bluuebunny/crossref_metadata_2025 huggingface dataset:
Risk Assessment of Large-Scale Infrastructure Projects—Assumptions and Context
Authors: Korytárová Jana , Hromádka Vít
Published: December 2020

This article deals with the partial outputs of large-scale infrastructure project risk assessment, specifically in the field of road and motorway construction. The Department of Transport spends a large amount of funds on project preparation and implementation, which however, must be allocated effectively, and with knowledge of the risks that may accompany them. Therefore, documentation for decision-making on project financing also includes their analysis. This article monitors the frequency of occurrence of individual risk factors within the qualitative risk analysis, with the support of the national risk register, and identifies dependent variables that represent part of the economic cash flows for determining project economic efficiency. At the same time, it compares these dependent variables identified by sensitivity analysis with critical variables, followed by testing the interaction of the critical variables’ effect on the project efficiency using the Monte Carlo method. A partial section of the research was focused on the analysis of the probability distribution of input variables, especially “the investment costs” and “time savings of infrastructure users” variables. The research findings conclude that it is necessary to pay attention to the setting of statistical characteristics of variables entering the economic efficiency indicator calculations, as the decision of whether or not to accept projects for funding is based on them.
Observations of Emissions and the Influence of Meteorological Conditions during Wildfires: A Case Study in the USA, Brazil, and Australia during the 2018/19 Period
Authors: Shikwambana Lerato , Kganyago Mahlatse
Published: December 2020

Wildfires can have rapid and long-term effects on air quality, human health, climate change, and the environment. Smoke from large wildfires can travel long distances and have a harmful effect on human health, the environment, and climate in other areas. More recently, in 2018–2019 there have been many large fires. This study focused on the wildfires that occurred in the United States of America (USA), Brazil, and Australia using Cloud-Aerosol Lidar with Orthogonal Polarisation (CALIOP) and a TROPOspheric Monitoring Instrument (TROPOMI). Specifically, we analyzed the spatial-temporal distribution of black carbon (BC) and carbon monoxide (CO) and the vertical distribution of smoke. Based on the results, the highest detection of smoke (~14 km) was observed in Brazil; meanwhile, Australia showed the largest BC column burden of ~1.5 mg/m2. The meteorological conditions were similar for all sites during the fires. Moderate temperatures (between 32 and 42 °C) and relative humidity (30–50%) were observed, which resulted in drier conditions favorable for the burning of fires. However, the number of active fires was different for each site, with Brazil having 13 times more active fires than the USA and five times more than the number of active fires in Australia. However, the high number of active fires did not translate to higher atmospheric constituent emissions. Overall, this work provides a better understanding of wildfire behavior and the role of meteorological conditions in emissions at various sites.
Modeling the Radial Stem Growth of the Pine (Pinus sylvestris L.) Forests Using the Satellite-Derived NDVI and LST (MODIS/AQUA) Data
Authors: Ivanova Yulia , Kovalev Anton , Soukhovolsky Vlad
Published: December 2020

The paper considers a new approach to modeling the relationship between the increase in woody phytomass in the pine forest and satellite-derived Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) (MODIS/AQUA) data. The developed model combines the phenological and forest growth processes. For the analysis, NDVI and LST (MODIS) satellite data were used together with the measurements of tree-ring widths (TRW). NDVI data contain features of each growing season. The models include parameters of parabolic approximation of NDVI and LST time series transformed using principal component analysis. The study shows that the current rate of TRW is determined by the total values of principal components of the satellite indices over the season and the rate of tree increment in the preceding year.
Observing System Simulation Experiment to Reproduce Kelvin Wave in the Venus Atmosphere
Authors: Sugimoto Norihiko , Fujisawa Yukiko , Shirasaka Mimo , Hosono Asako , Abe Mirai , Ando Hiroki , Takagi Masahiro , Yamamoto Masaru
Published: December 2020

Planetary-scale 4-day Kelvin-type waves at the cloud top of the Venus atmosphere have been reported from the 1980s, and their significance for atmospheric dynamics has been pointed out. However, these waves have not been reproduced in Venus atmospheric general circulation models (VGCMs). Recently, horizontal winds associated with the planetary-scale waves at the cloud top have been obtained from cloud images taken by cameras onboard Venus orbiters, which could enable us to clarify the structure and roles of Kelvin-type waves. In order to examine this possibility, our team carried out an idealized observing system simulation experiment (OSSE) with a data assimilation system which we developed. The wind velocity data provided by a CCSR/NIES (Center for Climate System Research/National Institute for Environmental Studies) VGCM where equatorial Kelvin-type waves were assumed below the cloud bottom was used as idealized observations. Results show that 4-day planetary-scale Kelvin-type waves are successfully reproduced if the wind velocity between 15° S and 15° N latitudes is assimilated every 6 h at 70 km altitude. It is strongly suggested that the Kelvin-type waves could be reproduced and investigated by the data assimilation with the horizontal wind data derived from Akatsuki ultraviolet images. The present results also contribute to planning future missions for understanding planetary atmospheres.
Quercetin as a Natural Therapeutic Candidate for the Treatment of Influenza Virus
Authors: Mehrbod Parvaneh , Hudy Dorota , Shyntum Divine , Markowski Jarosław , Łos Marek J. , Ghavami Saeid
Published: December 2020

The medical burden caused by respiratory manifestations of influenza virus (IV) outbreak as an infectious respiratory disease is so great that governments in both developed and developing countries have allocated significant national budget toward the development of strategies for prevention, control, and treatment of this infection, which is seemingly common and treatable, but can be deadly. Frequent mutations in its genome structure often result in resistance to standard medications. Thus, new generations of treatments are critical to combat this ever-evolving infection. Plant materials and active compounds have been tested for many years, including, more recently, active compounds like flavonoids. Quercetin is a compound belonging to the flavonols class and has shown therapeutic effects against influenza virus. The focus of this review includes viral pathogenesis as well as the application of quercetin and its derivatives as a complementary therapy in controlling influenza and its related symptoms based on the targets. We also touch on the potential of this class of compounds for treatment of SARS-COV-2, the cause of new pandemic.
Electrochemical Determination of Hydroxyurea in a Complex Biological Matrix Using MoS2-Modified Electrodes and Chemometrics
Authors: Cazelles Remi , Shukla Rajendra P. , Ware Russell E. , Vinks Alexander A. , Ben-Yoav Hadar
Published: December 2020

Hydroxyurea, an oral medication with important clinical benefits in the treatment of sickle cell anemia, can be accurately determined in plasma with a transition metal dichalcogenide-based electrochemical sensor. We used a two-dimensional molybdenum sulfide material (MoS2) selectively electrodeposited on a polycrystalline gold electrode via tailored waveform polarization in the gold electrical double layer formation region. The electro-activity of the modified electrode depends on the electrical waveform parameters used to electro-deposit MoS2. The concomitant oxidation of the MoS2 material during its electrodeposition allows for the tuning of the sensor’s specificity. Chemometrics, utilizing mathematical procedures such as principal component analysis and multivariable partial least square regression, were used to process the electrochemical data generated at the bare and the modified electrodes, thus allowing the hydroxyurea concentrations to be predicted in human plasma. A limit-of-detection of 22 nM and a sensitivity of 37 nA cm−2 µM−1 were found to be suitable for pharmaceutical and clinical applications.
Characterization of Early-Stage Alcoholic Liver Disease with Hyperhomocysteinemia and Gut Dysfunction and Associated Immune Response in Alcohol Use Disorder Patients
Authors: Vatsalya Vatsalya , Gala Khushboo S. , Hassan Ammar Z. , Frimodig Jane , Kong Maiying , Sinha Nachiketa , Schwandt Melanie L.
Published: December 2020

Heavy alcohol consumption can cause hyperhomocysteinemia, which could be consequential in the proinflammatory response and worsening of the neurobehavioral domains of alcohol use disorder (AUD), such as alcohol withdrawal. We examined the role of heavy drinking, hyperhomocysteinemia, gut dysfunction and inflammation in early-stage alcoholic liver disease (ALD) in AUD patients. A total of 110 AUD patients without clinical manifestations of liver injury were grouped by the serum homocysteine levels (SHL): normal ≤ 13 µmol/L (Group 1 (Gr.1); n = 80), and elevated > 13 µmol/L (Group 2 (Gr.2), n = 30). A comprehensive metabolic panel, SHL, a nutritional assessment, and drinking history assessed by the timeline followback questionnaire were evaluated. A subset analysis was performed on 47 subjects (Gr.1 n = 27; Gr.2 n = 20) for additional measures: Clinical Institute Withdrawal Assessment for Alcohol (CIWA) score, plasma cytokines (interleukin-1β (IL-1β)), gut dysfunction markers (lipopolysaccharide (LPS), and LPS-binding protein (LBP)); 27% of the AUD patients exhibited hyperhomocysteinemia. SHL was significantly associated (p = 0.034) with heavy drinking days (HDD90). Subset analyses showed that the withdrawal ratings were both clinically and statistically (p = 0.033) elevated and significantly associated with hyperhomocysteinemia (p = 0.016) in Gr.2. LBP, IL1-β, SHL, and HDD90 showed significant cumulative effects (adjusted R2 = 0.627) on withdrawal ratings in Gr.2 subset. Alanine aminotransferase (ALT) and aspartate aminotransferase (AST) were significantly higher in all Gr.2 patients; AUROC showed a fair level of true positivity for ALT (0.676), and AST (0.686). Il1-β, LBP, SHL, and HDD90 showed significant cumulative effects (adjusted R2 = 0.554) on the elevated ALT in Gr.2 subset as well. The gut-brain derived proinflammatory response, patterns of heavy drinking, and hyperhomocysteinemia were closely associated with clinically elevated alcohol withdrawal and elevated liver injury. Hyperhomocysteinemia could have a potential phenotypic marker response indicative of early-stage ALD along with AUD.
Pretreatment Effect of Inflammatory Stimuli and Characteristics of Tryptophan Transport on Brain Capillary Endothelial (TR-BBB) and Motor Neuron Like (NSC-34) Cell Lines
Authors: Gyawali Asmita , Kang Young-Sook
Published: December 2020

Tryptophan plays a key role in several neurological and psychiatric disorders. In this study, we investigated the transport mechanisms of tryptophan in brain capillary endothelial (TR-BBB) cell lines and motor neuron-like (NSC-34) cell lines. The uptake of [3H]l-tryptophan was stereospecific, and concentration- and sodium-dependent in TR-BBB cell lines. Transporter inhibitors and several neuroprotective drugs inhibited [3H]l-tryptophan uptake by TR-BBB cell lines. Gabapentin and baclofen exerted a competitive inhibitory effect on [3H]l-tryptophan uptake. Additionally, l-tryptophan uptake was time- and concentration-dependent in both NSC-34 wild type (WT) and mutant type (MT) cell lines, with a lower transporter affinity and higher capacity in MT than in WT cell lines. Gene knockdown of LAT1 (l-type amino acid transporter 1) and CAT1 (cationic amino acid transporter 1) demonstrated that LAT1 is primarily involved in the transport of [3H]l-tryptophan in both TR-BBB and NSC-34 cell lines. In addition, tryptophan uptake was increased by TR-BBB cell lines but decreased by NSC-34 cell lines after pro-inflammatory cytokine pre-treatment. However, treatment with neuroprotective drugs ameliorated tryptophan uptake by NSC-34 cell lines after inflammatory cytokines pretreatment. The tryptophan transport system may provide a therapeutic target for treating or preventing neurodegenerative diseases.
Evaluation of Nanoparticle Penetration in the Tumor Spheroid Using Two-Photon Microscopy
Authors: Pratiwi Feby Wijaya , Peng Chien-Chung , Wu Si-Han , Kuo Chiung Wen , Mou Chung-Yuan , Tung Yi-Chung , Chen Peilin
Published: December 2020

Mesoporous silica nanoparticles (MSNs) have emerged as a prominent nanomedicine platform, especially for tumor-related nanocarrier systems. However, there is increasing concern about the ability of nanoparticles (NPs) to penetrate solid tumors, resulting in compromised antitumor efficacy. Because the physicochemical properties of NPs play a significant role in their penetration and accumulation in solid tumors, it is essential to systematically study their relationship in a model system. Here, we report a multihierarchical assessment of the accumulation and penetration of fluorescence-labeled MSNs with nine different physicochemical properties in tumor spheroids using two-photon microscopy. Our results indicated that individual physicochemical parameters separately could not define the MSNs’ ability to accumulate in a deeper tumor region; their features are entangled. We observed that the MSNs’ stability determined their success in reaching the hypoxia region. Moreover, the change in the MSNs’ penetration behavior postprotein crowning was associated with both the original properties of NPs and proteins on their surfaces.
Pharmacotherapy in COVID 19: Potential Impact of Targeting the Complement System
Authors: Barkoff Courtney M. , Mousa Shaker A.
Published: December 2020

Coronavirus disease 2019 (COVID-19), a respiratory illness caused by infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has claimed over one million lives worldwide since December 2019. The complement system, while a first-line immune defense against invading pathogens, has off-target effects that lead to increases in inflammation, tissue damage, and thrombosis; these are common, life-threatening complications seen in patients with COVID-19. This review explores the potential impact of complement activation in COVID-19 and possible treatments targeting the complement system.
Demonstration of a Label-Free and Low-Cost Optical Cavity-Based Biosensor Using Streptavidin and C-Reactive Protein
Authors: Rho Donggee , Kim Seunghyun
Published: December 2020

An optical cavity-based biosensor (OCB) has been developed for point-of-care (POC) applications. This label-free biosensor employs low-cost components and simple fabrication processes to lower the overall cost while achieving high sensitivity using a differential detection method. To experimentally demonstrate its limit of detection (LOD), we conducted biosensing experiments with streptavidin and C-reactive protein (CRP). The optical cavity structure was optimized further for better sensitivity and easier fluid control. We utilized the polymer swelling property to fine-tune the optical cavity width, which significantly improved the success rate to produce measurable samples. Four different concentrations of streptavidin were tested in triplicate, and the LOD of the OCB was determined to be 1.35 nM. The OCB also successfully detected three different concentrations of human CRP using biotinylated CRP antibody. The LOD for CRP detection was 377 pM. All measurements were done using a small sample volume of 15 µL within 30 min. By reducing the sensing area, improving the functionalization and passivation processes, and increasing the sample volume, the LOD of the OCB are estimated to be reduced further to the femto-molar range. Overall, the demonstrated capability of the OCB in the present work shows great potential to be used as a promising POC biosensor.
Randomized Controlled Immunotherapy Clinical Trials for GBM Challenged
Authors: Van Gool Stefaan W. , Makalowski Jennifer , Fiore Simon , Sprenger Tobias , Prix Lothar , Schirrmacher Volker , Stuecker Wilfried
Published: December 2020

Immunotherapies represent a promising strategy for glioblastoma multiforme (GBM) treatment. Different immunotherapies include the use of checkpoint inhibitors, adoptive cell therapies such as chimeric antigen receptor (CAR) T cells, and vaccines such as dendritic cell vaccines. Antibodies have also been used as toxin or radioactive particle delivery vehicles to eliminate target cells in the treatment of GBM. Oncolytic viral therapy and other immunogenic cell death-inducing treatments bridge the antitumor strategy with immunization and installation of immune control over the disease. These strategies should be included in the standard treatment protocol for GBM. Some immunotherapies are individualized in terms of the medicinal product, the immune target, and the immune tumor–host contact. Current individualized immunotherapy strategies focus on combinations of approaches. Standardization appears to be impossible in the face of complex controlled trial designs. To define appropriate control groups, stratification according to the Recursive Partitioning Analysis classification, MGMT promotor methylation, epigenetic GBM sub-typing, tumor microenvironment, systemic immune functioning before and after radiochemotherapy, and the need for/type of symptom-relieving drugs is required. Moreover, maintenance of a fixed treatment protocol for a dynamic, deadly cancer disease in a permanently changing tumor–host immune context might be inappropriate. This complexity is illustrated using our own data on individualized multimodal immunotherapies for GBM. Individualized medicines, including multimodal immunotherapies, are a rational and optimal yet also flexible approach to induce long-term tumor control. However, innovative methods are needed to assess the efficacy of complex individualized treatments and implement them more quickly into the general health system.
Head and Neck Cancer Treatment during COVID-19 Pandemic: A Central Experience in Rome. Emergency Management, Infection Prevention and Control
Authors: Cassoni Andrea , Pucci Resi , Mangini Nicolò , Fadda Maria Teresa , Battisti Andrea , Giovannetti Filippo , Terenzi Valentina , Della Monaca Marco , Priore Paolo , Raponi Ingrid , Valentini Valentino
Published: December 2020

The COVID-19 pandemic has significantly affected the surgical units, especially those operating on the airways. This study evaluates the series of patients with tumors of the head and neck treated by our unit during Phase-1 of the pandemic and the efficacy of the preventive measures implemented for protecting both the patients and staff. A screening program was administered to all the patients who had to undergo surgery. None of the patients tested and operated during Phase 1, between 10 March and 18 May 2020, were positive for COVID-19. A significant portion of the patients was suffering from tumors in advanced stages (T3 and T4). Two patients developed respiratory symptoms during their stay at the unit, so they were put in precautionary isolation and tested, but resulted negative for COVID-19. All the surgical department staff followed the Italian Ministry of Health’s prevention protocol and underwent serological testing. IgG and IgM were negative in everyone, thus confirming that nobody had been exposed to the virus. This study highlights the commitment to efficiently treating patients suffering from tumors of the head and neck region and confirms the effectiveness of the safety measures used to protect our patients and staff’s health.
Metabolic Reprogramming of Fibroblasts as Therapeutic Target in Rheumatoid Arthritis and Cancer: Deciphering Key Mechanisms Using Computational Systems Biology Approaches
Authors: Aghakhani Sahar , Zerrouk Naouel , Niarakis Anna
Published: December 2020

Fibroblasts, the most abundant cells in the connective tissue, are key modulators of the extracellular matrix (ECM) composition. These spindle-shaped cells are capable of synthesizing various extracellular matrix proteins and collagen. They also provide the structural framework (stroma) for tissues and play a pivotal role in the wound healing process. While they are maintainers of the ECM turnover and regulate several physiological processes, they can also undergo transformations responding to certain stimuli and display aggressive phenotypes that contribute to disease pathophysiology. In this review, we focus on the metabolic pathways of glucose and highlight metabolic reprogramming as a critical event that contributes to the transition of fibroblasts from quiescent to activated and aggressive cells. We also cover the emerging evidence that allows us to draw parallels between fibroblasts in autoimmune disorders and more specifically in rheumatoid arthritis and cancer. We link the metabolic changes of fibroblasts to the toxic environment created by the disease condition and discuss how targeting of metabolic reprogramming could be employed in the treatment of such diseases. Lastly, we discuss Systems Biology approaches, and more specifically, computational modeling, as a means to elucidate pathogenetic mechanisms and accelerate the identification of novel therapeutic targets.
Optimal Preoperative Multidisciplinary Treatment in Borderline Resectable Pancreatic Cancer
Authors: Kimura Nana , Yamada Suguru , Takami Hideki , Murotani Kenta , Yoshioka Isaku , Shibuya Kazuto , Sonohara Fuminori , Hoshino Yui , Hirano Katsuhisa , Watanabe Toru , Baba Hayato , Mori Kosuke , Miwa Takeshi , Kanda Mitsuro , Hayashi Masamichi , Matsui Koshi , Okumura Tomoyuki , Kodera Yasuhiro , Fujii Tsutomu
Published: December 2020

Background: The objective of this study was to investigate the optimal neoadjuvant therapy (NAT) for borderline resectable pancreatic cancer invading the portal vein (BR-PV) or abutting major arteries (BR-A). Methods: We retrospectively analyzed 88 patients with BR-PV and 111 patients with BR-A. Results: In BR-PV patients who underwent upfront surgery (n = 46)/NAT (n = 42), survival was significantly better in the NAT group (3-year overall survival (OS): 5.8%/35.5%, p = 0.004). In BR-A patients who underwent upfront surgery (n = 48)/NAT (n = 63), survival was also significantly better in the NAT group (3-year OS:15.5%/41.7%, p < 0.001). The prognosis tended to be better in patients who received newer chemotherapeutic regimens, such as FOLFIRINOX and gemcitabine with nab-paclitaxel. In 36 BR-PV patients who underwent surgery after NAT, univariate analysis revealed that normalization of tumor marker (TM) levels (p = 0.028) and preoperative high prognostic nutritional index (PNI) (p = 0.022) were significantly associated with a favorable prognosis. In 39 BR-A patients who underwent surgery after NAT, multivariate analysis revealed that preoperative PNI > 42.5 was an independent prognostic factor (HR: 0.15, p = 0.014). Conclusions: NAT using newer chemotherapy is essential for improving the prognosis of BR pancreatic cancer. These findings suggest that prognosis may be prolonged by maintaining good nutritional status during preoperative treatment.
Update on Prostate Cancer Diagnosis, Prognosis, and Prediction to Response to Therapy
Authors: Montironi Rodolfo , Cimadamore Alessia , Lopez-Beltran Antonio , Cheng Liang , Scarpelli Marina
Published: December 2020

The wide range of novelties reported in this Special Issue of the journal Cells on prostate cancer (PCa) diagnosis, prognosis, and prediction to response to therapy, has led us to a series of considerations related to a better understanding of the current and future role of effective molecular biomarkers in individual patients with PCa [...]
Potentiometric Carboxylate Sensors Based on Carbazole-Derived Acyclic and Macrocyclic Ionophores
Authors: Yrjänä Ville , Saar Indrek , Ilisson Mihkel , Kadam Sandip A. , Leito Ivo , Bobacka Johan
Published: December 2020

Solid-contact ion-selective electrodes with carbazole-derived ionophores were prepared. They were characterized as acetate sensors, but can be used to determine a number of carboxylates. The potentiometric response characteristics (slope, detection limit, selectivity, and pH sensitivity) of sensors prepared with different membrane compositions (ionophore, ionophore concentration, anion exchanger concentration, and plasticizer) were evaluated. The results show that for the macrocyclic ionophores, a larger cavity provided better selectivity. The sensors exhibited modest selectivity for acetate but good selectivity for benzoate. The carbazole-derived ionophores effectively decreased the interference from lipophilic anions, such as bromide, nitrate, iodide, and thiocyanate. The selectivity, detection limit, and linear range were improved by choosing a suitable plasticizer and by reducing the ionophore and anion exchanger concentrations. The influence of the electrode body’s material upon the composition of the plasticized poly(vinyl chloride) membrane, and thus also upon the sensor characteristics, was also studied. The choice of materials for the electrode body significantly affected the characteristics of the sensors.
Tunable Microstructure and Morphology of the Self-Assembly Hydroxyapatite Coatings on ZK60 Magnesium Alloy Substrates Using Hydrothermal Methods
Authors: Wang Taolei , Lin Chao , Batalu Dan , Hu Jingzhou , Lu Wei
Published: December 2020

Hydroxyapatite coatings have been widely used to improve the corrosion resistance of biodegradable magnesium alloys. In this paper, in order to manufacture the ideal hydroxyapatite (HA) coating on the ZK60 magnesium substrate by hydrothermal method, formation mechanism of enhanced hydroxyapatite (HA) coatings, influence of pH values of the precursor solution on the HA morphology, corrosion resistance and cytotoxicity of HA coatings have been investigated. Results show that the growth pattern of the HA is influenced by the local pH value. HA has a preferential c-axis and higher crystallinity in the alkaline environment developing a nanorod-like structure, while in acid and neutral environments it has a preferential growth along the a(b)-plane with a lower crystallinity, developing a nanosheet-like structure. The different morphology and microstructure lead to different degradation behavior and performance of HA coatings. Immersion and electrochemical tests show that the neutral environment promote formation of HA coatings with high corrosion resistance. The cell culture experiments confirm that the enhanced corrosion resistance assure the biocompatibility of the substrate-coating system. In general, the HA coating prepared in neutral environment shows great potential in surface modification of magnesium alloys.
Improvement of the Tribological Properties and Corrosion Resistance of Epoxy–PTFE Composite Coating by Nanoparticle Modification
Authors: Ying Lixia , Wu Yunlong , Nie Chongyang , Wu Chunxi , Wang Guixiang
Published: December 2020

In order to meet the requirements of high corrosion resistance, wear resistance, and self-lubrication of composite coatings for marine applications, epoxy matrix composite coatings containing PTFE and TiO2 nanoparticles were prepared on the steel substrate. With silane coupling agent KH570 (CH2=C(CH3)COOC3H6Si(OCH3)3), titanium dioxide nanoparticles were modified, and organic functional groups were grafted on their surface to improve their dispersion and interface compatibility in the epoxy matrix. Then, the section morphology, tribological, and anticorrosion properties of prepared coatings, including pure epoxy, epoxy–PTFE, and the composite coating with unmodified and modified TiO2, respectively, were fully characterized by scanning electron microscopy, friction–abrasion testing machine, and an electrochemical workstation. The analytical results show that the modified TiO2 nanoparticles are able to improve the epoxy–PTFE composite coating’s mechanical properties of epoxy–PTFE composite coating including section toughness, hardness, and binding force. With the synergistic action of the friction reduction of PTFE and dispersion enhancement of TiO2 nanoparticles, the dry friction coefficient decreases by more than 73%. Simultaneously, modified titanium dioxide will not have much influence on the water contact angles of the coating. A larger water contact angle and uniform and compact microstructure make the composite coating incorporated modified TiO2 nanoparticles show excellent anti-corrosion ability, which has the minimum corrosion current density of 1.688 × 10−7 A·cm−2.
NADAL: A Neighbor-Aware Deep Learning Approach for Inferring Interpersonal Trust Using Smartphone Data
Authors: Bati Ghassan F. , Singh Vivek K.
Published: December 2020

Interpersonal trust mediates multiple socio-technical systems and has implications for personal and societal well-being. Consequently, it is crucial to devise novel machine learning methods to infer interpersonal trust automatically using mobile sensor-based behavioral data. Considering that social relationships are often affected by neighboring relationships within the same network, this work proposes using a novel neighbor-aware deep learning architecture (NADAL) to enhance the inference of interpersonal trust scores. Based on analysis of call, SMS, and Bluetooth interaction data from a one-year field study involving 130 participants, we report that: (1) adding information about neighboring relationships improves trust score prediction in both shallow and deep learning approaches; and (2) a custom-designed neighbor-aware deep learning architecture outperforms a baseline feature concatenation based deep learning approach. The results obtained at interpersonal trust prediction are promising and have multiple implications for trust-aware applications in the emerging social internet of things.
Aortic Root Dilatation in Taiwanese Patients with Mucopolysaccharidoses and the Long-Term Effects of Enzyme Replacement Therapy
Authors: Lin Hsiang-Yu , Chen Ming-Ren , Lee Chung-Lin , Lin Shan-Miao , Hung Chung-Lieh , Niu Dau-Ming , Chang Tung-Ming , Chuang Chih-Kuang , Lin Shuan-Pei
Published: December 2020

Background: Cardiovascular abnormalities have been observed in patients with mucopolysaccharidosis (MPS) of any type, with the most documented abnormalities being valvular regurgitation and stenosis and cardiac hypertrophy. Only a few studies have focused on aortic root dilatation and the long-term effects of enzyme replacement therapy (ERT) in these patients. Methods: We reviewed echocardiograms of 125 Taiwanese MPS patients (age range, 0.1 to 19.1 years; 11 with MPS I, 49 with MPS II, 25 with MPS III, 29 with MPS IVA, and 11 with MPS VI). The aortic root diameter was measured at the sinus of Valsalva. Results: Aortic root dilatation (z score >2) was observed in 47% of the MPS patients, including 66% of MPS IV, 51% of MPS II, 45% of MPS VI, 28% of MPS III, and 27% of MPS I patients. The mean aortic root diameter z score was 2.14 (n = 125). The patients with MPS IV had the most severe aortic root dilatation with a mean aortic root diameter z score of 3.03, followed by MPS II (2.12), MPS VI (2.06), MPS III (1.68), and MPS I (1.03). The aortic root diameter z score was positively correlated with increasing age (n = 125, p < 0.01). For the patients with MPS II, III, and IV, aortic root diameter z score was also positively correlated with increasing age (p < 0.01). For 16 patients who had received ERT and had follow-up echocardiographic data (range 2.0–16.2 years), the mean aortic root diameter z score change was −0.46 compared to baseline (baseline 2.49 versus follow-up 2.03, p = 0.490). Conclusions: Aortic root dilatation was common in the patients with all types of MPS, with the most severe aortic root dilatation observed in those with MPS IV. The severity of aortic root dilatation worsened with increasing age, reinforcing the concept of the progressive nature of this disease. ERT for MPS appears to stabilize the progression of aortic root dilatation.
Serum Biomarkers for the Diagnosis of Glaucoma
Authors: Shin Young Joo , Kim Eunbi , Han Bobby Kwanghoon , Yi Kayoung
Published: December 2020

Despite the importance of the early detection of glaucoma, most patients with progressive glaucoma show minimal symptoms. We aimed to evaluate biomarkers for glaucoma diagnosis in Korea. Forty-two volunteers with/without open-angle glaucoma were enrolled from January through October 2015—divided into a control or open-angle glaucoma group, which was further divided into normal-tension glaucoma (NTG) and high-tension glaucoma (HTG) groups—and underwent assessments for myelin basic protein (MBP), heat shock protein 60, anti-Sjögren’s-syndrome-related antigen A (SSA) and antigen B (SSB), anti-α-fodrin, and anti-nucleic acid. The glaucoma group showed a higher serum MBP level and lower serum anti-α-fodrin antibody level than the control group (p < 0.05). The NTG group showed higher serum anti-SSA and anti-SSB levels and lower anti-α-fodrin IgG/IgA levels than the HTG group. In the receiver operating characteristic curve analysis, the area under the curve (AUC) for serum MBP level was 0.917 in discriminating between controls and patients with glaucoma. Between the NTG and HTG groups, anti-SSA, anti-SSB, and anti-α-fodrin IgG/IgA levels showed an AUC above 0.8. Thus, these biomarkers were useful for diagnosing glaucoma and discriminating between controls and patients with glaucoma, and patients with NTG and HTG.
The Molecular Theory of Liquid Nanodroplets Energetics in Aerosols
Authors: Kaim Sergii D.
Published: December 2020

Studies of the coronavirus SARS-CoV-2 spread mechanisms indicate that the main mechanism is associated with the spread in the atmosphere of micro- and nanodroplets of liquid with an active agent. However, the molecular theory of aerosols of microdroplets in gases remains poorly developed. In this work, the energy properties of aerosol nanodroplets of simple liquids suspended in a gas were studied within the framework of molecular theory. The three components of the effective aerosol Hamiltonian were investigated: (1) the interaction energy of an individual atom with a liquid nanodroplet; (2) the surface energy of liquid nanodroplet; and (3) the interaction energy of two liquid nanodroplets. The size dependence of all contributions was investigated. The pairwise interparticle interactions and pairwise interparticle correlations were accounted for to study the nanodroplet properties using the Fowler approximation. In this paper, the problem of the adhesion energy calculation of a molecular complex and a liquid nanodroplet is discussed. The derived effective Hamiltonian is generic and can be used for the cases of multicomponent nano-aerosols and to account for particle size distributions.
Cloud-Based ICME Software Training
Authors: Koschmieder Lukas , Altenfeld Ralph , Eiken Janin , Böttger Bernd , Schmitz Georg J.
Published: December 2020

Hands-on type training of Integrated Computational Materials Engineering (ICME) is characterized by assisted application and combination of multiple simulation software tools and data. In this paper, we present recent experiences in establishing a cloud-based infrastructure to enable remote use of dedicated commercial and open access simulation tools during an interactive online training event. In the first part, we summarize the hardware and software requirements and illustrate how these have been met using cloud hardware services, a simulation platform environment, a suitable communication channel, common workspaces, and more. The second part of the article focuses (i) on the requirements for suitable online hands-on training material and (ii) on details of some of the approaches taken. Eventually, the practical experiences gained during three consecutive online training courses held in September 2020 with 35 nominal participants each, are discussed in detail.
MaxAFL: Maximizing Code Coverage with a Gradient-Based Optimization Technique
Authors: Kim Youngjoon , Yoon Jiwon
Published: December 2020

Evolutionary fuzzers generally work well with typical software programs because of their simple algorithm. However, there is a limitation that some paths with complex constraints cannot be tested even after long execution. Fuzzers based on concolic execution have emerged to address this issue. The concolic execution fuzzers also have limitations in scalability. Recently, the gradient-based fuzzers that use a gradient to mutate inputs have been introduced. Gradient-based fuzzers can be applied to real-world programs and achieve high code coverage. However, there is a problem that the existing gradient-based fuzzers require heavyweight analysis or sufficient learning time. In this paper, we propose a new type of gradient-based fuzzer, MaxAFL, to overcome the limitations of existing gradient-based fuzzers. Our approach constructs an objective function through fine-grained static analysis. After constructing a well-made objective function, we can apply the gradient-based optimization algorithm. We use a modified gradient-descent algorithm to minimize our objective function and propose some probabilistic techniques to escape local optimum. We introduce an adaptive objective function which aims to explore various paths in the program. We implemented MaxAFL based on the original AFL. MaxAFL achieved increase of code coverage per time compared with three other fuzzers in six open-source Linux binaries. We also measured cumulative code coverage per total execution, and MaxAFL outperformed the other fuzzers in this metric. Finally, MaxAFL can also find more bugs than the other fuzzers.
A Novel YOLOv3 Algorithm-Based Deep Learning Approach for Waste Segregation: Towards Smart Waste Management
Authors: Kumar Saurav , Yadav Drishti , Gupta Himanshu , Verma Om Prakash , Ansari Irshad Ahmad , Ahn Chang Wook
Published: December 2020

The colossal increase in environmental pollution and degradation, resulting in ecological imbalance, is an eye-catching concern in the contemporary era. Moreover, the proliferation in the development of smart cities across the globe necessitates the emergence of a robust smart waste management system for proper waste segregation based on its biodegradability. The present work investigates a novel approach for waste segregation for its effective recycling and disposal by utilizing a deep learning strategy. The YOLOv3 algorithm has been utilized in the Darknet neural network framework to train a self-made dataset. The network has been trained for 6 object classes (namely: cardboard, glass, metal, paper, plastic and organic waste). Moreover, for comparative assessment, the detection task has also been performed using YOLOv3-tiny to validate the competence of the YOLOv3 algorithm. The experimental results demonstrate that the proposed YOLOv3 methodology yields satisfactory generalization capability for all the classes with a variety of waste items.
Magniber v2 Ransomware Decryption: Exploiting the Vulnerability of a Self-Developed Pseudo Random Number Generator
Authors: Lee Sehoon , Park Myungseo , Kim Jongsung
Published: December 2020

With the rapid increase in computer storage capabilities, user data has become increasingly important. Although user data can be maintained by various protection techniques, its safety has been threatened by the advent of ransomware, defined as malware that encrypts user data, such as documents, photographs and videos, and demands money to victims in exchange for data recovery. Ransomware-infected files can be recovered only by obtaining the encryption key used to encrypt the files. However, the encryption key is derived using a Pseudo Random Number Generator (PRNG) and is recoverable only by the attacker. For this reason, the encryption keys of malware are known to be difficult to obtain. In this paper, we analyzed Magniber v2, which has exerted a large impact in the Asian region. We revealed the operation process of Magniber v2 including PRNG and file encryption algorithms. In our analysis, we found a vulnerability in the PRNG of Magniber v2 developed by the attacker. We exploited this vulnerability to successfully recover the encryption keys, which was by verified the result in padding verification and statistical randomness tests. To our knowledge, we report the first recovery result of Magniber v2-infected files.