bluuebunny/crossref_metadata_2025 huggingface dataset:
Engineering Synthetic Lipopeptide Antigen for Specific Detection of Mycobacterium avium subsp. paratuberculosis Infection
Authors: Bay Sylvie , Begg Douglas , Ganneau Christelle , Branger Maxime , Cochard Thierry , Bannantine John P. , Köhler Heike , Moyen Jean-Louis , Whittington Richard J. , Biet Franck
Published: April 2021

Unlike other MAC members, Mycobacterium avium subsp. paratuberculosis (MAP) does not produce glycopeptidolipids (GPL) on the surface of the cell wall but a lipopentapeptide called L5P (also termed Lipopeptide-I or Para-LP-01) characterized in C-type (bovine) strains. This lipopeptide antigen contains a pentapeptide core, D-Phenylalanine-N-methyl-L-Valine-L-Isoleucine-L-Phenylalanine-L-Alanine, in which the N-terminal D-Phenylalanine is amido-linked with a fatty acid (C18–C20). The molecular and genetic characterization of this antigen demonstrated that L5P is unique to MAP. Knowledge of the structure of L5P enabled synthetic production of this lipopeptide in large quantities for immunological evaluation. Various studies described the immune response directed against L5P and confirmed its capability for detection of MAP infection. However, the hydrophobic nature of lipopeptide antigens make their handling and use in organic solvents unsuitable for industrial processes. The objectives of this study were to produce, by chemical synthesis, a water-soluble variant of L5P and to evaluate these compounds for the serological diagnosis of MAP using well-defined serum banks. The native L5P antigen and its hydrosoluble analog were synthesized on solid phase. The pure compounds were evaluated on collections of extensively characterized sera from infected and non-infected cattle. ROC analysis showed that L5P and also its water-soluble derivative are suitable for the development of a serological test for Johne's disease at a population level. However, these compounds used alone in ELISA have lower sensitivity (Se 82% for L5P and Se 62% for the water-soluble variant of L5P) compared to the Se 98% of a commercial test. Advantageously, these pure synthetic MAP specific antigens can be easily produced in non-limiting quantities at low cost and in standardized batches for robust studies. The fact that L5P has not been validated in the context of ovine paratuberculosis highlights the need to better characterize the antigens expressed from the different genetic lineages of MAP to discover new diagnostic antigens. In the context of infections due to other mycobacteria such as M. bovis or the more closely related species M. avium subsp. hominissuis, the L5P did not cross react and therefore may be a valuable antigen to solve ambiguous results in other tests.
Text Indexing for Regular Expression Matching
Authors: Gibney Daniel , Thankachan Sharma V.
Published: April 2021

Finding substrings of a text T that match a regular expression p is a fundamental problem. Despite being the subject of extensive research, no solution with a time complexity significantly better than O(|T||p|) has been found. Backurs and Indyk in FOCS 2016 established conditional lower bounds for the algorithmic problem based on the Strong Exponential Time Hypothesis that helps explain this difficulty. A natural question is whether we can improve the time complexity for matching the regular expression by preprocessing the text T? We show that conditioned on the Online Matrix–Vector Multiplication (OMv) conjecture, even with arbitrary polynomial preprocessing time, a regular expression query on a text cannot be answered in strongly sublinear time, i.e., O(|T|1−ε) for any ε>0. Furthermore, if we extend the OMv conjecture to a plausible conjecture regarding Boolean matrix multiplication with polynomial preprocessing time, which we call Online Matrix–Matrix Multiplication (OMM), we can strengthen this hardness result to there being no solution with a query time that is O(|T|3/2−ε). These results hold for alphabet sizes three or greater. We then provide data structures that answer queries in O(|T||p|τ) time where τ∈[1,|T|] is fixed at construction. These include a solution that works for all regular expressions with Expτ·|T| preprocessing time and space. For patterns containing only ‘concatenation’ and ‘or’ operators (the same type used in the hardness result), we provide (1) a deterministic solution which requires Expτ·|T|log2|T| preprocessing time and space, and (2) when |p|≤|T|z for z=2o(log|T|), a randomized solution with amortized query time which answers queries correctly with high probability, requiring Expτ·|T|2Ωlog|T| preprocessing time and space.
Tightly Coupled Integrated Navigation Algorithm for Hypersonic Boost-Glide Vehicles in the LCEF Frame
Authors: Chen Kai , Pei Sensen , Shen Fuqiang , Liu Shangbo
Published: April 2021

According to the trajectory characteristics of hypersonic boost-glide vehicles, a tightly coupled integrated navigation algorithm for hypersonic vehicles based on the launch-centered Earth-fixed (LCEF) frame is proposed. First, the strapdown inertial navigation mechanization algorithm and discrete update algorithm in the LCEF frame are introduced. Subsequently, the attitude, velocity, and position error equations of strapdown inertial navigation in the LCEF frame are introduced. The strapdown inertial navigation system/global positioning system (SINS/GPS) pseudo-range and pseudo-range rate measurement equations in the LCEF frame are derived. Further, the tightly coupled SINS/GPS integrated navigation filter state equation and the measurement equation are presented. Finally, the tightly coupled SINS/GPS integrated navigation algorithm is verified in the hardware-in-the-loop (HWIL) simulation environment. The simulation results indicate that the precision of tightly coupled integrated navigation is better than that of loosely coupled integrated navigation. Moreover, even when the number of effective satellites is less than four, tightly coupled integrated navigation functions well, thus verifying the effectiveness and feasibility of the algorithm.
Extraction of Cannabinoids from Cannabis sativa L. (Hemp)—Review
Authors: Valizadehderakhshan Mehrab , Shahbazi Abolghasem , Kazem-Rostami Masoud , Todd Matthew Scott , Bhowmik Arnab , Wang Lijun
Published: April 2021

Cannabis plant has long been execrated by law in different nations due to the psychoactive properties of only a few cannabinoids. Recent scientific advances coupled with growing public awareness of cannabinoids as a medical commodity drove legislation change and brought about a historic transition where the demand rose over ten-fold in less than five years. On the other hand, the technology required for cannabis processing and the extraction of the most valuable chemical compounds from the cannabis flower remains the bottleneck of processing technology. This paper sheds light on the downstream processing steps and principles involved in producing cannabinoids from Cannabis sativa L. (Hemp) biomass. By categorizing the extraction technology into seed and trichome, we examined and critiqued different pretreatment methods and technological options available for large-scale extraction in both categories. Solvent extraction methods being the main focus, the critical decision-making parameters in each stage, and the applicable current technologies in the field, were discussed. We further examined the factors affecting the cannabinoid transformation that changes the medical functionality of the final cannabinoid products. Based on the current trends, the extraction technologies are continuously being revised and enhanced, yet they still fail to keep up with market demands.
Genes with Cold Shock Domain from Eutrema salsugineum (Pall.) for Generating a Cold Stress Tolerance in Winter Rape (Brassica napus L.) Plants
Authors: Khvatkov Pavel , Taranov Vasiliy , Pushin Alexander , Maletich Galina , Fedorov Vladislav , Chaban Inna , Babakov Alexsey , Dolgov Sergey , Chernobrovkina Mariya
Published: April 2021

The increased demand in vegetable oil for food purposes and high-protein feed for livestock and poultry encourages producers to expand the production of various oil crops, while occupying rather cold agroclimatic zones. Improved cold and frost resistance of cultivated crops would significantly increase the yield and expand the range of rape cultivation in a number of cold climate regions. Nine transgenic lines of winter rape containing genes encoding proteins with a cold shock domain (CspA и EsCSDP3) were obtained as a result of Agrobacterium transformation. In total, 260 explants were involved in transformation of rape using pBI121-CSPA-plant, with a transformation efficiency of 2.3%; among 750 explants using the pBI-EsCSDP3 construction, the efficiency was 0.4%. As a result of the studies, it was shown that the expression of the new gene Escsdp3 from the plant of Eutrema salsugineum was able to increase the cold and frost resistance of plants as effectively as the cspa gene from E. coli, which is classically used for this purpose. The cold resistance analysis of T1 transgenic plants generation revealed four cold resistant winter rape lines (three lines with the cspA-plant gene and one line with the Escsdp3 gene). The transfer of Escsdp3 and cspA-plant genes into winter rape plants led to a significant increase in frost resistance of plants. Two winter rapeseed lines were resistant to freezing (with the cspA-plant gene and with the Escsdp3 gene). Non-hardened transgenic plants remained viable after 24 h of exposure to negative temperatures up to −5 °C, and plants that passed through the hardening stage survived after freezing at −16 °C.
Microbial Ecotoxicity of Biochars in Agricultural Soil and Interactions with Linear Alkylbenzene Sulfonates
Authors: Nissen Rasmus , Khanal Gunadhish , Elsgaard Lars
Published: April 2021

Large-scale application of biochar on agricultural land offers the prospect of soil improvement and carbon sequestration for climate-change mitigation. However, negative side-effects on the soil microbial ecosystem are poorly understood, notably in relation to the functions of native microbiomes under realistic routes of biochar exposure. Due to divergent properties, different biochars might interact with soil in complex ways. This might result in decreased or increased ecotoxicity from biochar contaminants, such as heavy metals and polycyclic aromatic hydrocarbons (PAHs). Using five biochars produced from straw and wood under contrasting pyrolysis conditions, we traced their ecotoxicological dose-effect using a bioassay for potential ammonia oxidation (PAO), through microorganisms that are sensitive stress indicators. Assays were made after soil/biochar interaction for up to 3 weeks, where straw biochar with the lowest PAH content (<0.5 mg kg−1) showed the most pronounced dose-effects to PAO, corresponding to a 10% effect concentration (EC10) of 4.6% (dry weight biochar/dry weight soil). In comparison, straw biochar with the highest PAH content was least ecotoxic (EC10, 15.2% after 3 weeks) and wood biochars pyrolysed at high temperature (700–725 °C) showed no ecotoxicity to PAO. Interactions between biochars and anionic surfactants, i.e., linear alkylbenzene sulfonates, which are common soil pollutants, resulted in varying effects on PAO, but the effects were small and of limited ecological importance for soil-amended biochars. In conclusion, the results showed that short-term microbial side-effects of biochar in the soil ecosystem were minor at relevant field application rates (such as <30 Mg ha−1 mixed into a plough layer of 20 cm), and that inherent PAHs in biochar were not a likely source of short-term ecotoxicity. However, there were notable differences in the effects eventually observed at very high biochar rates, stressing that individual biochars need specific ecotoxicological assessment before their safe application at large scale in agricultural soils.
Exploratory Assessment to Evaluate Seed Sprouting under Elevated CO2 Revealed Improved Biomass, Physiology, and Nutritional Value of Trachyspermum ammi
Authors: Hassan Abdelrahim H. A. , Okla Mohammad K. , Al-amri Saud A. , El-Tayeb Mohamed A. , Moussa Ihab M. , B. Elbadawi Yahaya , Adel-Maksoud Mostafa A. , Ali Fatma H. M. , S. Almaary Khalid , Selim Samy , AbdElgawad Hamada
Published: April 2021

Elevated atmospheric CO2 (eCO2) can significantly enhance plant metabolism and improve their nutritional quality. Although several studies addressed the effect of eCO2 on plants, to our knowledge, there are no studies that have applied eCO2 to improve growth, chemical composition, and biological properties of ajwain (Trachyspermum ammi) during sprouting. Herein, eCO2 (620 µmol mol−1) was employed to enhance photosynthetic reactions. Improved photosynthesis induced primary and bioactive secondary metabolism, which led to improved biological activities of T. ammi sprouts in comparison with control sprouts and seeds. eCO2-treated sprouts showed significantly (p < 0.05) higher levels of most measured nutritional primary and secondary metabolites like soluble sugars, essential amino acids, organic acids, essential oils, phenolics, and flavonoids than control sprouts, which had significantly higher values than control seeds. eCO2 significantly improved the antimicrobial properties of T. ammi sprouts against 11 out of 13 microbial species than control sprouts, which had more potent antimicrobial activities than seeds. The significant increase in the antioxidant potential of treated sprouts was indicated by improved levels of ferric reducing antioxidant power (FRAP), DPPH, and oxygen radical absorbance capacity (ORAC). In addition, the anticancer activity against four different human tumor cell lines was significantly (p < 0.05) boosted by both sprouting and eCO2 exposure. Thus, the present study confirms the synergistic effect of sprouting with eCO2 exposure as promising approaches to produce ajwain sprouts with rich nutraceuticals, effective phytochemicals, and enhanced biological activities.
Genome Enhanced Marker Improvement for Potato Virus Y Disease Resistance in Potato
Authors: Caruana Brittney M. , Rodoni Brendan C. , Constable Fiona , Slater Anthony T. , Cogan Noel O. I.
Published: April 2021

Potato is an important food crop worldwide and is grown in a large number of countries. As such, the crop is under disease pressures and the need for selecting disease resistance genes during breeding programs is essential. Of particular importance within Australia and other parts of the world is the potyvirus, Potato virus Y (PVY). In this paper, three commonly used PVY resistance markers, M45, RYSC3 and M6, were evaluated using existing genomic resources and phenotypic data from the Australian potato breeding program to identify a region where the PVY resistance gene, Ryadg may reside. A region of Chromosome XI was investigated, and a cluster of disease resistance genes was identified that the resistance gene Ryadg is suspected to reside within. Protein characterization was also performed on the putative resistant gene. A specific variant that had complete association with the resistance gene was identified and a single nucleotide polymorphism (SNP) assay was designed to avoid dissociation of marker and gene in future breeding programs. This SNP marker (SNP37279) was validated as a Kompetitive Allele-specific PCR (KASP) genotyping assay and was found to perform more accurately than all previously used markers for detecting Ryadg.
Response of UK Horse, Pony and Donkey Owners to the Early Stages of the COVID-19 Pandemic
Authors: Hockenhull Jo , Bell Catherine , White Jo , Rogers Suzanne
Published: April 2021

In the UK, March 2020 was a time of great uncertainty as COVID-19 became increasingly widespread. The government responded by making suggestions about how people could reduce the risk of spread on 16 March, moved swiftly into closing schools on the 18 March before announcing a mandatory lockdown on the 23rd March. This was a challenging time for UK equestrians who had to balance maintaining their equine’s routine and daily care alongside the increasing biosecurity measures. A cross-sectional survey was distributed to UK equestrians via social media over two days (28 and 29 March 2020) to better understand the decisions made by UK horse, pony and donkey owners during this time. Data from 452 respondents were generated across all four countries comprising the UK, although there were no significant differences in owner response to the pandemic between locations. The changes respondents made differed between the 16th and the 18th of March 2020, with an early emphasis on improving yard biosecurity and opting to stop riding, as well as reducing the time spent at the yard. After the 18 March, respondents placed more emphasis on risk reduction by changing the activities they did with their horse, including riding, with common examples including avoiding “high risk” activities such as riding on busy roads, jumping, riding young or nervous horses. Few respondents reported having an emergency plan in place should they become ill or otherwise unable to care for their equine. The findings highlight areas that would significantly benefit from in-depth investigation in future research. Equestrian behaviour and mindset around risk-taking and risk perception have already been researched in relation to equestrian activities and sport but have received little attention in the context of wider health challenges. Understanding the uptake of emergency planning and preparation in the UK equestrian community also warrants consideration. Using this information effectively to promote forward planning is likely to be of great benefit in equestrian responses to future health or climate-related crises.
Economic Feasibility of Mixed-Species Grazing to Improve Rangeland Productivity
Authors: Hintze Kayla , Bir Courtney , Peel Derrell
Published: April 2021

Pasture and grazing land in the southern and central Great Plains is being invaded by woody species, especially eastern redcedar. As a result of woody plant encroachment, cattle production on native rangeland is becoming less profitable because stocking rates must be decreased. Eastern redcedar encroachment can be controlled by grazing management, herbicide use, prescribed fire, mechanical control and mixed species grazing. This study utilizes traditional management practices, prescribed fire and three types of mixed species grazing operations to determine the most economically feasible way to manage redcedar encroachment on rangeland. The cost-benefit analysis in this study found that the source of redcedar management on rangeland with the highest net present value was the use of a breeding goat operation in which goats were grazed alongside cattle with the use of prescribed fire. This suggests that producers who are fighting redcedar encroachment will likely be able to implement a mixed species grazing operation with breeding goats to better manage their land and increase returns.
The Link between Occurrence of Class I Integron and Acquired Aminoglycoside Resistance in Clinical MRSA Isolates
Authors: El-Baz Ahmed M. , Yahya Galal , Mansour Basem , El-Sokkary Mohamed M. A. , Alshaman Reem , Alattar Abdullah , El-Ganiny Amira M.
Published: April 2021

Methicillin-resistant Staphylococcus aureus (MRSA) is a major cause of nosocomial infections because of its high resistance. Here, we study the antibiotic resistance in MRSA clinical isolates and their relation to integron I occurrence. A total of 88 clinical Staphylococcusaureus isolates were collected. MRSA were identified by the disk diffusion method (DDM) and confirmed by PCR, and antibiogram was determined by DDM. Integron I, II and the aacA4 gene were investigated by PCR. Integrase-positive strains were analyzed for the presence of resistance gene cassettes by sequencing. All isolates were identified as MRSA by DDM and confirmed by PCR. All isolates were resistant to ampicillin and cefoxitin. Concerning aminoglycosides, the frequency of resistance was reported for streptomycin (60.7%), tobramycin (37.1%) gentamicin (36%), and for amikacin (15.9%). Integron I was detected in 41 isolates (46.6%), while integron II was detected in three isolates (3.4%). Sequencing of the integron I-cassette indicated the exclusive prevalence of addA gene variants mediating aminoglycoside resistance. The aacA4 gene was found in DNA of 31 isolates (35.22%). This study revealed the high existence of MRSA. Furthermore, the AacA4 gene and class I integron harboring aadA gene were predominant in MRSA isolates.
Calcium Dobesilate Reverses Cognitive Deficits and Anxiety-Like Behaviors in the D-Galactose-Induced Aging Mouse Model through Modulation of Oxidative Stress
Authors: Hakimizadeh Elham , Zamanian Mohammad , Giménez-Llort Lydia , Sciorati Clara , Nikbakhtzadeh Marjan , Kujawska Małgorzata , Kaeidi Ayat , Hassanshahi Jalal , Fatemi Iman
Published: April 2021

The long-term treatment of mice with D-galactose (D-gal) induces the overproduction of reactive oxygen species (ROS) and is a well-accepted experimental model of oxidative stress-linked cognitive disorders in physiological aging. Calcium dobesilate (CaD, Doxium®) is an established vasoactive and angioprotective drug commonly used for the clinical treatment of diabetic retinopathy and chronic venous insufficiency. It has antioxidant properties and controls vascular permeability. In the current study, we evaluated the protective effects of CaD (50 and 100 mg/kg/day p.o.) in male mice treated with D-gal (500 mg/kg/day p.o.) for six weeks. Results demonstrated that body weight loss, anxiety-like and cognitive impairments of D-gal-treated animals were reversed by CaD administration as evaluated by the measurement of mice performance in elevated plus-maze, Y-maze, and shuttle box tests. CaD treatment also inhibited the oxidative stress in aging mouse brains by decreasing malondialdehyde (MDA) levels and increasing superoxide dismutase (SOD), glutathione peroxidase (GPx), and catalase (CAT) enzyme activities. These results could open new perspectives for the clinical use of CaD in treating and preventing cognitive impairment in older people.
Assessment of Bioactive Compounds under Simulated Gastrointestinal Digestion of Bee Pollen and Bee Bread: Bioaccessibility and Antioxidant Activity
Authors: Aylanc Volkan , Tomás Andreia , Russo-Almeida Paulo , Falcão Soraia I. , Vilas-Boas Miguel
Published: April 2021

Bee pollen and bee bread have always been regarded as excellent natural resources for application in food and pharmaceutical fields due to their rich nutrient content and diversity of bioactive compounds with health-improving properties. Extensive studies on both bee products as ingredients for a healthy diet were reported, although the data concerning their metabolization on the gastrointestinal tract is quite limited. Here, we report, at each digestive stage, the bioactive profile for both bee products, their bioaccessibility levels and the antioxidant activity evaluation. The findings indicated that the average bioaccessibility level of total phenolic and total flavonoid content for bee pollen was 31% and 25%, respectively, while it was 38% and 35% for bee bread. This was reflected in a decrease of their antioxidant capacity at the end of in vitro gastrointestinal digestion, both in free radicals scavenging capacity and in reducing power. Moreover, within the 35 phytochemicals identified, the most affected by gastrointestinal digestion were phenylamides, with a complete digestibility at the end of the intestinal phase. Overall, our results highlight that bioactive compounds in both raw products do not reflect the real amount absorbed in the intestine, being bee bread more accessible in bioactive content than bee pollen.
Effects of Supplementing Rumen-Protected Methionine and Lysine on Milk Performance and Oxidative Status of Dairy Ewes
Authors: Mavrommatis Alexandros , Mitsiopoulou Christina , Christodoulou Christos , Kariampa Paraskevi , Simoni Marica , Righi Federico , Tsiplakou Eleni
Published: April 2021

There is limited information on the impact of dietary supplementation with separate rumen-protected (RP) amino acids (AA), or with their combination, on ewes’ oxidative status. Sixty ewes were divided into five groups; C: basal diet (control); M: basal diet + 6 g/ewe RP methionine; L: basal diet + 5 g/ewe RP lysine; LML: basal diet + 6 g methionine and 5 g lysine/ewe; and HML: basal diet + 12 g methionine + 5 g lysine/ewe. Milk’s fat content increased in RP-AA fed ewes, while that of protein in M and L only. In blood plasma, the malondialdehyde (MDA) content was reduced in the M, LML, and HML compared to C-fed ewes. An increase in glutathione transferase activity in the blood plasma of the M and LML compared to the C and HML-fed ewes were found. In milk, lower values of the ferric reducing ability of plasma (FRAP) in the LML and HML-fed ewes and of 2,2′-Azino-bis 3-ethylbenzthiazoline-6-sulfonic acid (ABTS) in LML only, were found. Lysine increased milk’s FRAP values and MDA content. Both L and HML diets increased milk’s protein carbonyls content. Methionine improves the organism’s oxidative status, without adversely affecting milk’s oxidative stability. Lysine dietary inclusion affects negatively the oxidative stability of milk.
Effect of Sawdust Particle Size on Physical, Mechanical, and Energetic Properties of Pinus durangensis Briquettes
Authors: Zepeda-Cepeda Christian Osvaldo , Goche-Télles José Rodolfo , Palacios-Mendoza Celina , Moreno-Anguiano Oswaldo , Núñez-Retana Víctor Daniel , Heya Maginot Ngangyo , Carrillo-Parra Artemio
Published: April 2021

Particle size is a physical property that sometimes limits the quality of briquettes, so it is recommended to use different sizes in mixtures for their manufacture. The objective of this research was to evaluate the effect of different particle sizes of sawdust in mixtures on some physical, mechanical, and energetic properties of briquettes made from Pinus durangensis sawdust, as well as set the ranges within the appropriate values found to obtain desired values. Three particle sizes were established (large, medium, and small), and 10 mixtures were prepared using different percentages of each particle classification. The particle density, volumetric swelling, compressive strength, impact resistance index (IRI), and gross calorific value of the briquettes were evaluated. For the determination of optimal mixtures, the surface response methodology was used under a three-factor simplex-lattice model. The particle density values were in the range 0.92 to 1.02 g cm−3 and the volumetric swelling was 0.96 to 3.9%. The highest resistance to compression was 37.01 N mm−1, and the IRI was found in the range of 53 to 107%. The gross calorific values were from 19.35 to 21.63 MJ kg−1. The selection of different particle sizes for the mixtures increases the quality of the briquettes.
Gallic Acid Induces S and G2 Phase Arrest and Apoptosis in Human Ovarian Cancer Cells In Vitro
Authors: He Zhiping , Liu Xingquan , Wu Fenghua , Wu Shaozhen , Rankin Gary O’Neal , Martinez Ivan , Rojanasakul Yon , Chen Yi Charlie
Published: April 2021

Ovarian cancer (OC) is among the top gynecologic cancers in the US with a death tally of 13,940 in the past year alone. Gallic acid (GA) is a natural compound with pharmacological benefits. In this research, the role of GA on cell proliferation, cell apoptosis, cell cycle-related protein expression was explored in OC cell lines OVCAR-3 and A2780/CP70. After 24, 48 and 72 h of GA treatment, the IC50 values in OVCAR-3 cells were 22.14 ± 0.45, 20.36 ± 0.18, 15.13 ± 0.53 μM, respectively and in A2780/CP70 cells IC50 values were 33.53 ± 2.64, 27.18 ± 0.22, 22.81 ± 0.56, respectively. Hoechst 33,342 DNA staining and flow cytometry results showed 20 μM GA exposure could significantly accelerate apoptosis in both OC cell lines and the total apoptotic rate increased from 5.34%(control) to 21.42% in OVCAR-3 cells and from 8.01%(control) to 17.69% in A2780/CP70 cells. Western blot analysis revealed that GA stimulated programmed OC cell death via a p53-dependent intrinsic signaling. In addition, GA arrested cell cycle at the S or G2 phase via p53-p21-Cdc2-cyclin B pathway in the same cells. In conclusion, we provide some evidence of the efficacy of GA in ovarian cancer prevention and therapy.
Experimental Performance Evaluation of Enhanced User Interaction Components for Web-Based Collaborative Extended Reality
Authors: Korečko Štefan , Hudák Marián , Sobota Branislav , Sivý Martin , Pleva Matúš , Steingartner William
Published: April 2021

COVID-19-related quarantine measures resulted in a significant increase of interest in online collaboration tools. This includes virtual reality (VR) or, in more general term, extended reality (XR) solutions. Shared XR allows for activities such as presentations, training of personnel or therapy to take place in a virtual space instead of a real one. To make online XR as accessible as possible, a significant effort has been put into the development of solutions that can run directly in web browsers. One of the most recognized solutions is the A-Frame software framework, created by Mozilla VR team and supporting most of the contemporary XR hardware. In addition, an extension called Networked-Aframe allows multiple users to share virtual environments, created using A-Frame, in real time. In this article, we introduce and experimentally evaluate three components that extend the functionality of A-Frame and Networked-Aframe. The first one extends Networked-Aframe with the ability to monitor and control users in a shared virtual scene. The second one implements six degrees of freedom motion tracking for smartphone-based VR headsets. The third one brings hand gesture support to the Microsoft HoloLens holographic computer. The evaluation was performed in a dedicated local network environment with 5, 10, 15 and 20 client computers. Each computer represented one user in a shared virtual scene. Since the experiments were carried out with and without the introduced components, the results presented here can also be regarded as a performance evaluation of A-Frame and Networked-Aframe themselves.
Optimal Dispatch Strategy of Virtual Power Plant for Day-Ahead Market Framework
Authors: Pal Poushali , Krishnamoorthy Parvathy Ayalur , Rukmani Devabalaji Kaliaperumal , Antony S. Joseph , Ocheme Simon , Subramanian Umashankar , Elavarasan Rajvikram Madurai , Das Narottam , Hasanien Hany M.
Published: April 2021

Renewable energy sources prevail as a clean energy source and their penetration in the power sector is increasing day by day due to the growing concern for climate action. However, the intermittent nature of the renewable energy based-power generation questions the grid security, especially when the utilized source is solar radiation or wind flow. The intermittency of the renewable generation can be met by the integration of distributed energy resources. The virtual power plant (VPP) is a new concept which aggregates the capacities of various distributed energy resources, handles controllable and uncontrollable loads, integrates storage devices and empowers participation as an individual power plant in the electricity market. The VPP as an energy management system (EMS) should optimally dispatch the power to its consumers. This research work is proposed to analyze the optimal scheduling of generation in VPP for the day-ahead market framework using the beetle antenna search (BAS) algorithm under various scenarios. A case study is considered for this analysis in which the constituting energy resources include a photovoltaic solar panel (PV), micro-turbine (MT), wind turbine (WT), fuel cell (FC), battery energy storage system (BESS) and controllable loads. The real-time hourly load curves are considered in this work. Three different scenarios are considered for the optimal dispatch of generation in the VPP to analyze the performance of the proposed technique. The uncertainties of the solar irradiation and the wind speed are modeled using the beta distribution method and Weibull distribution method, respectively. The performance of the proposed method is compared with other evolutionary algorithms such as particle swarm optimization (PSO) and the genetic algorithm (GA). Among these above-mentioned algorithms, the proposed BAS algorithm shows the best scheduling with the minimum operating cost of generation.
Vitamin D and Primary Ciliary Dyskinesia: A Topic to Be Further Explored
Authors: Sergi Consolato M.
Published: April 2021

Primary ciliary dyskinesia (PCD) is a genetic disease characterized by abnormalities in ciliary structure/function. The diagnosis of PCD relies on a combination of clinical evaluation and ultrastructural (electron microscopic) analysis of the ciliary architecture. This diagnosis may be challenging due to clinical and genetic heterogeneity and artifacts during the ciliary ultrastructure preparation and assessment. Recently, vitamin D supplementation has been proposed for several groups probably suffering from D-hypovitaminosis. Some patients with inflammatory bowel disease may have significant malabsorption, and vitamin D supplementation in these patients is recommended. Two recent reports suggest that a low plasmatic level of this vitamin is present in the PCD population. The utility of vitamin D supplementation may be essential in this group of individuals, and further investigations are warranted. Still, in examining the literature papers, it seems relevant that the authors concentrate solely on lung function in both studies. Future studies should probably target the intestinal function in patients with PCD independently from the vitamin D supplementation to fully evaluate its role.
Inverse Design for Silicon Photonics: From Iterative Optimization Algorithms to Deep Neural Networks
Authors: Mao Simei , Cheng Lirong , Zhao Caiyue , Khan Faisal Nadeem , Li Qian , Fu H. Y.
Published: April 2021

Silicon photonics is a low-cost and versatile platform for various applications. For design of silicon photonic devices, the light-material interaction within its complex subwavelength geometry is difficult to investigate analytically and therefore numerical simulations are majorly adopted. To make the design process more time-efficient and to improve the device performance to its physical limits, various methods have been proposed over the past few years to manipulate the geometries of silicon platform for specific applications. In this review paper, we summarize the design methodologies for silicon photonics including iterative optimization algorithms and deep neural networks. In case of iterative optimization methods, we discuss them in different scenarios in the sequence of increased degrees of freedom: empirical structure, QR-code like structure and irregular structure. We also review inverse design approaches assisted by deep neural networks, which generate multiple devices with similar structure much faster than iterative optimization methods and are thus suitable in situations where piles of optical components are needed. Finally, the applications of inverse design methodology in optical neural networks are also discussed. This review intends to provide the readers with the suggestion for the most suitable design methodology for a specific scenario.
Influence of Selected Model Parameters on the Electromagnetic Levitation Melting Efficiency
Authors: Nycz Blazej , Malinski Lukasz , Przylucki Roman
Published: April 2021

The article presents the results of multivariate calculations for the levitation metal melting system. The research had two main goals. The first goal of the multivariate calculations was to find the relationship between the basic electrical and geometric parameters of the selected calculation model and the maximum electromagnetic buoyancy force and the maximum power dissipated in the charge. The second goal was to find quasi-optimal conditions for levitation. The choice of the model with the highest melting efficiency is very important because electromagnetic levitation is essentially a low-efficiency process. Despite the low efficiency of this method, it is worth dealing with it because is one of the few methods that allow melting and obtaining alloys of refractory reactive metals. The research was limited to the analysis of the electromagnetic field modeled three-dimensionally. From among of 245 variants considered in the article, the most promising one was selected characterized by the highest efficiency. This variant will be a starting point for further work with the use of optimization methods.
Topology Optimization of Multi-Materials Compliant Mechanisms
Authors: Ge Wenjie , Kou Xin
Published: April 2021

In this article, a design method of multi-material compliant mechanism is studied. Material distribution with different elastic modulus is used to meet the rigid and flexible requirements of compliant mechanism at the same time. The solid isotropic material with penalization (SIMP) model is used to parameterize the design domain. The expressions for the stiffness matrix and equivalent elastic modulus under multi-material conditions are proposed. The least square error (LSE) between the deformed and target displacement of the control points is defined as the objective function, and the topology optimization design model of multi-material compliant mechanism is established. The oversaturation problem in the volume constraint is solved by pre-setting the priority of each material, and the globally convergent method of moving asymptotes (GCMMA) is used to solve the problem. Widely studied numerical examples are conducted, which demonstrate the effectiveness of the proposed method.
Lean Maturity Assessment in ETO Scenario
Authors: Chiera Mariastella , Lupi Francesco , Rossi Andrea , Lanzetta Michele
Published: April 2021

The obligatory path towards a lean manufacturing organization requires assessment and monitoring. However, a lean assessment framework is not yet available for the engineer to order (ETO) scenario. This work explored ten lean ETO maturity principles—identified from the literature—that take insight from three formally defined sets (Toyota Way, lean construction, and lean product development principles). A practical assessment model was proposed based on the evaluation of ten lean ETO objective criteria (four with mathematical formulation) and was validated on a real industrial case. A problem-solving tool, including a new lean tool, called the Problem Focus Matrix (PFM), was also presented; this tool was aimed toward development of an integrated framework that would include the organization mission, management, and continuous improvement.
Deep Learning-Based Autoscaling Using Bidirectional Long Short-Term Memory for Kubernetes
Authors: Dang-Quang Nhat-Minh , Yoo Myungsik
Published: April 2021

Presently, the cloud computing environment attracts many application developers to deploy their web applications on cloud data centers. Kubernetes, a well-known container orchestration for deploying web applications on cloud systems, offers an automatic scaling feature to meet clients’ ever-changing demands with the reactive approach. This paper proposes a system architecture based on Kubernetes with a proactive custom autoscaler using a deep neural network model to handle the workload during run time dynamically. The proposed system architecture is designed based on the Monitor–Analyze–Plan–Execute (MAPE) loop. The main contribution of this paper is the proactive custom autoscaler, which focuses on the analysis and planning phases. In analysis phase, Bidirectional Long Short-term Memory (Bi-LSTM) is applied to predict the number of HTTP workloads in the future. In the planning phase, a cooling-down time period is implemented to mitigate the oscillation problem. In addition, a resource removal strategy is proposed to remove a part of the resources when the workload decreases, so that the autoscaler can handle it faster when the burst of workload happens. Through experiments with two different realistic workloads, the Bi-LSTM model achieves better accuracy not only than the Long Short-Term Memory model but also than the state-of-the-art statistical auto-regression integrated moving average model in terms of short- and long-term forecasting. Moreover, it offers 530 to 600 times faster prediction speed than ARIMA models with different workloads. Furthermore, as compared to the LSTM model, the Bi-LSTM model performs better in terms of resource provision accuracy and elastic speedup. Finally, it is shown that the proposed proactive custom autoscaler outperforms the default horizontal pod autoscaler (HPA) of the Kubernetes in terms of accuracy and speed when provisioning and de-provisioning resources.
Monotonic Functions Method and Its Application to Staging of Patients with Prostate Cancer According to Pretreatment Data
Authors: Gitis Valeri , Derendyaev Alexander , Petrov Konstantin , Yurkov Eugene , Pirogov Sergey , Sergeeva Natalia , Alekseev Boris , Kaprin Andrey
Published: April 2021

Prostate cancer is the second most frequent malignancy (after lung cancer). Preoperative staging of PCa is the basis for the selection of adequate treatment tactics. In particular, an urgent problem is the classification of indolent and aggressive forms of PCa in patients with the initial stages of the tumor process. To solve this problem, we propose to use a new binary classification machine-learning method. The proposed method of monotonic functions uses a model in which the disease’s form is determined by the severity of the patient’s condition. It is assumed that the patient’s condition is the easier, the less the deviation of the indicators from the normal values inherent in healthy people. This assumption means that the severity (form) of the disease can be represented by monotonic functions from the values of the deviation of the patient’s indicators beyond the normal range. The method is used to solve the problem of classifying patients with indolent and aggressive forms of prostate cancer according to pretreatment data. The learning algorithm is nonparametric. At the same time, it allows an explanation of the classification results in the form of a logical function. To do this, you should indicate to the algorithm either the threshold value of the probability of successful classification of patients with an indolent form of PCa, or the threshold value of the probability of misclassification of patients with an aggressive form of PCa disease. The examples of logical rules given in the article show that they are quite simple and can be easily interpreted in terms of preoperative indicators of the form of the disease.
Football Juggling Learning Alters the Working Memory and White Matter Integrity in Early Adulthood: A Randomized Controlled Study
Authors: Shi Yifan , Cai Kelong , Zhu Hao , Dong Xiaoxiao , Xiong Xuan , Zhu Lina , Sun Zhiyuan , Chen Aiguo
Published: April 2021

Cross-sectional studies suggest that motor skill learning is associated with working memory (WM) and white matter integrity (WMI). However, it has not been established whether motor skill learning improves WM performance, and information on its neural mechanisms have not been clearly elucidated. Therefore, this study compared WM and WMI across time points prior to and following football juggling learning, in early adulthood (18–20 years old), relative to a control group. Study participants in the experimental group were subjected to football juggling for 10 weeks while participants in the control category went on with their routine life activities for the same period of time and were not involved in the learning-related activities. Data on cognitive measurements and that from diffusion tensor imaging (DTI) were collected before and after learning. There was a significant improvement in WM performance of the experimental group after motor learning, although no improvement was observed in the control group. Additionally, after learning, DTI data revealed a significant increase in functional anisotropy (FA) in the genu of corpus callosum (GOCC) and the right anterior corona radiata (R.ACR) in the experimental group. Moreover, the better WM associated with football juggling learning was correlated to a higher FA. Mediation analysis suggested that FA in the GOCC acts as a mediation variable between football juggling learning and WM. These findings show that motor skill learning improves the WM and remodels WMI in early adulthood. With a particular emphasis on the importance of WMI in motor skill learning and WM, this study also revealed the possible neural mechanisms mediated by WMI.
Basic Statistical Estimation Outperforms Machine Learning in Monthly Prediction of Seasonal Climatic Parameters
Authors: Hussein Eslam A. , Ghaziasgar Mehrdad , Thron Christopher , Vaccari Mattia , Bagula Antoine
Published: April 2021

Machine learning (ML) has been utilized to predict climatic parameters, and many successes have been reported in the literature. In this paper, we scrutinize the effectiveness of five widely used ML algorithms in the monthly prediction of seasonal climatic parameters using monthly image data. Specifically, we quantify the predictive performance of these algorithms applied to five climatic parameters using various combinations of features. We compare the predictive accuracy of the resulting trained ML models to that of basic statistical estimators that are computed directly from the training data. Our results show that ML never significantly outperforms the statistical baseline, and underperforms for most feature sets. Unlike previous similar studies, we provide error bars for the relative performance of different predictors based on jackknife estimates applied to differences in predictive error magnitudes. We also show that the practice of shuffling data sequences which was employed in some previous references leads to data leakage, resulting in over-estimated performance. Ultimately, the paper demonstrates the importance of using well-grounded statistical techniques when producing and analyzing the results of ML predictive models.
USA Mid-Atlantic Consumer Preferences for Front Label Attributes for Local Wine
Authors: Todd Marielle J. , Kelley Kathleen M. , Hopfer Helene
Published: April 2021

The purpose of this research was to investigate Mid-Atlantic USA wine consumers’ preferences for front wine label attributes for a lesser-known/unknown local wine variety. The wine consumer base in this part of the USA exceeds that of California. Although the mid-Atlantic is experiencing an increase in the number of wineries, there is a lack of region-specific consumer research that could be the basis for marketing strategies that may differ from those in more established wine regions, such as CA. We recruited 1011 mid-Atlantic consumers who drank wine (at least 1×/month) to view variations of a wine label, differing in wine tag, location description, font types, and images in a choice-based conjoint experiment. A greater percentage of consumers selected the “White Wine” tag and scripted fonts than the other options, with a generalized county text (“Proudly produced in Lehigh County, PA”) being selected by more participants than the American Viticultural Area (AVA) (“Lehigh Valley AVA”) or state (“Pennsylvania”) texts; however, the location text had a lower importance than the wine tag variable. This study implies that a generalized county text that describes a more specific location where the grapes were grown may be more favorable to mid-Atlantic consumers in comparison to AVA or state texts, and that traditional images and generic wine labels are more preferable than wine labels they have not seen before and more contemporary label styles. Wineries in the mid-Atlantic region may want to add generalized county texts to their labels to appeal to the regional audience. As AVAs are used to promote specific wine regions in the USA, and only some consumers choose wines based on these designations, governments and marketing organizations may want to increase education on local AVAs to increase consumer awareness and interest. In addition, consumer differences in variety-seeking behavior and subjective as well as objective wine knowledge, but not attitudes toward locally produced foods, affected wine label choice: Consumers scoring higher in variety-seeking and wine knowledge preferred the specific wine varietal over the generic wine tag; similarly, consumers that indicated familiarity with the wine varietal also preferred the specific wine tag over the generic label. Differences in consumer psychographics appear to modulate front wine label preferences.