bluuebunny/crossref_metadata_2025 huggingface dataset:
A Highly Active Chimeric Lysin with a Calcium-Enhanced Bactericidal Activity against Staphylococcus aureus In Vitro and In Vivo
Authors: Li Xiaohong , Wang Shujuan , Nyaruaba Raphael , Liu Huan , Yang Hang , Wei Hongping
Published: April 2021

Lysins, including chimeric lysins, have recently been explored as novel promising alternatives to failing antibiotics in treating multi-drug resistant (MDR) pathogens, including methicillin-resistant Staphylococcus aureus (MRSA). Herein, by fusing the CHAP (cysteine, histidine-dependent amidohydrolase/peptidase) catalytic domain from the Ply187 lysin with the non-SH3b cell-wall binding domain from the LysSA97 lysin, a new chimeric lysin ClyC was constructed with Ca2+-enhanced bactericidal activity against all S. aureus strains tested, including MRSA. Notably, treating S. aureus with 50 μg/mL of ClyC in the presence of 100 μM Ca2+ lead to a reduction of 9 Log10 (CFU/mL) in viable bacterial number, which was the first time to observe a lysin showing such a high activity. In addition, the effective concentration of ClyC could be decreased dramatically from 12 to 1 μg/mL by combination with 0.3 μg/mL of penicillin G. In a mouse model of S. aureus bacteremia, a single intraperitoneal administration of 0.1 mg/mouse of ClyC significantly improved the survival rates and reduced 2 Log10 (CFU/mL) of the bacterial burdens in the organs of the infected mice. ClyC was also found stable after lyophilization without cryoprotectants. Based on the above observations, ClyC could be a promising candidate against S. aureus infections.
Nitric Oxide Regulates Plant Growth, Physiology, Antioxidant Defense, and Ion Homeostasis to Confer Salt Tolerance in the Mangrove Species, Kandelia obovata
Authors: Hasanuzzaman Mirza , Inafuku Masashi , Nahar Kamrun , Fujita Masayuki , Oku Hirosuke
Published: April 2021

Facultative halophyte Kandelia obovata plants were exposed to mild (1.5% NaCl) and severe (3% NaCl) salt stress with or without sodium nitroprusside (SNP; 100 µM; a NO donor), hemoglobin (Hb, 100 µM; a NO scavenger), or Nω-nitro-L-arginine methyl ester (L-NAME, 100 µM; a NO synthase inhibitor). The plants were significantly affected by severe salt stress. They showed decreases in seedling growth, stomatal conductance, intercellular CO2 concentration, SPAD value, photosynthetic rate, transpiration rate, water use efficiency, and disrupted antioxidant defense systems, overproduction of reactive oxygen species, and visible oxidative damage. Salt stress also induced ion toxicity and disrupted nutrient homeostasis, as indicated by elevated leaf and root Na+ contents, decreased K+ contents, lower K+/Na+ ratios, and decreased Ca contents while increasing osmolyte (proline) levels. Treatment of salt-stressed plants with SNP increased endogenous NO levels, reduced ion toxicity, and improved nutrient homeostasis while further increasing Pro levels to maintain osmotic balance. SNP treatment also improved gas exchange parameters and enhanced antioxidant enzymes’ activities (catalase, ascorbate peroxidase, monodehydroascorbate reductase, and dehydroascorbate reductase). Treatment with Hb and l-NAME reversed these beneficial SNP effects and exacerbated salt damage, confirming that SNP promoted stress recovery and improved plant growth under salt stress.
Differential and Overlapping Effects of Melatonin and Its Metabolites on Keratinocyte Function: Bioinformatics and Metabolic Analyses
Authors: Stefan Joanna , Kim Tae-Kang , Schedel Fiona , Janjetovic Zorica , Crossman David K. , Steinbrink Kerstin , Slominski Radomir M. , Zmijewski Jaroslaw , Tulic Meri K. , Reiter Russel J. , Kleszczyński Konrad , Slominski Andrzej T.
Published: April 2021

We investigated the effects of melatonin and its selected metabolites, i.e., N1-Acetyl-N2-formyl-5-methoxykynurenamine (AFMK) and 6-hydroxymelatonin (6(OH)Mel), on cultured human epidermal keratinocytes (HEKs) to assess their homeostatic activities with potential therapeutic implications. RNAseq analysis revealed a significant number of genes with distinct and overlapping patterns, resulting in common regulation of top diseases and disorders. Gene Set Enrichment Analysis (GSEA), Reactome FIViZ, and Ingenuity Pathway Analysis (IPA) showed overrepresentation of the p53-dependent G1 DNA damage response gene set, activation of p53 signaling, and NRF2-mediated antioxidative pathways. Additionally, GSEA exhibited an overrepresentation of circadian clock and antiaging signaling gene sets by melatonin derivatives and upregulation of extension of telomere signaling in HEKs, which was subsequently confirmed by increased telomerase activity in keratinocytes, indicating possible antiaging properties of metabolites of melatonin. Furthermore, Gene Ontology (GO) showed the activation of a keratinocyte differentiation program by melatonin, and GSEA indicated antitumor and antilipidemic potential of melatonin and its metabolites. IPA also indicated the role of Protein Kinase R (PKR) in interferon induction and antiviral response. In addition, the test compounds decreased lactate dehydrogenase A (LDHA) and lactate dehydrogenase C (LDHC) gene expression. These results were validated by qPCR and by Seahorse metabolic assay with significantly decreased glycolysis and lactate production under influence of AFMK or 6(OH)Mel in cells with a low oxygen consumption rate. In summary, melatonin and its metabolites affect keratinocytes’ functions via signaling pathways that overlap for each tested molecule with some distinctions.
A Mobile Service Robot Global Path Planning Method Based on Ant Colony Optimization and Fuzzy Control
Authors: Tao Yong , Gao He , Ren Fan , Chen Chaoyong , Wang Tianmiao , Xiong Hegen , Jiang Shan
Published: April 2021

A global path planning method is proposed based on improved ant colony optimization according to the slow convergence speed in mobile service robot path planning. The distribution of initial pheromone is determined by the critical obstacle influence factor. The influence factor is introduced into the heuristic information to improve the convergence speed of the algorithm at an early stage. A new pheromone update rule is presented using fuzzy control to change the value of pheromone heuristic factor and expectation heuristic factor, adjusting the evaporation rate in stages. The method achieves fast convergence and guarantees global search capability. Finally, the simulation results show that the improved algorithm not only shortens the running time of global path planning, but also has a higher probability of obtaining a global optimal solution. The convergence speed of the algorithm is better than the traditional ant colony algorithm.
The Biocompatibility of Wireless Power Charging System on Human Neural Cells
Authors: Skovierova Henrieta , Pavelek Miroslav , Okajcekova Terezia , Palesova Janka , Strnadel Jan , Spanik Pavol , Halašová Erika , Frivaldsky Michal
Published: April 2021

The progress in technology and science leads to the invention and use of many electrical devices in the daily lives of humans. In addition to that, people have been easily exposed to increased newly generated artificial electromagnetic waves. Exponential use of modern electronic devices has automatically led to increase in electromagnetic wave exposure. Therefore, we constructed the prototype of wireless power charging system to study the biocompatibility of electromagnetic field (EMF) generated by this system on various human cell lines. There are many studies indicating the negative bio-effect of EMF on various types of cells, such as induction of apoptosis. From the other point of view, these effects could rather be beneficial in the way, that they could eliminate the progress of various diseases or disorders. For that reason, we compared the impact of EMF (87 kHz, 0.3–1.2 mT, 30 min) on human normal as well as cancer cell lines based on morphological and cellular level. Our results suggested that EMF generated by wireless power charging systems does not have any detrimental effect on cell morphology, viability and cytoskeletal structures of human neural cells.
Storage Capacity in Dependency of Supercooling and Cycle Stability of Different PCM Emulsions
Authors: Gschwander Stefan , Niedermaier Sophia , Gamisch Sebastian , Kick Moritz , Klünder Franziska , Haussmann Thomas
Published: April 2021

Phase-change materials (PCM) play off their advantages over conventional heat storage media when used within narrow temperature ranges. Many cooling and temperature buffering applications, such as cold storage and battery cooling, are operated within small temperature differences, and therefore, they are well-suited for the application of these promising materials. In this study, the storage capacities of different phase-change material emulsions are analysed under consideration of the phase transition behaviour and supercooling effect, which are caused by the submicron size scale of the PCM particles in the emulsion. For comparison reasons, the same formulation for the emulsions was used to emulsify 35 wt.% of different paraffins with different purities and melting temperatures between 16 and 40 °C. Enthalpy curves based on differential scanning calorimeter (DSC) measurements are used to calculate the storage capacities within the characteristic and defined temperatures. The enthalpy differences for the emulsions, including the first phase transition, are in a range between 69 and 96 kJ/kg within temperature differences between 6.5 and 10 K. This led to an increase of the storage capacity by a factor of 2–2.7 in comparison to water operated within the same temperature intervals. The study also shows that purer paraffins, which have a much higher enthalpy than blends, reveal, in some cases, a lower increase of the storage capacity in the comparison due to unfavourable crystallisation behaviour when emulsified. In a second analysis, the stability of emulsions was investigated by applying 100 thermal cycles with defined mechanical stress at the same time. An analysis of the viscosity, particle size and melting crystallisation behaviour was done by showing the changes in each property due to the cycling.
Effects of a Curved Heel Shape in a Running Shoe on Biomechanical Variables and Comfort
Authors: Ryu Sihyun , Stefanyshyn Darren , Kong Sejin , Park Sang-Kyoon
Published: April 2021

(1) Background: The purpose of this study was to investigate the effects of a rounded heel shoe (RHS) and rounded lateral heel shoe (RLHS) on impact and lower extremity stability as well as their relationships with comfort during running. (2) Methods: Twenty healthy male adults participated in the study. The data were collected using eight infrared cameras while participants were running at a speed of 2.7 m/s in three shoe conditions on an instrumented treadmill. (3) Results: The peak vertical ground reaction force (PVGRF) was statistically smaller for the RHS and RLHS compared with the normal shoes (NS) (p < 0.05). The range of motion of inversion–eversion at the ankle joint was statistically smaller for the RLHS compared with the NS and RHS (p < 0.05). Increased dorsiflexion of the ankle joint at heel contact was negatively related to the comfort of a running shoe, and increased dorsi-plantarflexion ROM was positively related to comfort. (4) Conclusions: Based on these results, a curved heel shape of a running shoe may provide a positive influence on the biomechanical function and the comfort of running shoes. Future study, including measurements of lower extremity muscle activations and long-term comfort, would be beneficial to help validate current findings and develop further applications.
Convolutional Neural Networks for Differential Diagnosis of Raynaud’s Phenomenon Based on Hands Thermal Patterns
Authors: Filippini Chiara , Cardone Daniela , Perpetuini David , Chiarelli Antonio Maria , Gualdi Giulio , Amerio Paolo , Merla Arcangelo
Published: April 2021

Raynaud’s phenomenon (RP) is a microvessels’ disorder resulting in transient ischemia. It can be either primary or secondary to connective tissue diseases, such as systemic sclerosis. The differentiation between primary and secondary to systemic sclerosis is of paramount importance to set the proper therapeutic strategy. Thus far, thermal infrared imaging has been employed to accomplish this task by monitoring the finger temperature response to a controlled cold challenge. A completely automated methodology based on deep convolutional neural network is here introduced with the purpose of being able to differentiate systemic sclerosis from primary RP patients by relying uniquely on thermal images of the hands acquired at rest. The classification performance of such a method was compared to that of a three-dimensional convolutional neural network model implemented to classify thermal images of the hands recorded during rewarming from a cold challenge. No significant differences were found between the two procedures, thus ensuring the possibility to avoid the cold challenge. Moreover, the convolutional neural network models were compared with standard feature-based approaches and showed higher performances, thus overcoming the limitations related to the feature extraction (e.g., biases introduced by the operator). Such automated procedures can constitute promising tools for large scale screening of primary RP and secondary to systemic sclerosis in clinical practice.
Analysis of Tunnel Water Inrush Considering the Influence of Surrounding Rock Permeability Coefficient by Excavation Disturbance and Ground Stress
Authors: Fu Helin , An Pengtao , Chen Long , Cheng Guowen , Li Jie , Yu Xiaohui
Published: April 2021

Affected by the coupling of excavation disturbance and ground stress, the heterogeneity of surrounding rock is very common. Presently, treating the permeability coefficient as a fixed value will reduce the prediction accuracy of the water inflow and the external water pressure of the structure, leading to distortion of the prediction results. Aiming at this problem, this paper calculates and analyzes tunnel water inflow when considering the heterogeneity of permeability coefficient of surrounding rock using a theoretical analysis method, and compares with field data, and verifies the rationality of the formula. The research shows that, when the influence of excavation disturbance and ground stress on the permeability coefficient of surrounding rock is ignored, the calculated value of the external water force of the tunnel structure is too small, and the durability and stability of the tunnel are reduced, which is detrimental to the safety of the structure. Considering the heterogeneity of surrounding rock, the calculation error of water inflow can be reduced from 27.3% to 13.2%, which improves the accuracy of water inflow prediction to a certain extent.
Surface Exposure Technology of Metal Powder Based on an Optically-Addressed Liquid Crystal Spatial Light Modulator
Authors: Cai Ying , Huang Dajie , Cheng He , Xia Gang , Fan Wei
Published: April 2021

Compared with the current mature point scanning metal additive manufacturing technology, the surface exposure technology by laser additive manufacturing can accelerate the construction speed, and the short pulse laser is expected to improve the resolution. Here, a surface exposure technology processing system was constructed based on a nanosecond pulsed laser source and an optically-addressed liquid crystal spatial light modulator with a damage threshold higher than 500 mJ/cm2. The resolution of the surface exposure processing system is proved to be about 100 μm.
Multi-Scale Safety Helmet Detection Based on SAS-YOLOv3-Tiny
Authors: Cheng Rao , He Xiaowei , Zheng Zhonglong , Wang Zhentao
Published: April 2021

In the practical application scenarios of safety helmet detection, the lightweight algorithm You Only Look Once (YOLO) v3-tiny is easy to be deployed in embedded devices because its number of parameters is small. However, its detection accuracy is relatively low, which is why it is not suitable for detecting multi-scale safety helmets. The safety helmet detection algorithm (named SAS-YOLOv3-tiny) is proposed in this paper to balance detection accuracy and model complexity. A light Sandglass-Residual (SR) module based on depthwise separable convolution and channel attention mechanism is constructed to replace the original convolution layer, and the convolution layer of stride two is used to replace the max-pooling layer for obtaining more informative features and promoting detection performance while reducing the number of parameters and computation. Instead of two-scale feature prediction, three-scale feature prediction is used here to improve the detection effect about small objects further. In addition, an improved spatial pyramid pooling (SPP) module is added to the feature extraction network to extract local and global features with rich semantic information. Complete-Intersection over Union (CIoU) loss is also introduced in this paper to improve the loss function for promoting positioning accuracy. The results on the self-built helmet dataset show that the improved algorithm is superior to the original algorithm. Compared with the original YOLOv3-tiny, the SAS-YOLOv3-tiny has significantly improved all metrics (including Precision (P), Recall (R), Mean Average Precision (mAP), F1) at the expense of only a minor speed while keeping fewer parameters and amounts of calculation. Meanwhile, the SAS-YOLOv3-tiny algorithm shows advantages in accuracy compared with lightweight object detection algorithms, and its speed is faster than the heavyweight model.
Multifunctional Activities of Gold Nanoparticles Biosynthesized Using Bacteria Isolated from Mining Areas
Authors: Chen Chih-Yu , Chang Yung-Chu , Tsai Teh-Hua , Liu Man-Hai , Chung Ying-Chien
Published: April 2021

Research on gold nanoparticles (AuNPs) has often focused on their physical, chemical, and crystalline characteristics. Commercial AuNPs have been applied in the diverse fields of biomedicine, catalysis, photovoltaics, and sensing. In this study, we explored the various activities of AuNPs to widen their applicability. This paper presents a simple and rapid synthesis process of AuNPs with bacteria isolated from a gold mining area. We also investigated the optimization of reaction parameters for AuNP synthesis. The study results revealed that among the isolated strains, Bifidobacterium lactis and Escherichia coli demonstrated the highest capabilities of AuNP synthesis. The optimal pH values for AuNP synthesis by B. lactis (BLAuNPs) and E. coli (ECAuNPs) were 5.0 for 72 h of incubation and 8.0 for 24 h of incubation. The average particle sizes of ECAuNPs and BLAuNPs were 4.2 and 5.6 nm, respectively. Furthermore, these biogenic AuNPs were found to be stable with no aggregation after 3 months of storage. BLAuNPs and ECAuNPs exhibited high levels of antimicrobial, antioxidant, photocatalytic, and antityrosinase activity. Moreover, they were noncytotoxic to skin cells even at 100% melanin inhibitory concentrations. Considering the demonstrated multifunctional activities of AuNPs, BLAuNPs and ECAuNPs have promising potential for commercialization.
Image-Guided Endoscopic Sinus Surgery with 3D Volumetric Visualization of the Nasal Cavity and Paranasal Sinuses: A Clinical Comparative Study
Authors: Lee Sang-Jeong , Yoo Ji-Yong , Yoo Sung-Keun , Ha Ryun , Lee Dong-Hyuk , Kim Seon-Tae , Yi Won-Jin
Published: April 2021

(1) Background: The purpose of this study was to develop an image-guided endoscopic sinus surgery (IGESS) system, named Medigator®, based on the leave-one-out registration strategy and three-dimensional (3D) volumetric visualization of the nasal cavity and paranasal sinuses. (2) Methods: A phantom was designed and fabricated using a 3D printer. We then performed a phantom-based accuracy evaluation to validate the performance of the developed registration method. We included 11 patients who underwent IGESS for clinical study to compare the performance of the developed IGESS system with that of a commercialized system. (3) Results: The fiducial registration error (FRE) was 0.14 mm, and the target registration error (TRE) was 0.82 ± 0.50 mm by the phantom-based evaluation. As a result of the clinical comparative study, the average registration times were 36.04 ± 4.7 and 89.35 ± 26.1 s for the developed and commercialized systems, respectively (p < 0.05). The image loading time of the developed system was also shorter than that of the commercialized system (p < 0.05). The average accuracy score of the developed system was not significantly different from that of the commercialized system (p > 0.05). (4) Conclusions: The developed system provided an accurate point-to-point registration method based on the leave-one-out strategy. According to the results of the clinical comparative study, we demonstrated that the developed system showed reliable potential for clinical application.
Mann-Type Inertial Subgradient Extragradient Rules for Variational Inequalities and Common Fixed Points of Nonexpansive and Quasi-Nonexpansive Mappings
Authors: Ceng Lu-Chuan , Yao Jen-Chih
Published: April 2021

Suppose that in a real Hilbert space H, the variational inequality problem with Lipschitzian and pseudomonotone mapping A and the common fixed-point problem of a finite family of nonexpansive mappings and a quasi-nonexpansive mapping with a demiclosedness property are represented by the notations VIP and CFPP, respectively. In this article, we suggest two Mann-type inertial subgradient extragradient iterations for finding a common solution of the VIP and CFPP. Our iterative schemes require only calculating one projection onto the feasible set for every iteration, and the strong convergence theorems are established without the assumption of sequentially weak continuity for A. Finally, in order to support the applicability and implementability of our algorithms, we make use of our main results to solve the VIP and CFPP in two illustrating examples.
Ancient Immunity. Phylogenetic Emergence of Recognition-Defense Mechanisms
Authors: Ballarin Loriano , Cammarata Matteo , Luporini Pierangelo
Published: April 2021

Although still scarcely considered by the majority of the biomedical world, invertebrates have greatly contributed to the elucidation of fundamental biological problems [...]
Exploration of Galectin Ligands Displayed on Gram-Negative Respiratory Bacterial Pathogens with Different Cell Surface Architectures
Authors: Campanero-Rhodes María A. , Kalograiaki Ioanna , Euba Begoña , Llobet Enrique , Ardá Ana , Jiménez-Barbero Jesús , Garmendia Junkal , Solís Dolores
Published: April 2021

Galectins bind various pathogens through recognition of distinct carbohydrate structures. In this work, we examined the binding of four human galectins to the Gram-negative bacteria Klebsiella pneumoniae (Kpn) and non-typeable Haemophilus influenzae (NTHi), which display different surface glycans. In particular, Kpn cells are covered by a polysaccharide capsule and display an O-chain-containing lipopolysaccharide (LPS), whereas NTHi is not capsulated and its LPS, termed lipooligosacccharide (LOS), does not contain O-chain. Binding assays to microarray-printed bacteria revealed that galectins-3, -4, and -8, but not galectin-1, bind to Kpn and NTHi cells, and confocal microscopy attested binding to bacterial cells in suspension. The three galectins bound to array-printed Kpn LPS. Moreover, analysis of galectin binding to mutant Kpn cells evidenced that the O-chain is the docking point for galectins on wild type Kpn. Galectins-3, -4, and -8 also bound the NTHi LOS. Microarray-assisted comparison of the binding to full-length and truncated LOSs, as well as to wild type and mutant cells, supported LOS involvement in galectin binding to NTHi. However, deletion of the entire LOS oligosaccharide chain actually increased binding to NTHi cells, indicating the availability of other ligands on the bacterial surface, as similarly inferred for Kpn cells devoid of both O-chain and capsule. Altogether, the results illustrate galectins’ versatility for recognizing different bacterial structures, and point out the occurrence of so far overlooked galectin ligands on bacterial surfaces.
Regulation of Phosphoinositide Levels in the Retina by Protein Tyrosine Phosphatase 1B and Growth Factor Receptor-Bound Protein 14
Authors: Rajala Raju V. S. , McCauley Austin , Rajala Rahul , Teel Kenneth , Rajala Ammaji
Published: April 2021

Protein tyrosine kinases and protein phosphatases play a critical role in cellular regulation. The length of a cellular response depends on the interplay between activating protein kinases and deactivating protein phosphatases. Protein tyrosine phosphatase 1B (PTP1B) and growth factor receptor-bound protein 14 (Grb14) are negative regulators of receptor tyrosine kinases. However, in the retina, we have previously shown that PTP1B inactivates insulin receptor signaling, whereas phosphorylated Grb14 inhibits PTP1B activity. In silico docking of phosphorylated Grb14 and PTP1B indicate critical residues in PTP1B that may mediate the interaction. Phosphoinositides (PIPs) are acidic lipids and minor constituents in the cell that play an important role in cellular processes. Their levels are regulated by growth factor signaling. Using phosphoinositide binding protein probes, we observed increased levels of PI(3)P, PI(4)P, PI(3,4)P2, PI(4,5)P2, and PI(3,4,5)P3 in PTP1B knockout mouse retina and decreased levels of these PIPs in Grb14 knockout mouse retina. These observations suggest that the interplay between PTP1B and Grb14 can regulate PIP metabolism.
Bromodomain and Extraterminal Protein Inhibitor, Apabetalone (RVX-208), Reduces ACE2 Expression and Attenuates SARS-Cov-2 Infection In Vitro
Authors: Gilham Dean , Smith Audrey L. , Fu Li , Moore Dalia Y. , Muralidharan Abenaya , Reid St. Patrick M. , Stotz Stephanie C. , Johansson Jan O. , Sweeney Michael , Wong Norman C. W. , Kulikowski Ewelina , El-Gamal Dalia
Published: April 2021

Effective therapeutics are urgently needed to counter infection and improve outcomes for patients suffering from COVID-19 and to combat this pandemic. Manipulation of epigenetic machinery to influence viral infectivity of host cells is a relatively unexplored area. The bromodomain and extraterminal (BET) family of epigenetic readers have been reported to modulate SARS-CoV-2 infection. Herein, we demonstrate apabetalone, the most clinical advanced BET inhibitor, downregulates expression of cell surface receptors involved in SARS-CoV-2 entry, including angiotensin-converting enzyme 2 (ACE2) and dipeptidyl-peptidase 4 (DPP4 or CD26) in SARS-CoV-2 permissive cells. Moreover, we show that apabetalone inhibits SARS-CoV-2 infection in vitro to levels comparable to those of antiviral agents. Taken together, our study supports further evaluation of apabetalone to treat COVID-19, either alone or in combination with emerging therapeutics.
Effective Separation of Prime Olefins from Gas Stream Using Anion Pillared Metal Organic Frameworks: Ideal Adsorbed Solution Theory Studies, Cyclic Application and Stability
Authors: Khraisheh Majeda , Almomani Fares , Walker Gavin
Published: April 2021

The separation of C3H4/C3H6 is one of the most energy intensive and challenging operations, requiring up to 100 theoretical stages, in traditional cryogenic distillation. In this investigation, the potential application of two MOFs (SIFSIX-3-Ni and NbOFFIVE-1-Ni) was tested by studying the adsorption-desorption behaviors at a range of operational temperatures (300–360 K) and pressures (1–100 kPa). Dynamic adsorption breakthrough tests were conducted and the stability and regeneration ability of the MOFs were established after eight consecutive cycles. In order to establish the engineering key parameters, the experimental data were fitted to four isotherm models (Langmuir, Freundlich, Sips and Toth) in addition to the estimation of the thermodynamic properties such as the isosteric heats of adsorption. The selectivity of the separation was tested by applying ideal adsorbed solution theory (IAST). The results revealed that SIFSIX-3-Ni is an effective adsorbent for the separation of 10/90 v/v C3H4/C3H6 under the range of experimental conditions used in this study. The maximum adsorption reported for the same combination was 3.2 mmol g−1. Breakthrough curves confirmed the suitability of this material for the separation with a 10-min gab before the lighter C3H4 is eluted from the column. The separated C3H6 was obtained with a 99.98% purity.
Microbial Removal of Pb(II) Using an Upflow Anaerobic Sludge Blanket (UASB) Reactor
Authors: Chimhundi Jeremiah , Hörstmann Carla , Chirwa Evans M. N. , Brink Hendrik G.
Published: April 2021

The main objective of this study was to achieve the continuous biorecovery and bioreduction of Pb(II) using an industrially obtained consortia as a biocatalyst. An upflow anaerobic sludge blanket reactor was used in the treatment process. The bioremediation technique that was applied made use of a yeast extract as the microbial substrate and Pb(NO3)2 as the source of Pb(II). The UASB reactor exhibited removal efficiencies of between 90 and 100% for the inlet Pb concentrations from 80 to 2000 ppm and a maximum removal rate of 1948.4 mg/(L·d) was measured. XRD and XPS analyses of the precipitate revealed the presence of Pb0, PbO, PbS and PbSO4. Supporting experimental work carried out included growth measurements, pH, oxidation–reduction potentials and nitrate levels.
A Propagated Skeleton Approach to High Throughput Screening of Neurite Outgrowth for In Vitro Parkinson’s Disease Modelling
Authors: Schikora Justus , Kiwatrowski Nina , Förster Nils , Selbach Leonie , Ostendorf Friederike , Pallapies Frida , Hasse Britta , Metzdorf Judith , Gold Ralf , Mosig Axel , Tönges Lars
Published: April 2021

Neuronal models of neurodegenerative diseases such as Parkinson’s Disease (PD) are extensively studied in pathological and therapeutical research with neurite outgrowth being a core feature. Screening of neurite outgrowth enables characterization of various stimuli and therapeutic effects after lesion. In this study, we describe an autonomous computational assay for a high throughput skeletonization approach allowing for quantification of neurite outgrowth in large data sets from fluorescence microscopic imaging. Development and validation of the assay was conducted with differentiated SH-SY5Y cells and primary mesencephalic dopaminergic neurons (MDN) treated with the neurotoxic lesioning compound Rotenone. Results of manual annotation using NeuronJ and automated data were shown to correlate strongly (R2-value 0.9077 for SH-SY5Y cells and R2-value 0.9297 for MDN). Pooled linear regressions of results from SH-SY5Y cell image data could be integrated into an equation formula (y=0.5410·x+1792; y=0.8789·x+0.09191 for normalized results) with y depicting automated and x depicting manual data. This automated neurite length algorithm constitutes a valuable tool for modelling of neurite outgrowth that can be easily applied to evaluate therapeutic compounds with high throughput approaches.
Neurobiological Processes Induced by Aerobic Exercise through the Endocannabinoidome
Authors: Forteza Fabiola , Giorgini Giada , Raymond Frédéric
Published: April 2021

Evidence suggesting the triangulation of the endocannabinoid system, exercise, and neurological health is emerging. In addition to the endocannabinoids N-arachidonoylethanolamine (anandamide; AEA) and 2-arachidonoylglycerol (2-AG), the expanded endocannabinoid system, known as the endocannabinoidome (eCBome), appears to be an important player in this relationship. The eCBome includes several endocannabinoid-like mediators such as N-acylethanolamines and 2-monoacylglycerols, the enzymes involved in their biosynthesis and degradation, and the receptors they affect. This review aims to relate the functional interactions between aerobic exercise, and the molecular and cellular pathways related to endocannabinoids, in the hypothalamus, hippocampus, and the periphery, with special attention given to associations with emotional state, cognition, and mental health. Given the well-documented roles of many eCBome members in regulating stress and neurological processes, we posit that the eCBome is an important effector of exercise-induced central and peripheral adaptive mechanisms that benefit mental health. Gut microbiota imbalance, affecting the gut-brain axis and metabolism, also influences certain eCBome-modulated inflammation pathways. The integrity of the gut microbiota could thus be crucial in the onset of neuroinflammation and mental conditions. Further studies on how the modulation by exercise of the peripheral eCBome affects brain functions could reveal to be key elements in the prevention and treatment of neuropsychological disorders.
On the Breaking of the Milankovitch Cycles Triggered by Temperature Increase: The Stochastic Resonance Response
Authors: Caccamo Maria Teresa , Magazù Salvatore
Published: April 2021

Recent decades have registered the hottest temperature variation in instrumentally recorded data history. The registered temperature rise is particularly significant in the so-called hot spot or sentinel regions, characterized by higher temperature increases in respect to the planet average value and by more marked connected effects. In this framework, in the present work, following the climate stochastic resonance model, the effects, due to a temperature increase independently from a specific trend, connected to the 105 year Milankovitch cycle were tested. As a result, a breaking scenario induced by global warming is forecasted. More specifically, a wavelet analysis, innovatively performed with different sampling times, allowed us, besides to fully characterize the cycles periodicities, to quantitatively determine the stochastic resonance conditions by optimizing the noise level. Starting from these system resonance conditions, numerical simulations for increasing planet temperatures have been performed. The obtained results show that an increase of the Earth temperature boosts a transition towards a chaotic regime where the Milankovitch cycle effects disappear. These results put into evidence the so-called threshold effect, namely the fact that also a small temperature increase can give rise to great effects above a given threshold, furnish a perspective point of view of a possible future climate scenario, and provide an account of the ongoing registered intensity increase of extreme meteorological events.
Characterising Supramolecular Architectures in Crystals Featuring I⋯Br Halogen Bonding: Persistence of X⋯X’ Secondary-Bonding in Their Congeners
Authors: Tiekink Edward R. T.
Published: April 2021

The Cambridge Structural Database was surveyed for crystals featuring I⋯Br secondary-bonding in their supramolecular assemblies occurring independently of other obvious supramolecular synthons and devoid of other halogen bonding interactions. In all, 41 crystals satisfied these criteria, with nine examples of zero-dimensional aggregation (uniformly two-molecule aggregates) and 30 one-dimensional chains of varying topology (linear, zigzag and helical). There is one example each of two- and three-dimensional patterns. Type-I, type-II and intermediate bonding situations are apparent; for type-II bonding, the ratio of iodide:bromide functioning as the electrophile is 2:1. Most molecules participated, on average, in one I⋯Br contact, although smaller numbers of half (zero-dimensional) or two contacts (two- and three-dimensional) were observed. The propensity of the formation of related halogen bonding interactions in congeners of the 41 investigated crystals was also studied. Congeners were apparent for 11 crystals, with seven of these exhibiting isostructural relationships, in terms of space-group symmetry and unit-cell parameters. Isostructural relationships do not ensure the formation of analogous aggregation patterns, particularly and in accord with expectation, for the lighter halides. When formed, often distinct aggregation patterns are observed despite the isostructural relationships. Hetero-atomic halogen bonding offers surprises and opportunities in crystal engineering endeavours.
Modelling Reliability Characteristics of Technical Equipment of Local Area Computer Networks
Authors: Teslyuk Vasyl , Sydor Andriy , Karovič Vincent , Pavliuk Olena , Kazymyra Iryna
Published: April 2021

Technical systems in the modern global world are rapidly evolving and improving. In most cases, these are large-scale multi-level systems and one of the problems that arises in the design process of such systems is to determine their reliability. Accordingly, in the paper, a mathematical model based on the Weibull distribution has been developed for determining a computer network reliability. In order to simplify calculating the reliability characteristics, the system is considered to be a hierarchical one, ramified to level 2, with bypass through the level. The developed model allows us to define the following parameters: the probability distribution of the count of working output elements, the availability function of the system, the duration of the system’s stay in each of its working states, and the duration of the system’s stay in the prescribed availability condition. The accuracy of the developed model is high. It can be used to determine the reliability parameters of the large, hierarchical, ramified systems. The research results of modelling a local area computer network are presented. In particular, we obtained the following best option for connecting workstations: 4 of them are connected to the main hub, and the rest (16) are connected to the second level hub, with a time to failure of 4818 h.
Effective Cloud Resource Utilisation in Cloud ERP Decision-Making Process for Industry 4.0 in the United States
Authors: Marinho Marlene , Prakash Vijay , Garg Lalit , Savaglio Claudio , Bawa Seema
Published: April 2021

Cloud enterprise resource planning (C-ERP) represents an evolution of traditional ERP, which also offers the advantages of cloud computing (CC) such as ease of use and resource elasticity. This article presents the opportunities and challenges of the C-ERP adoption for industry 4.0 in the United States as well as the factors that boost or hinder such a decision. The quantitative research method is used to gather the predictor factors and correlation amongst them. An online survey questionnaire received 109 responses, mainly decision-makers and professionals from the US consumer goods industry. Statistical analysis has been carried out to rank the different levels of influence in the C-ERP adoption decision. The predictor’s complexity and regulatory compliance positively influence C-ERP private service deployment, whereas technology readiness is a good predictor of community service deployment. This paper also proposes a decision support system (DSS), tailored to industry 4.0, and aimed at assisting decision-makers in adopting C-ERP as an effective resource for decision-making. The DSS is built upon the predictors using the analytic hierarchy process (AHP) and it supports decision-makers in the selection of services and deployment models for C-ERP as a resource.
Wireless Powered Mobile Edge Computing Systems: Simultaneous Time Allocation and Offloading Policies
Authors: Irshad Amna , Abbas Ziaul Haq , Ali Zaiwar , Abbas Ghulam , Baker Thar , Al-Jumeily Dhiya
Published: April 2021

To improve the computational power and limited battery capacity of mobile devices (MDs), wireless powered mobile edge computing (MEC) systems are gaining much importance. In this paper, we consider a wireless powered MEC system composed of one MD and a hybrid access point (HAP) attached to MEC. Our objective is to achieve a joint time allocation and offloading policy simultaneously. We propose a cost function that considers both the energy consumption and the time delay of an MD. The proposed algorithm, joint time allocation and offload policy (JTAOP), is used to train a neural network for reducing the complexity of our algorithm that depends on the resolution of time and the number of components in a task. The numerical results are compared with three benchmark schemes, namely, total local computation, total offloading and partial offloading. Simulations show that the proposed algorithm performs better in producing the minimum cost and energy consumption as compared to the considered benchmark schemes.
Semi-Supervised Extreme Learning Machine Channel Estimator and Equalizer for Vehicle to Vehicle Communications
Authors: Salazar Eduardo , Azurdia-Meza Cesar A. , Zabala-Blanco David , Bolufé Sandy , Soto Ismael
Published: April 2021

Wireless vehicular communications are a promising technology. Most applications related to vehicular communications aim to improve road safety and have special requirements concerning latency and reliability. The traditional channel estimation techniques used in the IEEE 802.11 standard do not properly perform over vehicular channels. This is because vehicular communications are subject to non-stationary, time-varying, frequency-selective wireless channels. Therefore, the main goal of this work is the introduction of a new channel estimation and equalization technique based on a Semi-supervised Extreme Learning Machine (SS-ELM) in order to address the harsh characteristics of the vehicular channel and improve the performance of the communication link. The performance of the proposed technique is compared with traditional estimators, as well as state-of-the-art machine-learning-based algorithms over an urban scenario setup in terms of bit error rate. The proposed SS-ELM scheme outperformed the extreme learning machine and the fully complex extreme learning machine algorithms for the evaluated scenarios. Compared to traditional techniques, the proposed SS-ELM scheme has a very similar performance. It is also observed that, although the SS-ELM scheme requires the largest operation time among the evaluated techniques, its execution time is still far away from the latency requirements specified by the standard for safety applications.
Polarization-Encoded Fully-Phase Encryption Using Transport-of-Intensity Equation
Authors: Gupta Alok K. , Kumar Praveen , Nishchal Naveen K. , Alfalou Ayman
Published: April 2021

In this study, we propose a novel method to encrypt fully-phase information combining the concepts of the transport of intensity equation and spatially variant polarization encoding. The transport of intensity equation is a non-iterative and non-interferometric phase-retrieval method which recovers the phase information from defocused intensities. Spatially variant polarization encoding employs defocused intensity measurements. The proposed cryptosystem uses a two-step optical experimentation process—primarily, a simple set-up for defocused intensities recording for phase retrieval and then a set-up for encoding. Strong security, convenient intensity-based measurements, and noise-free decryption are the main features of the proposed method. The simulation results have been presented in support of the proposed idea. However, the TIE section of the cryptosystem, as of now, has been experimentally demonstrated for micro-lens.
A Multi-Objective Approach toward Optimal Design of Sustainable Integrated Biodiesel/Diesel Supply Chain Based on First- and Second-Generation Feedstock with Solid Waste Use
Authors: Ganev Evgeniy , Ivanov Boyan , Vaklieva-Bancheva Natasha , Kirilova Elisaveta , Dzhelil Yunzile
Published: April 2021

This study proposes a multi-objective approach for the optimal design of a sustainable Integrated Biodiesel/Diesel Supply Chain (IBDSC) based on first- (sunflower and rapeseed) and second-generation (waste cooking oil and animal fat) feedstocks with solid waste use. It includes mixed-integer linear programming (MILP) models of the economic, environmental and social impact of IBDSC, and respective criteria defined in terms of costs. The purpose is to obtain the optimal number, sizes and locations of bio-refineries and solid waste plants; the areas and amounts of feedstocks needed for biodiesel production; and the transportation mode. The approach is applied on a real case study in which the territory of Bulgaria with its 27 districts is considered. Optimization problems are formulated for a 5-year period using either environmental or economic criteria and the remainder are defined as constraints. The obtained results show that in the case of the economic criterion, 14% of the agricultural land should be used for sunflower and 2% for rapeseed cultivation, while for the environmental case, 12% should be used for rapeseed and 3% for sunflower. In this case, the price of biodiesel is 14% higher, and the generated pollutants are 6.6% lower. The optimal transport for both cases is rail.
Convolutional Neural Networks Using Enhanced Radiographs for Real-Time Detection of Sitophilus zeamais in Maize Grain
Authors: Barboza da Silva Clíssia , Silva Alysson Alexander Naves , Barroso Geovanny , Yamamoto Pedro Takao , Arthur Valter , Toledo Claudio Fabiano Motta , Mastrangelo Thiago de Araújo
Published: April 2021

The application of artificial intelligence (AI) such as deep learning in the quality control of grains has the potential to assist analysts in decision making and improving procedures. Advanced technologies based on X-ray imaging provide markedly easier ways to control insect infestation of stored products, regardless of whether the quality features are visible on the surface of the grains. Here, we applied contrast enhancement algorithms based on peripheral equalization and calcification emphasis on X-ray images to improve the detection of Sitophilus zeamais in maize grains. In addition, we proposed an approach based on convolutional neural networks (CNNs) to identity non-infested and infested classes using three different architectures; (i) Inception-ResNet-v2, (ii) Xception and (iii) MobileNetV2. In general, the prediction models developed based on the MobileNetV2 and Xception architectures achieved higher accuracy (≥0.88) in identifying non-infested grains and grains infested by maize weevil, with a correct classification from 0.78 to 1.00 for validation and test sets. Hence, the proposed approach using enhanced radiographs has the potential to provide precise control of Sitophilus zeamais for safe human consumption of maize grains. The proposed method can automatically recognize food contaminated with hidden storage pests without manual features, which makes it more reliable for grain inspection.
Sausages: Nutrition, Safety, Processing and Quality Improvement
Authors: Carballo Javier
Published: April 2021

Sausages are one of the oldest processed foods known to man [...]