bluuebunny/crossref_metadata_2025 huggingface dataset:
Metabolic Soft Spot and Pharmacokinetics: Functionalization of C-3 Position of an Eph–Ephrin Antagonist Featuring a Bile Acid Core as an Effective Strategy to Obtain Oral Bioavailability in Mice
Authors: Ferlenghi Francesca , Giorgio Carmine , Incerti Matteo , Guidetti Lorenzo , Chiodelli Paola , Rusnati Marco , Tognolini Massimiliano , Vacondio Federica , Mor Marco , Lodola Alessio
Published: December 2021

UniPR129, an L-β-homotryptophan conjugate of the secondary bile acid lithocholic acid (LCA), acts as an effective protein-protein interaction (PPI) inhibitor of the Eph–ephrin system but suffers from a poor oral bioavailability in mice. To improve UniPR129 bioavailability, a metabolic soft spot, i.e., the 3α-hydroxyl group on the LCA steroidal ring, was functionalized to 3-hydroxyimine. In vitro metabolism of UniPR129 and 3-hydroxyimine derivative UniPR500 was compared in mouse liver subcellular fractions, and main metabolites were profiled by high resolution (HR-MS) and tandem (MS/MS) mass spectrometry. In mouse liver microsomes (MLM), UniPR129 was converted into several metabolites: M1 derived from the oxidation of the 3-hydroxy group to 3-oxo, M2–M7, mono-hydroxylated metabolites, M8–M10, di-hydroxylated metabolites, and M11, a mono-hydroxylated metabolite of M1. Phase II reactions were only minor routes of in vitro biotransformation. UniPR500 shared several metabolic pathways with parent UniPR129, but it showed higher stability in MLM, with a half-life (t1/2) of 60.4 min, if compared to a t1/2 = 16.8 min for UniPR129. When orally administered to mice at the same dose, UniPR500 showed an increased systemic exposure, maintaining an in vitro valuable pharmacological profile as an EphA2 receptor antagonist and an overall improvement in its physico-chemical profile (solubility, lipophilicity), if compared to UniPR129. The present work highlights an effective strategy for the pharmacokinetic optimization of aminoacid conjugates of bile acids as small molecule Eph–ephrin antagonists.
Influence of Cold-TRP Receptors on Cold-Influenced Behaviour
Authors: Thapa Dibesh , Barrett Brentton , Argunhan Fulye , Brain Susan D.
Published: December 2021

The transient receptor potential (TRP) channels, TRPA1 and TRPM8, are thermo-receptors that detect cold and cool temperatures and play pivotal roles in mediating the cold-induced vascular response. In this study, we investigated the role of TRPA1 and TRPM8 in the thermoregulatory behavioural responses to environmental cold exposure by measuring core body temperature and locomotor activity using a telemetry device that was surgically implanted in mice. The core body temperature of mice that were cooled at 4 °C over 3 h was increased and this was accompanied by an increase in UCP-1 and TRPM8 level as detected by Western blot. We then established an effective route, by which the TRP antagonists could be administered orally with palatable food. This avoids the physical restraint of mice, which is crucial as that could influence the behavioural results. Using selective pharmacological antagonists A967079 and AMTB for TRPA1 and TRPM8 receptors, respectively, we show that TRPM8, but not TRPA1, plays a direct role in thermoregulation response to whole body cold exposure in the mouse. Additionally, we provide evidence of increased TRPM8 levels after cold exposure which could be a protective response to increase core body temperature to counter cold.
Albumin–Methotrexate Prodrug Analogues That Undergo Intracellular Reactivation Following Entrance into Cancerous Glioma Cells
Authors: Cooper Itzik , Schnaider-Beeri Michal , Fridkin Mati , Shechter Yoram
Published: December 2021

A family of monomodified bovine serum albumin (BSA) linked to methotrexate (MTX) through a variety of spacers was prepared. All analogues were found to be prodrugs having low MTX-inhibitory potencies toward dihydrofolate reductase in a cell-free system. The optimal conjugates regenerated their antiproliferative efficacies following entrance into cancerous glioma cell lines and were significantly superior to MTX in an insensitive glioma cell line. A BSA–MTX conjugate linked through a simple ethylene chain spacer, containing a single peptide bond located 8.7 Å distal to the protein back bone, and apart from the covalently linked MTX by about 12 Å, was most effective. The inclusion of an additional disulfide bond in the spacer neither enhanced nor reduced the killing potency of this analogue. Disrupting the native structure of the carrier protein in the conjugates significantly reduced their antiproliferative activity. In conclusion, we have engineered BSA–MTX prodrug analogues which undergo intracellular reactivation and facilitate antiproliferative activities following their entrance into glioma cells.
New, Biocompatible, Chitosan-Gelled Microemulsions Based on Essential Oils and Sucrose Esters as Nanocarriers for Topical Delivery of Fluconazole
Authors: Vlaia Lavinia , Olariu Ioana , Muţ Ana Maria , Coneac Georgeta , Vlaia Vicenţiu , Anghel Dan Florin , Maxim Monica Elisabeta , Stângă Gabriela , Dobrescu Amadeus , Suciu Maria , Szabadai Zoltan , Lupuleasa Dumitru
Published: December 2021

Biocompatible gel microemulsions containing natural origin excipients are promising nanocarrier systems for the safe and effective topical application of hydrophobic drugs, including antifungals. Recently, to improve fluconazole skin permeation, tolerability and therapeutic efficacy, we developed topical biocompatible microemulsions based on cinnamon, oregano or clove essential oil (CIN, ORG or CLV) as the oil phase and sucrose laurate (D1216) or sucrose palmitate (D1616) as surfactants, excipients also possessing intrinsic antifungal activity. To follow up this research, this study aimed to improve the adhesiveness of respective fluconazole microemulsions using chitosan (a biopolymer with intrinsic antifungal activity) as gellator and to evaluate the formulation variables’ effect (composition and concentration of essential oil, sucrose ester structure) on the gel microemulsions’ (MEGELs) properties. All MEGELs were evaluated for drug content, pH, rheological behavior, viscosity, spreadability, in vitro drug release and skin permeation and antifungal activity. The results showed that formulation variables determined distinctive changes in the MEGELs’ properties, which were nevertheless in accordance with official requirements for semisolid preparations. The highest flux and release rate values and large diameters of the fungal growth inhibition zone were produced by formulations MEGEL-FZ-D1616-CIN 10%, MEGEL-FZ-D1216-CIN 10% and MEGEL-FZ-D1616-ORG 10%. In conclusion, these MEGELs were demonstrated to be effective platforms for fluconazole topical delivery.
TYMS 3′-UTR Polymorphism: A Novel Association with FOLFIRINOX-Induced Neurotoxicity in Pancreatic Cancer Patients
Authors: Emelyanova Marina , Pokataev Ilya , Shashkov Igor , Kopantseva Elena , Lyadov Vladimir , Heydarov Rustam , Mikhailovich Vladimir
Published: December 2021

Pancreatic ductal adenocarcinoma (PDAC) is a highly fatal malignancy that has the worst 5-year survival rate of all of the common malignant tumors. Surgery, chemotherapy, and/or chemoradiation remain the main tactics for PDAC treatment. The efficacy of chemotherapy is often compromised because of the substantial risk of severe toxicities. In our study, we focused on identification of polymorphisms in the genes involved in drug metabolism, DNA repair and replication that are associated with inter-individual differences in drug-induced toxicities. Using the microarray, we genotyped 12 polymorphisms in the DPYD, XPC, GSTP1, MTHFR, ERCC1, UGT1A1, and TYMS genes in 78 PDAC patients treated with FOLFIRINOX. It was found that the TYMS rs11280056 polymorphism (6 bp-deletion in TYMS 3′-UTR) predicted grade 1–2 neurotoxicity (p = 0.0072 and p = 0.0019, according to co-dominant (CDM) and recessive model (RM), respectively). It is the first report on the association between TYMS rs11280056 and peripheral neuropathy. We also found that PDAC patients carrying the GSTP1 rs1695 GG genotype had a decreased risk for grade 3–4 hematological toxicity as compared to those with the AA or AG genotypes (p = 0.032 and p = 0.014, CDM and RM, respectively). Due to relatively high p-values, we consider that the impact of GSTP1 rs1695 requires further investigation in a larger sample size.
Overcoming MDR by Associating Doxorubicin and pH-Sensitive PLGA Nanoparticles Containing a Novel Organoselenium Compound—An In Vitro Study
Authors: Macedo Letícia Bueno , Nogueira-Librelotto Daniele Rubert , Mathes Daniela , de Vargas Josiele Melo , da Rosa Raquel Mello , Rodrigues Oscar Endrigo Dorneles , Vinardell Maria Pilar , Mitjans Montserrat , Rolim Clarice Madalena Bueno
Published: December 2021

In this study, we developed PLGA nanoparticles (NPs) as an effective carrier for 5′-Se-(phenyl)-3-(amino)-thymidine (ACAT-Se), an organoselenium compound, nucleoside analogue that showed promising antitumor activity in vitro. The PLGA NPs were prepared by the nanoprecipitation method and modified with a pH-responsive lysine-based surfactant (77KL). The ACAT-Se-PLGA-77KL-NPs presented nanometric size (around 120 nm), polydispersity index values < 0.20 and negative zeta potential values. The nanoencapsulation of ACAT-Se increased its antioxidant (DPPH and ABTS assays) and antitumor activity in MCF-7 tumor cells. Hemolysis study indicated that ACAT-Se-PLGA-77KL-NPs are hemocompatible and that 77KL provided a pH-sensitive membranolytic behavior to the NPs. The NPs did not induce cytotoxic effects on the nontumor cell line 3T3, suggesting its selectivity for the tumor cells. Moreover, the in vitro antiproliferative activity of NPs was evaluated in association with the antitumor drug doxorubicin. This combination result in synergistic effect in sensitive (MCF-7) and resistant (NCI/ADR-RES) tumor cells, being especially able to successfully sensitize the MDR cells. The obtained results suggested that the proposed ACAT-Se-loaded NPs are a promising delivery system for cancer therapy, especially associated with doxorubicin.
Self-Assessment of Cultural Competence and Social Determinants of Health within a First-Year Required Pharmacy Course
Authors: Kucherepa Ulyana , O’Connell Mary Beth
Published: December 2021

As social determinants of health (SDOH) and health disparities are integrated with cultural competence in healthcare education, tools assessing multiple topics are needed. The Self-Assessment of Perceived Level of Cultural Competence (SAPLCC) survey is validated in student pharmacists and includes SDOH. The research objective was to determine if the SAPLCC survey can quantify cultural competence and SDOH course learning. First-year student pharmacists (N = 87) completed the SAPLCC survey anonymously before and after a social and administrative sciences course. The survey had 75 items with 1–4 Likert scales (4 high, total 300 points). All items were summed for the total score. Each item was assigned to a domain and factor. Factors were assigned to domains. The baseline total score was 190 ± 29 points, increasing by 63 ± 33 points post-course. All domains (i.e., knowledge, skills, attitudes, encounters, abilities, awareness), 13 of 14 factors, and total scores statistically increased. The SAPLCC tool captured student pharmacists’ self-reported changes in cultural competence and SDOH.
Toward Real-Time Giga-Voxel Optoacoustic/Photoacoustic Microscopy: GPU-Accelerated Fourier Reconstruction with Quasi-3D Implementation
Authors: Subochev Pavel , Spadin Florentin , Perekatova Valeriya , Khilov Aleksandr , Kovalchuk Andrey , Pavlova Ksenia , Kurnikov Alexey , Frenz Martin , Jaeger Michael
Published: December 2021

We propose a GPU-accelerated implementation of frequency-domain synthetic aperture focusing technique (SAFT) employing truncated regularized inverse k-space interpolation. Our implementation achieves sub-1s reconstruction time for data sizes of up to 100 M voxels, providing more than a tenfold decrease in reconstruction time as compared to CPU-based SAFT. We provide an empirical model that can be used to predict the execution time of quasi-3D reconstruction for any data size given the specifications of the computing system.
Efficiency of Photoconductive Terahertz Generation in Nitrogen-Doped Diamonds
Authors: Kononenko Vitali V. , Komlenok Maxim S. , Chizhov Pavel A. , Bukin Vladimir V. , Bulgakova Vladislava V. , Khomich Andrey A. , Bolshakov Andrey P. , Konov Vitaly I. , Garnov Sergey V.
Published: December 2021

The efficiency of the generation of terahertz radiation from nitrogen-doped (∼0.1–100 ppm) diamonds was investigated. The synthetic polycrystalline and monocrystalline diamond substrates were pumped by a 400 nm femtosecond laser and tested for the photoconductive emitter operation. The dependency of the emitted THz power on the intensity of the optical excitation was measured. The nitrogen concentrations of the diamonds involved were measured from the optical absorbance, which was found to crucially depend on the synthesis technique. The observed correlation between the doping level and the level of the performance of diamond-based antennas demonstrates the prospects of doped diamond as a material for highly efficient large-aperture photoconductive antennas.
High-Temperature and Drought Stress Effects on Growth, Yield and Nutritional Quality with Transpiration Response to Vapor Pressure Deficit in Lentil
Authors: El Haddad Noureddine , Choukri Hasnae , Ghanem Michel Edmond , Smouni Abdelaziz , Mentag Rachid , Rajendran Karthika , Hejjaoui Kamal , Maalouf Fouad , Kumar Shiv
Published: December 2021

High temperature and water deficit are among the major limitations reducing lentil (Lens culinaris Medik.) yield in many growing regions. In addition, increasing atmospheric vapor pressure deficit (VPD) due to global warming causes a severe challenge by influencing the water balance of the plants, thus also affecting growth and yield. In the present study, we evaluated 20 lentil genotypes under field conditions and controlled environments with the following objectives: (i) to investigate the impact of temperature stress and combined temperature-drought stress on traits related to phenology, grain yield, nutritional quality, and canopy temperature under field conditions, and (ii) to examine the genotypic variability for limited transpiration (TRlim) trait in response to increased VPD under controlled conditions. The field experiment results revealed that high-temperature stress significantly affected all parameters compared to normal conditions. The protein content ranged from 23.4 to 31.9%, while the range of grain zinc and iron content varied from 33.1 to 64.4 and 62.3 to 99.3 mg kg−1, respectively, under normal conditions. The grain protein content, zinc and iron decreased significantly by 15, 14 and 15% under high-temperature stress, respectively. However, the impact was more severe under combined temperature-drought stress with a reduction of 53% in protein content, 18% in zinc and 20% in iron. Grain yield declined significantly by 43% in temperature stress and by 49% in the combined temperature-drought stress. The results from the controlled conditions showed a wide variation in TR among studied lentil genotypes. Nine genotypes displayed TRlim at 2.76 to 3.51 kPa, with the genotypes ILL 7833 and ILL 7835 exhibiting the lowest breakpoint. Genotypes with low breakpoints had the ability to conserve water, allowing it to be used at later stages for increased yield. Our results identified promising genotypes including ILL 7835, ILL 7814 and ILL 4605 (Bakria) that could be of great interest in breeding for high yields, protein and micronutrient contents under high-temperature and drought stress. In addition, it was found that the TRlim trait has the potential to select for increased lentil yields under field water-deficit environments.
Cyclodextrins in Polymer-Based Active Food Packaging: A Fresh Look at Nontoxic, Biodegradable, and Sustainable Technology Trends
Authors: Velázquez-Contreras Friné , Zamora-Ledezma Camilo , López-González Iván , Meseguer-Olmo Luis , Núñez-Delicado Estrella , Gabaldón José Antonio
Published: December 2021

Using cyclodextrins (CDs) in packaging technologies helps volatile or bioactive molecules improve their solubility, to guarantee the homogeneous distribution of the complexed molecules, protecting them from volatilization, oxidation, and temperature fluctuations when they are associated with polymeric matrices. This technology is also suitable for the controlled release of active substances and allows the exploration of their association with biodegradable polymer targeting to reduce the negative environmental impacts of food packaging. Here, we present a fresh look at the current status of and future prospects regarding the different strategies used to associate cyclodextrins and their derivatives with polymeric matrices to fabricate sustainable and biodegradable active food packaging (AFP). Particular attention is paid to the materials and the fabrication technologies available to date. In addition, the use of cutting-edge strategies, including the trend of nanotechnologies in active food packaging, is emphasized. Furthermore, a critical view on the risks to human health and the associated updated legislation is provided. Some of the more representative patents and commercial products that currently use AFP are also listed. Finally, the current and future research challenges which must be addressed are discussed.
Correction: Foroozani Behbahani, A.; Harmandaris, V. Gradient of Segmental Dynamics in Stereoregular Poly(methyl methacrylate) Melts Confined between Pristine or Oxidized Graphene Sheets. Polymers 2021, 13, 830
Authors: Foroozani Behbahani Alireza , Harmandaris Vagelis
Published: December 2021

The authors wish to make the following corrections to this paper: [...]
Progressing Ultragreen, Energy-Efficient Biobased Depolymerization of Poly(ethylene terephthalate) via Microwave-Assisted Green Deep Eutectic Solvent and Enzymatic Treatment
Authors: Attallah Olivia A. , Azeem Muhammad , Nikolaivits Efstratios , Topakas Evangelos , Fournet Margaret Brennan
Published: December 2021

Effective interfacing of energy-efficient and biobased technologies presents an all-green route to achieving continuous circular production, utilization, and reproduction of plastics. Here, we show combined ultragreen chemical and biocatalytic depolymerization of polyethylene terephthalate (PET) using deep eutectic solvent (DES)-based low-energy microwave (MW) treatment followed by enzymatic hydrolysis. DESs are emerging as attractive sustainable catalysts due to their low toxicity, biodegradability, and unique biological compatibility. A green DES with triplet composition of choline chloride, glycerol, and urea was selected for PET depolymerization under MW irradiation without the use of additional depolymerization agents. Treatment conditions were studied using Box-Behnken design (BBD) with respect to MW irradiation time, MW power, and volume of DES. Under the optimized conditions of 20 mL DES volume, 260 W MW power, and 3 min MW time, a significant increase in the carbonyl index and PET percentage weight loss was observed. The combined MW-assisted DES depolymerization and enzymatic hydrolysis of the treated PET residue using LCC variant ICCG resulted in a total monomer conversion of ≈16% (w/w) in the form of terephthalic acid, mono-(2-hydroxyethyl) terephthalate, and bis-(2-hydroxyethyl) terephthalate. Such high monomer conversion in comparison to enzymatically hydrolyzed virgin PET (1.56% (w/w)) could be attributed to the recognized depolymerization effect of the selected DES MW treatment process. Hence, MW-assisted DES technology proved itself as an efficient process for boosting the biodepolymerization of PET in an ultrafast and eco-friendly manner.
Evaluation of Particleboards Made from Giant Reed (Arundo donax L.) Bonded with Cement and Potato Starch
Authors: Ferrandez-García Aranzazu Alejandra , Ortuño Teresa Garcia , Ferrandez-Villena Manuel , Ferrandez-Garcia Antonio , Ferrandez-García Maria Teresa
Published: December 2021

There is a general concern about the rationalization of resources and the management of waste. Plant residues can contribute to the development of new non-polluting construction materials. The objective of this study was to valorize a plant residue such as the giant reed and obtain a particleboard with cement using potato starch as a plasticizer in a manufacturing process involving compression and heat. The influence of cement and starch in different proportions and its stability over time were analyzed. Finally, their physical and mechanical properties were evaluated and compared to European Standards. High-quality sustainable particleboards (boards with high structural performance) were obtained and can be classified as P6 according to European Standards. Mechanical properties were improved by increasing the starch content and pressing time, whereas greater resistance to water was obtained by increasing the cement content. Giant reed particles seem to tolerate the alkalinity of the cement since there was no sign of degradation of its fibers. The use of these residues in the manufacture of construction materials offers a very attractive alternative in terms of price, technology and sustainability.
The Mechanics of Forming Ideal Polymer–Solvent Combinations for Open-Loop Chemical Recycling of Solvents and Plastics
Authors: Tsampanakis Ioannis , Orbaek White Alvin
Published: December 2021

The inherent value and use of hydrocarbons from waste plastics and solvents can be extended through open-loop chemical recycling, as this process converts plastic to a range of non-plastic materials. This process is enhanced by first creating plastic–solvent combinations from multiple sources, which then are streamlined through a single process stream. We report on the relevant mechanics for streamlining industrially relevant polymers such as polystyrene (PS), polypropylene (PP), high-density polyethylene (HDPE), and acrylonitrile butadiene styrene (ABS) into chemical slurries mixed with various organic solvents such as toluene, xylene, and cyclohexane. The miscibility of the polymer feedstock within the solvent was evaluated using the Relative Energy Difference method, and the dissolution process was evaluated using the “Molecular theories in a continuum framework” model. These models were used to design a batch process yielding 1 tonne/h slurry by setting appropriate assumptions including constant viscosity of solvents, disentanglement-controlled dissolution mechanism, and linear increase in the dissolved polymer’s mass fraction over time. Solvent selection was found to be the most critical parameter for the dissolution process. The characteristics of the ideal solvent are high affinity to the desired polymer and low viscosity. This work serves as a universal technical guideline for the open-loop chemical recycling of plastics, avoiding the growth of waste plastic by utilising them as a carbon feedstock towards a circular economy framework.
Enhanced Saccharification of Purple Alfalfa via Sequential Pretreatment with Acidified Ethylene Glycol and Urea/NaOH
Authors: Fan Bo , Zhang Lin , Tang Zhengyu , Chen Liang , He Yu-Cai
Published: December 2021

Purple Alfalfa is an inexpensive, abundant, readily available lignocellulosic material. This work was attempted to develop an efficient combination pretreatment by sequential HClO4–ethyl glycol–H2O (1.2:88.8:10, w/w/w) extraction at 130 °C in 0.5 h and urea/NaOH (urea 12 wt%, NaOH 7 wt%) soaking at −20 °C for 0.5 h for the pretreatment of purple alfalfa. The porosity, morphology, and crystallinity of pretreated purple alfalfa were characterized with SEM, FM, XRD, and FTIR. This combination pretreatment had a significant influence on hemicellulose removal and delignification. The above changes could enhance cellulose accessibility to enzymes and improve the enzymatic digestibility of cellulose. High yields of reducing sugars from pretreated purple alfalfa were obtained at 93.4%. In summary, this combination pretreatment has high potential application in the future.
Numerical Simulation of New Axial Flow Gas-Liquid Separator
Authors: Kou Jie , Li Zhaoyang
Published: December 2021

At present, most of the incoming liquids from the oilfield combined stations are not pre-separated for natural gas, which makes the subsequent process of oil-water separation less effective. Therefore, it is necessary to carry out gas-liquid separation. A new type of axial flow gas-liquid separator was proposed in this paper. The numerical simulation was carried out by CFD FLUENT software, and the changes of concentration field, velocity field and pressure field in the axial flow gas-liquid separator were analyzed. It was found that there were gas-liquid separation developments and stabilization segments in the inner cylinder of the separator. The axial velocity will form a zero-speed envelope in the inner cylinder, and the direction of the velocity in front of and behind the zero-speed envelope was opposite. The tangential velocity showed a “W” shape distribution in the radial position of the inner cylinder. The pressure on the left wall of the guide vane was higher than that on the right side. Therefore, the left wall was more likely to be damaged than the right wall.
In the Shadow of Death: Jewish Affirmations of Life
Authors: Mendes-Flohr Paul
Published: December 2021

The Book of Genesis reports that “On the sixth day of Creation “God saw everything that he had made, and behold, it was very good” (1:31). The very, so a Talmudic sage taught refers to “death”. We are to share God’s exultant affirmation of His work of creation as culminating in death. For death is intrinsic to the blessings of life. As Buber notes in the epigraph cited above, life is “unspeakably beautiful because death looks over our shoulder”. The seeming paradox—an existential antinomy—inflected the vernacular Yiddish of my late father which was also that of Buber’s youth “the one thing needful” (Luke 10:42); “love is strong as death” (Song of Songs; 8:6).
The Architecture of Eco-Theology: Towards a New Typology for Christian Sacred Space
Authors: Chiotti Roberto
Published: December 2021

This paper will begin by exploring the underlying scriptural and theological foundations for a Christian response to the ecological crisis with particular focus on the writings of cultural historian, Father Thomas Berry, CP. It will then describe the first worship space in Canada that attempts to embody the emergent “Eco-theology” to invoke both the transcendental and imminent presence of the divine by reconsidering every design decision from first principles. As articulated in its architecture, the traditional elements of Roman Catholic sacred space have been re-imagined and given unique expression to emphasize that when we gather for Christian worship, we do so within the greater context of creation. St. Gabriel’s Passionist Parish church therefore represents a distinctly new typology for Christian Worship that contributes towards an understanding of early scriptural teachings which emphasized the sacredness of all creation and not just the sacredness of humankind. The new building as sacred space presents a “Gestalt whole”, and like the medieval cathedrals of Europe, becomes itself a form of Catechetical pedagogy, engaging the senses, demanding reflection, and inviting transformation.
Hugh MacDiarmid’s ‘On Raised Beach’: ‘Geopoetics’ in a Time of Catastrophic Crisis’
Authors: Roberts Richard H.
Published: December 2021

The poet Hugh MacDiarmid (1892–1978) was the major driving force behind the twentieth-century Scottish literary renaissance and was also a passionate Scottish nationalist. His poem ‘On a Raised Beach’ (1934) has been understood in theological and philosophical terms as a metaphysical exploration, albeit one grounded in an immediate experience of nature that took place on Shetland. In this paper, MacDiarmid’s epic is placed in the context of the present environmental crisis and the ongoing consequences of the COVID-19 pandemic. ‘On a Raised Beach’ can now be re-located within the hermeneutical tradition of ‘Geopoetics’, a Scottish genre that is articulated and asserted by the poet Kenneth White (1938–). Whilst, however, White draws upon the highly contested and polyvalent concept of ‘shamanism’ in elaborating his standpoint, we shall argue that it is also appropriate to look for affinities between this dynamic poem and the ethos and mysticism of ‘deep ecology’, a perspective that invokes the equally contested mythology of ‘Gaia’.
Mechatronic Model of a Compliant 3PRS Parallel Manipulator
Authors: Ruiz Antonio , Campa Francisco J. , Altuzarra Oscar , Herrero Saioa , Diez Mikel
Published: December 2021

Compliant mechanisms are widely used for instrumentation and measuring devices for their precision and high bandwidth. In this paper, the mechatronic model of a compliant 3PRS parallel manipulator is developed, integrating the inverse and direct kinematics, the inverse dynamic problem of the manipulator and the dynamics of the actuators and the control. The kinematic problem is solved, assuming a pseudo-rigid model for the deflection in the compliant revolute and spherical joints. The inverse dynamic problem is solved, using the Principle of Energy Equivalence. The mechatronic model allows the prediction of the bandwidth of the manipulator motion in the 3 degrees of freedom for a given control and set of actuators, helping in the design of the optimum solution. A prototype is built and validated, comparing experimental signals with the ones from the model.
Assessing Waterlogging Stress Level of Winter Wheat from Hyperspectral Imagery Based on Harmonic Analysis
Authors: Yang Feifei , Liu Shengping , Wang Qiyuan , Liu Tao , Li Shijuan
Published: December 2021

Frequent waterlogging disasters can have serious effects on regional ecology, food safety, and socioeconomic sustainable development. Early monitoring of waterlogging stress levels is vital for accurate production input management and reduction of crop production-related risks. In this study, a pot experiment on winter wheat was designed using three varieties and seven gradients of waterlogging stress. Hyperspectral imagery of the winter wheat canopy in the jointing stage, heading stage, flowering stage, filling stage, and maturation stage were measured and then classified. Wavebands of imaging data were screened. Waterlogging stress level was assessed by a combined harmonic analysis method, and application of this method at field scale was discussed preliminarily. Results show that compared to the k-nearest neighbor and support vector machine algorithms, the random forest algorithm is the best batch classification method for hyperspectral imagery of potted winter wheat. It can recognize waterlogging stress well in the wavebands of red absorption valley (RW: 640–680 nm), red-edge (RE: 670–737 nm), and near-infrared (NIR: 700–900 nm). In the RW region, amplitudes of the first three harmonic sub-signals (c1, c2, and c3) can be used as indexes to recognize the waterlogging stress level that each winter wheat variety undertakes. The third harmonic sub-signal amplitude c3 of the RE region is also suitable for judging stress levels of JM31 (one of the three varieties which is highly sensitive to water content). This study has important theoretical significance and practical application values related to the accurate control of waterlogging stress, and functions as a new method to monitor other types of environmental stress levels such as drought stress, freezing stress, and high-temperature stress levels.
GMT-WGAN: An Adversarial Sample Expansion Method for Ground Moving Targets Classification
Authors: Yao Xin , Shi Xiaoran , Li Yaxin , Wang Li , Wang Han , Ren Shijie , Zhou Feng
Published: December 2021

In the field of target classification, detecting a ground moving target that is easily covered in clutter has been a challenge. In addition, traditional feature extraction techniques and classification methods usually rely on strong subjective factors and prior knowledge, which affect their generalization capacity. Most existing deep-learning-based methods suffer from insufficient feature learning due to the lack of data samples, which makes it difficult for the training process to converge to a steady-state. To overcome these limitations, this paper proposes a Wasserstein generative adversarial network (WGAN) sample enhancement method for ground moving target classification (GMT-WGAN). First, the micro-Doppler characteristics of ground moving targets are analyzed. Next, a WGAN is constructed to generate effective time–frequency images of ground moving targets and thereby enrich the sample database used to train the classification network. Then, image quality evaluation indexes are introduced to evaluate the generated spectrogram samples, with an aim to verify the distribution similarity of generated and real samples. Afterward, by feeding augmented samples to the deep convolutional neural networks with good generalization capacity, the classification performance of the GMT-WGAN is improved. Finally, experiments conducted on different datasets validate the effectiveness and robustness of the proposed method.
Detection of Larch Forest Stress from Jas’s Larch Inchworm (Erannis jacobsoni Djak) Attack Using Hyperspectral Remote Sensing
Authors: Xi Guilin , Huang Xiaojun , Xie Yaowen , Gang Bao , Bao Yuhai , Dashzebeg Ganbat , Nanzad Tsagaantsooj , Dorjsuren Altanchimeg , Enkhnasan Davaadorj , Ariunaa Mungunkhuyag
Published: December 2021

Detection of forest pest outbreaks can help in controlling outbreaks and provide accurate information for forest management decision-making. Although some needle injuries occur at the beginning of the attack, the appearance of the trees does not change significantly from the condition before the attack. These subtle changes cannot be observed with the naked eye, but usually manifest as small changes in leaf reflectance. Therefore, hyperspectral remote sensing can be used to detect the different stages of pest infection as it offers high-resolution reflectance. Accordingly, this study investigated the response of a larch forest to Jas’s Larch Inchworm (Erannis jacobsoni Djak) and performed the different infection stages detection and identification using ground hyperspectral data and data on the forest biochemical components (chlorophyll content, fresh weight moisture content and dry weight moisture content). A total of 80 sample trees were selected from the test area, covering the following three stages: before attack, early-stage infection and middle- to late-stage infection. Combined with the Findpeaks-SPA function, the response relationship between biochemical components and spectral continuous wavelet coefficients was analyzed. The support vector machine classification algorithm was used for detection infection. The results showed that there was no significant difference in the biochemical composition between healthy and early-stage samples, but the spectral continuous wavelet coefficients could reflect these subtle changes with varying degrees of sensitivity. The continuous wavelet coefficients corresponding to these stresses may have high potential for infection detection. Meanwhile, the highest overall accuracy of the model based on chlorophyll content, fresh weight moisture content and dry weight moisture content were 90.48%, 85.71% and 90.48% respectively, and the Kappa coefficients were 0.85, 0.79 and 0.86 respectively.
Evaluation of the Integrity Risk for Precise Point Positioning
Authors: Xue Bing , Yuan Yunbin , Wang Han , Wang Haitao
Published: December 2021

Global Navigation Satellite System (GNSS) Precise Point Positioning (PPP) is an attractive positioning technology due to its high precision and flexibility. However, the vulnerability of PPP brings a safety risk to its application in the field of life safety, which must be evaluated quantitatively to provide integrity for PPP users. Generally, PPP solutions are processed recursively based on the extended Kalman filter (EKF) estimator, utilizing both the previous and current measurements. Therefore, the integrity risk should be qualified considering the effects of all the potential observation faults in history. However, this will cause the calculation load to explode over time, which is impractical for long-time missions. This study used the innovations in a time window to detect the faults in the measurements, quantifying the integrity risk by traversing the fault modes in the window to maintain a stable computation cost. A non-zero bias was conservatively introduced to encapsulate the effect of the faults before the window. Coping with the multiple simultaneous faults, the worst-case integrity risk was calculated to overbound the real risk in the multiple fault modes. In order to verify the proposed method, simulation and experimental tests were carried out in this study. The results showed that the fixed and hold mode adopted for ambiguity resolution is critical to an integrity risk evaluation, which can improve the observation redundancy and remove the influence of the biased predicted ambiguities on the integrity risk. Increasing the length of the window can weaken the impact of the conservative assumption on the integrity risk due to the smoothing effect of the EKF estimator. In addition, improving the accuracy of observations can also reduce the integrity risk, which indicates that establishing a refined PPP random model can improve the integrity performance.
Estimation of Cotton Leaf Area Index (LAI) Based on Spectral Transformation and Vegetation Index
Authors: Ma Yiru , Zhang Qiang , Yi Xiang , Ma Lulu , Zhang Lifu , Huang Changping , Zhang Ze , Lv Xin
Published: December 2021

Unmanned aerial vehicles (UAV) has been increasingly applied to crop growth monitoring due to their advantages, such as their rapid and repetitive capture ability, high resolution, and low cost. LAI is an important parameter for evaluating crop canopy structure and growth without damage. Accurate monitoring of cotton LAI has guiding significance for nutritional diagnosis and the accurate fertilization of cotton. This study aimed to obtain hyperspectral images of the cotton canopy using a UAV carrying a hyperspectral sensor and to extract effective information to achieve cotton LAI monitoring. In this study, cotton field experiments with different nitrogen application levels and canopy spectral images of cotton at different growth stages were obtained using a UAV carrying hyperspectral sensors. Hyperspectral reflectance can directly reflect the characteristics of vegetation, and vegetation indices (VIs) can quantitatively describe the growth status of plants through the difference between vegetation in different band ranges and soil backgrounds. In this study, canopy spectral reflectance was extracted in order to reduce noise interference, separate overlapping samples, and highlight spectral features to perform spectral transformation; characteristic band screening was carried out; and VIs were constructed using a correlation coefficient matrix. Combined with canopy spectral reflectance and VIs, multiple stepwise regression (MSR) and extreme learning machine (ELM) were used to construct an LAI monitoring model of cotton during the whole growth period. The results show that, after spectral noise reduction, the bands screened by the successive projections algorithm (SPA) are too concentrated, while the sensitive bands screened by the shuffled frog leaping algorithm (SFLA) are evenly distributed. Secondly, the calculation of VIs after spectral noise reduction can improve the correlation between vegetation indices and LAI. The DVI (540,525) correlation was the largest after standard normal variable transformation (SNV) pretreatment, with a correlation coefficient of −0.7591. Thirdly, cotton LAI monitoring can be realized only based on spectral reflectance or VIs, and the ELM model constructed by calculating vegetation indices after SNV transformation had the best effect, with verification set R2 = 0.7408, RMSE = 1.5231, and rRMSE = 24.33%, Lastly, the ELM model based on SNV-SFLA-SNV-VIs had the best performance, with validation set R2 = 0.9066, RMSE = 0.9590, and rRMSE = 15.72%. The study results show that the UAV equipped with a hyperspectral sensor has broad prospects in the detection of crop growth index, and it can provide a theoretical basis for precise cotton field management and variable fertilization.
Evolutions of 30-Year Spatio-Temporal Distribution and Influencing Factors of Suaeda salsa in Bohai Bay, China
Authors: Yin Hongyan , Hu Yuanman , Liu Miao , Li Chunlin , Chang Yu
Published: December 2021

Suaeda salsa (L.) Pall. (S. salsa) acts as a pioneer species in coastal wetlands due to its high salt tolerance. It has significant biodiversity maintenance, socioeconomic values (e.g., tourism) due to its vibrant color, and carbon sequestration (blue carbon). Bohai Bay region, the mainly distributed area of S. salsa, is an economic intensive region with the largest economic aggregate and population in northern China. The coastal wetland is one of the most vulnerable ecosystems with the urbanization and economic developments. S. salsa in Bohai Bay has been changed significantly due to several threats to its habitat in past decades. In this paper, we analyzed all available archived Landsat TM/ETM+/OLI images of the Bohai Bay region by using a decision tree algorithm method based on the Google Earth Engine (GEE) platform to generate annual maps of S. salsa from 1990 to 2020 at a 30-m spatial resolution. The temporal-spatial dynamic changes in S. salsa were studied by landscape metric analysis. The influencing factors of S. salsa changes were analyzed based on principal component analysis (PCA) and a logistic regression model (LRM). The results showed that S. salsa was mainly distributed in three regions: the Liao River Delta (Liaoning Province), Yellow River Delta (Shandong Province), and Hai River Estuary (Hebei Province, Tianjin). During the past 31 years, the total area of S. salsa has dramatically decreased from 692.93 km2 to 51.04 km2, which means that 92.63% of the area of S. salsa in the Bohai Bay region was lost. In the 641.89 km2 area of S. salsa that was lost, 348.80 km2 of this area was converted to other anthropic land use categories, while 293.09 km2 was degraded to bare land. The landscape fragmentation of S. salsa has gradually intensified since 1990. National Nature Reserves have played an important role in the restoration of suitable S. salsa habitats. The analysis results for the natural influencing factors indicated that precipitation, temperature, elevation, and distance to the coastline were considered to be the major influencing factors for S. salsa changes. The results are valuable for monitoring the dynamic changes of S. salsa and can be used as effective factors for the restoration of S. salsa in coastal wetlands.
Fault Diagnosis of Rotating Machinery Based on Improved Self-Supervised Learning Method and Very Few Labeled Samples
Authors: Wei Meirong , Liu Yan , Zhang Tao , Wang Ze , Zhu Jiaming
Published: December 2021

Convolution neural network (CNN)-based fault diagnosis methods have been widely adopted to obtain representative features and used to classify fault modes due to their prominent feature extraction capability. However, a large number of labeled samples are required to support the algorithm of CNNs, and, in the case of a limited amount of labeled samples, this may lead to overfitting. In this article, a novel ResNet-based method is developed to achieve fault diagnoses for machines with very few samples. To be specific, data transformation combinations (DTCs) are designed based on mutual information. It is worth noting that the selected DTC, which can complete the training process of the 1-D ResNet quickly without increasing the amount of training data, can be randomly used for any batch training data. Meanwhile, a self-supervised learning method called 1-D SimCLR is adopted to obtain an effective feature encoder, which can be optimized with very few unlabeled samples. Then, a fault diagnosis model named DTC-SimCLR is constructed by combining the selected data transformation combination, the obtained feature encoder and a fully-connected layer-based classifier. In DTC-SimCLR, the parameters of the feature encoder are fixed, and the classifier is trained with very few labeled samples. Two machine fault datasets from a cutting tooth and a bearing are conducted to evaluate the performance of DTC-SimCLR. Testing results show that DTC-SimCLR has superior performance and diagnostic accuracy with very few samples.
Numerical Forecast Correction of Temperature and Wind Using a Single-Station Single-Time Spatial LightGBM Method
Authors: Tang Rongnian , Ning Yuke , Li Chuang , Feng Wen , Chen Youlong , Xie Xiaofeng
Published: December 2021

Achieving high-performance numerical weather prediction (NWP) is important for people’s livelihoods and for socioeconomic development. However, NWP is obtained by solving differential equations with globally observed data without capturing enough local and spatial information at the observed station. To improve the forecasting performance, we propose a novel spatial lightGBM (Light Gradient Boosting Machine) model to correct the numerical forecast results at each observation station. By capturing the local spatial information of stations and using a single-station single-time strategy, the proposed method can incorporate the observed data and model data to achieve high-performance correction of medium-range predictions. Experimental results for temperature and wind prediction in Hainan Province show that the proposed correction method performs well compared with the ECWMF model and outperforms other competing methods.
Recent Advances in Evolving Computing Paradigms: Cloud, Edge, and Fog Technologies
Authors: Angel Nancy A , Ravindran Dakshanamoorthy , Vincent P M Durai Raj , Srinivasan Kathiravan , Hu Yuh-Chung
Published: December 2021

Cloud computing has become integral lately due to the ever-expanding Internet-of-things (IoT) network. It still is and continues to be the best practice for implementing complex computational applications, emphasizing the massive processing of data. However, the cloud falls short due to the critical constraints of novel IoT applications generating vast data, which entails a swift response time with improved privacy. The newest drift is moving computational and storage resources to the edge of the network, involving a decentralized distributed architecture. The data processing and analytics perform at proximity to end-users, and overcome the bottleneck of cloud computing. The trend of deploying machine learning (ML) at the network edge to enhance computing applications and services has gained momentum lately, specifically to reduce latency and energy consumed while optimizing the security and management of resources. There is a need for rigorous research efforts oriented towards developing and implementing machine learning algorithms that deliver the best results in terms of speed, accuracy, storage, and security, with low power consumption. This extensive survey presented on the prominent computing paradigms in practice highlights the latest innovations resulting from the fusion between ML and the evolving computing paradigms and discusses the underlying open research challenges and future prospects.