bluuebunny/crossref_metadata_2025 huggingface dataset:
The Effect of Cooling Rates on Thermal, Crystallization, Mechanical and Barrier Properties of Rotational Molding Polyamide 11 as the Liner Material for High-Capacity High-Pressure Vessels
Authors: Yu Muhuo , Qi Liangliang , Cheng Lele , Min Wei , Mei Zhonghao , Gao Ruize , Sun Zeyu
Published: March 2023

The rapid development of hydrogen fuel cells has been paralleled by increased demand for lightweight type IV hydrogen storage vessels with high hydrogen storage density, which raises the performance requirements of internal plastic liners. An appropriate manufacturing process is important to improve the quality of polymer liners. In this paper, DSC, WAXD, a universal testing machine and a differential pressure gas permeameter were used to investigate the effect of the cooling rate of the rotational molding polyamide 11 on the thermal, crystallization, mechanical and barrier properties. The cooling rate is formulated according to the cooling rate that can be achieved in actual production. The results suggest that two PA11 liner materials initially exhibited two-dimensional (circular) growth under non-isothermal crystallization conditions and shifted to one-dimensional space growth due to spherulite collision and crowding during the secondary crystallization stage. The slower the cooling process, the greater the crystallinity of the specimen. The increase in crystallinity significantly improved the barrier properties of the two PA11 liner materials, and the gas permeability coefficient was 2-3-fold higher than at low crystallinity. Moreover, the tensile strength, the tensile modulus, the flexural strength, and the flexural modulus increased, and the elongation at break decreased as the crystallinity increased.
Properties and Characterization Techniques of Graphene Modified Asphalt Binders
Authors: Polo-Mendoza Rodrigo , Navarro-Donado Tatiana , Ortega-Martinez Daniela , Turbay Emilio , Martinez-Arguelles Gilberto , Peñabaena-Niebles Rita
Published: March 2023

Graphene is a carbon-based nanomaterial used in various industries to improve the performance of hundreds of materials. For instance, graphene-like materials have been employed as asphalt binder modifying agents in pavement engineering. In the literature, it has been reported that (in comparison to an unmodified binder) the Graphene Modified Asphalt Binders (GMABs) exhibit an enhanced performance grade, a lower thermal susceptibility, a higher fatigue life, and a decreased accumulation of permanent deformations. Nonetheless, although GMABs stand out significantly from traditional alternatives, there is still no consensus on their behavior regarding chemical, rheological, microstructural, morphological, thermogravimetric, and surface topography properties. Therefore, this research conducted a literature review on the properties and advanced characterization techniques of GMABs. Thus, the laboratory protocols covered by this manuscript are atomic force microscopy, differential scanning calorimetry, dynamic shear rheometer, elemental analysis, Fourier transform infrared spectroscopy, Raman spectroscopy, scanning electron microscopy, thermogravimetric analysis, X-ray diffraction, and X-ray photoelectron spectroscopy. Consequently, the main contribution of this investigation to the state-of-the-art is the identification of the prominent trends and gaps in the current state of knowledge.
Nutritional Intake Differences in Combinations of Carbohydrate-Rich Foods in Pirapó, Republic of Paraguay
Authors: Caballero Yuko , Matakawa Konomi , Ushiwata Ai , Akatsuka Tomoko , Sudo Noriko
Published: March 2023

A national strategy for obesity prevention has been promoted in Paraguay, reflecting the situation where half of adults and 23.4% of children (under 5 years old) are overweight. However, the detailed nutritional intake of the population has not yet been studied, especially in rural areas. Therefore, this study aimed to identify obesity-causing factors in Pirapó by analyzing the results from a food frequency questionnaire (FFQ) and one-day weighed food records (WFRs). From June to October 2015, 433 volunteers (200 males and 233 females) completed the FFQ with 36 items and one-day WFRs. Body mass index (BMI) positively correlated with the consumption of sandwiches, hamburgers, and bread and with age and diastolic blood pressure, although pizza and fried bread (pireca) had a negative correlation in males (p < 0.05). BMI positively correlated with systolic blood pressure, whereas it negatively correlated with the consumption of cassava and rice in females (p < 0.05). The FFQ revealed that fried food with wheat flour was consumed once a day. WFRs showed that 40% of meals consisted of two or more carbohydrate-rich dishes, significantly higher in energy, lipids, and sodium than those containing only one carbohydrate-rich dish. These results imply that less oily wheat dish consumption and healthy combinations of dishes should be considered for obesity prevention.
Impact of a Low-Insulin-Stimulating Bread on Weight Development—A Real Life Randomised Controlled Trial
Authors: Kempf Kerstin , Röhling Martin , Kolb Hubert , Martin Stephan
Published: March 2023

The impact on body weight development is usually analysed by comparing different diet types. Our approach was to change only one component, namely bread, common to most diets. In a single-centre triple-blind randomised controlled trial the effects of two different breads on body weight were analyzed without further lifestyle modification. Overweight adult volunteers (n = 80) were randomised 1:1 to exchange previously consumed breads for either a rye bread from milled whole grain (control) or a medium-carbohydrate, low-insulin-stimulating bread (intervention). Pre-tests demonstrated that the two bread types strongly differed in the glucose and insulin response elicited, but had similar energy content, texture and taste. The primary endpoint was the estimated treatment difference (ETD) in change of body weight after 3 months of treatment. Whereas body weight remained unchanged in the control group (−0.1 ± 2.0 kg), significant weight reduction was observed in the intervention group (−1.8 ± 2.9 kg), with an ETD of −1.7 ± 0.2 kg (p = 0.007), that was more pronounced in participants ≥ 55 years (−2.6 ± 3.3 kg), paralleled by significant reductions in body mass index and hip circumference. Moreover, in the intervention group, the percentage of participants with significant weight loss (≥1 kg) was twice as high as in the control group (p < 0.001). No other statistically significant changes in clinical or lifestyle parameters were noted. Simply exchanging a common insulinogenic bread for a low-insulin-stimulating bread demonstrates potential to induce weight loss in overweight persons, especially those at older age.
Magnesium Improves Cardiac Function in Experimental Uremia by Altering Cardiac Elastin Protein Content
Authors: Barros Xoana , Friesen Xenia , Mathias Brandenburg Vincent , Liehn Elisa Anamaria , Steppan Sonja , Kiessling Fabian , Kramann Rafael , Floege Jürgen , Krüger Thilo , Kaesler Nadine
Published: March 2023

Cardiovascular complications are accompanied by life-threatening complications and represent the major cause of death in patients with chronic kidney disease (CKD). Magnesium is important for the physiology of cardiac function, and its deficiency is common in CKD. In the present study, we investigated the impact of oral magnesium carbonate supplementation on cardiac function in an experimental model of CKD induced in Wistar rats by an adenine diet. Echocardiographic analyses revealed restoration of impaired left ventricular cardiac function in animals with CKD. Cardiac histology and real-time PCR confirmed a high amount of elastin protein and increased collagen III expression in CKD rats supplemented with dietary magnesium as compared with CKD controls. Both structural proteins are crucial in maintaining cardiac health and physiology. Aortic calcium content increased in CKD as compared with tissue from control animals. Magnesium supplementation numerically lowered the increases in aortic calcium content as it remained statistically unchanged, compared with controls. In summary, the present study provides evidence for an improvement in cardiovascular function and aortic wall integrity in a rat model of CKD by magnesium, as evidenced by echocardiography and histology.
Association between Serum Magnesium and Fractures: A Systematic Review and Meta-Analysis of Observational Studies
Authors: Dominguez Ligia J. , Veronese Nicola , Ciriminna Stefano , Pérez-Albela José Luis , Vásquez-López Vania Flora , Rodas-Regalado Santiago , Di Bella Giovanna , Parisi Angela , Tagliaferri Federica , Barbagallo Mario
Published: March 2023

Magnesium, an essential cation for numerous cellular processes, is a major component of bone. However, its relationship with the risk of fractures is still uncertain. The present systematic review and meta-analysis aim to investigate the impact of serum Mg on the risk of incident fractures. A systematic search was conducted using several databases including PubMed/Medline and Scopus from inception to 24 May 2022, including observational studies investigating serum Mg and the incidence of fractures considered as outcomes. Abstract and full-text screenings, data extractions, and risk of bias assessments were conducted by two investigators independently. Any inconsistencies were resolved by consensus with a third author. The Newcastle–Ottawa Scale was used to assess the study quality/risk of bias. Among 1332 records initially screened, 16 were retrieved as full-texts; of them, four papers were included in the systematic review with a total of 119,755 participants. We found that lower serum Mg concentrations were associated with a significantly higher risk of incident fractures (RR = 1.579; 95%CI: 1.216–2.051; p = 0.001; I2 = 46.9%). Our systematic review with meta-analysis suggests a strong association of serum Mg concentrations with incident fractures. Further research is needed to confirm our results among other populations and to assess whether serum Mg is potentially relevant in the prevention of fractures, which continue to increase and represent a significant health burden due to the associated disability.
Marketed Quinoa (Chenopodium quinoa Willd.) Seeds: A Mycotoxin-Free Matrix Contaminated by Mycotoxigenic Fungi
Authors: Quaglia Mara , Beccari Giovanni , Vella Giovanna Fabiana , Filippucci Riccardo , Buldini Dario , Onofri Andrea , Sulyok Michael , Covarelli Lorenzo
Published: March 2023

A total of 25 marketed quinoa seed samples different for origin, farming system and packaging were analyzed for the presence of mycotoxigenic fungi (by isolation both on Potato Dextrose Agar and with the deep-freezing blotter method) and relative contamination by mycotoxins (by LC-MS/MS analysis). Fungal microorganisms, but not mycotoxins, were detected in all the samples, and 25 isolates representative of the mycobiota were obtained. Morphological and molecular characterization and, for some isolates, the in vitro mycotoxigenic profile, allowed the identification of 19 fungal species within five different genera: Alternaria, Aspergillus, Penicillium, Cladosporium and Fusarium. Among the identified species, Alternaria abundans, A. chartarum, A. arborescens, Cladosporium allicinum, C. parasubtilissimum, C. pseudocladosporioides, C. uwebraunianum, Aspergillus jensenii, A. tubingensis, Penicillium dipodomyis, P. verrucosum and P. citreosulfuratum were first reported on quinoa, and Alternaria infectoria and Fusarium oxysporum were first reported on quinoa seeds. The geographical origin, farming system and packaging were showed to affect the amount and type of the isolated fungal species, highlighting that the level of fungal presence and their related secondary metabolites is conditioned by different steps of the quinoa supply chain. However, despite the presence of mycotoxigenic fungi, the marketed quinoa seeds analyzed resulted in being free from mycotoxins.
Increasing Skeletal Muscle Mass in Mice by Non-Invasive Intramuscular Delivery of Myostatin Inhibitory Peptide by Iontophoresis
Authors: Michiue Kohki , Takayama Kentaro , Taniguchi Atsuhiko , Hayashi Yoshio , Kogure Kentaro
Published: March 2023

Sarcopenia is a major public health issue that affects older adults. Myostatin inhibitory-D-peptide-35 (MID-35) can increase skeletal muscle and is a candidate therapeutic agent, but a non-invasive and accessible technology for the intramuscular delivery of MID-35 is required. Recently, we succeeded in the intradermal delivery of various macromolecules, such as siRNA and antibodies, by iontophoresis (ItP), a non-invasive transdermal drug delivery technology that uses weak electricity. Thus, we expected that ItP could deliver MID-35 non-invasively from the skin surface to skeletal muscle. In the present study, ItP was performed with a fluorescently labeled peptide on mouse hind leg skin. Fluorescent signal was observed in both skin and skeletal muscle. This result suggested that the peptide was effectively delivered to skeletal muscle from skin surface by ItP. Then, the effect of MID-35/ItP on skeletal muscle mass was evaluated. The skeletal muscle mass increased 1.25 times with ItP of MID-35. In addition, the percentage of new and mature muscle fibers tended to increase, and ItP delivery of MID-35 showed a tendency to induce alterations in the levels of mRNA of genes downstream of myostatin. In conclusion, ItP of myostatin inhibitory peptide is a potentially useful strategy for treating sarcopenia.
In Vitro Antiviral Effect and Potential Neuroprotection of Salvadora persica L. Stem Bark Extract against Lipopolysaccharides-Induced Neuroinflammation in Mice: LC-ESI-MS/MS Analysis of the Methanol Extract
Authors: Binsuwaidan Reem , Negm Walaa A. , Elekhnawy Engy , Attallah Nashwah G. M. , Ahmed Eman , Magdeldin Sameh , Moglad Ehssan , Mostafa Sally Abdallah , El-Sherbeni Suzy A.
Published: March 2023

Neuroinflammation is a serious immunomodulatory complex disorder that causes neurological and somatic ailments. The treatment of brain inflammation with new drugs derived from natural sources is a significant therapeutic goal. Utilizing LC-ESI-MS/MS analysis, the active constituents of Salvadora persica extract (SPE) were identified tentatively as exerting antioxidant and anti-inflammatory effects in natural medicine. Herein, we determined the antiviral potential of SPE against herpes simplex virus type 2 (HSV-2) using the plaque assay. HSV-2 is a neurotropic virus that can cause neurological diseases. SPE exhibited promising antiviral potential with a half-maximal cytotoxic concentration (CC50) of 185.960 ± 0.1 µg/mL and a half-maximal inhibitory concentration (IC50) of 8.946 ± 0.02 µg/mL. The in vivo study of the SPE impact against lipopolysaccharide (LPS)-induced neuroinflammation was performed using 42 mice divided into seven groups. All groups were administered LPS (0.25 mg/kg) intraperitoneally, except for the normal and SPE groups 1 and 2. Groups 5, 6, and 7 received 100, 200, and 300 mg/kg SPE. It was revealed that SPE inhibited acetylcholinesterase in the brain. It increased superoxide dismutase and catalase while decreasing malondialdehyde, which explains its antioxidative stress activity. SPE downregulated the gene expression of the inducible nitric oxide synthase, as well as the apoptotic markers (caspase-3 and c-Jun). In addition, it decreased the expression of the proinflammatory cytokines (interleukin-6 and tumor necrosis factor-alpha). Mice administered SPE (300 mg/kg) with LPS exhibited normal neurons in the cerebral cortices, hippocampus pyramidal layer, and cerebellum, as determined by the histopathological analysis. Therefore, using S. persica to prevent and treat neurodegeneration could be a promising new therapeutic strategy to be explored.
Potential Anti-Amnesic Activity of a Novel Multimodal Derivative of Salicylamide, JJGW08, in Mice
Authors: Żmudzka Elżbieta , Lustyk Klaudia , Sałaciak Kinga , Siwek Agata , Jaśkowska Jolanta , Kołaczkowski Marcin , Sapa Jacek , Pytka Karolina
Published: March 2023

Memory impairments constitute a significant problem worldwide, and the COVID-19 pandemic dramatically increased the prevalence of cognitive deficits. Patients with cognitive deficits, specifically memory disturbances, have underlying comorbid conditions such as schizophrenia, anxiety, or depression. Moreover, the available treatment options have unsatisfactory effectiveness. Therefore, there is a need to search for novel procognitive and anti-amnesic drugs with additional pharmacological activity. One of the important therapeutic targets involved in the modulation of learning and memory processes are serotonin receptors, including 5-HT1A, 5-HT6, and 5-HT7, which also play a role in the pathophysiology of depression. Therefore, this study aimed to assess the anti-amnesic and antidepressant-like potential of JJGW08, a novel arylpiperazine alkyl derivative of salicylamide with strong antagonistic properties at 5-HT1A and D2 receptors and weak at 5-HT2A and 5-HT7 receptors in rodents. First, we investigated the compound’s affinity for 5-HT6 receptors using the radioligand assays. Next, we assessed the influence of the compound on long-term emotional and recognition memory. Further, we evaluated whether the compound could protect against MK-801-induced cognitive impairments. Finally, we determined the potential antidepressant-like activity of the tested compound. We found that JJGW08 possessed no affinity for 5-HT6 receptors. Furthermore, JJGW08 protected mice against MK-801-induced recognition and emotional memory deficits but showed no antidepressant-like effects in rodents. Therefore, our preliminary study may suggest that blocking serotonin receptors, especially 5-HT1A and 5-HT7, might be beneficial in treating cognitive impairments, but it requires further investigation.
Xanthone-1,2,4-triazine and Acridone-1,2,4-triazine Conjugates: Synthesis and Anticancer Activity
Authors: Santra Sougata , Sharapov Ainur D. , Fatykhov Ramil F. , Potapova Anastasya P. , Khalymbadzha Igor A. , Valieva Maria I. , Kopchuk Dmitry S. , Zyryanov Grigory V. , Bunev Alexander S. , Melekhin Vsevolod V. , Gaviko Vasiliy S. , Zonov Andrey A.
Published: March 2023

A total of 21 novel xanthone and acridone derivatives were synthesized using the reactions of 1,2,4-triazine derivatives with 1-hydroxy-3-methoxy-10-methylacridone, 1,3-dimethoxy-, and 1,3-dihydroxanthone, followed by optional dihydrotiazine ring aromatization. The synthesized compounds were evaluated for their anticancer activity against colorectal cancer HCT116, glioblastoma A-172, breast cancer Hs578T, and human embryonic kidney HEK-293 tumor cell lines. Five compounds (7a, 7e, 9e, 14a, and 14b) displayed good in vitro antiproliferative activities against these cancer cell lines. Compounds 7a and 7e demonstrated low toxicity for normal human embryonic kidney (HEK-293) cells, which determines the possibility of further development of these compounds as anticancer agents. Annexin V assay demonstrated that compound 7e activates apoptotic mechanisms and inhibits proliferation in glioblastoma cells.
On the Use of Temperature Measurements as a Process Analytical Technology (PAT) for the Monitoring of a Pharmaceutical Freeze-Drying Process
Authors: Vallan Alberto , Fissore Davide , Pisano Roberto , Barresi Antonello A.
Published: March 2023

The measurement of product temperature is one of the methods that can be adopted, especially in the pharmaceutical industry, to monitor the freeze-drying process and to obtain the values of the process parameters required by mathematical models useful for in-line (or off-line) optimization. Either a contact or a contactless device and a simple algorithm based on a mathematical model of the process can be employed to obtain a PAT tool. This work deeply investigated the use of direct temperature measurement for process monitoring to determine not only the product temperature, but also the end of primary drying and the process parameters (heat and mass transfer coefficients), as well as evaluating the degree of uncertainty of the obtained results. Experiments were carried out with thin thermocouples in a lab-scale freeze-dryer using two different model products, sucrose and PVP solutions; they are representative of two types of commonly freeze-dried products, namely those whose structures are strongly nonuniform in the axial direction, showing a variable pore size with the cake depth and a crust (leading to a strongly nonlinear cake resistance), as well as those whose structures are uniform, with an open structure and, consequently, a cake resistance varying linearly with thickness. The results confirm that the model parameters in both cases can be estimated with an uncertainty that is in agreement with that obtained with other more invasive and expensive sensors. Finally, the strengths and weaknesses of the proposed approach coupled with the use of thermocouples was discussed, comparing with a case using a contactless device (infrared camera).
Interspecific Drought Cuing in Plants
Authors: Falik Omer , Novoplansky Ariel
Published: March 2023

Plants readily communicate with their pollinators, herbivores, symbionts, and the predators and pathogens of their herbivores. We previously demonstrated that plants could exchange, relay, and adaptively utilize drought cues from their conspecific neighbors. Here, we studied the hypothesis that plants can exchange drought cues with their interspecific neighbors. Triplets of various combinations of split-root Stenotaphrum secundatum and Cynodon dactylon plants were planted in rows of four pots. One root of the first plant was subjected to drought while its other root shared its pot with one of the roots of an unstressed target neighbor, which, in turn, shared its other pot with an additional unstressed target neighbor. Drought cuing and relayed cuing were observed in all intra- and interspecific neighbor combinations, but its strength depended on plant identity and position. Although both species initiated similar stomatal closure in both immediate and relayed intraspecific neighbors, interspecific cuing between stressed plants and their immediate unstressed neighbors depended on neighbor identity. Combined with previous findings, the results suggest that stress cuing and relay cuing could affect the magnitude and fate of interspecific interactions, and the ability of whole communities to endure abiotic stresses. The findings call for further investigation into the mechanisms and ecological implications of interplant stress cuing at the population and community levels.
LED omics in Rocket Salad (Diplotaxis tenuifolia): Comparative Analysis in Different Light-Emitting Diode (LED) Spectrum and Energy Consumption
Authors: Tsaballa Aphrodite , Xanthopoulou Aliki , Sperdouli Ilektra , Bantis Filippos , Boutsika Anastasia , Chatzigeorgiou Ioanna , Tsaliki Eleni , Koukounaras Athanasios , Ntinas Georgios K. , Ganopoulos Ioannis
Published: March 2023

By applying three different LED light treatments, designated as blue (B), red (R)/blue (B), red (R) and white (W) light, as well as the control, the effect on Diplotaxis tenuifolia phenotype (yield and quality), and physiological, biochemical, and molecular status, as well as growing system resource use efficiency, was examined. We observed that basic leaf characteristics, such as leaf area, leaf number, relative chlorophyll content, as well as root characteristics, such as total root length and root architecture, remained unaffected by different LEDs. Yield expressed in fresh weight was slightly lower in LED lights than in the control (1113 g m−2), with R light producing the least (679 g m−2). However, total soluble solids were significantly affected (highest, 5.5° Brix, in R light) and FRAP was improved in all LED lights (highest, 191.8 μg/g FW, in B) in comparison to the control, while the nitrate content was less (lowest, 949.2 μg/g FW, in R). Differential gene expression showed that B LED light affected more genes in comparison to R and R/B lights. Although total phenolic content was improved under all LED lights (highest, 1.05 mg/g FW, in R/B), we did not detect a significant amount of DEGs in the phenylpropanoid pathway. R light positively impacts the expression of the genes encoding for photosynthesis components. On the other hand, the positive impact of R light on SSC was possibly due to the expression of key genes being induced, such as SUS1. In summary, this research is an integrative and innovative study, where the exploration of the effect of different LED lights on rocket growing under protected cultivation, in a closed chamber cultivation system, was performed at multiple levels.
Secondary Metabolite Profiling, Antioxidant, Antidiabetic and Neuroprotective Activity of Cestrum nocturnum (Night Scented-Jasmine): Use of In Vitro and In Silico Approach in Determining the Potential Bioactive Compound
Authors: Ahmad Saheem , Alrouji Mohammed , Alhajlah Sharif , Alomeir Othman , Pandey Ramendra Pati , Ashraf Mohammad Saquib , Ahmad Shafeeque , Khan Saif
Published: March 2023

This study aims to describe the therapeutic potential of C. nocturnum leaf extracts against diabetes and neurological disorders via the targeting of α-amylase and acetylcholinesterase (AChE) activities, followed by computational molecular docking studies to establish a strong rationale behind the α-amylase and AChE inhibitory potential of C. nocturnum leaves-derived secondary metabolites. In our study, the antioxidant activity of the sequentially extracted C. nocturnum leaves extract was also investigated, in which the methanolic fraction exhibited the strongest antioxidant potential against DPPH (IC50 39.12 ± 0.53 µg/mL) and ABTS (IC50 20.94 ± 0.82 µg/mL) radicals. This extract strongly inhibited the α-amylase (IC50188.77 ± 1.67 µg/mL) and AChE (IC50 239.44 ± 0.93 µg/mL) in a non-competitive and competitive manner, respectively. Furthermore, in silico analysis of compounds identified in the methanolic extract of the leaves of C. nocturnum using GC-MS revealed high-affinity binding of these compounds with the catalytic sites of α-amylase and AChE, with binding energy ranging from −3.10 to −6.23 kcal/mol and from −3.32 to −8.76 kcal/mol, respectively. Conclusively, the antioxidant, antidiabetic, and anti-Alzheimer activity of this extract might be driven by the synergistic effect of these bioactive phytoconstituents.
Design of New Dispersants Using Machine Learning and Visual Analytics
Authors: Martínez María Jimena , Naveiro Roi , Soto Axel J. , Talavante Pablo , Kim Lee Shin-Ho , Gómez Arrayas Ramón , Franco Mario , Mauleón Pablo , Lozano Ordóñez Héctor , Revilla López Guillermo , Bernabei Marco , Campillo Nuria E. , Ponzoni Ignacio
Published: March 2023

Artificial intelligence (AI) is an emerging technology that is revolutionizing the discovery of new materials. One key application of AI is virtual screening of chemical libraries, which enables the accelerated discovery of materials with desired properties. In this study, we developed computational models to predict the dispersancy efficiency of oil and lubricant additives, a critical property in their design that can be estimated through a quantity named blotter spot. We propose a comprehensive approach that combines machine learning techniques with visual analytics strategies in an interactive tool that supports domain experts’ decision-making. We evaluated the proposed models quantitatively and illustrated their benefits through a case study. Specifically, we analyzed a series of virtual polyisobutylene succinimide (PIBSI) molecules derived from a known reference substrate. Our best-performing probabilistic model was Bayesian Additive Regression Trees (BART), which achieved a mean absolute error of 5.50±0.34 and a root mean square error of 7.56±0.47, as estimated through 5-fold cross-validation. To facilitate future research, we have made the dataset, including the potential dispersants used for modeling, publicly available. Our approach can help accelerate the discovery of new oil and lubricant additives, and our interactive tool can aid domain experts in making informed decisions based on blotter spot and other key properties.
Enhanced Yield of Large-Sized Ti3C2Tx MXene Polymers Nanosheets via Cyclic Ultrasonic-Centrifugal Separation
Authors: Hou Kun , Yang Yafeng , Zhou Hu , Chen Xiangmeng , Ge Shengbo
Published: March 2023

Water pollution has spurred the development of membrane separation technology as a potential means of solving the issue. In contrast to the irregular and asymmetric holes that are easily made during the fabrication of organic polymer membranes, forming regular transport channels is essential. This necessitates the use of large-size, two-dimensional materials that can enhance membrane separation performance. However, some limitations regarding yield are associated with preparing large-sized MXene polymer-based nanosheets, which restrict their large-scale application. Here, we propose a combination of wet etching and cyclic ultrasonic-centrifugal separation to meet the needs of the large-scale production of MXene polymers nanosheets. It was found that the yield of large-sized Ti3C2Tx MXene polymers nanosheets reached 71.37%, which was 2.14 times and 1.77 times higher than that prepared with continuous ultrasonication for 10 min and 60 min, respectively. The size of the Ti3C2Tx MXene polymers nanosheets was maintained at the micron level with the help of the cyclic ultrasonic-centrifugal separation technology. In addition, certain advantages of water purification were evident due to the possibility of attaining the pure water flux of 36.5 kg m−2 h−1 bar−1 for the Ti3C2Tx MXene membrane prepared with cyclic ultrasonic-centrifugal separation. This simple method provided a convenient way for the scale-up production of Ti3C2Tx MXene polymers nanosheets.
Microplastic Removal from Drinking Water Using Point-of-Use Devices
Authors: Cherian Ashlyn G. , Liu Zeyuan , McKie Michael J. , Almuhtaram Husein , Andrews Robert C.
Published: March 2023

The occurrence of microplastics in drinking water has drawn increasing attention due to their ubiquity and unresolved implications regarding human health. Despite achieving high reduction efficiencies (70 to >90%) at conventional drinking water treatment plants (DWTPs), microplastics remain. Since human consumption represents a small portion of typical household water use, point-of-use (POU) water treatment devices may provide the additional removal of microplastics (MPs) prior to consumption. The primary objective of this study was to evaluate the performance of commonly used pour-through POU devices, including those that utilize combinations of granular activated carbon (GAC), ion exchange (IX), and microfiltration (MF), with respect to MP removal. Treated drinking water was spiked with polyethylene terephthalate (PET) and polyvinyl chloride (PVC) fragments, along with nylon fibers representing a range of particle sizes (30–1000 µm) at concentrations of 36–64 particles/L. Samples were collected from each POU device following 25, 50, 75, 100 and 125% increases in the manufacturer’s rated treatment capacity, and subsequently analyzed via microscopy to determine their removal efficiency. Two POU devices that incorporate MF technologies exhibited 78–86% and 94–100% removal values for PVC and PET fragments, respectively, whereas one device that only incorporates GAC and IX resulted in a greater number of particles in its effluent when compared to the influent. When comparing the two devices that incorporate membranes, the device with the smaller nominal pore size (0.2 µm vs. ≥1 µm) exhibited the best performance. These findings suggest that POU devices that incorporate physical treatment barriers, including membrane filtration, may be optimal for MP removal (if desired) from drinking water.
The Influence of Sample Size on Long-Term Performance of a 6σ Process
Authors: Boroiu Andrei Alexandru , Titu Aurel Mihail , Boroiu Alexandru , Dragomir Mihai , Pop Alina Bianca , Titu Stefan
Published: March 2023

There are many criticisms for the association between the Six Sigma concept and the two statistical metrics associated to 6σ processes: 1.5σ shift for maximum deviation and 3.4 PPM non-conformities for the long-term performance. As a result, the paper aims to carry out an analysis of this problem, and the first result obtained is that a stable process can reach a maximum drift, but its value depends on the volume of the sample. It is also highlighted that, using only the criterion “values outside the control limits” for monitoring stability through the Xbar chart, a minimum value can be calculated for the long-term performance of a process depending on the sample size. The main conclusion resulting from the calculations is that, in the case of a 6σ process, the long-term performance is much better than the established value of 3400 PPB: For small volume samples of two pieces it is below 700 PPB, for three pieces it is below 200 PPB, and for samples with a volume greater than or equal to four pieces the performance already reaches values below 100 PPB! So, the long-term performance of 6σ processes is certainly even better than the known value of 3.4 PPM.
Tropical Dry Forest Dynamics Explained by Topographic and Anthropogenic Factors: A Case Study in Mexico
Authors: Gao Yan , Solórzano Jonathan V. , Estoque Ronald C. , Tsuyuzaki Shiro
Published: March 2023

Tropical dry forest is one of the most threatened ecosystems, and it is disappearing at an alarming rate. Shifting cultivation is commonly cited as a driver of tropical dry forest loss, although it helps to maintain the forest coverage but with less density. We investigated tropical dry forest dynamics and their contributing factors to find out if there is an equilibrium between these two processes. We classified multi-temporal Sentinel-2A images with machine learning algorithms and used a logistic regression model to associate topographic, anthropogenic, and land tenure variables as plausible factors in the dynamics. We carried out an accuracy assessment of the detected changes in loss and gain considering the imbalance in area proportion between the change classes and the persistence classes. We estimated a 1.4% annual loss rate and a 0.7% annual gain rate in tropical dry forest and found that the topographic variable of slope and the anthropogenic variable of distance to roads helped explain the occurrence probability of both tropical forest loss and tropical forest gain. Since the area estimation yielded a wide confidence interval for both tropical forest loss and gain despite the measures that we took to counterbalance the disproportion in areas, we cannot conclude that the loss process was more intense than the gain process, but rather that there was an equilibrium in tropical dry forest dynamics under the influence of shifting cultivation.
Glaciogenic Periglacial Landform in the Making—Geomorphological Evolution of a Rockfall on a Small Glacier in the Horlachtal, Stubai Alps, Austria
Authors: Fleischer Fabian , Haas Florian , Altmann Moritz , Rom Jakob , Ressl Camillo , Becht Michael
Published: March 2023

Deglaciation in high mountain areas signifies the transition from glacial to periglacial conditioned landscapes. Due to the reduced melt rate of debris-covered glacier ice, these areas of the glacier may persist long after the surrounding glacier has melted, resulting in the formation of distinct post-glacial landforms. In this study, we examine the geomorphological evolution and potential future development of a 19,267 m3 ± 204 m3 rockfall from the permafrost-affected headwall on the low-elevated Zwieselbachferner in the Horlachtal, Stubai Alps, Austria. The analysis uses multi-epochal remote sensing data, including photogrammetrically and airborne laser scanning-derived digital elevation models, orthophotos, and satellite data, covering a period from the initial rockfall in 2003/2004 to 2022. The data reveals that the rockfall event resulted in the formation of a supraglacial debris layer of varying thickness, spanning an area of 15,920 m2. Subsequently, 13 further rockfalls ranging from 67 m3 ± 6 m3 to 4250 m3 ± 121 m3 were detected. The mean ice thickness of the debris-covered area only slightly decreased between 2006 and 2022, in contrast to the surrounding glacier, whose thickness and length have strongly decreased. This results in the formation of a steep front and flanks that become increasingly covered by debris redistribution. The study suggests that the glacier ice covered by rockfall-derived debris will remain as a periglacial landform of glacial origin after the complete melting of the surrounding glacier.
Snow Cover Phenology in Xinjiang Based on a Novel Method and MOD10A1 Data
Authors: Wang Qingxue , Ma Yonggang , Li Junli
Published: March 2023

Using Earth observation to accurately extract snow phenology changes is of great significance for deepening the understanding of the ecological environment and hydrological process, agricultural and animal husbandry production, and high-quality development of the social economy in Xinjiang. Considering snow cover phenology based on MODIS product MOD10A1 data, this paper constructed a method for automatically extracting key phenological parameters in Xinjiang and calculated three key phenological parameters in Xinjiang from 2001 to 2020, including SCD (snow cover duration), SOD (snow onset date), and SED (snow end date). The daily data of four field camera observation points during an overlapping period from 2017 to 2019 were used to evaluate the snow cover phenological parameters extracted by MOD10A1, and the mean absolute error (MAE) and root mean square error (RMSE) values were 0.65 and 1.07, respectively. The results showed the following: 1. The spatiotemporal variation in snow phenology was highly altitude dependent. The mean gradients of SCD in the Altai Mountains, Tienshan Mountains, and Kunlun Mountains is 2.6, 2.1, and 1.2 d/100 m, respectively. The variation trend of snow phenology with latitude and longitude was mainly related to the topography of Xinjiang. Snow phenological parameters of different land-use types were different. The SCD values in wasteland were the lowest and the SED was the earliest, while forest land was the first to enter SOD accumulation. According to the study, the mean annual values of SCD, SOD, and SED were 25, 342 (8 December), and 51 (8 February) as day of year (DOY), respectively. The snow cover area was mainly distributed in the Altai Mountains, Junggar Basin, Tianshan Mountains, and Kunlun Mountains. 2. The variation trend and significance of snow cover phenological parameters in different regions are different, and the variation trend of snow cover phenological parameters in most regions of Xinjiang is non-significant.
Multi-GNSS Differential Inter-System Bias Estimation for Smartphone RTK Positioning: Feasibility Analysis and Performance
Authors: Shang Rui , Gao Chengfa , Gan Lu , Zhang Ruicheng , Gao Wang , Meng Xiaolin
Published: March 2023

An inter-system model for multi-GNSSs (global navigation satellite systems) makes the interoperability among different GNSS constellations possible. In recent years, inter-system models for geodetic receivers have been extensively studied. However, the precise positioning of smartphones suffers from various problems, and the current research mostly focuses on how to achieve the GNSS ambiguity resolution. Based on the research of receiver channel-dependent bias, in this study, we will research the temporal behaviors of differential inter-system bias (DISB) and implement an inter-system model for smartphones. A representative Huawei P40 (HP40) smartphone was used in the experiments, and the results show the following: (1) For the HP40, the frequencies of Code Division Multiple Access (CDMA) systems are free of receiver channel-dependent phase bias, which provides the chances for further interoperability among these systems. However, the code observations of the HP40 are influenced by receiver channel-dependent code bias; it is therefore suggested to set a large initial standard deviation (STD) value for code observations in the positioning. (2) GPS L1/QZSS L1 and BDS-2 B1I /BDS-3 B1I are free of phase DISB, and there is obvious phase DISB between GPS L1 and Galileo E1; even so, the valuations are sufficiently stable and the STD is close to 0.005 cycles. However, the phase DISB of GPS L1/BDS B1I is unstable. (3) For kinematic positioning, when the stable phase DISB is introduced, a 3–38.9% improvement in the N/E/U directions of the positioning accuracies in the inter-system differencing is achieved compared with the intra-system differencing.
Identification and Classification of Small Sample Desert Grassland Vegetation Communities Based on Dynamic Graph Convolution and UAV Hyperspectral Imagery
Authors: Zhang Tao , Bi Yuge , Zhu Xiangbing , Gao Xinchao
Published: March 2023

Desert steppes are the last barrier to protecting the steppe ecosystem. However, existing grassland monitoring methods still mainly use traditional monitoring methods, which have certain limitations in the monitoring process. Additionally, the existing deep learning classification models of desert and grassland still use traditional convolutional neural networks for classification, which cannot adapt to the classification task of irregular ground objects, which limits the classification performance of the model. To address the above problems, this paper uses a UAV hyperspectral remote sensing platform for data acquisition and proposes a spatial neighborhood dynamic graph convolution network (SN_DGCN) for degraded grassland vegetation community classification. The results show that the proposed classification model had the highest classification accuracy compared to the seven classification models of MLP, 1DCNN, 2DCNN, 3DCNN, Resnet18, Densenet121, and SN_GCN; its OA, AA, and kappa were 97.13%, 96.50%, and 96.05% in the case of only 10 samples per class of features, respectively; The classification performance was stable under different numbers of training samples, had better generalization ability in the classification task of small samples, and was more effective for the classification task of irregular features. Meanwhile, the latest desert grassland classification models were also compared, which fully demonstrated the superior classification performance of the proposed model in this paper. The proposed model provides a new method for the classification of vegetation communities in desert grasslands, which is helpful for the management and restoration of desert steppes.
A Study on the Effectiveness of Deep Learning-Based Anomaly Detection Methods for Breast Ultrasonography
Authors: Yun Changhee , Eom Bomi , Park Sungjun , Kim Chanho , Kim Dohwan , Jabeen Farah , Kim Won Hwa , Kim Hye Jung , Kim Jaeil
Published: March 2023

In the medical field, it is delicate to anticipate good performance in using deep learning due to the lack of large-scale training data and class imbalance. In particular, ultrasound, which is a key breast cancer diagnosis method, is delicate to diagnose accurately as the quality and interpretation of images can vary depending on the operator’s experience and proficiency. Therefore, computer-aided diagnosis technology can facilitate diagnosis by visualizing abnormal information such as tumors and masses in ultrasound images. In this study, we implemented deep learning-based anomaly detection methods for breast ultrasound images and validated their effectiveness in detecting abnormal regions. Herein, we specifically compared the sliced-Wasserstein autoencoder with two representative unsupervised learning models autoencoder and variational autoencoder. The anomalous region detection performance is estimated with the normal region labels. Our experimental results showed that the sliced-Wasserstein autoencoder model outperformed the anomaly detection performance of others. However, anomaly detection using the reconstruction-based approach may not be effective because of the occurrence of numerous false-positive values. In the following studies, reducing these false positives becomes an important challenge.
PointPainting: 3D Object Detection Aided by Semantic Image Information
Authors: Gao Zhentong , Wang Qiantong , Pan Zongxu , Zhai Zhenyu , Long Hui
Published: March 2023

A multi-modal 3D object-detection method, based on data from cameras and LiDAR, has become a subject of research interest. PointPainting proposes a method for improving point-cloud-based 3D object detectors using semantic information from RGB images. However, this method still needs to improve on the following two complications: first, there are faulty parts in the image semantic segmentation results, leading to false detections. Second, the commonly used anchor assigner only considers the intersection over union (IoU) between the anchors and ground truth boxes, meaning that some anchors contain few target LiDAR points assigned as positive anchors. In this paper, three improvements are suggested to address these complications. Specifically, a novel weighting strategy is proposed for each anchor in the classification loss. This enables the detector to pay more attention to anchors containing inaccurate semantic information. Then, SegIoU, which incorporates semantic information, instead of IoU, is proposed for the anchor assignment. SegIoU measures the similarity of the semantic information between each anchor and ground truth box, avoiding the defective anchor assignments mentioned above. In addition, a dual-attention module is introduced to enhance the voxelized point cloud. The experiments demonstrate that the proposed modules obtained significant improvements in various methods, consisting of single-stage PointPillars, two-stage SECOND-IoU, anchor-base SECOND, and an anchor-free CenterPoint on the KITTI dataset.
Cognitive Video Surveillance Management in Hierarchical Edge Computing System with Long Short-Term Memory Model
Authors: Ugli Dilshod Bazarov Ravshan , Kim Jingyeom , Mohammed Alaelddin F. Y. , Lee Joohyung
Published: March 2023

Nowadays, deep learning (DL)-based video surveillance services are widely used in smart cities because of their ability to accurately identify and track objects, such as vehicles and pedestrians, in real time. This allows a more efficient traffic management and improved public safety. However, DL-based video surveillance services that require object movement and motion tracking (e.g., for detecting abnormal object behaviors) can consume a substantial amount of computing and memory capacity, such as (i) GPU computing resources for model inference and (ii) GPU memory resources for model loading. This paper presents a novel cognitive video surveillance management with long short-term memory (LSTM) model, denoted as the CogVSM framework. We consider DL-based video surveillance services in a hierarchical edge computing system. The proposed CogVSM forecasts object appearance patterns and smooths out the forecast results needed for an adaptive model release. Here, we aim to reduce standby GPU memory by model release while avoiding unnecessary model reloads for a sudden object appearance. CogVSM hinges on an LSTM-based deep learning architecture explicitly designed for future object appearance pattern prediction by training previous time-series patterns to achieve these objectives. By referring to the result of the LSTM-based prediction, the proposed framework controls the threshold time value in a dynamic manner by using an exponential weighted moving average (EWMA) technique. Comparative evaluations on both simulated and real-world measurement data on the commercial edge devices prove that the LSTM-based model in the CogVSM can achieve a high predictive accuracy, i.e., a root-mean-square error metric of 0.795. In addition, the suggested framework utilizes up to 32.1% less GPU memory than the baseline and 8.9% less than previous work.