bluuebunny/crossref_metadata_2025 huggingface dataset:
Microplastics in Agricultural Systems: Analytical Methodologies and Effects on Soil Quality and Crop Yield
Authors: Pérez-Reverón Raquel , Álvarez-Méndez Sergio J. , Kropp Rebecca Magdalena , Perdomo-González Adolfo , Hernández-Borges Javier , Díaz-Peña Francisco J.
Published: August 2022

Around one million metric ton of plastics is produced worldwide daily. Plastic contamination is aggravated when the particles reach sizes between 5 mm and 1 μm, giving rise to microplastics, which are omnipresent in the environment, especially in agroecosystems. To appreciate the magnitude of this problem, this review analyzes 177 scientific works to focus on the occurrence and effects of microplastics in agricultural soils. Firstly, the sources, behavior and fate of microplastics in agroecosystems are evaluated. Then, in the absence of a standard methodology for the study of microplastics in farmland soils, the procedures which have been employed for microplastic separation (density and floatation in 73% of the discussed works), identification and quantification (stereomicroscopy, 77%; infrared analysis, 62%) are addressed to provide a practical work guideline. Finally, we highlight the interaction between microplastics and soil microbiota, fauna and vegetation (negative effects reported in 83% of cases), including crop production (decrease in growth parameters in 63% of the reports). From this review, it can be inferred that microplastics may disrupt the biophysical environment of farmland soil, potentially leading to economic losses and to their entrance into the trophic food chain, affecting human feeding and health.
Study on the Dynamic Cutting Mechanism of Green Pepper (Zanthoxylum armatum) Branches under Optimal Tool Parameters
Authors: Li Yexin , Li Binjie , Jiang Yiyao , Xu Chengrui , Zhou Baidong , Niu Qi , Li Chengsong
Published: August 2022

In order to design a branch-cutting type green pepper harvesting device, we firstly study the whole process of straight knife green pepper cutting to reveal the cutting mechanism and provide theoretical guidance to the design. A finite element model was established for the cutting of pepper branches across the distance, and single-factor and multi-factor finite element simulation tests were conducted on the knife feed angle, tool edge angle, and knife feed speed of the working parts of the pepper cutting and harvesting device. The results of the experiment were analyzed by ANOVA, which showed the different degrees of importance of these factors, and the optimal parameters were obtained by response surface methodology (RSM). With the optimal parameters selected, the predicted maximum cutting force and cutting completion were 803.35 N and 98.58%, respectively, this satisfies the efficiency and economy requirements of agricultural machinery design. In addition, the cutting force of green pepper branches was analyzed and a theoretical mechanical model was developed to help us understand the variation of cutting force numerically. The stress–strain system, high-speed photography system and numerical prediction were innovatively combined to observe and measure the stress and other key state variables in the cutting process in detail, summarize their changing trend, and establish a time-based monitoring and comparison model. The above research results can provide a reference for the design of green pepper branch cutting and harvesting devices, such as direct guidance on the selection of working parameters, materials, etc., and guidance on the operation in actual work.
Meta-Analysis of the Response of the Productivity of Different Crops to Parameters and Processes in Soil Nitrogen Cycle under Biochar Addition
Authors: Zhang Leiyi , Wu Zhuohao , Zhou Jingyan , Zhou Lingli , Lu Yang , Xiang Yangzhou , Zhang Renduo , Deng Qi , Wu Wencheng
Published: August 2022

Biochar addition has been proposed to influence soil nitrogen (N) cycle and improve crop productivity. However, a comprehensive understanding of the impact of soil N cycle on the productivity of different crops under biochar addition remains elusive. Thus, a meta-analysis of 93 peer-reviewed field experiments was undertaken to investigate these outcomes of biochar addition. Results show that biochar addition significantly enhances crop productivity by 13.0%. The productivities of legumes, maize, and wheat were significantly increased by 21.2%, 14.3%, and 8.00% following biochar addition in the fields, respectively. However, the improvement in rice productivity is the lowest (3.36%), insignificant following biochar addition. The aggregated boosted tree, and partial least squares path analyses, indicated that the changes in the soil N pool (i.e., TN, NO3−-N, and NH4+-N) and plant N uptake were the most critical factors in increasing crop productivity under biochar addition. Although biochar addition had no significant enhancement on rice productivity, enhancing field rice nitrogen uptake and modest application of nitrogen fertilizers greatly improved rice productivity. The amount of soil NH4+-N was vital to improving legume productivity rather than biological N2 fixation when biochar was applied. Increases in NH4+-N content and decreasing NO3−-N content were favorable to improving maize productivity under biochar addition. In contrast, biochar additions did not significantly regulate the parameters and processes of soil N cycle to enhance wheat productivity. Overall, the productivity of different types of crops is greatly influenced by soil N cycle under biochar addition.
High-Resolution Mapping and Assessment of Salt-Affectedness on Arable Lands by the Combination of Ensemble Learning and Multivariate Geostatistics
Authors: Hateffard Fatemeh , Balog Kitti , Tóth Tibor , Mészáros János , Árvai Mátyás , Kovács Zsófia Adrienn , Szűcs-Vásárhelyi Nóra , Koós Sándor , László Péter , Novák Tibor József , Pásztor László , Szatmári Gábor
Published: August 2022

Soil salinization is one of the main threats to soils worldwide, which has serious impacts on soil functions. Our objective was to map and assess salt-affectedness on arable land (0.85 km2) in Hungary, with high spatial resolution, using a combination of ensemble machine learning and multivariate geostatistics on three salt-affected soil indicators (i.e., alkalinity, electrical conductivity, and sodium adsorption ratio (n = 85 soil samples)). Ensemble modelling with five base learners (i.e., random forest, extreme gradient boosting, support vector machine, neural network, and generalized linear model) was carried out and the results showed that ensemble modelling outperformed the base learners for alkalinity and sodium adsorption ratio with R2 values of 0.43 and 0.96, respectively, while only the random forest prediction was acceptable for electrical conductivity. Multivariate geostatistics was conducted on the stochastic residuals derived from machine learning modelling, as we could reasonably assume that there is spatial interdependence between the selected salt-affected soil indicators. We used 10-fold cross-validation to check the performance of the spatial predictions and uncertainty quantifications, which provided acceptable results for each selected salt-affected soil indicator (for pH value, electrical conductivity, and sodium adsorption ratio, the root mean square error values were 0.11, 0.86, and 0.22, respectively). Our results showed that the methodology applied in this study is efficient in mapping and assessing salt-affectedness on arable lands with high spatial resolution. A probability map for sodium adsorption ratio represents sodic soils exceeding a threshold value of 13, where they are more likely to have soil structure deterioration and water infiltration problems. This map can help the land user to select the appropriate agrotechnical operation for improving soil quality and yield.
Durum Wheat Response to Organic and Mineral Fertilization with Application of Different Levels and Types of Phosphorus-Based Fertilizers
Authors: Gadaleta Agata , Lacolla Giovanni , Giove Stefania Lucia , Fortunato Stefania , Nigro Domenica , Mastro Mario Alberto , De Corato Ugo , Caranfa Davide , Cucci Giovanna , de Pinto Maria Concetta , Vita Federico
Published: August 2022

The use of green compost is a suitable technology to recycle organic waste into environmentally friendly soil improvement mitigating the pressure on landfills and contributing to sustainability. Among the major nutrients, phosphorus (P) stands at a significant position for seed and fruit quality, photosynthesis, and metabolic function in plants. This work evaluates the effects of different doses of mineral/organic fertilizers on two durum wheat cultivars: Anco Marzio and Vespucci. The fertilization trials compared one unfertilized control test and six treatments performed with different types of fertilizers (four minerals and two organics, based on green compost). Grain yield, compared with the unfertilized control, increased with the mineral fertilization by 125.5% for Anco Marzio and 136.42% for Vespucci, while organic fertilization alone determined an increase of 25.52% and 30.92% for Anco Marzio and Vespucci, respectively. The contribution of a higher dose of phosphorus (140 kg ha−1), combined with nitrogen and potassium, favored a further increase in grain production (+9.34%), compared with 100 kg ha−1. The content of chlorophylls and carotenoids was highly increased (5%) in both the cultivars by all kinds of phosphate fertilization, whereas an increase in the phosphate content of caryopses resulted in Anco Marzio across the two years but not in Vespucci. Among the two cultivars of durum wheat, Vespucci produced a greater quantity of grains but with a less vitreous consistency and poorer in proteins than Anco Marzio. The fertilization management also influenced the wheat behavior to stripe yellow rust attack by showing the highest index severity with the compost-based fertilization. The best management of fertilizers associated with the use of more phosphorus-use-efficient genotypes, are essential for improving quality and for the development of a sustainable agriculture.
Social Licence to Operate: What Can Equestrian Sports Learn from Other Industries?
Authors: Douglas Janet , Owers Roly , Campbell Madeleine L. H.
Published: August 2022

The concept of ‘social licence to operate’ (SLO) is relevant to all animal-use activities. An SLO is an intangible, implicit agreement between the public and an industry/group. Its existence allows that industry/group to pursue its activities with minimal formalised restrictions because such activities have widespread societal approval. In contrast, the imposition of legal restrictions—or even an outright ban—reflect qualified or lack of public support for an activity. This review discusses current threats to equestrianism’s SLO and suggests actions that those across the equine sector need to take to justify the continuation of the SLO. The most important of these is earning the trust of all stakeholders, including the public. Trust requires transparency of operations, establishment and communication of shared values, and demonstration of competence. These attributes can only be gained by taking an ethics-based, proactive, progressive, and holistic approach to the protection of equine welfare. Animal-use activities that have faced challenges to their SLO have achieved variable success in re-establishing the approval of society, and equestrianism can learn from the experience of these groups as it maps its future. The associated effort and cost should be regarded as an investment in the future of the sport.
Synthetic Antimicrobial Immunomodulatory Peptides: Ongoing Studies and Clinical Trials
Authors: Lesiuk Małgorzata , Paduszyńska Małgorzata , Greber Katarzyna E.
Published: August 2022

The increasingly widespread antimicrobial resistance forces the search for new antimicrobial substances capable of fighting infection. Antimicrobial peptides (AMPs) and their synthetic analogs form an extensive group of compounds of great structural diversity and multifunctionality, different modes of antimicrobial action, and considerable market potential. Some AMPs, in addition to their proven antibacterial, antifungal, and antiviral activity, also demonstrate anti-inflammatory and immunomodulatory capabilities; these are called innate defense regulator (IDR) peptides. IDR peptides stimulate or inhibit the body’s immune system, e.g., by stimulating leukocyte migration to the site of infection, driving macrophage differentiation and activation, providing chemotactic action for neutrophils, degranulation and activation of mast cells, altering chemokine and cytokine production, and even induction of angiogenesis and wound healing. Such multifunctional immunomodulatory peptide molecules are currently being investigated and developed. Exploring and utilizing IDR peptides as an indirect weapon against infectious diseases could represent a completely new strategy to cope with the issue of antimicrobial resistance.
The Glyoxalase System Is a Novel Cargo of Amniotic Fluid Stem-Cell-Derived Extracellular Vesicles
Authors: Romani Rita , Talesa Vincenzo Nicola , Antognelli Cinzia
Published: August 2022

The glyoxalase system is a ubiquitous cellular metabolic pathway whose main physiological role is the removal of methylglyoxal (MG). MG, a glycolysis byproduct formed by the spontaneous degradation of triosephosphates glyceraldehyde-3-phosphate (GA3P) and dihydroxyacetonephosphate (DHAP), is an arginine-directed glycating agent and precursor of the major advanced glycation end product arginine-derived, hydroimidazolone (MG-H1). Extracellular vesicles (EVs) are a heterogeneous family of lipid-bilayer-vesicular structures released by virtually all living cells, involved in cell-to-cell communication, specifically by transporting biomolecules to recipient cells, driving distinct biological responses. Emerging evidence suggests that included in the EVs cargo there are different metabolic enzymes. Specifically, recent research has pointed out that EVs derived from human amniotic fluid stem cell (HASC-EVs) contain glycolytic pay-off phase enzymes, such as glyceraldehyde-3-phosphate dehydrogenase (GAPDH). Since GAPDH catalyzes the sixth step of glycolysis using as a substrate GA3P, from which MG spontaneously origins, we wanted to investigate whether MG-derived MG-H1, as well as glyoxalases, could be novel molecule cargo in these EVs. By using immunoassays and spectrophotometric methods, we found, for the first time ever, that HASC-EVs contain functional glyoxalases and MG-H1, pioneering research to novel and exciting roles of these eclectic proteins, bringing them to the limelight once more.
Functional Characterization of Arylalkylamine N-Acetyltransferase, a Pivotal Gene in Antioxidant Melatonin Biosynthesis from Chlamydomonas reinhardtii
Authors: Hwang Ok-Jin , Back Kyoungwhan
Published: August 2022

Arylalkylamine N-acetyltransferase (AANAT) is a pivotal enzyme in melatonin biosynthesis that catalyzes the conversion of serotonin to N-acetylserotonin. Homologs of animal AANAT genes are present in animals, but not in plants. An AANAT homolog was found in Chlamydomonas reinhardtii, but not other green algae. The characteristics of C. reinhardtii AANAT (CrAANAT) are unclear. Here, full-length CrAANAT was chemically synthesized and expressed in Escherichia coli. Recombinant CrAANAT exhibited AANAT activity with a Km of 247 μM and Vmax of 325 pmol/min/mg protein with serotonin as the substrate. CrAANAT was localized to the cytoplasm in tobacco leaf cells. Transgenic rice plants overexpressing CrAANAT (CrAANAT-OE) exhibited increased melatonin production. CrAANAT-OE plants showed a longer seed length and larger second leaf angle than wild-type plants, indicative of the involvement of brassinosteroids (BRs). As expected, BR biosynthesis- and signaling-related genes such as D2, DWARF4, DWARF11, and BZR1 were upregulated in CrAANAT-OE plants. Therefore, an increased endogenous melatonin level by ectopic overexpression of CrAANAT seems to be closely associated with BR biosynthesis, thereby influencing seed size.
Design Optimization and Electromagnetic Performance Analysis of an Axial-Flux Permanent Magnet Brushless DC Motor with Unequal-Thickness Magnets
Authors: Wu Shasha , Wang Baojian , Zhang Tao , Gu Quanhao
Published: August 2022

To improve electromagnetic performance, an axial-flux permanent magnet brushless DC motor (AFPMBLDCM) with unequal-thickness arc permanent magnets is proposed in this paper. Firstly, the structure and magnetic circuit of the AFPMBLDCM with unequal-thickness arc permanent magnets were designed. Then, the mathematical models and design method of the main parameters were derived. According to the rated power and rated speed, the main parameters were further designed, and the analytical model was established by using Maxwell 3D. The air-gap flux density, back electromotive force (EMF) and torque under no-load and load conditions were calculated and analyzed to verify the validity of the model and design. Finally, based on a parameter scanning optimization method, the effects of the permanent magnet thickness, pole arc coefficient and permanent magnet radius on cogging torque were analyzed. The optimized parameters of the AFPMBLDCM with unequal-thickness arc permanent magnets were obtained. The results show that the sinusoidal degree of the air-gap magnetic field is improved, and the maximum torque ripple of the AFPMBLDCM is reduced to 2.92%.
Effects of Converging Sidewalls on Skimming Flow over Converging Stepped Spillway
Authors: Chen Yuling , Liu Guangyuan , Qian Shangtuo , Xu Hui , Feng Jiangang , Wang Xiaosheng
Published: August 2022

A numerical study is conducted for converging stepped spillways with various spillway slopes, sidewall convergence and flow discharges to understand the influences of converging sidewalls on skimming flows. Compared with the traditional uniform-width stepped spillway, the converging sidewall changes the skimming flow features by generating standing waves on the free-surface, curving the mainstream streamlines and squeezing and distorting the bottom rotations. For free-surface, mainstream and bottom rotations, the width of disturbed regions by the converging sidewall varies, with that for bottom rotations being 1.5 times that for mainstream and 3 times that for free-surface. The variation rules of disturbed region widths along the spillway are obtained, and the maximum widths increase as the convergence angle and incoming flow discharge increase, and the spillway slope decreases. Three equations are established for predicting the maximum widths of disturbed regions for free-surface, mainstream and bottom rotations of skimming flow. Since the disturbed region of skimming flow generated by the converging sidewall is characterized by strong standing waves, high flow velocity and low air concentration, appropriate engineering measurements should be taken for the disturbed region to meet the challenges to overtopping, energy dissipation and cavitation control.
Eigenmode Wavefront Decoupling Algorithm for LC–DM Adaptive Optics Systems
Authors: Wang Yukun , Li Dayu , Jin Chengbin
Published: August 2022

To realize the decoupling control of the dual corrector of liquid crystal (LC)–deformable mirror (DM) adaptive optics (AO) systems and prevent the loss of correction ability induced by coupling aberrations, a wavefront decoupling method based on DM eigenmodes was proposed. The coupling relationship of two correctors was studied, and the distribution of aberrations corrected using the DM and LC was investigated. First, a DM eigenmode matrix was derived according to the DM influence function. Then, aberrations were decomposed according to the Strehl ratio, and the projection of the LC response matrix on the DM eigenmode matrix, that is, the coupling term, was derived. Before using the LC corrector, the coupling item was eliminated for the decoupling of the two correctors, and the decoupling effect was verified through simulations. Finally, a 2 m telescope LC–DM AO system was developed to validate the proposed method. The simulation and experimental results showed that the root mean square of the DM-corrected residual after 55 eigenmodes’ correction was 0.09 μm. After decoupling correction, the resolution of the 700–1700 nm wide band improved from 1.1 to 1 times the diffraction limit, which is 1.2 times better than that obtained using the traditional Zernike mode correction.
4D Printing of Multicomponent Shape-Memory Polymer Formulations
Authors: Razzaq Muhammad Yasar , Gonzalez-Gutierrez Joamin , Mertz Gregory , Ruch David , Schmidt Daniel F. , Westermann Stephan
Published: August 2022

Four-dimensional (4D) printing technology, as a next-generation additive manufacturing method, enables printed objects to further change their shapes, functionalities, or properties upon exposure to external stimuli. The 4D printing of programmable and deformable materials such as thermo-responsive shape-memory polymers (trSMPs), which possess the ability to change shape by exposure to heat, has attracted particular interest in recent years. Three-dimensional objects based on SMPs have been proposed for various potential applications in different fields, including soft robotics, smart actuators, biomedical and electronics. To enable the manufacturing of complex multifunctional 3D objects, SMPs are often coupled with other functional polymers or fillers during or before the 3D printing process. This review highlights the 4D printing of state-of-the-art multi-component SMP formulations. Commonly used 4D printing technologies such as material extrusion techniques including fused filament fabrication (FFF) and direct ink writing (DIW), as well as vat photopolymerization techniques such as stereolithography (SLA), digital light processing (DLP), and multi-photon polymerization (MPP), are discussed. Different multicomponent SMP systems, their actuation methods, and potential applications of the 3D printed objects are reviewed. Finally, current challenges and prospects for 4D printing technology are summarized.
Distributed Ledger Technologies and Their Applications: A Review
Authors: Soltani Reza , Zaman Marzia , Joshi Rohit , Sampalli Srinivas
Published: August 2022

With the success of Bitcoin and the introduction of different uses of Blockchain, such as smart contracts in Ethereum, many researchers and industries have turned their attention to applications that use this technology. In response to the advantages and disadvantages of Blockchain, similar technologies have emerged with alterations to the original structure. Distributed ledger technology (DLT) is a generalized distributed technology encompassing these new variants. Several studies have examined the challenges and applications of Blockchain technology. This article explores the possibilities of using different DLTs to solve traditional distributed computing problems based on their advantages and disadvantages. In this paper, we provide an overview and comparison of different DLTs, such as Hashgraph, Tangle, Blockchains, Side Chain and Holochain. The main objective of the article is to examine whether distributed ledger technologies can replace traditional computational methods in other areas instead of traditional methods. Based on the primary keywords, we conducted a systematic review of more than 200 articles. Based on the data extracted from articles related to the use of DLT, we conclude that that DLTs can complement other methods, but cannot completely replace them. Furthermore, several DLTs such as Sidechain, Holochain and Hashgraph are still in their infancy, and we foresee much research work in this area in the coming years.
STDecoder-CD: How to Decode the Hierarchical Transformer in Change Detection Tasks
Authors: Zhao Bo , Luo Xiaoyan , Tang Panpan , Liu Yang , Wan Haoming , Ouyang Ninglei
Published: August 2022

Change detection (CD) is in demand in satellite imagery processing. Inspired by the recent success of the combined transformer-CNN (convolutional neural network) model, TransCNN, originally designed for image recognition, in this paper, we present STDecoder-CD for change detection applications, which is a combination of the Siamese network (“S”), the TransCNN backbone (“T”), and three types of decoders (“Decoder”). The Type I model uses a UNet-like decoder, and the Type II decoder is defined by a combination of three modules: the difference detector, FPN (feature pyramid network), and FCN (fully convolutional network). The Type III model updates the change feature map by introducing a transformer decoder. The effectiveness and advantages of the proposed methods over the state-of-the-art alternatives were demonstrated on several CD datasets, and experimental results indicate that: (1) STDecoder-CD has excellent generalization ability and has strong robustness to pseudo-changes and noise. (2) An end-to-end CD network architecture cannot be completely free from the influence of the decoding strategy. In our case, the Type I decoder often obtained finer details than Types II and III due to its multi-scale design. (3) Using the ablation or replacing strategy to modify the three proposed decoder architectures had a limited impact on the CD performance of STDecoder-CD. To the best of our knowledge, we are the first to investigate the effect of different decoding strategies on CD tasks.
Performance Analysis of Wavelength Division Multiplexing-Based Passive Optical Network Protection Schemes by Means of the Network Availability Evaluator
Authors: Róka Rastislav
Published: August 2022

This paper is focused on the performance analysis of protection mechanisms utilized in common wavelength division multiplexing-based passive optical networks. The main aim of the proposed research is providing an option of comparing different traffic protection scenarios for advanced optical network designs, evaluating their possible realizations from a viewpoint of the total optical power budget and analyzing their network availabilities with accommodation to concrete optical access infrastructures. First, a short basic classification of passive optical network architectures utilizing advanced wavelength division multiplexing techniques is introduced. Second, considered presumptive protection scenarios deployed to this kind of passive optical networks involved in the performance analysis are presented. For the performance analysis, corresponding reliability diagrams, relations and formulas used for the calculation of the total network availability are prepared for any specific scenario. In addition, the optical power budget is considered and subsequently evaluated for each protection scheme. For evaluating possible migration scenarios related to considered protection schemes and for comparing protection possibilities of various passive optical networks, a realization of the appropriate simulation tool must be executed. The simulation program utilizes specific parameters of particular optical components utilized in a selected protection scheme and presents its resultant network availability. Values of considered specific parameters can be changed according to the well-known data resources or specific network operator’s data. Subsequently, relevant simulation results obtained by the Network Availability Evaluator that can provide insights into relationships between a number of protection schemes are used for the performance analysis. Finally, an evaluation of the total network availability for considered traffic protection scenarios utilized in passive optical networks with advanced wavelength division multiplexing is included.
A Review of Blockchain-Based Secure Sharing of Healthcare Data
Authors: Xi Peng , Zhang Xinglong , Wang Lian , Liu Wenjuan , Peng Shaoliang
Published: August 2022

Medical data contains multiple records of patient data that are important for subsequent treatment and future research. However, it needs to be stored and shared securely to protect the privacy of the data. Blockchain is widely used in the management of healthcare data because of its decentralized and tamper-proof features. In order to study the development of blockchain in healthcare, this paper evaluates it from various perspectives. We analyze blockchain-based approaches from different application scenarios. These are blockchain-based electronic medical record sharing, blockchain and the Internet of Medical Things and blockchain-based federal learning. The results show that blockchain and smart contracts have a natural advantage in the field of medical data since they are tamper-proof and traceable. Finally, the challenges and future directions of blockchain in healthcare are discussed, which can help drive the field forward.
Lincomycin Administration against Persistent Multi-Drug Resistant Chronic Endometritis in Infertile Women with a History of Repeated Implantation Failure
Authors: Kitaya Kotaro , Ishikawa Tomomoto
Published: August 2022

Chronic endometritis (CE) is an infectious disease of the uterine lining, which is characterized by endometrial stromal plasmacyte (ESPC) infiltration. CE is often seen in infertile women with a history of repeated implantation failure (RIF) following an in vitro fertilization-embryo transfer program, recurrent pregnancy loss, and unknown etiology. Oral antibiotic agents, such as doxycycline, metronidazole, ciprofloxacin, azithromycin, and moxifloxacin, have been prescribed and are effective in the treatment of CE. Multi-drug resistance (MDR), however, is an emerging issue, as in other medical fields. We report six cases of persistent MDR-CE in infertile women who were resistant to all the aforementioned antibiotic agents. The bacterial genera and microbial communities unique to persistent MDR-CE were not identified in their vaginal secretions and/or endometrial fluid. Oral lincomycin administration (14 days, 1500 mg/day) was effective in the eradication of ESPCs in these women. In the embryo transfer cycles following histopathologic confirmation of cure (elimination of ESPCs) of persistent MDR-CE, three out of them had a successful live birth.
Analysis of MONARC and ACTIVATE Airborne Aerosol Data for Aerosol-Cloud Interaction Investigations: Efficacy of Stairstepping Flight Legs for Airborne In Situ Sampling
Authors: Dadashazar Hossein , Crosbie Ewan , Choi Yonghoon , Corral Andrea F. , DiGangi Joshua P. , Diskin Glenn S. , Dmitrovic Sanja , Kirschler Simon , McCauley Kayla , Moore Richard H. , Nowak John B. , Robinson Claire E. , Schlosser Joseph , Shook Michael , Thornhill Kenneth Lee , Voigt Christiane , Winstead Edward L. , Ziemba Luke D. , Sorooshian Armin
Published: August 2022

A challenging aspect of conducting airborne in situ observations of the atmosphere is how to optimize flight plans for specific objectives and constraints associated with weather and flight restrictions. For aerosol-cloud interaction research, two recent campaigns utilized a “stairstepping” approach whereby an aircraft conducts level legs at various altitudes while moving forward with each subsequent leg: the 2019 MONterey Aerosol Research Campaign (MONARC) over the northeast Pacific and the 2020–2022 Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) over the northwest Atlantic. We examine the homogeneity of several atmospheric variables both vertically and horizontally in the marine boundary layer with a focus on the sub-cloud environment. In well-mixed boundary layers, there was generally good horizontal and vertical homogeneity in potential temperature, winds, water vapor mixing ratio, various trace gases, and many aerosol variables. Selected aerosol variables exhibited the most variability owing to sensitivity to humidity and near-cloud conditions (supermicrometer aerosol concentrations), coastal pollution gradients (e.g., organic aerosol mass), and small spatial scale phenomena such as new particle formation (aerosol number concentration for particles with diameter >3 nm). Illustrative cases are described when stairstepping can pose issues requiring extra caution for data analysis: (i) poor vertical mixing and layers decoupled from those below; (ii) multiple cloud layers; (iii) fluctuating cloud base/top and boundary layer top heights; and (iv) horizontal variability across specific features leading to sharp gradients such as right near coastlines and over the Gulf Stream with strong sea surface temperature changes. Results from this study provide a guide both for future studies aiming to examine these mission datasets and for designing new airborne campaigns.
Using an Ensemble Filter to Improve the Representation of Temporal Source Variations in a Volcanic Ash Forecasting System
Authors: Zidikheri Meelis J.
Published: August 2022

The use of ensemble models to forecast the dispersion and transport of airborne volcanic ash in operational contexts is increasingly being explored. The ensemble members are usually constructed to represent a priori uncertainty estimates in meteorological fields and volcanic ash source parameters. Satellite data can be used to further filter ensemble members within an analysis time window by rejecting poorly performing members, leading to improved forecasts. In this study, the ensemble filtering technique is used to improve the representation of temporal source variations. Ensemble members are initially created by representing the source time variations as random functions of time that are modulated by crude initial estimates of the variations estimated from satellite imagery. Ensemble filtering is then used to remove members whose fields match poorly with observations within a specified analysis time window that are represented by satellite retrievals of volcanic ash properties such as mass load, effective radius, and cloud top height. The filtering process leads to an ensemble with statistics in closer agreement with the observations. It is shown in the context of the 30 May 2014 Sangeang Api eruption case study that this method leads to significantly enhanced forecasting skill beyond the analysis time window—about 20% improvement on average—when compared to a system that assumes constant emission rates for the duration of the eruption, as is the case in many operational volcanic ash forecasting systems.
Assessing the Impact of Lightning NOx Emissions in CMAQ Using Lightning Flash Data from WWLLN over the Contiguous United States
Authors: Kang Daiwen , Hogrefe Christian , Sarwar Golam , East James D. , Madden J. Mike , Mathur Rohit , Henderson Barron H.
Published: August 2022

Comparison of lightning flash data from the National Lightning Detection Network (NLDN) and from the World Wide Lightning Location Network (WWLLN) over the contiguous United States (CONUS) for the 2016–2018 period reveals temporally and spatially varying flash rates that would influence lightning NOx (LNOx) production due to known detection efficiency differences especially during summer months over land (versus over ocean). However, the lightning flash density differences between the two networks show persistent seasonal patterns over geographical regions (e.g., land versus ocean). Since the NLDN data are considered to have higher accuracy (lightning detection with >95% efficiency), we developed scaling factors for the WWLLN flash data based on the ratios of WWLLN to NLDN flash data over time (months of year) and space. In this study, sensitivity simulations using the Community Multiscale Air Quality (CMAQ) model are performed utilizing the original data sets (both NLDN and WWLLN) and the scaled WWLLN flash data for LNOx production over the CONUS. The model performance of using the different lightning flash datasets for ambient O3 and NOx mixing ratios that are directly impacted by LNOx emissions and the wet and dry deposition of oxidized nitrogen species that are indirectly impacted by LNOx emissions is assessed based on comparisons with ground-based observations, vertical profile measurements, and satellite products. During summer months, the original WWLLN data produced less LNOx emissions (due to its lower lightning detection efficiency) compared to the NLDN data, which resulted in less improvement in model performance than the simulation using NLDN data as compared to the simulation without any LNOx emissions. However, the scaled WWLLN data produced LNOx estimates and model performance comparable with the NLDN data, suggesting that scaled WWLLN may be used as a substitute for the NLDN data to provide LNOx estimates in air quality models when the NLDN data are not available (e.g., due to prohibitive cost or lack of spatial coverage).
Hydrogen Sulfide Emission Properties from Two Large Landfills in New York State
Authors: Catena Alexandra M. , Zhang Jie , Commane Roisin , Murray Lee T. , Schwab Margaret J. , Leibensperger Eric M. , Marto Joseph , Smith Mackenzie L. , Schwab James J.
Published: August 2022

Landfills are a source of malodors, greenhouse gases, harmful pollutants, pests, noise, and litter. To reduce their impact on neighboring communities, landfill facilities and the policies they follow must reduce emissions of trace gases such as hydrogen sulfide (H2S) and methane (CH4). However, a comprehensive understanding of the spatial variability of both pollutants at landfills should first be established to obtain a clear picture of emissions at landfills. This study measured the mixing ratios of H2S and CH4 at two landfills in New York State (Fresh Kills Landfill and Seneca Meadows Landfill) in November 2021 using laser-based methods deployed in a mobile lab. H2S emission fluxes were estimated based on a mass balance calculation. The highest mixing ratios of both H2S and CH4 were measured at Fresh Kills Landfill, at up to 7 parts per billion (ppb) and ~140 parts per million (ppm), respectively, yet these values resulted in a low ΔH2S/ΔCH4 ratio, at approximately 5.2 ± 2.6 × 10−5 mol mol−1 and a H2S emission flux of 0.02 ± 0.01 mg m−2 day−1. The highest ΔH2S/ΔCH4 ratio was observed at the Seneca Meadows Landfill at 8.6 ± 4.3 × 10−4 mol mol−1 and yielded a H2S emission flux estimate of 17.7 ± 12.9 mg m−2-day−1. The variability in mixing ratios and ΔH2S/ΔCH4 ratios measured at the landfills can be attributed to various factors, including facility operations and design, landfill age, meteorology, types of waste, and pH levels, but further multiday measurements are needed at each landfill to improve emission estimates and determine a more accurate and resolute reasoning behind these variations.
Towards Strong Convergence and Cauchy Sequences in Binary Metric Spaces
Authors: Yadav Shubham , Gopal Dhananjay , Chaipunya Parin , Martínez-Moreno Juan
Published: August 2022

A Kuratowski topology is a topology specified in terms of closed sets rather than open sets. Recently, the binary metric was introduced as a symmetric, distributive-lattice-ordered magma-valued function of two variables satisfying a “triangle inequality” and subsequently proved that every Kuratowski topology can be induced by such a binary metric. In this paper, we define the strong convergence of a sequence in a binary metric space and prove that strong convergence implies convergence. We state the conditions under which strong convergence is equivalent to convergence. We define a strongly Cauchy sequence and a strong complete binary metric space. Finally, we give the strong completion of all binary metric spaces with a countable indexing set.
Bifurcation Results for Periodic Third-Order Ambrosetti-Prodi-Type Problems
Authors: Minhós Feliz , Oliveira Nuno
Published: August 2022

This paper presents sufficient conditions for the existence of a bifurcation point for nonlinear periodic third-order fully differential equations. In short, the main discussion on the parameter s about the existence, non-existence, or the multiplicity of solutions, states that there are some critical numbers σ0 and σ1 such that the problem has no solution, at least one or at least two solutions if s<σ0, s=σ0 or σ0>s>σ1, respectively, or with reversed inequalities. The main tool is the different speed of variation between the variables, together with a new type of (strict) lower and upper solutions, not necessarily ordered. The arguments are based in the Leray–Schauder’s topological degree theory. An example suggests a technique to estimate for the critical values σ0 and σ1 of the parameter.
Functional Connectivity Alterations Based on Hypometabolic Region May Predict Clinical Prognosis of Temporal Lobe Epilepsy: A Simultaneous 18F-FDG PET/fMRI Study
Authors: Shan Yi , Zhou Hu-Cheng , Shang Kun , Cui Bi-Xiao , Fan Xiao-Tong , Zhang Qi , Shan Yong-Zhi , Jiang Jie-Hui , Zhao Guo-Guang , Lu Jie
Published: August 2022

(1) Background: Accurate localization of the epileptogenic zone and understanding the related functional connectivity (FC) alterations are critical for the prediction of clinical prognosis in patients with temporal lobe epilepsy (TLE). We aim to localize the hypometabolic region in TLE patients, compare the differences in FC alterations based on hypometabolic region and structural lesion, respectively, and explore their relationships with clinical prognosis. (2) Methods: Thirty-two TLE patients and 26 controls were recruited. Patients underwent 18F-FDG PET/MR scan, surgical treatment, and a 2–3-year follow-up. Visual assessment and voxel-wise analyses were performed to identify hypometabolic regions. ROI-based FC analyses were performed. Relationships between clinical prognosis and FC values were performed by using Pearson correlation analyses and receiver operating characteristic (ROC) analysis. (3) Results: Hypometabolic regions in TLE patients were found in the ipsilateral hippocampus, parahippocampal gyrus, and temporal lobe (p < 0.001). Functional alterations based on hypometabolic regions showed a more extensive whole-brain FC reduction. FC values of these regions negatively correlated with epilepsy duration (p < 0.05), and the ROC curve of them showed significant accuracy in predicting postsurgical outcome. (4) Conclusions: In TLE patients, FC related with hypometabolic region obtained by PET/fMRI may provide value in the prediction of disease progression and seizure-free outcome.
Evaluating the Phenotypic and Genomic Characterization of Some Egyptian Phages Infecting Shiga Toxin-Producing Escherichia coli O157:H7 for the Prospective Application in Food Bio-Preservation
Authors: El-Sayed Dina , Elsayed Tarek , Amin Nadia , Al-Shahaby Ahmad , Goda Hanan
Published: August 2022

Shiga toxin-producing E. coli (STEC) is considered a worldwide public health and food safety problem. Despite the implementation of various different approaches to control food safety, outbreaks persist. The aim of study is to evaluate the applicability of phages, isolated against STEC O157:H7, as prospective food bio-preservatives. Considering the relatively wide host range and greatest protein diversity, two phages (STEC P2 and P4) from four were furtherly characterized. Complete genome analysis confirmed the absence of toxins and virulence factors—encoding genes. The results confirmed the close relation of STEC P2 to phages of Myoviridae, and STEC P4 to the Podoviridae family. The phages retained higher lytic competence of 90.4 and 92.68% for STEC P2 and P4, respectively with the HTST pasteurization. The strong acidic (pH 1) and alkaline (pH 13) conditions had influential effect on the surviving counts of the two phages. The lowest survivability of 63.37 and 86.36% in STEC P2 and P4 lysate, respectively appeared in 2% bile salt solution after 3 h. The results confirmed the strong effect of simulated gastric fluid (SGF) on the survivability of the two phages comparing with simulated intestinal fluid (SIF). Therefore, the two phages could be applied as a natural alternative for food preservation.
In Silico and In Vitro Analysis of MAP3773c Protein from Mycobacterium avium subsp. Paratuberculosis
Authors: Hernández-Guevara Esteban , Gutiérrez-Pabello José A. , Quintero-Chávez Kaina , Brito-Perea Mirna Del Carmen , Hurtado-Ayala Lilia Angélica , Ibarra-Molina German , Cortez-Hernández Omar , Dueñas-Mena Dulce Liliana , Fernández-Otal Ángela , Fillat María F. , Landeros-Sánchez Bertha
Published: August 2022

Paratuberculosis is a disease caused by Mycobacterium avium subsp. paratuberculosis (MAP). It is of great interest to better understand the proteins involved in the pathogenicity of this organism in order to be able to identify potential therapeutic targets and design new vaccines. The protein of interest–MAP3773c–was investigated, and molecular modeling in silico, docking, cloning, expression, purification, and partial characterization of the recombinant protein were achieved. In the in silico study, it was shown that MAP3773c of MAP has 34% sequence similarity with Mycobacterium tuberculosis (MTB) FurB, which is a zinc uptake regulator (Zur) protein. The docking data showed that MAP3773c exhibits two metal-binding sites. The presence of structural Zn2+ in the purified protein was confirmed by SDS-PAGE PAR staining. The purification showed one band that corresponded to a monomer, which was confirmed by liquid chromatography–mass spectrometry (LC-MS). The presence of a monomer was verified by analyzing the native protein structure through BN-SDS-PAGE (Native Blue (BN) Two-Dimensional Electrophoresis) and BN–Western blotting. The MAP3773c protein contains structural zinc. In conclusion, our results show that MAP3773c displays the features of a Fur-type protein with two metal-binding sites, one of them coordinating structural Zn2+.
Vitamin A Deficiency Alters the Phototransduction Machinery and Distinct Non-Vision-Specific Pathways in the Drosophila Eye Proteome
Authors: Kumar Mukesh , Has Canan , Lam-Kamath Khanh , Ayciriex Sophie , Dewett Deepshe , Bashir Mhamed , Poupault Clara , Schuhmann Kai , Knittelfelder Oskar , Raghuraman Bharath Kumar , Ahrends Robert , Rister Jens , Shevchenko Andrej
Published: August 2022

The requirement of vitamin A for the synthesis of the visual chromophore and the light-sensing pigments has been studied in vertebrate and invertebrate model organisms. To identify the molecular mechanisms that orchestrate the ocular response to vitamin A deprivation, we took advantage of the fact that Drosophila melanogaster predominantly requires vitamin A for vision, but not for development or survival. We analyzed the impacts of vitamin A deficiency on the morphology, the lipidome, and the proteome of the Drosophila eye. We found that chronic vitamin A deprivation damaged the light-sensing compartments and caused a dramatic loss of visual pigments, but also decreased the molar abundance of most phototransduction proteins that amplify and transduce the visual signal. Unexpectedly, vitamin A deficiency also decreased the abundances of specific subunits of mitochondrial TCA cycle and respiratory chain components but increased the levels of cuticle- and lens-related proteins. In contrast, we found no apparent effects of vitamin A deficiency on the ocular lipidome. In summary, chronic vitamin A deficiency decreases the levels of most components of the visual signaling pathway, but also affects molecular pathways that are not vision-specific and whose mechanistic connection to vitamin A remains to be elucidated.