bluuebunny/crossref_metadata_2025 huggingface dataset:
Influence of Inlets Morphology and Forcing Mechanisms on Water Exchange between Coastal Basins and the Sea: A Hindcast Study for a Mediterranean Lagoon
Authors: Simonetti Irene , Cappietti Lorenzo
Published: December 2022

A numerical model, validated with field measurements, was applied to comparatively reconstruct the hydrodynamics of a eutrophic coastal lagoon in a set of scenarios over the last two centuries. The effect of major morphological changes on the water exchange with the open sea and water residence time is evaluated. The results show that the number and morphology of the lagoon inlets are crucial in determining the volume of water exchanged with the sea, the water transport timescales, and the extent of poorly circulated stagnant areas with poor flushing potential, which are areas where anoxic crises might develop. When all the relevant forcing mechanisms on the hydrodynamics are considered, great variability of the water residence time is found in the different historical scenarios, with values varying between 83 and 305 days. The effect of anthropic actions on the system hydrodynamics was quantitatively evaluated, consolidating the background knowledge to support the present and future management of this environmental system.
Defense Strategy against False Data Injection Attacks in Ship DC Microgrids
Authors: Zeng Hong , Zhao Yuanhao , Wang Tianjian , Zhang Jundong
Published: December 2022

False Data Injection Attacks (FDIA) on ship Direct Current (DC) microgrids may result in the priority trip of a large load, a black-out, and serious accidents of ship collisions when maneuvering in the port. The key of the prevention of FDIA is the detection of and countermeasures to false data. In this paper, a defense strategy is developed to detect and mitigate against FDIA on ship DC microgrids. First, a DC bus voltage estimator is trained with an Artificial Neural Network (ANN) model. The error between the estimate value and the measure value is compared with a threshold generated from history data to detect the occurrence of FDIA. Combined with the correlation of artificial neural network inputs, bad data are identified and recovered. The method is tested under six cases with different network and physical disturbances in Matlab/Simulink. The results show that the method can identify and mitigate the FDIA effectively; the error of identifying FDIA by ANN is less than 0.5 V. Therefore, the deviation between the actual bus voltage and the reference voltage is less than 0.5 V.
Response of the Black Sea Zooplankton to the Marine Heat Wave 2010: Case of the Sevastopol Bay
Authors: Gubanova Alexandra , Goubanova Katerina , Krivenko Olga , Stefanova Kremena , Garbazey Oksana , Belokopytov Vladimir , Liashko Tatiana , Stefanova Elitsa
Published: December 2022

Global warming is increasing the frequency and severity of the marine heat waves, which poses a serious threat to the marine ecosystem. This study analyzes seasonal and interannual dynamics in the abundance and structure of the mesozooplankton community in Sevastopol Bay based on bi-monthly routine observations over 2003–2014. The focus is on the impact of the summer 2010 marine heat wave (MHW2010) on crustaceans belonging to different ecological groups. As a response to the MHW2010, three warm-water species (O. davisae, A. tonsa and P. avirostris) exhibiting the maximum seasonal density in latter summer showed a sharp increase in the annual abundance and their share in the mesozooplankton community. The increase in the annual abundance in 2010 of the eurythermal species P. parvus and P. polyphemoides exhibiting seasonal peaks in spring and autumn is not related to the MHW2010 but can be explained by a rise of temperature in the first part of the year. O. davisae and A. tonsa showed the most pronounced response among the species to the MHW2010, confirming that non-native species exhibited great flexibility as an adaptive response to environmental changes, especially in the case of climate warming. Among crustaceans observed in this study, O. davisae can be considered as an indicator of the environmental conditions associated with the warming of the Black Sea and the Mediterranean basin as a whole.
Accumulation and Dispersion of Microplastics near A Submerged Structure: Basic Study Using A Numerical Wave Tank
Authors: Quyen Le Duc , Choi Jun Myoung
Published: December 2022

The presence of microplastics has been reported in most marine environments. Their accumulation can affect the marine ecosystem, and their consumption by small organisms of various sizes can indirectly affect human beings who consume them. Recent observations have reported the pathways and fates of microplastics surrounding man-made coastal structures, such as artificial reefs. However, basic research elucidating the physical behavior near the structure is scarce. We implemented a two-dimensional numerical wave flume simulating intermediate waves with a weak current in a coastal area to investigate the behaviors of microplastics corresponding to parameters such as particle size (0.2, 1, and 5 mm), particle density (900, 1000, and 1100 kg/m3), and submerged artificial structure. The results showed that smaller particles had a stronger horizontal dispersion but a weaker horizontal advection. Installing a submerged structure increased the flow rate above the structure. It also increased particle accumulation upstream and downstream near the edge and corner of the structure. The accumulation was significantly affected by the installation of the structure when the resuspension of microplastics occurred intermittently. This work elucidates the mechanisms underlying the distribution, accumulation, and dispersion of microplastics that are important in predicting the fate of microplastics in the vicinity of artificial structures.
Deep Genotypic Species Delimitation of Aspergillus Section Flavi Isolated from Brazilian Foodstuffs and the Description of Aspergillus annui sp. nov. and Aspergillus saccharicola sp. nov.
Authors: Silva Josué J. , Fungaro Maria H. P. , Wang Xinhui , Larsen Thomas O. , Frisvad Jens C. , Taniwaki Marta H. , Iamanaka Beatriz T.
Published: December 2022

Aspergillus section Flavi is a fungal group that is important in food because it contains spoilage and potentially aflatoxigenic species. Aflatoxins are metabolites that are harmful to human and animal health and have been recognized as the primary natural contaminant in food. Therefore, recognizing the biodiversity of this group in food is necessary to reduce risks to public health. Our study aimed to investigate the diversity of Aspergillus section Flavi isolated from Brazilian foodstuffs such as cassava, sugarcane, black pepper, paprika, Brazil nuts, yerba-mate, peanuts, rice, and corn. A polyphasic approach integrating phenotypic data and multilocus genotypic analyses (CaM, BenA, and RPB2) was performed for 396 strains. Two new species in the Aspergillus subgenus Circumdati section Flavi are proposed using maximum-likelihood analysis, Bayesian inference, and coalescence-based methods: Aspergillus saccharicola sp. nov. and Aspergillus annui sp. nov. A. saccharicola sp. nov. belongs to the series Flavi, is a potentially aflatoxigenic species (B1, B2, G1, and G2), closely related to Aspergillus arachidicola, and was found mostly in sugarcane. A. annui sp. nov. was isolated from samples of sweet paprika. To accommodate A. annui sp. nov., a new series Annuorum was proposed.
Future Newborns with Opioid-Induced Neonatal Abstinence Syndrome (NAS) Could Be Assessed with the Genetic Addiction Risk Severity (GARS) Test and Potentially Treated Using Precision Amino-Acid Enkephalinase Inhibition Therapy (KB220) as a Frontline Modality Instead of Potent Opioids
Authors: Ceccanti Mauro , Blum Kenneth , Bowirrat Abdalla , Dennen Catherine A. , Braverman Eric R. , Baron David , Mclaughlin Thomas , Giordano John , Gupta Ashim , Downs Bernard W. , Bagchi Debasis , Barh Debmalya , Elman Igor , Thanos Panayotis K. , Badgaiyan Rajendra D. , Edwards Drew , Gold Mark S.
Published: December 2022

In this nonsystematic review and opinion, including articles primarily selected from PubMed, we examine the pharmacological and nonpharmacological treatments of neonatal abstinence syndrome (NAS) in order to craft a reasonable opinion to help forge a paradigm shift in the treatment and prevention of primarily opioid-induced NAS. Newborns of individuals who use illicit and licit substances during pregnancy are at risk for withdrawal, also known as NAS. In the US, the reported prevalence of NAS has increased from 4.0 per 1000 hospital births in 2010 to 7.3 per 1000 hospital births in 2017, which is an 82% increase. The management of NAS is varied and involves a combination of nonpharmacologic and pharmacologic therapy. The preferred first-line pharmacological treatment for NAS is opioid therapy, specifically morphine, and the goal is the short-term improvement in NAS symptomatology. Nonpharmacological therapies are individualized and typically focus on general care measures, the newborn–parent/caregiver relationship, the environment, and feeding. When used appropriately, nonpharmacologic therapies can help newborns with NAS avoid or reduce the amount of pharmacologic therapy required and the length of hospitalization. In addition, genetic polymorphisms of the catechol-o-methyltransferase (COMT) and mu-opioid receptor (OPRM1) genes appear to affect the length of stay and the need for pharmacotherapy in newborns with prenatal opioid exposure. Therefore, based on this extensive literature and additional research, this team of coauthors suggests that, in the future, in addition to the current nonpharmacological therapies, patients with opioid-induced NAS should undergo genetic assessment (i.e., the genetic addiction risk severity (GARS) test), which can subsequently be used to guide DNA-directed precision amino-acid enkephalinase inhibition (KB220) therapy as a frontline modality instead of potent opioids.
Effect of a NICU to Home Physical Therapy Intervention on White Matter Trajectories, Motor Skills, and Problem-Solving Skills of Infants Born Very Preterm: A Case Series
Authors: Butera Christiana Dodd , Rhee Claire , Kelly Claire E. , Dhollander Thijs , Thompson Deanne K. , Wisnowski Jessica , Molinini Rebecca M. , Sargent Barbara , Lepore Natasha , Vorona Greg , Bessom Dave , Shall Mary S. , Burnsed Jennifer , Stevenson Richard D. , Brown Shaaron , Harper Amy , Hendricks-Muñoz Karen D. , Dusing Stacey C.
Published: December 2022

Infants born very preterm (VPT; ≤29 weeks of gestation) are at high risk of developmental disabilities and abnormalities in neural white matter characteristics. Early physical therapy interventions such as Supporting Play Exploration and Early Development Intervention (SPEEDI2) are associated with improvements in developmental outcomes. Six VPT infants were enrolled in a randomised clinical trial of SPEEDI2 during the transition from the neonatal intensive care unit to home over four time points. Magnetic resonance imaging scans and fixel-based analysis were performed, and fibre density (FD), fibre cross-section (FC), and fibre density and cross-section values (FDC) were computed. Changes in white matter microstructure and macrostructure were positively correlated with cognitive, motor, and motor-based problem solving over time on developmental assessments. In all infants, the greatest increase in FD, FC, and FDC occurred between Visit 1 and 2 (mean chronological age: 2.68–6.22 months), suggesting that this is a potential window of time to optimally support adaptive development. Results warrant further studies with larger groups to formally compare the impact of intervention and disparity on neurodevelopmental outcomes in infants born VPT.
The Predictive Value of Systemic Immune-Inflammation Index and Symptom Severity Score for Sepsis and Systemic Inflammatory Response Syndrome in Odontogenic Infections
Authors: Pricop Marius , Ancusa Oana , Talpos Serban , Urechescu Horatiu , Bumbu Bogdan Andrei
Published: December 2022

Acute Odontogenic Infections (OI) are the leading cause of emergency visits and hospitalizations to the maxillofacial department, and may induce systemic inflammatory complications. Increasing numbers of OI patients need extended hospitalizations, various treatments, and intensive care. The Symptom Severity score (SS) helps doctors assess the likelihood of infection and admission complications. Systemic Immune-inflammation Index (SII) is a biomarker-based inflammatory prognosis score. It was hypothesized that greater SII and SS values might suggest a higher risk for sepsis and systemic inflammatory response syndrome (SIRS). Therefore, this research aims to discover whether SII and SS scores can reliably predict odontogenic infection severity and prognosis, and if they can be used to predict the development of SIRS and sepsis in OI using admission features. The study was designed as a retrospective cohort, with patients’ data being retrieved from medical records between January 2017 to April 2022. A total of 108 OI patients were matched 1:1 as low-severity and high-severity groups. Most individuals with severe infections had diabetes and smoking as comorbidities. Severe patients had longer hospital stays (12.0 days vs. 4.1 days), although mortality rates did not significantly differ. A total of 11.1% lower-severity patients (Group A) had SIRS during hospitalization, compared to Group B with 25.9%. Group A had 7.4% of patients that developed sepsis compared to Group B’s rate of 22.2%. The correlation between OI’s SS and SII index values was positive and statistically significant (r = 0.6314). The total SII index mean was 1303, whereas the mean values by severity were 696.3 in Group A and 2312.4 in Group B. Group A’s mean SS score was 6.1, while Group B’s was 13.6. According to the calculated AUC plots, SII and SS scores were accurate predictors of sepsis and SIRS development using OI admission parameters. The adjusted odds ratio for SIRS in OI patients was 2.09, and 2.27 for sepsis. Medical professionals and dentistry teams should be encouraged to use the SII and SS scores to diagnose and anticipate sepsis and SIRS, hence improving disease management decisions.
Distributed Ledger Technology (DLT): A Game Changer for MNEs in Emerging Markets
Authors: Agmon Tamir , Kallir Ido
Published: December 2022

Global trade determines how we live. Technology determines the extent of the market and the ease of trade. The transportation revolution reduced costs and cut travel times. The communication revolution (ICT) improved the quality and quantity of information in the global market and cut the cost of global trade in goods and services, including labor. Global trade has become a B2B market wherein multinational enterprises (MNEs) are major players. While MNEs began as major companies in developed countries, their success in importing labor from the emerging market through production of consumer goods in the developed countries led to emerging MNE markets. In an earlier paper on MNEs in emerging markets, Agmon suggested that blockchains reduce the cost of using the global price mechanism, and both production and consumption decisions can be made by individuals in a global market. In this paper, we discuss the case of the multinational industry of venture capital-supported small start-ups, wherein individuals with ideas for better goods, production processes, and services approach capital markets in major countries for financing their ideas. The accompanying distributed ledger technology (DLT) takes global trade a step further by opening up the possibility of global trade among individuals and loosely organized, task-oriented groups of individuals located in both developed and emerging economies. In a DLT world with decentralized markets, no transaction costs, and perfect information, the key to global trade will lie in the capabilities of the individual, or a specific task-oriented, loosely organized group of individuals. Small countries are finding it increasingly difficult to compete in international markets. We seek to examine whether the conceptual framework of DLT, when implemented in a small country that chooses to export ideas rather than products, thereby eliminating the need for a complex supply chain, can be the first empirical example of the DLT concept as a “game changer”. The experience of the Israeli VC industry points to exciting potential through the application of the mindset and the unique legal and financial structures of the “start-up nation”, wherein an economy was created that relies on small and frequently changing high-tech firms. In a country where VC investment capital is entirely imported, there is more room for investment in DLT technologies. Such an economy is compatible with the DLT concept and provides a unique empirical example of the DLT technological change’s effect on the economy of a small country.
Do Stock Market Volatility and Cybercrime Affect Cryptocurrency Returns? Evidence from South African Economy
Authors: Mthembu Nosipho , Sanusi Kazeem Abimbola , Eita Joel Hinaunye
Published: December 2022

The study investigates the effects of stock market volatility and cybercrime on cryptocurrency returns in the South African economy. Daily time series data on four different types of cryptocurrencies (Bitcoin, Ethereum, Tether, and BMB) were employed. The data covers the period from 1 January 2019–31 December 2021. The study employed the dynamic conditional correlation (DCC GARCH) and Bayesian liner regression model to investigate time-varying correlations among the variables. Empirical findings suggest that stock market volatility has a positive impact on the returns of BNB, Bitcoin, and Ethereum. However, it has a negative impact on Tether. Expectedly, cybercrime poses negative impacts on the returns of BNB, Bitcoin, and Ethereum but could be said to have no impact on the returns of Tether. The study concludes that ongoing efforts to reduce cybercrime activities need to be strengthened to further the use of digital currencies.
Monitoring Beach Shape Development and Sediment Dynamics on a Sandy Beach with Low Anthropogenic Influence
Authors: Zuber Alain , Álvarez María-Carmen , Mendoza Edgar , Díaz-Flores Miguel Ángel , Galicia-Pérez Marco , Torres-Orozco Ernesto
Published: December 2022

This study examined the evolution of the beach profile and sedimentary balance in Playa del Coco, Mexico, during one year (September 2013–September 2014) to monitor these conditions at a site with little or no anthropogenic influence. The type of beach profile was determined according to the energy profile of the geomorphology, resulting in three types of profiles: low, medium, and high energy. In addition, sediment volumes were quantified, and erosion or accumulation at each study site was described. The results showed that the medium-energy profile was characteristic of the beach most of the time. High-energy conditions were recorded only once due to the influence of a high-category hurricane (Odile, III) during the hurricane season. The dominant sediment size was medium, moderately well-classified to well-classified, coinciding with the medium-energy profile. Coarse, well-sorted sand was recorded at the end of the study, coinciding with the highest loss of sediment on the beach. Playa del Coco showed a state of quasi-equilibrium before the end of the annual cycle, recovering the characteristics of the beach at the beginning of the study. After that time, there was a great loss of sedimentary material influenced by Hurricane Odile (III), modifying the beach’s state of recovery. Therefore, the stability of this beach could be cyclical and respond to the self-organization principle rather than to seasonal parameters. However, the duration of the cycles that influence Playa del Coco seems to be determined by the hurricane season, especially the combination of two main factors: the proximity to the coast of the hurricane and the amount of rainfall associated with the hurricane.
Nonlinear Cooling Effect of Street Green Space Morphology: Evidence from a Gradient Boosting Decision Tree and Explainable Machine Learning Approach
Authors: Liu Ziyi , Ma Xinyao , Hu Lihui , Liu Yong , Lu Shan , Chen Huilin , Tan Zhe
Published: December 2022

Mitigation of the heat island effect is critical due to the frequency of extremely hot weather. Urban street greening can achieve this mitigation and improve the quality of urban spaces and people’s welfare. However, a clear definition of street green space morphology is lacking, and the nonlinear mechanism of its cooling effect is still unclear; the interaction between street green space morphology and the surrounding built environment has not been investigated. This study used machine learning, deep learning, and computer vision methods to predict land surface temperature based on street green space morphology and the surrounding built environment. The performances of the XGBoost, LightGBM, and CatBoost models were then compared, and the nonlinear cooling effects offered by the street green space morphology were analyzed using the Shapley method. The results show that streets with a high level of green environment exposure (GVI > 0.4, NDVI > 4) can accommodate more types of green space morphology while maintaining the cooling effect. Additionally, the proportion of vegetation with simple geometry (FI < 0.2), large leaves (FD < 0.65), light-colored leaves (CSI > 13), and high leaf density (TDE > 3) should be increased in streets with a low level of green environment exposure (GVI < 0.1, NDVI < 2.5). Meanwhile, streets with highly variable building heights (AFI > 1.5) or large areas covered by buildings (BC > 0.3) should increase large leaf vegetation (FD < 0.65) while decreasing dark leaf vegetation (CSI < 13). The study uses machine learning methods to construct a nonlinear cooling benefit model for street green space morphology, proposes design recommendations for different street green spaces that consider climate adaptation, and provides a reference for urban thermal environment regulation.
Characterizing Spatial-Temporal Variation of Cultural Tourism Internet Attention in Western Triangle Economic Zone, China
Authors: Zhang Yang , Jin Xue , Wang Yuwei , Liu Rongtian , Jing Ying
Published: December 2022

More and more tourists tend to seek cultural enjoyment while taking trips based on their satisfied socio-economic needs. The spatiality of cultural tourism determines the feasibility and convenience of the access to cultural tourism resources. Given that spatial research on cultural tourism rarely involves the underdeveloped regions in China, especially via Baidu Index data, this study aims to explore the dynamic spatial pattern of cultural tourism Internet attention based on Baidu Index through social network analysis (i.e., network density, centrality analysis, core–periphery model, etc.) in the Western Triangle Economic Zone (WTEZ), China. Research findings are as follows. (1) Temporally, the centrality is increasingly enhanced in terms of the core cities with high cultural tourism Internet attention, as well as their radiation effect. (2) Spatially, the distribution pattern of cultural tourism Internet attention is shifting from polarization to equilibrium. However, the overall network density still presents a mode of loose connection and fails to extend from the core triangle structure in the planar dimension. (3) The cultural tourism Internet attention in WTEZ presents an obvious core–periphery pattern. Xi’an–Chengdu–Chongqing is in a dominant position, and the core area spreads from south to north. (4) The spatial-temporal pattern of cultural tourism Internet attention in WTEZ is influenced by transportation, reception facilities, consumption ability, and political environment, and the main driving factors are the number of hotels, per capita income, total highway mileage, and cultural tourism policy indicators. This study is conducive to sustainable spatial planning of cultural tourism through smart data governance.
Impact of Farmland Change on Vegetation NPP in the One River and Two Streams Region of Tibet
Authors: Liu Yunxi , Wang Xue , Xin Liangjie , Lu Yahan
Published: December 2022

Studies on the impacts of a particular land use type change are relatively rare, especially in the Tibetan Plateau region (TP). This study focused on the impacts of farmland use change on grain supply and ecosystem stability in the Yarlung Zangbo river and its two tributaries (also known as One River and Two Streams, ORTS), using net primary productivity (NPP), known as the total amount of organic matter left after removal of carbon absorbed from the atmosphere by vegetation through photosynthesis, as a common proxy for farmland productivity and ecosystem stability. The trend analysis method was applied to measure the inter-annual change of NPP, and an ecological impact index was constructed to quantify the impact of farmland use change on the NPP change in the ORTS region. The results showed that: (1) The total area of farmland decreased by 6.09% from 2000 to 2018. Built-up land occupation and ecological restoration were the main reasons for the decrease of farmland area, while there was also new reclaimed farmland, transferred from ecological land. (2) The NPP in the ORTS region was roughly on an increasing trend, while the trends of NPP in different farmland change areas were not the same. Specifically, the NPP of ecological restoration, newly reclaimed farmland, and unchanged farmland areas all showed a significant increasing trend, while the NPP in the area of farmland occupied by built-up land showed a significant decreasing trend. (3) The impact of farmland changes from 2000 to 2018 contributed 1.22% to the increase of NPP in the ORTS region. This study not only provides a research paradigm in quantifying the production and ecological impacts of a particular land use type change that can be applied in related studies in other regions, but at the same time, the results of the empirical analysis in the ORTS region can also provide suggestions for the rational use and conservation of farmland and the stability and sustainable development of ecosystems for the region and even the TP.
Research on the Law of China’s Rural Land Institutional Changes: An Analytical Framework of Economic Efficiency and Distributive Equity
Authors: Zhang Minghui , Xia Weiqi
Published: December 2022

Institutions affect economic development and social stability, and the characteristics of institutional change are a complex and widely discussed topic. This paper constructs a theoretical analysis framework to describe the relationship between institutional change, resource conditions, and overall social welfare, so as to explore the preconditions for the formation of institutions with greater equity and higher economic efficiency. On the basis of this analytical framework, we conduct a case study on China’s rural land institutional changes over the past 70 years to explore the law of institutional changes. We found that when resources are scarce, economic efficiency and distributive equity usually pose difficulty to being improved and present a substitution relationship, while only when resources are sufficient could they realise these goals. The findings indicate that for regions with meagre resources, the advantageous sectors need to be identified and prioritised at the beginning of the development so as to recognise the appropriate initial resource accumulation. A certain accumulation of resources is the prerequisite for creating institutions that could improve economic efficiency and offer equitable distribution.
A Robust Computer-Aided Automated Brain Tumor Diagnosis Approach Using PSO-ReliefF Optimized Gaussian and Non-Linear Feature Space
Authors: Ali Muhammad Umair , Kallu Karam Dad , Masood Haris , Hussain Shaik Javeed , Ullah Safee , Byun Jong Hyuk , Zafar Amad , Kim Kawang Su
Published: December 2022

Brain tumors are among the deadliest diseases in the modern world. This study proposes an optimized machine-learning approach for the detection and identification of the type of brain tumor (glioma, meningioma, or pituitary tumor) in brain images recorded using magnetic resonance imaging (MRI). The Gaussian features of the image are extracted using speed-up robust features (SURF), whereas its non-linear features are obtained using KAZE, owing to their high performance against rotation, scaling, and noise problems. To retrieve local-level information, all brain MRI images are segmented into an 8 × 8 pixel grid. To enhance the accuracy and reduce the computational time, the variance-based k-means clustering and PSO-ReliefF algorithms are employed to eliminate the redundant features of the brain MRI images. Finally, the performance of the proposed hybrid optimized feature vector is evaluated using various machine learning classifiers. An accuracy of 96.30% is obtained with 169 features using a support vector machine (SVM). Furthermore, the computational time is also reduced to 1 min compared to the non-optimized features used for training of the SVM. The findings are also compared with previous research, demonstrating that the suggested approach might assist physicians and doctors in the timely detection of brain tumors.
Helicobacter Pylori: A Review of Current Treatment Options in Clinical Practice
Authors: Roberts Logan T. , Issa Peter P. , Sinnathamby Evan S. , Granier Mallory , Mayeux Holly , Eubanks Treniece N. , Malone Kevin , Ahmadzadeh Shahab , Cornett Elyse M. , Shekoohi Sahar , Kaye Alan D.
Published: December 2022

Background: When prescribing antibiotics, infection eradication rates, local resistance rates, and cost should be among the most essential considerations. Helicobacter pylori is among the most common infections worldwide, and it can lead to burdensome sequela for the patient and the healthcare system, without appropriate treatment. Due to constantly fluctuating resistance rates, regimens must be constantly assessed to ensure effectiveness. Methods: This was a narrative review. The sources for this review are as follows: searching on PubMed, Google Scholar, Medline, and ScienceDirect; using keywords: Helicobacter pylori, Treatment Options, Clinical Practice. Results: Multiple antibiotics are prescribed as part of the regimen to thwart high resistance rates. This can lead to unwanted adverse reactions and adherence issues, due to the amount and timing of medication administration, which also may contribute to resistance. Single-capsule combination capsules have reached the market to ease this concern, but brand-only may be problematic for patient affordability. Due to the previously mentioned factors, effectiveness and affordability must be equally considered. Conclusions: This review will utilize guidelines to discuss current treatment options and give cost considerations to elicit the most effective regimen for the patient.
Diversity Analysis of Leaf Nutrient Endophytes and Metabolites in Dioecious Idesia polycarpa Maxim Leaves during Reproductive Stages
Authors: Feng Jian , Rana Sohel , Liu Zhen , Wang Yanmei , Cai Qifei , Geng Xiaodong , Zhou Huina , Zhang Tao , Wang Shasha , Xue Xiaoyan , Li Mingwan , Jemim Razia Sultana , Li Zhi
Published: December 2022

Leaves are essential vegetative organs of plants. Studying the variations in leaf nutrient content and microbial communities of male and female plants at reproductive stages helps us understand allocation and adaptation strategies. This study aimed to determine the nutrient characteristics and microbial differences in the leaves of male and female Idesia polycarpa at reproductive stages. Seven-year-old female and male plants were used as test materials in this experiment. The samples were collected at three stages: flowering (May), fruit matter accumulation (July), and fruit ripening (October). The nitrogen (TN), phosphorus (TP), potassium (TK), carbon (TC), and the pH of the female and male leaves were analyzed. In addition, the leaf microbial diversity and differential metabolites were determined using the Illumina high-throughput sequencing method and the ultra-high performance liquid chromatography–tandem mass spectrometry (UPLC–MS/MS) method at the reproductive developmental stages. This study found that male and female plant leaves had different TN and TK contents over time but no difference in TC and TP content. The significant differences in bacterial diversity between male and female plants and the richness of the fungi of male plants at the flowering and fruit maturity stages were observed. Proteobacteria, Pseudomonadaceae, Ascomycota, and Aspergillus were the dominant bacteria and fungi in the Idesia polycarpa leaves. The presence of microorganisms differed in the two sexes in different periods. Alphaproteobacteria and Sordariomycetes were the indicator groups for male leaves, and Pseudomonas and Sordariomycetes were the indicator groups for female leaves. Significant differences in phenolic acid were found between male and female leaves. A KEGG enrichment analysis revealed that differential metabolites were enriched in metabolic pathways, amino acid biosynthesis, and the nucleotide metabolism. According to a correlation analysis, leaf TK and TP were strongly correlated with endophytic bacteria abundance and differential metabolite composition. This study revealed the changes in substances and microorganisms in the leaves of male and female plants in their reproductive stages. It provides a theoretical basis for developing and utilizing the leaves of Idesia polycarpa and for field management.
Nasal Microbiota and Neuroinflammation: Relationship between Nasal Flora and Multiple Sclerosis Onset/Progression
Authors: Gioacchini Federico Maria , Ferlito Salvatore , Ralli Massimo , Scarpa Alfonso , La Mantia Ignazio , Re Massimo , Romani Luigina , Di Stadio Arianna
Published: December 2022

The role of nasal microbiota in contributing to neuroinflammation is gradually emerging. Multiple sclerosis and chronic rhinosinusitis share important clinical and epidemiological similarities, and the hypothetical connection among these two pathological entities should be carefully investigated. This editorial is based on a review of available literature on this topic. The main international databases were searched using the following keywords: neuroinflammation, nasal microbiota, multiple sclerosis, chronic rhino-sinusal disorders, chronic sinusitis. Four fully-consistent articles that investigated nasal microbiota alteration and/or chronic rhinosinusitis presence in subjects affected by multiple sclerosis were identified. Overall, these studies showed a significant connection between nasal microbiota dysbiosis and the presence of multiple sclerosis. New specific studies to analyze the nasal microbiota and its metabolism in patients affected by multiple sclerosis should be performed. In fact, a series of treatments able to change this flora could improve the rhino-sinusal state with consequent reduction of recurrent episodes of neuro-inflammation.
Signs, Symptoms, and Side-Effects Presented by Different Types of COVID-19 Vaccines: A Prospective Cohort Study
Authors: Zare Zahra , Assarroudi Abdolghader , Armat Mohammad Reza , Laal Ahangar Mojtaba , Estaji Mahdie , MoghaddamHosseini Vahideh , Dianatinasab Mostafa
Published: December 2022

The concern about post-COVID-19 vaccine complications still remains. In addition, the evidence on Sinopharm, Sputnik V, Covaxin, and, in particular, COVIran Barekat, as well as comparisons between them by dosage after post-vaccination, is scarce. This study aimed to investigate and compare the prevalence of self-reported post-vaccination signs and symptoms following the first and second doses of different types of COVID-19 vaccines. Research design and methods: This prospective cohort study was conducted on more than 1500 health professionals who had received at least one dose of any type of Sputnik V, Sinopharm, Oxford AstraZeneca, Covaxin, and COVIran Barekat vaccines in Iran. The survey questionnaire was sent to participants online, 28 days after receiving each dose of the vaccine. Results: About 73% of health professionals reported at least one post-vaccination sign or symptom, developing mostly within the first 12 h (69.9%) and lasting up to 12 h (59.0%). Pain and tenderness at the injection site, fever, and muscle pain were the most common post-vaccination signs and symptoms in all vaccines, which were significantly higher in the Oxford AstraZeneca vaccine (p < 0.001) for both the first and second doses. The incidence rate of all post-vaccination signs and symptoms was significantly higher in the first dose than in the second dose (p < 0.05). Conclusion: The Oxford AstraZeneca vaccine showed the highest incidence rate, onset, and lasting time of signs and symptoms in both doses; however, they were not life-threatening. The onset time of signs and symptoms was significantly higher for the COVIran Barekat and Oxford AstraZeneca vaccines in both the first and second doses.
Hospital-Based Quasi-Experimental Study on Hydroxychloroquine Pre-Exposure Prophylaxis for COVID-19 in Healthcare Providers with Its Potential Side-Effects
Authors: Shahrin Lubaba , Mahfuz Mustafa , Rahman Md. Waliur , Hossain Md. Rezaul , Khandaker Afsana Mim , Alam Md. Ashraful , Osmany Din M. M. F. , Islam Md. Munirul , Chisti Mohammod Jobayer , Ahmed Chaudhury Meshkat , Ahmed Tahmeed
Published: December 2022

Considering that it has been more than 24 months since SARS-CoV-2 emerged, it is crucial to identify measures that prevent and control pathogen transmission in workplace settings. Our aim was to report results of a hospital-based program that delivered hydroxychloroquine (HCQ) tablets as COVID-19 prophylaxis to the frontline healthcare workers (HCW)s who cared for COVID-19 patients and to evaluate the efficacy of HCQ. Setting and participants: Quasi-experimental, controlled, single-center study. The included participants were doctors, nurses, health workers, cleaning staff, and non-healthcare supportive staff. The main outcome was contracting COVID-19 anytime during the period of taking the prophylaxis, confirmed by RT-PCR. A total of 336 participants, without any clinical evidence of COVID-19 and without any known contact with family members, were included in the trial; 230 were assigned to HCQ and 106 declined to take any drug. Results: Among the participants, 43 (18.7%) in the HCQ group and 11 (10.4%) participants in the control group developed COVID-19. For the evaluation of side effects, we evaluated 12-lead ECGs of both groups at the baseline and after 4 weeks to monitor QTc interval. A total of 91% (198 of 217) participants in the prophylaxis group and 92% (11 of 12) in the control group had a QTc < 45o msec, which is within normal limits. Conclusions: Although the number of symptomatic infections in health personnel was lower in the control group, the difference was not statistically significant. However, in the absence of any effective pre-exposure prophylaxis medicine for COVID-19, practicing proper infection prevention and control (IPC) and vaccination is the only way forward.
Novel Virus Identification through Metagenomics: A Systematic Review
Authors: Bassi Cristian , Guerriero Paola , Pierantoni Marina , Callegari Elisa , Sabbioni Silvia
Published: December 2022

Metagenomic Next Generation Sequencing (mNGS) allows the evaluation of complex microbial communities, avoiding isolation and cultivation of each microbial species, and does not require prior knowledge of the microbial sequences present in the sample. Applications of mNGS include virome characterization, new virus discovery and full-length viral genome reconstruction, either from virus preparations enriched in culture or directly from clinical and environmental specimens. Here, we systematically reviewed studies that describe novel virus identification through mNGS from samples of different origin (plant, animal and environment). Without imposing time limits to the search, 379 publications were identified that met the search parameters. Sample types, geographical origin, enrichment and nucleic acid extraction methods, sequencing platforms, bioinformatic analytical steps and identified viral families were described. The review highlights mNGS as a feasible method for novel virus discovery from samples of different origins, describes which kind of heterogeneous experimental and analytical protocols are currently used and provides useful information such as the different commercial kits used for the purification of nucleic acids and bioinformatics analytical pipelines.
Assessment of Poorly Compactable Sands by Recycling and Recompaction: Experimental Program and Packing Particle Analysis
Authors: Arias-Trujillo Juana , Matías-Sánchez Agustín
Published: December 2022

Compaction is a common ground improvement technique based on the densification of soils for an energy level and optimum water content, mainly influenced by the particle size and curve gradation. Poorly compactable sands, characterized as cohesionless, fine and uniformly graded, are a challenge for earthworks since compaction is not effective due to the lack of a larger range of particle sizes to infill the voids and the compaction energy is not relevant either. These characteristics are common to other materials, i.e., desert sand, industrial or mining by-products or quarry fines, which are mostly discarded to landfill and replaced by proper soils, causing serious environmental issues. To enlarge the technical feasibilities of poorly compactable sands, reducing construction waste and raw material consumption, a mechanical stabilization, based on a repetitive series of recycling and recompaction without binder, is experimentally explored. The behavior observed is also analyzed from reported correlations and a packing particle approach, attending to densification stage, saturation degree, recompaction series, coordination number and packing density. The improvement achieved is moderate and dependent on the cycles applied, showing a characteristic repetitive pattern in the compaction curve, and approaching the estimated minimum void ratio and the theoretical maximum packing possibilities without degradation of the material.
Effect of Mat Moisture Content, Adhesive Amount and Press Time on the Performance of Particleboards Bonded with Fructose-Based Adhesives
Authors: Rosenfeld Catherine , Solt-Rindler Pia , Sailer-Kronlachner Wilfried , Kuncinger Thomas , Konnerth Johannes , Geyer Andreas , van Herwijnen Hendrikus W. G.
Published: December 2022

The study evaluates the performance of laboratory, single-layered particleboards made out of fructose-hydroxymethylfurfural-bishexamethylenetriamine (SusB) adhesive as a sustainable alternative. Several production parameters such as mat moisture content (MMC), adhesive amount and press time were varied and their effect on the bonding efficiency investigated. The internal bond strength (IB) and thickness swelling after 24 h of water immersion (TS) were taken as evaluation criteria for the bonding efficiency. pMDI-bonded particleboards were produced as fossil-based, formaldehyde-free reference. Particleboard testing was complemented by tensile shear strength measurements and thermal analysis. It was found that the MMC has the highest impact on the internal bond strength of SusB-bonded particleboards. In the presence of water, the reaction enthalpy of the main curing reaction (occurring at 117.7 °C) drops from 371.9 J/mol to 270.5 J/mol, leading to side reactions. By reducing the MMC from 8.7%, the IB increases to 0.61 N/mm2, thus surpassing P2 requirements of the European standard EN312. At a press factor of 10 s/mm, SusB-bonded particleboards have a similar IB strength as pMDI-bonded ones, with 0.59 ± 0.12 N/mm2 compared to 0.59 ± 0.09 N/mm2. Further research on the improvement of the dimensional stabilization of SusB-bonded PBs is needed, as the TS ranges from 30–40%.
Sustainable Recycling Techniques of Pavement Materials
Authors: Wang Jiaqing , Li Qiang , Huang Kaijian , Ge Dongdong , Gong Fangyuan
Published: December 2022

Innovative sustainable techniques for transportation infrastructure enhancement have been proposed in recent decades [...]
Novel Carboxymethyl Cellulose-Based Hydrogel with Core–Shell Fe3O4@SiO2 Nanoparticles for Quercetin Delivery
Authors: Mahdi Eshaghi Mohammad , Pourmadadi Mehrab , Rahdar Abbas , Díez-Pascual Ana M.
Published: December 2022

A nanocomposite composed of carboxymethyl cellulose (CMC) and core–shell nanoparticles of Fe3O4@SiO2 was prepared as a pH-responsive nanocarrier for quercetin (QC) delivery. The nanoparticles were further entrapped in a water-in-oil-in-water emulsion system for a sustained release profile. The CMC/Fe3O4@SiO2/QC nanoparticles were characterized using dynamic light scattering (DLS), Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), a field emission scanning electron microscope (FE-SEM), and a vibrating sample magnetometer (VSM) to obtain insights into their size, stability, functional groups/chemical bonds, crystalline structure, morphology, and magnetic properties, respectively. The entrapment and loading efficiency were slightly improved after the incorporation of Fe3O4@SiO2 NPs within the hydrogel network. The dialysis method was applied for drug release studies. It was found that the amount of QC released increased with the decrease in pH from 7.4 to 5.4, while the sustained-release pattern was preserved. The A549 cell line was chosen to assess the anticancer activity of the CMC/Fe3O4@SiO2/QC nanoemulsion and its components for lung cancer treatment via an MTT assay. The L929 cell line was used in the MTT assay to determine the possible side effects of the nanoemulsion. Moreover, a flow cytometry test was performed to measure the level of apoptosis and necrosis. Based on the obtained results, CMC/Fe3O4@SiO2 can be regarded as a novel promising system for cancer therapy.
Ultrafine Grain Ferrite Transformed from Fine Austenite Grains Produced by Dynamic Reversal Transformation
Authors: Li Hongbin , Zheng Xiaoping , Fan Lifeng , Xu Haiwei , Tian Yaqiang , Dai Xin , Chen Liansheng
Published: December 2022

The medium carbon steel warm deformation was carried out in a Gleeble-3500 simulator, and the microstructure was observed on a scan electron microscopy (SEM) and optical microscope (OM). The results show that the dynamic reversal transformation (DRT) of austenite occurred during the multipass deformation at a temperature of 675 °C. The austenite grain size is about 3.4 μm at the stain of 2.67. The thermodynamics was discussed based on the stress activation model. The critical stress of DRT is in the range of 265.94–294.28 MPa, which is related to the Schmit factor, without considering the distortion energy. Meanwhile, the submicron ferrite was obtained after the air cooling stage. The texture of the ultrafine ferrite possessed the characteristics of good, deep drawing properties.
Recent Progress on Anti-Humidity Strategies of Chemiresistive Gas Sensors
Authors: Wang Yanjie , Zhou Yong
Published: December 2022

In recent decades, chemiresistive gas sensors (CGS) have been widely studied due to their unique advantages of expedient miniaturization, simple fabrication, easy operation, and low cost. As one ubiquitous interference factor, humidity dramatically affects the performance of CGS, which has been neglected for a long time. With the rapid development of technologies based on gas sensors, including the internet of things (IoT), healthcare, environment monitoring, and food quality assessing, the humidity interference on gas sensors has been attracting increasing attention. Inspiringly, various anti-humidity strategies have been proposed to alleviate the humidity interference in this field; however, comprehensive summaries of these strategies are rarely reported. Therefore, this review aims to summarize the latest research advances on humidity-independent CGS. First, we discussed the humidity interference mechanism on gas sensors. Then, the anti-humidity strategies mainly including surface engineering, physical isolation, working parameters modulation, humidity compensation, and developing novel gas-sensing materials were successively introduced in detail. Finally, challenges and perspectives of improving the humidity tolerance of gas sensors were proposed for future research.