bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis of the Effect of Various Potential Antimicrobial Agents on the Quality of the Unpasteurized Carrot Juice
Authors: Ratajczak Katarzyna , Piotrowska-Cyplik Agnieszka , Cyplik Paweł
Published: August 2023

Short shelf-life and poor microbial quality of minimally processed foods of plant origin pose a serious problem for the food industry. Novel techniques of minimal treatment combined with disinfection are being researched, and, for fresh juice, the addition of antimicrobial agents appears to be a promising route. In this research, fresh, nonfiltered, unpasteurized carrot juice was mixed with four potential antimicrobials (bourbon vanilla extract, peppermint extract, cannabidiol oil, and grapefruit extract). All four variants and the reference pure carrot juice were analyzed for metapopulational changes, microbial changes, and physicochemical changes. The potential antimicrobials used in the research have improved the overall microbial quality of carrot juice across 4 days of storage. However, it is important to notice that each of the four agents had a different spectrum of effectiveness towards the groups identified in the microflora of carrot juice. Additionally, the antimicrobials have increased the diversity of the carrot juice microbiome but did not prevent the occurrence of pathogenic bacteria. In conclusion, the use of antimicrobial agents such as essential oils or their derivatives may be a promising way of improving the microbial quality and prolonging the shelf-life of minimally processed foods, such as fresh juices, but the technique requires further research.
Sensitive Detection of Various Forms of Hydrogen Sulfide via Highly Selective Naphthalimide-Based Fluorescent Probe
Authors: Słowiński Daniel , Świerczyńska Małgorzata , Romański Jarosław , Podsiadły Radosław
Published: August 2023

Hydrogen sulfide (H2S) is an important gasotransmitter, but only a few methods are available for real-time detection. Fluorescent probes are attractive tools for biological applications because of their high sensitivity, convenience, rapid implementation, noninvasive monitoring capability, and simplicity in fluorescent imaging of living cells and tissues. Herein, we report on a pro-fluorescent probe, NAP-Py-N3 based on naphthalimide derivative, which was found to show high selectivity toward H2S over various other analytes, including biothiols, making it feasible to detect H2S. After reaction with H2S, this probe showed rapid and significant turn-on green fluorescent enhancement at 553 nm (about 54-fold, k2 = 9.62 M−1s−1), high sensitivity (LOD: 15.5 nM), significant Stokes shift (118 nm), and it was found that the fluorescence quantum yield of fluorescence product can reach 0.36. Moreover, the probe has also been successfully applied to detect the gaseous H2S and to confirm the presence of H2S released from modern organic donors, which in recent years have been commonly used to investigate the role of H2S in biological systems. All the results indicate that this probe is excellent and highly valuable.
Influence of Block-Copolymers’ Composition as Compatibilizers for Epoxy/Silicone Blends
Authors: Delaite Christelle , Bistac Sophie , Rusu Daniela
Published: August 2023

The objective of this study was to prepare crosslinked epoxy networks containing liquid silicone particles in order to improve their mechanical properties and obtain less brittle materials. Different copolymers were used as compatibilizers. These copolymers vary in their chemical composition and structure. All of the copolymers contain hydrophobic (PDMS sequences) and hydrophilic groups. The effect of their chemical structure and architecture on the morphology of the dispersed phase, and on the final physico-chemical and flexural characteristics of epoxy/silicone blends, was explored. The morphology of crosslinked formulations was studied by scanning electron microscopy (SEM), and the thermal characteristics (glass transition temperature, Tg, and curing exothermic peak) were determined by differential scanning calorimetry (DSC). The experimental results have shown that the average diameter and particle size distribution of silicone particles depend on the chemical structure and architecture of the compatibilizers. One copolymer has been identified as the best compatibilizer, allowing a lower mean diameter and particle size distribution in addition to the best mechanical properties of the final network (less brittle character). This study has consequently evidenced the possibility of creating in situ silicone capsules inside an epoxy network by adding tailored compatibilizers to epoxy/silicone formulations.
Comparative Analysis of Secondary Metabolites in Diplodia corticola Strains with Different Virulence Degrees Associated with Canker and Dieback of Quercus spp.
Authors: Salvatore Maria Michela , Russo Maria Teresa , Nicoletti Rosario , Mahamedi Alla Eddine , Berraf-Tebbal Akila , Cimmino Alessio , Masi Marco , Andolfi Anna
Published: August 2023

Diplodia corticola is one of the most aggressive fungal pathogens of Quercus species involved in the decline of Mediterranean oak forests. In this study, three strains of D. corticola associated with holm (Quercus ilex) and cork (Quercus suber) oak trees exhibiting dieback symptoms and cankers in Algeria were selected to investigate the production of secondary metabolites. Metabolomic analyses revealed the production of several known compounds, such as sphaeropsidins, diplopyrones and diplofuranones. Moreover, the comparative investigation of secondary metabolites produced by the analyzed strains with different degrees of virulence revealed possible implications of these compounds in the fungal virulence. In particular, sphaeropsidins seem to be the main phytotoxic compounds of D. corticola involved in the infections of Quercus species, with a possible synergistic influence of the less representative compounds in the fungal virulence.
Removal of Methylene Blue and Methyl Red from Aqueous Solutions Using Activated Carbons Obtained by Chemical Activation of Caraway Seed
Authors: Paluch Dorota , Bazan-Wozniak Aleksandra , Nosal-Wiercińska Agnieszka , Pietrzak Robert
Published: August 2023

In this study, activated carbons were produced through the chemical activation of caraway seeds using three different activators: Na2CO3, K2CO3, and H3PO4. A 1:2 weight ratio of precursor to activator was maintained in every instance. Comprehensive analyses were conducted on the resultant activated carbons, including elemental analysis, textural parameters determination, Boehm titration for surface oxygen functional groups, pH assessment of aqueous extracts, and quantification of ash content. The produced materials were subjected to adsorption tests for methylene blue and methyl red sodium salt from the liquid phase and the effects of adsorbent dosage, pH of the aqueous dye solution, process temperature, and adsorbent–adsorbate contact time on sorption capacity obtained. To characterize the adsorption model of the examined pollutants, both the Langmuir and Freundlich equations were employed. In addition, the sorption capacity of the obtained carbon materials against an iodine aqueous solution was assessed. The specific surface area of the obtained adsorbents ranged from 269 to 926 m2/g. By employing potassium carbonate to chemically activate the starting substance, the resulting activated carbons show the highest level of specific surface area development and the greatest sorption capacity against the tested impurities—296 mg/g for methylene blue and 208 mg/g for methyl red sodium salt. The adsorption rate for both dyes was determined to align with a pseudo-second-order kinetic model. The experimental adsorption data for methylene blue were well-described by the Langmuir model, whereas the Freundlich model was found to be congruent with the data pertaining to methyl red sodium salt.
Dynamic Instrumental and Sensory Methods Used to Link Aroma Release and Aroma Perception: A Review
Authors: Le Quéré Jean-Luc , Schoumacker Rachel
Published: August 2023

Perception of flavor is a dynamic process during which the concentration of aroma molecules at the olfactory epithelium varies with time as they are released progressively from the food in the mouth during consumption. The release kinetics depends on the food matrix itself but also on food oral processing, such as mastication behavior and food bolus formation with saliva, for which huge inter-individual variations exist due to physiological differences. Sensory methods such as time intensity (TI) or the more-recent methods temporal dominance of sensations (TDS) and temporal check-all-that-apply (TCATA) are used to account for the dynamic and time-related aspects of flavor perception. Direct injection mass spectrometry (DIMS) techniques that measure in real time aroma compounds directly in the nose (nosespace), aimed at obtaining data that reflect the pattern of aroma release in real time during food consumption and supposed to be representative of perception, have been developed over the last 25 years. Examples obtained with MS operated in chemical ionization mode at atmospheric or sub-atmospheric pressure (atmospheric pressure chemical ionization APCI or proton-transfer reaction PTR) are given, with emphases on studies conducted with simultaneous dynamic sensory evaluation. Inter-individual variations in terms of aroma release and their relevance for understanding flavor perception are discussed as well as the evidenced cross-modal interactions.
The Nighttime Fragrance of Guettarda scabra (Rubiaceae): Flower Scent and Its Implications for Moth Pollination
Authors: Pimienta María Cleopatra , Salazar Diego , Koptur Suzanne
Published: August 2023

Floral scent is crucial for attracting pollinators, especially in plants that bloom at night. However, chemical profiles of flowers from nocturnal plants with varied floral morphs are poorly documented, limiting our understanding of their pollination ecology. We investigated the floral scent in Guettarda scabra (L.) Vent. (Rubiaceae), a night-blooming species with short- and long-styled floral morphs, found in the threatened pine rocklands in south Florida, US. By using dynamic headspace sampling and GC–MS analysis, we characterized the chemical profiles of the floral scent in both morphs. Neutral red staining was also employed to determine the specific floral regions responsible for scent emission in G. scabra. The results revealed that G. scabra’s fragrance consists entirely of benzenoid and terpenoid compounds, with benzeneacetaldehyde and (E)-β-ocimene as dominant components. There were no differences in the chemical profiles between the long- and short-styled flowers. Staining assays indicated that the corolla lobes, anthers, and stigma were the primary sources of the scent. These findings indicate that G. scabra’s floral scent is consistent with that of night-blooming plants pollinated by nocturnal hawkmoths, providing important insights into its chemical ecology and pollinator attraction. This study demonstrates how floral scent chemistry can validate predictions based on flower morphology in hawkmoth-pollinated plants.
Modified Rice Bran Arabinoxylan by Lentinus edodes Mycelial Enzyme as an Immunoceutical for Health and Aging—A Comprehensive Literature Review
Authors: Ooi Soo Liang , Micalos Peter S. , Pak Sok Cheon
Published: August 2023

Rice bran arabinoxylan compound (RBAC) is derived from defatted rice bran enzymatically treated with Lentinus edodes mycelium. This review explores biologically active compounds and mechanisms of action that support RBAC as an immunomodulating nutraceutical in generally healthy and/or aging individuals. Thirty-seven (n = 37) primary research articles fulfilled the selection criteria for review. Most research is based on Biobran MGN-3, which consists of complex heteropolysaccharides with arabinoxylan as its primary structure while also containing galactan and glucan. RBAC was found to invoke immunological activities through direct absorption via the digestive tract and interaction with immune cells at the Peyer’s patches. RBAC was shown to promote innate defence by upregulating macrophage phagocytosis and enhancing natural killer cell activity while lowering oxidative stress. Through induction of dendritic cell maturation, RBAC also augments adaptive immunity by promoting T and B lymphocyte proliferation. RBAC acts as an immunomodulator by inhibiting mast cell degranulation during allergic reactions, attenuating inflammation, and downregulating angiogenesis by modulating cytokines and growth factors. RBAC has been shown to be a safe and effective nutraceutical for improving immune health, notably in aging individuals with reduced immune function. Human clinical trials with geriatric participants have demonstrated RBAC to have prophylactic benefits against viral infection and may improve their quality of life. Further research should explore RBAC’s bioavailability, pharmacodynamics, and pharmacokinetics of the complex heteropolysaccharides within. Translational research to assess RBAC as a nutraceutical for the aging population is still required, particularly in human studies with larger sample sizes and cohort studies with long follow-up periods.
Evaluating the Aphrodisiac Potential of Mirabilis jalapa L. Root Extract: Phytochemical Profiling and In Silico, In Vitro, and In Vivo Assessments in Normal Male Rats
Authors: Rahman Asad Ur , Alam Fiaz , Khan Muhammad , Sarfraz Muhammad , Basit Abdul , Ahmad Tawseef , Khokhar Muhammad Ali , Ali Sayyad , Khan Kifayat Ullah
Published: August 2023

The traditional use of Mirabilis jalapa L. roots to enhance male sexual performance prompted us to assess the in silico, in vitro, and in vivo aphrodisiac activities of its hydroethanolic extract using normal male rats. Spectroscopic characterization indicated the presence of ß-D-glucopyranoside, methyl-1,9-benzyl-2,6-dichloro-9H-purine, and Bis-(2-ethylhexyl)-phthalate; these compounds have a significant inhibitory effect on the phosphodiesterase-5 (PDE-5) enzyme in silico evaluation and minerals (including zinc, cadmium, and magnesium). Other phytochemical analyses revealed the presence of phenolic compounds and flavonoids. These phytochemicals and minerals may contribute to the aphrodisiac activities of the extract. Additionally, the in vivo study revealed that the administration of M. jalapa root extract (300 mg/kg) significantly enhanced (p < 0.01, p < 0.03) mount, intromission, and ejaculation frequencies while significantly (p < 0.05) decreasing the mount and intromission latencies, as well as the post-ejaculatory interval time, in comparison with the standard drugs sildenafil and ginseng, resulting in enhanced erection and sexual performance in the rats. Furthermore, the extract significantly (p < 0.05) increased penile reflexes and also elevated the levels of testosterone and luteinizing hormones. Extract (300 mg/kg) significantly (p < 0.05) inhibited the PDE-5 enzyme in an in vitro study. Concludingly, the comprehensive findings of this study suggest that a standardized herbal extract derived from M. jalapa roots alleviates erectile dysfunction and premature ejaculation in male rats. M. jalapa root extract proved to be an alternative treatment for erectile dysfunction and premature ejaculation.
A Chitosan-Based Fluorescent Probe Combined with Smartphone Technology for the Detection of Hypochlorite in Pure Water
Authors: Yuan Xushuo , Zhang Wenli , Liu Li , Lin Yanfei , Xie Linkun , Chai Xijuan , Xu Kaimeng , Du Guanben , Zhang Lianpeng
Published: August 2023

Using chitosan as a raw material, 1,8-naphthimide as the fluorescent chromophore, and sulfur-containing compounds as the recognition groups, a novel naphthimide-functionalized chitosan probe, CS-BNS, for the detection of ClO− was successfully synthesized. The modification of chitosan was verified by SEM, XRD, FTIR, mapping, 13C-NMR, TG and the structure of the probe molecule was characterized. The identification performance of the probes was studied using UV and fluorescence spectrophotometers. The results show that CS-BNS exhibits a specific response to ClO− based on the oxidative reaction of ClO− to the recognition motifs, as well as a good resistance to interference. And the probe has high sensitivity and fast response time, and can complete the detection of ClO− in a pure water system within 60 s. The probe can also quantify ClO− (y = 30.698x + 532.37, R2 = 0.9833) with a detection limit as low as 0.27 μM. In addition, the combination of the probe with smartphone technology enables the visualization and real-time monitoring of ClO−. Moreover, an identification system for ClO− was established by combining the probe with smartphone technology, which realized the visualization and real-time monitoring of ClO−.
Attenuation of Aging-Related Oxidative Stress Pathways by Phytonutrients: A Computational Systems Biology Analysis
Authors: Ayyadurai V. A. Shiva , Deonikar Prabhakar
Published: August 2023

Aging results from gradual accumulation of damage to the cellular functions caused by biochemical processes such as oxidative stress, inflammation-driven prolonged cellular senescence state, immune system malfunction, psychological stress, and epigenetic changes due to exposure to environmental toxins. Plant-derived bioactive molecules have been shown to ameliorate the damage from oxidative stress. This research seeks to uncover the mechanisms of action of how phytochemicals from fruit/berry/vegetable (FBV) juice powder mitigate oxidative stress. The study uses a computational systems biology approach to (1) identify biomolecular pathways of oxidative stress; (2) identify phytochemicals from FBV juice powder and their specific action on oxidative stress mechanisms; and (3) quantitatively estimate the effects of FBV juice powder bioactive compounds on oxidative stress. The compounds in FBV affected two oxidative stress molecular pathways: (1) reactive oxygen species (ROS) production and (2) antioxidant enzyme production. Six bioactive compounds including cyanidin, delphinidin, ellagic acid, kaempherol, malvidin, and rutin in FBV significantly lowered production of ROS and increased the production of antioxidant enzymes such as catalase, heme oxygenase-1, superoxide dismutase, and glutathione peroxidase. FBV juice powder provides a combination of bioactive compounds that attenuate aging by affecting multiple pathways of oxidative stress.
Molecular Epidemiology and Genetic Diversity of Human Respiratory Syncytial Virus in Sicily during Pre- and Post-COVID-19 Surveillance Seasons
Authors: Tramuto Fabio , Maida Carmelo Massimo , Mazzucco Walter , Costantino Claudio , Amodio Emanuele , Sferlazza Giuseppe , Previti Adriana , Immordino Palmira , Vitale Francesco
Published: August 2023

Human respiratory syncytial virus (hRSV) is an important pathogen of acute respiratory tract infection of global significance. In this study, we investigated the molecular epidemiology and the genetic variability of hRSV over seven surveillance seasons between 2015 and 2023 in Sicily, Italy. hRSV subgroups co-circulated through every season, although hRSV-B mostly prevailed. After the considerable reduction in the circulation of hRSV due to the widespread implementation of non-pharmaceutical preventive measures during the COVID-19 pandemic, hRSV rapidly re-emerged at a high intensity in 2022–2023. The G gene was sequenced for genotyping and analysis of deduced amino acids. A total of 128 hRSV-A and 179 hRSV-B G gene sequences were obtained. The phylogenetic analysis revealed that the GA2.3.5a (ON1) and GB5.0.5a (BA9) genotypes were responsible for the hRSV epidemics in Sicily.; only one strain belonged to the genotype GB5.0.4a. No differences were observed in the circulating genotypes during pre- and post-pandemic years. Amino acid sequence alignment revealed the continuous evolution of the G gene, with a combination of amino acid changes specifically appearing in 2022–2023. The predicted N-glycosylation sites were relatively conserved in ON1 and BA9 genotype strains. Our findings augment the understanding and prediction of the seasonal evolution of hRSV at the local level and its implication in the monitoring of novel variants worth considering in better design of candidate vaccines.
Regional Differences in Intestinal Parasitic Infections among Army Recruits in a Southern Mozambique Training Center: A Cross-Sectional Study
Authors: Casmo Verónica , Chicumbe Sérgio , Chambisse Rosa , Nalá Rassul
Published: August 2023

Due to the high prevalence and diversity of clinical manifestations, intestinal parasitic infections (IPIs) represent a public health problem. The objective of the work was to determine the prevalence of IPIs among army recruits at a practice and training center in southern Mozambique. Sociodemographic information was obtained through semi-structured interviews. Single urine and stool samples were collected from 362 recruits. Parasite diagnosis was made by filtration, formaldehyde-ether and Kato-Katz techniques. Positive individuals underwent abdominal ultrasound. Then, descriptive statistics and cross-tabulations were performed, and p-values < 0.05 were considered significant. The prevalence of infection with at least one parasite was 25.1% (95% CI: 20.5–29.6; n = 91). The most common parasites were Entamoeba coli (10.7%; 95% CI: 7.4–13.7; n = 37) and Trichuris trichiura (6.1%; 95% CI: 4.6–9.9; n = 25). Parasitic infection was associated with the origin of the participant (p-value < 0.001), and the province of Sofala had the highest prevalence among the provinces studied (70.6%; 95% CI: 47.0–87.8; 12/17). Since oral fecal transmission occurs for several parasites, routine screening and deworming prior to enrollment at the army training center is recommended to reduce transmission of intestinal parasites among recruits.
Linum usitatissimum AccD Enhances Seed Fatty Acid Accumulation and Tolerance to Environmental Stresses during Seed Germination in Arabidopsis thaliana
Authors: Du Rui , Li Xinye , Hu Huan , Zhao Yu , Chen Mingxun , Liu Zijin
Published: August 2023

Flax (Linum usitatissimum L.), as an important oil-producing crop, is widely distributed throughout the world, and its seeds are rich in polyunsaturated fatty acids (FAs). Previous studies have revealed that Arabidopsis thaliana ACETYL-CoA CARBOXYLASE (AtACCase) is vital for FA biosynthesis. However, the functions of L. usitatissimum AccD (LuAccD) on FA accumulation and seed germination remain unclear. In the present study, we cloned the LuAccD coding sequence from the flax cultivar ‘Longya 10’, identified conserved protein domains, and performed a phylogenetic analysis to elucidate its relationship with homologs from a range of plant species. Ectopic expression of LuAccD in A. thaliana wild-type background enhanced seed FA accumulation without altering seed morphological characteristics, including seed size, 1000-seed weight, and seed coat color. Consistently, the expression of key genes involved in FA biosynthesis was greatly up-regulated in the developing seeds of LuAccD overexpression lines. Additionally, we demonstrated that LuAccD acts as a positive regulator of salt and mannitol tolerance during seed germination in A. thaliana. These results provide important insights into the functions of LuAccD, which facilitates the oil quantity and abiotic stress tolerance of oil-producing crops through genetic manipulation.
Pump-Controlled AGC Micro-Displacement Position Control of Lithium Battery Pole Strip Mill Based on Friction Model
Authors: Wang Kai , Chen Gexin , Zhang Tiangui
Published: August 2023

Electrode roll-forming refers to rolling a battery electrode into a preset thickness through the electro-hydraulic servo pump-controlled hydraulic roll gap thickness automatic control system (known to as pump-controlled AGC). Compared with the motor servo system, the friction problem of the electro-hydraulic servo system is more serious and the friction problem of the actuator itself is very prominent. Moreover, low-speed performance is one of its core indicators, the friction phenomenon is the most abundant during the low-speed stage and the impact on the servo system is also the most obvious. Therefore, for high-performance electro-hydraulic servo control, friction compensation is not only unavoidable, but also a very difficult problem. Aiming to influence the friction on the position control of the pump-controlled system of a lithium battery pole strip mill, the rolling mechanism and process procedure under micro-displacement position control based on the friction model were studied and compared from the perspective of considering friction factors, and a friction compensation controller based on the LuGre model was designed. The control precision of a pump-controlled AGC system was improved through combination with an adaptive robust controller. Because of the diversity of unmeasurable states of the system, a dual observer was designed, and the known model of the system was added to the observer. In the final comparative experiment, the steady-state accuracy of the friction adaptive robust compensation controller system based on the LuGre model reached ±0.3 μm, which is superior to the fuzzy IMC compensation and traditional PID control strategies.
Evaluation of Potential Factors Affecting Steel Slag Carbonation
Authors: Baras Amer , Li Jiajie , Ni Wen , Hussain Zahid , Hitch Michael
Published: August 2023

Steel slag is a solid waste product generated during the carbonation stage of steelmaking. It has high levels of heavy metals and substantial amounts of free calcium and magnesium oxide, making it unsuitable for use as a cement material. Furthermore, the disposal of steel slag in landfills requires many resources and can seriously contaminate the surrounding environment. One method of reducing its negative environmental impact is carbonation, which involves reacting steel slag with carbon dioxide to form stable minerals. However, many parameters influence the carbonation efficiency of steelmaking slag, including temperature, time, particle size, pressure, CO2 concentration, liquid-to-solid ratio, moisture content, humidity, additives, etc. To this end, this paper comprehensively reviews the most important steel slag carbonation-influencing factors. Moreover, it compares the characteristics from two perspectives based on their causes and effects on carbonation. Finally, this article reviews earlier studies to identify the factors that affect steel slag carbonation and the potential of carbonated steel slag as a sustainable construction material. Based on previous research, it systematically examines all the elements for future work that need to be improved.
Religious Materiality and Virtual Sainthood: The Case of Shna Ndou (St. Anthony) Pilgrimage in Laç
Authors: Bria Gianfranco , Giorda Maria Chiara
Published: August 2023

The interdisciplinary perspective, between history and anthropology, of our contribution has as its subject the pilgrimage at Kisha e Shna Ndout (Sanctuary of St. Anthony of Padua) in Laç, northern Albania, which is one of the most visited religious sites in southeastern Europe. The church, built there and ministered by Franciscans, is now an impressive place of worship frequented throughout the year by thousands of pilgrims. On the 12th and 13th of June of each year, an official pilgrimage is held, which reaches its climax on the night of the 12th, when thousands of Albanians sleep in the shrine seeking blessings and healing. The pilgrimage practices show how materiality is a privileged means of reaching out to a religious place. This materiality is grounded in the multilayered built environment, which has been built and rebuilt and especially reconstructed after the collapse of the socialist regime—a process that reveals the pivotal function of secular infrastructures in the case of religious places. Virtuality is also an important aspect of the pilgrimage, and so materiality and virtuality form a single milieu that reshapes perceptions. Through participation in this pilgrimage, virtuality is sacralized and promotes sanctity.
Pricing Pandemic Bonds under Hull–White & Stochastic Logistic Growth Model
Authors: Manathunga Vajira , Deng Linmiao
Published: August 2023

Pandemic bonds can be used as an effective tool to mitigate the economic losses that governments face during pandemics and transfer them to the global capital market. Once considered as an “uninsurable” event, pandemic bonds caught the attention of the world with the issuance of pandemic bonds by the World Bank in 2017. Compared to other CAT bonds, pandemic bonds received less attention from actuaries, industry professionals, and academic researchers. Existing research focused mainly on how to bring epidemiological parameters to the pricing mechanism through compartmental models. In this study, we introduce the stochastic logistic growth model-based pandemic bond pricing framework. We demonstrate the proposed model with two numerical examples. First, we calculate what investor is willing to pay for the World Bank issued pandemic bond while accounting for possible future pandemic, but require to have the same yield to maturity when no pandemic is there, and without using COVID-19 data. In the second example, we calculate the fair value of a pandemic bond with characteristics similar to the World Bank issued pandemic bond, but using COVID-19 data. The model can be used as an alternative to epidemic compartmental model-based pandemic bond pricing mechanisms.
Improving the Accuracy of Random Forest Classifier for Identifying Burned Areas in the Tangier-Tetouan-Al Hoceima Region Using Google Earth Engine
Authors: Badda Houda , Cherif El Khalil , Boulaassal Hakim , Wahbi Miriam , Yazidi Alaoui Otmane , Maatouk Mustapha , Bernardino Alexandre , Coren Franco , El Kharki Omar
Published: August 2023

Forest fires have become a major concern in the northern parts of Morocco, particularly in the Tangier-Tetouan-Al Hoceima (TTA) region, causing significant damage to the environment and human lives. To address this pressing issue, this study proposes an approach that utilizes remote sensing (RS) and machine learning (ML) techniques to detect burned areas in the TTA region within the Google Earth Engine platform. The study focuses on burned areas resulting from forest fires in three specific locations in the TTA region that have experienced such fires in recent years, namely Tangier-Assilah in 2017, M’diq Fnideq in 2020, and Chefchaouen in 2021. In our study, we extensively explored multiple combinations of spectral indices, such as normalized burn ratio (dNBR), normalized difference vegetation index (dNDVI), soil-adjusted vegetation index (dSAVI), and burned area index (dBAI), in conjunction with Sentinel-2 (S2) satellite images. These combinations were employed within the Random Forest (RF) algorithm, allowing us to draw important conclusions. Initially, we assess the individual effectiveness of the dNBR index, which yields accuracy rates of 83%, 90%, and 82% for Tangier-Assilah, Chefchaouen, and M’diq Fnideq, respectively. Recognizing the need for improved outcomes, we expand our analysis by incorporating spectral indices and S2 bands. However, the results obtained from this expanded combination lack consistency and stability across different locations. While Tangier-Assilah and M’diq Fnideq experience accuracy improvements, reaching 95% and 88%, respectively, the inclusion of Sentinel bands has an adverse effect on Chefchaouen, resulting in a decreased accuracy of 87%. To achieve optimal accuracy, our focus shifted towards the combination of dNBR and the other spectral indices. The results were truly remarkable, with accuracy rates of 96%, 97%, and 97% achieved for Tangier-Assilah, Chefchaouen, and M’diq Fnideq, respectively. Our decision to prioritize the spectral indices was based on the feature importance method, which highlights the significance of each feature in the classification process. The practical implications of our study extend to fire management and prevention in the TTA region. The insights gained from our analysis can inform the development of effective policies and strategies to mitigate the impact of forest fires. By harnessing the potential of RS and ML techniques, along with the utilization of spectral indices, we pave the way for enhanced fire monitoring and response capabilities in the region.
A Coherent Integration and Parameter Estimation Method for Constant Radial Acceleration Weak Target via SOKT-IAR-LVD
Authors: Zhang Renli , Xu Nan
Published: August 2023

In order to enhance the detection and parameter estimation capacity to the maneuvering target with complex motions, a low complexity coherent integration and parameter estimation method named SOKT-IAR-LVD is proposed in this paper. In SOKT-IAR-LVD, first, the second-order keystone transform (SOKT) is utilized to eliminate the range curvature induced by target acceleration. Second, improved axis rotation (IAR) is applied to regulate the linear range migration by rotating the fast time axis and the target envelope is aligned along the slow time axis with a quadratic phase characteristic. At last, the target signal is coherently integrated via the Lv’s Distribution (LVD) transform. The target motion parameters, including range, velocity, and acceleration, are estimated by the IAR and LVD results. The integration gain and computational load of SOKT-IAR-LVD are analyzed. Without needing to estimate the Doppler ambiguity number and target acceleration, the computational burden of SOKT-IAR-LVD is three orders of magnitude lower than that of the Radon-Lv’s Distribution (RLVD) method. Simulation results demonstrate that the detection performance of SOKT-IAR-LVD is almost the same as that of RLVD and that the required input SNR of SOKT-IAR-LVD is 17.4 dB lower than that of SOKT–Radon Fourier transform (SOKT-RFT) when the detection threshold is set to 12 dB.
Glacier Change in the West Kunlun Main Peak Area from 2000 to 2020
Authors: Zhang Cong , Yao Xiaojun , Li Suju , Liu Longfei , Sha Te , Zhang Yuan
Published: August 2023

Glaciers are sensitive indicators of climate change, and investigation of their dynamics is crucial for ensuring regional ecological security as well as disaster prevention and mitigation measures. Based on Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper Plus (ETM+)/Operational Land Imager (OLI) imagery, the outlines and length of glaciers in the West Kunlun Main Peak Area (WKMPA) during 2000–2020 were obtained by combining a band ratio method with manual interpretation and an automatic extraction method for the glacier centerline, respectively. There were 440 glaciers in the WKMPA in 2020, covering an area of 2964.59 ± 54.87 km2, with an average length of 2916 ± 60 m. The glacier count increased due to division, while the area and length all exhibited a declining trend from 2000 to 2020, at rates of −0.04%·a−1 (24.83 km2) and −0.11%·a−1 (66 m), respectively. Glacier retreat was primarily observed during the early period (2000–2005). Except for glaciers located above an elevation of 6250 m, the glacier area decreased with each altitude interval from 2000 to 2020, and the rate of relative change in glacier area generally decreased with increasing altitude. Moreover, except for a slight increase in north-facing glaciers, the area of glaciers facing other orientations decreased during 2000–2020. The accuracy of the empirical formula fit for glacier length was highly dependent on glacier class, with greater precision observed for smaller glaciers and lower precision for larger valley-basin glaciers due to their complex morphological structures being neglected and only a single quantitative relationship being considered. There was a time lag of 12 years between temperature changes and glacier area response in this region. The mechanism by which glacier division affects glacier change is complex, requiring dissection of multiple factors such as area, length, and terminal elevation before and after division.
An Integrated Framework for Remote Sensing Assessment of the Trophic State of Large Lakes
Authors: Meng Dinghua , Mao Jingqiao , Li Weifeng , Zhu Shijie , Gao Huan
Published: August 2023

The trophic state is an important factor reflecting the health state of lake ecosystems. To accurately assess the trophic state of large lakes, an integrated framework was developed by combining remote sensing data, field monitoring data, machine learning algorithms, and optimization algorithms. First, key meteorological and environmental factors from in situ monitoring were combined with remotely sensed reflectance data and statistical analysis was used to determine the main factors influencing the trophic state. Second, a trophic state index (TSI) inversion model was constructed using a machine learning algorithm, and this was then optimized using the sparrow search algorithm (SSA) based on a backpropagation neural network (BP-NN) to establish an SSA-BP-NN model. Third, a typical lake in China (Hongze Lake) was chosen as the case study. The application results show that, when the key environmental factors (pH, temperature, average wind speed, and sediment content) and the band combination data from Sentinel-2/MSI were used as input variables, the performance of the model was improved (R2 = 0.936, RMSE = 1.133, MAPE = 1.660%, MAD = 0.604). Compared with the performance prior to optimization (R2 = 0.834, RMSE = 1.790, MAPE = 2.679%, MAD = 1.030), the accuracy of the model was improved by 12.2%. It is worth noting that this framework could accurately identify water bodies in different trophic states. Finally, based on this framework, we mapped the spatial distribution of TSI in Hongze Lake in different seasons from 2019 to 2020 and analyzed its variation characteristics. The framework can combine regional special feature factors influenced by a complex environment with S-2/MSI data to achieve an assessment accuracy of over 90% for TSI in sensitive waters and has strong applicability and robustness.
Estimation of Coastal Wetland Soil Organic Carbon Content in Western Bohai Bay Using Remote Sensing, Climate, and Topographic Data
Authors: Zhang Yongbin , Kou Caiyao , Liu Mingyue , Man Weidong , Li Fuping , Lu Chunyan , Song Jingru , Song Tanglei , Zhang Qingwen , Li Xiang , Tian Di
Published: August 2023

Coastal wetland soil organic carbon (CW-SOC) is crucial for wetland ecosystem conservation and carbon cycling. The accurate prediction of CW-SOC content is significant for soil carbon sequestration. This study, which employed three machine learning (ML) methods, including random forest (RF), gradient boosting machine (GBM), and extreme gradient boosting (XGBoost), aimed to estimate CW-SOC content using 98 soil samples, SAR images, optical images, and climate and topographic data. Three statistical metrics and leave-one-out cross-validation were used to evaluate model performance. Optimal models using different ML methods were applied to predict the spatial distribution of CW-SOC content. The results showed the following: (1) The models built using optical images had higher predictive accuracy than models built using synthetic aperture radar (SAR) images. The model that combined SAR images, optical images, and climate data demonstrated the highest prediction accuracy. Compared to the model using only optical images and SAR images, the prediction accuracy was improved by 0.063 and 0.115, respectively. (2) Regardless of the combination of predictive variables, the XGBoost method achieved higher prediction accuracy than the RF and GBM methods. (3) Optical images were the main explanatory variables for predicting CW-SOC content, explaining more than 65% of the variability. (4) The CW-SOC content predicted by the three ML methods showed similar spatial distribution characteristics. The central part of the study area had higher CW-SOC content, while the southern and northern regions had lower levels. This study accurately predicted the spatial distribution of CW-SOC content, providing data support for ecological environmental protection and carbon neutrality of coastal wetlands.
CE-RX: A Collaborative Cloud-Edge Anomaly Detection Approach for Hyperspectral Images
Authors: Wang Yunchang , Cai Jiang , Zhou Junlong , Sun Jin , Xu Yang , Zhang Yi , Wei Zhihui , Plaza Javier , Plaza Antonio , Wu Zebin
Published: August 2023

Due to the constrained processing capabilities of real-time detection techniques in remote sensing applications, it is often difficult to obtain detection results with high accuracy in practice. To address this problem, we introduce a new real-time anomaly detection algorithm for hyperspectral images called cloud–edge RX (CE-RX). The algorithm combines the advantages of cloud and edge computing. During the data acquisition process, the edge performs real-time detection on the data just captured to obtain a coarse result and find the suspicious anomalies. At regular intervals, the suspicious anomalies are sent to the cloud for further detection with a highly accurate algorithm, then the cloud sends back the (high-accuracy) results to the edge for information updating. After receiving the results from the cloud, the edge updates the information of the detector in the real-time algorithm to improve the detection accuracy of the next acquired piece of data. Our experimental results demonstrate that the proposed cloud–edge collaborative algorithm can obtain more accurate results than existing real-time detection algorithms.
Remote Sensing Image Dehazing through an Unsupervised Generative Adversarial Network
Authors: Zhao Liquan , Yin Yanjiang , Zhong Tie , Jia Yanfei
Published: August 2023

The degradation of visual quality in remote sensing images caused by haze presents significant challenges in interpreting and extracting essential information. To effectively mitigate the impact of haze on image quality, we propose an unsupervised generative adversarial network specifically designed for remote sensing image dehazing. This network includes two generators with identical structures and two discriminators with identical structures. One generator is focused on image dehazing, while the other generates images with added haze. The two discriminators are responsible for distinguishing whether an image is real or generated. The generator, employing an encoder–decoder architecture, is designed based on the proposed multi-scale feature-extraction modules and attention modules. The proposed multi-scale feature-extraction module, comprising three distinct branches, aims to extract features with varying receptive fields. Each branch comprises dilated convolutions and attention modules. The proposed attention module includes both channel and spatial attention components. It guides the feature-extraction network to emphasize haze and texture within the remote sensing image. For enhanced generator performance, a multi-scale discriminator is also designed with three branches. Furthermore, an improved loss function is introduced by incorporating color-constancy loss into the conventional loss framework. In comparison to state-of-the-art methods, the proposed approach achieves the highest peak signal-to-noise ratio and structural similarity index metrics. These results convincingly demonstrate the superior performance of the proposed method in effectively removing haze from remote sensing images.
Real-Time Embedded Eye Image Defocus Estimation for Iris Biometrics
Authors: Ruiz-Beltrán Camilo A. , Romero-Garcés Adrián , González-García Martín , Marfil Rebeca , Bandera Antonio
Published: August 2023

One of the main challenges faced by iris recognition systems is to be able to work with people in motion, where the sensor is at an increasing distance (more than 1 m) from the person. The ultimate goal is to make the system less and less intrusive and require less cooperation from the person. When this scenario is implemented using a single static sensor, it will be necessary for the sensor to have a wide field of view and for the system to process a large number of frames per second (fps). In such a scenario, many of the captured eye images will not have adequate quality (contrast or resolution). This paper describes the implementation in an MPSoC (multiprocessor system-on-chip) of an eye image detection system that integrates, in the programmable logic (PL) part, a functional block to evaluate the level of defocus blur of the captured images. In this way, the system will be able to discard images that do not have the required focus quality in the subsequent processing steps. The proposals were successfully designed using Vitis High Level Synthesis (VHLS) and integrated into an eye detection framework capable of processing over 57 fps working with a 16 Mpixel sensor. Using, for validation, an extended version of the CASIA-Iris-distance V4 database, the experimental evaluation shows that the proposed framework is able to successfully discard unfocused eye images. But what is more relevant is that, in a real implementation, this proposal allows discarding up to 97% of out-of-focus eye images, which will not have to be processed by the segmentation and normalised iris pattern extraction blocks.
Negative Design Margin Realization through Deep Path Activity Detection Combined with Dynamic Voltage Scaling in a 55 nm Near-Threshold 32-Bit Microcontroller
Authors: Yu Run-Ze , Li Zhen-Hao , Deng Xi , Liu Zheng-Lin
Published: August 2023

This paper presents an innovative approach for predicting timing errors tailored to near-/sub-threshold operations, addressing the energy-efficient requirements of digital circuits in applications, such as IoT devices and wearables. The method involves assessing deep path activity within an adjustable window prior to the root clock’s rising edge. By dynamically adapting the prediction window and supply voltage based on error detection outcomes, the approach effectively mitigates false predictions—an essential concern in low-voltage prediction techniques. The efficacy of this strategy is demonstrated through its implementation in a near-/sub-threshold 32-bit microprocessor system. The approach incurs only a modest 6.84% area overhead attributed to well-engineered lightweight design methodologies. Furthermore, with the integration of clock gating, the system functions seamlessly across a voltage range of 0.4 V–1.2 V (5–100 MHz), effectively catering to adaptive energy efficiency. Empirical results highlight the potential of the proposed strategy, achieving a significant 46.95% energy reduction at the Minimum Energy Point (MEP, 15 MHz) compared to signoff margins. Additionally, a 19.75% energy decrease is observed compared to the zero-margin operation, demonstrating successful realization of negative margins.
Monitoring Distracted Driving Behaviours with Smartphones: An Extended Systematic Literature Review
Authors: Papatheocharous Efi , Kaiser Christian , Moser Johanna , Stocker Alexander
Published: August 2023

Driver behaviour monitoring is a broad area of research, with a variety of methods and approaches. Distraction from the use of electronic devices, such as smartphones for texting or talking on the phone, is one of the leading causes of vehicle accidents. With the increasing number of sensors available in vehicles, there is an abundance of data available to monitor driver behaviour, but it has only been available to vehicle manufacturers and, to a limited extent, through proprietary solutions. Recently, research and practice have shifted the paradigm to the use of smartphones for driver monitoring and have fuelled efforts to support driving safety. This systematic review paper extends a preliminary, previously carried out author-centric literature review on smartphone-based driver monitoring approaches using snowballing search methods to illustrate the opportunities in using smartphones for driver distraction detection. Specifically, the paper reviews smartphone-based approaches to distracted driving behaviour detection, the smartphone sensors and detection methods applied, and the results obtained.