bluuebunny/crossref_metadata_2025 huggingface dataset:
Wildfire Pyroconvection and CAPE: Buoyancy’s Drying and Atmospheric Intensification—Fort McMurray
Authors: Bakhshaii Atoossa , Johnson Edward A. , Nayebi Kiana
Published: July 2020

The accurate prediction of wildfire behavior and spread is possible only when fire and atmosphere simulations are coupled. In this work, we present a mechanism that causes a small fire to intensify by altering the atmosphere. These alterations are caused by fire-related fluxes at the surface. The fire plume and fluxes increase the convective available potential energy (CAPE) and the chance of the development of a strong pyroconvection system. To study this possible mechanism, we used WRF-Fire to capture fire line propagation as the result of interactions between heat and moisture fluxes, pressure perturbations, wind shear development and dry air downdraft. The wind patterns and dynamics of the pyroconvection system are simulated for the Horse River wildfire at Fort McMurray, Canada. The results revealed that the updraft speed reached up to 12 m/s. The entrainment mixed the mid and upper-level dry air and lowered the atmospheric moisture. The mid-level and upper-level dew point temperature changed by 5–10 ∘ C in a short period of time. The buoyant air strengthened the ascent as soon as the nocturnal inversion was eliminated by daytime heating. The 887 J/kg total increase of CAPE in less than 5 h and the high bulk Richardson number (BRN) of 93 were indicators of the growing pyro-cumulus cell. The presented simulation has not improved the original model or supported leading-edge numerical weather prediction (NWP) achievements, except for adapting WRF-Fire for Canadian biomass fuel. However, we were able to present a great deal of improvements in wildfire nowcasting and short-term forecasting to save lives and costs associated with wildfires. The simulation is sufficiently fast and efficient to be considered for a real-time operational model. While the project was designed and succeeded as an NWP application, we are still searching for a solution for the intractable problems associated with political borders and the current liable authorities for the further development of a new generation of national atmosphere–wildfire forecasting systems.
Efficacy of Radiant Catalytic Ionization in Reduction of Enterococcus spp., Clostridioides difficile and Staphylococcus aureus in Indoor Air
Authors: Skowron Krzysztof , Grudlewska-Buda Katarzyna , Kożuszko Sylwia , Wiktorczyk Natalia , Skowron Karolina Jadwiga , Mikucka Agnieszka , Bernaciak Zuzanna , Gospodarek-Komkowska Eugenia
Published: July 2020

(1) Background: An aerogenic way is one of main rout of spreading microorganisms (including antibiotic resistant), that cause healthcare-associated infections. The source of microorganisms in the air can be patients, personnel, visitors, outdoor air, hospital surfaces and equipment, and even sink drains. (2) Methods: The standardized suspensions (0.5 McFarland) of the examined strains (Enterococcus spp., Clostridioides difficile, Staphylococcus aureus) were nebulized in sterile chamber. Then the Induct 750 (ActivTek) device, generating RCI (radiant catalytic ionization) phenomenon, was used for 20 min. Next, the number of bacteria in the air was calculated using collision method. The percentage of reduction coefficient (R) was calculated. (3) Results: In case of enterococci, the R value was >90% and there are no statistically significant differences among tested strains. For C. difficile strains the R value range from 64–95%. The R value calculated for hypervirulent, antibiotic resistant CDI PCR 27 strain was statistically significantly lower than for other examined strains. For S. aureus non-MRSA the R value was 99.87% and for S. aurues MRSA the R value was 95.61%. (4) Conclusions: The obtained results indicate that the use of RCI may contribute to reducing the occurrence of dangerous pathogens in the air, and perhaps transmission and persistence in the hospital buildings environment.
Capturing the Variability in Instantaneous Vehicle Emissions Based on Field Test Data
Authors: Zhai Zhiqiang , Tu Ran , Xu Junshi , Wang An , Hatzopoulou Marianne
Published: July 2020

Emission models are important tools for traffic emission and air quality estimates. Existing instantaneous emission models employ the steady-state “engine emissions map” to estimate emissions for individual vehicles. However, vehicle emissions vary significantly, even under the same driving conditions. Variability in the emissions at a specific driving condition depends on various influencing factors. It is important to gain insight into the effects of these factors, to enable detailed modeling of individual vehicle emissions. This study employs a portable emissions measurement system (PEMS), to collect vehicle emissions including the corresponding parameters of engine condition, vehicle activity, catalyst temperature, geography, and meteorology, to analyze the variability in emission rates as a function of those factors, across different vehicle specific power (VSP) categories. We observe that carbon dioxide, carbon monoxide, nitrogen oxides, and particle number emissions are strongly correlated with engine parameters (engine speed, torque, load, and air-fuel ratio) and vehicle activity parameters (vehicle speed and acceleration). In the same VSP bin, emissions per second on highways and ramps are higher than those on arterial roads, and the emissions when the vehicle is traveling downhill tend to be higher than the emissions during uphill traveling, because of higher observed speeds and accelerations. Morning emissions are higher than afternoon emissions, due to lower temperatures.
Climate Change, Climatic Extremes, and Human Societies in the Past
Authors: Lee Harry F.
Published: July 2020

More people appreciate the importance of global sustainability [...]
Recent Trends in Injury Models to Study Skeletal Muscle Regeneration and Repair
Authors: Sicherer Sydnee T. , Venkatarama Rashmi S. , Grasman Jonathan M.
Published: July 2020

Skeletal muscle injuries that occur from traumatic incidents, such as those caused by car accidents or surgical resections, or from injuries sustained on the battlefield, result in the loss of functionality of the injured muscle. To understand skeletal muscle regeneration and to better treat these large scale injuries, termed volumetric muscle loss (VML), in vivo injury models exploring the innate mechanisms of muscle injury and repair are essential for the creation of clinically applicable treatments. While the end result of a muscle injury is often the destruction of muscle tissue, the manner in which these injuries are induced as well as the response from the innate repair mechanisms found in muscle in each animal models can vary. This targeted review describes injury models that assess both skeletal muscle regeneration (i.e., the response of muscle to myotoxin or ischemic injury) and skeletal muscle repair (i.e., VML injury). We aimed to summarize the injury models used in the field of skeletal muscle tissue engineering, paying particular attention to strategies to induce muscle damage and how to standardize injury conditions for future experiments.
An Approach towards a GMP Compliant In-Vitro Expansion of Human Adipose Stem Cells for Autologous Therapies
Authors: Jossen Valentin , Muoio Francesco , Panella Stefano , Harder Yves , Tallone Tiziano , Eibl Regine
Published: July 2020

Human Adipose Tissue Stem Cells (hASCs) are a valuable source of cells for clinical applications (e.g., treatment of acute myocardial infarction and inflammatory diseases), especially in the field of regenerative medicine. However, for autologous (patient-specific) and allogeneic (off-the-shelf) hASC-based therapies, in-vitro expansion is necessary prior to the clinical application in order to achieve the required cell numbers. Safe, reproducible and economic in-vitro expansion of hASCs for autologous therapies is more problematic because the cell material changes for each treatment. Moreover, cell material is normally isolated from non-healthy or older patients, which further complicates successful in-vitro expansion. Hence, the goal of this study was to perform cell expansion studies with hASCs isolated from two different patients/donors (i.e., different ages and health statuses) under xeno- and serum-free conditions in static, planar (2D) and dynamically mixed (3D) cultivation systems. Our primary aim was I) to compare donor variability under in-vitro conditions and II) to develop and establish an unstructured, segregated growth model as a proof-of-concept study. Maximum cell densities of between 0.49 and 0.65 × 105 hASCs/cm2 were achieved for both donors in 2D and 3D cultivation systems. Cell growth under static and dynamically mixed conditions was comparable, which demonstrated that hydrodynamic stresses (P/V = 0.63 W/m3, τnt = 4.96 × 10−3 Pa) acting at Ns1u (49 rpm for 10 g/L) did not negatively affect cell growth, even under serum-free conditions. However, donor-dependent differences in the cell size were found, which resulted in significantly different maximum cell densities for each of the two donors. In both cases, stemness was well maintained under static 2D and dynamic 3D conditions, as long as the cells were not hyperconfluent. The optimal point for cell harvesting was identified as between cell densities of 0.41 and 0.56 × 105 hASCs/cm2 (end of exponential growth phase). The growth model delivered reliable predictions for cell growth, substrate consumption and metabolite production in both types of cultivation systems. Therefore, the model can be used as a basis for future investigations in order to develop a robust MC-based hASC production process for autologous therapies.
Lactate-Based Model Predictive Control Strategy of Cell Growth for Cell Therapy Applications
Authors: Van Beylen Kathleen , Youssef Ali , Peña Fernández Alberto , Lambrechts Toon , Papantoniou Ioannis , Aerts Jean-Marie
Published: July 2020

Implementing a personalised feeding strategy for each individual batch of a bioprocess could significantly reduce the unnecessary costs of overfeeding the cells. This paper uses lactate measurements during the cell culture process as an indication of cell growth to adapt the feeding strategy accordingly. For this purpose, a model predictive control is used to follow this a priori determined reference trajectory of cumulative lactate. Human progenitor cells from three different donors, which were cultivated in 12-well plates for five days using six different feeding strategies, are used as references. Each experimental set-up is performed in triplicate and for each run an individualised model-based predictive control (MPC) controller is developed. All process models exhibit an accuracy of 99.80% ± 0.02%, and all simulations to reproduce each experimental run, using the data as a reference trajectory, reached their target with a 98.64% ± 0.10% accuracy on average. This work represents a promising framework to control the cell growth through adapting the feeding strategy based on lactate measurements.
Pharmacological Effects of a Novel Bradykinin-Related Peptide (RR-18) from the Skin Secretion of the Hejiang Frog (Ordorrana hejiangensis) on Smooth Muscle
Authors: Zhou Xiaowei , Xu Jie , Zhong Ruimin , Ma Chengbang , Zhou Mei , Cao Zhijian , Xi Xinping , Shaw Chris , Chen Tianbao , Wang Lei , Kwok Hang Fai
Published: July 2020

Bradykinin (BK) and bradykinin-related peptides (BRPs), which were identified from a diversity of amphibian skin secretions, exerted contractile and relaxing effects on non-vascular and vascular smooth muscle, respectively. Here, we report a novel bradykinin-related peptide with a molecular mass of 1890.2 Da, RVAGPDKPARISGLSPLR, which was isolated and identified from Ordorrana hejiangensis skin secretions, followed by a C-terminal extension sequence VAPQIV. The biosynthetic precursor-encoding cDNA was cloned by the “shotgun” cloning method, and the novel RR-18 was identified and structurally confirmed by high-performance liquid chromatography (HPLC) and tandem mass spectrometry (MS/MS). Subsequently, the myotropic activity of the synthetic replicate of RR-18 was investigated on the rat bladder, uterus, tail artery and ileum smooth muscle. The peptide was named RR-18 in accordance (R = N-terminal arginine, R = C-terminal arginine, 18 = number of residues). In this study, the synthetic replicates of RR-18 showed no agonist/antagonism of BK-induced rat bladder and uterus smooth muscle contraction. However, it displayed an antagonism of bradykinin-induced rat ileum contraction and arterial smooth muscle relaxation. The EC50 values of BK for ileum and artery, were 214.7 nM and 18.3 nM, respectively. When the tissue was pretreated with the novel peptide, RR-18, at the maximally effective concentration of bradykinin (1 × 10−6 M), bradykinin-induced contraction of the ileum and relaxation of the arterial smooth muscle was reduced by 50–60% and 30–40%, respectively. In conclusion, RR-18 represents novel bradykinin antagonising peptide from amphibian skin secretions. It may provide new insight into possible treatment options for chronic pain and chronic inflammation.
Domain Mapping and Deep Learning from Multiple MRI Clinical Datasets for Prediction of Molecular Subtypes in Low Grade Gliomas
Authors: Ali Muhaddisa Barat , Gu Irene Yu-Hua , Berger Mitchel S. , Pallud Johan , Southwell Derek , Widhalm Georg , Roux Alexandre , Vecchio Tomás Gomez , Jakola Asgeir Store
Published: July 2020

Brain tumors, such as low grade gliomas (LGG), are molecularly classified which require the surgical collection of tissue samples. The pre-surgical or non-operative identification of LGG molecular type could improve patient counseling and treatment decisions. However, radiographic approaches to LGG molecular classification are currently lacking, as clinicians are unable to reliably predict LGG molecular type using magnetic resonance imaging (MRI) studies. Machine learning approaches may improve the prediction of LGG molecular classification through MRI, however, the development of these techniques requires large annotated data sets. Merging clinical data from different hospitals to increase case numbers is needed, but the use of different scanners and settings can affect the results and simply combining them into a large dataset often have a significant negative impact on performance. This calls for efficient domain adaption methods. Despite some previous studies on domain adaptations, mapping MR images from different datasets to a common domain without affecting subtitle molecular-biomarker information has not been reported yet. In this paper, we propose an effective domain adaptation method based on Cycle Generative Adversarial Network (CycleGAN). The dataset is further enlarged by augmenting more MRIs using another GAN approach. Further, to tackle the issue of brain tumor segmentation that requires time and anatomical expertise to put exact boundary around the tumor, we have used a tight bounding box as a strategy. Finally, an efficient deep feature learning method, multi-stream convolutional autoencoder (CAE) and feature fusion, is proposed for the prediction of molecular subtypes (1p/19q-codeletion and IDH mutation). The experiments were conducted on a total of 161 patients consisting of FLAIR and T1 weighted with contrast enhanced (T1ce) MRIs from two different institutions in the USA and France. The proposed scheme is shown to achieve the test accuracy of 74 . 81 % on 1p/19q codeletion and 81 . 19 % on IDH mutation, with marked improvement over the results obtained without domain mapping. This approach is also shown to have comparable performance to several state-of-the-art methods.
Mouse Tracking to Explore Motor Inhibition Processes in Go/No-Go and Stop Signal Tasks
Authors: Benedetti Viola , Gavazzi Gioele , Giovannelli Fabio , Bravi Riccardo , Giganti Fiorenza , Minciacchi Diego , Mascalchi Mario , Cincotta Massimo , Viggiano Maria Pia
Published: July 2020

Response inhibition relies on both proactive and reactive mechanisms that exert a synergic control on goal-directed actions. It is typically evaluated by the go/no-go (GNG) and the stop signal task (SST) with response recording based on the key-press method. However, the analysis of discrete variables (i.e., present or absent responses) registered by key-press could be insufficient to capture dynamic aspects of inhibitory control. Trying to overcome this limitation, in the present study we used a mouse tracking procedure to characterize movement profiles related to proactive and reactive inhibition. A total of fifty-three participants performed a cued GNG and an SST. The cued GNG mainly involves proactive control whereas the reactive component is mainly engaged in the SST. We evaluated the velocity profile from mouse trajectories both for responses obtained in the Go conditions and for inhibitory failures. Movements were classified as one-shot when no corrections were observed. Multi-peaked velocity profiles were classified as non-one-shot. A higher proportion of one-shot movements was found in the SST compared to the cued GNG when subjects failed to inhibit responses. This result suggests that proactive control may be responsible for unsmooth profiles in inhibition failures, supporting a differentiation between these tasks.
Tolerability and Blinding of Transcranial Direct Current Stimulation in People with Parkinson’s Disease: A Critical Review
Authors: Workman Craig D. , Fietsam Alexandra C. , Rudroff Thorsten
Published: July 2020

Transcranial direct current stimulation (tDCS) is accompanied by transient sensations (e.g., tingling, itching, burning), which may affect treatment outcomes or break the blinding of the study protocol. Assessing tolerability and blinding is integral to providing ample evidence of a “real effect” from the applied stimulation and dispelling the possibility of placebo effects. People with Parkinson’s disease (PwPD) endure many motor and non-motor symptoms that might be amenable to tDCS. However, because the disease also affects sensation capabilities, these subjects might report tolerability and blinding differently than other cohorts. Therefore, the purpose of this review was to aggregate the tolerability and blinding reports of tDCS studies in PwPD and recommend a standard tolerability and blinding reporting practice. A literature search of the PubMed and Scopus databases from 1 January 2020 to 1 April 2020 was performed to identify publications that applied tDCS to PwPD. Seventy studies were potentially reviewable, but only 36 (nine with quantitative tolerability reports, 20 with qualitative tolerability reports, and seven that only reported blinding) provided sufficient information to be included in the review. Quantitative information on tDCS tolerability and blinding maintenance in PwPD is scarce, and future reviews and metanalyses should carefully consider the possibility of placebo effects in their included studies.
Human Papillomavirus 16 E7 Promotes EGFR/PI3K/AKT1/NRF2 Signaling Pathway Contributing to PIR/NF-κB Activation in Oral Cancer Cells
Authors: Carrillo-Beltrán Diego , Muñoz Juan P. , Guerrero-Vásquez Nahir , Blanco Rancés , León Oscar , de Souza Lino Vanesca , Tapia Julio C. , Maldonado Edio , Dubois-Camacho Karen , Hermoso Marcela A. , Corvalán Alejandro H. , Calaf Gloria M. , Boccardo Enrique , Aguayo Francisco
Published: July 2020

A subset of oral carcinomas is etiologically related to high-risk human papillomavirus (HR-HPV) infection, with HPV16 being the most frequent HR-HPV type found in these carcinomas. The oncogenic role of HR-HPV is strongly dependent on the overexpression of E6 and E7 oncoproteins, which, in turn, induce p53 and pRb degradation, respectively. Additionally, it has been suggested that HR-HPV oncoproteins are involved in the regulation of nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB), inducing cancer progression and metastasis. Previously, we reported that HPV16 E7 oncoprotein promotes Pirin upregulation resulting in increased epithelial–mesenchymal transition (EMT) and cell migration, with Pirin being an oxidative stress sensor and activator of NF-κB. In this study, we demonstrate the mechanism by which HPV16 E7-mediated Pirin overexpression occurs by promoting EGFR/PI3K/AKT1/NRF2 signaling, thus causing PIR/NF-κB activation in oral tumor cells. Our results demonstrate a new mechanism by which E7 contributes to oral cancer progression, proposing PIR as a potential new therapeutic target.
Real-World Data on Thromboprophylaxis in Active Cancer Patients: Where Are We? Are We Getting There?
Authors: Tsoukalas Nikolaos , Papakotoulas Pavlos , Christopoulou Athina , Ardavanis Alexandros , Koumakis Georgios , Papandreou Christos , Papatsimpas Georgios , Papakostas Pavlos , Samelis Georgios , Andreadis Charalambos , Aravantinos Gerasimos , Ziras Nikolaos , Kalofonos Charalambos , Samantas Epameinondas , Souggleri Maria , Makrantonakis Paris , Pentheroudakis Georgios , Athanasiadis Athanasios , Stergiou Helen , Tripodaki Elli-Sofia , Bokas Alexandros , Grivas Anastasios , Timotheadou Eleni , Bournakis Evangelos , Varthalitis Ioannis , Boukovinas Ioannis
Published: July 2020

Background: Cancer patients are at high risk for cancer-associated thrombosis (CAT). CAT is the second leading cause of death in these patients but it can be preventable with thromboprophylaxis. Patients and Methods: An observational, prospective, multicenter study aiming to record CAT management in clinical practice was conducted by the Hellenic Society of Medical Oncology (HeSMO). Results: A total of 426 active cancer patients (mean age 65.3 years, mean BMI: 26.1 kg/m2) who received thromboprophylaxis, were included from 18 oncology units. Tumor types were lung 25.1%, pancreas 13.9%, breast 8.7%, stomach 8.5%, ovarian 7.8%, and others 36%, while 69% had metastases. A total of 71% had a Khorana score ≤2 and 61% received High Thrombotic Risk Chemotherapy Agents (HTRCAs, e.g., platinum). For thromboprophylaxis patients received mainly Low Molecular Weight Heparins (LMWHs), on higher than prophylactic doses in 50% of cases. Overall, 16 (3.8%) thrombotic events and 6 (1.4%) bleeding events were recorded. Notably, patients on higher doses of LMWHs compared to patients who received standard prophylactic doses had 70% lower odds to develop thrombotic events (OR: 0.3, 95% CI: 0.10–1.0, p = 0.04). Conclusion: CAT is an important issue in oncology. Along with the Khorana score, factors as metastases and use of HTRCAs should also be taken into consideration. Thromboprophylaxis for active cancer patients with LMWHs, even on higher doses is safe and efficient.
The Density and Length of Filopodia Associate with the Activity of Hyaluronan Synthesis in Tumor Cells
Authors: Kyykallio Heikki , Oikari Sanna , Bueno Álvez María , Gallardo Dodd Carlos José , Capra Janne , Rilla Kirsi
Published: July 2020

Filopodia are multifunctional finger-like plasma membrane protrusions with bundles of actin filaments that exist in virtually all cell types. It has been known for some time that hyaluronan synthesis activity induces filopodial growth. However, because of technical challenges in the studies of these slender and fragile structures, no quantitative analyses have been performed so far to indicate their association with hyaluronan synthesis. In this work we comprehensively address the direct quantification of filopodial traits, covering for the first time length and density measurements in a series of human cancer cell lines with variable levels of hyaluronan synthesis. The synthesis and plasma membrane binding of hyaluronan were manipulated with hyaluronan synthase 3 (HAS3) and hyaluronan receptor CD44 overexpression, and treatments with mannose, 4-methylumbelliferone (4-MU), and glucosamine. The results of this work show that the growth of filopodia was associated with the levels of hyaluronan synthesis but was not dependent on CD44 expression. The results confirm the hypothesis that abundance and length of filopodia in cancer cells is associated with the activity of hyaluronan synthesis.
The LIM Protein Ajuba Augments Tumor Metastasis in Colon Cancer
Authors: Dommann Noëlle , Sánchez-Taltavull Daniel , Eggs Linda , Birrer Fabienne , Brodie Tess , Salm Lilian , Baier Felix Alexander , Medová Michaela , Humbert Magali , Tschan Mario P. , Beldi Guido , Candinas Daniel , Stroka Deborah
Published: July 2020

Colorectal cancer, along with its high potential for recurrence and metastasis, is a major health burden. Uncovering proteins and pathways required for tumor cell growth is necessary for the development of novel targeted therapies. Ajuba is a member of the LIM domain family of proteins whose expression is positively associated with numerous cancers. Our data shows that Ajuba is highly expressed in human colon cancer tissue and cell lines. Publicly available data from The Cancer Genome Atlas shows a negative correlation between survival and Ajuba expression in patients with colon cancer. To investigate its function, we transduced SW480 human colon cancer cells, with lentiviral constructs to knockdown or overexpress Ajuba protein. The transcriptome of the modified cell lines was analyzed by RNA sequencing. Among the pathways enriched in the differentially expressed genes, were cell proliferation, migration and differentiation. We confirmed our sequencing data with biological assays; cells depleted of Ajuba were less proliferative, more sensitive to irradiation, migrated less and were less efficient in colony formation. In addition, loss of Ajuba expression decreased the tumor burden in a murine model of colorectal metastasis to the liver. Taken together, our data supports that Ajuba promotes colon cancer growth, migration and metastasis and therefore is a potential candidate for targeted therapy.
Algorithm Scheme to Simulate the Distortions during Gas Quenching in a Single-Piece Flow Technology
Authors: Sawicki Jacek , Krupanek Krzysztof , Stachurski Wojciech , Buzalski Victoria
Published: July 2020

Low-pressure carburizing followed by high-pressure quenching in single-piece flow technology has shown good results in avoiding distortions. For better control of specimen quality in these processes, developing numerical simulations can be beneficial. However, there is no commercial software able to simulate distortion formation during gas quenching that considers the complex fluid flow field and heat transfer coefficient as a function of space and time. For this reason, this paper proposes an algorithm scheme that aims for more refined results. Based on the physical phenomena involved, a numerical scheme was divided into five modules: diffusion module, fluid module, thermal module, phase transformation module, and mechanical module. In order to validate the simulation, the results were compared with the experimental data. The outcomes showed that the average difference between the numerical and experimental data for distortions was 1.7% for the outer diameter and 12% for the inner diameter of the steel element. Numerical simulation also showed the differences between deformations in the inner and outer diameters as they appear in the experimental data. Therefore, a numerical model capable of simulating distortions in the steel elements during high-pressure gas quenching after low-pressure carburizing using a single-piece flow technology was obtained, whereupon the complex fluid flow and variation of the heat transfer coefficient was considered.
Naproxen-Based Hydrazones as Effective Corrosion Inhibitors for Mild Steel in 1.0 M HCl
Authors: Chafiq Maryam , Chaouiki Abdelkarim , Al-Hadeethi Mustafa R. , Ali Ismat H. , Mohamed Shaaban K. , Toumiat Karima , Salghi Rachid
Published: July 2020

The corrosion-inhibiting performance of (E)-N’-(4-bromobenzylidene)-2-(6-methoxynaphthalen-2-yl) propanehydrazide (BPH) and (E)-N’-(4-(dimethylamino) benzylidene)-2-(6-methoxynaphthalen-2-yl) propanehydrazide (MPH) for mild steel (MS) in 1.0 M HCl was investigated using electrochemical methods, weight loss measurements, and scanning electron microscope (SEM) coupled with energy dispersive X-ray spectroscope (EDX) analysis. Raising the concentration of both inhibitors towards an optimal value of 5 × 10−3 M reduced the corrosion current density (icorr) and the corrosion rate of mild steel. The inhibitory effect of MPH, which showed the highest inhibition efficiency, was explored under a range of temperatures between 303 and 333 K. The inhibitory performance of both compounds significantly improved when the inhibitor concentration increased. The main result that flowed from potentiodynamic polarization (PDP) tests was that both compounds acted as mixed-type inhibitors, with a predominance cathodic effect. The adsorption of both compounds follows the Langmuir isotherm. SEM/EDX confirmed the excellent inhibition performance of tested compounds.
Effect of Aggregate Type and Specimen Configuration on Concrete Compressive Strength
Authors: Yehia Sherif , Abdelfatah Akmal , Mansour Doaa
Published: July 2020

In this paper, concrete mixes utilizing two sizes of natural aggregate and two sources of lightweight and recycled aggregates were used to investigate the effect of aggregate type and specimen size and shape on the compressive strength of concrete. In addition, samples from ready-mix concrete producers with different strengths were evaluated using standard size cylinders and cubes. Results were obtained on the 7th, 28th, and 90th day. In addition, flexural strength, split tension, and modulus of elasticity were evaluated on the 28th and 90th day. Statistical analyses were conducted to examine the significance of the difference between the compressive strength values for each two mixes using tests of hypotheses. Moreover, other mechanical properties as a function of compressive strength were discussed and compared to those predicated by the American Concrete Institute (ACI) specifications. Results indicate specimen shape has a noticeable effect on the compressive strength as the Cylinder/Cube ratio on the 90th day was ranging between 0.781 and 0.929. The concrete compressive strength and modulus of elasticity were significantly affected by the aggregate type. The flexural strength and split tensile strength were less affected by the aggregate type, which was also confirmed by the values predicted with the ACI equations.
The Effect of Operating Temperature on the Response Time of Optically Driven Liquid Crystal Displays
Authors: Chigrinov Vladimir , Sun Jiatong , Kuznetsov Mikhail M. , Belyaev Victor , Chausov Denis
Published: July 2020

Optically driven liquid crystal displays (ODLCDs) realizes their display function by tuning the easy axis of liquid crystal (LC) molecules under polarized blue light, which has been utilized in some optical devices due to its advantages of ultra-low power consumption. However, a big issue arises in response time, i.e., the rewriting time of the ODLCD. The rewriting time of ODLCD samples was studied. Rotational viscosity plays a very important role for decreasing the rewriting time of the ODLCD. The operating temperature was changed from room temperature to nearly clearing point, the rewriting time decreased a lot as the rotational viscosity decreased for the five different kinds of the LCs. The rewriting time can be decreased from 5.2 s to 0.2 s around 25 times for the LC N4.
Coexistence of Two Closely Related Cyprinid Fishes (Hemiculter bleekeri and Hemiculter leucisculus) in the Upper Yangtze River, China
Authors: Li Wen Jing , Gao Xin , Liu Huan Zhang , Cao Wen Xuan
Published: July 2020

Species coexistence is one of the most important concepts in ecology for understanding how biodiversity is shaped and changed. In this study, we investigated the mechanism by which two small cyprinid fishes (H. leucisculus and H. bleekeri) coexist by analyzing their niche segregation and morphological differences in the upper Yangtze River. Morphological analysis indicated that H. leucisculus has posteriorly located dorsal fins, whereas H. bleekeri has a more slender body, bigger eyes, longer anal fin base, and a higher head. Niche segregation analysis showed spatial and trophic niche segregation between these two species: on the spatial scale, H. leucisculus was more widely distributed than H. bleekeri, indicating that H. leucisculus is more of a generalist in the spatial dimension; on the trophic scale, H. bleekeri had a wider niche than H. leucisculus. Therefore, these two species adopt different adaptation mechanisms to coexist
On Gap-Based Lower Bounding Techniques for Best-Arm Identification
Authors: Truong Lan V. , Scarlett Jonathan
Published: July 2020

In this paper, we consider techniques for establishing lower bounds on the number of arm pulls for best-arm identification in the multi-armed bandit problem. While a recent divergence-based approach was shown to provide improvements over an older gap-based approach, we show that the latter can be refined to match the former (up to constant factors) in many cases of interest under Bernoulli rewards, including the case that the rewards are bounded away from zero and one. Together with existing upper bounds, this indicates that the divergence-based and gap-based approaches are both effective for establishing sample complexity lower bounds for best-arm identification.
A Protocol Design Paradigm for Batched Sparse Codes
Authors: Yin Hoover H. F. , Yeung Raymond W. , Yang Shenghao
Published: July 2020

Internet of Things (IoT) connects billions of everyday objects to the Internet. The mobility of devices can be facilitated by means of employing multiple wireless links. However, packet loss is a common phenomenon in wireless communications, where the traditional forwarding strategy undergoes severe performance issues in a multi-hop wireless network. One solution is to apply batched sparse (BATS) codes. A fundamental difference from the traditional strategy is that BATS codes require the intermediate network nodes to perform recoding, which generates recoded packets by network coding operations. Literature showed that advanced recoding schemes and burst packet loss can enhance and diminish the performance of BATS codes respectively. However, the existing protocols for BATS codes cannot handle both of them at the same time. In this paper, we propose a paradigm of protocol design for BATS codes. Our design can be applied in different layers of the network stack and it is compatible to the existing network infrastructures. The modular nature of the protocol can support different recoding techniques and different ways to handle burst packet loss. We also give some examples to demonstrate how to use the protocol.
MADFU: An Improved Malicious Application Detection Method Based on Features Uncertainty
Authors: Yuan Hongli , Tang Yongchuan
Published: July 2020

Millions of Android applications (apps) are widely used today. Meanwhile, the number of malicious apps has increased exponentially. Currently, there are many security detection technologies for Android apps, such as static detection and dynamic detection. However, the uncertainty of the features in detection is not considered sufficiently in these technologies. Permissions play an important role in the security detection of Android apps. In this paper, a malicious application detection model based on features uncertainty (MADFU) is proposed. MADFU uses logistic regression function to describe the input (permissions) and output (labels) relationship. Moreover, it uses the Markov chain Monte Carlo (MCMC) algorithm to solve features’ uncertainty. After experimenting with 2037 samples, for malware detection, MADFU achieves an accuracy of up to 95.5%, and the false positive rate (FPR) is 1.2%. MADFU’s Android app detection accuracy is higher than the accuracy of directly using 24 dangerous permission. The results also indicate that the method for an unknown/new sample’s detection accuracy is 92.7%. Compared to other state-of-the-art approaches, the proposed method is more effective and efficient, by detecting malware.
An Alertness-Adjustable Cloud/Fog IoT Solution for Timely Environmental Monitoring Based on Wildfire Risk Forecasting
Authors: Tsipis Athanasios , Papamichail Asterios , Angelis Ioannis , Koufoudakis George , Tsoumanis Georgios , Oikonomou Konstantinos
Published: July 2020

Internet of Things (IoT) appliances, especially those realized through wireless sensor networks (WSNs), have been a dominant subject for heavy research in the environmental and agricultural sectors. To address the ever-increasing demands for real-time monitoring and sufficiently handle the growing volumes of raw data, the cloud/fog computing paradigm is deemed a highly promising solution. This paper presents a WSN-based IoT system that seamlessly integrates all aforementioned technologies, having at its core the cloud/fog hybrid network architecture. The system was intensively validated using a demo prototype in the Ionian University facilities, focusing on response time, an important metric of future smart applications. Further, the developed prototype is able to autonomously adjust its sensing behavior based on the criticality of the prevailing environmental conditions, regarding one of the most notable climate hazards, wildfires. Extensive experimentation verified its efficiency and reported on its alertness and highly conforming characteristics considering the use-case scenario of Corfu Island’s 2019 fire risk severity. In all presented cases, it is shown that through fog leveraging it is feasible to contrive significant delay reduction, with high precision and throughput, whilst controlling the energy consumption levels. Finally, a user-driven web interface is highlighted to accompany the system; it is capable of augmenting the data curation and visualization, and offering real-time wildfire risk forecasting based on Chandler’s burning index scoring.
Supertwisting Sliding Mode Algorithm Based Nonlinear MPPT Control for a Solar PV System with Artificial Neural Networks Based Reference Generation
Authors: Ahmed Shahzad , Muhammad Adil Hafiz Mian , Ahmad Iftikhar , Azeem Muhammad Kashif , e Huma Zil , Abbas Khan Safdar
Published: July 2020

The problem of extracting maximum power from a photovoltaic (PV) system with negligible power loss is concerned with the power generating capability of the PV array and nature of the output load. Changing weather conditions and nonlinear behavior of PV systems pose a challenge in tracking of varying maximum power point. A robust nonlinear controller is required to ensure maximum power point tracking (MPPT) by handling nonlinearities of a system and making it robust against changing environmental conditions. Sliding mode controller is robust against disturbances, model uncertainties and parametric variations. It depicts undesirable phenomenon like chattering, inherent in it causing power and heat losses. In this paper, a supertwisting sliding mode algorithm based nonlinear robust controller has been designed for MPPT of a PV system which not only removes the chattering but also enhances the overall system’s dynamic response. Moreover, supertwisting sliding mode controller is robust against changing environmental conditions like change in temperature and irradiance. Noninverting DC-DC Buck-Boost converter has been used as an interface between source and the load. The efficiency of MPPT of a PV system depends upon the accuracy of reference for peak power voltage, therefore an efficient mechanism for reference generation has also been proposed in this work. The reference for peak power voltage has been generated by using a trained artificial neural network, which is to be tracked by proposed nonlinear controllers. Sliding mode controller (SMC) and synergetic controllers have also been designed for MPPT of a PV system in order to compare them with supertwisting sliding mode controller (ST-SMC). Global asymptotic stability of the system has been ensured by using Lyapunov stability criterion. The performance of the proposed nonlinear controllers has been validated in MATLAB/Simulink ODE 45 environment. ST-SMC has also been compared with recently proposed integral backstepping controller and other conventional MPPT controllers given in the literature. The simulation results show the better performance of ST-SMC in terms of best dynamic response and robustness.
Fatty Acid Methyl Esters from the Herbal Industry Wastes as a Potential Feedstock for Biodiesel Production
Authors: Sienkiewicz Aneta , Piotrowska-Niczyporuk Alicja , Bajguz Andrzej
Published: July 2020

Due to thegrowing awareness of fossil fuel depletion and environmental issues, biodiesel alternative fuel is currently of substantial interest. This research assessed herbal industry wastes as a potential resource for biodiesel production for the first time. Fatty acid methyl esters (FAMEs), obtained in the transesterification reaction, were extracted from the herbal samples by ultrasound-assisted extraction and identified withgas chromatography-mass spectrometry in the selected ion monitoring mode. The presence of at least 20 (e.g., in chamomile and chicory) FAMEs, up to 31 in nettle and senna, was reported. The unsaturated FAMEs were found in higher amounts than saturated. Linoleic acidwas the major polyunsaturated FAME in herbal wastes, while palmitic acid was the major saturated FAME. The highest content of FAMEs was identified in rye bran, Figure tea, and chicory. According to the cetane number prediction, BS EN 14214:2012+A2:2019, and hierarchical clustering on principal components (HCPC)wastes from, e.g., nettle, sage, and senna, are the most suitable in biodiesel production with fuel properties acceptable by the EuropeanStandards.Principal component analysis and HCPC allowed to classify and groupsimilar plants according to their FAMEs content; however, additional studies of herbal biofuel properties are needed.
Computational Methods for Modelling and Optimization of Flow Control Devices
Authors: Ballesteros-Coll Alejandro , Fernandez-Gamiz Unai , Aramendia Iñigo , Zulueta Ekaitz , Lopez-Guede Jose Manuel
Published: July 2020

Over the last few years, the advances in size and weight for wind turbines have led to the development of flow control devices. The current work presents an innovative method to model flow control devices based on a cell-set model, such as Gurney flaps (GFs). This model reuses the cells which are around the required geometry and a wall boundary condition is assigned to the generated region. Numerical simulations based on RANS equations and with Re = 2 × 10 6 have been performed. Firstly, a performance study of the cell-set model on GFs was carried out by comparing it with a fully mesh model of a DU91W250 airfoil. A global relative error of 1.13% was calculated. Secondly, optimum GF lengths were determined (from 0% to 2% of c) for a DU97W300 airfoil and an application of them. The results showed that for lower angles of attack (AoAs) larger GFs were needed, and as the AoA increased, the optimum GF length value decreased. For the purpose of studying the effects generated by two flow control devices (vortex generators (VGs) and optimum GF) working together, a triangular VG based on the jBAY model was implemented. Resulting data indicated, as expected, that when both flow control devices were implemented, higher CL and lower CD values appeared.
Induction Motor Adaptive Backstepping Control and Efficiency Optimization Based on Load Observer
Authors: Chen Chuanguang , Yu Haisheng , Gong Fei , Wu Herong
Published: July 2020

In this paper, an adaptive load torque observer based on backstepping control is designed, which achieves accurate load estimation where the load is unknown. Based on this, in order to reduce the loss of the motor at low load, a smooth switching strategy of rotor flux based on speed error is designed. According to the real-time speed error of the induction motor, the smooth switching strategy achieves dynamic flux switching. Firstly, when the uncertain load occurs for the first time in the recursive design, the adaptive law of the load is designed, and a novel adaptive load torque observer is obtained, which accurately estimates the uncertain load torque in real time. Secondly, the relationship between the loss and the rotor flux is established by analyzing the loss model of induction motor, and the optimal rotor flux is obtained. The smooth switching control strategy based on speed error is designed to realize the efficiency optimization of induction motor. Finally, the control strategy proposed in this paper is experimentally verified on the LINKS-RT platform. The results show that the proposed control strategy has excellent load disturbance attenuation performance and reduces the energy loss.
Bibliometric Analysis of Trends in Biomass for Bioenergy Research
Authors: Ferrari Giovanni , Pezzuolo Andrea , Nizami Abdul-Sattar , Marinello Francesco
Published: July 2020

This paper aims to provide a bibliometric analysis of publication trends on the themes of biomass and bioenergy worldwide. A wide range of studies have been performed in the field of the usage of biomass for energy production, in order to contribute to the green transition from fossil fuels to renewable energies. Over the past 20 years (from 2000 to 2019), approximately 10,000 articles have been published in the “Agricultural and Biological Sciences” field on this theme, covering all stages of production—from the harvesting of crops to the particular type of energy produced. Articles were obtained from the SCOPUS database and examined with a text mining tool in order to analyze publication trends over the last two decades. Publications per year in the bioenergy theme have grown from 91 in 2000 to 773 in 2019. In particular the analyses showed how environmental aspects have increased their importance (from 7.3% to 11.8%), along with studies related to crop conditions (from 10.4% to 18.6%). Regarding the use of energy produced, growing trends were recognized for the impact of biofuels (mentions moved from 0.14 times per article in 2000 to 0.38 in 2019) and biogases (from 0.14 to 0.42 mentions). Environmental objectives have guided the interest of researchers, encouraging studies on biomass sources and the optimal use of the energy produced. This analysis aims to describe the research evolution, providing an analysis that can be helpful to predict future scenarios and participation among stakeholders in the sector.
Modelling Energy Distribution in Residential Areas: A Case Study Including Energy Storage Systems in Catania, Southern Italy
Authors: Fichera Alberto , Pluchino Alessandro , Volpe Rosaria
Published: July 2020

Complexity is a widely acknowledged feature of urban areas. Among the different levels to which this definition applies, the energy sector is one of the most representative of this way of conceiving cities. An evidence of this complexity can be detected in the growing impact of prosumers. Prosumers produce energy to meet their own demands, distribute it directly to neighbors and, eventually, store the energy neither consumed nor distributed. The modelling of distribution networks is a challenging task that requires ad hoc models to simulate the mutual energy exchanges occurring among prosumers. To serve at this scope, this paper proposes an agent-based model aiming at determining which operating conditions enhance the energy distribution among prosumers and diminish the supply from traditional power plants. An application of the model within a residential territory is then presented and simulations are conducted under two scenarios: the first investigating the distribution among prosumers equipped with photovoltaics (PV) systems, the second integrating energy storage systems to PV panels. Both scenarios are studied at varying the installed PV capacity within the territory, the allowed distance of connection among prosumers, as well as the rate of utilization of the links of the network. Results from the simulated case study reveal that the energy distribution among prosumers can be enhanced by providing short-range links for the electricity exchange. Similar advantages can be achieved by integrating storage systems to PV, along with a significant reduction in the electricity requested to the centralized grid.