bluuebunny/crossref_metadata_2025 huggingface dataset:
Mechanism for Utilization of the Populus-Derived Metabolite Salicin by a Pseudomonas—Rahnella Co-Culture
Authors: Dahal Sanjeev , Hurst Gregory , Chourey Karuna , Engle Nancy , Burdick Leah , Morrell-Falvey Jennifer , Tschaplinski Timothy , Doktycz Mitchel , Pelletier Dale
Published: January 2023

Pseudomonas fluorescens GM16 associates with Populus, a model plant in biofuel production. Populus releases abundant phenolic glycosides such as salicin, but P. fluorescens GM16 cannot utilize salicin, whereas Pseudomonas strains are known to utilize compounds similar to the aglycone moiety of salicin–salicyl alcohol. We propose that the association of Pseudomonas to Populus is mediated by another organism (such as Rahnella aquatilis OV744) that degrades the glucosyl group of salicin. In this study, we demonstrate that in the Rahnella–Pseudomonas salicin co-culture model, Rahnella grows by degrading salicin to glucose 6-phosphate and salicyl alcohol which is secreted out and is subsequently utilized by P. fluorescens GM16 for its growth. Using various quantitative approaches, we elucidate the individual pathways for salicin and salicyl alcohol metabolism present in Rahnella and Pseudomonas, respectively. Furthermore, we were able to establish that the salicyl alcohol cross-feeding interaction between the two strains on salicin medium is carried out through the combination of their respective individual pathways. The research presents one of the potential advantages of salicyl alcohol release by strains such as Rahnella, and how phenolic glycosides could be involved in attracting multiple types of bacteria into the Populus microbiome.
Modeling and Prediction of Water-Jet-Guided Laser Cutting Depth for Inconel 718 Material Using Response Surface Methodology
Authors: Zhao Chuang , Zhao Yugang , Zhao Dandan , Liu Qian , Meng Jianbing , Cao Chen , Zheng Zhilong , Li Zhihao , Yu Hanlin
Published: January 2023

In this study, the water-jet-guided laser (WJGL) method was used to cut Inconel 718 alloy with high temperature resistance. The effect of critical parameters of the water-jet-guided laser machining method on the cutting depth was studied by a Taguchi orthogonal experiment. Furthermore, the mathematical prediction model of cutting depth was established by the response surface method (RSM). The validation experiments showed that the mathematical model had a high predictive ability for cutting depth. The optimal cutting depth was obtained by model prediction, and the error was 5.5% compared with the experimental results. Compared with the traditional dry laser cutting, the water conducting laser method reduced the thermal damage and improved the cutting quality. This study provides a reference for the precision machining of Inconel 718 with a water-jet-guided laser.
Evaluation of Bacterial Composition and Viability of Equine Feces after Processing for Transplantation
Authors: Loublier Clémence , Taminiau Bernard , Heinen Julia , Lecoq Laureline , Amory Hélène , Daube Georges , Cesarini Carla
Published: January 2023

Fecal microbiota transplantation (FMT) has been used empirically for decades in equine medicine to treat intestinal dysbiosis but evidence-based information is scarce. This in vitro study aimed at assessing the effect of a commonly used pre-FMT processing method on the bacterial composition and viability of the fecal filtrate. Three samples of fresh equine manure (T0) were processed identically: the initial manure was mixed with 1 L of lukewarm water and chopped using an immersion blender to obtain a mixture (T1), which was left uncovered during 30 min (T2) and percolated through a sieve to obtain a fecal filtrate (T3). Samples were taken throughout the procedure (Tn) and immediately stored at 4 °C until processing. The 16S rDNA amplicon profiling associated with propidium monoazide treatment was performed on each sample to select live bacteria. Analyses of α and β diversity and main bacterial populations and quantitative (qPCR) analysis were performed and statistically compared (significance p < 0.05) between time points (T0–T3). No significant differences in ecological indices or mean estimated total living bacteria were found in the final fecal filtrate (T3) in regard to the original manure (T0); however, relative abundances of some minor genera (Fibrobacter, WCHB1-41_ge and Akkermansia) were significantly different in the final filtrate. In conclusion, the results support the viability of the major bacterial populations in equine feces when using the described pre-FMT protocol.
Biochemical Pilot Study on Effects of Pomegranate Seed Oil Extract and Cosmetic Cream on Neurologically Mediated Skin Inflammation in Animals and Humans: A Comparative Observational Study
Authors: Hamouda Asmaa Fathi , Felemban Shifa
Published: January 2023

The presence of phenobarbital and formaldehyde in drugs, food, and beverages can lead to various health issues, including inflammation, oncogenesis, and neurological distress. Psychological stress leads to mood fluctuations and the onset of skin inflammation. Skin inflammation has a range of causes, including chemicals, heavy metals, infection, immune-related disorders, genetics, and stress. The various treatments for skin inflammation include medical and cosmetic creams, diet changes, and herbal therapy. In this study, we investigated the effects of Avocom-M and pomegranate seed oil extract (PSOE) against phenobarbital- and formaldehyde-induced skin biochemical changes in rats. We analyzed the constituents of PSOE using gas chromatography–mass spectrometry and inductively coupled plasma–mass spectrometry. We also observed biochemical changes in the skin of human volunteers with and without TROSYD and PSOE as a skin cream. We compared the biochemical changes in human volunteers’ skin before treatment and 21 days after the treatment stopped. The outcomes showed an improvement in the rats’ biochemical status, due to PSOE and Avocom-M treatment. The human volunteers treated with TROSYD and PSOE showed substantial amelioration of skin inflammation. PSOE, Avocom-M, and TROSYD produced beneficial effects by reducing the levels of cyclooxygenase-2, lipid peroxidation, tyrosinase, hyaluronidase, elastase, collagenase, and nitric oxide in the animals tested on and in human volunteers.
Identifying Systematic Force Field Errors Using a 3D-RISM Element Counting Correction
Authors: Casillas Lizet , Grigorian Vahe M. , Luchko Tyler
Published: January 2023

Hydration free energies of small molecules are commonly used as benchmarks for solvation models. However, errors in predicting hydration free energies are partially due to the force fields used and not just the solvation model. To address this, we have used the 3D reference interaction site model (3D-RISM) of molecular solvation and existing benchmark explicit solvent calculations with a simple element count correction (ECC) to identify problems with the non-bond parameters in the general AMBER force field (GAFF). 3D-RISM was used to calculate hydration free energies of all 642 molecules in the FreeSolv database, and a partial molar volume correction (PMVC), ECC, and their combination (PMVECC) were applied to the results. The PMVECC produced a mean unsigned error of 1.01±0.04kcal/mol and root mean squared error of 1.44±0.07kcal/mol, better than the benchmark explicit solvent calculations from FreeSolv, and required less than 15 s of computing time per molecule on a single CPU core. Importantly, parameters for PMVECC showed systematic errors for molecules containing Cl, Br, I, and P. Applying ECC to the explicit solvent hydration free energies found the same systematic errors. The results strongly suggest that some small adjustments to the Lennard–Jones parameters for GAFF will lead to improved hydration free energy calculations for all solvent models.
Design and Synthesis of New Modified Flexible Purine Bases as Potential Inhibitors of Human PNP
Authors: Khandazhinskaya Anastasia , Fateev Ilja , Eletskaya Barbara , Maslova Anna , Konstantinova Irina , Seley-Radtke Katherine , Kochetkov Sergey , Matyugina Elena
Published: January 2023

The great interest in studying the structure of human purine nucleoside phosphorylase (hPNP) and the continued search for effective inhibitors is due to the importance of the enzyme as a target in the therapy of T-cell proliferative diseases. In addition, hPNP inhibitors are used in organ transplant surgeries to provide immunodeficiency during and after the procedure. Previously, we showed that members of the well-known fleximer class of nucleosides are substrates of E. coli PNP. Fleximers have great promise as they have exhibited significant biological activity against a number of viruses of pandemic concern. Herein, we describe the synthesis and inhibition studies of a series of new fleximer compounds against hPNP and discuss their possible binding mode with the enzyme. At a concentration of 2 mM for the flex-7-deazapurines 1–4, a decrease in enzymatic activity by more than 50% was observed. 4-Amino-5-(1H-pyrrol-3-yl)pyridine 2 was the best inhibitor, with a Ki = 0.70 mM. Docking experiments have shown that ligand 2 is localized in the selected binding pocket Glu201, Asn243 and Phe200. The ability of the pyridine and pyrrole fragments to undergo rotation around the C–C bond allows for multiple binding modes in the active site of hPNP, which could provide several plausible bioactive conformations.
Recent Developments in Carbon-11 Chemistry and Applications for First-In-Human PET Studies
Authors: Pees Anna , Chassé Melissa , Lindberg Anton , Vasdev Neil
Published: January 2023

Positron emission tomography (PET) is a molecular imaging technique that makes use of radiolabelled molecules for in vivo evaluation. Carbon-11 is a frequently used radionuclide for the labelling of small molecule PET tracers and can be incorporated into organic molecules without changing their physicochemical properties. While the short half-life of carbon-11 (11C; t½ = 20.4 min) offers other advantages for imaging including multiple PET scans in the same subject on the same day, its use is limited to facilities that have an on-site cyclotron, and the radiochemical transformations are consequently more restrictive. Many researchers have embraced this challenge by discovering novel carbon-11 radiolabelling methodologies to broaden the synthetic versatility of this radionuclide. This review presents new carbon-11 building blocks and radiochemical transformations as well as PET tracers that have advanced to first-in-human studies over the past five years.
Preparation, Characterization, and Environmental Safety Assessment of Dithiocarbazate Loaded Mesoporous Silica Nanoparticles
Authors: Menezes Thacilla , Bouguerra Sirine , Andreani Tatiana , Pereira Ruth , Pereira Carlos
Published: January 2023

Dithiocarbazates comprise an important class of Schiff bases with remarkable biological applications due to the imine group present in their structure. However, full exploitation of the biological activity of 3-methyl-5-phenyl-pyrazoline-1-(S-benzyldithiocarbazate) (DTC) is limited due to its easy degradation and poor solubility in aqueous solutions. The loading of DTC into mesoporous silica nanoparticles (MSiNPs) can be an excellent strategy to improve the solubility of DTC in the aqueous medium. Therefore, the main goal of the present work was to design MSiNP-DTC and to evaluate the success of the loading process by measuring its physicochemical properties and evaluating the environmental safety of the new DTC formulation using different aquatic organisms, such as the microalgae Raphidocelis subcapitata, the macrophyte Lemna minor, and the marine bacterium Aliivibrio fischeri. DTC, MSiNP, and MSiNP-DTC concentrations ranging from 8.8 to 150 mg L−1 were tested for all the species, showing low toxicity against aquatic organisms. Loading DTC into MSiNPs caused a slight increase in the toxicity at the concentrations tested, only allowing for the estimation of the effect concentration causing a 20% reduction in bioluminescence or growth rate (EC20). Therefore, despite the potential of MSiNPs as a drug delivery system (DDS), it is of utmost importance to assess its impact on the safety of the new formulations.
Particles’ Organization in Direct Oil-in-Water and Reverse Water-in-Oil Pickering Emulsions
Authors: Ramos Diego M. , Sadtler Véronique , Marchal Philippe , Lemaitre Cécile , Niepceron Frédérick , Benyahia Lazhar , Roques-Carmes Thibault
Published: January 2023

This paper addresses the impact of the particle initial wetting and the viscosity of the oil phase on the structure and rheological properties of direct (Oil/Water) and reverse (Water/Oil) Pickering emulsions. The emulsion structure was investigated via confocal microscopy and static light scattering. The flow and viscoelastic properties were probed by a stress-controlled rheometer. Partially hydrophobic silica particles have been employed at 1 and 4 wt.% to stabilize dodecane or paraffin-based emulsions at 20 vol.% of the dispersed phase. W/O emulsions were obtained when the particles were dispersed in the oily phase while O/W emulsions were prepared when the silica was introduced in the aqueous phase. We demonstrated that, although the particles adsorbed at the droplets interfaces for all the emulsions, their organization, the emulsion structure and their rheological properties depend in which phase they were previously dispersed in. We discuss these features as a function of the particle concentration and the oil viscosity.
Low-Dimensional-Materials-Based Flexible Artificial Synapse: Materials, Devices, and Systems
Authors: Lu Qifeng , Zhao Yinchao , Huang Long , An Jiabao , Zheng Yufan , Yap Eng Hwa
Published: January 2023

With the rapid development of artificial intelligence and the Internet of Things, there is an explosion of available data for processing and analysis in any domain. However, signal processing efficiency is limited by the Von Neumann structure for the conventional computing system. Therefore, the design and construction of artificial synapse, which is the basic unit for the hardware-based neural network, by mimicking the structure and working mechanisms of biological synapses, have attracted a great amount of attention to overcome this limitation. In addition, a revolution in healthcare monitoring, neuro-prosthetics, and human–machine interfaces can be further realized with a flexible device integrating sensing, memory, and processing functions by emulating the bionic sensory and perceptual functions of neural systems. Until now, flexible artificial synapses and related neuromorphic systems, which are capable of responding to external environmental stimuli and processing signals efficiently, have been extensively studied from material-selection, structure-design, and system-integration perspectives. Moreover, low-dimensional materials, which show distinct electrical properties and excellent mechanical properties, have been extensively employed in the fabrication of flexible electronics. In this review, recent progress in flexible artificial synapses and neuromorphic systems based on low-dimensional materials is discussed. The potential and the challenges of the devices and systems in the application of neuromorphic computing and sensory systems are also explored.
Contribution of Central and Peripheral Glial Cells in the Development and Persistence of Itch: Therapeutic Implication of Glial Modulation
Authors: Gazerani Parisa
Published: January 2023

Chronic itch (CI) is an unpleasant skin sensation accompanied by an intense scratching desire that lasts 6 weeks or longer. Despite the high prevalence and negative impact on affected individuals and a huge healthcare burden, CI mechanisms are only partially understood, and consequently, treatment of CI remains sub-optimal. The complexity of CI treatment also stems from the comorbid existence of persistent itch with other somatic and psychological disorders. Etiologies of CI are multiple and diverse, although CI is often a result of dermatologically related conditions such as atopic dermatitis and psoriasis. Unfolding the pathophysiology of CI can provide possibilities for better therapy. Itch signaling is complex and neurons and non-neuronal cells play a role. This review focuses on recent findings on the role of glial cells in itch. Central glia (astrocytes and microglia) and peripheral glia (satellite glial cells and Schwann cells) are found to contribute to the development or persistence of itch. Hence, glial modulation has been proposed as a potential option in CI treatment. In experimental models of itch, the blockade of signal transducer and the activator of transcription (STAT) 3-mediated reactive astrogliosis have been shown to suppress chronic itch. Administration of a microglial inhibitor, minocycline, has also been demonstrated to suppress itch-related microglial activation and itch. In sensory ganglia, gap-junction blockers have successfully blocked itch, and hence, gap-junction-mediated coupling, with a potential role of satellite glial cells have been proposed. This review presents examples of glial involvement in itch and opportunities and challenges of glial modulation for targeting itch.
Gut Microbiome Composition and Metabolic Capacity Differ by FUT2 Secretor Status in Exclusively Breastfed Infants
Authors: Thorman Alexander W. , Adkins Grace , Conrey Shannon C. , Burrell Allison R. , Yu Ying , White Brendon , Burke Rachel , Haslam David , Payne Daniel C. , Staat Mary A. , Morrow Ardythe L. , Newburg David S.
Published: January 2023

A major polymorphism in the fucosyltransferase2 (FUT2) gene influences risk of multiple gut diseases, but its impact on the microbiome of breastfed infants was unknown. In individuals with an active FUT2 enzyme (“secretors”), the intestinal mucosa is abundantly fucosylated, providing mutualist bacteria with a rich endogenous source of fucose. Non-secretors comprise approximately one-fifth of the population, and they lack the ability to create this enzyme. Similarly, maternal secretor status influences the abundance of a breastfeeding mother’s fucosylated milk oligosaccharides. We compared the impact of maternal secretor status, measured by FUT2 genotype, and infant secretor status, measured by FUT2 genotype and phenotype, on early infant fecal microbiome samples collected from 2-month-old exclusively breastfed infants (n = 59). Infant secretor status (19% non-secretor, 25% low-secretor, and 56% full-secretor) was more strongly associated with the infant microbiome than it was with the maternal FUT2 genotype. Alpha diversity was greater in the full-secretors than in the low- or non-secretor infants (p = 0.049). Three distinct microbial enterotypes corresponded to infant secretor phenotype (p = 0.022) and to the dominance of Bifidobacterium breve, B. longum, or neither (p < 0.001). Infant secretor status was also associated with microbial metabolic capacity, specifically, bioenergetics pathways. We concluded that in exclusively breastfed infants, infant—but not maternal—secretor status is associated with infant microbial colonization and metabolic capacity.
Nutritional Care in Children with Cystic Fibrosis
Authors: Mariotti Zani Elena , Grandinetti Roberto , Cunico Daniela , Torelli Lisa , Fainardi Valentina , Pisi Giovanna , Esposito Susanna
Published: January 2023

Patients with cystic fibrosis (CF) are prone to malnutrition and growth failure, mostly due to malabsorption caused by the derangement in the chloride transport across epithelial surfaces. Thus, optimal nutritional care and support should be an integral part of the management of the disease, with the aim of ameliorating clinical outcomes and life expectancy. In this report, we analyzed the nutrition support across the different ages, in patients with CF, with a focus on the relationships with growth, nutritional status, disease outcomes and the use of the CF transmembrane conductance regulator (CFTR) modulators. The nutrition support goal in CF care should begin as early as possible after diagnosis and include the achievement of an optimal nutritional status to support the growth stages and puberty development in children, that will further support the maintenance of an optimal nutritional status in adult life. The cornerstone of nutrition in patients with CF is a high calorie, high-fat diet, in conjunction with a better control of malabsorption due to pancreatic enzyme replacement therapy, and attention to the adequate supplementation of fat-soluble vitamins. When the oral caloric intake is not enough for reaching the anthropometric nutritional goals, supplemental enteral feeding should be initiated to improve growth and the nutritional status. In the last decade, the therapeutic possibilities towards CF have grown in a consistent way. The positive effects of CFTR modulators on nutritional status mainly consist in the improvement in weight gain and BMI, both in children and adults, and in an amelioration in terms of the pulmonary function and reduction of exacerbations. Several challenges need to be overcome with the development of new drugs, to transform CF from a fatal disease to a treatable chronic disease with specialized multidisciplinary care.
Association between Vitamin B and Obesity in Middle-Aged and Older Chinese Adults
Authors: Fu Yu , Zhu Zhanyong , Huang Zhaolan , He Ruikun , Zhang Ying , Li Yuanyuan , Tan Wei , Rong Shuang
Published: January 2023

Objective: Previous studies have found that obese people have lower levels of vitamin B, but most have focused on obesity as defined by body mass index (BMI), and its relationship with other types of obesity is unclear. The aim of this study was to explore the relationship between vitamin B levels and obesity assessed by different definitions among Chinese middle-aged and older community-dwelling adults. Methods: This cross-sectional study included 887 participants aged 45 years and older (45–82 years). The concentrations of vitamin B (B1, B2, B6, and B9) were measured by robotic dry blood spot extraction systems in combination with liquid chromatography–tandem mass spectrometry. BMI, body fat percentage (BF%), visceral fat area (VFA), and waist circumference (WC) were used to diagnose obesity. VFA and BF% were assessed by bioelectrical impedance analysis. The logistic regression model was used to assess the associations between vitamin B levels and the odds of obesity. Results: The average age of all participants was 60.77 (SD 6.33) years. The prevalence of obesity varied from 8.6% to 52.4% depending on different diagnostic criteria. After adjusting for covariates, a negative correlation was observed between vitamin B1 level and obesity according to the criteria of WC, VFA, and BF%, and the adjusted odds ratio (OR) was 0.47, 0.52, and 0.46, respectively. When using WC and BF% to define obesity, higher quartiles of vitamin B2 were negatively associated with the odds of obesity (OR: 0.62 and 0.62, respectively). Vitamin B6 was inversely associated with VFA-defined and BF%-defined obesity (OR: 0.64 and 0.64, respectively). When using VFA and BF% to define obesity, a negative correlation was observed in vitamin B9 (OR: 0.61 and 0.67, respectively). Conclusions: Vitamin B (B1, B2, B6, and B9) level was negatively related to obesity (defined by WC, VFA, or BF%) in Chinese middle-aged and older adults.
Inequity of Access: Scoping the Barriers to Assisted Reproductive Technologies
Authors: Mackay Amanda , Taylor Selina , Glass Beverley
Published: January 2023

Infertility impacts millions of people of reproductive age worldwide, with approximately 10–15% of couples affected. When infertility is present, there are many potential barriers to treatment, leading to inequity of access. Assisted reproductive technologies (ART) are the mainstay of medical treatment for infertility and include procedures such as in vitro fertilisation. This scoping review aims to explore the barriers to accessing assisted reproductive technologies to highlight a potential role for the pharmacist in addressing these barriers. Five databases, including CINAHL, Emcare, Medline, Scopus, and Web of Science, were searched using keywords that resulted in 19 studies that explored barriers to initially accessing or continuing ART. Studies identified more than one barrier to accessing ART, with the most mentioned barrier being the geographic location of the patient, with others themed as psychological, financial, minority groups, educational level, and the age of the patient. Recommendations were made to address barriers to accessing ART, which included changes to government regulations to increase health education and promotion of infertility. Pharmacists’ accessibility, even in geographically remote locations, places them in an ideal position to address many of the challenges experienced by people accessing infertility treatment to improve outcomes for these people.
Morpho-Physiological and Hormonal Response of Winter Wheat Varieties to Drought Stress at Stem Elongation and Anthesis Stages
Authors: Duvnjak Jurica , Lončarić Ante , Brkljačić Lidija , Šamec Dunja , Šarčević Hrvoje , Salopek-Sondi Branka , Španić Valentina
Published: January 2023

Drought stress can significantly reduce wheat growth and development as well as grain yield. This study investigated morpho-physiological and hormonal (abscisic (ABA) and salicylic (SA) acids) responses of six winter wheat varieties during stem elongation and anthesis stage as well grain yield-related traits were measured after harvest. To examine drought response, plants were exposed to moderate non-lethal drought stress by withholding watering for 45 and 65% of the volumetric soil moisture content (VSMC) for 14 days at separate experiments for each of those two growth stages. During the stem elongation phase, ABA was increased, confirming the stress status of plants, and SA showed a tendency to increase, suggesting their role as stress hormones in the regulation of stress response, such as the increase in the number of leaves and tillers in drought stress conditions, and further keeping turgor pressure and osmotic adjustment in leaves. At the anthesis stage, heavier drought stress resulted in ABA accumulation in flag leaves that generated an integrated response of maturation, where ABA was not positively correlated with any of investigated traits. After harvest, the variety Bubnjar, followed by Pepeljuga and Anđelka, did not significantly decrease the number of grains per ear and 1000 kernel weight (except Anđelka) in drought treatments, thus, declaring them more tolerant to drought. On the other hand, Rujana, Fifi, and particularly Silvija experienced the highest reduction in grain yield-related traits, considering them drought-sensitive varieties.
Impact Comparison of El Niño and Ageing Crops on Malaysian Oil Palm Yield
Authors: Khor Jen Feng , Ling Lloyd , Yusop Zulkifli , Chin Ren Jie , Lai Sai Hin , Kwan Ban Hoe , Ng Danny Wee Kiat
Published: January 2023

Ageing oil palm crops show a significant correlation with the declining oil palm yield in Malaysia. Not only do aged crops result in lower production, but they are also more costly and difficult to harvest. The Malaysian oil palm yield recovered to the pre-El Niño level after the 1997/98 El Niño event. However, the oil palm yield failed to recover after the recent 2015/16 El Niño. Due to the accumulation of aged oil palm plantations in Malaysia, the financial losses from different magnitudes of El Niño events are increasing. Thirty-four years of monthly oil palm yield trends in Malaysia were compared with the El Niño–free yield dataset to show that the oil palm yield downtrend pattern is the same with or without El Niño events in Malaysia for the most recent 15 years (2005 to 2019). The performance of oil palm yield did not show any significant difference from 2000 to 2019. This study estimates that ageing oil palms would lead to a minimum opportunity loss of USD 431 million by December 2022. Without a proper replanting program, the total combined loss attributable to the ageing crops from 2009 to 2022 is estimated to be USD 3.94 billion, which is more profound than losses due to El Niño events within the same period. This study also concluded that a continuous 7-year replanting scheme of at least 115,000 hectares per year is needed to address the adverse impact of ageing crops on the Malaysian oil palm yield, which accounts for nearly 30% of the global palm oil production.
The Impact of Coronavirus Disease of 2019 (COVID-19) Lockdown Restrictions on the Criteria Pollutants
Authors: Verma Puneet , Sisodiya Sohil , Banait Sachin Kumar , Chowdhury Subhankar , Dwivedi Gaurav , Zare Ali
Published: January 2023

Air pollution is accountable for various long-term and short-term respiratory diseases and even deaths. Air pollution is normally associated with a decreasing life expectancy. Governments have been implementing strategies to improve air quality. However, natural events have always played an important role in the concentration of air pollutants. In Australia, the lockdown period followed the Black Summer of 2019–2020 and coincided with the season of prescribed burns. This paper investigates the changes in the concentration of criteria pollutants such as particulate matter, nitrogen dioxide, ozone, and sulphur dioxide. The air quality data for the lockdown period in 2020 was compared with the pre-lockdown period in 2020 and with corresponding periods of previous years from 2016 to 2019. The results were also compared with the post-lockdown scenario of 2020 and 2021 to understand how the concentration levels changed due to behavioural changes and a lack of background events. The results revealed that the COVID-19 restrictions had some impact on the concentration of pollutants; however, the location of monitoring stations played an important role.
Signal Processing Methods of Enhanced Magnetic Memory Testing
Authors: Luo Xu , Wang Lihong , Cao Shufeng , Xiao Qiuhan , Yang Hongjuan , Zhao Jianguo
Published: January 2023

As a particular kind of detection technology under weak magnetization, metal magnetic memory testing is very likely to be affected by external factors in the detecting process, which may lead to incorrect results. In order to minimize the negative influence of interrupting signals and improve the detection accuracy, this paper adopted the enhanced metal magnetic memory testing method to preliminarily increase the signal-to-noise ratio (SNR) of the detection signal and then compares the denoising effects of wavelet threshold denoising method, empirical mode decomposition (EMD) denoising method, EMD-wavelet threshold denoising method, ensemble EMD (EEMD), complementary EEMD (CEEMD), variational mode decomposition (VMD), local mean decomposition (LMD) and empirical wavelet transform (EWT) on the detection signal and the gradient signal respectively. The results show that the enhanced metal magnetic memory testing method can significantly increase the SNR of the obtained signal and cannot improve the SNR of a gradient signal which is generated from the obtained signal. The different denoising methods can further boost the SNR and improve the detection accuracy of the obtained signal and the gradient signal. Among the eight signal processing methods, wavelet threshold, EMD and its improved methods are more applicable in the denoising of enhanced metal magnetic memory testing signals. The Wavelet threshold denoising, EMD-wavelet threshold denoising and EEMD denoising all have good denoising effects, and the denoising results to the same signal are analogous.
Study on Salt Dissolution Law of High Salinity Reservoir and Its Influence on Fracturing
Authors: Pan Liyan , Wang Lei , Zheng Weijie , Han Feipeng , Zibibula Ariya , Zhu Zhenlong , Li Shengxiang
Published: January 2023

For the high-salt reservoir of the Fengcheng Formation in the Mahu area, the production decreases rapidly due to the conductivity decrease after fracturing. The analysis shows that this has a great relationship with the special salt dissolution characteristics of the High salinity reservoir. In order to study the problem of salt dissolution pattern, the effect of different temperatures, the salt concentration of fracturing fluid, the viscosity of fracturing fluid, and injection rate on the rate of salt dissolution was evaluated by using the dynamic experimental evaluation method of salt dissolution. Through the grey correlation analysis of salt rock dissolution rate, it can be found that the degree of influence is from large to small which the influence of temperature is greater than fracturing fluid velocity, followed by fracturing fluid viscosity and, finally, fracturing fluid salt concentration. The results of compressive strength tests on salt-bearing rocks after dissolution show that the compressive strength is greatly reduced after salt dissolution by more than 60%. At the same time, the test results of proppant-free conductivity showed that the conductivity increased first and then decreased sharply after salt dissolution. This shows that in the early stage of salt dissolution, the flow channel will increase through dissolution. The rock strength decreases greatly with the increase of salt dissolution. As a result, collapse leads to a sharp reduction in the facture conductivity. Therefore, it is necessary to choose saturated brine fracturing fluid. In the proppant conductivity experiments, by optimizing the use of saturated brine fracturing fluid with 30/50 mesh or 20/40 mesh ceramic proppant with a sand concentration of 5 Kg/m2, a high facture conductivity can be achieved under high closure pressure conditions. Based on the above study, directions and countermeasures for improving high saline reservoirs are proposed, which point the way to improve the fracturing conductivity.
Special Issue on “Biological Network Approaches and Applications”
Authors: Cho Seong Beom
Published: January 2023

Biological phenomena comprise various interactions between genes and molecules [...]
The Hermeneutics of Hospitality for Epistemic Justice
Authors: Ku Eliana Ah-Rum
Published: January 2023

Although we live in a diasporic world, we need interpretive strategies for reading the Bible through the eyes of history and the experiences of marginalized groups, most of whom are still on the margins. Attempts to bring diverse voices without exclusion, discrimination, and disregard into biblical interpretation in the diasporic world have been linked to the study of epistemic injustice. I consider signifiers of those norms that make the power/knowledge of ‘others’ inferior through the contemporary hospitality perspectives. I consider how reading and interpreting the Bible, without dualistic language, plays a role in creatively participating in new situations, and not claiming absolute ownership of fixed spaces, discourses, and movements. In particular, by reading Lot’s story of biblical hospitality as a discourse on hostility and hospitality, this study will examine how an interpretive lens of contemporary hospitality can expand and apply to encourage epistemic justice in a more relational and plentiful way.
Detecting Urban Floods with Small and Large Scale Analysis of ALOS-2/PALSAR-2 Data
Authors: Gokon Hideomi , Endo Fuyuki , Koshimura Shunichi
Published: January 2023

When a large-scale flood disaster occurs, it is important to identify the flood areas in a short time in order to effectively support the affected areas afterwards. Synthetic Aperture Radar (SAR) is promising for flood detection. A number of change detection methods have been proposed to detect flooded areas with pre- and post-event SAR data. However, it remains difficult to detect flooded areas in built-up areas due to the complicated scattering of microwaves. To solve this issue, in this paper we propose the idea of analyzing the local changes in pre- and post-event SAR data as well as the larger-scale changes, which may improve accuracy for detecting floods in built-up areas. Therefore, we aimed at evaluating the effectiveness of multi-scale SAR analysis for flood detection in built-up areas using ALOS-2/PALSAR-2 data. First, several features were determined by calculating standard deviation images, difference images, and correlation coefficient images with several sizes of kernels. Then, segmentation on both small and large scales was applied to the correlation coefficient image and calculated explanatory variables with the features at each segment. Finally, machine learning models were tested for their flood detection performance in built-up areas by comparing a small-scale approach and multi-scale approach. Ten-fold cross-validation was used to validate the model, showing that highest accuracy was offered by the AdaBoost model, which improved the F1 Score from 0.89 in the small-scale analysis to 0.98 in the multi-scale analysis. The main contribution of this manuscript is that, from our results, it can be inferred that multi-scale analysis shows better performance in the quantitative detection of floods in built-up areas.
A Uniformity Index for Precipitation Particle Axis Ratios Derived from Radar Polarimetric Parameters for the Identification and Analysis of Raindrop Areas
Authors: Sun Yue , Xiao Hui , Yang Huiling , Chen Haonan , Feng Liang , Shu Weixi , Yao Han
Published: January 2023

A uniformity index for the axis ratios (Uar) derived from dual polarization weather radar data is proposed for raindrop area identification and analysis. The derivation of this new parameter is based on radar scattering simulations and assumptions. Uar is between 0 and 1 and can be calculated from the differential reflectivity (ZDR) and the copolar correlation coefficient (ρhv), which reflects the uniformity of the axis ratio (r) of the particle group. For raindrops, Uar is close to 1 under ideal conditions, but is clearly different from that of ice particles whose value is close to 0. Studies conducted during two convective weather events observed by X-band and S-band radar are presented to show the Uar features. In convective areas, high Uar presents a U-shaped vertical structure. One branch corresponds to the ZDR column, while the other branch is located at the rear of the convective cloud zone and is lower in altitude, representing the process of ice particles melting into raindrops and then being transported upward by a strong updraft. In stratiform cloud areas, a more than 95% overall identification ratio is obtained when the threshold of Uar is set to 0.2~0.3 for discriminating rain layers.
Deep Network Architectures as Feature Extractors for Multi-Label Classification of Remote Sensing Images
Authors: Stoimchev Marjan , Kocev Dragi , Džeroski Sašo
Published: January 2023

Data in the form of images are now generated at an unprecedented rate. A case in point is remote sensing images (RSI), now available in large-scale RSI archives, which have attracted a considerable amount of research on image classification within the remote sensing community. The basic task of single-target multi-class image classification considers the case where each image is assigned exactly one label from a predefined finite set of class labels. Recently, however, image annotations have become increasingly complex, with images labeled with several labels (instead of just one). In other words, the goal is to assign multiple semantic categories to an image, based on its high-level context. The corresponding machine learning tasks is called multi-label classification (MLC). The classification of RSI is currently predominantly addressed by deep neural network (DNN) approaches, especially convolutional neural networks (CNNs), which can be utilized as feature extractors as well as end-to-end methods. After only considering single-target classification for a long period, DNNs have recently emerged that address the task of MLC. On the other hand, trees and tree ensembles for MLC have a long tradition and are the best-performing class of MLC methods, but need predefined feature representations to operate on. In this work, we explore different strategies for model training based on the transfer learning paradigm, where we utilize different families of (pre-trained) CNN architectures, such as VGG, EfficientNet, and ResNet. The architectures are trained in an end-to-end manner and used in two different modes of operation, namely, as standalone models that directly perform the MLC task, and as feature extractors. In the latter case, the learned representations are used with tree ensemble methods for MLC, such as random forests and extremely randomized trees. We conduct an extensive experimental analysis of methods over several publicly available RSI datasets and evaluate their effectiveness in terms of standard MLC measures. Of these, ranking-based evaluation measures are most relevant, especially ranking loss. The results show that, for addressing the RSI-MLC task, it is favorable to use lightweight network architectures, such as EfficientNet-B2, which is the best performing end-to-end approach, as well as a feature extractor. Furthermore, in the datasets with a limited number of images, using traditional tree ensembles for MLC can yield better performance compared to end-to-end deep approaches.
Deep Object Detection of Crop Weeds: Performance of YOLOv7 on a Real Case Dataset from UAV Images
Authors: Gallo Ignazio , Rehman Anwar Ur , Dehkordi Ramin Heidarian , Landro Nicola , La Grassa Riccardo , Boschetti Mirco
Published: January 2023

Weeds are a crucial threat to agriculture, and in order to preserve crop productivity, spreading agrochemicals is a common practice with a potential negative impact on the environment. Methods that can support intelligent application are needed. Therefore, identification and mapping is a critical step in performing site-specific weed management. Unmanned aerial vehicle (UAV) data streams are considered the best for weed detection due to the high resolution and flexibility of data acquisition and the spatial explicit dimensions of imagery. However, with the existence of unstructured crop conditions and the high biological variation of weeds, it remains a difficult challenge to generate accurate weed recognition and detection models. Two critical barriers to tackling this challenge are related to (1) a lack of case-specific, large, and comprehensive weed UAV image datasets for the crop of interest, (2) defining the most appropriate computer vision (CV) weed detection models to assess the operationality of detection approaches in real case conditions. Deep Learning (DL) algorithms, appropriately trained to deal with the real case complexity of UAV data in agriculture, can provide valid alternative solutions with respect to standard CV approaches for an accurate weed recognition model. In this framework, this paper first introduces a new weed and crop dataset named Chicory Plant (CP) and then tests state-of-the-art DL algorithms for object detection. A total of 12,113 bounding box annotations were generated to identify weed targets (Mercurialis annua) from more than 3000 RGB images of chicory plantations, collected using a UAV system at various stages of crop and weed growth. Deep weed object detection was conducted by testing the most recent You Only Look Once version 7 (YOLOv7) on both the CP and publicly available datasets (Lincoln beet (LB)), for which a previous version of YOLO was used to map weeds and crops. The YOLOv7 results obtained for the CP dataset were encouraging, outperforming the other YOLO variants by producing value metrics of 56.6%, 62.1%, and 61.3% for the mAP@0.5 scores, recall, and precision, respectively. Furthermore, the YOLOv7 model applied to the LB dataset surpassed the existing published results by increasing the mAP@0.5 scores from 51% to 61%, 67.5% to 74.1%, and 34.6% to 48% for the total mAP, mAP for weeds, and mAP for sugar beets, respectively. This study illustrates the potential of the YOLOv7 model for weed detection but remarks on the fundamental needs of large-scale, annotated weed datasets to develop and evaluate models in real-case field circumstances.
Ecosystem Service Synergies Promote Ecological Tea Gardens: A Case Study in Fuzhou, China
Authors: Wang Chunyi , Zhao Mingyue , Xu Yinlong , Zhao Yuncheng , Zhang Xiao
Published: January 2023

Exploring the trade-off/synergy among ecosystem services (ESs) of agroecosystems could provide effective support for improving agricultural resilience for sustainable development. The construction of ecological tea gardens is emerging, aims to achieve a win-win situation for the tea industry and ecological environment protection. However, the effect of ES trade-offs/synergies on tea production is still not clear. In this study, we selected Fuzhou city, China, as a case study and explored the relationship among tea production and ESs in 2010 and 2020. Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) and Intelligent Urban Ecosystem Management System (IUEMS) models were used to assess the ecosystem (dis)services, which were tea production, water yield, soil retention, net primary productivity (NPP), climate regulation, soil erosion and carbon emissions. Then, the sum of trade-off/synergy coefficients of ESs (Cts) were defined to reveal the trade-off/synergy in tea gardens and areas except tea gardens (ETG areas). K-means clustering was used to assess the spatiotemporal change of traditional tea garden and ecological tea garden, reflecting the effect of ecological tea garden construction. The results showed that: (1) the high-value areas of tea production were mainly distributed in Lianjiang County, with yields up to 3.6 t/ha, and the low-value areas in Yongtai County, with yields from 0.1–1.0 t/ha. Other ESs showed spatial heterogeneity. (2) The trade-offs in ETG areas intensified from 2010 to 2020, with Cts decreasing from −0.28 to −0.73, and the synergy in tea garden was at risk of decline, with Cts decreasing from 4.46 to 1.02. (3) From 2010 to 2020, 96.72% of traditional tea gardens (Area I) were transformed into ecological tea gardens (Areas IV and V). (4) Further, we classified the tea garden into five zones based on tea yield, with Zone I as the low tea yield areas and Zone V as the highest. From Zone I to Zone V, the Cts increased from 2.6 to 7.5 in 2010, and from 1.9 to 6.5 in 2020, respectively. These results demonstrate the effectiveness of the construction of ecological tea gardens in Fuzhou and provide a reference for subsequent studies on the ESs of tea gardens and governance of ecological tea gardens.
Three-Dimensional Point Cloud Semantic Segmentation for Cultural Heritage: A Comprehensive Review
Authors: Yang Su , Hou Miaole , Li Songnian
Published: January 2023

In the cultural heritage field, point clouds, as important raw data of geomatics, are not only three-dimensional (3D) spatial presentations of 3D objects but they also have the potential to gradually advance towards an intelligent data structure with scene understanding, autonomous cognition, and a decision-making ability. The approach of point cloud semantic segmentation as a preliminary stage can help to realize this advancement. With the demand for semantic comprehensibility of point cloud data and the widespread application of machine learning and deep learning approaches in point cloud semantic segmentation, there is a need for a comprehensive literature review covering the topics from the point cloud data acquisition to semantic segmentation algorithms with application strategies in cultural heritage. This paper first reviews the current trends of acquiring point cloud data of cultural heritage from a single platform with multiple sensors and multi-platform collaborative data fusion. Then, the point cloud semantic segmentation algorithms are discussed with their advantages, disadvantages, and specific applications in the cultural heritage field. These algorithms include region growing, model fitting, unsupervised clustering, supervised machine learning, and deep learning. In addition, we summarized the public benchmark point cloud datasets related to cultural heritage. Finally, the problems and constructive development trends of 3D point cloud semantic segmentation in the cultural heritage field are presented.