corporation requests, social networks, and personal contacts. The questionnaire was also designed to explore barriers to ERAS implementation. Identified barriers were allocated by two independent assessors to one of the fourteen domains of the Theoretical Domains Framework (TDF), which is an integrative framework based on behavior change theories that can be used to identify issues relating to evidence on the implementation of best practice in healthcare settings. One hundred and fifty-three French healthcare providers answered the online questionnaire (76% female, median age 35 years (IQR: 29 to 48)). Physiotherapists, nurses, and dieticians were the most represented professions (31.4%, 24.2%, and, 14.4%, respectively). Amongst those surveyed, thirty-one practiced ERAS (20.3%, 95%CI: 13.9 to 26.63). Major barriers to ERAS practice were related to the “Environmental context and resources” domain (57.6%, 95%CI: 49.5–65.4), e.g., lack of professionals, funding, and coordination, and the “Knowledge” domain (52.8%, 95%CI: 44.7–60.8), e.g., ERAS unawareness. ERAS in major surgery is seldom practiced in France due to the unfavorable environment (i.e., logistics issues, and lack of professionals and funding) and a low rate of procedure awareness. Future studies should focus on devising and assessing strategies (e.g., education and training, collaboration, institutional support, the development of healthcare networks, and leveraging telehealth and technology) to overcome these barriers, thereby promoting the wider implementation of ERAS.
Mechanical Characteristics of Gas Hydrate-Bearing Sediments: An Experimental Study from the South China Sea
Authors: Yuan Qingmeng , Kong Liang , Liang Qianyong , Liang Jinqiang , Yang Lin , Dong Yifei , Wang Zhigang , Wu Xuemin
Published: February 2024

Clarifying the mechanical characteristics of gas hydrate-bearing sediments (GHBS) from a mechanical perspective is crucial for ensuring the long-term, safe, and efficient extraction of natural gas hydrates. In this study, seabed soft clay from the northern South China Sea was utilized to prepare clayey silt samples, aligning with gradation curves related to hydrate extraction projects in the Shenhu area of the South China Sea. Utilizing the high-pressure low-temperature hydrate triaxial testing system (ETAS), twelve sets of triaxial shear tests were conducted. The results highlight that increases in hydrate saturation and confining pressure significantly enhance GHBS’ strength and stiffness, with more pronounced volume expansion observed during shearing. These tests have elucidated the mechanical responses of GHBS. Subsequently, empirical formulas were developed to characterize their properties under varying conditions. Additionally, based on the experimental data, the micro-mechanisms of GHBS were analyzed, suggesting that hydrates notably contribute to the filling and cementing effects in GHBS, with these effects varying with changes in hydrate saturation and confining pressure. This study contributes to a deeper understanding of the fundamental mechanical properties of GHBS.
Assessing Peru’s Land Monitoring System Contributions towards Fulfilment of Its International Environmental Commitments
Authors: Boza Espinoza Tatiana Erika , Salinas Norma , Cosio Eric G. , Tito Richard , Nina-Quispe Alex , Roman-Cuesta Rosa María
Published: February 2024

Land use change (LUC) is recognized as one of the major drivers of the global loss of biodiversity and represents a major threat to ecosystems. Deforestation through LUC is mainly driven by fire regimes, logging, farming (cropping and ranching), and illegal mining, which are closely linked with environmental management policies. Efficient land management strategies, however, require reliable and robust information. Land monitoring is one such approach that can provide critical information to coordinate policymaking at the global, regional, and local scales, and enable a programmed implementation of shared commitments under the Rio Conventions: the United Nations Convention on Biological Diversity (CBD), Convention to Combat Desertification (UNCCD), and Framework Convention on Climate Change (UNFCCC). Here we use Peru as a case study to evaluate how a land monitoring system enables environmental policy decisions which appear in the country’s international commitment reports. Specifically, we synthesize how effective the ongoing land monitoring system has been in responding to current and future environmental challenges; and how improvements in land monitoring can assist in the achievement of national commitments under the Rio Conventions. We find that Peruvian policies and commitments need to be improved to be consistent with the 1.5 °C temperature limit of the Paris agreement. Regarding the Aichi targets, Peru has achieved 17% land area with sustainable management; however, the funding deficit is a great challenge. Even though Peru commits to reducing GHG emissions by reducing LUC and improving agricultural and land use forestry practices, it needs policy improvements in relation to land tenure, governance, and equity. Potential explanations for the observed shortcomings include the fragmentation and duplication of government roles across sectors at both a national and regional scale.
Localization and Mapping for Self-Driving Vehicles: A Survey
Authors: Charroud Anas , El Moutaouakil Karim , Palade Vasile , Yahyaouy Ali , Onyekpe Uche , Eyo Eyo U.
Published: February 2024

The upsurge of autonomous vehicles in the automobile industry will lead to better driving experiences while also enabling the users to solve challenging navigation problems. Reaching such capabilities will require significant technological attention and the flawless execution of various complex tasks, one of which is ensuring robust localization and mapping. Recent surveys have not provided a meaningful and comprehensive description of the current approaches in this field. Accordingly, this review is intended to provide adequate coverage of the problems affecting autonomous vehicles in this area, by examining the most recent methods for mapping and localization as well as related feature extraction and data security problems. First, a discussion of the contemporary methods of extracting relevant features from equipped sensors and their categorization as semantic, non-semantic, and deep learning methods is presented. We conclude that representativeness, low cost, and accessibility are crucial constraints in the choice of the methods to be adopted for localization and mapping tasks. Second, the survey focuses on methods to build a vehicle’s environment map, considering both the commercial and the academic solutions available. The analysis proposes a difference between two types of environment, known and unknown, and develops solutions in each case. Third, the survey explores different approaches to vehicle localization and also classifies them according to their mathematical characteristics and priorities. Each section concludes by presenting the related challenges and some future directions. The article also highlights the security problems likely to be encountered in self-driving vehicles, with an assessment of possible defense mechanisms that could prevent security attacks in vehicles. Finally, the article ends with a debate on the potential impacts of autonomous driving, spanning energy consumption and emission reduction, sound and light pollution, integration into smart cities, infrastructure optimization, and software refinement. This thorough investigation aims to foster a comprehensive understanding of the diverse implications of autonomous driving across various domains.
A Dual Fusion Pipeline to Discover Tactical Knowledge Guided by Implicit Graph Representation Learning
Authors: Wang Xiaodong , He Pei , Yao Hongjing , Shi Xiangnan , Wang Jiwei , Guo Yangming
Published: February 2024

Discovering tactical knowledge aims to extract tactical data derived from battlefield signal data, which is vital in information warfare. The learning and reasoning from battlefield signal information can help commanders make effective decisions. However, traditional methods are limited in capturing sequential and global representation due to their reliance on prior knowledge or feature engineering. The current models based on deep learning focus on extracting implicit behavioral characteristics from combat process data, overlooking the embedded martial knowledge within the recognition of combat intentions. In this work, we fill the above challenge by proposing a dual fusion pipeline introducing graph representation learning into sequence learning to construct tactical behavior sequence graphs expressing implicit martial knowledge, named TBGCN. Specifically, the TBGCN utilizes graph representation learning to represent prior knowledge by building a graph to induce deep learning paradigms, and sequence learning finds the hidden representation from the target’s serialized data. Then, we employ a fusion module to merge two such representations. The significance of integrating graphs with deep learning lies in using the artificial experience of implicit graph structure guiding adaptive learning, which can improve representation ability and model generalization. Extensive experimental results demonstrate that the proposed TBGCN can effectively discover tactical knowledge and significantly outperform the traditional and deep learning methods.
A Bilevel DEA Model for Efficiency Evaluation and Target Setting with Stochastic Conditions
Authors: Georgiou Andreas C. , Kaparis Konstantinos , Vretta Eleni-Maria , Bitsis Kyriakos , Paltayian George
Published: February 2024

The effective allocation of limited resources and the establishment of targeted goals play a pivotal role in enhancing the overall efficiency of large enterprises and organizations. To achieve optimal organizational efficiency, managers seek dynamic strategies that adapt to the constraints of limited and uncertain historical data. This paper introduces an evaluation of organizational efficiency through a stochastic framework, employing a bilevel data envelopment analysis (DEA) approach. This decision-making process is centralized within a decision-making unit (DMU) overseeing subordinate decision-making units (subDMUs). Discrete scenarios, each associated with a realization probability, define the uncertain parameters in the bilevel DEA-based model. This stochastic approach allows for recourse actions upon scenario realization leading to an enhanced overall organizational strategy. Decision-makers acting within uncertain and dynamic environments can benefit from this research since it allows the investigation of efficiency assessment under alternative scenarios in the presence of volatility and risk. The potential impact of applying this methodology varies depending on the specific domain. Although, the context of this paper focuses on banking, in general, enhancing resource allocation and target setting under stochasticity, contributes to advancing sustainability across all its three dimensions (economic, environmental, social). As mentioned earlier, the practical application of our approach is demonstrated via a case study in the banking sector.