bluuebunny/crossref_metadata_2025 huggingface dataset:
Erythromycin Treatment of Brassica campestris Seedlings Impacts the Photosynthetic and Protein Synthesis Pathways
Authors: Yoon Young-Eun , Cho Hyun Min , Bae Dong-won , Lee Sung Joong , Choe Hyeonji , Kim Min Chul , Cheong Mi Sun , Lee Yong Bok
Published: November 2020

Erythromycin (Ery) is a commonly used veterinary drug that prevents infections and promotes the growth of farm animals. Ery is often detected in agricultural fields due to the effects of manure application in the ecosystem. However, there is a lack of information on Ery toxicity in crops. In this study, we performed a comparative proteomic analysis to identify the molecular mechanisms of Ery toxicity during seedling growth based on our observation of a decrease in chlorophyll (Chl) contents using Brassica campestris. A total of 452 differentially abundant proteins (DAPs) were identified including a ribulose-1,5-bisphosphate carboxylase (RuBisCO). The proteomic analysis according to gene ontology (GO) classification revealed that many of these DAPs responding to Ery treatment functioned in a cellular process and a metabolic process. The molecular function analysis showed that DAPs classified within catalytic activity were predominantly changed by Ery, including metabolite interconversion enzyme and protein modifying enzyme. An analysis of functional pathways using MapMan revealed that many photosynthesis components were downregulated, whereas many protein biosynthesis components were upregulated. A good relationship was observed between protein and transcript abundance in a photosynthetic pathway, as determined by qPCR analysis. These combined results suggest that Ery affects plant physiological activity by downregulating protein abundance in the photosynthetic pathway.
An Accelerating Numerical Computation of the Diffusion Term in a Nonlocal Reaction-Diffusion Equation
Authors: CRAUS Mitică , PAVĂL Silviu-Dumitru
Published: November 2020

In this paper we propose and compare two methods to optimize the numerical computations for the diffusion term in a nonlocal formulation for a reaction-diffusion equation. The diffusion term is particularly computationally intensive due to the integral formulation, and thus finding a better way of computing its numerical approximation could be of interest, given that the numerical analysis usually takes place on large input domains having more than one dimension. After introducing the general reaction-diffusion model, we discuss a numerical approximation scheme for the diffusion term, based on a finite difference method. In the next sections we propose two algorithms to solve the numerical approximation scheme, focusing on finding a way to improve the time performance. While the first algorithm (sequential) is used as a baseline for performance measurement, the second algorithm (parallel) is implemented using two different memory-sharing parallelization technologies: Open Multi-Processing (OpenMP) and CUDA. All the results were obtained by using the model in image processing applications such as image restoration and segmentation.
Some Improvements of the Cauchy-Schwarz Inequality Using the Tapia Semi-Inner-Product
Authors: Minculete Nicuşor , Moradi Hamid Reza
Published: November 2020

The aim of this article is to establish several estimates of the triangle inequality in a normed space over the field of real numbers. We obtain some improvements of the Cauchy–Schwarz inequality, which is improved by using the Tapia semi-inner-product. Finally, we obtain some new inequalities for the numerical radius and norm inequalities for Hilbert space operators.
The Consistency of the CUSUM-Type Estimator of the Change-Point and Its Application
Authors: Ding Saisai , Li Xiaoqin , Dong Xiang , Yang Wenzhi
Published: November 2020

In this paper, we investigate the CUSUM-type estimator of mean change-point models based on m-asymptotically almost negatively associated (m-AANA) sequences. The family of m-AANA sequences contains AANA, NA, m-NA, and independent sequences as special cases. Under some weak conditions, some convergence rates are obtained such as OP(n1/p−1), OP(n1/p−1log1/pn) and OP(nα−1), where 0≤α<1 and 1<p≤2. Our rates are better than the ones obtained by Kokoszka and Leipus (Stat. Probab. Lett., 1998, 40, 385–393). In order to illustrate our results, we do perform simulations based on m-AANA sequences. As important applications, we use the CUSUM-type estimator to do the change-point analysis based on three real data such as Quebec temperature, Nile flow, and stock returns for Tesla. Some potential applications to change-point models in finance and economics are also discussed in this paper.
Interval Model of the Efficiency of the Functioning of Information Web Resources for Services on Ecological Expertise
Authors: Dyvak Mykola , Papa Oleksandr , Melnyk Andrii , Pukas Andriy , Porplytsya Nataliya , Rot Artur
Published: November 2020

Mathematical models of the efficiency dynamics of information web resources are considered in this paper. The application of interval discrete models in the form of difference equations is substantiated and the approach to estimation of the model parameters is proposed. The proposed approach is based on the artificial bee colony algorithm (ABCA). A number of experimental studies have been carried out based on data on the functioning of web resources related to environmental monitoring services. The indicator of an information web resource user’s activity has been investigated. Three cases of model building in the form of difference equations as interval discrete models (IDM) have been considered. They vary in the general kind of expression. As a result of the computational experiments, it is shown that the adequacy of a model depends on the expression of the difference equation. In the case of its incorrect choice, the proposed method of parameters’ identification may be ineffective. The obtained interval discrete model in the difference equation form, which describes the efficiency of a web resource, makes it possible to optimize business processes in an organization that uses this web resource, as well as optimally allocate organizational resources and the workload of employees of the administrative service center. Based on the conducted experiments, the efficiency of the proposed model’s application is confirmed.
The Structure of the Lipid A of Gram-Negative Cold-Adapted Bacteria Isolated from Antarctic Environments
Authors: Di Lorenzo Flaviana , Crisafi Francesca , La Cono Violetta , Yakimov Michail M. , Molinaro Antonio , Silipo Alba
Published: November 2020

Gram-negative Antarctic bacteria adopt survival strategies to live and proliferate in an extremely cold environment. Unusual chemical modifications of the lipopolysaccharide (LPS) and the main component of their outer membrane are among the tricks adopted to allow the maintenance of an optimum membrane fluidity even at particularly low temperatures. In particular, the LPS’ glycolipid moiety, the lipid A, typically undergoes several structural modifications comprising desaturation of the acyl chains, reduction in their length and increase in their branching. The investigation of the structure of the lipid A from cold-adapted bacteria is, therefore, crucial to understand the mechanisms underlying the cold adaptation phenomenon. Here we describe the structural elucidation of the highly heterogenous lipid A from three psychrophiles isolated from Terra Nova Bay, Antarctica. All the lipid A structures have been determined by merging data that was attained from the compositional analysis with information from a matrix-assisted laser desorption ionization (MALDI) time of flight (TOF) mass spectrometry (MS) and MS2 investigation. As lipid A is also involved in a structure-dependent elicitation of innate immune response in mammals, the structural characterization of lipid A from such extremophile bacteria is also of great interest from the perspective of drug synthesis and development inspired by natural sources.
Fear-Avoidance Behavior and Sickness Absence in Patients with Work-Related Musculoskeletal Disorders
Authors: Macías-Toronjo Israel , Sánchez-Ramos José L. , Rojas-Ocaña María J. , García-Navarro Esperanza Begoña
Published: November 2020

(1) Background and objectives: The purpose of this work is to determine the association of fear-avoidance attitudes with sickness absence status, its duration and disability in a work accident context. (2) Materials and Methods: This is a descriptive observational design, conducting the study in two occupational insurance provider clinics with patients with nonspecific low back and neck pain during the study period. Clinical variables were the Fear Avoidance Questionnaire, Roland Morris Disability Questionnaire, Neck Disability Index, Numerical Pain Scale; sociodemographic variables were sex, age, occupational, educational level, sickness absence status, and duration in days of absence from work. Multiple logistic and linear regressions were used to explore the association between variables. (3) Results: Fear-avoidance behavior is related to sickness absence status (OR = 1.048, p = 0.007), and the physical activity dimension (OR = 1.098, p = 0.013) is more relevant than the work dimension (OR = 1.056, p = 0.028). The duration of sickness absence is related to higher values on the fear-avoidance behavior scale in its global dimension (b = 0.84, p = 0.003, r = 0.327), and the results of the physical activity dimension (B = 1.37, p = 0.035, r = 0.236) were more relevant than the work dimension (B = 1.21, p = 0.003, r = 0.324). Fear-avoidance behavior is related to disability in both dimensions (B = 0.912, p ˂ 0.001, r = 0.505). (4) Conclusions: Fear-avoidance behaviors may influence the typification of sickness absence status, its duration both in its physical activity and work dimension, and its disability reported with higher values than in other healthcare contexts.
Quality of Life of Informal Caregivers behind the Scene of the COVID-19 Epidemic in Serbia
Authors: Todorovic Natasa , Vracevic Milutin , Rajovic Nina , Pavlovic Vedrana , Madzarevic Petar , Cumic Jelena , Mostic Tanja , Milic Nikola , Rajovic Tatjana , Sapic Rosa , Milcanovic Petar , Velickovic Igor , Culafic Slobodan , Stanisavljevic Dejana , Milic Natasa
Published: November 2020

Background and objectives: The COVID-19 pandemic has had an unprecedented reliance on informal caregivers as one of the pillars of healthcare systems. The aim of this study was to assess the quality of life of informal caregivers during the COVID-19 epidemic in Serbia. Materials and Methods: A cross-sectional study was conducted among informal caregivers during the COVID-19 epidemic in Serbia. Physical and mental quality of life was measured by the 36-Item Short-Form Health Survey. Additional data included sociodemographic characteristics, caregiver and care recipient characteristics, and COVID-19 related concerns. The qualitative component was performed using focus groups and individual in-depth interviews. Results: Out of 112 informal caregivers enrolled, most were female (80%), and the average age was 51.1 ± 12.3 years. The majority was delivering care to one person, who was a family member, on a daily basis (86.4%, 92%, and 91.1%, respectively). In multiple regression models, significant predictors of caregivers’ physical health were delivering care to a family member and a higher level of care complexity, while significant predictors of caregivers’ mental health were a higher level of care complexity and increased concerns about self-health and the health of the person being cared for due to the COVID-19 epidemic. Conclusions: Informal caregivers are experiencing negative physical and mental health outcomes during the COVID-19 epidemic in Serbia.
Neurodevelopmental Outcome in Extremely Low Birth Weight Infants at 2–3 Years of Age
Authors: Kyriakidou Maria , Chatziioannidis Ilias , Mitsiakos Georgios , Lampropoulou Sofia , Pouliakis Abraham
Published: November 2020

Background and objectives: The aims of this study were to examine the relationship between neurological outcomes at 3- and 6-months corrected age with the neurodevelopmental outcome at 3 years of age; to identify the perinatal/neonatal risk factors for poor neurodevelopmental outcomes at 3 years of age. Materials and methods: In our single-centre longitudinal cohort study, of the 73 consecutive infants admitted to our Neonatal Intensive Care Unit (NICU), 49 infants (80%) received both Hammersmith Infant Neurological Examination (HINE) at 3- and 6-months corrected age and Bayley–III neurodevelopmental assessment at 2–3 years chronological age. At 3 months follow up, 8.2% had suboptimal scores (below 10th percentile) on the HINE. At 6 months follow up, 4.1% had suboptimal scores (below 10th percentile) on the HINE. The means(±SD) for Bayley-III cognitive, language, and motor subscales were (96.3 ± 9.8), (99.9 ± 11.9), (93.2 ± 9.9). Results: At 3 months corrected age, higher total HINE scores and subscores for function of cranial nerves, posture, tone, were associated with better cognitive scores while poorer scores for function of cranial nerves, posture, movements, tone, and total HINE score were associated with lower motor scores. Infants with a HINE subscore of function of cranial nerves in the suboptimal range have three times higher odds of having a motor delay. Infants with a HINE subscore of function of cranial nerves in the suboptimal range have more than two times higher odds of having a language delay. At 6 months corrected age, poorer scores for function of cranial nerves, movements, tone, reflexes, and total HINE score were associated with worse Bayley-III motor scores whilst infants who have a total HINE score and a subscore of reflexes in the suboptimal range have four and seven times, respectively, higher odds of having a motor delay. Conclusions: Early identification of infants at risk for adverse long-term outcomes is essential in introducing early intervention therapies for optimizing neurodevelopmental outcomes.
A Continuous Cell Separation and Collection Approach on a Microfilter and Negative Dielectrophoresis Combined Chip
Authors: Wang Qiong , Zhang Xiaoling , Yin Danfen , Deng Jinan , Yang Jun , Hu Ning
Published: November 2020

Cell separation plays an important role in the fields of analytical chemistry and biomedicine. To solve the blockage problem and improve the separation throughput in the traditional microstructure filtration-based separation approach, a continuous cell separation and collection approach via micropost array railing on a microfilter and negative dielectrophoresis combined chip is proposed. By tilting the micropost array at a certain angle, microparticles or cells enter the collection area under micropost array railing. The effects of the inclination angle of the micropost array and the electrode distance on the microparticle collection efficiency were investigated. Based on the optimized microfluidic chip structure, 37- and 16.3-μm particles were collected with 85% and 89% efficiencies, respectively. Additionally, algal cells were separated and collected by using the optimized microchip. The chip also had good separation and collection effects on biological samples, which effectively solved the blockage problem and improved the separation throughput, laying a foundation for subsequent microstructure filtration separation-based research and application.
Recent Advances in The Polymer Dispersed Liquid Crystal Composite and Its Applications
Authors: Saeed Mohsin Hassan , Zhang Shuaifeng , Cao Yaping , Zhou Le , Hu Junmei , Muhammad Imran , Xiao Jiumei , Zhang Lanying , Yang Huai
Published: November 2020

Polymer dispersed liquid crystals (PDLCs) have kindled a spark of interest because of their unique characteristic of electrically controlled switching. However, some issues including high operating voltage, low contrast ratio and poor mechanical properties are hindering their practical applications. To overcome these drawbacks, some measures were taken such as molecular structure optimization of the monomers and liquid crystals, modification of PDLC and doping of nanoparticles and dyes. This review aims at detailing the recent advances in the process, preparations and applications of PDLCs over the past six years.
Measurement of CeO2 Nanoparticles in Natural Waters Using a High Sensitivity, Single Particle ICP-MS
Authors: Jreije Ibrahim , Azimzada Agil , Hadioui Madjid , Wilkinson Kevin J.
Published: November 2020

As the production and use of cerium oxide nanoparticles (CeO2 NPs) increases, so does the concern of the scientific community over their release into the environment. Single particle inductively coupled plasma mass spectrometry is emerging as one of the best techniques for NP detection and quantification; however, it is often limited by high size detection limits (SDL). To that end, a high sensitivity sector field ICP-MS (SF-ICP-MS) with microsecond dwell times (50 µs) was used to lower the SDL of CeO2 NPs to below 4.0 nm. Ag and Au NPs were also analyzed for reference. SF-ICP-MS was then used to detect CeO2 NPs in a Montreal rainwater at a concentration of (2.2 ± 0.1) × 108 L−1 with a mean diameter of 10.8 ± 0.2 nm; and in a St. Lawrence River water at a concentration of ((1.6 ± 0.3) × 109 L−1) with a higher mean diameter (21.9 ± 0.8 nm). SF-ICP-MS and single particle time of flight ICP-MS on Ce and La indicated that 36% of the Ce-containing NPs detected in Montreal rainwater were engineered Ce NPs.
Pharmacokinetic Characterization of (Poly)phenolic Metabolites in Human Plasma and Urine after Acute and Short-Term Daily Consumption of Mango Pulp
Authors: Fan Jiayi , Xiao Di , Zhang Liyun , Edirisinghe Indika , Burton-Freeman Britt , Sandhu Amandeep K.
Published: November 2020

Pharmacokinetic (PK) evaluation of polyphenolic metabolites over 24 h was conducted in human subjects (n = 13, BMI = 22.7 ± 0.4 kg/m2) after acute mango pulp (MP), vitamin C (VC) or MP + VC test beverage intake and after 14 days of MP beverage intake. Plasma and urine samples were collected at different time intervals and analyzed using targeted and non-targeted mass spectrometry. The maximum concentrations (Cmax) of gallotannin metabolites were significantly increased (p < 0.05) after acute MP beverage intake compared to VC beverage alone. MP + VC beverage non-significantly enhanced the Cmax of gallic acid metabolites compared to MP beverage alone. Pyrogallol (microbial-derived metabolite) derivatives increased (3.6%) after the 14 days of MP beverage intake compared to 24 h acute MP beverage intake (p < 0.05). These results indicate extensive absorption and breakdown of gallotannins to galloyl and other (poly)phenolic metabolites after MP consumption, suggesting modulation and/or acclimation of gut microbiota to daily MP intake.
Natural Products Extracted from Fungal Species as New Potential Anti-Cancer Drugs: A Structure-Based Drug Repurposing Approach Targeting HDAC7
Authors: Maruca Annalisa , Rocca Roberta , Catalano Raffaella , Mesiti Francesco , Costa Giosuè , Lanzillotta Delia , Salatino Alessandro , Ortuso Francesco , Trapasso Francesco , Alcaro Stefano , Artese Anna
Published: November 2020

Mushrooms can be considered a valuable source of natural bioactive compounds with potential polypharmacological effects due to their proven antimicrobial, antiviral, antitumor, and antioxidant activities. In order to identify new potential anticancer compounds, an in-house chemical database of molecules extracted from both edible and non-edible fungal species was employed in a virtual screening against the isoform 7 of the Histone deacetylase (HDAC). This target is known to be implicated in different cancer processes, and in particular in both breast and ovarian tumors. In this work, we proposed the ibotenic acid as lead compound for the development of novel HDAC7 inhibitors, due to its antiproliferative activity in human breast cancer cells (MCF-7). These promising results represent the starting point for the discovery and the optimization of new HDAC7 inhibitors and highlight the interesting opportunity to apply the “drug repositioning” paradigm also to natural compounds deriving from mushrooms.
Self-Assembly of Low-Molecular-Weight Asymmetric Linear Triblock Terpolymers: How Low Can We Go?
Authors: Miskaki Christina , Moutsios Ioannis , Manesi Gkreti-Maria , Artopoiadis Konstantinos , Chang Cheng-Yen , Bersenev Egor A. , Moschovas Dimitrios , Ivanov Dimitri A. , Ho Rong-Ming , Avgeropoulos Apostolos
Published: November 2020

The synthesis of two (2) novel triblock terpolymers of the ABC type and one (1) of the BAC type, where A, B and C are chemically different segments, such as polystyrene (PS), poly(butadiene) (PB1,4) and poly(dimethylsiloxane) (PDMS), is reported; moreover, their corresponding molecular and bulk characterizations were performed. Very low dimensions are evident from the characterization in bulk from transmission electron microscopy studies, verified by small-angle X-ray data, since sub-16 nm domains are evident in all three cases. The self-assembly results justify the assumptions that the high Flory–Huggins parameter, χ, even in low molecular weights, leads to significantly well-ordered structures, despite the complexity of the systems studied. Furthermore, it is the first time that a structure/properties relationship was studied for such systems in bulk, potentially leading to prominent applications in nanotechnology and nanopatterning, for as low as sub-10 nm thin-film manipulations.
Synthesis and Properties of Pentafluorosulfanyl Group (SF5)-Containing Meta-Diamide Insecticides
Authors: Kim Jae Gon , Kang On-Yu , Kim Sang Mee , Issabayeva Guldana , Oh In Seok , Lee Yaeji , Lee Won Hyung , Lim Hwan Jung , Park Seong Jun
Published: November 2020

Herein, we describe novel pentafluorosulfanyl (SF5) group-containing meta-diamide insecticides. For the facile preparation of the SF5-based compounds 4a–d, practical synthetic methods were applied. Among newly synthesized compounds, 3-benzamido-N-(2,6-dimethyl-4-(pentafluoro-λ6-sulfanyl)phenyl)-2-fluorobenzamide 4d showed (i) a high insecticidal activity, (ii) an excellent selectivity to insects, and (iii) good levels of water solubility and log P values. In this study, we demonstrated that the pentafluorosulfanyl moiety could serve as an attractive functionality for the discovery of a new scope of crop-protecting agents.
Biosynthesis of Polyhydroxyalkanoates (PHAs) by the Valorization of Biomass and Synthetic Waste
Authors: Javaid Hadiqa , Nawaz Ali , Riaz Naveeda , Mukhtar Hamid , -Ul-Haq Ikram , Shah Kanita Ahmed , Khan Hooria , Naqvi Syeda Michelle , Shakoor Sheeba , Rasool Aamir , Ullah Kaleem , Manzoor Robina , Kaleem Imdad , Murtaza Ghulam
Published: November 2020

Synthetic pollutants are a looming threat to the entire ecosystem, including wildlife, the environment, and human health. Polyhydroxyalkanoates (PHAs) are natural biodegradable microbial polymers with a promising potential to replace synthetic plastics. This research is focused on devising a sustainable approach to produce PHAs by a new microbial strain using untreated synthetic plastics and lignocellulosic biomass. For experiments, 47 soil samples and 18 effluent samples were collected from various areas of Punjab, Pakistan. The samples were primarily screened for PHA detection on agar medium containing Nile blue A stain. The PHA positive bacterial isolates showed prominent orange–yellow fluorescence on irradiation with UV light. They were further screened for PHA estimation by submerged fermentation in the culture broth. Bacterial isolate 16a produced maximum PHA and was identified by 16S rRNA sequencing. It was identified as Stenotrophomonas maltophilia HA-16 (MN240936), reported first time for PHA production. Basic fermentation parameters, such as incubation time, temperature, and pH were optimized for PHA production. Wood chips, cardboard cutouts, plastic bottle cutouts, shredded polystyrene cups, and plastic bags were optimized as alternative sustainable carbon sources for the production of PHAs. A vital finding of this study was the yield obtained by using plastic bags, i.e., 68.24 ± 0.27%. The effective use of plastic and lignocellulosic waste in the cultivation medium for the microbial production of PHA by a novel bacterial strain is discussed in the current study.
MatMouse: A Mouse Movements Tracking and Analysis Toolbox for Visual Search Experiments
Authors: Krassanakis Vassilios , Kesidis Anastasios L.
Published: November 2020

The present study introduces a new MATLAB toolbox, called MatMouse, suitable for the performance of experimental studies based on mouse movements tracking and analysis. MatMouse supports the implementation of task-based visual search experiments. The proposed toolbox provides specific functions which can be utilized for the experimental building and mouse tracking processes, the analysis of the recorded data in specific metrics, the production of related visualizations, as well as for the generation of statistical grayscale heatmaps which could serve as an objective ground truth product. MatMouse can be executed as a standalone package or integrated in existing MATLAB scripts and/or toolboxes. In order to highlight the functionalities of the introduced toolbox, a complete case study example is presented. MatMouse is freely distributed to the scientific community under the third version of GNU General Public License (GPL v3) on GitHub platform.
Dynamics and Pretransitional Effects in C60 Fullerene Nanoparticles and Liquid Crystalline Dodecylcyanobiphenyl (12CB) Hybrid System
Authors: Rzoska Sylwester J. , Starzonek Szymon , Łoś Joanna , Drozd-Rzoska Aleksandra , Kralj Samo
Published: November 2020

The report shows the strong impact of fullerene C60 nanoparticles on phase transitions and complex dynamics of rod-like liquid crystal dodecylcyanobiphenyl (12CB), within the limit of small concentrations. Studies were carried out using broadband dielectric spectroscopy (BDS) via the analysis of temperature dependences of the dielectric constant, the maximum of the primary loss curve, and relaxation times. They revealed a strong impact of nanoparticles, leading to a ~20% change of dielectric constant even at x = 0.05% of C60 fullerene. The application of the derivative-based and distortion-sensitive analysis showed that pretransitional effects dominate in the isotropic liquid phase up to 65 K above the clearing temperature and in the whole Smectic A mesophase. The impact of nanoparticles on the pretransitional anomaly appearance is notable for the smectic–solid phase transition. The fragility-based analysis of relaxation times revealed the universal pattern of its temperature changes, associated with scaling via the “mixed” (“activated” and “critical”) relation. Phase behavior and dynamics of tested systems are discussed within the extended Landau–de Gennes–Ginzburg mesoscopic approach.
Spin Susceptibility in Neutron Matter from Quantum Monte Carlo Calculations
Authors: Riz Luca , Pederiva Francesco , Lonardoni Diego , Gandolfi Stefano
Published: November 2020

The spin susceptibility in pure neutron matter is computed from auxiliary field diffusion Monte Carlo calculations over a wide range of densities. The calculations are performed for different spin asymmetries, while using twist-averaged boundary conditions to reduce finite-size effects. The employed nuclear interactions include both the phenomenological Argonne AV8′ + UIX potential and local interactions that are derived from chiral effective field theory up to next-to-next-to-leading order.
Erratum: Blume, C., et al. Modulation of Human Airway Barrier Functions during Burkholderia thailandensis and Francisella tularensis Infection Running Title: Airway Barrier Functions during Bacterial Infections. Pathogens 2016, 5, 53
Authors: Blume Cornelia , David Jonathan , Bell Rachel E. , Laver Jay R. , Read Robert C. , Clark Graeme C. , Davies Donna E. , Swindle Emily J.
Published: November 2020

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The Association between Cognitive Impairment and Diabetic Foot Care: Role of Neuropathy and Glycated Hemoglobin
Authors: Brognara Lorenzo , Volta Iacopo , Cassano Vito Michele , Navarro-Flores Emmanuel , Cauli Omar
Published: November 2020

Diabetes mellitus is associated with impairment in cognitive functions which can complicate adherence to self-care behaviors. We evaluated the incidence of cognitive impairment in patients with diabetes mellitus to determine the strength of the association between diabetic foot (a complication that occurs in about 10% of diabetic patients), adherence to the clinician’s recommendations, glycemic control, and cognitive function. A prospective study was carried out in a probabilistic sample of older patients with diabetic foot living in three nursing homes. Cognitive functions were evaluated by the MMSE (Mini-Mental State Examination), the Trail Making test (TMT), and the Michigan neuropathy screening instrument (MNSI). There were no significant associations between cognitive function and neuropathy or foot alterations, although glycated hemoglobin (HB1Ac > 7%) significantly (p < 0.05) associated with MMSE and adherence to treatment in the 1 month follow-up visit. Receiver operating characteristic curve analysis showed that both HB1Ac and the MNSI score significantly (p < 0.05) discriminate subsequent adherence to treatment for foot complication, with a sensitivity of 80.0–73.3% and specificity 70.6–64.7%, respectively. Proper control of foot complications in diabetic patients involves appropriate glycemic control and less severe neuropathy, and seems to be unrelated to cognitive dysfunction, and warrants further studies in order to tailor appropriate treatments to central and peripheral nervous system disorders. Poor glycemic control (Hb1Ac level > 7%) and a neuropathy score of 5.5 in the MNSI are the best-cut off points to discriminate poor adherence to the clinician’s recommendations for self-care behaviors in people with diabetic foot complication. In this study, we observed that foot disorders were associated with impaired global cognitive function in elderly patients (aged ≥ 65). Podiatrists and physicians should consider cognitive dysfunction as an important chronic complication in the management of diabetic foot.
Heat Transfer and Rheological Behavior of Fumed Silica Nanofluids
Authors: Gómez-Merino A.I. , Jiménez-Galea J.J. , Rubio-Hernández F.J. , Arjona-Escudero J.L. , Santos-Ráez I.M.
Published: November 2020

The addition of nanoparticles to liquid media can improve thermomechanical properties of dispersants. This ability gives rise to the development of multiple applications of nanofluids (NF) in branches so different as electronic and photonic devices or cosmetic industry. Logically, these applications require a good control of heat transfer and flow properties. Moreover, if we consider the necessity to optimize industrial processes in which NF take part, it is necessary to obtain possible relationships between both physical mechanisms. Specifically, in this work, a study about thermal conductivity and rheological behavior of fumed silica suspensions in polypropylene glycol (PPG400) and polyethylene glycol (PEG200) was performed. The study of these two suspensions is interesting because the flow behaviors are very dissimilar (while the fumed silica in PEG200 suspension is viscoplastic, the fumed silica in PPG400 suspension shows shear-thickening behavior between two shear-thinning regions), despite the addition of fumed silica producing similar enhancement of the relative thermal conductivity in both liquid phases. The more outstanding contribution of this work lies in the combination of rheological and conductivity measurements to deepen in the understanding of the heat transfer phenomenon in NF. The combination of rheological together with thermal conductivity measurements have permitted establishing the mechanisms of liquid layering and aggregate formation as the more relevant in the heat transfer of these silica fumed suspensions.
Trimeric SARS-CoV-2 Spike Proteins Produced from CHO Cells in Bioreactors Are High-Quality Antigens
Authors: Pino Paco , Kint Joeri , Kiseljak Divor , Agnolon Valentina , Corradin Giampietro , Kajava Andrey V. , Rovero Paolo , Dijkman Ronald , den Hartog Gerco , McLellan Jason S. , Byrne Patrick O. , Wurm Maria J. , Wurm Florian M.
Published: November 2020

The spike protein of the pandemic human corona virus is essential for its entry into human cells. In fact, most neutralizing antibodies against Severe Acute Respiratory Syndrome Corona Virus 2 (SARS-CoV-2) are directed against the Virus-surface exposed spike protein, making it the antigen of choice for use in vaccines and diagnostic tests. In the current pandemic context, global demand for spike proteins has rapidly increased and could exceed hundreds of grams to kilograms annually. Coronavirus spikes are large heavily glycosylated homo-trimeric complexes, with inherent instability. The poor manufacturability now threatens the availability of these proteins for vaccines and diagnostic tests. Here, we outline scalable, Good Manufacturing Practice (GMP) compliant, and chemically defined processes for the production of two cell-secreted stabilized forms of the trimeric spike proteins (Wuhan and D614G variant). The processes are chemically defined and based on clonal suspension-CHO cell populations and on protein purification via a two-step scalable downstream process. The trimeric conformation was confirmed using electron microscopy and HPLC analysis. Binding to susceptible cells was shown using a virus-inhibition assay. The diagnostic sensitivity and specificity for detection of serum SARS-CoV-2-specific-immunoglobulin molecules was found to exceed that of spike fragments (Spike subunit-1, S1 and Receptor Binding Domain, RBD). The process described here will enable production of sufficient high-quality trimeric spike protein to meet the global demand for SARS-CoV-2 diagnostic tests and potentially vaccines.
Preliminary Practices: Bloody Knees, Calloused Palms, and the Transformative Nature of Women’s Labor
Authors: Fitzgerald Kati
Published: November 2020

In this article, I explore the prostration accumulation portion of the Preliminary Practices of a specific group of Tibetan Buddhist women in Bongwa Mayma, a rural area of Yushu Tibetan Autonomous Prefecture in Qinghai Province. I focus specifically on the nuns and lay women who utilize this set of teachings and practices. The Preliminary Practices not only initiate practitioners into a specific tradition (that of the Drikung Kagyu and more specifically the Amitabha practices of this lineage), but also more fundamentally into Vajrayāna Buddhism as it is practiced in contemporary Tibet. Although monks and male lay practitioners in this region also tend to perform the same Preliminary Practices, I focus specifically on women because of their unique relationship with bodily labor. I begin this article with a discussion of the domestic and economic labor practices of contemporary Tibetan women in rural Yushu, followed by an analysis of Preliminary Practices as understood through the Preliminary Practice text and oral commentaries utilized by all interviewees and interviews (collected from 2016–2020) with female practitioners about their motivations, experiences, and realizations during the Refuge and prostration accumulation portion of their Preliminary Practices. Women themselves view bodily labor as a productive and inevitable aspect of life. On the one hand, women state openly that their domestic duties impede upon their ability to achieve religious realization. On the other, they frequently extol the virtues of hard work, perseverance, patience, and fortitude that their lives of labor helped them to cultivate. Prostration is meant to embody the act of going for Refuge, of submitting oneself to the teachings of the Buddha, to the path of the dharma, and to the community of religious practitioners with whom they will study and grow. Prostrations are meant to embody the extreme difficulty of Refuge, to remove obscurations, to crush the ego, and to confirm a dedication to endure the hardships on the path to realization. Buddhist women, despite their ambiguous relationship with physical labor, see the physical pain of this process as a transformative experience that allows them a glimpse of the spaciousness of mind and freedom from attachment-filled desire promised in the teachings they receive.
Utilization of Common Reed (Phragmites australis) as Bedding for Housed Suckler Cows: Practical and Economic Aspects for Farmers
Authors: Durant Daphné , Farruggia Anne , Tricheur Alexandre
Published: November 2020

The common reed (Phragmites australis) has long been used in wetlands of the French Atlantic coast as fodder and bedding or roof thatching, among other uses. This article explores the practical and economic aspects of utilizing common reed for housing suckler cows compared to straw. Based on a study conducted over two years on a research farm of the French National Research Institute for Agriculture, Food and the Environment (INRAE), located in the marshes of Rochefort-sur-Mer, we show that reed is a good alternative to cereal straw and its cost is quite competitive compared to straw; the closer the reed bed is to the farm, the more competitive it is. By mobilizing the concept of restoration of natural capital, we lay the foundations for a debate on a possible revival of this ancient practice, with the idea that ecological restoration of reed beds can benefit biodiversity and the economy of wetlands farms.
A Satellite-Based High-Resolution (1-km) Ambient PM2.5 Database for India over Two Decades (2000–2019): Applications for Air Quality Management
Authors: Dey Sagnik , Purohit Bhavesh , Balyan Palak , Dixit Kuldeep , Bali Kunal , Kumar Alok , Imam Fahad , Chowdhury Sourangsu , Ganguly Dilip , Gargava Prashant , Shukla V. K.
Published: November 2020

Fine particulate matter (PM2.5) is a major criteria pollutant affecting the environment, health and climate. In India where ground-based measurements of PM2.5 is scarce, it is important to have a long-term database at a high spatial resolution for an efficient air quality management plan. Here we develop and present a high-resolution (1-km) ambient PM2.5 database spanning two decades (2000–2019) for India. We convert aerosol optical depth from Moderate Resolution Imaging Spectroradiometer (MODIS) retrieved by Multiangle Implementation of Atmospheric Correction (MAIAC) algorithm to surface PM2.5 using a dynamic scaling factor from Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) data. The satellite-derived daily (24-h average) and annual PM2.5 show a R2 of 0.8 and 0.97 and root mean square error of 25.7 and 7.2 μg/m3, respectively against surface measurements from the Central Pollution Control Board India network. Population-weighted 20-year averaged PM2.5 over India is 57.3 μg/m3 (5–95 percentile ranges: 16.8–86.9) with a larger increase observed in the present decade (2010–2019) than in the previous decade (2000 to 2009). Poor air quality across the urban–rural transact suggests that this is a regional scale problem, a fact that is often neglected. The database is freely disseminated through a web portal ‘satellite-based application for air quality monitoring and management at a national scale’ (SAANS) for air quality management, epidemiological research and mass awareness.
An Accurate Vegetation and Non-Vegetation Differentiation Approach Based on Land Cover Classification
Authors: Kwan Chiman , Gribben David , Ayhan Bulent , Li Jiang , Bernabe Sergio , Plaza Antonio
Published: November 2020

Accurate vegetation detection is important for many applications, such as crop yield estimation, land cover land use monitoring, urban growth monitoring, drought monitoring, etc. Popular conventional approaches to vegetation detection incorporate the normalized difference vegetation index (NDVI), which uses the red and near infrared (NIR) bands, and enhanced vegetation index (EVI), which uses red, NIR, and the blue bands. Although NDVI and EVI are efficient, their accuracies still have room for further improvement. In this paper, we propose a new approach to vegetation detection based on land cover classification. That is, we first perform an accurate classification of 15 or more land cover types. The land covers such as grass, shrub, and trees are then grouped into vegetation and other land cover types such as roads, buildings, etc. are grouped into non-vegetation. Similar to NDVI and EVI, only RGB and NIR bands are needed in our proposed approach. If Laser imaging, Detection, and Ranging (LiDAR) data are available, our approach can also incorporate LiDAR in the detection process. Results using a well-known dataset demonstrated that the proposed approach is feasible and achieves more accurate vegetation detection than both NDVI and EVI. In particular, a Support Vector Machine (SVM) approach performed 6% better than NDVI and 50% better than EVI in terms of overall accuracy (OA).
Correction: Doke, R., et al. Very Local Subsidence near the Hot Spring Region in Hakone Volcano, Japan, Inferred from InSAR Time Series Analysis of ALOS/PALSAR Data. Remote Sens. 2020, 12, 2842
Authors: Doke Ryosuke , Kikugawa George , Itadera Kazuhiro
Published: November 2020

The authors wish to make the following corrections to this paper [...]
A Sensor Fusion Method for Pose Estimation of C-Legged Robots
Authors: De León Jorge , Cebolla Raúl , Barrientos Antonio
Published: November 2020

In this work the authors present a novel algorithm for estimating the odometry of “C” legged robots with compliant legs and an analysis to estimate the pose of the robot. Robots with “C” legs are an alternative to wheeled and tracked robots for overcoming obstacles that can be found in different scenarios like stairs, debris, etc. Therefore, this kind of robot has become very popular for its locomotion capabilities, but at this point these robots do not have developed algorithms to implement autonomous navigation. With that objective in mind, the authors present a novel algorithm using the encoders of the legs to improve the estimation of the robot localization together with other sensors. Odometry is necessary for using some algorithms like the Extended Kalman Filter, which is used for some autonomous navigation algorithms. Due to the flexible properties of the “C” legs and the localization of the rotational axis, obtaining the displacement at every step is not as trivial as in a wheeled robot; to solve those complexities, the algorithm presented in this work makes a linear approximation of the leg compressed instead of calculating in each iteration the mechanics of the leg using finite element analysis, so the calculus level is reduced. Furthermore, the algorithm was tested in simulations and with a real robot. The results obtained in the tests are promising and together with the algorithm and fusion sensor can be used to endow the robots with autonomous navigation.
Multi-Object Tracking Algorithm for RGB-D Images Based on Asymmetric Dual Siamese Networks
Authors: Zhang Wen-Li , Yang Kun , Xin Yi-Tao , Zhao Ting-Song
Published: November 2020

Currently, intelligent security systems are widely deployed in indoor buildings to ensure the safety of people in shopping malls, banks, train stations, and other indoor buildings. Multi-Object Tracking (MOT), as an important component of intelligent security systems, has received much attention from many researchers in recent years. However, existing multi-objective tracking algorithms still suffer from trajectory drift and interruption problems in crowded scenes, which cannot provide valuable data for managers. In order to solve the above problems, this paper proposes a Multi-Object Tracking algorithm for RGB-D images based on Asymmetric Dual Siamese networks (ADSiamMOT-RGBD). This algorithm combines appearance information from RGB images and target contour information from depth images. Furthermore, the attention module is applied to repress the redundant information in the combined features to overcome the trajectory drift problem. We also propose a trajectory analysis module, which analyzes whether the head movement trajectory is correct in combination with time-context information. It reduces the number of human error trajectories. The experimental results show that the proposed method in this paper has better tracking quality on the MICC, EPFL, and UMdatasets than the previous work.
Wireless Sensor Network in Agriculture: Model of Cyber Security
Authors: Prodanović Radomir , Rančić Dejan , Vulić Ivan , Zorić Nenad , Bogićević Dušan , Ostojić Gordana , Sarang Sohail , Stankovski Stevan
Published: November 2020

Nowadays, wireless sensor networks (WSN) are widely used in agriculture monitoring to improve the quality and productivity of farming. In this application, sensors gather different types of data (i.e., humidity, carbon dioxide level, and temperature) in real-time scenarios. Thus, data gathering, transmission, and rapid response to new circumstances require a secured data mechanism to avoid malicious adversaries. Therefore, this paper focuses on data security from the data origin source to the end-user, and proposes a general data security model that is independent of the network topology and structure, and can be widely used in the agriculture monitoring application. The developed model considers practical aspects, the architecture of the sensor node, as well as the necessity to save energy while ensuring data security, and optimize the model through the application of organizational and technical measures. The model evaluation is conducted through simulation in terms of energy consumption. The result shows that the proposed model ensures good data security at the cost of a slight increase in energy consumption at receiver and sender nodes, and energy consumption per bit, up to 2%, 7%, and 1.3%, respectively, due to overhead added for authentication in the network.
Deep-Learning-Based Detection of Infants with Autism Spectrum Disorder Using Auto-Encoder Feature Representation
Authors: Lee Jung Hyuk , Lee Geon Woo , Bong Guiyoung , Yoo Hee Jeong , Kim Hong Kook
Published: November 2020

Autism spectrum disorder (ASD) is a developmental disorder with a life-span disability. While diagnostic instruments have been developed and qualified based on the accuracy of the discrimination of children with ASD from typical development (TD) children, the stability of such procedures can be disrupted by limitations pertaining to time expenses and the subjectivity of clinicians. Consequently, automated diagnostic methods have been developed for acquiring objective measures of autism, and in various fields of research, vocal characteristics have not only been reported as distinctive characteristics by clinicians, but have also shown promising performance in several studies utilizing deep learning models based on the automated discrimination of children with ASD from children with TD. However, difficulties still exist in terms of the characteristics of the data, the complexity of the analysis, and the lack of arranged data caused by the low accessibility for diagnosis and the need to secure anonymity. In order to address these issues, we introduce a pre-trained feature extraction auto-encoder model and a joint optimization scheme, which can achieve robustness for widely distributed and unrefined data using a deep-learning-based method for the detection of autism that utilizes various models. By adopting this auto-encoder-based feature extraction and joint optimization in the extended version of the Geneva minimalistic acoustic parameter set (eGeMAPS) speech feature data set, we acquire improved performance in the detection of ASD in infants compared to the raw data set.